diff --git a/data/covid/preprints-summary.csv b/data/covid/preprints-summary.csv index 240eb124..249c16cc 100644 --- a/data/covid/preprints-summary.csv +++ b/data/covid/preprints-summary.csv @@ -1,50 +1,50 @@ -geriatric medicine,health informatics,psychiatry and clinical psychology,pharmacology and therapeutics,radiology and imaging,orthopedics,intensive care and critical care medicine,evolutionary biology,surgery,hiv aids,health economics,Total,immunology,biochemistry,obstetrics and gynecology,cardiovascular medicine,epidemiology,pediatrics,primary care research,respiratory medicine,infectious diseases,neurology,oncology,scientific communication and education,bioinformatics,ophthalmology,genomics,allergy and immunology,biophysics,public and global health,systems biology,health systems and quality improvement,genetic and genomic medicine,pathology,microbiology,molecular biology,emergency medicine,dentistry and oral medicine,occupational and environmental health,health policy,dermatology,month -,,,,,,,,,,,4,,,,,1,,,,1,,,,,,,,,2,,,,,,,,,,,,Feb-24 -,,,,,,,,,,,3,,,,,,,,,,,,,,,,,,2,,,,,,,,,1,,,Jan-24 -,,,,,,,,,,2,10,,,,1,4,,,,,1,,,,,,,,1,,,,,,,,,1,,,Dec-23 -,,,,,,,,,,,4,,,,,2,,,,1,,1,,,,,,,,,,,,,,,,,,,Nov-23 -,1,,,,,,,,,,5,1,,,,1,,,1,1,,,,,,,,,,,,,,,,,,,,,Oct-23 -,,,,,,,,,,,1,,,,,,,,,1,,,,,,,,,,,,,,,,,,,,,Sep-23 -,,,,,,,,,,,7,,,,,4,,1,,,,,,,,,,,1,,,,,,,,,1,,,Aug-23 -,,,,,,,,,,,7,,,,,3,,,,,,,,,,,,,1,,2,1,,,,,,,,,Jul-23 -,1,,,,1,,,,,,6,,,,,1,,,,2,,,1,,,,,,,,,,,,,,,,,,Jun-23 -,,,,,,,,,,,6,1,,,,2,,,1,1,,,,,,,,,1,,,,,,,,,,,,May-23 -,,,,,,,,,,,3,,,,,,,,,1,,,,,,,,,2,,,,,,,,,,,,Apr-23 -,,1,,,,,,,,,9,,,,,2,,,,3,,,,,,,,,2,,,,,,,,,1,,,Mar-23 -,,,,,,,,,,,7,,,,,4,,,,,1,,,,,,,,2,,,,,,,,,,,,Feb-23 -,,,,,,,,,,,6,,,,,5,,,,1,,,,,,,,,,,,,,,,,,,,,Jan-23 -,,,,,,,,,,,12,,,,,3,,,2,4,,,,,,,,,1,,,,1,,,,,,1,,Dec-22 -,,,,,,,,,,,4,,,,,,,,,4,,,,,,,,,,,,,,,,,,,,,Nov-22 -,,,,,,,,,,,6,,,,1,1,,,,2,,,,,,,,,2,,,,,,,,,,,,Oct-22 -,,,,,,,,,,,9,,,,,1,1,,1,2,,,,,,,,,1,,,,,1,,,,2,,,Sep-22 -,,,,,,,,,,,10,,,,,4,,,,3,,,,,,,,,3,,,,,,,,,,,,Aug-22 -,1,,,,,,,,,,7,,,,,2,1,,,3,,,,,,,,,,,,,,,,,,,,,Jul-22 -,1,5,,,,,,,,,17,,,,,6,,,,3,,,,,,,,,1,,,1,,,,,,,,,Jun-22 -,,2,,,,,,,,1,14,,,,,2,,1,,5,,,,,,,,,1,,1,,,1,,,,,,,May-22 -,,,,,,,,,,1,16,,,,1,5,,,1,3,,,,,,,,,1,,2,,,1,,,,1,,,Apr-22 -,,1,,,,,1,,,,18,,,,,9,,1,1,5,,,,,,,,,,,,,,,,,,,,,Mar-22 -,,,,,,,,,,,11,,,,,5,,,,4,1,,,,,,,,1,,,,,,,,,,,,Feb-22 -,1,,,,,,,,,,13,1,,,1,5,,,,3,,,,,,,,,1,,,,,,,,,1,,,Jan-22 -,,,,,,,,,,,23,,,,1,10,1,1,,7,1,,,,,,,,1,,,,,1,,,,,,,Dec-21 -,,1,,,,1,,,,,24,,,,,8,,1,,5,1,,,,,1,,1,3,,2,,,,,,,,,,Nov-21 -1,,2,,,,,,,,,11,,,,,4,1,,,3,,,,,,,,,,,,,,,,,,,,,Oct-21 -,1,,1,,,1,,,,,16,,,,1,5,,,,5,,,,,,,,,2,,,,,,,,,,,,Sep-21 -,1,,,,,1,,,,,12,,,,1,2,,,,3,,,,,,,,,3,,,,,,,,,1,,,Aug-21 -,,,,,,1,,,,,26,,,,,3,1,,2,12,,1,,,,,,,4,,,1,,,,1,,,,,Jul-21 -,1,1,,,,1,,,,,27,1,,,,6,1,1,,7,1,,,,,,1,,4,,1,,,,,,,1,,,Jun-21 -,1,1,,,,,,,,,22,,,,,9,,,,8,,,,,,,,,1,,,1,,,,,,,,1,May-21 -,1,1,,,,,,,,,20,,,,,4,,1,,7,,,,,,,1,,1,,1,,,1,,,,2,,,Apr-21 -2,2,1,,1,,,,1,,,38,,1,,,5,1,,,17,1,,,,,,,,5,,,1,,,,,,,,,Mar-21 -,1,,,,,,,1,,1,22,,,,1,9,,,,7,,,,,,,,,1,,1,,,,,,,,,,Feb-21 -1,,1,,,,1,,,,,21,1,,,,3,,1,,8,,,,,,,,,3,,,,,,,,1,,1,,Jan-21 -,3,2,,,,,,,,,23,,,,2,4,,1,,4,,,,,,2,,,3,,1,,,1,,,,,,,Dec-20 -,1,,,,,,,,,,28,1,,,,6,,,,13,,,,1,,,,,5,,,,,,,,,,1,,Nov-20 -1,1,3,,,,1,,,,,29,1,,,,6,,1,,11,,1,,1,,,,,,1,,,,,,,,,1,,Oct-20 -,1,2,,,,,,,1,,25,,,,,6,,1,,8,,,,,,,,,3,,,,,,,3,,,,,Sep-20 -,,,,,,,,,,,27,,,1,,6,,,,12,,,,,,,,,2,,1,1,,,1,2,,1,,,Aug-20 -,,1,,,,1,,,,,28,1,,,1,10,,,1,8,,,,,,1,,,4,,,,,,,,,,,,Jul-20 -1,1,4,,,,3,,,,,36,1,,,1,6,,,1,10,,1,,1,1,,,,3,,1,,,,,,,,1,,Jun-20 -1,,,,,,1,,,,1,36,,,,2,8,,,1,10,,1,,1,,,,,9,,,,,,,,,1,,,May-20 -,,,,,,,,,,,17,,,,,6,,,,6,,,,,,1,,,1,,1,2,,,,,,,,,Apr-20 -,,,,,,,,,,,8,,,,,4,,,,1,,,,,,,,,3,,,,,,,,,,,,Mar-20 -,,,,,,,,,,,6,,,,,3,,,,1,,,,,,,,,2,,,,,,,,,,,,Feb-20 +health informatics,microbiology,emergency medicine,orthopedics,genomics,biochemistry,neurology,pathology,dermatology,biophysics,epidemiology,immunology,respiratory medicine,oncology,health policy,Total,primary care research,obstetrics and gynecology,pharmacology and therapeutics,bioinformatics,occupational and environmental health,radiology and imaging,intensive care and critical care medicine,surgery,molecular biology,pediatrics,dentistry and oral medicine,genetic and genomic medicine,evolutionary biology,month,allergy and immunology,hiv aids,scientific communication and education,geriatric medicine,psychiatry and clinical psychology,public and global health,health economics,cardiovascular medicine,health systems and quality improvement,systems biology,infectious diseases +,,,,,,,,,,1,,,,,4,,,,,,,,,,,,,,Feb-24,,,,,,2,,,,,1 +,,,,,,,,,,,,,,,3,,,,,1,,,,,,,,,Jan-24,,,,,,2,,,,, +,,,,,,1,,,,4,,,,,9,,,,,1,,,,,,,,,Dec-23,,,,,,1,2,,,, +,,,,,,,,,,2,,,1,,4,,,,,,,,,,,,,,Nov-23,,,,,,,,,,,1 +1,,,,,,,,,,1,1,1,,,5,,,,,,,,,,,,,,Oct-23,,,,,,,,,,,1 +,,,,,,,,,,,,,,,1,,,,,,,,,,,,,,Sep-23,,,,,,,,,,,1 +,,,,,,,,,,4,,,,,7,1,,,,1,,,,,,,,,Aug-23,,,,,,1,,,,, +,,,,,,,,,,3,,,,,7,,,,,,,,,,,,1,,Jul-23,,,,,,1,,,2,, +1,,,1,,,,,,,1,,,,,7,,,,,1,,,,,,,,,Jun-23,,,1,,,,,,,,2 +,,,,,,,,,,2,1,1,,,6,,,,,,,,,,,,,,May-23,,,,,,1,,,,,1 +,,,,,,,,,,,,,,,3,,,,,,,,,,,,,,Apr-23,,,,,,2,,,,,1 +,,,,,,,,,,2,,,,,9,,,,,1,,,,,,,,,Mar-23,,,,,1,2,,,,,3 +,,,,,,1,,,,4,,1,,,8,,,,,,,,,,,,,,Feb-23,,,,,,2,,,,, +,,,,,,,,,,5,,,,,6,,,,,,,,,,,,,,Jan-23,,,,,,,,,,,1 +,,,,,,,1,,,3,,2,,1,12,,,,,,,,,,,,,,Dec-22,,,,,,1,,,,,4 +,,,,,,,,,,,,,,,4,,,,,,,,,,,,,,Nov-22,,,,,,,,,,,4 +,,,,,,,,,,1,,,,,6,,,,,,,,,,,,,,Oct-22,,,,,,2,,1,,,2 +,1,,,,,,,,,1,,1,,,9,,,,,2,,,,,1,,,,Sep-22,,,,,,1,,,,,2 +,,,,,,,,,,2,,,,,8,,,,,,,,,,,,,,Aug-22,,,,,,3,,,,,3 +1,,,,,,,,,,1,1,,,,7,,,,,,,,,,1,,,,Jul-22,,,,,,,,,,,3 +,,,,,,,,,,6,,,,,17,,,,,,,,,,,,1,,Jun-22,,,,,5,1,,,,,4 +,1,,,,,,,,,2,,,,,14,1,,,,,,,,,,,,,May-22,,,,,2,1,1,,1,,5 +,1,,,,,,,,,5,,1,,,15,,,,,1,,,,,,,,,Apr-22,,,,,,1,1,,2,,3 +,,,,,,,,,,9,,,,,17,1,,,,,,,,,,,,1,Mar-22,,,,,1,,,,,,5 +,,,,,,1,,,,6,,,,,12,,,,,,,,,,,,,,Feb-22,,,,,,1,,,,,4 +2,,,,,,,,,,5,1,,,,14,,,,,1,,,,,,,,,Jan-22,,,,,,1,,1,,,3 +,1,,,,,1,,,,7,,,,,21,1,,,,,,,,,1,,,,Dec-21,,,,,,1,,1,,,8 +,,,,1,,1,,,1,9,,,,,25,1,,,,,,1,,,,,,,Nov-21,,,,,1,3,,,2,,5 +,,,,,,,,,,4,,,,,11,,,,,,,,,,1,,,,Oct-21,,,,1,2,,,,,,3 +1,,,,,,,,,,6,,,,,17,,,1,,,,1,,,,,,,Sep-21,,,,,,2,,1,,,5 +1,,,,,,,,,,2,,1,,,13,,,,,1,,1,,,,,,,Aug-21,,,,,,3,,1,,,3 +,,1,,,,,,,,3,,2,1,,25,,,,,,,1,,,1,,1,,Jul-21,,,,,,4,,,,,11 +1,,,,,,1,,,,7,1,,,,28,1,,,,1,,1,,,1,,,,Jun-21,1,,,,1,4,,,1,,7 +1,,,,,,,,1,,11,,,,,23,,,,,,,,,,,,1,,May-21,,,,,1,,,,,,8 +1,1,,,,,,,,,4,,,,,20,1,,,,2,,,,,,,,,Apr-21,1,,,,1,1,,,1,,7 +2,,,,,1,1,,,,6,,,,,38,,,,,,1,,,,1,,1,,Mar-21,,,,2,1,5,,,,,17 +1,,,,,,,,,,8,,,,,23,,,,,,,,1,,,,,,Feb-21,,,,,,1,1,1,1,,9 +,,,,,,,,,,4,1,,,1,22,1,,,,,,1,,,,1,,,Jan-21,,,,1,1,3,,,1,,7 +3,1,,,2,,,,,,4,,,,,23,1,,,,,,,,,,,,,Dec-20,,,,,2,3,,2,1,,4 +1,,,,,,,,,,6,1,,,1,28,,,,1,,,,,,,,,,Nov-20,,,,,,5,,,,,13 +1,,,,,,,,,,6,1,,1,,29,1,,,1,,,1,,,,,,,Oct-20,,,,1,3,,,,,1,12 +1,1,3,,,,,,,,5,,,,,26,1,,,,,,1,,,,,,,Sep-20,,1,,,2,3,,,,,8 +,,1,,,,,,,,6,,,,,26,,1,,,1,,,,1,,,1,,Aug-20,,,,,,2,,,1,,12 +,,,,1,,,,,,9,1,1,,,27,,,,,,,1,,,,,,,Jul-20,,,,,1,4,,1,,,8 +1,,,,,,,,,,7,1,1,1,1,34,,,,1,,,3,,,,,,,Jun-20,,,,1,3,2,,1,1,,10 +1,,,,,,,,,,7,,1,1,,36,,,,1,1,,1,,,,,,,May-20,,,,1,,9,1,2,,,10 +,,,,1,,,,,,7,,,,,18,,,,,,,,,,,,2,,Apr-20,,,,,,1,,,1,,6 +,,,,,,,,,,4,,,,,8,,,,,,,,,,,,,,Mar-20,,,,,,3,,,,,1 +,,,,,,,,,,4,,,,,7,,,,,,,,,,,,,,Feb-20,,,,,,2,,,,,1 diff --git a/data/covid/preprints.csv b/data/covid/preprints.csv index 2f653f93..25f34e61 100644 --- a/data/covid/preprints.csv +++ b/data/covid/preprints.csv @@ -88,20 +88,6 @@ Results277 long covid patients and 50 frequency-matched healthy volunteers were ConclusionMore than half of long covid patients experienced OI symptoms during NLT and more than one in ten patients met the criteria for either PoTS or OH, half of whom did not report previous typical OI symptoms. We recommend all patients attending long covid clinics are offered an NLT and appropriate management commenced. Trial registration numbers NCT05057260, ISRCTN15022307",neurology,fuzzy,100,100 -medRxiv,10.1101/2023.12.07.23299429,2023-12-09,https://medrxiv.org/cgi/content/short/2023.12.07.23299429,Mechanisms underlying exercise intolerance in Long COVID: an accumulation of multi-system dysfunction,Alexandra Jamieson; Lamia Al Saikhan; Lamis Alghamdi; Lee Hamill Howes; Helen Purcell; Toby Hillman; Melissa J Heightman; Thomas A. Treibel; Michele Orini; Robert Midgley Bell; Marie Scully; Mark Hamer; Nishi Chaturvedi; Alun Hughes; Ronan Astin; Siana Jones,"University College London; Imam Abdulrahman Bin Faisal University; University College London; University College London; University College London Hospitals NHS Foundation Trust; University College London Hospitals NHS Foundation Trust; UCLH; University College London; University College London; The Hatter Cardiovascular Institute, University College London; University College London Hospitals NHS Foundation Trust; UCL; University College London; UCL; University College London Hospitals NHS Foundation Trust; University College London","The pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood. - -Cases were recruited from a Long COVID clinic (N=32; 44{+/-}12y; 10(31%)men), and age/sex- matched healthy controls (HC) (N=19; 40{+/-}13y; 6(32%)men) from University College London staff and students. We assessed exercise performance, lung and cardiac function, vascular health, skeletal muscle oxidative capacity and autonomic nervous system (ANS) function. Key outcome measures for each physiological system were compared between groups using potential outcome means(95% confidence intervals) adjusted for potential confounders. Long COVID participant outcomes were compared to normative values. - -When compared to HC, cases exhibited reduced Oxygen Uptake Efficiency Slope (1847(1679,2016) vs (2176(1978,2373) ml/min, p=0.002) and Anaerobic Threshold (13.2(12.2,14.3) vs 15.6(14.4,17.2) ml/Kg/min, p<0.001), and lower oxidative capacity on near infrared spectroscopy ({tau}: 38.7(31.9,45.6) vs 24.6(19.1,30.1) seconds, p=0.001). In cases, ANS measures fell below normal limits in 39%. - -Long COVID is associated with reduced measures of exercise performance and skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology. There was evidence of attendant ANS dysregulation in a significant proportion. These multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers. - -Key PointsO_LIThe pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood. -C_LIO_LIWe show that Long COVID is associated with reduced measures of exercise performance in line with previous work. -C_LIO_LIIn Long COVID cases, we observed reduced skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology. -C_LIO_LIWe also observed evidence of attendant autonomic nervous system (ANS) dysregulation in a significant proportion of Long COVID cases. -C_LIO_LIThese multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers. -C_LI",cardiovascular medicine,fuzzy,100,100 medRxiv,10.1101/2023.12.06.23299601,2023-12-07,https://medrxiv.org/cgi/content/short/2023.12.06.23299601,The impact of Long COVID on Health-Related Quality-of-life using OpenPROMPT,Oliver Carlile; Andrew Briggs; Alasdair Henderson; Ben Butler-Cole; John Tazare; Laurie Tomlinson; Michael Marks; Mark Jit; Liang-Yu Lin; Chris Bates; John Parry; Sebastian Bacon; Iain Dillingham; William Dennison; Ruth Costello; Alex Walker; William J Hulme; Ben Goldacre; Amir Mehrkar; Brian MacKenna; - The OpenSAFELY Collaborative; Emily Herrett; Rosalind Eggo,"London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Patient and Public Involvement Steering Committee; London School of Hygiene and Tropical Medicine; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; -; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine","BackgroundLong COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. MethodsWith the approval of NHS England, we developed OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. @@ -338,6 +324,13 @@ Findings: Certain groups were found to be at overall higher risk of postbooster Meaning: This work has implications for prioritisation of vaccination booster doses worldwide. We highlight which groups with health conditions are at elevated risk of postbooster COVID-19 death.",public and global health,fuzzy,100,100 medRxiv,10.1101/2023.06.29.23292056,2023-07-01,https://medrxiv.org/cgi/content/short/2023.06.29.23292056,Genome-wide Association Study of Long COVID,Vilma Lammi; Tomoko Nakanishi; Samuel E Jones; Shea J Andrews; Juha Karjalainen; Beatriz Cortes; Heath E O'Brien; Brian E Fulton-Howard; Hele H Haapaniemi; Axel Schmidt; Ruth E Mitchell; Abdou Mousas; Massimo Mangino; Alicia Huerta-Chagoya; Nasa Sinnott-Armstrong; Elizabeth T Cirulli; Marc Vaudel; Alex SF Kwong; Amit K Maiti; Minttu M Marttila; Chiara Batini; Francesca Minnai; Anna R Dearman; CA Robert Warmerdam; Celia B Sequeros; Thomas W Winkler; Daniel M Jordan; Lindsay Guare; Ekaterina Vergasova; Eirini Marouli; Pasquale Striano; Ummu Afeera Zainulabid; Ashutosh Kumar; Hajar Fauzan Ahmad; Ryuya Edahiro; Shuhei Azekawa; - Long COVID Host Genetics Initiative; - FinnGen; - DBDS Genomic Consortium; - GEN-COVID Multicenter Study; Joseph J Grzymski; Makoto Ishii; Yukinori Okada; Noam D Beckmann; Meena Kumari; Ralf Wagner; Iris M Heid; Catherine John; Patrick J Short; Per Magnus; Karina Banasik; Frank Geller; Lude H Franke; Alexander Rakitko; Emma L Duncan; Alessandra Renieri; Konstantinos K Tsilidis; Rafael de Cid; Ahmadreza Niavarani; Teresa Tusie-Luna; Shefali S Verma; George Davey Smith; Nicholas J Timpson; Mark J Daly; Andrea Ganna; Eva C Schulte; J Brent Richards; Kerstin U Ludwig; Michael Hultstrom; Hugo Zeberg; Hanna M Ollila,Institute for Molecular Medicine Finland (FIMM); Department of Human Genetics; Institute for Molecular Medicine Finland (FIMM); University of California San Francisco; Institute for Molecular Medicine Finland (FIMM); Genomes for Life-GCAT lab; Sano Genetics Limited; Genetics and Genomic Sciences; Institute for Molecular Medicine Finland (FIMM); Institute of Human Genetics; Centre for Clinical Brain Sciences; Department of Hygiene and Epidemiology; Department of Twin Research; Departamento de Medicina Genomica y Toxicologia Ambiental; Herbold Computational Biology Program; Helix; Mohn Center for Diabetes Precision Medicine; University of Bristol; Department of Genetics and Genomics; University of Helsinki; Department of Population Health Sciences; Institute for Biomedical Technologies - National Research Council; Institute for Social and Economic Research; Department of Genetics; Novo Nordisk Foundation Center for Protein Research; Department of Genetic Epidemiology; Charles Bronfman Institute for Personalized Medicine; Department of Pathology and Laboratory Medicine; Genotek Ltd.; William Harvey Research Institute; IRCCS G; Department of Internal Medicine; Department of Anatomy; Faculty of Industrial Sciences and Technology; Department of Statistical Genetics; Division of Pulmonary Medicine; ; ; ; ; Center for Genomic Medicine; Division of Pulmonary Medicine; Department of Statistical Genetics; Charles Bronfman Institute for Personalized Medicine; Institute for Social and Economic Research; Institute of Medical Microbiology & Hygiene; Department of Genetic Epidemiology; Department of Population Health Sciences; Sano Genetics Limited; Centre for Fertility and Health; Novo Nordisk Foundation Center for Protein Research; Statens Serum Institute; Department of Genetics; Genotek Ltd.; Department of Twin Research and Genetic Epidemiology; Medical Genetics; Department of Hygiene and Epidemiology; Genomes for Life-GCAT lab; Digestive Oncology Research Center; Instituto de Investigaciones Biomedicas Unam/ Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran; Department of Pathology and Laboratory Medicine; MRC Integrative Epidemiology Unit at the University of Bristol; MRC Integrative Epidemiology Unit at the University of Bristol; Institute for Molecular Medicine Finland (FIMM); Institute for Molecular Medicine Finland (FIMM); Institute of Psychiatric Phenomics & Genomics; Department of Human Genetics; Institute of Human Genetics; Anaesthesiology and Intensive Care Medicine; Department of Evolutionary Genetics; Institute for Molecular Medicine Finland (FIMM),"Infections can lead to persistent or long-term symptoms and diseases such as shingles after varicella zoster, cancers after human papillomavirus, or rheumatic fever after streptococcal infections1, 2. Similarly, infection by SARS-CoV-2 can result in Long COVID, a condition characterized by symptoms of fatigue and pulmonary and cognitive dysfunction3-5. The biological mechanisms that contribute to the development of Long COVID remain to be clarified. We leveraged the COVID-19 Host Genetics Initiative6, 7 to perform a genome-wide association study for Long COVID including up to 6,450 Long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We identified the first genome-wide significant association for Long COVID at the FOXP4 locus. FOXP4 has been previously associated with COVID-19 severity6, lung function8, and cancers9, suggesting a broader role for lung function in the pathophysiology of Long COVID. While we identify COVID-19 severity as a causal risk factor for Long COVID, the impact of the genetic risk factor located in the FOXP4 locus could not be solely explained by its association to severe COVID-19. Our findings further support the role of pulmonary dysfunction and COVID-19 severity in the development of Long COVID.",genetic and genomic medicine,fuzzy,100,100 +medRxiv,10.1101/2023.06.30.23292079,2023-06-30,https://medrxiv.org/cgi/content/short/2023.06.30.23292079,Synthesis and new evidence from the PROTECT UK National Core Study: Determining occupational risks of SARS-CoV-2 infection and COVID-19 mortality,Sarah Rhodes; Sarah Beale; Mark Cherrie; William Mueller; Fiona Holland; Melissa Matz; Ioannis Basinas; Jack D Wilkinson; Matthew Gittins; Bernardine Farrell; Andrew Hayward; Neil Pearce; Martie van Tongeren,University of Manchester; University College London; Institute of Occupational Medicine; Institute of Occupational Medicine; University of Manchester; London School of Hygiene and Tropical Medicine; University of Manchester; University of Manchester; University of Manchester; University of Manchester; UCL; London School of Hygiene and Tropical Medicine; University of Manchester,"IntroductionThe PROTECT National Core Study was funded by the UK Health and Safety Executive (HSE) to investigate routes of transmission for SARS-CoV-2 and variation between settings. + +MethodsA workshop was organised in Oct 2022.We brought together evidence from five published epidemiological studies that compared risks of SARS-CoV-2 infection or COVID-19 mortality by occupation or sector funded by PROTECT relating to three non-overlapping data sets, plus additional unpublished analyses relating to the Omicron period. We extracted descriptive study level data and model results. We investigated risk across four pandemic waves using forest plots for key occupational groups by time-period. + +ResultsResults were largely consistent across different studies with different expected biases. Healthcare and social care sectors saw elevated risks of SARS-CoV-2 infection and COVID-19 mortality early in the pandemic, but thereafter this declined and varied by specific occupational subgroup. The education sector saw sustained elevated risks of infection after the initial lockdown period with little evidence of elevated mortality. + +ConclusionsIncreased in risk of infection and mortality were consistently observed for occupations in high risk sectors particularly during the early stage of the pandemic. The education sector showed a different pattern compared to the other high risk sectors, as relative risk of infections remained high in the later phased of the pandemic, although no increased in COVID-19 mortality (compared to low-risk occupations) was observed in this sector in any point during the pandemic.",occupational and environmental health,fuzzy,100,100 medRxiv,10.1101/2023.06.29.23292043,2023-06-30,https://medrxiv.org/cgi/content/short/2023.06.29.23292043,Risk of SARS-CoV-2 reinfection during multiple Omicron variant waves in the UK general population,Jia Wei; Nicole Stoesser; Philippa Matthews; Tarnjit Khera; Owen Gethings; Ian Diamond; Ruth Studley; Nick Taylor; tim E peto; Ann Sarah Walker; Koen Pouwels; David W Eyre,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; oxford university; University of Oxford; University of Oxford; University of Oxford,"SARS-CoV-2 reinfections increased substantially after Omicron variants emerged. Large-scale community-based comparisons across multiple Omicron waves of reinfection characteristics, risk factors, and protection afforded by previous infection and vaccination, are limited, especially after widespread national testing stopped. We studied 245,895 adults [≥]18y in the UKs national COVID-19 Infection Survey with at least one infection (identified from positive swab tests done within the study, linked from national testing programmes, or self-reported by participants, up to their last study assessment). We quantified the risk of reinfection in multiple infection waves, including those driven by BA.1, BA.2, BA.4/5, and most recently BQ.1/CH.1.1/XBB.1.5 variants, in which most reinfections occurred. Reinfections had higher cycle threshold (Ct) values (lower viral load) and lower percentages self-reporting symptoms compared with first infections. Across multiple Omicron waves, protection against reinfection was significantly higher in those previously infected with more recent than earlier variants, even at the same time from previous infection. Protection against Omicron reinfections decreased over time from the most recent infection if this was the previous or penultimate variant (generally within the preceding year), but did not change or even slightly increased over time if this was with an even earlier variant (generally >1 year previously). Those 14-180 days after receiving their most recent vaccination had a lower risk of reinfection with all Omicron variants except BA.2 than those >180 days from their most recent vaccination. Reinfection risk was independently higher in those aged 30-45 years, and with either low or high Ct values in their most recent previous infection. Overall, the risk of Omicron reinfection is high, but with lower severity than first infections; reinfection risk is likely driven as much by viral evolution as waning immunity.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2023.06.23.23291776,2023-06-29,https://medrxiv.org/cgi/content/short/2023.06.23.23291776,Patient characteristics associated with clinically coded long COVID: an OpenSAFELY study using electronic health records,Yinghui Wei; Elsie M F Horne; Rochelle Knight; Genevieve Cezard; Alex J Walker; Louis Fisher; Rachel Denholm; Kurt Taylor; Venexia Walker; Stephanie Riley; Dylan M Williams; Robert John Willans; Simon Davy; Sebastian Bacon; Ben John Goldacre; Amir-Reza Mehrkar-Asl; Spiros Denaxas; Felix Greaves; Richard Silverwood; Aziz Sheikh; Nish Chaturvedi; Angela Wood; John Macleod; Claire Steves; Jonathan A C Sterne,"University of Plymouth; University of Bristol; University of Bristol; University of Cambridge; University of Oxford; University of Oxford; University of Bristol; University of Bristol; University of Bristol; University of Plymouth; UCL; National Institute of Health and Care Excellence; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University College London; Imperial College London; University College London; The University of Edinburgh; University College London; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, United Kingdom; University of Bristol; King's College London; University of Bristol","Despite reports of post-COVID-19 syndromes (long COVID) are rising, clinically coded long COVID cases are incomplete in electronic health records. It is unclear how patient characteristics may be associated with clinically coded long COVID. With the approval of NHS England, we undertook a cohort study using electronic health records within the OpenSAFELY-TPP platform in England, to study patient characteristics associated with clinically coded long COVID from 29 January 2020 to 31 March 2022. We estimated age-sex adjusted hazard ratios and fully adjusted hazard ratios for coded long COVID. Patient characteristics included demographic factors, and health behavioural and clinical factors. Among 17,986,419 adults, 36,886 (0.21%) were clinically coded with long COVID. Patient characteristics associated with coded long COVID included female sex, younger age (under 60 years), obesity, living in less deprived areas, ever smoking, greater consultation frequency, and history of diagnosed asthma, mental health conditions, pre-pandemic post-viral fatigue, or psoriasis. The strength of these associations was attenuated following two-dose vaccination compared to before vaccination. The incidence of coded long COVID was higher after hospitalised than non-hospitalised COVID-19. These results should be interpreted with caution given that long COVID was likely under-recorded in electronic health records.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2023.06.23.23291820,2023-06-29,https://medrxiv.org/cgi/content/short/2023.06.23.23291820,Impact of the Covid-19 Pandemic on Audiology Service Delivery: Observational Study of the Role of Social Media in Patient Communication,Adeel Hussain; Zain Hussain; Mandar Gogate; Kia Dashtipour; Adele Goman; Aziz Sheikh; Amir Hussain,Edinburgh Napier University; The University of Edinburgh; Edinburgh Napier University School of Computing: Edinburgh Napier University School of Computing Engineering and the Built Environment; Edinburgh Napier University School of Computing: Edinburgh Napier University School of Computing Engineering and the Built Environment; Edinburgh Napier University School of Life Sciences: Edinburgh Napier University School of Health and Social Care; The University of Edinburgh Edinburgh Medical School; Edinburgh Napier University School of Computing: Edinburgh Napier University School of Computing Engineering and the Built Environment,"The Covid-19 pandemic has highlighted an era in hearing health care that necessitates a comprehensive rethinking of audiology service delivery. There has been a significant increase in the number of individuals with hearing loss who seek information online. An estimated 430 million individuals worldwide suffer from hearing loss, including 11 million in the United Kingdom. The objective of this study was to identify NHS audiology service social media posts and understand how they were used to communicate service changes within audiology departments at the onset of the Covid-19 pandemic.Facebook and Twitter posts relating to audiology were extracted over a six week period (March 23 to April 30 2020) from the United Kingdom. We manually filtered the posts to remove those not directly linked to NHS audiology service communication. The extracted data was then geospatially mapped, and themes of interest were identified via a manual review. We also calculated interactions (likes, shares, comments) per post to determine the posts efficacy. A total of 981 Facebook and 291 Twitter posts were initially mined using our keywords, and following filtration, 174 posts related to NHS audiology change of service were included for analysis. The results were then analysed geographically, along with an assessment of the interactions within the included posts. NHS Trusts and Boards should consider incorporating and promoting social media to communicate service changes. Users would be notified of service modifications in real-time, and different modalities could be used (e.g. videos), resulting in a more efficient service.",health informatics,fuzzy,100,100 @@ -532,6 +525,17 @@ Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Ovid ME Added value of this studyWe conducted age-standardised time series analyses using comprehensive, linked, anonymised, individual-level routinely-collected, population-scale health data for the population of Wales, UK. By accounting for seasonal variations in prescribing and mortality, we demonstrated that the absolute increase in antipsychotic prescribing in people with dementia of any cause during the COVID-19 pandemic was small. In contrast, antipsychotic prescribing in the youngest age group (60-64 years) and in people with a subtype diagnosis of Alzheimers disease increased throughout the five-year study period. Accounting for seasonal variation, all-cause mortality rates in people with dementia began to increase in late 2019 and increased sharply during the first few months of the pandemic. COVID-19 became the leading non-dementia cause of death in people with dementia from 2020 to 2021. Stroke mortality increased during the pandemic, following a similar pattern to that of all-cause mortality, whereas myocardial infarction rates decreased. Implications of all the available evidenceDuring COVID-19 we observed a large increase in all-cause and stroke mortality in people with dementia. When seasonal variations are accounted for, antipsychotic prescribing rates in all-cause dementia increased by a small amount before and during the pandemic in the UK. The increased prescribing rates in younger age groups and in people with Alzheimers disease warrants further investigation.",neurology,fuzzy,100,100 +medRxiv,10.1101/2023.02.16.23286017,2023-02-18,https://medrxiv.org/cgi/content/short/2023.02.16.23286017,Long-term outdoor air pollution and COVID-19 mortality in London: an individual-level analysis,Loes Charlton; Chris Gale; Jasper Morgan; Myer Glickman; Sean Beevers; Anna L Hansell; Vahé Nafilyan,Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Imperial College London; University of Leicester; Office for National Statistics,"BackgroundThe risk of COVID-19 severity and mortality differs markedly by age, socio-demographic characteristics and pre-existing health status. Various studies have suggested that higher air pollution exposures also increase the likelihood of dying from COVID-19. + +Objectives: To assess the association between long-term outdoor air pollution (NO2, NOx, PM10 and PM2.5) concentrations and the risk of death involving COVID-19, using a large individual-level dataset. + +MethodsWe used comprehensive individual-level data from the Office for National Statistics Public Health Data Asset for September 2020 to January 2022 and London Air Quality Network modelled air pollution concentrations available for 2016. Using Cox proportional hazard regression models, we adjusted for potential confounders including age, sex, vaccination status, dominant virus variants, geographical factors (such as population density), ethnicity, area and household-level deprivation, and health comorbidities. + +ResultsThere were 737,356 confirmed COVID-19 cases including 9,315 COVID-related deaths. When only adjusting for age, sex, and vaccination status, there was an increased risk of dying from COVID-19 with increased exposure to all air pollutants studied (NO2: HR 1.07 [95% confidence interval: 1.04-1.12] per 10 g/m3; NOx: 1.05[1.02-1.09] per 20 g/m3; PM10: 1.32[1.15-1.51] per 10 g/m3; PM2.5: 1.29[1.12-1.49] per 5 g/m3). However, after adjustment including ethnicity and socio-economic factors the HRs were close to unity (NO2: 0.98[0.90-1.06]; NOx: 0.99[0.94-1.04]; PM10: 0.95[0.74-1.22]; PM2.5: 0.90[0.67-1.20]). Additional adjustment for dominant variant or pre-existing health comorbidities did not alter the results. + +ConclusionsObserved associations between long-term outdoor air pollution exposure and COVID-19 mortality in London are strongly confounded by geography, ethnicity and deprivation. + +SummaryUsing a large individual-level dataset, we found that a positive association between long-term outdoor air pollution and COVID-19 mortality in London did not persist after adjusting for confounders including population density, ethnicity and deprivation.",respiratory medicine,fuzzy,100,100 medRxiv,10.1101/2023.02.10.23285717,2023-02-14,https://medrxiv.org/cgi/content/short/2023.02.10.23285717,The long COVID evidence gap: comparing self-reporting and clinical coding of long COVID using longitudinal study data linked to healthcare records.,Anika Knuppel; Andy Boyd; John Macleod; Nishi Chaturvedi; Dylan M Williams,"MRC Unit of Lifelong Health and Ageing at UCL, University College London, London W1E 7HB, London, United Kingdom; Institute of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom; Institute of Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, United Kingdom; MRC Unit of Lifelong Health and Ageing at UCL, University College London, London W1E 7HB, London, United Kingdom; MRC Unit of Lifelong Health and Ageing at UCL, University College London, London W1E 7HB, London, United Kingdom","The term ""long COVID"" (LC) was coined in spring 2020 by individuals with ongoing symptoms following COVID-19, but it took until December 2020 for clinical codes to be created in order to record persistent post-COVID-19 illness and referrals within electronic health records (EHRs). Analysis of whole-population EHR databases have helped understand the epidemiology of LC; yet concerns exist about the completeness of accessible EHRs for LC. UK longitudinal population studies (LPS) collected self-reported data on COVID-19 and LC from early 2020 and deposited these data in the UK Longitudinal Linkage Collaboration (UK LLC) research database where they are systematically linked to the participants EHRs. Comparisons of LPS reported LC with recorded LC in the EHRs of the same individuals may be helpful in understanding the epidemiology of emerging conditions such as LC. We used data from 10 UK LPS in the UK LLC to investigate whether participants self-reporting LC had a LC diagnosis or referral code in their English EHR after 10 to 22 months of follow up. Of 6412 participants with COVID-19 symptom duration data and linkage to health records, 898 (14.0%) self-reported LC of any severity in LPS surveys. Among these, just 42 (4.7%; 95% CI: 3.5, 6.3) were identified with LC-related codes in EHRs. In individuals reporting debilitating LC, this proportion was only marginally higher (5.6%; 95% CI: 3.7, 8.3). Our data show a striking discrepancy between LC as perceived and reported by participants in LPS and evidence of LC recorded in their EHRs; and that this discrepancy was patterned by ethnicity and possibly by indicators of deprivation. Self-reported symptoms may not be reflected in coded EHRs due to factors including variations in individuals help seeking behaviours, clinician coding practices and the availability of appropriate codes. However, these considerations appear unlikely to provide a complete explanation for the substantial observed reporting discrepancy. These results may indicate substantial unmet clinical need, in keeping with patient reports of difficulties accessing healthcare and sub-optimal recognition of, and response to, their illness when they do. They may also indicate potential shortcomings of epidemiological research on LC based on EHR- or LPS-based ascertainment alone and illustrate the value of triangulation between LPS and EHR data where linked and made available through resources such as the UK LLC.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2023.02.09.23285649,2023-02-14,https://medrxiv.org/cgi/content/short/2023.02.09.23285649,"Antibody prevalence after 3 or more COVID-19 vaccine doses in 23,000 immunosuppressed individuals: a cross-sectional study from MELODY",Fiona A Pearce; Sean Hua Lim; Mary Bythell; Peter Lanyon; Rachel Hog; Adam Taylor; Gillian Powter; Graham Cooke; Helen Ward; Joseph Chilcot; Helen Thomas; Lisa Mumford; Stephen P McAdoo; Gavin J Pettigrew; Liz Lightstone; Michelle Willicombe,"Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, UK; Centre for Cancer Immunology, University of Southampton, Southampton, UK; National Disease Registration Service, NHS Digital; Department of Rheumatology, Nottingham University Hospitals NHS Trust, Nottingham, UK; Statistics and Clinical Research, NHS Blood and Transplant, Bristol, UK; Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, UK; NHS Blood and Transplant Clinical Trials Unit, Oxford, UK; Imperial College; Imperial College London; Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; Statistics and Clinical Research, NHS Blood and Transplant, Bristol, UK; Statistics and Clinical Research, NHS Blood and Transplant, Bristol, UK; Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, Hammersmith Campus, Du Cane Road, London, UK.; Department of Surgery, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, Hammersmith Campus, Du Cane Road, London, UK.; Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, Hammersmith Campus, Du Cane Road, London, UK.","ObjectivesTo investigate the prevalence of spike-protein antibodies following at least 3 COVID-19 vaccine doses in immunocompromised individuals. @@ -932,9 +936,6 @@ MethodsThis protocol and study materials were co-produced with a Community Advis Ethics and disseminationEthical approval has been obtained from the Faculty of Medicine Ethics Committee and Research Integrity and Governance, University of Southampton. (reference number 72400). Findings will be reported in a report and submitted for peer-reviewed publication. Definitive methods of dissemination will be decided by the CAB. Summaries of the findings will also be shared on the STIMULATE-ICP website, locally in the study area and through social media. We will specifically target policy makers and those responsible for shaping and commissioning Long Covid healthcare services and social support such as NHSE England Long Covid Group.",public and global health,fuzzy,100,100 medRxiv,10.1101/2022.08.22.22278973,2022-08-24,https://medrxiv.org/cgi/content/short/2022.08.22.22278973,The Impact of SARS-CoV-2 Vaccine Dose Separation and Dose Targeting on Hospital Admissions and Deaths from COVID-19 in England,Matt J Keeling; Sam Moore; Bridget Penman; Edward M Hill,University of Warwick; University of Warwick; University of Warwick; University of Warwick,"In late 2020, the JCVI (the Joint Committee on Vaccination and Immunisation, which provides advice to the Department of Health and Social Care, England) made two important recommendations for the initial roll-out of the COVID-19 vaccine. The first was that vaccines should be targeted to the elderly and vulnerable, with the aim of maximally preventing disease rather than infection. The second was to increase the interval between first and second doses from 3 to 12 weeks. Here, we re-examine these recommendations through a mathematical model of SARS-CoV-2 infection in England. We show that targeting the most vulnerable had the biggest immediate impact (compared to targeting younger individuals who may be more responsible for transmission). The 12-week delay was also highly beneficial, estimated to have averted between 32-72 thousand hospital admissions and 4-9 thousand deaths over the first ten months of the campaign (December 2020 - September 2021) depending on the assumed interaction between dose interval and efficacy.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2022.08.17.22278893,2022-08-18,https://medrxiv.org/cgi/content/short/2022.08.17.22278893,Uptake of Sotrovimab for prevention of severe COVID-19 and its safety in the community in England,Martina Patone; Holly Tibble; Andrew JHL Snelling; Carol Coupland; Aziz Sheikh; Julia Hippisley-Cox,University of Oxford; University of Edinburgh; University of Oxford; University of Oxford; University of Edinburgh; University of Oxford,"Sotrovimab is a neutralising monoclonal antibody (nMAB), currently administrated in England to treat extremely clinically vulnerable COVID-19 patients. Trials have shown it to have mild or moderate side effects, however safety in real-world settings has not been yet evaluated. We used national databases to investigate its uptake and safety in community patients across England. We used a cohort study to describe uptake and a self-controlled case series design to evaluate the risks of 49 pre-specified suspected adverse events in the 2-28 days post-treatment. Between December 11, 2021 and May 24, 2022, there were 172,860 COVID-19 patients eligible for treatment. Of the 22,815 people who received Sotrovimab, 21,487 (94.2%) had a positive SARS-CoV-2 test and 5,999 (26.3%) were not on the eligible list. Between treated and untreated eligible individuals, the mean age (54.6, SD: 16.1 vs 54.1, SD: 18.3) and sex distribution (women: 60.9% vs 58.1%; men: 38.9% vs 41.1%) were similar. There were marked variations in uptake between ethnic groups, which was higher amongst Indian (15.0%; 95%CI 13.8, 16.3), Other Asian (13.7%; 95%CI 11.9, 15.8), White (13.4%; 95%CI 13.3, 13.6), and Bangladeshi (11.4%; 95%CI 8.8, 14.6); and lower amongst Black Caribbean individuals (6.4%; 95%CI 5.4, 7.5) and Black Africans (4.7%; 95%CI 4.1, 5.4). We found no increased risk of any of the suspected adverse events in the overall period of 2-28 days post-treatment, but an increased risk of rheumatoid arthritis (IRR 3.08, 95% CI 1.44, 6.58) and of systematic lupus erythematosus (IRR 5.15, 95% CI 1.60, 16.60) in the 2-3 days post-treatment, when we narrowed the risk period. - -FundingNational Institute of Health Research (Grant reference 135561)",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.08.13.22278733,2022-08-16,https://medrxiv.org/cgi/content/short/2022.08.13.22278733,QCovid 4 - Predicting risk of death or hospitalisation from COVID-19 in adults testing positive for SARS-CoV-2 infection during the Omicron wave in England,Julia Hippisley-Cox; Kamlesh Khunti; Aziz Sheikh; Jonathan Nguyen-Van-Tam; Carol Coupland,University of Oxford; University of Leicester; University of Edinburgh; University of Nottingham; University of Oxford,"ObjectivesTo (a) derive and validate risk prediction algorithms (QCovid4) to estimate risk of COVID-19 mortality and hospitalisation in UK adults with a SARS-CoV-2 positive test during the Omicron pandemic wave in England and (b) evaluate performance with earlier versions of algorithms developed in previous pandemic waves and the high-risk cohort identified by NHS Digital in England. DesignPopulation-based cohort study using the QResearch database linked to national data on COVID-19 vaccination, high risk patients prioritised for COVID-19 therapeutics, SARS-CoV-2 results, hospitalisation, cancer registry, systemic anticancer treatment, radiotherapy and the national death registry. @@ -975,13 +976,6 @@ Results14175 residents and 19973 staff were included. In residents without prior ConclusionsBooster vaccination provides sustained protection against severe outcomes following infection with the Omicron variant, but no protection against infection from 3 months onwards. Ongoing surveillance for SARS-CoV-2 in LTCFs is crucial. SummaryThe COVID-19 pandemic has severely impacted residents in long-term care facilities (LTCFs). Booster vaccination provides sustained moderate protection against severe outcomes, but no protection against infection was apparent from around 3 months onwards. Ongoing surveillance in LTCFs is crucial.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2022.08.07.22278510,2022-08-09,https://medrxiv.org/cgi/content/short/2022.08.07.22278510,Metabolomic and gut microbiome profiles across the spectrum of community-based COVID and non-COVID disease: A COVID-19 Biobank study.,Marc F Österdahl; Ronan Whiston; Carole H Sudre; Francesco Asnicar; Nathan J Cheetham; Aitor Blanco Miguez; Vicky Bowyer; Michela Antonelli; Olivia Snell; Liane dos Santos Canas; Christina Hu; Jonathan Wolf; Cristina Menni; Michael Malim; Deborah Hart; Tim Spector; Sarah Berry; Nicola Segata; Katie Doores; Sebastien Ourselin; Emma L Duncan; Claire J Steves,King's College London; King's College London; King's College London; University of Trento; King's College London; University of Trento; King's College London; King's College London; King's College London; King's College London; ZOE Global Ltd.; ZOE Global Ltd.; King's College London; King's College London; King's College London; King's College London; King's College London; University of Trento; King's College London; King's College London; King's College London; King's College London,"Whilst many with SARS-CoV-2 infection have mild disease, managed in the community, individuals with cardiovascular risk factors experienced often more severe acute disease, requiring hospitalisation. Increasing concern has also developed over long symptom duration in many individuals, including the majority who managed acutely in the community. Risk factors for long symptom duration, including biological variables, are still poorly defined. - -We examine post-illness metabolomic and gut-microbiome profiles, in community-dwelling participants with SARS-CoV-2, ranging from asymptomatic illness to Post-COVID Syndrome, and participants with prolonged non-COVID-19 illnesses. We also assess a pre-established metabolomic biomarker score for its association with illness duration. - -We found an atherogenic-dyslipidaemic metabolic profile, and greater biomarker scores, associated with longer illness, both in individuals with and without SARS-CoV-2 infection. We found no association between illness duration and gut microbiome in convalescence. - -Findings highlight the potential role of cardiometabolic dysfunction to the experience of long illness duration, including after COVID-19.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.08.08.22278493,2022-08-09,https://medrxiv.org/cgi/content/short/2022.08.08.22278493,Inequalities in colorectal cancer screening uptake in Wales: examination of the impact of the temporary suspension of the screening programme during the COVID-19 pandemic,Diana Bright; Sharon Hillier; Jiao Song; Dyfed W Huws; Giles Greene; Karen Hodgson; Ashley Akbari; Rowena Griffiths; Alisha R Davies,"Public Health Wales; Public Health Wales; Public Health Wales; Public Health Wales; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales; Public Health Wales; Public Health Wales; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales; Population Data Science, Swansea University Medical School, Faculty of Medicine, Health & Life Science, Swansea University, Swansea, Wales; Public Health Wales","BackgroundResponse to the early stages of the COVID-19 pandemic resulted in the temporary disruption of cancer screening in the UK, and strong public messaging to stay safe and to protect NHS capacity. Following reintroduction in services, we explored the impact on inequalities in uptake of the Bowel Screening Wales (BSW) programme to identify groups who may benefit from tailored interventions. MethodsRecords within the BSW were linked to electronic health records (EHR) and administrative data within the Secured Anonymised Information Linkage (SAIL) Databank. Ethnic group was obtained from a linked data method available within SAIL. We examined uptake for the first 3 months of invitations (August to October) following the reintroduction of BSW programme in 2020, compared to the same period in the preceding 3 years. Uptake was measured across a 6 month follow-up period. Logistic models were conducted to analyse variations in uptake by sex, age group, income deprivation quintile, urban/rural location, ethnic group, and clinically extremely vulnerable (CEV) status in each period; and to compare uptake within sociodemographic groups between different periods. @@ -1053,13 +1047,7 @@ MethodsOn behalf of NHS England, we used the OpenSAFELY-TPP database to match ad Results1,528,431 people were matched in each group, contributing a total 23,150,504 person-weeks of follow-up. The 12-week risks per 1,000 people of positive SARS-CoV-2 test were 103.2 (95%CI 102.4 to 104.0) for BNT162b2 and 96.0 (95.2 to 96.8) for mRNA-1273: the HR comparing mRNA-1273 with BNT162b2 was 0.92 (95%CI 0.91 to 0.92). For COVID-19 hospitalisations the 12-week risks per 1,000 were 0.65 (95%CI 0.56 to 0.75) and 0.44 (0.36 to 0.54): HR 0.67 (95%CI 0.58 to 0.78). COVID-19 deaths were rare: the 12-week risks per 1,000 were 0.03 (95%CI 0.02 to 0.06) and 0.01 (0.01 to 0.02): HR 1.23 (95%CI 0.59 to 2.56). Comparative effectiveness was generally similar within subgroups defined by the primary course vaccine brand, age, prior SARS-CoV-2 infection and clinical vulnerability. ConclusionBooster vaccination with mRNA-1273 COVID-19 vaccine was more effective than BNT162b2 in preventing SARS-CoV-2 infection and COVID-19 hospitalisation during the first 12 weeks after vaccination, during a period of Delta followed by Omicron variant dominance.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2022.07.20.22277838,2022-07-21,https://medrxiv.org/cgi/content/short/2022.07.20.22277838,"National and regional prevalence of SARS-CoV-2 antibodies in primary and secondary school children in England: the School Infection Survey, a national open cohort study, November 2021",Annabel A Powell; Georgina Ireland; Rebecca Leeson; Andrea Lacey; Ben Ford; John Poh; Samreen Ijaz; Justin Shute; Peter Cherepanov; Richard Tedder; Christian Bottomley; Fiona Dawe; Punam Mangtani; Peter Jones; Patrick Nguipdop-Djomo; Shamez Ladhani,UK Health Security Agency; UK Health Security Agency; Office for National Statistics; Office for National Statistics; Office for National Statistics; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; Imperial College London; Francis Crick Institute; London School of Hygiene & Tropical Medicine; Office for National Statistics; London School of Hygiene & Tropical Medicine; Office for National Statistics; London School of Hygiene & Tropical Medicine; UK Health Security Agency,"BackgroundRisk factors for infection and, therefore, antibody positivity rates will be different in children compared to adults. We aim to estimate national and regional prevalence of SARS-CoV-2 antibodies in primary (4-11-year-olds) and secondary (11-15-year-olds) school children between 10 November and 10 December 2021. - -MethodsCross-sectional surveillance in England using two stage sampling, firstly stratifying into regions and selecting local authorities, then selecting schools according to a stratified sample within selected local authorities. Participants were sampled using a novel oral fluid validated assay for SARS-CoV-2 spike and nucleocapsid IgG antibodies. - -Results4,980 students from 117 state-funded schools (2,706 from 83 primary schools, 2,274 from 34 secondary schools) provided a valid sample. After weighting for age, sex and ethnicity, and adjusting for assay accuracy, the national prevalence of SARS-CoV-2 antibodies in primary school students, who were all unvaccinated, was 40.1% (95%CI; 37.3-43.0). Antibody prevalence increased with age (p<0.001) and were higher in urban than rural schools (p=0.01). In secondary school students, the adjusted, weighted national prevalence of SARS-CoV-2 antibodies was 82.4% (95%CI; 79.5-85.1); including 57.5% (95%CI; 53.9-61.1) in unvaccinated and 97.5% (95%CI; 96.1-98.5) in vaccinated students. Antibody prevalence increased with age (p<0.001), and was not significantly different in urban versus rural students (p=0.1). - -ConclusionsUsing a validated oral fluid assay, we estimated national and regional seroprevalence of SARS-CoV-2 antibodies in primary and secondary school students. In November 2021, 40% of primary school students and nearly all secondary school students in England had SARS-CoV2 antibodies through a combination of natural infection and vaccination.",epidemiology,fuzzy,92,100 +bioRxiv,10.1101/2022.07.26.501570,2022-07-26,https://biorxiv.org/cgi/content/short/2022.07.26.501570,Primary Omicron infection elicits weak antibody response but robust cellularimmunity in children,Alexander C Dowell; Tara Lancaster; Rachel Bruton; Georgina Ireland; Christopher Bentley; Panagiota Sylla; Jianmin Zuo; Sam Scott; Azar Jardin; Jusnara Begum; Thomas Roberts; Christine Stephens; Shabana Ditta; Rebecca Shepherdson; Annable Powell; Andrew Brent; Bernadette Brent; Frances Baawuah; Ifeanyichukwu Okike; Joanna Beckmann; Shazaad Ahmad; Felicity Aiano; Joanna Garstang; Mary Ramsay; Rafaq Azad; Dagmar Waiblinger; Brian Willet; John Wright; Shamez Ladhani; Paul Moss,"Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; East London NHS Foundation Trust, 9 Allie Street, London E1 8DE, UK; Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Birmingham Community Healthcare NHS Trust, Holt Street, Aston B7 4BN, UK; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK","Omicron variants of SARS-CoV-2 are globally dominant and infection rates are very high in children. We determined immune responses following Omicron BA.1/2 infection in children aged 6-14 years and related this to prior and subsequent SARS-CoV-2 infection or vaccination. Primary Omicron infection elicited a weak antibody response with poor functional neutralizing antibodies. Subsequent Omicron reinfection or COVID-19 vaccination elicited increased antibody titres with broad neutralisation of Omicron subvariants. Prior pre-Omicron SARS-CoV-2 virus infection or vaccination primed for robust antibody responses following Omicron infection but these remained primarily focussed against ancestral variants. Primary Omicron infection thus elicits a weak antibody response in children which is boosted after reinfection or vaccination. Cellular responses were robust and broadly equivalent in all groups, providing protection against severe disease irrespective of SARS-CoV-2 variant. Immunological imprinting is likely to act as an important determinant of long-term humoral immunity, the future clinical importance of which is unknown.",immunology,fuzzy,100,100 medRxiv,10.1101/2022.07.21.22277893,2022-07-21,https://medrxiv.org/cgi/content/short/2022.07.21.22277893,"STIMULATE-ICP: A pragmatic, multi-centre, cluster randomised trial of an integrated care pathway with a nested, Phase III, open label, adaptive platform randomised drug trial in individuals with Long COVID: a structured protocol",Denise Forshaw; Emma C Wall; Gordon Prescott; Hakim-Moulay Dehbi; Angela Green; Emily Attree; Lyth Hismeh; William D Strain; Michael G Crooks; Caroline Watkins; Chris Robson; Rajarshi Banerjee; Paula Lorgelly; Melissa Heightman; Amitava Banerjee; - the STIMULATE-ICP trial team,University of Central Lancashire; The Francis Crick Institute; University of Central Lancashire; University College London; Hull University Teaching Hospitals NHS Trust; STIMULATE-ICP study; STIMULATE-ICP study; University of Exeter; University of Hull; University of Central Lancashire; Living with; Perspectum Ltd; The University of Auckland; University College London Hospitals NHS Foundation Trust; University College London; -,"IntroductionLong COVID (LC), the persistent symptoms [≥]12 weeks following acute COVID-19, presents major threats to individual and public health across countries, affecting over 1.5 million people in the UK alone. Evidence-based interventions are urgently required and an integrated care pathway (ICP) approach in pragmatic trials, which include investigations, treatments and rehabilitation for LC, could provide scalable and generalisable solutions at pace. Methods and analysisThis is a pragmatic, multi-centre, cluster-randomised clinical trial of two components of an ICP (Coverscan, a multi-organ MRI, and Living with COVID Recovery, a digitally enabled rehabilitation platform) with a nested, Phase III, open label, platform randomised drug trial in individuals with LC. Cluster randomisation is at level of primary care networks so that ICP interventions are delivered as ""standard of care"" in that area. The drug trial randomisation is at individual level and initial arms are rivaroxaban, colchicine, famotidine/loratadine, compared with no drugs, with potential to add in further drug arms. The trial is being carried out in 6-10 NHS LC clinics in the UK and is evaluating the effectiveness of a pathway of care for adults with LC in reducing fatigue and other physical, psychological and functional outcomes (e.g. EQ-5D-5L, GAD-7, PHQ-9, WSAS, PDQ-5, CFQ, SF-12, MRC Dyspnoea score) at 3 months. The trial also includes an economic evaluation which will be described separately. @@ -1092,6 +1080,13 @@ ResultsThe study was launched on 1st May 2020 and closed to recruitment on 6th O ConclusionsThe COVIDENCE UK dataset represents a valuable resource containing granular information on factors influencing susceptibility to, and impacts of, COVID-19 in UK adults. Researchers wishing to access anonymised participant-level data should contacting the corresponding author for further information.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.06.20.22275994,2022-06-20,https://medrxiv.org/cgi/content/short/2022.06.20.22275994,Characterising patterns of COVID-19 and long COVID symptoms: Evidence from nine UK longitudinal studies,Ruth C E Bowyer; Charlotte Huggins; Renin Toms; Richard John Shaw; Bo Hou; Ellen J Thompson; Alex Siu Fung Kwong; Dylan M Williams; Milla Kibble; George B Ploubidis; Nicholas J Timpson; Jonathan A C Sterne; Nishi Chaturvedi; Claire J Steves; Kate Tilling; Richard J Silverwood,King's College London; University of Edinburgh; University of Bristol; University of Glasgow; Bradford Institute for Health Research; King's College London; University of Bristol; UCL; King's College London; University College London; University of Bristol; University of Bristol; University College London; King's College London; University of Bristol; University College London,"Multiple studies across global populations have established the primary symptoms characterising COVID-19 (Coronavirus Disease 2019) and long COVID. However, as symptoms may also occur in the absence of COVID-19, a lack of appropriate controls has often meant that specificity of symptoms to acute COVID-19 or long COVID could not be examined. We aimed to characterise patterns of COVID-19 and long COVID symptoms across nine UK longitudinal studies, totalling over 42,000 participants. Conducting latent class analyses separately in three groups ( no COVID-19, COVID-19 in last 12 weeks, COVID-19 > 12 weeks ago), the data did not support the presence of more than two distinct symptom patterns, representing high and low symptom burden, in each group. Comparing the high symptom burden classes between the COVID-19 in last 12 weeks and no COVID-19 groups we identified symptoms characteristic of acute COVID-19, including loss of taste and smell, fatigue, cough, shortness of breath and muscle pains or aches. Comparing the high symptom burden classes between the COVID-19 > 12 weeks ago and no COVID-19 groups we identified symptoms characteristic of long COVID, including fatigue, shortness of breath, muscle pain or aches, difficulty concentrating and chest tightness. The identified symptom patterns among individuals with COVID-19 > 12 weeks ago were strongly associated with self-reported length of time unable to function as normal due to COVID-19 symptoms, suggesting that the symptom pattern identified corresponds to long COVID. Building the evidence base regarding typical long COVID symptoms will improve diagnosis of this condition and the ability to elicit underlying biological mechanisms, leading to better patient access to treatment and services.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2022.06.18.22276437,2022-06-19,https://medrxiv.org/cgi/content/short/2022.06.18.22276437,A patient-centric characterization of systemic recovery from SARS-CoV-2 infection,Hélène Ruffieux; Aimee Hanson; Samantha Lodge; Nathan Lawler; Luke Whiley; Nicola Gray; Tui Nolan; Laura Bergamaschi; Federica Mescia; - CITIID-NIHR COVID BioResource Collaboration; Nathalie Kingston; John Bradley; Elaine Holmes; Julien Wist; Jeremy Nicholson; Paul Lyons; Kenneth Smith; Sylvia Richardson; Glenn Bantug; Christoph Hess,University of Cambridge; University of Cambridge; Murdoch University; Murdoch University; Murdoch University; Murdoch University; University of Cambridge; University of Cambridge; University of Cambridge; ; University of Cambridge; University of Cambridge; Murdoch University; Murdoch University; Murdoch University; University of Cambridge; University of Cambridge; University of Cambridge; University and University Hospital Basel; University of Cambridge,"The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data, covering a year post disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct ""systemic recovery"" profiles with specific progression and resolution of the inflammatory, immune, metabolic and clinical responses, over weeks to several months after infection. In particular, we found a strong intra-patient temporal covariation of innate immune cell numbers, kynurenine- and host lipid-metabolites, which suggested candidate immunometabolic pathways putatively influencing restoration of homeostasis, the risk of death and of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery on the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-systemic-recovery-prediction-app, designed to test our findings prospectively. + +Graphical abstract + +O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=""FIGDIR/small/22276437v1_ufig1.gif"" ALT=""Figure 1""> +View larger version (38K): +org.highwire.dtl.DTLVardef@12b0afborg.highwire.dtl.DTLVardef@ddf3b2org.highwire.dtl.DTLVardef@1aa670forg.highwire.dtl.DTLVardef@5415ec_HPS_FORMAT_FIGEXP M_FIG C_FIG",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2022.06.17.22276433,2022-06-17,https://medrxiv.org/cgi/content/short/2022.06.17.22276433,It hurts your heart: frontline healthcare worker experiences of moral injury during the COVID-19 pandemic,Siobhan Hegarty; Danielle Lamb; Sharon Stevelink; Rupa Bhundia; Rosalind Raine; Mary Jane Docherty; Hannah Rachel Scott; Anne Marie Rafferty; Victoria Williamson; Sarah Dorrington; Matthew hotopf; Reza Razavi; Neil Greenberg; Simon Wessely,King's College London; UCL; King's College London; King's College London; University College London; South London and Maudsley NHS Foundation Trust; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London,"BackgroundMoral injury is defined as the strong emotional and cognitive reactions following events which clash with someones moral code, values or expectations. During the COVID-19 pandemic, increased exposure to potentially morally injurious events (PMIEs) has placed healthcare workers (HCWs) at risk of moral injury. Yet little is known about the lived experience of cumulative PMIE exposure and how NHS staff respond to this. ObjectiveWe sought to rectify this knowledge gap by qualitatively exploring the lived experiences and perspectives of clinical frontline NHS staff who responded to COVID-19. @@ -1152,17 +1147,6 @@ ResultsThe first national lockdown was associated with reductions in all primary ConclusionMajor changes in primary and secondary HCU have been observed during the COVID-19 pandemic. Secondary HCU reduced more in those without LTCs and the ratio of utilisation between the most and least deprived increased for the majority of HCU measures. Overall primary HCU measures and secondary care HCU for some LTC groups had not returned to pre-pandemic levels by the end of the study.",epidemiology,fuzzy,100,92 medRxiv,10.1101/2022.06.09.22276196,2022-06-14,https://medrxiv.org/cgi/content/short/2022.06.09.22276196,Accelerated waning of the humoral response to SARS-CoV-2 vaccines in obesity,"Agatha A. van der Klaauw MD, PhD; Emily C. Horner BSc; Pehuen Pereyra-Gerber PhD; Utkarsh Agrawal PhD; William S. Foster BSc, MRes,; Sarah Spencer MD, BSc; Bensi Vergese BSc Hons.; Miriam E. Smith BSc PhD; Elana Henning B.Soc.Sc; Isobel D. Ramsay MA BM BCh; Jack A. Smith BSc MBiol; Stephane M. Guillaume BSc; Hayley J. Sharpe BSc, PhD; Iain M. Hay BSc, PhD; Sam Thompson BSc; Silvia Innocentin BSc., Ph.D; Lucy H Booth BSc; Chris Robertson Ph.D.; Colin McCowan Ph.D.; Thomas E Mulroney PhD; Martin J O'Reilly; Thevinya P Guragama; Lihinya P Guragama; Maria A Rust BSc; Alex Ferreira; Soraya Ebrahimi MSc; Lourdes Ceron-Gutierrez MSc.; Jacopo Scotucci MD; Barbara Kronsteiner Ph.D.; Susanna J. Dunachie MD., Ph.D.; Paul Klenerman MD., Ph.D.; - PITCH Consortium; Adrian J. Park MD PhD; Francesco Rubino MD.,; Hannah Stark BSc; Nathalie Kingson PhD; Rainer Doffinger PhD; Michelle A. Linterman BBmedSc (H; Nicholas J. Matheson MA BM BCh; Aziz Sheikh MD; I. Sadaf Farooqi MD, PhD; James E. Thaventhiran MD, PhD","University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-Medical Research Council (MRC) Institute of Meta; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR; Cambridge Institute for Therapeutic Immunology and Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, University of Cambridge, UK; Department of Medi; School of Medicine, University of St. Andrews; Immunology, Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR; University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-Medical Research Council (MRC) Institute of Meta; University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-Medical Research Council (MRC) Institute of Meta; University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-Medical Research Council (MRC) Institute of Meta; 1. Cambridge Institute for Therapeutic Immunology and Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, University of Cambridge, UK 2. Department of; 1. Cambridge Institute for Therapeutic Immunology and Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, University of Cambridge, UK 2. Department of; Immunology, Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT; Signalling, Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT; Signalling, Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT; Cambridge Institute for Medical Research, Cambridge UK.; Flow cytometry core, Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT; Babraham Institute, Babraham Research Campus, Cambridge; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR; Department of Mathematics and Statistics, University of Strathclyde; School of Medicine, University of St. Andrews; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR; NIHR Cambridge Clinical Research Facility, Departments of Immunology and Clinical Biochemistry; NIHR Cambridge Clinical Research Facility, Departments of Immunology and Clinical Biochemistry; University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-Medical Research Council (MRC) Institute of Meta; Nuffield Department of Clinical Medicine, University of Oxford; Nuffield Department of Clinical Medicine, University of Oxford; Nuffield Department of Clinical Medicine, University of Oxford; ; Cambridge University Hospitals NHS Foundation Trust, Department of Clinical Biochemistry, Cambridge, United Kingdom; Kings College London, Department of Diabetes, School of Life Course Science, London; NIHR BioResource; NIHR BioResource; NIHR Cambridge Clinical Research Facility, Departments of Immunology, Clinical Biochemistry; Immunology, Babraham Institute, Babraham Research Campus, Cambridge CB22 3AT; 1. Cambridge Institute for Therapeutic Immunology and Infectious Disease (CITIID), Jeffrey Cheah Biomedical Centre, University of Cambridge, UK 2. Department of; Usher Institute, University of Edinburgh; University of Cambridge Metabolic Research Laboratories and NIHR Cambridge Biomedical Research Centre, Wellcome-Medical Research Council (MRC) Institute of Meta; Medical Research Council Toxicology Unit, University of Cambridge, Gleeson Building, Tennis Court Road, Cambridge, CB2 1QR","Obesity is associated with an increased risk of severe Covid-19. However, the effectiveness of SARS-CoV-2 vaccines in people with obesity is unknown. Here we studied the relationship between body mass index (BMI), hospitalization and mortality due to Covid-19 amongst 3.5 million people in Scotland. Vaccinated people with severe obesity (BMI>40 kg/m2) were significantly more likely to experience hospitalization or death from Covid-19. Excess risk increased with time since vaccination. To investigate the underlying mechanisms, we conducted a prospective longitudinal study of the immune response in a clinical cohort of vaccinated people with severe obesity. Compared with normal weight people, six months after their second vaccine dose, significantly more people with severe obesity had unquantifiable titres of neutralizing antibody against authentic SARS-CoV-2 virus, reduced frequencies of antigen-experienced SARS-CoV-2 Spike-binding B cells, and a dissociation between anti-Spike antibody levels and neutralizing capacity. Neutralizing capacity was restored by a third dose of vaccine, but again declined more rapidly in people with severe obesity. We demonstrate that waning of SARS-CoV-2 vaccine-induced humoral immunity is accelerated in people with severe obesity and associated with increased hospitalization and mortality from breakthrough infections. Given the prevalence of obesity, our findings have significant implications for global public health.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2022.06.08.22276134,2022-06-14,https://medrxiv.org/cgi/content/short/2022.06.08.22276134,Implementation of a digital early warning score (NEWS2) in a cardiac specialist and general hospital settings in the COVID-19 pandemic: A qualitative study.,Baneen Alhmoud; Timothy Bonicci; Riyaz Patel; Daniel Melley; Louise Hicks; Amitava Banerjee,"University College London, University College London Hospital, Barts Health Trust.; University College London, University College London Hospital; University College London, University College London Hospital.; Barts Health Trust; Barts Health Trust; University College London, University College London Hospital, Barts Health Trust.","ObjectivesTo evaluate implementation of EHR-integrated NEWS2 in a cardiac care setting and a general hospital setting in the COVID-19 pandemic. - -DesignThematic analysis of qualitative semi-structured interviews with purposefully sampled nurses and managers, as well as online surveys. - -SettingsSpecialist cardiac hospital (St Bartholomews Hospital) and General teaching hospital (University College London Hospital). - -ParticipantsEleven nurses and managers from cardiology, cardiac surgery, oncology, and intensive care wards (St Bartholomews) and medical, haematology and intensive care wards (UCLH) were interviewed and sixty-seven were surveyed online. - -ResultsThree main themes emerged: (i) Implementing NEWS2 challenges and supports; (ii) Value of NEWS2 to alarm, escalate, particularly during the pandemic; and (iii) Digitalisation: EHR integration and automation. The value of NEWS2 was partly positive in escalation, yet there were concerns by nurses who undervalued NEWS2 particularly in cardiac care. Challenges, like clinicians behaviours, lack of resources and training and the perception of NEWS2 value, limit the success of this implementation. Changes in guidelines in the pandemic have led to overlooking NEWS2. EHR integration and automated monitoring are improvement solutions that are not fully employed yet. - -ConclusionWhether in specialist or general medical settings, the health professionals implementing EWS in healthcare face cultural and systems related challenges to adopting NEWS2 and digital solutions. The validity of NEWS2 in specialised settings and complex conditions is not yet apparent and requires comprehensive validation. EHRs integration and automation are powerful tools to facilitate NEWS2 if its principles are reviewed and rectified, and resources and training are accessible. Further examination of implementation from the cultural and automation domains are needed.",health informatics,fuzzy,100,100 medRxiv,10.1101/2022.06.13.22276316,2022-06-13,https://medrxiv.org/cgi/content/short/2022.06.13.22276316,Patterns of Reported Infection and Reinfection of SARS-CoV-2 in England,Matt J Keeling,University of Warwick,"One of the key features of any infectious disease is whether infection generates long-lasting immunity or whether repeated reinfection is common. In the former, the long-term dynamics are driven by the birth of susceptible individuals while in the latter the dynamics are governed by the speed of waning immunity. Between these two extremes a range of scenarios is possible. During the early waves of SARS-CoV-2, the underlying paradigm was for long-lasting immunity, but more recent data and in particular the 2022 Omicron waves have shown that reinfection can be relatively common. Here we investigate reported SARS-CoV-2 cases in England, partitioning the data into four main waves, and consider the temporal distribution of first and second reports of infection. We show that a simple low-dimensional statistical model of random (but scaled) reinfection captures much of the observed dynamics, with the value of this scaling, k, providing information of underlying epidemiological patterns. We conclude that there is considerable heterogeneity in risk of reporting reinfection by wave, age-group and location. The high levels of reinfection in the Omicron wave (we estimate that 18% of all Omicron cases had been previously infected, although not necessarily previously reported infection) point to reinfection events dominating future COVID-19 dynamics.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.06.12.22276307,2022-06-13,https://medrxiv.org/cgi/content/short/2022.06.12.22276307,"Occupation, Worker Vulnerability, and COVID-19 Vaccination Uptake: Analysis of the Virus Watch prospective cohort study",Sarah Beale; Rachel Burns; Isobel Braithwaite; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Susan J Hoskins; Jana Kovar; Annalan Mathew Dwight Navaratnam; Parth Patel; Alexei Yavlinsky; Martie J Van Tongeren; Robert W Aldridge; Andrew Hayward,University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University of Manchester; University College London; University College London,"BackgroundOccupational disparities in COVID-19 vaccine uptake can impact the effectiveness of vaccination programmes and introduce particular risk for vulnerable workers and those with high workplace exposure. This study aimed to investigate COVID-19 vaccine uptake by occupation, including for vulnerable groups and by occupational exposure status. @@ -1408,13 +1392,6 @@ What is the key question?Can sustained patient interaction and improved patient What is the bottom line?Participants continue to use the LenusCOPD patient app, with an average of 3-3.5 interactions per person per week sustained >1-year post-onboarding. COPD- related hospital admissions and occupied bed days were reduced following LenusCOPD onboarding in participants with a history of a severe exacerbation in the previous year, with a median time to readmission of 380 days compared with 50 days in a contemporary matched control patient cohort. Why read on?Feasibility and utility results support scale-up adoption of these digital tools, to support optimised co-management of COPD and other long-term conditions within a continuous implementation-evaluation framework. This will establish a test-bed infrastructure for additional innovations including artificial intelligence-insights for MDT decision support.",respiratory medicine,fuzzy,100,91 -medRxiv,10.1101/2022.04.03.22272610,2022-04-04,https://medrxiv.org/cgi/content/short/2022.04.03.22272610,Cardiac impairment in Long Covid 1-year post-SARS-CoV-2 infection,Adriana Roca-Fernandez; Malgorzata Wamil; Alison Telford; Valentina Carapella; Alessandra Borlotti; David Monteiro; Helena Thomaides-Brears; Matthew D Kelly; Andrea Dennis; Rajarshi Banerjee; Matthew Robson; Michael Brady; Gregory Lip; Sacha Bull; Melissa J Heightman; Ntobeko Ntusi; Amitava Banerjee,"Perspectum Diagnostics; Great Western Hospital Foundation NHS Trust, Swindon, UK; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; University of Liverpool; Royal Berkshire Hospital, Reading; UCLH; University of Cape Town, Cape Town, South Africa; University College London","BackgroundLong Covid is associated with multiple symptoms and impairment in multiple organs. Cardiac impairment has been reported to varying degrees by varying methodologies in cross-sectional studies. Using cardiac magnetic resonance (CMR), we investigated the 12-month trajectory of cardiac impairment in individuals with Long Covid. - -Methods534 individuals with Long Covid underwent baseline CMR (T1 and T2 mapping, cardiac mass, volumes, function, and strain) and multi-organ MRI at 6 months (IQR 4.3,7.3) since first post-COVID-19 symptoms and 330 were rescanned at 12.6 (IQR 11.4, 14.2) months if abnormal findings were reported at baseline. Symptoms, standardised questionnaires, and blood samples were collected at both timepoints. Cardiac impairment was defined as one or more of: low left or right ventricular ejection fraction (LVEF and RVEF), high left or right ventricular end diastolic volume (LVEDV and RVEDV), low 3D left ventricular global longitudinal strain (GLS), or elevated native T1 in [≥]3 cardiac segments. A significant change over time was reported by comparison with 92 healthy controls. - -ResultsThe technical success of this multiorgan assessment in non-acute settings was 99.1% at baseline, and 98.3% at follow up, with 99.6% and 98.8% for CMR respectively. Of individuals with Long Covid, 102/534 [19%] had cardiac impairment at baseline; 71/102 had complete paired data at 12 months. Of those, 58% presented with ongoing cardiac impairment at 12 months. High sensitivity cardiac troponin I and B-type natriuretic peptide were not predictive of CMR findings, symptoms, or clinical outcomes. At baseline, low LVEF, high RVEDV and low GLS were associated with cardiac impairment. Low LVEF at baseline was associated with persistent cardiac impairment at 12 months. - -ConclusionCardiac impairment, other than myocarditis, is present in 1 in 5 individuals with Long Covid at 6 months, persisting in over half of those at 12 months. Cardiac-related blood biomarkers are unable to identify cardiac impairment in Long COVID. Subtypes of disease (based on symptoms, examination, and investigations) and predictive biomarkers are yet to be established. Interventional trials with pre-specified subgroup analyses are required to inform therapeutic options.",cardiovascular medicine,fuzzy,100,100 medRxiv,10.1101/2022.03.29.22272997,2022-04-04,https://medrxiv.org/cgi/content/short/2022.03.29.22272997,Glasses and risk of COVID-19 transmission - analysis of the Virus Watch Community Cohort study.,Annalan Mathew Dwight Navaratnam; Chris O'Callaghan; Sarah Beale; Vincent Nguyen; Anna Aryee; Isobel Braithwaite; Thomas E Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Susan Hoskins; Jana Kovar; Parth Patel; Madhumita Shrotri; Sophie Weber; Alexei Yavlinsky; Robert W Aldridge; Andrew C Hayward,University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London,"BackgroundRespiratory viruses, including SARS-CoV-2, can infect the eyes or pass into the nose via the nasolacrimal duct. The importance of transmission via the eyes is unknown but might plausibly be reduced in those who wear glasses. Previous studies have mainly focussed on protective eyewear in healthcare settings. MethodsParticipants from the Virus Watch prospective community cohort study in England and Wales responded to a questionnaire on the use of glasses and contact lenses. This included frequency of use, purpose, and likelihood of wearing a mask with glasses. Infection was confirmed through data linkage with Second Generation Surveillance System (Pillar 1 and Pillar 2), weekly questionnaires to self-report positive polymerase chain reaction or lateral flow results, and, for a subgroup, monthly capillary blood testing for antibodies (nucleocapsid and spike). A multivariable logistic regression model, controlling for age, sex, income and occupation, was used to identify odds of infection depending on the frequency and purpose of using glasses or contact lenses. @@ -1576,13 +1553,6 @@ Added value of this studyWe assessed multiple components of the UK vaccination c Implications of all the available evidenceOur data confirm that first dose BNT162b2 vaccination in CYP reduces risk of infection by SARS-CoV-2 variants, with generally local and brief side-effects. If infected after vaccination, COVID-19 is milder, if manifest at all. The study aims to contribute quantitative evidence to the risk-benefit evaluation of vaccination in CYP to inform discussion regarding rationale for their vaccination and the designing of national immunisation campaigns for this age group; and applies citizen-science approaches in the conduct of epidemiological surveillance and data collection in the UK community. Importantly, this study was conducted during Delta and Omicron predominance in UK; specificity of vaccine efficacy to variants is also illustrated; and results may not be generalizable to future SARS-CoV-2 strains.",epidemiology,fuzzy,94,100 -medRxiv,10.1101/2022.03.10.22272081,2022-03-12,https://medrxiv.org/cgi/content/short/2022.03.10.22272081,Interstitial lung damage following COVID-19 hospitalisation: an interim analysis of the UKILD Post-COVID study.,I Stewart; J Jacob; PM George; PL Molyneaux; JC Porter; RJ Allen; JK Baillie; SL Barratt; P Beirne; SM Bianchi; JF Blaikley; J Chalmers; RC Chambers; N Chadhuri; C Coleman; G Collier; EK Denneny; A Docherty; O Elneima; RA Evans; L Fabbri; MA Gibbons; FV Gleeson; B Gooptu; NJ Greening; B Guillen Guio; IP Hall; NA Hanley; V Harris; E Harrison; M Heightman; TE Hillman; A Horsley; L Houchen-Wolloff; I Jarrold; SR Johnson; MG Jones; F Khan; R Lawson; OC Leavy; N Lone; M Marks; H McAuley; P Mehta; E Omer; D Parekh; K Piper Hanley; M Plate; J Pearl; K Poinasamy; JK Quint; B Raman; M Richardson; P Rivera-Ortega; L Saunders; R Saunders; MG Semple; M Sereno; A Shikotra; AJ Simpson; A Singapuri; DJF Smith; M Spears; LG Spencer; S Stanel; D Thickett; AAR Thompson; M Thorpe; R Thwaites; SLF Walsh; S Walker; ND Weatherley; M Weeks; JM Wild; DG Wootton; CE Brightling; LP Ho; LV Wain; RG Jenkins,"National Heart & Lung Institute, Imperial College London; Respiratory Medicine, University College London; Royal Brompton and Harefield NHS Foundation Trust; National Heart & Lung Institute, Imperial College London; University College London; University of Leicester; University of Edinburgh; North Bristol NHS Trust; Leeds Teaching Hospitals & University of Leeds; Sheffield Teaching Hospitals NHS Foundation Trust; University of Manchester; University of Dundee; Respiratory Medicine, University College London; University of Manchester; University of Nottingham; University of Sheffield; University College London; University of Edinburgh; University Hospitals of Leicester NHS Trust; University Hospitals of Leicester NHS Trust; National Heart & Lung Institute, Imperial College London; Royal Devon and Exeter NHS Foundation Trust; Oxford University Hospitals NHS Foundation Trust; University of Leicester; University of Leicester; University of Leicester; University of Nottingham; University of Manchester; University Hospitals of Leicester NHS Trust; University of Edinburgh; University College London Hospital; University College London Hospital; University of Manchester; University Hospitals of Leicester NHS Trust; Asthma UK British Lung Foundation; University of Nottingham; Faculty of Medicine, University of Southampton; University of Nottingham; Sheffield Teaching Hospitals NHS Foundation Trust; University of Leicester; Usher Institute, University of Edinburgh; University College London Hospital; University of Leicester; University College London Hospital; University of Leicester; University of Birmingham; University of Manchester; University College London Hospital; University of Leicester; British Lung Foundation; National Heart & Lung Institute, Imperial College London; University of Oxford; University of Leicester; University of Manchester; University of Sheffield; University of Leicester; Liverpool University; University of Leicester; University Hospitals of Leicester NHS Trust; Newcastle University; University of Leicester; Royal Brompton and Harefield NHS Foundation Trust; Perth Royal Infirmary, NHS Tayside; Liverpool University Hospitals NHS Foundation Trust; University of Manchester; University of Birmingham; University of Sheffield; University of Edinburgh; National Heart & Lung Institute, Imperial College London; National Heart & Lung Institute, Imperial College London; Sheffield Teaching NHS Foundation Trust; Sheffield Teaching NHS Foundation Trust; National Heart & Lung Institute, Imperial College London; Sheffield Teaching NHS Foundation Trust; University of Liverpool; University Hospitals of Leicester NHS Trust; University of Oxford; University of Leicester; National Heart & Lung Institute, Imperial College London","IntroductionShared characteristics between COVID-19 and pulmonary fibrosis, including symptoms, genetic architecture, and circulating biomarkers, suggests interstitial lung disease (ILD) development may be associated with SARS-CoV-2 infection. - -MethodsThe UKILD Post-COVID study planned interim analysis was designed to stratify risk groups and estimate the prevalence of Post-COVID Interstitial Lung Damage (ILDam) using the Post-HOSPitalisation COVID-19 (PHOSP-COVID) Study. Demographics, radiological patterns and missing data were assessed descriptively. Bayes binomial regression was used to estimate the risk ratio of persistent lung damage >10% involvement in linked, clinically indicated CT scans. Indexing thresholds of percent predicted DLco, chest X-ray findings and severity of admission were used to generate risk strata. Number of cases within strata were used to estimate the amount of suspected Post-COVID ILDam. - -ResultsA total 3702 people were included in the UKILD interim cohort, 2406 completed an early follow-up research visit within 240 days of discharge and 1296 had follow-up through routine clinical review. We linked the cohort to 87 clinically indicated CTs with visually scored radiological patterns (median 119 days from discharge; interquartile range 83 to 155, max 240), of which 74 people had ILDam. ILDam was associated with abnormal chest X-ray (RR 1.21 95%CrI 1.05; 1.40), percent predicted DLco<80% (RR 1.25 95%CrI 1.00; 1.56) and severe admission (RR 1.27 95%CrI 1.07; 1.55). A risk index based on these features suggested 6.9% of the interim cohort had moderate to very-high risk of Post-COVID ILDam. Comparable radiological patterns were observed in repeat scans >90 days in a subset of participants. - -ConclusionThese interim data highlight that ILDam was not uncommon in clinically indicated thoracic CT up to 8 months following SARS-CoV-2 hospitalisation. Whether the ILDam will progress to ILD is currently unknown, however health services should radiologically and physiologically monitor individuals who have Post-COVID ILDam risk factors.",respiratory medicine,fuzzy,91,100 medRxiv,10.1101/2022.03.09.22272098,2022-03-12,https://medrxiv.org/cgi/content/short/2022.03.09.22272098,"Duration of vaccine effectiveness against SARS-CoV2 infection, hospitalisation, and death in residents and staff of Long-Term Care Facilities (VIVALDI): a prospective cohort study, England, Dec 2020-Dec 2021",Madhumita Shrotri; Maria Krutikov; Hadjer Nacer-Laidi; Borscha Azmi; Tom Palmer; Rebecca Giddings; Chris Fuller; Aidan Irwin-Singer; Verity Baynton; Gokhan Tut; Paul Moss; Andrew Hayward; Andrew Copas; Laura Shallcross,"University College London; University College London; University College London; University College London; University College London; University College London; University College London; UK Government Department of Health & Social Care; UK Government Department of Health & Social Care; University of Birmingham, Medical School; University of Birmingham; UCL; University College London; UCL","BackgroundLong-term care facilities (LTCF) have been prioritised for vaccination, but data on potential waning of vaccine effectiveness (VE) and the impact of booster doses in this vulnerable population remains scarce. MethodsWe included residents and staff from 331 LTCFs enrolled in VIVALDI (ISRCTN 14447421), who underwent routine PCR testing between Dec 8, 2020 - Dec 11, 2021 in a Cox proportional hazards regression, estimating VE against SARS-CoV2 infection, COVID-19-related hospitalisation, and COVID-19-related death after 1-3 vaccine doses, stratifying by previous SARS-CoV2 exposure. @@ -1708,6 +1678,21 @@ ResultsFrom 102,174 valid tests in round 17, weighted prevalence of swab positiv Within round 17, prevalence was decreasing overall (R=0.95, 95% CrI, 0.93, 0.97) but increasing in children aged 5 to 17 years (R=1.13, 95% CrI, 1.09, 1.18). Those 75 years and older had a swab-positivity prevalence of 2.46% (95% CI, 2.16%, 2.80%) reflecting a high level of infection among a highly vulnerable group. Among the 3,613 swab-positive individuals reporting whether or not they had had previous infection, 2,334 (64.6%) reported previous confirmed COVID-19. Of these, 64.4% reported a positive test from 1 to 30 days before their swab date. Risks of infection were increased among essential/key workers (other than healthcare or care home workers) with mutually adjusted Odds Ratio (OR) of 1.15 (95% CI, 1.05, 1.26), people living in large compared to single-person households (6+ household size OR 1.73; 95% CI, 1.44, 2.08), those living in urban vs rural areas (OR 1.24, 95% CI, 1.13, 1.35) and those living in the most vs least deprived areas (OR 1.34, 95% CI, 1.20, 1.49). ConclusionsWe observed unprecedented levels of infection with SARS-CoV-2 in England in January 2022, an almost complete replacement of Delta by Omicron, and evidence for a growth advantage for BA.2 compared to BA.1. The increase in the prevalence of infection with Omicron among children (aged 5 to 17 years) during January 2022 could pose a risk to adults, despite the current trend for prevalence in adults to decline. (Funded by the Department of Health and Social Care in England.)",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2022.02.04.22270479,2022-02-06,https://medrxiv.org/cgi/content/short/2022.02.04.22270479,Comparative effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections: A time-varying cohort analysis using trial emulation in the Virus Watch community cohort,Vincent Nguyen; Alexei Yavlinsky; Sarah Beale; Susan J Hoskins; Vasileios J Lampos; Isobel Braithwaite; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan Mathew Dwight Navaratnam; Parth Patel; Madhumita Shrotri; Sophie Weber; Andrew Hayward; Robert W Aldridge,"University College London; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London, London School of Hygiene &Tropical Medicine; UCL, London School of Hygiene & Tropical Medicine; University College London; University College London; University College London; University College London; Univeristy College London; University College London; University College London; University College London","ImportanceThe Omicron (B.1.1.529) variant has increased SARs-CoV-2 infections in double vaccinated individuals globally, particularly in ChAdOx1 recipients. To tackle rising infections, the UK accelerated booster vaccination programmes used mRNA vaccines irrespective of an individuals primary course vaccine type with booster doses rolled out according to clinical priority. There is limited understanding of the effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections and how time-varying confounders can impact the evaluations comparing different vaccines as primary courses for mRNA boosters. + +ObjectiveTo evaluate the comparative effectiveness of ChAdOx1 versus BNT162b2 as primary doses against SARs-CoV-2 in booster vaccine recipients whilst accounting for time-varying confounders. + +DesignTrial emulation was used to reduce time-varying confounding-by-indication driven by prioritising booster vaccines based upon age, vulnerability and exposure status e.g. healthcare worker. Trial emulation was conducted by meta-analysing eight cohort results whose booster vaccinations were staggered between 16/09/2021 to 05/01/2022 and followed until 23/01/2022. Time from booster vaccination until SARS-CoV-2 infection, loss of follow-up or end-of-study was modelled using Cox proportional hazards models for each cohort and adjusted for age, sex, minority ethnic status, clinically vulnerability, and deprivation. + +SettingProspective observational study using the Virus Watch community cohort in England and Wales. + +ParticipantsPeople over the age of 18 years who had their booster vaccination between 16/09/2021 to 05/01/2022 without prior natural immunity. + +ExposuresChAdOx1 versus BNT162b2 as a primary dose, and an mRNA booster vaccine. + +ResultsAcross eight cohorts, 19,692 mRNA vaccine boosted participants were analysed with 12,036 ChAdOx1 and 7,656 BNT162b2 primary courses with a median follow-up time of 73 days (IQR:54-90). Median age, clinical vulnerability status and infection rates fluctuate through time. 7.2% (n=864) of boosted adults with ChAdOx1 primary course experienced a SARS-CoV-2 infection compared to 7.6% (n=582) of those with BNT162b2 primary course during follow-up. The pooled adjusted hazard ratio was 0.99 [95%CI:0.88-1.11], demonstrating no difference between the incidence of SARs-CoV-2 infections based upon the primary vaccine course. + +Conclusion and RelevanceIn mRNA boosted individuals, we found no difference in protection comparing those with a primary course of BNT162b2 to those with aChAdOx1 primary course. This contrasts with pre-booster findings where previous research shows greater effectiveness of BNT162b2 than ChAdOx1 in preventing infection.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.02.01.22270269,2022-02-02,https://medrxiv.org/cgi/content/short/2022.02.01.22270269,Nucleocapsid and spike antibody responses post virologically confirmed SARS-CoV-2 infection: An observational analysis in the Virus Watch community cohort,Annalan Mathew Dwight Navaratnam; Madhumita Shrotri; Vincent Nguyen; Isobel Braithwaite; Sarah Beale; Thomas E Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Susan Hoskins; Jana Kovar; Parth Patel; Alexei Yavlinsky; Anna Aryee; Alison Rodger; Andrew C Hayward; Robert W Aldridge,University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London,"IntroductionSeroprevalence studies can provide a measure of cumulative incidence of SARS-CoV-2 infection, but a better understanding of antibody dynamics following infection is needed to assess longevity of detectability. Infection is characterised by detection of spike (anti-S) and nucleocapsid (anti-N) antibodies, whereas vaccination only stimulates anti-S. Consequently, in the context of a highly vaccinated population, presence of anti-N can be used as a marker of previous infection but waning over time may limit its use. MethodsAdults aged [≥]18 years old, from households enrolled in the Virus Watch prospective community cohort study in England and Wales, provided monthly capillary blood samples which were tested for anti-S and anti-N. Participants self-reported vaccination dates and past medical history. Prior polymerase chain reaction (PCR) swabs were obtained through Second Generation Surveillance System (SGSS) linkage data. Primary outcome variables were seropositivity (antibodies at or above the manufacturers cut-off for positivity) and total anti-N and anti-S levels after PCR confirmed infection. Outcomes were analysed by days since infection, self-reported demographic and clinical factors. @@ -1806,6 +1791,7 @@ medRxiv,10.1101/2022.01.16.22269146,2022-01-17,https://medrxiv.org/cgi/content/s Method and FindingsThis multi-phase, prospective mixed-methods study took place between April and August 2021 in the United Kingdom (UK). A conceptual framework and initial item pool were developed from published systematic reviews. Further concept elicitation and content validation was undertaken with adults with lived experience (n = 13) and clinicians (n = 10), and face validity was confirmed by the Therapies for Long COVID Study Patient and Public Involvement group (n = 25). The draft SBQ-LC was field tested by adults with self-reported Long COVID recruited via social media and international Long COVID support groups (n = 274). Thematic analysis of interview and survey transcripts established content validity and informed construction of the draft questionnaire. Rasch analysis of field test data guided item and scale refinement and provided evidence of the final SBQ-LCs measurement properties. The Rasch-derived SBQ-LC is composed of 17 independent scales with promising psychometric properties. Respondents rate symptom burden during the past 7-days using a dichotomous response or 4-point rating scale. Each scale provides coverage of a different symptom domain and returns a summed raw score that may be converted to a linear (0 - 100) score. Higher scores represent higher symptom burden. ConclusionsThe SBQ-LC is a comprehensive patient-reported assessment of Long COVID symptom burden developed using modern psychometric methods. It measures symptoms of Long COVID important to individuals with lived experience and may be used to evaluate the impact of interventions and inform best practice in clinical management.",health informatics,fuzzy,100,100 +medRxiv,10.1101/2022.01.13.22268948,2022-01-14,https://medrxiv.org/cgi/content/short/2022.01.13.22268948,Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: Insights from Rapid COVID-19 Diagnosis by Adversarial Learning,Jenny Yang; Andrew AS Soltan; Yang Yang; David A Clifton,The University of Oxford; University of Oxford; The University of Oxford; The University of Oxford,"Machine learning is becoming increasingly prominent in healthcare. Although its benefits are clear, growing attention is being given to how machine learning may exacerbate existing biases and disparities. In this study, we introduce an adversarial training framework that is capable of mitigating biases that may have been acquired through data collection or magnified during model development. For example, if one class is over-presented or errors/inconsistencies in practice are reflected in the training data, then a model can be biased by these. To evaluate our adversarial training framework, we used the statistical definition of equalized odds. We evaluated our model for the task of rapidly predicting COVID-19 for patients presenting to hospital emergency departments, and aimed to mitigate regional (hospital) and ethnic biases present. We trained our framework on a large, real-world COVID-19 dataset and demonstrated that adversarial training demonstrably improves outcome fairness (with respect to equalized odds), while still achieving clinically-effective screening performances (NPV>0.98). We compared our method to the benchmark set by related previous work, and performed prospective and external validation on four independent hospital cohorts. Our method can be generalized to any outcomes, models, and definitions of fairness.",health informatics,fuzzy,100,100 medRxiv,10.1101/2022.01.05.21268323,2022-01-06,https://medrxiv.org/cgi/content/short/2022.01.05.21268323,Lineage replacement and evolution captured by the United Kingdom Covid Infection Survey,Katrina A Lythgoe; Tanya Golubchik; Matthew Hall; Thomas House; Roberto Cahuantzi; George MacIntyre-Cockett; Helen Fryer; Laura Thomson; Anel Nurtay; Mahan Ghafari; David Buck; Angie Green; Amy Trebes; Paolo Piazza; Lorne J Lonie; Ruth Studley; Emma Rourke; Darren Smith; Matthew Bashton; Andrew Nelson; Matthew Crown; Clare McCann; Gregory R Young; Rui Andre Nunes de Santos; Zack Richards; Adnan Tariq; - Wellcome Sanger Institute COVID-19 Surveillance Team; - COVID-19 Infection Survey Group; - The COVID-19 Genomics UK (COG-UK) consortium; Christophe Fraser; Ian Diamond; Jeff Barrett; Ann Sarah Walker; David Bonsall,University of Oxford; University of Oxford; University of Oxford; University of Manchester; University of Manchester; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Northumbria University; Wellcome Sanger Institute; Office for National Statistics; ; University of Oxford; Office for National Statistics; Wellcome Sanger Institute; University of Oxford; University of Oxford,"The Office for National Statistics COVID-19 Infection Survey (ONS-CIS) is the largest surveillance study of SARS-CoV-2 positivity in the community, and collected data on the United Kingdom (UK) epidemic from April 2020 until March 2023 before being paused. Here, we report on the epidemiological and evolutionary dynamics of SARS-CoV-2 determined by analysing the sequenced samples collected by the ONS-CIS during this period. We observed a series of sweeps or partial sweeps, with each sweeping lineage having a distinct growth advantage compared to their predecessors. The sweeps also generated an alternating pattern in which most samples had either S-gene target failure (SGTF) or non- SGTF over time. Evolution was characterised by steadily increasing divergence and diversity within lineages, but with step increases in divergence associated with each sweeping major lineage. This led to a faster overall rate of evolution when measured at the between-lineage level compared to within lineages, and fluctuating levels of diversity. These observations highlight the value of viral sequencing integrated into community surveillance studies to monitor the viral epidemiology and evolution of SARS-CoV-2, and potentially other pathogens, particularly in the current phase of the pandemic with routine RT-PCR testing now ended in the community.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2022.01.01.21268131,2022-01-05,https://medrxiv.org/cgi/content/short/2022.01.01.21268131,Bayesian Estimation of real-time Epidemic Growth Rates using Gaussian Processes: local dynamics of SARS-CoV-2 in England,Laura Marcela Guzman Rincon; Edward M Hill; Louise Dyson; Michael J Tildesley; Matt J Keeling,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"Quantitative assessments of the recent state of an epidemic and short-term projections into the near future are key public health tools that have substantial policy impacts, helping to determine if existing control measures are sufficient or need to be strengthened. Key to these quantitative assessments is the ability to rapidly and robustly measure the speed with which the epidemic is growing or decaying. Frequently, epidemiological trends are addressed in terms of the (time-varying) reproductive number R. Here, we take a more parsimonious approach and calculate the exponential growth rate, r, using a Bayesian hierarchical model to fit a Gaussian process to the epidemiological data. We show how the method can be employed when only case data from positive tests are available, and the improvement gained by including the total number of tests as a measure of heterogeneous testing effort. Although the methods are generic, we apply them to SARS-CoV-2 cases and testing in England, making use of the available high-resolution spatio-temporal data to determine long-term patterns of national growth, highlight regional growth and spatial heterogeneity.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.12.31.21268587,2022-01-02,https://medrxiv.org/cgi/content/short/2021.12.31.21268587,"The adverse impact of COVID-19 pandemic on cardiovascular disease prevention and management in England, Scotland and Wales: A population-scale descriptive analysis of trends in medication data",Caroline E Dale; Rohan Takhar; Ray Carragher; Fatemeh Torabi; Michalis Katsoulis; Stephen Duffield; Seamus Kent; Tanja Mueller; Amanj Kurdi; Stuart McTaggart; Hoda Abbasizanjani; Sam Hollings; Andrew Scourfield; Ronan Lyons; Rowena Griffiths; Jane Lyons; Gareth Davies; Dan Harris; Alex Handy; Mehrdad Alizadeh Mizani; Chris Tomlinson; Mark Ashworth; Spiros Denaxas; Amitava Banerjee; Jonathan Sterne; Kate Lovibond; Paul Brown; Ian Bullard; Rouven Priedon; Mamas A Mamas; Ann Slee; Paula Lorgelly; Munir Pirmohamed; Kamlesh Khunti; Naveed Sattar; Andrew Morris; Cathie Sudlow; Ashley Akbari; Marion Bennie; Reecha Sofat; - CVD-COVID-UK Consortium,"Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde; Swansea University; Institute of Health Informatics Research, University College London; NICE; NICE; University of Strathclyde; Strathclyde Institute of Pharmacy & Biomedical Sciences, University of Strathclyde; Public Health Scotland; Swansea University; NHS Digital, Leeds; UCLH NHS Foundation Trust; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; Institute of Health Informatics Research, University College London; King's College London; Institute of Health Informatics Research, University College London; University College London; University of Bristol; Royal College of Physicians; NHS Digital, Leeds; NHS Digital; British Heart Foundation Data Science Centre, Health Data Research UK, London; Keele University; NHSX; Department of Applied Health Research, University College London; University of Liverpool; University of Leicester; University of Glasgow; Health Data Research UK; British Heart Foundation Data Science Centre, Health Data Research UK, London; Swansea University; University of Strathclyde; Institute of Health Informatics Research, University College London; ","ObjectivesTo estimate the impact of the COVID-19 pandemic on cardiovascular disease (CVD) and CVD management using routinely collected medication data as a proxy. @@ -1837,9 +1823,6 @@ RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, Added value of this studyWe used national databases of COVID-19 case surveillance, laboratory testing, and vaccination from Brazil to investigate effectiveness of CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2 among individuals with a prior, laboratory-confirmed SARS-CoV-2 infection. We matched >22,000 RT-PCR-confirmed re-infections with >145,000 RT-PCR-negative controls using a test-negative design. All four vaccines were effective against symptomatic SARS-CoV-2 infections, with effectiveness from 14 days after series completion ranging from 39-65%. For vaccines with two-dose regimens, the second dose provided significantly increased effectiveness compared with one dose. Effectiveness against COVID-19-associated hospitalization or death from 14 days after series completion was >80% for CoronaVac, ChAdOx1and BNT162b2. Implications of all the available evidenceWe find evidence that four vaccines, using three different platforms, all provide protection to previously infected individuals against symptomatic SARS-CoV-2 infection and severe outcomes, with a second dose conferring significant additional benefits. These results support the provision of a full vaccine series among individuals with prior SARS-CoV-2 infection.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2021.12.23.21268276,2021-12-25,https://medrxiv.org/cgi/content/short/2021.12.23.21268276,Risk of myocarditis following sequential COVID-19 vaccinations by age and sex,Martina Patone; Winnie Xue Mei; Lahiru Handunnetthi; Sharon Dixon; Francesco Zaccardi; Manu Shankar-Hari; Peter Watkinson; Kamlesh Khunti; Anthony Harnden; Carol AC Coupland; Keith M. Channon; Nicholas L Mills; Aziz Sheikh; Julia Hippisley-Cox,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Leicester; University of Edinburgh; University of Oxford; University of Leicester; University of Oxford; University of Oxford; University of Oxford; University of Edinburgh; University of Edinburgh; University of Oxford,"In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy. - -FundingHealth Data Research UK.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.12.23.21268279,2021-12-25,https://medrxiv.org/cgi/content/short/2021.12.23.21268279,Remote Covid Assessment in Primary Care (RECAP) risk prediction tool: derivation and real-world validation studies.,Ana B Espinosa-Gonzalez; Denys Prociuk; Francesca Fiorentino; Christian Ramtale; Ella Mi; Emma Mi; Ben Glampson; Cecilia Okusi; Jack Macartney; Laiba Husain; Martina Brown; Ben Browne; Caroline Warren; Rachna Chowla; Jonty Heaversedge; Trisha Greenhalgh; Simon de Lusignan; Brendan C Delaney,"Institute of Global Health Innovation, Dept of Surgery and Cancer, Imperial College London, UK; Institute of Global Health Innovation, Dept of Surgery and Cancer, Imperial College London, UK; Nightingale-Saunders Clinical Trials & Epidemiology Unit, King's Clinical Trials Unit, King's College London; Institute of Global Health Innovation, Dept of Surgery and Cancer, Imperial College London, UK; Institute of Global Health Innovation, Dept of Surgery and Cancer, Imperial College London, UK; Institute of Global Health Innovation, Dept of Surgery and Cancer, Imperial College London, UK; Imperial College Healthcare NHS Trust, London, UK; Nuffield Dept of Primary Care, University of Oxford, UK; Nuffield Dept of Primary Care, University of Oxford, UK; Nuffield Dept of Primary Care, University of Oxford, UK; South Central Ambulance Service NHS Trust, UK; South Central Ambulance Service NHS Trust, UK; South Central Ambulance Service NHS Trust, UK; Kings Health Partners, London, UK; South East London NHS Clinical Commissioning Group, London UK; Nuffield Dept of Primary Care, University of Oxford, UK; Nuffield Dept of Primary Care, University of Oxford, UK; Institute of Global Health Innovation, Dept of Surgery and Cancer, Imperial College London, UK","BackgroundAccurate assessment of COVID-19 severity in the community is essential for best patient care and efficient use of services and requires a risk prediction score that is COVID-19 specific and adequately validated in a community setting. Following a qualitative phase to identify signs, symptoms and risk factors, we sought to develop and validate two COVID-19-specific risk prediction scores RECAP-GP (without peripheral oxygen saturation (SpO2)) and RECAP-O2 (with SpO2). MethodsProspective cohort study using multivariable logistic regression for model development. Data on signs and symptoms (model predictors) were collected on community-based patients with suspected COVID-19 via primary care electronic health records systems and linked with secondary data on hospital admission (primary outcome) within 28 days of symptom onset. Data sources: RECAP-GP: Oxford-Royal College of General Practitioners Research and Surveillance Centre (RSC) primary care practices (development), Northwest London (NWL) primary care practices, NHS COVID-19 Clinical Assessment Service (CCAS) (validation). RECAP-O2: Doctaly Assist platform (development, and validation in subsequent sample). Estimated sample size was 2,880 per model. @@ -1961,13 +1944,6 @@ METHODSParticipants consisted of 247 249 individuals from seven cohorts across s FINDINGSA total of 9979 individuals (4%) were diagnosed with COVID-19 during the study period and presented overall with a higher symptom burden of depression (prevalence ratio [PR] 1{middle dot}18, 95% confidence interval [95% CI] 1{middle dot}03-1{middle dot}36) and poorer sleep quality (1{middle dot}13, 1{middle dot}03-1{middle dot}24) but not with higher levels of symptoms of anxiety or COVID-19 related distress compared with individuals without a COVID-19 diagnosis. While the prevalence of depression and COVID-19 related distress attenuated with time, the trajectories varied significantly by COVID-19 acute infection severity. Individuals diagnosed with COVID-19 but never bedridden due to their illness were consistently at lower risks of depression and anxiety (PR 0{middle dot}83, 95% CI 0{middle dot}75-0{middle dot}91 and 0{middle dot}77, 0{middle dot}63-0{middle dot}94, respectively), while patients bedridden for more than 7 days were persistently at higher risks of symptoms of depression and anxiety (PR 1{middle dot}61, 95% CI 1{middle dot}27-2{middle dot}05 and 1{middle dot}43, 1{middle dot}26-1{middle dot}63, respectively) throughout the 16-month study period. CONCLUSIONAcute infection severity is a key determinant of long-term mental morbidity among COVID-19 patients.",public and global health,fuzzy,100,92 -medRxiv,10.1101/2021.12.14.21267460,2021-12-15,https://medrxiv.org/cgi/content/short/2021.12.14.21267460,Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales,Sarah Beale; Susan J Hoskins; Thomas Edward Byrne; Erica Wing Lam Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan MD Navaratnam; Vincent Nguyen; Parth Patel; Alexei Yavlinsky; Anne Johnson; Martie Van Tongeren; Robert W Aldridge; Andrew Hayward,University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University of Manchester; University College London; University College London,"BackgroundWorkers differ in their risk of SARS-CoV-2 infection according to their occupation, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase. - -MethodsData from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR). - -FindingsIncreased risk was seen in nurses (aRR=1.44, 1.25-1.65; AF=30%, 20-39%), doctors (aRR=1.33, 1.08-1.65; AF=25%, 7-39%), carers (1.45, 1.19-1.76; AF=31%, 16-43%), primary school teachers (aRR=1.67, 1.42-1.96; AF=40%, 30-49%), secondary school teachers (aRR=1.48, 1.26-1.72; AF=32%, 21-42%), and teaching support occupations (aRR=1.42, 1.23-1.64; AF=29%, 18-39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020 - May 2021) and attenuated later (June - October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves. - -InterpretationOccupational differentials in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.12.13.21267723,2021-12-14,https://medrxiv.org/cgi/content/short/2021.12.13.21267723,"Differential impact of Covid-19 on incidence of diabetes mellitus and cardiovascular diseases in acute, post-acute and long Covid-19: population-based cohort study in the United Kingdom",Emma Rezel-Potts; Abdel Douiri; Xiaohui Sun; Phillip J Chowienczyk; Ajay M Shah; Martin C Gulliford,King's College London; King's College London; King's College London; King's College London; King's College London; King's College London,"ObjectiveThis study aimed to estimate the incidence of new diabetes mellitus (DM) and cardiovascular diseases (CVD) up to one year after Covid-19 compared with matched controls. MethodsA cohort study was conducted using electronic records for 1,473 family practices with a population of 14.9 million. Covid-19 patients without DM or CVD were individually matched with controls and followed up to October 2021. A difference-in-difference analysis estimated the net effect of Covid-19 allowing for baseline differences and covariates. @@ -1975,32 +1951,13 @@ MethodsA cohort study was conducted using electronic records for 1,473 family pr ResultsThere were 372,816 Covid-19 patients, with 2,935 CVD and 3,139 DM events, and 372,816 matched controls with 1,193 CVD and 1,861 DM events following the index date. Net incidence of DM increased in acute Covid-19 up to four weeks from index date (adjusted rate ratio, RR 1.71, 1.40 to 2.10) and remained elevated in post-acute (five to 12 weeks from index date; RR 1.17, 1.01 to 1.36) and long-Covid-19 (13 to 52 weeks, 1.20, 1.09 to 1.31). Acute Covid-19 was associated with net increased CVD incidence (RR 6.02, 95% confidence interval 4.84 to 7.47) including pulmonary embolism (RR 14.5, 7.72 to 27.4), atrial arrythmias (6.58, 3.78 to 11.4) and venous thromboses (5.44, 3.22 to 9.17). CVD incidence declined in post-acute Covid-19 (1.68, 1.41 to 2.01) and showed no net increase in long Covid-19 (0.95, 0.85 to 1.06). ConclusionsDM incidence remains elevated up to one year following Covid-19. CVD is increased early after Covid-19 mainly from pulmonary embolism, atrial arrhythmias and venous thromboses.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.12.09.21267516,2021-12-09,https://medrxiv.org/cgi/content/short/2021.12.09.21267516,Changes in the trajectory of Long Covid symptoms following COVID-19 vaccination: community-based cohort study,Daniel Ayoubkhani; Charlotte Bermingham; Koen B Pouwels; Myer Glickman; Vahe Nafilyan; Francesco Zaccardi; Kamlesh Khunti; Nisreen A Alwan; Ann Sarah Walker,Office for National Statistics; Office for National Statistics; University of Oxford; Office for National Statistics; Office for National Statistics; University of Leicester; University of Leicester; University of Southampton; University of Oxford,"ObjectiveTo estimate associations between COVID-19 vaccination and Long Covid symptoms in adults who were infected with SARS-CoV-2 prior to vaccination. - -DesignObservational cohort study using individual-level interrupted time series analysis. - -SettingRandom sample from the community population of the UK. - -Participants28,356 COVID-19 Infection Survey participants (mean age 46 years, 56% female, 89% white) aged 18 to 69 years who received at least their first vaccination after test-confirmed infection. - -Main outcome measuresPresence of long Covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021. - -ResultsMedian follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (84% of participants). First vaccination was associated with an initial 12.8% decrease (95% confidence interval: -18.6% to -6.6%) in the odds of Long Covid, but increasing by 0.3% (-0.6% to +1.2%) per week after the first dose. Second vaccination was associated with an 8.8% decrease (-14.1% to -3.1%) in the odds of Long Covid, with the odds subsequently decreasing by 0.8% (-1.2% to -0.4%) per week. There was no statistical evidence of heterogeneity in associations between vaccination and Long Covid by socio-demographic characteristics, health status, whether hospitalised with acute COVID-19, vaccine type (adenovirus vector or mRNA), or duration from infection to vaccination. +medRxiv,10.1101/2021.12.08.21267458,2021-12-08,https://medrxiv.org/cgi/content/short/2021.12.08.21267458,"Relative contribution of leaving home for work or education, transport, shopping and other activities on risk of acquiring COVID-19 infection outside the household in the second wave of the pandemic in England and Wales",Susan J Hoskins; Sarah Beale; Robert W Aldridge; Colette Smith; Clare French; Alex Yavlinksky; Vincent Nguyen; Thomas Edward Byrne; Jana Kovar; Ellen Fragaszy; W Fong; Cyril Geismar; Parth Patel; Ann Johnson; Andrew Edward Hayward,Univerity College London; University College London; UCL; University College London; University of Bristol; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCL,"BackgroundWith the potential for and emergence of new COVID-19 variants, such as the reportedly more infectious Omicron, and their potential to escape the existing vaccines, understanding the relative importance of which non-household activities increase risk of acquisition of COVID-19 infection is vital to inform mitigation strategies. -ConclusionsThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second dose. Vaccination may contribute to a reduction in the population health burden of Long Covid, though longer follow-up time is needed. +MethodsWithin an adult subset of the Virus Watch community cohort study, we sought to identify which non-household activities increased risk of acquisition of COVID-19 infection and which accounted for the greatest proportion of non-household acquired COVID-19 infections during the second wave of the pandemic. Among participants who were undertaking antibody tests and self-reporting PCR and lateral flow tests taken through the national testing programme, we identified those who were thought to be infected outside the household during the second wave of the pandemic. We used exposure data on attending work, using public or shared transport, using shops and other non-household activities taken from monthly surveys during the second wave of the pandemic. We used multivariable logistic regression models to assess the relative independent contribution of these exposures on risk of acquiring infection outside the household. We calculated Adjusted Population Attributable Fractions (APAF - the proportion of non-household transmission in the cohort thought to be attributable to each exposure) based on odds ratios and frequency of exposure in cases. -Summary boxWhat is already known on this topic - -O_LICOVID-19 vaccines are effective at reducing rates of SARS-CoV-2 infection, transmission, hospitalisation, and death -C_LIO_LIThe incidence of Long Covid may be reduced if infected after vaccination, but the relationship between vaccination and pre-existing long COVID symptoms is unclear, as published studies are generally small and with self-selected participants -C_LI - -What this study adds +ResultsBased on analysis of 10475 adult participants including 874 infections acquired outside the household, infection was independently associated with: leaving home for work (AOR 1.20 (1.02 - 1.42) p=0.0307, APAF 6.9%); public transport use (AOR for use more than once per week 1.82 (1.49 - 2.23) p<0.0001, APAF for public transport 12.42%); and shopping (AOR for shopping more than once per week 1.69 (1.29 - 2.21) P=0.0003, APAF for shopping 34.56%). Other non-household activities such as use of hospitality and leisure venues were rare due to restrictions and there were no significant associations with infection risk. -O_LIThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second dose -C_LIO_LIThere was no evidence of differences in this relationship by socio-demographic characteristics, health-related factors, vaccine type, or duration from infection to vaccination -C_LIO_LIAlthough causality cannot be inferred from this observational evidence, vaccination may contribute to a reduction in the population health burden of Long Covid; further research is needed to understand the biological mechanisms that may ultimately contribute to the development of therapeutics for Long Covid -C_LI",epidemiology,fuzzy,100,100 +ConclusionsA high proportion of the second wave of the pandemic was spent under conditions where people were being advised to work from home where possible, and to minimize exposure to shops, and a wide range of other businesses were subject to severe restrictions. Vaccines were being rolled out to high-risk groups. During this time, going to work was an important risk factor for infection but public transport use likely accounted for a lot of this risk. Only a minority of the cohort left home for work or used public or shared transport. By contrast, the majority of participants visited shops and this activity accounted for about one-third of non-household transmission.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.12.08.21267353,2021-12-08,https://medrxiv.org/cgi/content/short/2021.12.08.21267353,The challenge of limited vaccine supplies: impact of prior infection on anti-spike IgG antibody trajectories after a single COVID-19 vaccination,Jia Wei; Philippa Matthews; Nicole Stoesser; Ian Diamond; Ruth Studley; Emma Rourke; Duncan Cook; John Bell; John Newton; Jeremy Farrar; Alison Howarth; Brian Marsden; Sarah Hoosdally; Yvonne Jones; David Stuart; Derrick W Crook; tim E peto; Ann Sarah Walker; David W Eyre; Koen B Pouwels; - COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; NIHR Oxford Biomedical Research Centre; oxford university; University of Oxford; University of Oxford; University of Oxford; ,"Given high SARS-CoV-2 incidence, coupled with slow and inequitable vaccine roll-out, there is an urgent need for evidence to underpin optimum vaccine deployment, aiming to maximise global population immunity at speed. We evaluate whether a single vaccination in previously infected individuals generates similar initial and subsequent antibody responses to two vaccinations in those without prior infection. We compared anti-spike IgG antibody responses after a single dose of ChAdOx1, BNT162b2, or mRNA-1273 SARS-CoV-2 vaccines in the COVID-19 Infection Survey in the UK general population. In 100,849 adults who received at least one vaccination, 13,404 (13.3%) had serological and/or PCR evidence of prior infection. Prior infection significantly boosted antibody responses for all three vaccines, producing a higher peak level and longer half-life, and a response comparable to those without prior infection receiving two vaccinations. In those with prior infection, median time above the positivity threshold was estimated to last for >1 year after the first dose. Single-dose vaccination targeted to those previously infected may provide protection in populations with high rates of previous infection faced with limited vaccine supply, as an interim measure while vaccine campaigns are scaled up.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.12.03.21266112,2021-12-05,https://medrxiv.org/cgi/content/short/2021.12.03.21266112,Brain Injury in COVID-19 is Associated with Autoinflammation and Autoimmunity,Edward J Needham; Alex L Ren; Richard J Digby; Joanne G Outtrim; Dorothy A Chatfield; Virginia FJ Newcombe; Rainer Doffinger; Gabriela Barcenas-Morales; Claudia Fonseca; Michael J Taussig; Rowan M Burnstein; Cordelia Dunai; Nyarie Sithole; Nicholas J Ashton; Henrik Zetterberg; Magnus Gisslen; Eden Arvid; Emelie Marklund; Michael J Griffiths; Jonathan Cavanagh; Gerome Breen; Sarosh R Irani; Anne Elmer; Nathalie Kingston; John R Bradley; Leonie S Taams; Benedict D michael; Edward T Bullmore; Kenneth GC Smith; Paul A Lyons; Alasdair JC Coles; David K Menon; - Cambridge NeuroCOVID Group; - NIHR Cambridge Covid BioResource; - NIHR Cambridge Clinical Research Facility,"Department of Clinical Neurosciences, University of Cambridge, UK; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK.; Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK.; Cambridge Protein Arrays Ltd, Babraham Research Campus, Cambridge, UK; Cambridge Protein Arrays Ltd, Babraham Research Campus, Cambridge, UK; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; Clinical Infection Microbiology and Neuroimmunology, Institute of Infection, Veterinary and Ecological Science, Liverpool, UK.; Department of Infectious Diseases, Cambridge University NHS Hospitals Foundation Trust, Cambridge, UK.; Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Molndal, Sweden.; Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Molndal, Sweden; C; Department of Infectious Diseases, Institute of Biomedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotaland; Department of Infectious Diseases, Institute of Biomedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotaland; Department of Infectious Diseases, Institute of Biomnedicine, the Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden; Region Vastra Gotalan; Institute of Infection, Veterinary & Ecological Sciences, University of Liverpool, Liverpool, UK.; Centre for Immunobiology, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, U; Department of Social Genetic and Developmental Psychiatry, King's College London, London, UK.; Oxford Autoimmune Neurology Group, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK; Department of Neurology, Oxford University H; Cambridge Clinical Research Centre, NIHR Clinical Research Facility, Cambridge University Hospitals NHS Foundation Trust, Addenbrooke's Hospital, Cambridge, UK ; NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK.; NIHR BioResource, Cambridge University Hospitals NHS Foundation, Cambridge Biomedical Campus, Cambridge, UK; Department of Medicine, University of Cambridge, Ad; Centre for Inflammation Biology and Cancer Immunology and Dept Inflammation Biology, School of Immunology and Microbial Sciences, Kings College London, Guys Cam; Clinical Infection Microbiology and Neuroimmunology, Institute of Infection, Veterinary and Ecological Science, Liverpool, UK.; Department of Psychiatry, University of Cambridge, Herchel Smith Building for Brain and Mind Sciences, Cambridge Biomedical Campus, Cambridge, UK.; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Je; Department of Medicine, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Cambridge Institute of Therapeutic Immunology and Infectious Disease, Je; Department of Clinical Neurosciences, University of Cambridge, UK; Division of Anaesthesia, Department of Medicine, University of Cambridge, UK.; ; ; ","COVID-19 has been associated with many neurological complications including stroke, delirium and encephalitis. Furthermore, many individuals experience a protracted post-viral syndrome which is dominated by neuropsychiatric symptoms, and is seemingly unrelated to COVID-19 severity. The true frequency and underlying mechanisms of neurological injury are unknown, but exaggerated host inflammatory responses appear to be a key driver of severe COVID-19 more broadly. @@ -2156,6 +2113,7 @@ Research in ContextO_ST_ABSEvidence before the studyC_ST_ABSWe searched PubMed o Added value of this studyTo our knowledge, this is the first study providing a comprehensive view of COVID-19 across pandemic waves using national data and focusing on severity, vaccination, and patient trajectories. Drawing on linked electronic health record (EHR) data on a national scale (56.6 million people alive and registered with GP in England), we describe key demographic factors, frequency of comorbidities, impact of the two main waves in England, and effect of full vaccination on COVID-19 severities. Additionally, we identify and describe patient trajectory networks which illustrate the main transition pathways of COVID-19 patients in the healthcare system. Finally, we provide reproducible COVID-19 phenotyping algorithms reflecting clinically relevant stages of disease severity i.e. positive tests, primary care diagnoses, hospitalisation, critical care treatments (e.g. ventilatory support) and mortality. Implications of all the available evidenceThe COVID-19 phenotypes and trajectory analysis framework outlined produce a reproducible, extensible and repurposable means to generate national-scale data to support critical policy decision making. By modelling patient trajectories as a series of interactions with healthcare systems, and linking these to demographic and outcome data, we provide a means to identify and prioritise care pathways associated with adverse outcomes and highlight healthcare system touch points which may act as tangible targets for intervention.",public and global health,fuzzy,100,100 +medRxiv,10.1101/2021.11.05.21265977,2021-11-09,https://medrxiv.org/cgi/content/short/2021.11.05.21265977,"Waning, Boosting and a Path to Endemicity for SARS-CoV-2.",Matt J Keeling; Amy C Thomas; Edward M Hill; Robin N Thompson; Louise Dyson; Michael Tildesley; Sam Moore,University of Warwick; University of Bristol; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"In many countries, an extensive vaccination programme has substantially reduced the public-health impact of SARS-CoV-2, limiting the number of hospital admissions and deaths compared to an unmitigated epidemic. Ensuring a low-risk transition from the current situation to one in which SARS-CoV-2 is endemic requires maintenance of high levels of population immunity. The observed waning of vaccine efficacy over time suggests that booster doses may be required to maintain population immunity especially in the most vulnerable groups. Here, using data and models for England, we consider the dynamics of COVID-19 over a two-year time-frame, and the role that booster vaccinations can play in mitigating the worst effects. We find that boosters are necessary to suppress the imminent wave of infections that would be generated by waning vaccine efficacy. Projecting further into the future, the optimal deployment of boosters is highly sensitive to their long-term action. If protection from boosters wanes slowly (akin to protection following infection) then a single booster dose to the over 50s may be all that is needed over the next two-years. However, if protection wanes more rapidly (akin to protection following second dose vaccination) then annual or even biannual boosters are required to limit subsequent epidemic peaks an reduce the pressure on public health services.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.11.05.21264590,2021-11-08,https://medrxiv.org/cgi/content/short/2021.11.05.21264590,Prone positioning of patients with moderate hypoxia due to COVID-19: A multicenter pragmatic randomized trial,Mike Fralick; Michael Colacci; Laveena Munshi; Kevin Venus; Lee Fidler; Haseena Hussein; Karen Britto; Rob Fowler; Bruno da Costa; Irfan Dhalla; Richard Dunbar-Yaffe; Laura Branfield Day; Thomas MacMillan; Jonathan Zipursky; Travis Carpenter; Terence Tang; Amanda Cooke; Rachel Hensel; Melissa Bregger; Alexis Gordon; Erin Worndl; Stephanie Go; Keren Mandelzweig; Lana Castellucci; Daniel Tamming; Fahad Razak; Amol Verma; - COVID PRONE Investigators,University of Toronto; University of Toronto - Department of Medicine; Sinai Health System; University Health Network; Sunnybrook Health Sciences Centre; William Osler Health System; William Osler Health System; Sunnybrook Health Sciences Centre; St. Michael's Hospital; Unity Health Toronto; University Health Network; University of Toronto; University of Toronto; Sunnybrook Health Sciences Centre; University of Toronto; Trillium Health Partners; Beth Israel Deaconess Medical Center; Beth Israel Deaconess Medical Center; Northwestern University Feinberg School of Medicine; Scarborough Health Network; Scarborough Health Network; Humber River Hospital; Humber River Hospital; Ottawa Hospital Research Institute; Unity Health Toronto; University of Toronto; University of Toronto; ,"ObjectivesTo assess the effectiveness of prone positioning to reduce the risk of death or respiratory failure in non-critically ill patients hospitalized with COVID-19 DesignPragmatic randomized clinical trial of prone positioning of patients hospitalized with COVID-19 across 15 hospitals in Canada and the United States from May 2020 until May 2021. @@ -2392,6 +2350,17 @@ Methods and findingsWe performed a rapid systematic review, searching Medline, E ConclusionsWe found minimal high quality or consistent evidence that any drug groups increase susceptibility, severity or mortality in COVID-19. Converse to initial hypotheses, we found some evidence that regular use of ACEIs and ARBs prior to infection may be effective in reducing the level of care required, such as requiring intensive care, in patients with COVID-19.",pharmacology and therapeutics,fuzzy,100,100 medRxiv,10.1101/2021.09.13.21263487,2021-09-16,https://medrxiv.org/cgi/content/short/2021.09.13.21263487,SARS-CoV-2 anti-spike IgG antibody responses after second dose of ChAdOx1 or BNT162b2 in the UK general population,Jia Wei; Koen B. Pouwels; Nicole Stoesser; Philippa C. Matthews; Ian Diamond; Ruth Studley; Emma Rourke; Duncan Cook; John I Bell; John N Newton; Jeremy Farrar; Alison Howarth; Brian D. Marsden; Sarah Hoosdally; E Yvonne Jones; David I Stuart; Derrick W. Crook; Tim E.A. Peto; A.Sarah Walker; David W. Eyre,University of Oxford; University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"We investigated anti-spike IgG antibody responses and correlates of protection following second doses of ChAdOx1 or BNT162b2 SARS-CoV-2 vaccines in the UK general population. In 222,493 individuals, we found significant boosting of anti-spike IgG by second doses of both vaccines in all ages and using different dosing intervals, including the 3-week interval for BNT162b2. After second vaccination, BNT162b2 generated higher peak levels than ChAdOX1. Older individuals and males had lower peak levels with BNT162b2 but not ChAdOx1, while declines were similar across ages and sexes with ChAdOX1 or BNT162b2. Prior infection significantly increased antibody peak level and half-life with both vaccines. Anti-spike IgG levels were associated with protection from infection after vaccination and, to an even greater degree, after prior infection. At least 67% protection against infection was estimated to last for 2-3 months after two ChAdOx1 doses and 5-8 months after two BNT162b2 doses in those without prior infection, and 1-2 years for those unvaccinated after natural infection. A third booster dose may be needed, prioritised to ChAdOx1 recipients and those more clinically vulnerable.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2021.09.13.21262360,2021-09-16,https://medrxiv.org/cgi/content/short/2021.09.13.21262360,Efficacy of two doses of COVID-19 vaccine against severe COVID-19 in those with risk conditions and residual risk to the clinically extremely vulnerable: the REACT-SCOT case-control study,Paul M McKeigue; David McAllister; Chris Robertson; Sharon J Hutchinson; Stuart McGurnaghan; Diane Stockton; Helen M Colhoun,University of Edinburgh; University of Glasgow; University of Strathclyde; Glasgow Caledonian University; University of Edinburgh; Public Health Scotland; University of Edinburgh,"ObjectivesTo determine whether COVID-19 efficacy varies with clinical risk category and to investigate risk factors for severe COVID-19 in those who have received two doses of vaccine. + +DesignMatched case-control study (REACT-SCOT). + +SettingPopulation of Scotland from 1 December 2020 to 8 September 2021. + +Main outcome measureSevere COVID-19, defined as cases with entry to critical care or fatal outcome. + +ResultsEfficacy against severe COVID-19 of two doses of vaccine was 94% (95 percent CI 93% to 96%) in those without designated risk conditions, 89% (95 percent CI 86% to 91%) in those with moderate risk conditions, but only 73% (95 percent CI 64% to 79%) in those designated as clinically extremely vulnerable (CEV) and eligible for shielding. Of the 641 cases of severe COVID-19 in double-vaccinated individuals, 47% had moderate risk conditions and 38% were CEV. In the double-vaccinated CEV group, the rate ratio for severe disease (with no risk condition as reference category) was highest in solid organ transplants at 101 (95% CI 47 to 214) but even in this subgroup the absolute risk of severe COVID-19 was low (35 cases in 23678 person-months of follow-up). + +ConclusionsTwo doses of vaccine protect against severe COVID-19 in CEV individuals but the residual risk in double-vaccinated individuals remains far higher in those who are CEV than in those who are not. These results lay a basis for determining eligibility for additional measures including passive immunization to protect those at highest risk.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.09.10.21263372,2021-09-15,https://medrxiv.org/cgi/content/short/2021.09.10.21263372,Localising Vaccination Services: Qualitative Insights on an Orthodox Jewish Collaboration with Public health during the UK coronavirus Vaccine Programme,Ben Kasstan; Sandra Mounier-Jack; Louise Letley; Katherine M Gaskell; Chrissy h Roberts; Neil Stone; Sham Lal; Rosalind M Eggo; Michael Marks; Tracey Chantler,University of Bristol; LSHTM; Public Health England; LSHTM; London School of Hygiene & Tropical Medicine (LSHTM); LSHTM; LSHTM; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine,"Ethnic and religious minorities have been disproportionately affected by the SARS-CoV-2 pandemic and are less likely to accept coronavirus vaccinations. Orthodox (Haredi) Jewish neighbourhoods in England experienced high incidences of SARS-CoV-2 in 2020-21 and measles outbreaks (2018-19) due to suboptimal childhood vaccination coverage. The objective of our study was to explore how the coronavirus vaccination programme (CVP) was co-delivered between public health services and an Orthodox Jewish health organisation. Methods included 28 semi-structured interviews conducted virtually with public health professionals, community welfare and religious representatives, and household members. We examined CVP delivery from the perspectives of those involved in organising services and vaccine beneficiaries. Interview data was contextualised within debates of the CVP in Orthodox (Haredi) Jewish print and social media. Thematic analysis generated five considerations: i) Prior immunisation-related collaboration with public health services carved a role for Jewish health organisations to host and promote coronavirus vaccination sessions, distribute appointments, and administer vaccines ii) Public health services maintained responsibility for training, logistics, and maintaining vaccination records; iii) The localised approach to service delivery promoted vaccination in a minority with historically suboptimal levels of coverage; iv) Co-delivery promoted trust in the CVP, though a minority of participants maintained concerns around safety; v) Provision of CVP information and stakeholders response to situated (context-specific) challenges and concerns. @@ -2541,6 +2510,15 @@ MethodsPopulation-level birth outcomes in Wales: Stillbirths, prematurity, birth FindingsThere was no significant difference between annual outcomes including gestation and birth weight, stillbirths, and Caesarean sections for infants born in 2020 compared to 2016-2019. There was an increase in late term births ([≥]42 weeks gestation) during the first lockdown (OR: 1.28, p=0.019) and a decrease in moderate to late preterm births (32-36 weeks gestation) during the second lockdown (OR: 0.74, p=0.001). Fewer babies were born in 2020 (N=29,031) compared to 2016-2019 (average N=32,582). All babies received their immunisations in 2020, but there were minor delays in the timings of vaccines. Those due at 8-weeks were 8% less likely to be on time (within 28-days) and at 16-weeks, they were 19% less likely to be on time. The pandemic had a negative impact on the mental health of 71% of survey respondents, who reported anxiety, stress and loneliness; this was associated with attending scans without their partner, giving birth alone, and minimal contact with midwives. InterpretationThe pandemic had a negative impact on mothers experiences of pregnancy; however, population-level data suggests that this did not translate to adverse birth outcomes for babies born during the pandemic.",public and global health,fuzzy,100,100 +medRxiv,10.1101/2021.08.17.21262196,2021-08-22,https://medrxiv.org/cgi/content/short/2021.08.17.21262196,Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY disease (CLARITY): Statistical analysis plan for a randomised controlled Bayesian adaptive sample size trial,James McGree; Carinna Hockham; Sradha Kotwal; Arlen Wilcox; Abhinav Bassi; Carol Pollock; Louise M Burrell; Tom Snelling; Vivek Jha; Meg Jardine; Mark Jones,Queensland University of Technology; Imperial College London; University of New South Wales; University of New South Wales; The George Institute for Global Health; Royal North Shore Hospital; University of Melbourne; The University of Sydney; University of New South Wales; University of New South Wales; The University of Sydney,"The CLARITY trial (Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY Disease) investigates the effectiveness of angiotensin receptor blockers in addition to standard care compared to placebo (in Indian sites) with standard care in reducing the duration and severity of lung failure in patients with COVID-19. The CLARITY trial is a multi-centre, randomised controlled Bayesian adaptive trial with regular planned analyses where pre-specified decision rules will be assessed to determine whether the trial should be stopped due to sufficient evidence of treatment effectiveness or futility. Here we describe the statistical analysis plan for the trial, and define the pre-specified decision rules, including those that could lead to the trial being halted. The primary outcome is clinical status on a 7-point ordinal scale adapted from the WHO Clinical Progression scale assessed at Day 14. The primary analysis will follow the intention-to-treat principle. A Bayesian adaptive trial design was selected because there is considerable uncertainty about the extent of potential benefit of this treatment. + +Trial registrationClinicalTrials.gov, NCT04394117. Registered on 19 May 2020. + +https://clinicaltrials.gov/ct2/show/NCT04394117 + +Clinical Trial Registry of India: CTRI/2020/07/026831 + +Version and revisionsVersion 1.0. No revisions.",respiratory medicine,fuzzy,100,100 medRxiv,10.1101/2021.08.13.21261889,2021-08-18,https://medrxiv.org/cgi/content/short/2021.08.13.21261889,Robust SARS-CoV-2-specific and heterologous immune responses after natural infection in elderly residents of Long-Term Care Facilities,Gokhan Tut; Tara Lancaster; Megan S Butler; Panagiota Sylla; Eliska Spalkova; David Bone; Nayandeep Kaur; Christopher Bentley; Umayr Amin; Azar T Jadir; Samuel Hulme; Morenike Ayodele; Alexander C Dowell; Hayden Pearce; Sandra Margielewska-Davies; Kriti Verma; Samantha Nicol; Jusnara Begum; Elizabeth Jinks; Elif Tut; Rachel Bruton; Maria Krutikov; Madhumita Shrotri; Rebecca Giddings; Borscha Azmi; Chris Fuller; Aidan Irwin-Singer; Andrew Hayward; Andrew Copas; Laura Shallcross; Paul Moss,"Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; Department of Health and Social Care, London, UK; Health Data Research UK; UCL Institute for Global Health, London, UK; UCL Institute of Health Informatics, London, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK","Long term care facilities (LTCF) provide residential and/or nursing care support for frail and elderly people and many have suffered from a high prevalence of SARS-CoV-2 infection. Although mortality rates have been high in LTCF residents there is little information regarding the features of SARS-CoV-2-specific immunity after infection in this setting or how this may influence immunity to other infections. We studied humoral and cellular immunity against SARS-CoV-2 in 152 LTCF staff and 124 residents over a prospective 4-month period shortly after the first wave of infection and related viral serostatus to heterologous immunity to other respiratory viruses and systemic inflammatory markers. LTCF residents developed high levels of antibodies against spike protein and RBD domain which were stable over 4 months of follow up. Nucleocapsid-specific responses were also elevated in elderly donors but showed waning across all populations. Antibodies showed stable and equivalent levels of functional inhibition against spike-ACE2 binding in all age groups with comparable activity against viral variants of concern. SARS-CoV-2 seropositive donors showed high levels of antibodies to other beta-coronaviruses but serostatus did not impact humoral immunity to influenza or RSV. SARS-CoV-2-specific cellular responses were equivalent across the life course but virus-specific populations showed elevated levels of activation in older donors. LTCF residents who are survivors of SARS-CoV-2 infection thus show robust and stable immunity which does not impact responses to other seasonal viruses. These findings augur well for relative protection of LTCF residents to re-infection. Furthermore, they underlie the potent influence of previous infection on the immune response to Covid-19 vaccine which may prove to be an important determinant of future vaccine strategy. One sentence summeryCare home residents show waning of nucleocapsid specific antibodies and enhanced expression of activation markers on SARS-CoV-2 specific cells",infectious diseases,fuzzy,100,100 @@ -2762,7 +2740,6 @@ MethodsWe fit a stochastic individual-based model of secondary schools to both c FindingsThe within-school reproduction number, Rschool, has remained below 1 from 31st August 2020 until 21st May 2021. Twice weekly mass testing using LFTs have helped to control within-school transmission in secondary schools in England. A strategy of serial contact testing alongside mass testing substantially reduces absences compared to strategies involving isolating close contacts, with only a marginal increase in within-school transmission. InterpretationSecondary school control strategies involving mass testing have the potential to control within-school transmission while substantially reducing absences compared to an isolation of close contacts policy.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2021.07.12.21260360,2021-07-15,https://medrxiv.org/cgi/content/short/2021.07.12.21260360,The impact of hypoxia on B cells in COVID-19,Prasanti Kotagiri; Federica Mescia; Aimee Hanson; Lorinda Turner; Laura Bergamaschi; Ana Penalver; Nathan Richoz; Stephen Moore; Brian Ortmann; Benjamin Dunmore; Helene Ruffieux; Michael Morgan; Zewen Kelvin Tuong; Rachael Bashford Rogers; Myra Hosmillo; Stephen Baker; Anne Elmer; Ian Goodfellow; Ravindra Gupta; Nathalie Kingston; Paul Lehner; Nicholas Matheson; Sylvia Richardson; Caroline Saunders; Michael Weekes; Berthold Gottgens; Mark Toshner; Christoph Hess; Patrick Maxwell; Menna Clatworthy; James A Nathan; John Bradley; Paul Lyons; Natalie Burrows; Kenneth G C Smith,Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Oxford University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University,"Prominent early features of COVID-19 include severe, often clinically silent, hypoxia and a pronounced reduction in B cells, the latter important in defence against SARS-CoV-2. This brought to mind the phenotype of mice with VHL-deficient B cells, in which Hypoxia-Inducible Factors are constitutively active, suggesting hypoxia might drive B cell abnormalities in COVID-19. We demonstrated the breadth of early and persistent defects in B cell subsets in moderate/severe COVID-19, including reduced marginal zone-like, memory and transitional B cells, changes we also observed in B cell VHL-deficient mice. This was corroborated by hypoxia-related transcriptional changes in COVID-19 patients, and by similar B cell abnormalities in mice kept in hypoxic conditions, including reduced marginal zone and germinal center B cells. Thus hypoxia might contribute to B cell pathology in COVID-19, and in other hypoxic states. Through this mechanism it may impact on COVID-19 outcome, and be remediable through early oxygen therapy.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.07.07.21253295,2021-07-08,https://medrxiv.org/cgi/content/short/2021.07.07.21253295,Mortality among Care Home Residents in England during the first and second waves of the COVID-19 pandemic: an analysis of 4.3 million adults over the age of 65,Anna Schultze; Emily Nightingale; David Evans; William J Hulme; Alicia Rosello; Chris Bates; Jonathan Cockburn; Brian MacKenna; Helen J Curtis; Caroline E Morton; Richard Croker; Seb Bacon; Helen I McDonald; Christopher T. Rentsch; Krishnan Bhaskaran; Rohini Mathur; Laurie A Tomlinson; Elizabeth J Williamson; Harriet Forbes; John Tazare; Daniel J Grint; Alex J Walker; Peter Inglesby; Nicholas J DeVito; Amir Mehrkar; George Hickman; Simon Davy; Tom Ward; Louis Fisher; Amelia CA Green; Kevin Wing; Angel YS Wong; Robert McManus; John Parry; Frank Hester; Sam Harper; Stephen JW Evans; Ian J Douglas; Liam Smeeth; Rosalind M Eggo; Ben Goldacre; David A Leon,"London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene & Tropical Medicine; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; TPP, TPP House, 129 Low Lane, Horsforth, Leeds, LS18 5PX; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford, OX26GG; London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT","BackgroundResidents in care homes have been severely impacted by the COVID-19 pandemic. We describe trends in risk of mortality among care home residents compared to residents in private homes in England. MethodsOn behalf of NHS England, we used OpenSAFELY-TPP, an analytics platform running across the linked electronic health records of approximately a third of the English population, to calculate monthly age-standardised risks of death due to all causes and COVID-19 among adults aged >=65 years between 1/2/2019 and 31/03/2021. Care home residents were identified using linkage to the Care and Quality Commission. @@ -2947,6 +2924,7 @@ MethodsParticipants reported disruptions from March 2020 up to late January 2021 ResultsPrevalence of disruption varied across studies; between 6.4% (TwinsUK) and 31.8 % (Understanding Society) of study participants reported any disruption. Females (Odd Ratio (OR): 1.27 [95%CI: 1.15,1.40]; I2=53%), older persons (e.g. OR: 1.39 [1.13,1.72]; I2=77% for 65-75y vs 45-54y), and Ethnic minorities (excluding White minorities) (OR: 1.19 [1.05,1.35]; I2=0% vs White) were more likely to report healthcare disruptions. Those in a more disadvantaged social class (e.g. OR: 1.17 [1.08, 1.27]; I2=0% for manual/routine vs managerial/professional) were also more likely to report healthcare disruptions, but no clear differences were observed by education levels. ConclusionThe COVID-19 pandemic has led to unequal healthcare disruptions, which, if unaddressed, could contribute to the maintenance or widening of existing health inequalities.",health systems and quality improvement,fuzzy,97,100 +medRxiv,10.1101/2021.06.07.21258476,2021-06-10,https://medrxiv.org/cgi/content/short/2021.06.07.21258476,Possible future waves of SARS-CoV-2 infection generated by variants of concern with a range of characteristics,Louise Dyson; Edward M Hill; Sam Moore; Jacob Curran-Sebastian; Michael J Tildesley; Katrina A Lythgoe; Thomas House; Lorenzo Pellis; Matt J Keeling,"The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C; The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C; The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C; Department of Mathematics, University of Manchester, Manchester, United Kingdom; The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C; Big Data Institute, Old Road Campus, University of Oxford, United Kingdom.; Department of Mathematics, University of Manchester, Manchester, United Kingdom.; Department of Mathematics, University of Manchester, Manchester, United Kingdom.; The Zeeman Institute for Systems Biology \& Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, ","Viral reproduction of SARS-CoV-2 provides opportunities for the acquisition of advantageous mutations, altering viral transmissibility, disease severity, and/or allowing escape from natural or vaccine-derived immunity. We use three mathematical models: a parsimonious deterministic model with homogeneous mixing; an age-structured model; and a stochastic importation model to investigate the effect of potential variants of concern (VOCs). Calibrating to the situation in England in May 2021, we find epidemiological trajectories for putative VOCs are wide-ranging and dependent on their transmissibility, immune escape capability, and the introduction timing of a postulated VOC-targeted vaccine. We demonstrate that a VOC with a substantial transmission advantage over resident variants, or with immune escape properties, can generate a wave of infections and hospitalisations comparable to the winter 2020-2021 wave. Moreover, a variant that is less transmissible, but shows partial immune-escape could provoke a wave of infection that would not be revealed until control measures are further relaxed.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.06.08.21258535,2021-06-08,https://medrxiv.org/cgi/content/short/2021.06.08.21258535,Altered neutrophil phenotype and function in non-ICU COVID-19 patients correlated with disease severity,Kylie BR Belchamber; Onn S Thein; Jon Hazeldine; Frances S Grudzinska; Michael J Hughes; Alice E Jasper; Kay Por Yip; Elizabeth Sapey; Dhruv Parekh; David R Thickett; Aaron Scott,"Institute of Inflammation and Ageing, University of Birmingham; Institute of Inflammation and Ageing, University of Birmingham; 2National Institute for Health Research Surgical Reconstruction and Microbiology Research Centre, University of Birmingham; Institute of Inflammation and Ageing, University of Birmingham; Institute of Inflammation and Ageing, University of Birmingham; Institute of Inflammation and Ageing, University of Birmingham; Institute of Inflammation and Ageing, University of Birmingham; Institute of Inflammation and Ageing, University of Birmingham; Institute of Inflammation and Ageing, University of Birmingham; Institute of Inflammation and Ageing, University of Birmingham; Institute of Inflammation and Ageing, University of Birmingham","RationalInfection with the SARS-CoV2 virus is associated with elevated neutrophil counts. Evidence of neutrophil dysfunction in COVID-19 is based predominantly on transcriptomics or single functional assays. Cell functions are interwoven pathways, and so understanding the effect of COVID-19 across the spectrum of neutrophil function may identify tractable therapeutic targets. ObjectivesExamine neutrophil phenotype and functional capacity in COVID-19 patients versus age-matched controls (AMC) @@ -3012,6 +2990,21 @@ medRxiv,10.1101/2021.05.27.21257032,2021-05-31,https://medrxiv.org/cgi/content/s Significance statementCross-protection from seasonal epidemics of human coronaviruses (HCoVs) has been hypothesised to contribute to the relative sparing of children during the early phase of the pandemic. Testing this relies on understanding the pre-pandemic age-distribution of recent HCoV infections, but little is known about their dynamics. Using England and Wales as a case study, we use a transmission model to estimate the duration of immunity to seasonal coronaviruses, and show how cross-protection could have affected the age distribution of susceptibility during the first wave, and alter SARS-CoV-2 transmission patterns over the coming decade.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.05.22.21257633,2021-05-26,https://medrxiv.org/cgi/content/short/2021.05.22.21257633,Genomic reconstruction of the SARS-CoV-2 epidemic across England from September 2020 to May 2021,Harald S. Vohringer; Theo Sanderson; Matthew Sinnott; Nicola De Maio; Thuy Nguyen; Richard Goater; Frank Schwach; Ian Harrison; Joel Hellewell; Cristina Ariani; Sonia Goncalves; David Jackson; Ian Johnston; Alexander W. Jung; Callum Saint; John Sillitoe; Maria Suciu; Nick Goldman; Jasmina Panovska-Griffiths; - The Wellcome Sanger Institute Covid-19 Surveillance Team; - The COVID-19 Genomics UK (COG-UK) Consortium; Ewan Birney; Erik Volz; Sebastian Funk; Dominic Kwiatkowski; Meera Chand; Inigo Martincorena; Jeffrey C. Barrett; Moritz Gerstung,"European Molecular Biology Laboratory, European Bioinformatics Institute EMBL-EBI, Hinxton, UK; Current address: Joint Biosecurity Center JBC; Wellcome Sanger Institute, Hinxton, UK; The Francis Crick Institute, London, UK; Wellcome Sanger Institute, Hinxton, UK; European Molecular Biology Laboratory, European Bioinformatics Institute EMBL-EBI, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; Public Health England PHE; Public Health England PHE; London School of Hygiene & Tropical Medicine, London, UK; Wellcome Sanger Institute, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; European Molecular Biology Laboratory, European Bioinformatics Institute EMBL-EBI, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; European Molecular Biology Laboratory, European Bioinformatics Institute EMBL-EBI, Hinxton, UK; Joint Biosecurity Center JBC, Big Data Institute, University of Oxford, UK; ; ; European Molecular Biology Laboratory, European Bioinformatics Institute EMBL-EBI, Hinxton, UK; Imperial College, London, UK; London School of Hygiene & Tropical Medicine, London, UK; Wellcome Sanger Institute, Hinxton, UK; Public Health England PHE; Wellcome Sanger Institute, Hinxton, UK; Wellcome Sanger Institute, Hinxton, UK; European Molecular Biology Laboratory, European Bioinformatics Institute EMBL-EBI, Hinxton, UK; German Cancer Research Centre dkfz, Heidelberg, Germany","The evolution of the SARS-CoV-2 pandemic continuously produces new variants, which warrant timely epidemiological characterisation. Here we use the dense genomic surveillance generated by the COVID-19 Genomics UK Consortium to reconstruct the dynamics of 71 different lineages in each of 315 English local authorities between September 2020 and June 2021. This analysis reveals a series of sub-epidemics that peaked in the early autumn of 2020, followed by a jump in transmissibility of the B.1.1.7/Alpha lineage. Alpha grew when other lineages declined during the second national lockdown and regionally tiered restrictions between November and December 2020. A third more stringent national lockdown suppressed Alpha and eliminated nearly all other lineages in early 2021. However, a series of variants (mostly containing the spike E484K mutation) defied these trends and persisted at moderately increasing proportions. Accounting for sustained introductions, however, indicates that their transmissibility is unlikely to have exceeded that of Alpha. Finally, B.1.617.2/Delta was repeatedly introduced to England and grew rapidly in the early summer of 2021, constituting approximately 98% of sampled SARS-CoV-2 genomes on June 26.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2021.05.24.21257738,2021-05-26,https://medrxiv.org/cgi/content/short/2021.05.24.21257738,"Post-vaccination SARS-CoV-2 infection: risk factors and illness profile in a prospective, observational community-based case-control study",Michela Antonelli; Rose S Penfold; Jordi Merino; Carole H Sudre; Erika Molteni; Sarah Berry; Liane S Canas; Mark S Graham; Kerstin Klaser; Marc Modat; Benjamin Murray; Eric Kerfoot; Liyuan Chen; Jie Deng; Marc F Österdahl; Nathan J Cheetham; David Alden Drew; Long Alden Nguyen; Joan Capdeila; Christina Hu; Somesh Selvachandran; Lorenzo Polidori; Anna May; Jonathan Wolf; Andrew T Chan; Alexander Hammers; Emma Duncan; Timothy Spector; Sebastien Ourselin; Claire J Steves,"King's College London; King's College London; Department of Medicine, Harvard Medical School, Boston, MA, USA; Centre for Medical Image Computing, University College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; King's College London; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK; Massachusetts General Hospital; Massachusetts General Hospital and Harvard Medical School; Zoe Global, London, UK; Zoe Global, London, UK; Zoe Global, London, UK; Lorenzo Polidori; Zoe Global, London, UK; Zoe Global, London, UK; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK; King's College London; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK","BackgroundCOVID-19 vaccines show excellent efficacy in clinical trials and real-world data, but some people still contract SARS-CoV-2 despite vaccination. This study sought to identify risk factors associated with SARS-CoV-2 infection post-vaccination and describe characteristics of post-vaccination illness. + +MethodsAmongst 1,102,192 vaccinated UK adults from the COVID Symptom Study, 2394 (0.2%) cases of post-vaccination SARS-CoV-2 infection were identified between 8th December 2020 and 1st May 2021. Using a control group of vaccinated individuals testing negative, we assessed the associations of age, frailty, comorbidity, area-level deprivation and lifestyle factors with infection. Illness profile post-vaccination was assessed using a second control group of unvaccinated cases. + +FindingsOlder adults with frailty (OR=2.78, 95% CI=[1.98-3.89], p-value<0.0001) and individuals living in most deprived areas (OR=1.22 vs. intermediate group, CI[1.04-1.43], p-value=0.01) had increased odds of post-vaccination infection. Risk was lower in individuals without obesity (OR=0.6, CI[0.44-0.82], p-value=0.001) and those reporting healthier diet (OR=0.73, CI[0.62-0.86], p-value<0.0001). Vaccination was associated with reduced odds of hospitalisation (OR=0.36, CI[0.28-0.46], p-value<0.0001), and high acute-symptom burden (OR=0.51, CI[0.42-0.61], p-value<0.0001). In older adults, risk of [≥]28 days illness was lower following vaccination (OR=0.72, CI[0.51-1.00], p-value=0.05). Symptoms were reported less in positive-vaccinated vs. positive-unvaccinated individuals, except sneezing, which was more common post-vaccination (OR=1.24, CI[1.05-1.46], p-value=0.01). + +InterpretationOur findings suggest that older individuals with frailty and those living in most deprived areas are at increased risk of infection post-vaccination. We also showed reduced symptom burden and duration in those infected post-vaccination. Efforts to boost vaccine effectiveness in at-risk populations, and to targeted infection control measures, may still be appropriate to minimise SARS-CoV-2 infection. + +FundingThis work is supported by UK Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre (BRC) award to Guys & St Thomas NHS Foundation Trust in partnership with Kings College London and Kings College Hospital NHS Foundation Trust and via a grant to ZOE Global; the Wellcome Engineering and Physical Sciences Research Council (EPSRC) Centre for Medical Engineering at Kings College London (WT 203148/Z/16/Z). Investigators also received support from the Chronic Disease Research Foundation, the Medical Research Council (MRC), British Heart Foundation, the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, the Wellcome Flagship Programme (WT213038/Z/18/Z and Alzheimers Society (AS-JF-17-011), and the Massachusetts Consortium on Pathogen Readiness (MassCPR). + +Research in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify existing evidence for risk factors and characteristics of SARS-CoV-2 infection post-vaccination, we searched PubMed for peer-reviewed articles published between December 1, 2020 and May 18, 2021 using keywords (""COVID-19"" OR ""SARS-CoV-2"") AND (""Vaccine"" OR ""vaccination"") AND (""infection"") AND (""risk factor*"" OR ""characteristic*""). We did not restrict our search by language or type of publication. Of 202 articles identified, we found no original studies on individual risk and protective factors for COVID-19 infection following vaccination nor on nature and duration of symptoms in vaccinated, community-based individuals. Previous studies in unvaccinated populations have shown that social and occupational factors influence risk of SARS-CoV-2infection, and that personal factors (age, male sex, multiple morbidities and frailty) increased risk for adverse outcomes in COVID-19. Phase III clinical trials have demonstrated good efficacy of BNT162b2 and ChAdOx1 vaccines against SARS-CoV-2 infection, confirmed in published real-world data, which additionally showed reduced risk of adverse outcomes including hospitalisation and death. + +Added value of this studyThis is the first observational study investigating characteristics of and factors associated with SARS-CoV-2 infection after COVID-19 vaccination. We found that vaccinated individuals with frailty had higher rates of infection after vaccination than those without. Adverse determinants of health such as increased social deprivation, obesity, or a less healthy diet were associated with higher likelihood of infection after vaccination. In comparison with unvaccinated individuals, those with post-vaccination infection had fewer symptoms of COVID-19, and more were entirely asymptomatic. Fewer vaccinated individuals experienced five or more symptoms, required hospitalisation, and, in the older adult group, fewer had prolonged illness duration (symptoms lasting longer than 28 days). + +Implications of all the available evidenceSome individuals still contract COVID-19 after vaccination and our data suggest that frail older adults and those living in more deprived areas are at higher risk. However, in most individuals illness appears less severe, with reduced need for hospitalisation and lower risk of prolonged illness duration. Our results are relevant for health policy post-vaccination and highlight the need to prioritise those most at risk, whilst also emphasising the balance between the importance of personal protective measures versus adverse effects from ongoing social restrictions. Strategies such as timely prioritisation of booster vaccination and optimised infection control could be considered for at-risk groups. Research is also needed on how to enhance the immune response to vaccination in those at higher risk.",epidemiology,fuzzy,94,100 medRxiv,10.1101/2021.05.25.21257505,2021-05-25,https://medrxiv.org/cgi/content/short/2021.05.25.21257505,Plitidepsin has a positive therapeutic index in adult patients with COVID-19 requiring hospitalization.,Jose F. Varona; Pedro Landete; Jose A Lopez-Martin; Vicente Estrada; Roger Paredes; Pablo Guisado-Vasco; Lucia Fernandez de Orueta; Miguel Torralba; Jesus Fortun; Roberto Vates; Jose Barberan; Bonaventura Clotet; Julio Ancochea; Daniel Carnevali; Noemi Cabello; Lourdes Porras; Paloma Gijon; Alfonso Monereo; Daniel Abad; Sonia Zuñiga; Isabel Sola; Jordi Rodon; Nuria Izquierdo-Useros; Salvador Fudio; Maria Jose Pontes; Beatriz de Rivas; Patricia Giron de Velasco; Belen Sopesen; Antonio Nieto; Javier Gomez; Pablo Aviles; Rubin Lubomirov; Kris M White; Romel Rosales; Soner Yildiz; Ann-Kathrin Reuschl; Lucy G. Thorne; Clare Jolly; Greg J. Towers; Lorena Zuliani-Alvarez; Mehdi Bouhaddou; Kirsten Obernier; Luis Enjuanes; Jose M Fernandez-Sousa; - Plitidepsin COVID Study Group; Nevan J Krogan; Jose M. Jimeno; Adolfo Garcia-Sastre,"Departamento de Medicina Interna, Hospital Universitario HM Monteprincipe, HM Hospitales, Madrid, Spain. Facultad de Medicina, Universidad San Pablo-CEU, Madrid; Hospital Universitario de La Princesa. Madrid, Spain. Universidad Autonoma de Madrid, Madrid, Spain.; PharmaMar. Virology & Inflammation Dept. Colmenar Viejo, Madrid, Spain.; Hospital Clinico San Carlos, Madrid, Spain. Universidad Complutense de Madrid, Madrid, Spain.; IrsiCaixa AIDS Research Institute; Internal Medicine Department, Hospital Universitario Quironsalud, Madrid, Spain. Universidad Europea, Madrid, Spain.; Internal Medicine Department, Hospital Universitario de Getafe, Madrid, Spain. European University of Madrid, Madrid, Spain.; Internal Medicine, Guadalajara University Hospital, Guadalajara, Spain. University of Alcala, Madrid, Spain.; Hospital Universitario Ramon y Cajal, Madrid, Spain.; Internal Medicine Department, Hospital Universitario de Getafe, Madrid, Spain.; Hospital Universitario HM Monteprincipe, Madrid, Spain. Facultad de Medicina San Pablo CEU, Madrid, Spain.; Head of Infectious Diseases Department, Director of the Research Lab, IrsiCaixa, Barcelone, Spain. Professor of the UAB and the UVIC-UCC, Barcelone, Spain.; Hospital Universitario La Princesa, Madrid, Spain. Centro de Investigacion en Red de Enfermedades Respiratorias (CIBERES), Instituto de Salud Carlos III (ISCIII; Hospital Universitario Quironsalud, Madrid, Spain Universidad Europea, Madrid, Spain.; Infectious Diseases Department, San Carlos University Hospital. Madrid Spain.; Internal Medicine, Hospital General de Ciudad Real, Ciudad Real, Spain.; Clinical Microbiology and Infectious Diseases Department, Hospital General Universitario Gregorio Marañon, Instituto de Investigacion Sanitaria Gregorio Marañon; Internal Medicine Department, Hospital Universitario de Getafe, Madrid, Spain; Internal Medicine Department, Hospital Universitario de Getafe, Madrid, Spain. European University of Madrid, Madrid, Spain.; Department of Molecular and Cell Biology, Centro Nacional de Biotecnologia (CNBCSIC), Madrid, Spain.; Department of Molecular and Cell Biology, Centro Nacional de Biotecnologia (CNBCSIC), Madrid, Spain.; IRTA, Centre de Recerca en Sanitat Animal (CReSA, IRTA-UAB), Campus de la UAB, Bellaterra, Spain; IrsiCaixa AIDS Research Institute, 08916, Badalona, Spain. Germans Trias i Pujol Research Institute (IGTP), Can Ruti Campus, 08916, Badalona, Spain.; PharmaMar - Clinical Pharmacology Unit. Colmenar Viejo, Madrid, Spain; PharmaMar - Medical Affairs Unit. Colmenar Viejo. Madrid, Spain.; PharmaMar - Medical Affairs Unit. Colmenar Viejo, Madrid, Spain.; PharmaMar. Virology & Inflammation Dept. Colmenar Viejo, Madrid, Spain.; PharmaMar. Virology & Inflammation Dept. Colmenar Viejo, Madrid, Spain. Sylentis, S.A.U., Tres Cantos, Madrid, Spain. Biocross, S.L., Valladolid, Spain.; PharmaMar - Statistics Unit. Colmenar Viejo, Madrid, Spain.; PharmaMar - Statistics Unit. Colmenar Viejo, Madrid, Spain.; PharmaMar - Preclinical Unit. Colmenar Viejo, Madrid, Spain; PharmaMar - Clinical Pharmacology Unit. Colmenar Viejo, Madrid, Spain; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Global Health Emerging Pathogens Institute, Icahn School of Medicine at ; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Global Health Emerging Pathogens Institute, Icahn School of Medicine at ; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Global Health Emerging Pathogens Institute, Icahn School of Medicine at ; Division of Infection and Immunity, University College Londo, London, WC1E 6BT, United Kigdom.; Division of Infection and Immunity, University College Londo, London, WC1E 6BT, United Kigdom.; Division of Infection and Immunity, University College Londo, London, WC1E 6BT, United Kigdom.; Division of Infection and Immunity, University College Londo, London, WC1E 6BT, United Kigdom; Quantitative Biosciences Institute (QBI), San Francisco, CA 94158, USA. J. David Gladstone Institutes, San Francisco, CA 94158, USA. QBI, Coronavirus Research G; Quantitative Biosciences Institute (QBI), San Francisco, CA 94158, USA. J. David Gladstone Institutes, San Francisco, CA 94158, USA. QBI, Coronavirus Research G; Quantitative Biosciences Institute (QBI), San Francisco, CA 94158, USA. J. David Gladstone Institutes, San Francisco, CA 94158, USA. QBI, Coronavirus Research G; Department of Molecular and Cell Biology, Centro Nacional de Biotecnologia (CNB-CSIC), Madrid, Spain.; PharmaMar, S.A., Colmenar Viejo, Madrid, Spain.; ; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Quantitative Biosciences Institute (QBI), San Francisco, CA 94158, USA. ; PharmaMar. Virology & Inflammation Dept. Colmenar Viejo, Madrid, Spain.; Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA. Global Health Emerging Pathogens Institute, Icahn School of Medicine at ","Plitidepsin is a marine-derived cyclic-peptide that inhibits SARS-CoV-2 replication at low nanomolar concentrations by the targeting of host protein eEF1A (eukaryotic translation-elongation-factor-1A). We evaluated a model of intervention with plitidepsin in hospitalized COVID-19 adult patients where three doses were assessed (1.5, 2 and 2.5 mg/day for 3 days, as a 90-minute intravenous infusion) in 45 patients (15 per dose-cohort). Treatment was well tolerated, with only two Grade 3 treatment-related adverse events observed (hypersensitivity and diarrhea). The discharge rates by Days 8 and 15 were 56.8% and 81.8%, respectively, with data sustaining dose-effect. A mean 4.2 log10 viral load reduction was attained by Day 15. Improvement in inflammation markers was also noted in a seemingly dose-dependent manner. These results suggest that plitidepsin impacts the outcome of patients with COVID-19. One-Sentence SummaryPlitidepsin, an inhibitor of SARS-Cov-2 in vitro, is safe and positively influences the outcome of patients hospitalized with COVID-19.",infectious diseases,fuzzy,100,100 @@ -3084,28 +3077,6 @@ MethodsThe Virus Watch study is an online, prospective, community cohort study f ResultsOut of 24,887 illnesses reported, 915 tested positive for SARS-CoV-2 and 186 likely infector-infectee pairs in 186 households amongst 372 individuals were identified. The mean COVID-19 serial interval was 3.18 (95%CI: 2.55 - 3.81) days. There was no significant difference (p=0.267) between the mean serial interval for Variants of Concern (VOC) hotspots (mean = 3.64 days, (95%CI: 2.55 - 4.73)) days and non-VOC hotspots, (mean = 2.72 days, (95%CI: 1.48 - 3.96)). ConclusionsOur estimates of the average serial interval of COVID-19 are broadly similar to estimates from previous studies and we find no evidence that B.1.1.7 is associated with a change in serial intervals. Alternative explanations such as increased viral load, longer period of viral shedding or improved receptor binding may instead explain the increased transmissibility and rapid spread and should undergo further investigation.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.05.13.21257146,2021-05-17,https://medrxiv.org/cgi/content/short/2021.05.13.21257146,Sociodemographic inequality in COVID-19 vaccination coverage amongst elderly adults in England: a national linked data study,Vahe Nafilyan; Ted Dolby; Cameron Razieh; Charlotte Gaughan; Jasper Morgan; Daniel Ayoubkhani; Ann Sarah Walker; Kamlesh Khunti; Myer Glickman; Thomas Yates,"Office for National Statistics; Office for National Statistics; Diabetes Research Centre, University of Leicester; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Diabetes Research Centre, University of Leicester; Office for National Statistics; Diabetes Research Centre, University of Leicester","ObjectiveTo examine inequalities in COVID-19 vaccination rates amongst elderly adults in England - -DesignCohort study - -SettingPeople living in private households and communal establishments in England - -Participants6,829,643 adults aged [≥] 70 years (mean 78.7 years, 55.2% female) who were alive on 15 March 2021. - -Main outcome measuresHaving received the first dose of a vaccine against COVID-19 by 15 March 2021. We calculated vaccination rates and estimated unadjusted and adjusted odds ratios using logistic regression models. - -ResultsBy 15 March 2021, 93.2% of people living in England aged 70 years and over had received at least one dose of a COVID-19 vaccine. While vaccination rates differed across all factors considered apart from sex, the greatest disparities were seen between ethnic and religious groups. The lowest rates were in people of Black African and Black Caribbean ethnic backgrounds, where only 67.2% and 73.9% had received a vaccine, with adjusted odds of not being vaccinated at 5.01 (95% CI 4.86 - 5.16) and 4.85 (4.75 - 4.96) times greater than the White British group. The proportion of individuals self-identifying as Muslim and Buddhist who had received a vaccine was 79.1% and 84.1%, respectively. Older age, greater area deprivation, less advantaged socio-economic position (proxied by living in a rented home), being disabled and living either alone or in a multi-generational household were also associated with higher odds of not having received the vaccine. - -ConclusionPeople disproportionately affected seem most hesitant to COVID-19 vaccinations. Policy Interventions to improve these disparities are urgently needed. - -Summary BoxO_ST_ABSWhat is already known on this subject?C_ST_ABSThe UK began an ambitious vaccination programme to combat the COVID-19 pandemic on 8th December 2020. Existing evidence suggests that COVID-19 vaccination rates differ by level of area deprivation, ethnicity and certain underlying health conditions, such as learning disability and mental health problems. - -What does this study add?Our study shows that first dose vaccination rates in adults aged 70 or over differed markedly by ethnic group and self-reported religious affiliation, even after adjusting for geography, socio-demographic factors and underlying health conditions. Our study also highlights differences in vaccination rates by deprivation, household composition, and disability status, factors disproportionately associated with SARS-CoV-2 infection. Public health policy and community engagement aimed at promoting vaccination uptake is these groups are urgently needed. - -Strengths and limitations of this studyO_LIUsing nationwide linked population-level data from clinical records and the 2011 Census, we examined a wide range of socio-demographic characteristics not available n electronic health records -C_LIO_LIMost demographic and socio-economic characteristics are derived from the 2011 Census and therefore are 10 years old. However, we focus primarily on characteristics that are unlikely to change over time, such as ethnicity or religion, or likely to be stable for our population -C_LIO_LIBecause the data are based on the 2011 Census, it excluded people living in England in 2011 but not taking part in the 2011 Census; respondents who could not be linked to the 2011-2013 NHS patients register; recent migrants. Consequently, we excluded 5.4% of vaccinated people who could not be linked -C_LI",public and global health,fuzzy,100,100 medRxiv,10.1101/2021.05.12.21257102,2021-05-15,https://medrxiv.org/cgi/content/short/2021.05.12.21257102,"Spike-antibody responses following first and second doses of ChAdOx1 and BNT162b2 vaccines by age, gender, and clinical factors - a prospective community cohort study (Virus Watch)",Madhumita Shrotri; Ellen Fragaszy; Cyril Geismar; Vincent Nguyen; Sarah Beale; Isobel Braithwaite; Thomas Edward Byrne; Wing Lam Erica Fong; Jana Kovar; Annalan M D Navaratnam; Parth Patel; Anna Aryee; Jamie Lopez Bernal; Anne M Johnson; Alison Rodger; Andrew C Hayward; Robert W Aldridge,University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; Public Health England; University College London; University College London; University College London; University College London,"BackgroundVaccination constitutes the best long-term solution against Coronavirus Disease 2019 (COVID-19). Real-world immunogenicity data are sparse, particularly for ChAdOx1 and in populations with chronic conditions; and given the UKs extended dosing interval, it is also important to understand antibody responses in SARS-CoV-2-naive individuals following a single dose. MethodsAdults aged [≥]18 years from households enrolled in Virus Watch, a prospective community cohort study in England and Wales, provided capillary blood samples and self-reported vaccination status. Primary outcome variables were quantitative Spike total antibody levels (U/ml) and seropositivity to Spike ([≥]0.8 U/ml), as per Roches Elecsys Anti-SARS-CoV-2 S assay. Samples seropositive for Nucleocapsid, and samples taken prior to vaccination, were excluded. Outcomes were analysed by days since vaccination, vaccine type (BNT162b2 and ChAdOx1), and a range of self-reported demographic and clinical factors. @@ -3187,6 +3158,9 @@ MethodsGlobal cross-sectional study using a primary outcome of self-reported wor Results4,043 people with psoriasis (without COVID-19) from 86 countries self-reported to PsoProtectMe (mean age 47.2 years [SD 15.1]; mean BMI 27.6kg/m2 [SD 6.0], 2,684 [66.4%] female and 3,016 [74.6%] of white European ethnicity). 1,728 (42.7%) participants (1322 [77%] female) reported worsening of their psoriasis in the pandemic. A positive screen for anxiety or depression associated with worsening psoriasis in age and gender adjusted (OR 2.04, 95% CI 1.77-2.36), and fully adjusted (OR 2.01, 95% CI 1.72-2.34) logistic regression models. Female sex, obesity, shielding behaviour and systemic immunosuppressant non-adherence also associated with worsening psoriasis. The commonest reason for non-adherence was concern regarding complications related to COVID-19. ConclusionsThese data indicate an association between poor mental health and worsening psoriasis in the pandemic. Access to holistic care including psychological support may mitigate potentially long-lasting effects of the pandemic on health outcomes in psoriasis. The study also highlights an urgent need to address patient concerns about immunosuppressant-related risks, which may be contributing to non-adherence.",dermatology,fuzzy,100,100 +medRxiv,10.1101/2021.04.28.21256261,2021-05-02,https://medrxiv.org/cgi/content/short/2021.04.28.21256261,Aspirin and NSAID use and the risk of COVID-19,David Alden Drew; Chuan-Guo Guo; Karla Lee; Long Nguyen; Amit D Joshi; Chun-Han Lo; Wenjie Ma; Raaj S Mehta; Sohee Kwon; Christina M Astley; Mingyang Song; Richard Davies; Joan Capdevila; Mary M Ni Lochlainn; Carole Sudre; Mark S Graham; Thomas Varsavsky; Maria F. Gomez; Beatrice Kennedy; Hugo Fitipaldi; Jonathan Wolf; Timothy Spector; Sebastien Ourselin; Claire Steves; Andrew T. Chan,Massachusetts General Hospital; Massachusetts General Hospital; Department of Twin Research and Genetic Epidemiology; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Boston Children's Hospital; Massachusetts General Hospital; Zoe Global Ltd.; Zoe Global Ltd; King's College London; Kings College London; King's College London; Kings College London; Lund University; Uppsala University; Lund University; Zoe Global Ltd.; King's College London; King's College London; King's College London; Massachusetts General Hospital,"Early reports raised concern that use of non-steroidal anti-inflammatory drugs (NSAIDs) may increase risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19). Users of the COVID Symptom Study smartphone application reported use of aspirin and other NSAIDs between March 24 and May 8, 2020. Users were queried daily about symptoms, COVID-19 testing, and healthcare seeking behavior. Cox proportional hazards regression was used to determine the risk of COVID-19 among according to aspirin or non-aspirin NSAID users. Among 2,736,091 individuals in the U.S., U.K., and Sweden, we documented 8,966 incident reports of a positive COVID-19 test over 60,817,043 person-days of follow-up. Compared to non-users and after stratifying by age, sex, country, day of study entry, and race/ethnicity, non-aspirin NSAID use was associated with a modest risk for testing COVID-19 positive (HR 1.23 [1.09, 1.32]), but no significant association was observed among aspirin users (HR 1.13 [0.92, 1.38]). After adjustment for lifestyle factors, comorbidities and baseline symptoms, any NSAID use was not associated with risk (HR 1.02 [0.94, 1.10]). Results were similar for those seeking healthcare for COVID-19 and were not substantially different according to lifestyle and sociodemographic factors or after accounting for propensity to receive testing. Our results do not support an association of NSAID use, including aspirin, with COVID-19 infection. Previous reports of a potential association may be due to higher rates of comorbidities or use of NSAIDs to treat symptoms associated with COVID-19. + +One Sentence SummaryNSAID use is not associated with COVID-19 risk.",epidemiology,fuzzy,94,100 medRxiv,10.1101/2021.04.30.21256119,2021-04-30,https://medrxiv.org/cgi/content/short/2021.04.30.21256119,Association between oral anticoagulants and COVID-19 related outcomes: two cohort studies,Angel YS Wong; Laurie Tomlinson; Jeremy P Brown; William Elson; Alex J Walker; Anna J Schultze; Caroline E Morton; David Evans; Peter Inglesby; Brian MacKenna; Krishnan Bhaskaran; Christopher T. Rentsch; Emma Powell; Elizabeth T. Williamson; Richard Croker; Seb Bacon; William Hulme; Chris Bates; Helen J Curtis; Amir Mehrkar; Jonathan Cockburn; Helen I McDonald; Rohini I Mathur; Kevin Wing; Harriet Forbes; Rosalind M Eggo; Stephen Evans; Liam Smeeth; Ben Goldacre; Ian J Douglas,"London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Trop. Med.; University of Oxford; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; TPP; London School of Medicine and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Bristol; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine","ObjectivesWe investigated the role of routinely prescribed oral anticoagulants (OACs) in COVID-19 outcomes, comparing current OAC use versus non-use in Study 1; and warfarin versus direct oral anticoagulants (DOACs) in Study 2. DesignTwo cohort studies, on behalf of NHS England. @@ -3509,6 +3483,7 @@ MethodsA national record linkage study determined documented COVID-19 cases and ResultsThe cohort comprised of 194,362 household members (mean age 31{middle dot}1 {+/-} 20{middle dot}9 years) and 144,525 healthcare workers (mean age 44{middle dot}4 {+/-} 11{middle dot}4 years). 113,253 (78{middle dot}3%) of healthcare workers received at least one dose of the BNT162b2 mRNA or ChAdOx1 nCoV-19 vaccine and 36,227 (25{middle dot}1%) received a second dose. There were 3,123 and 4,343 documented COVID-19 cases and 175 and 177 COVID-19 hospitalisations in household members of healthcare workers and healthcare workers respectively. Household members of vaccinated healthcare workers had a lower risk of COVID-19 case compared to household members of unvaccinated healthcare worker (rate per 100 person-years 9{middle dot}40 versus 5{middle dot}93; HR 0{middle dot}70, 95% confidence interval [CI] 0{middle dot}63 to 0{middle dot}78). The effect size for COVID-19 hospitalisation was similar, with the confidence interval crossing the null (HR 0{middle dot}77 [95% CI 0{middle dot}53 to 1{middle dot}10]). The rate per 100 person years was lower in vaccinated compared to unvaccinated healthcare workers for documented (20{middle dot}13 versus 8{middle dot}51; HR 0{middle dot}45 [95% CI 0{middle dot}42 to 0{middle dot}49]) and hospitalized COVID-19 (0{middle dot}97 versus 0{middle dot}14; HR 0{middle dot}16 [95% CI 0{middle dot}09 to 0{middle dot}27]). Compared to the period before the first dose, the risk of documented COVID-19 case was lower at [≥] 14 days after the second dose for household members (HR 0{middle dot}46 [95% CI 0{middle dot}30to 0{middle dot}70]) and healthcare workers (HR 0{middle dot}08 [95% CI 0{middle dot}04 to 0{middle dot}17]). InterpretationVaccination of health care workers was associated with a substantial reduction in COVID-19 cases in household contacts consistent with an effect of vaccination on transmission.",public and global health,fuzzy,100,100 +medRxiv,10.1101/2021.03.17.21253853,2021-03-20,https://medrxiv.org/cgi/content/short/2021.03.17.21253853,"Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest optimal policies varies with rural-urban settings",Xilin Jiang; Wenfeng Gong; Zlatina Dobreva; Ya Gao; Matthew Quaife; Christophe Fraser; Chris Holmes,"University of Oxford; Bill & Melinda Gates Foundation; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; Department of International Health, Johns Hopkins University; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; University of Oxford; University of Oxford","Low- and middle-income countries (LMICs) remain of high potential for hotspots for COVID-19 deaths and emerging variants given the inequality of vaccine distribution and their vulnerable healthcare systems. We aim to evaluate containment strategies that are sustainable and effective for LMICs. We constructed synthetic populations with varying contact and household structures to capture LMIC demographic characteristics that vary across communities. Using an agent- based model, we explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic tests, symptom screening, contact tracing and physical distancing. In low-density rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. In urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In high density communities that resemble slums and squatter settlements, physical distancing is less effective compared to rural and urban communities. Lastly, we demonstrated contact tracing is essential for effective containment. Our findings suggested that rapid diagnostic tests could be prioritised for control and monitor COVID-19 transmission and highlighted that contact survey data could guide strategy design to save resources for LMICs. An accompanying open source R package is available for simulating COVID-19 transmission based on contact network models.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.03.18.21253443,2021-03-20,https://medrxiv.org/cgi/content/short/2021.03.18.21253443,Intensity of COVID-19 in care homes following Hospital Discharge in the early stages of the UK epidemic,Joe Hollinghurst; Laura North; Chris Emmerson; Ashley Akbari; Fatemeh Torabi; Ronan A Lyons; Alan G Hawkes; Ed Bennett; Mike B Gravenor; Richard Fry,Swansea University; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University,"BackgroundA defining feature of the COVID-19 pandemic in many countries was the tragic extent to which care home residents were affected, and the difficulty preventing introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was transfer of patients from hospitals, which were experiencing high levels of nosocomial events. MethodsWe tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in cases rates following exposure to a hospital discharge using multi-level hierarchical logistic regression, and a novel stochastic Hawkes process outbreak model. @@ -3683,25 +3658,6 @@ MethodsAll 178578 diagnosed cases of COVID-19 in Scotland from 1 March 2020 to 1 ResultsWith those without risk conditions as reference category, the univariate rate ratio for severe COVID-19 was 3.21 (95% CI 3.01 to 3.41) in those with moderate risk conditions and 6.3 (95% CI 5.8 to 6.8) in those eligible for shielding. The highest rate was in solid organ transplant recipients: rate ratio 13.4 (95% CI 9.6 to 18.8). Risk of severe COVID-19 increased with the number of adults but decreased with the number of school-age children in the household. Severe COVID-19 was strongly associated with recent exposure to hospital (defined as 5 to 14 days before presentation date): rate ratio 12.3 (95% CI 11.5 to 13.2) overall. To test for causality, a case-crossover analysis was undertaken; with less recent exposure only (15 to 24 days before first testing positive) as reference category, the rate ratio associated with recent exposure only was 5.9 (95% CI 3.6 to 9.7). The population attributable risk fraction for recent exposure to hospital peaked at 50% in May 2020 and again at 65% in December 2020. ConclusionsThe effectiveness of shielding vulnerable individuals was limited by the inability to control transmission in hospital and from other adults in the household. For solid organ transplant recipients, in whom the efficacy of vaccines is uncertain, these results support a policy of offering vaccination to household contacts. Mitigating the impact of the epidemic requires control of nosocomial transmission.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.02.27.21252593,2021-03-01,https://medrxiv.org/cgi/content/short/2021.02.27.21252593,Surgical activity in England and Wales during the COVID-19 pandemic: a nationwide observational cohort study,Thomas D Dobbs; John A G Gibson; Alexander J Fowler; Tom E Abbott; Tasnin Shahid; Fatemeh Torabi; Rowena Griffiths; Ronan A Lyons; Rupert M Pearse; Iain S Whitaker,"Swansea University Medical School; Swansea University Medical School; Queen Mary, University of London; Queen Mary University of London; Queen Mary University of London; Swansea University; Swansea University; Swansea University; Queen Mary University of London; Swansea University Medical School","ObjectivesTo report the volume of surgical activity and the number of cancelled surgical procedures during the COVID-19 pandemic. - -Design and settingAnalysis of electronic health record data from the National Health Service (NHS) in England and Wales. - -MethodsWe used hospital episode statistics for all adult patients undergoing surgery between 1st January 2020 and 31st December 2020. We identified surgical procedures using a previously published list of procedure codes. Procedures were stratified by urgency of surgery as defined by NHS England. We calculated the deficit of surgical activity by comparing the expected number of procedures from the years 2016-2019 with the actual number of procedures in 2020. We estimated the cumulative number of cancelled procedures by 31st December 2021 according patterns of activity in 2020. - -ResultsThe total number of surgical procedures carried out in England and Wales in 2020 was 3,102,674 compared to the predicted number of 4,671,338. This represents a 33.6% reduction in the national volume of surgical activity. There were 763,730 emergency surgical procedures (13.4% reduction), compared to 2,338,944 elective surgical procedures (38.6% reduction). The cumulative number of cancelled or postponed procedures was 1,568,664. We estimate that this will increase to 2,358,420 by 31st December 2021. - -ConclusionsThe volume of surgical activity in England and Wales was reduced by 33.6% in 2020, resulting in over 1,568,664 cancelled operations. This deficit will continue to grow in 2021. - -Summary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIThe COVID-19 pandemic necessitated a rapid change in the provision of care, including the suspension of a large proportion of surgical activity -C_LIO_LISurgical activity has yet to return to normal and has been further impacted by subsequent waves of the pandemic -C_LIO_LIThis will lead to a large backlog of cases -C_LI - -What this study addsO_LI3,102,674 surgical procedures were performed in England and Wales during 2020, a 33.6% reduction on the expected yearly surgical activity -C_LIO_LIOver 1.5 million procedures were not performed, with this deficit likely to continue to grow to 2.3 million by the end of 2021 -C_LIO_LIThis deficit is the equivalent of more than 6 months of pre-pandemic surgical activity, requiring a monumental financial and logistic challenge to manage -C_LI",surgery,fuzzy,100,100 medRxiv,10.1101/2021.02.26.21252512,2021-03-01,https://medrxiv.org/cgi/content/short/2021.02.26.21252512,REACT-2 Round 5: increasing prevalence of SARS-CoV-2 antibodies demonstrate impact of the second wave and of vaccine roll-out in England,Helen Ward Professor; Graham Cooke Professor; Matthew Whitaker Mr; Rozlyn Redd Dr; Oliver Eales Mr; Jonathan Brown Mr; Katharine Collet Ms; Emily Cooper Ms; Daunt Anna Dr; Jones Kathryn Dr; Moshe Maya Ms; Michelle Willicombe Dr; Sophie Day Professor; Christina Atchison Dr; Ara Darzi Professor; Christl A Donnelly Professor; Steven Riley Professor; Deborah Ashby Professor; Wendy S Barclay Professor; Paul Elliott Professor,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"BackgroundEngland has experienced high rates of SARS-CoV-2 infection during the COVID-19 pandemic, affecting in particular minority ethnic groups and more deprived communities. A vaccination programme began in England in December 2020, with priority given to administering the first dose to the largest number of older individuals, healthcare and care home workers. MethodsA cross-sectional community survey in England undertaken between 26 January and 8 February 2021 as the fifth round of the REal-time Assessment of Community Transmission-2 (REACT-2) programme. Participants completed questionnaires, including demographic details and clinical and COVID-19 vaccination histories, and self-administered a lateral flow immunoassay (LFIA) test to detect IgG against SARS-CoV-2 spike protein. There were sufficient numbers of participants to analyse antibody positivity after 21 days from vaccination with the PfizerBioNTech but not the AstraZeneca/Oxford vaccine which was introduced slightly later. @@ -3833,6 +3789,11 @@ MethodsWorking on behalf of NHS England, we used data from the OpenSAFELY platfo ResultsFor all outcomes except death there was a lower count of events in April 2020 compared to April 2019. For most outcomes the minimum count of events was in April 2020, where the decrease compared to April 2019 in events ranged from 5.9% (PE) to 40.0% (heart failure). Despite hospitalised COVID-19 patients making up just 0.14% of the population in April 2020, these patients accounted for an extremely high proportion of cardiometabolic and respiratory events in that month (range of proportions 10.3% (DVT) to 33.5% (AKI)). InterpretationWe observed a substantial drop in the incidence of cardiometabolic and pulmonary events in the non-COVID-19 general population, but high occurrence of COVID-19 among patients with these events. Shortcomings in routine NHS secondary care data, especially around the timing and order of events, make causal interpretations challenging. We caution that the intermediate findings reported here should be used to inform the design and interpretation of any studies using a general population comparator to evaluate the relationship between COVID-19 and other clinical events.",epidemiology,fuzzy,100,100 +medRxiv,10.1101/2021.02.10.21251484,2021-02-16,https://medrxiv.org/cgi/content/short/2021.02.10.21251484,An analysis of school absences in England during the Covid-19 pandemic,Emma R Southall; Alex Holmes; Edward M Hill; Benjamin D Atkins; Trystan Leng; Robin N Thompson; Louise J Dyson; Matt J Keeling; Michael Tildesley,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"The introduction of SARS-CoV-2, the virus that causes COVID-19 infection, in the UK in early 2020, resulted in the UK government introducing several control policies in order to reduce the spread of disease. As part of these restrictions, schools were closed to all pupils in March (except for vulnerable and key worker children), before re-opening to certain year groups in June. Finally all school children returned to the classroom in September. In this paper, we analyse the data on school absences from September 2020 to December 2020 as a result of COVID-19 infection and how that varied through time as other measures in the community were introduced. We utilise data from the Educational Settings database compiled by the Department for Education and examine how pupil and teacher absences change in both primary and secondary schools. + +Our results show that absences as a result of COVID-19 infection rose steadily following the re-opening of schools in September. Cases in teachers were seen to decline during the November lockdown, particularly in those regions that had previously been in tier 3, the highest level of control at the time. Cases in secondary school pupils increased for the first two weeks of the November lockdown, before decreasing. Since the introduction of the tier system, the number of absences owing to confirmed infection in primary schools was observed to be significantly lower than in secondary schools across all regions and tiers. + +In December, we observed a large rise in the number of absences per school in secondary school settings in the South East and Greater London, but such rises were not observed in other regions or in primary school settings. We conjecture that the increased transmissibility of the new variant in these regions may have contributed to this rise in cases in secondary schools. Finally, we observe a positive correlation between cases in the community and cases in schools in most regions, with weak evidence suggesting that cases in schools lag behind cases in the surrounding community. We conclude that there is not significant evidence to suggest that schools are playing a significant role in driving spread in the community and that careful monitoring may be required as schools re-open to determine the effect associated with open schools upon community incidence.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.02.10.21251480,2021-02-12,https://medrxiv.org/cgi/content/short/2021.02.10.21251480,Symptom reporting in over 1 million people: community detection of COVID-19,Joshua Elliott; Matthew Whitaker; Barbara Bodinier; Steven Riley; Helen Ward; Graham Cooke; Ara Darzi; Marc Chadeau-Hyam; Paul Elliott,Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London,,infectious diseases,fuzzy,96,100 medRxiv,10.1101/2021.02.11.21251587,2021-02-12,https://medrxiv.org/cgi/content/short/2021.02.11.21251587,Assessing the impact of secondary school reopening strategies on within-school COVID-19 transmission and absences: a modelling study,Trystan Leng; Edward M Hill; Robin N Thompson; Michael J Tildesley; Matt J Keeling; Louise J Dyson,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,,infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.02.11.21249258,2021-02-11,https://medrxiv.org/cgi/content/short/2021.02.11.21249258,"Tocilizumab in patients admitted to hospital with COVID-19 (RECOVERY): preliminary results of a randomised, controlled, open-label, platform trial",Peter W Horby; Mark Campbell; Natalie Staplin; Enti Spata; Jonathan R Emberson; Guilherme Pessoa-Amorim; Leon Peto; Christopher E Brightling; Rahuldeb Sarkar; Koshy Thomas; Vandana Jeebun; Abdul Ashish; Redmond Tully; David Chadwick; Muhammad Sharafat; Richard Stewart; Banu Rudran; J Kenneth Baillie; Maya H Buch; Lucy C Chappell; Jeremy N Day; Saul N Furst; Thomas Jaki; Katie Jeffery; Edmund Juszczak; Wei Shen Lim; Alan Montgomery; Andrew Mumford; Kathryn Rowan; Guy Thwaites; Marion Mafham; Richard Haynes; Martin J Landray,"Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Institute for Lung Health, Leicester NIHR Biomedical Research Centre, University of Leicester, Leicester, United Kingdom; Medway Foundation NHS Trust, Gillingham, United Kingdom; King?s College London, London, United Kingdom; Basildon and Thurrock Hospitals NHS Foundation Trust, Basildon, United Kingdom; Department of Respiratory Medicine, North Tees & Hartlepool NHS Foundation Trust, Stockton-on-Tees, United Kingdom; Wrightington Wigan and Leigh NHS Foundation Trust, Wigan, United Kingdom; Royal Oldham Hospital, Northern Care Alliance, Oldham, United Kingdom; Centre for Clinical Infection, James Cook University Hospital, Middlesbrough, United Kingdom; North West Anglia NHS Foundation Trust, Peterborough, United Kingdom; Milton Keynes University Hospital, Milton Keynes, United Kingdom; Luton & Dunstable University Hospital, Luton, United Kingdom; Roslin Institute, University of Edinburgh, Edinburgh, United Kingdom; Centre for Musculoskeletal Research, University of Manchester, Manchester, United Kingdom; School of Life Sciences, Kings College London, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; NIHR Southampton Clinical Research Facility and Biomedical Research Centre, University Hospital Southampton NHS Foundation Trust and University of Southampton, ; Department of Mathematics and Statistics, Lancaster University, Lancaster, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; Respiratory Medicine Department, Nottingham University Hospitals NHS Foundation Trust, Nottingham, United Kingdom; School of Medicine, University of Nottingham, Nottingham, United Kingdom; School of Cellular and Molecular Medicine, University of Bristol, Bristol, United Kingdom; Intensive Care National Audit and Research Centre, London, United Kingdom; Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam, and Nuffield Department of Medicine, University of Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; MRC Population Health Research Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom; Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom","Findings: Between 23 April 2020 and 25 January 2021, 4116 adults were included in the assessment of tocilizumab, including 562 (14%) patients receiving invasive mechanical ventilation, 1686 (41%) receiving non-invasive respiratory support, and. 1868 (45%) receiving no respiratory support other than oxygen. Median CRP was 143 [IQR 107-205] mg/L and 3385 (82%) patients were receiving systemic corticosteroids at randomisation. Overall, 596 (29%) of the 2022 patients allocated tocilizumab and 694 (33%) of the 2094 patients allocated to usual care died within 28 days (rate ratio 0.86; 95% confidence interval [CI] 0.77-0.96; p=0.007). Consistent results were seen in all pre-specified subgroups of patients, including those receiving systemic corticosteroids. Patients allocated to tocilizumab were more likely to be discharged from hospital alive within 28 days (54% vs. 47%; rate ratio 1.23; 95% CI 1.12-1.34; p<0.0001). Among those not receiving invasive mechanical ventilation at baseline, patients allocated tocilizumab were less likely to reach the composite endpoint of invasive mechanical ventilation or death (33% vs. 38%; risk ratio 0.85; 95% CI 0.78-0.93; p=0.0005). Interpretation: In hospitalised COVID-19 patients with hypoxia and systemic inflammation, tocilizumab improved survival and other clinical outcomes regardless of the level of respiratory support received and in addition to the use of systemic corticosteroids.",infectious diseases,fuzzy,100,100 @@ -3924,9 +3885,21 @@ Research in contextO_ST_ABSEvidence before this studyC_ST_ABSA recent systematic Added value of this studyUsing data from the Office for National Statistics (ONS) Public Health Data Asset on 29 million adults aged 30-100 years living in private households in England, we conducted an observational cohort study to examine the differences in the risk of death involving COVID-19 between ethnic groups in the first wave (from 24th January 2020 until 31st August 2020) and second wave (from 1st September to 28th December 2020). We find that in the first wave all ethnic minority groups were at elevated risk of COVID-19 related death compared to the White British population. In the second wave, the differences in the risk of COVID-19 related death attenuated for Black African and Black Caribbean groups, remained substantially higher in people from Bangladeshi background, and worsened in people from Pakistani background. We also find that some of the factors explaining these differences in mortality have changed in the two waves. Implications of all the available evidenceThe risk of COVID-19 mortality during the first wave of the pandemic was elevated in people from ethnic minority background. An appreciable reduction in the difference in COVID-19 mortality in the second wave of the pandemic between people from Black ethnic background and people from the White British group is reassuring, but the continued higher rate of mortality in people from Bangladeshi and Pakistani background is alarming and requires focused public health campaign and policy response. Focusing on treating underlying conditions, although important, may not be enough in reducing the inequalities in COVID-19 mortality. Focused public health policy as well as community mobilisation and participatory public health campaign involving community leaders may help reduce the existing and widening inequalities in COVID-19 mortality.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2021.02.03.21250974,2021-02-05,https://medrxiv.org/cgi/content/short/2021.02.03.21250974,Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US,Estee Y Cramer; Evan L Ray; Velma K Lopez; Johannes Bracher; Andrea Brennen; Alvaro J Castro Rivadeneira; Aaron Gerding; Tilmann Gneiting; Katie H House; Yuxin Huang; Dasuni Jayawardena; Abdul H Kanji; Ayush Khandelwal; Khoa Le; Anja Muehlemann; Jarad Niemi; Apurv Shah; Ariane Stark; Yijin Wang; Nutcha Wattanachit; Martha W Zorn; Youyang Gu; Sansiddh Jain; Nayana Bannur; Ayush Deva; Mihir Kulkarni; Srujana Merugu; Alpan Raval; Siddhant Shingi; Avtansh Tiwari; Jerome White; Neil F Abernethy; Spencer Woody; Maytal Dahan; Spencer Fox; Kelly Gaither; Michael Lachmann; Lauren Ancel Meyers; James G Scott; Mauricio Tec; Ajitesh Srivastava; Glover E George; Jeffrey C Cegan; Ian D Dettwiller; William P England; Matthew W Farthing; Robert H Hunter; Brandon Lafferty; Igor Linkov; Michael L Mayo; Matthew D Parno; Michael A Rowland; Benjamin D Trump; Yanli Zhang-James; Samuel Chen; Stephen V Faraone; Jonathan Hess; Christopher P Morley; Asif Salekin; Dongliang Wang; Sabrina M Corsetti; Thomas M Baer; Marisa C Eisenberg; Karl Falb; Yitao Huang; Emily T Martin; Ella McCauley; Robert L Myers; Tom Schwarz; Daniel Sheldon; Graham Casey Gibson; Rose Yu; Liyao Gao; Yian Ma; Dongxia Wu; Xifeng Yan; Xiaoyong Jin; Yu-Xiang Wang; YangQuan Chen; Lihong Guo; Yanting Zhao; Quanquan Gu; Jinghui Chen; Lingxiao Wang; Pan Xu; Weitong Zhang; Difan Zou; Hannah Biegel; Joceline Lega; Steve McConnell; VP Nagraj; Stephanie L Guertin; Christopher Hulme-Lowe; Stephen D Turner; Yunfeng Shi; Xuegang Ban; Robert Walraven; Qi-Jun Hong; Stanley Kong; Axel van de Walle; James A Turtle; Michal Ben-Nun; Steven Riley; Pete Riley; Ugur Koyluoglu; David DesRoches; Pedro Forli; Bruce Hamory; Christina Kyriakides; Helen Leis; John Milliken; Michael Moloney; James Morgan; Ninad Nirgudkar; Gokce Ozcan; Noah Piwonka; Matt Ravi; Chris Schrader; Elizabeth Shakhnovich; Daniel Siegel; Ryan Spatz; Chris Stiefeling; Barrie Wilkinson; Alexander Wong; Sean Cavany; Guido Espana; Sean Moore; Rachel Oidtman; Alex Perkins; David Kraus; Andrea Kraus; Zhifeng Gao; Jiang Bian; Wei Cao; Juan Lavista Ferres; Chaozhuo Li; Tie-Yan Liu; Xing Xie; Shun Zhang; Shun Zheng; Alessandro Vespignani; Matteo Chinazzi; Jessica T Davis; Kunpeng Mu; Ana Pastore y Piontti; Xinyue Xiong; Andrew Zheng; Jackie Baek; Vivek Farias; Andreea Georgescu; Retsef Levi; Deeksha Sinha; Joshua Wilde; Georgia Perakis; Mohammed Amine Bennouna; David Nze-Ndong; Divya Singhvi; Ioannis Spantidakis; Leann Thayaparan; Asterios Tsiourvas; Arnab Sarker; Ali Jadbabaie; Devavrat Shah; Nicolas Della Penna; Leo A Celi; Saketh Sundar; Russ Wolfinger; Dave Osthus; Lauren Castro; Geoffrey Fairchild; Isaac Michaud; Dean Karlen; Matt Kinsey; Luke C. Mullany; Kaitlin Rainwater-Lovett; Lauren Shin; Katharine Tallaksen; Shelby Wilson; Elizabeth C Lee; Juan Dent; Kyra H Grantz; Alison L Hill; Joshua Kaminsky; Kathryn Kaminsky; Lindsay T Keegan; Stephen A Lauer; Joseph C Lemaitre; Justin Lessler; Hannah R Meredith; Javier Perez-Saez; Sam Shah; Claire P Smith; Shaun A Truelove; Josh Wills; Maximilian Marshall; Lauren Gardner; Kristen Nixon; John C. Burant; Lily Wang; Lei Gao; Zhiling Gu; Myungjin Kim; Xinyi Li; Guannan Wang; Yueying Wang; Shan Yu; Robert C Reiner; Ryan Barber; Emmanuela Gaikedu; Simon Hay; Steve Lim; Chris Murray; David Pigott; Heidi L Gurung; Prasith Baccam; Steven A Stage; Bradley T Suchoski; B. Aditya Prakash; Bijaya Adhikari; Jiaming Cui; Alexander Rodriguez; Anika Tabassum; Jiajia Xie; Pinar Keskinocak; John Asplund; Arden Baxter; Buse Eylul Oruc; Nicoleta Serban; Sercan O Arik; Mike Dusenberry; Arkady Epshteyn; Elli Kanal; Long T Le; Chun-Liang Li; Tomas Pfister; Dario Sava; Rajarishi Sinha; Thomas Tsai; Nate Yoder; Jinsung Yoon; Leyou Zhang; Sam Abbott; Nikos I Bosse; Sebastian Funk; Joel Hellewell; Sophie R Meakin; Katharine Sherratt; Mingyuan Zhou; Rahi Kalantari; Teresa K Yamana; Sen Pei; Jeffrey Shaman; Michael L Li; Dimitris Bertsimas; Omar Skali Lami; Saksham Soni; Hamza Tazi Bouardi; Turgay Ayer; Madeline Adee; Jagpreet Chhatwal; Ozden O Dalgic; Mary A Ladd; Benjamin P Linas; Peter Mueller; Jade Xiao; Yuanjia Wang; Qinxia Wang; Shanghong Xie; Donglin Zeng; Alden Green; Jacob Bien; Logan Brooks; Addison J Hu; Maria Jahja; Daniel McDonald; Balasubramanian Narasimhan; Collin Politsch; Samyak Rajanala; Aaron Rumack; Noah Simon; Ryan J Tibshirani; Rob Tibshirani; Valerie Ventura; Larry Wasserman; Eamon B O'Dea; John M Drake; Robert Pagano; Quoc T Tran; Lam Si Tung Ho; Huong Huynh; Jo W Walker; Rachel B Slayton; Michael A Johansson; Matthew Biggerstaff; Nicholas G Reich,"University of Massachusetts, Amherst; University of Massachusetts, Amherst; Centers for Disease Control and Prevention; Chair of Econometrics and Statistics, Karlsruhe Institute of Technology; Computational Statistics Group, Heidelberg Institute for Theoretical Studies; IQT; University of Massachusetts, Amherst; University of Massachusetts, Amherst; Institute of Stochastics, Karlsruhe Institute of Technology; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; Institute of Mathematical Statistics and Actuarial Science, University of Bern; Iowa State University; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; Unaffiliated; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; University of Washington; University of Texas at Austin; Texas Advanced Computing Center; University of Texas at Austin; Texas Advanced Computing Center; Santa Fe Institute; University of Texas at Austin; University of Texas at Austin; University of Texas at Austin; University of Southern California; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; State University of New York Upstate Medical University; State University of New York Upstate Medical University; State University of New York Upstate Medical University; State University of New York Upstate Medical University; State University of New York Upstate Medical University; Syracuse University; State University of New York Upstate Medical University; University of Michigan - Ann Arbor; Trinity University, San Antonio; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Massachusetts, Amherst; University of Massachusetts, Amherst; Northeastern University; University of California, San Diego; University of Washington; University of California, San Diego; University of California, San Diego; University of California at Santa Barbara; University of California at Santa Barbara; University of California at Santa Barbara; University of California, Merced; Jilin University; University of Science and Technology of China; University of California, Los Angeles; University of California, Los Angeles; University of California, Los Angeles; University of California, Los Angeles; University of California, Los Angeles; University of California, Los Angeles; University of Arizona; University of Arizona; Construx; Signature Science, LLC; Signature Science, LLC; Signature Science, LLC; Signature Science, LLC; Rensselaer Polytechnic Institute; University of Washington; Unaffiliated; Arizona State University; Brown University; Manhasset Secondary School; Brown University; Predictive Science, Inc; Predictive Science, Inc; Imperial College, London; Predictive Science, Inc; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; University of Notre Dame; University of Notre Dame; University of Notre Dame; University of Chicago; University of Notre Dame; University of Notre Dame; Masaryk University; Masaryk University; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; ISI Foundation; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Operations Research Center, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Sloan School of Management, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Sloan School of Management, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Massachusetts Institute of Technology; Massachusetts Institute of Technology; Massachusetts Institute of Technology; New York University; Massachusetts Institute of Technology; Massachusetts Institute of Technology; Massachusetts Institute of Technology; Institute for Data, Systems, and Society, Massachusetts Institute of Technology; Institute for Data, Systems, and Society, Massachusetts Institute of Technology; Institute for Data, Systems, and Society, Massachusetts Institute of Technology; Laboratory for Computational Physiology, Massachusetts Institute of Technology; Laboratory for Computational Physiology, Massachusetts Institute of Technology; River Hill High School; SAS Institute Inc; Los Alamos National Laboratory; Los Alamos National Laboratory; Los Alamos National Laboratory; Los Alamos National Laboratory; TRIUMF; University of Victoria; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; Unaffiliated; University of Utah; Johns Hopkins Bloomberg School of Public Health; Ecole Polytechnique Federale de Lausanne; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Unaffiliated; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Unaffiliated; Johns Hopkins University; Johns Hopkins University; Johns Hopkins University; Unaffiliated; Iowa State University; Iowa State University; Iowa State University; Iowa State University; Clemson University; College of William & Mary; Iowa State University; University of Virginia; University of Washington; University of Washington; University of Washington; University of Washington; University of Washington; University of Washington; University of Washington; IEM, Inc.; IEM, Inc.; IEM, Inc.; IEM, Inc.; Georgia Institute of Technology; University of Iowa; Georgia Institute of Technology; Georgia Institute of Technology; Georgia Institute of Technology; Virginia Tech; Georgia Institute of Technology; Georgia Insitute of Technology; Metron, Inc.; Georgia Insitute of Technology; Georgia Insitute of Technology; Georgia Insitute of Technology; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Harvard University; Google Cloud; Google Cloud; Google Cloud; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; The University of Texas at Austin; The University of Texas at Austin; Columbia University; Columbia University; Columbia University; Operations Research Center, Massachusetts Institute of Technology; Sloan School of Management, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Emory University Medical School; Georgia Insitute of Technology; MGH; MGH; Value Analytics Labs; MGH; Boston University School of Medicine; MGH; Georgia Insitute of Technology; Columbia University; Columbia University; Columbia University; UNC Chapel Hill; Carnegie Mellon University; University of Southern California; Carnegie Mellon University; Carnegie Mellon University; Carnegie Mellon University; University of British Columbia; Stanford University; Carnegie Mellon University; Stanford University; Carnegie Mellon University; University of Washington; Carnegie Mellon University; Stanford University; Carnegie Mellon University; Carnegie Mellon University; University of Georgia; University of Georgia; Unaffiliated; Walmart Inc.; Dalhousie University; Virtual Power System Inc.; Centers for Disease Control and Prevention; Centers for Disease Control and Prevention; Centers for Disease Control and Prevention; Centers for Disease Control and Prevention; University of Massachusetts, Amherst","Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naive baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks. +medRxiv,10.1101/2021.02.01.21250839,2021-02-03,https://medrxiv.org/cgi/content/short/2021.02.01.21250839,Extremely high SARS-CoV-2 seroprevalence in a strictly-Orthodox Jewish community in the UK,Katherine M Gaskell; Marina Johnson; Victoria Gould; Adam Hunt; Neil RH Stone; William Waites; Ben Kasstan; Tracey Chantler; Sham Lal; Chrissy h. Roberts; David Goldblatt; Rosalind M Eggo; Michael M Marks,"Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK & Hospital for Tropical Diseases, University C; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Centre for Health, Law and Society, University of Bristol Law School, Bristol. BS1 1RJ; Department of Global Health and Development, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK & Hospital for Tropical Diseases, University C","BackgroundEthnic and religious minorities have been disproportionately affected by SARS-CoV-2 worldwide. The UK strictly-Orthodox Jewish community has been severely affected by the pandemic. This group shares characteristics with other ethnic minorities including larger family sizes, higher rates of household crowding and relative socioeconomic deprivation. We studied a UK strictly-Orthodox Jewish population to understand how COVID-19 had spread within this community. + +MethodsWe performed a household-focused cross-sectional SARS-CoV-2 serosurvey specific to three antigen targets. Randomly-selected households completed a standardised questionnaire and underwent serological testing with a multiplex assay for SARS-CoV-2 IgG antibodies. We report clinical illness and testing before the serosurvey, seroprevalence stratified by age and gender. We used random-effects models to identify factors associated with infection and antibody titres. + +FindingsA total of 343 households, consisting of 1,759 individuals, were recruited. Serum was available for 1,242 participants. The overall seroprevalence for SARS-CoV-2 was 64.3% (95% CI 61.6-67.0%). The lowest seroprevalence was 27.6% in children under 5 years and rose to 73.8% in secondary school children and 74% in adults. Antibody titres were higher in symptomatic individuals and declined over time since reported COVID-19 symptoms, with the decline more marked for nucleocapsid titres. + +InterpretationIn this tight-knit religious minority population in the UK, we report one of the highest SARS-CoV-2 seroprevalence levels in the world to date. In the context of this high force of infection, all age groups experienced a high burden of infection. Actions to reduce the burden of disease in this and other minority populations are urgently required. + +FundingThis work was jointly funded by UKRI and NIHR [COV0335; MR/V027956/1], a donation from the LSHTM Alumni COVID-19 response fund, HDR UK, the MRC and the Wellcome Trust. The funders had no role in the design, conduct or analysis of the study or the decision to publish. The authors have no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work. -Significance StatementThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.",epidemiology,fuzzy,100,100 +Research In ContextO_ST_ABSEvidence before the studyC_ST_ABSIn January 2020, we searched PubMed for articles on rates of SARS-CoV-2 infection amongst ethnic minority groups and amongst the Jewish population. Search teams included ""COVID-19"", ""SARS-CoV-2"", seroprevalence, ""ethnic minority"", and ""Jewish"" with no language restrictions. We also searched UK government documents on SARS-CoV-2 infection amongst minority groups. By January 2020, a large number of authors had reported that ethnic minority groups experienced higher numbers of cases and increased hospitalisations due to COVID-19. A small number of articles provided evidence that strictly-Orthodox Jewish populations had experienced a high rate of SARS-CoV-2 infection but extremely limited data was available on overall population level rates of infection amongst specific ethnic minority population groups. There was also extremely limited data on rates of infection amongst young children from ethnic minority groups. + +Added value of the studyWe report findings from a population representative, household survey of SARS-CoV-2 infection amongst a UK strictly Orthodox Jewish population. We demonstrate an extremely high seroprevalence rate of SARS-CoV-2 in this population which is more than five times the estimated seroprevalence nationally and five times the estimated seroprevalence in London. In addition the large number of children in our survey, reflective of the underlying population structure, allows us to demonstrate that in this setting there is a significant burden of disease in all age groups with secondary school aged children having an equivalent seroprevalence to adults. + +Implications of the available evidenceOur data provide clear evidence of the markedly disproportionate impact of SARS-CoV-2 in minority populations. In this setting infection occurs at high rates across all age groups including pre-school, primary school and secondary school-age children. Contextually appropriate measures to specifically reduce the impact of SARS-CoV-2 amongst minority populations are urgently required.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2021.02.02.21250989,2021-02-03,https://medrxiv.org/cgi/content/short/2021.02.02.21250989,Short report: Ethnicity and COVID-19 death in the early part of the COVID-19 second wave in England: an analysis of OpenSAFELY data from 1st September to 9th November 2020,Krishnan Bhaskaran; Rohini Mathur; Christopher T Rentsch; Caroline E Morton; William J Hulme; Anna Schultze; Brian McKenna; Rosalind M Eggo; Angel YS Wong; Elizabeth J Williamson; Harriet J Forbes; Kevin Wing; Helen I McDonald; Chris J Bates; Sebastian CJ Bacon; Alex J Walker; David Evans; Peter Inglesby; Amir Mehrkar; Helen J Curtis; Nichola J DeVito; Richard Croker; Henry Drysdale; Jonathan Cockburn; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Laurie Tomlinson; Stephen JW Evans; Richard Grieve; Liam Smeeth; Ben Goldacre,"London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; London School of Hygiene and Tropical Medicine; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP, TPP House, Horsforth, Leeds; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford; TPP, TPP House, Horsforth, Leeds; TPP, TPP House, Horsforth, Leeds; TPP, TPP House, Horsforth, Leeds; TPP, TPP House, Horsforth, Leeds; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The DataLab, Nuffield Department of Primary Care Health Sciences, University of Oxford","Black and minority ethnic groups were at raised risk of dying from COVID-19 during the first few months of the COVID-19 epidemic in England. We aimed to investigate whether ethnic inequalities in COVID-19 deaths were similar in the more recent ""second wave"" of the epidemic. Working on behalf of NHS England, we used primary care and linked ONS mortality data within the OpenSAFELY platform. All adults in the database at 1st September 2020 and with at least 1 year of prior follow-up and a record of ethnicity were included. The outcome was COVID-19-related death (death with COVID-19 listed as a cause of death on the death certificate). Follow-up was to 9th November 2020. Hazard ratios for ethnicity were calculated using Cox regression models adjusted for age and sex, and then further adjusted for deprivation. 13,223,154 people were included. During the study period, people of South Asian ethnicity were at higher risk of death due to COVID-19 than white people after adjusting for age and sex (HR = 3.47, 95% CI 2.99-4.03); the association attenuated somewhat on further adjustment for index of multiple deprivation (HR = 2.86, 2.46-3.33, Table 2). In contrast with the first wave of the epidemic, we found little evidence of a raised risk in black or other ethnic groups compared to white (HR for black vs white = 1.28, 0.87-1.88 adjusted for age and sex; and 1.01, 0.69-1.49 further adjusted for deprivation). Our findings suggest that ethnic inequalities in the risk of dying COVID-19-related death have changed between the first and early second wave of the epidemic in England. O_TBL View this table: @@ -4041,6 +4014,15 @@ MethodsWorking on behalf of NHS England we analysed 57.9 million patient records Results20,852,692 patients (36%) received a COVID-19 vaccine between December 8th 2020 and March 17th 2021. Of patients aged [≥]80 not in a care home (JCVI group 2) 94.7% received a vaccine, but with substantial variation by ethnicity (White 96.2% vaccinated, Black 68.3%) and deprivation (least deprived 96.6%, most deprived 90.7%). Overall, patients with pre-existing medical conditions were equally or more likely to be vaccinated with two exceptions: severe mental illness (89.5% vaccinated) and learning disability (91.4%). 275,205 vaccine recipients were identified as care home residents (priority group 1; 91.2% coverage). 1,257,914 (6.0%) recipients have had a second dose. Detailed characteristics of recipients in all cohorts are reported. ConclusionsThe NHS in England has rapidly delivered mass vaccination. We were able to deploy a data monitoring framework using publicly auditable methods and a secure, in-situ processing model, using linked but pseudonymised patient-level NHS data on 57.9 million patients with very short delays from vaccine administration to completed analysis. Targeted activity may be needed to address lower vaccination coverage observed among certain key groups: ethnic minorities, those living in deprived areas, and people with severe mental illness or learning disabilities.",public and global health,fuzzy,100,100 +medRxiv,10.1101/2021.01.22.21250304,2021-01-25,https://medrxiv.org/cgi/content/short/2021.01.22.21250304,Rates of serious clinical outcomes in survivors of hospitalisation with COVID-19: a descriptive cohort study within the OpenSAFELY platform,John Tazare; Alex J Walker; Laurie Tomlinson; George Hickman; Christopher T Rentsch; Elizabeth J Williamson; Krishnan Bhaskaran; David Evans; Kevin Wing; Rohini Mathur; Angel YS Wong; Anna Schultze; Sebastian CJ Bacon; Christopher Bates; Caroline E Morton; Helen J Curtis; Emily Nightingale; Helen I McDonald; Amir Mehrkar; Peter Inglesby; Simon Davy; Brian MacKenna; Jonathan Cockburn; William J Hulme; Charlotte Warren-Gash; Ketaki Bhate; Emma Powell; Any Mulick; Harriet Forbes; Caroline Minassian; Richard Croker; John Parry; Frank Hester; Sam Harper; Rosalind M Eggo; Stephen JW Evans; Liam Smeeth; Ian J Douglas; Ben Goldacre,London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundPatients with COVID-19 are thought to be at higher risk of cardiometabolic and pulmonary complications, but quantification of that risk is limited. We aimed to describe the overall burden of these complications in survivors of severe COVID-19. + +MethodsWorking on behalf of NHS England, we used linked primary care records, death certificate and hospital data from the OpenSAFELY platform. We constructed three cohorts: patients discharged following hospitalisation with COVID-19, patients discharged following hospitalisation with pneumonia in 2019, and a frequency-matched cohort from the general population in 2019. We studied eight cardiometabolic and pulmonary outcomes. Absolute rates were measured in each cohort and Cox regression models were fitted to estimate age/sex adjusted hazard ratios comparing outcome rates between discharged COVID-19 patients and the two comparator cohorts. + +ResultsAmongst the population of 31,716 patients discharged following hospitalisation with COVID-19, rates for majority of outcomes peaked in the first month post-discharge, then declined over the following four months. Patients in the COVID-19 population had markedly increased risk of all outcomes compared to matched controls from the 2019 general population, especially for pulmonary embolism (HR 12.86; 95% CI: 11.23 - 14.74). Outcome rates were more similar when comparing patients discharged with COVID-19 to those discharged with pneumonia in 2019, although COVID-19 patients had increased risk of type 2 diabetes (HR 1.23; 95% CI: 1.05 - 1.44). + +InterpretationCardiometabolic and pulmonary adverse outcomes are markedly raised following hospitalisation for COVID-19 compared to the general population. However, the excess risks were more comparable to those seen following hospitalisation with pneumonia. Identifying patients at particularly high risk of outcomes would inform targeted preventive measures. + +FundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, UK Research and Innovation, Health and Safety Executive.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2021.01.22.21249968,2021-01-25,https://medrxiv.org/cgi/content/short/2021.01.22.21249968,An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: national validation cohort study in England,Vahe Nafilyan; Ben Humberstone; Nisha Metha; Ian Diamond; Luke Lorenzi; Piotr Pawelek; Ryan Schofield; Jasper Morgan; Paul Brown; Ronan Lyons; Aziz Sheikh; Julia Hippisley-Cox,Office for National Statistics; Office for National Statistics; Office of the Chief Medical Officer; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Swansea University; University of Edinburgh; University of Oxford,"BackgroundTo externally validate a risk prediction algorithm (QCovid) to estimate mortality outcomes from COVID-19 in adults in England. MethodsPopulation-based cohort study using the ONS Public Health Linked Data Asset, a cohort based on the 2011 Census linked to Hospital Episode Statistics, the General Practice Extraction Service Data for pandemic planning and research, radiotherapy and systemic chemotherapy records. The primary outcome was time to COVID-19 death, defined as confirmed or suspected COVID-19 death as per death certification. Two time periods were used: (a) 24th January to 30th April 2020; and (b) 1st May to 28th July 2020. We evaluated the performance of the QCovid algorithms using measures of discrimination and calibration for each validation time period. @@ -4174,19 +4156,15 @@ What is already known on this topicPre-pandemic, higher occupancy of intensive c What this study addsThe results of this study suggest that survival rates for patients with COVID-19 in intensive care settings appears to deteriorate as the occupancy of (surge capacity) beds compatible with mechanical ventilation (a proxy for operational pressure), increases. Moreover, this risk doesnt occur above a specific threshold, but rather appears linear; whereby going from 0% occupancy to 100% occupancy increases risk of mortality by 69% (after adjusting for relevant individual-level factors). Furthermore, risk of mortality based on occupancy on the date of recorded outcome is even higher; OR 2.98 (95% posterior credible interval: 2.33 - 3.83). As such, this national-level cohort study of England provides compelling evidence for a relationship between occupancy and critical care mortality, and highlights the needs for decisive action to control the incidence and prevalence of COVID-19. C_TEXTBOX",intensive care and critical care medicine,fuzzy,100,100 -medRxiv,10.1101/2020.12.27.20248896,2021-01-02,https://medrxiv.org/cgi/content/short/2020.12.27.20248896,Vaccination and Non-Pharmaceutical Interventions: when can the UK relax about COVID-19?,Sam Moore; Edward M Hill; Michael Tildesley; Louise M Dyson; Matt J Keeling,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"BackgroundThe announcement of efficacious vaccine candidates against SARS-CoV-2 has been met with worldwide acclaim and relief. Many countries already have detailed plans for vaccine targeting based on minimising severe illness, death and healthcare burdens. Normally, relatively simple relationships between epidemiological parameters, vaccine efficacy and vaccine uptake predict the success of any immunisation programme. However, the dynamics of vaccination against SARS-CoV-2 is made more complex by age-dependent factors, changing levels of infection and the potential relaxation of non-pharmaceutical interventions (NPIs) as the perceived risk declines. - -MethodsIn this study we use an age-structured mathematical model, matched to a range of epidemiological data in the UK, that also captures the roll-out of a two-dose vaccination programme targeted at specific age groups. - -FindingsWe consider the interaction between the UK vaccination programme and future relaxation (or removal) of NPIs. Our predictions highlight the population-level risks of early relaxation leading to a pronounced wave of infection, hospital admissions and deaths. Only vaccines that offer high infection-blocking efficacy with high uptake in the general population allow relaxation of NPIs without a huge surge in deaths. +medRxiv,10.1101/2021.01.06.21249352,2021-01-08,https://medrxiv.org/cgi/content/short/2021.01.06.21249352,OpenSAFELY NHS Service Restoration Observatory 1: describing trends and variation in primary care clinical activity for 23.3 million patients in England during the first wave of COVID-19,Helen J Curtis; Brian MacKenna; Richard Croker; Alex J Walker; Peter Inglesby; Jessica Morley; Amir Mehrkar; Caroline E Morton; Seb Bacon; George Hickman; Chris Bates; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan T. Bhaskaran; Anna Schultze; Christopher T. Rentsch; Elizabeth J Williamson; Will Hulme; Helen I McDonald; Laurie Tomlinson; Kevin Wing; Rohini I Mathur; Harriet Forbes; Angel Wong; Rosalind M Eggo; Henry Drysdale; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Stephen Evans; Liam Smeeth; Ben Goldacre,"University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; LSHTM; US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine; LSHTM; University of Oxford; London School of Medicine and Tropical Medicine; LSHTM; LSHTM; London School of Hygiene and Tropical Medicine; LSHTM; London School of Hygiene and Tropical Medicine; LSHTM; University of Oxford; TPP; TPP; TPP; LSHTM; LSHTM; LSHTM; University of Oxford","BackgroundThe COVID-19 pandemic has disrupted healthcare activity globally. The NHS in England stopped most non-urgent work by March 2020, but later recommended that services should be restored to near-normal levels before winter where possible. The authors are developing the OpenSAFELY NHS Service Restoration Observatory, using data to describe changes in service activity during COVID-19, and reviewing signals for action with commissioners, researchers and clinicians. Here we report phase one: generating, managing, and describing the data. -InterpretationWhile the novel vaccines against SARS-CoV-2 offer a potential exit strategy for this outbreak, this is highly contingent on the infection-blocking (or transmission-blocking) action of the vaccine and the population uptake, both of which need to be carefully monitored as vaccine programmes are rolled out in the UK and other countries. +ObjectiveTo describe the volume and variation of coded clinical activity in English primary care across 23.8 million patients records, taking respiratory disease and laboratory procedures as key examples. -Research in contextO_ST_ABSEvidence before this studyC_ST_ABSVaccination has been seen as a key tool in the fight against SARS-CoV-2. The vaccines already developed represent a major technological achievement and have been shown to generate significant immune responses, as well as offering considerable protection against disease. However, to date there is limited information on the degree of infection-blocking these vaccines are likely to induce. Mathematical models have already successfully been used to consider age- and risk-structured targeting of vaccination, highlighting the importance of prioritising older and high-risk individuals. +MethodsWorking on behalf of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care EHR data on 23.8 million patients; and conducted a population cohort-based study to describe activity using CTV3 coding hierarchy and keyword searches from January 2019-September 2020. -Added value of this studyTranslating current knowledge and uncertainty of vaccine behaviour into meaningful public health messages requires models that fully capture the within-country epidemiology as well as the complex roll-out of a two-dose vaccination programme. We show that under reasonable assumptions for vaccine efficacy and uptake the UK is unlikely to reach herd immunity, which means that non-pharmaceutical interventions cannot be released without generating substantial waves of infection. +ResultsMuch activity recorded in general practice declined to some extent during the pandemic, but largely recovered by September 2020, with some exceptions. There was a large drop in coded activity for commonly used laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was blood coagulation tests such as International Normalised Ratio (INR), with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 7.0). The overall pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as ""no change"" from the previous year. Respiratory tract infections exhibited a sustained drop compared with pre-pandemic levels, not returning to pre-pandemic levels by September 2020. Various COVID-19 codes increased through the period. We observed a small decline associated with high level codes for long-term respiratory conditions such as chronic obstructive pulmonary disease (COPD) and asthma. Asthma annual reviews experienced a small drop but since recovered, while COPD annual reviews remain below baseline. -Implications of all the available evidenceVaccination is likely to provide substantial individual protection to those receiving two doses, but the degree of protection to the wider population is still uncertain. While substantial immunisation of the most vulnerable groups will allow for some relaxation of controls, this must be done gradually to prevent large scale public health consequences.",infectious diseases,fuzzy,100,100 +ConclusionsWe successfully delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September 2020, with some important tests less affected. Records of respiratory infections decreased with the exception of codes related to COVID-19, whilst activity of other respiratory disease codes was mixed. We are expanding the NHS Service Restoration Observatory in collaboration with clinicians, commissioners and researchers and welcome feedback.",health systems and quality improvement,fuzzy,100,100 medRxiv,10.1101/2020.12.30.20248603,2021-01-01,https://medrxiv.org/cgi/content/short/2020.12.30.20248603,SARS-CoV-2 positivity in asymptomatic-screened dental patients,David I Conway; Shauna Culshaw; Maura Edwards; Claire Clark; Chris Watling; Chris Robertson; Raymond Braid; Emma O'Keefe; Niall McGoldrick; Jacky Burns; Stacey Provan; Harper VanSteenhouse; Jodie Hay; Rory Gunson; - Dental COVID-19 Surveillance Survey Group,University of Glasgow and Public Health Scotland; University of Glasgow; NHS Ayrshire and Arran; Public Health Scotland; Public Health Scotland; Strathclyde University and Public Health Scotland; Public Health Scotland; NHS Fife; NHS Fife; NHS Fife; NHS Greater Glasgow & Clyde; BioClavis Ltd; University of Glasgow; NHS Greater Glasgow & Clyde; ,"Enhanced community surveillance is a key pillar of the public health response to COVID-19. Asymptomatic carriage of SARS-CoV-2 is a potentially significant source of transmission, yet remains relatively poorly understood. Disruption of dental services continues with significantly reduced capacity. Ongoing precautions include pre- and/or at appointment COVID-19 symptom screening and use of enhanced personal protective equipment (PPE). This study aimed to investigate SARS-CoV-2 infection in dental patients to inform community surveillance and improve understanding of risks in the dental setting. Thirty-one dental care centres across Scotland invited asymptomatic screened patients over 5-years-old to participate. Following verbal consent and completion of sociodemographic and symptom history questionnaire, trained dental teams took a combined oropharyngeal and nasal swab sample using standardised VTM-containing testkits. Samples were processed by the Lighthouse Lab and patients informed of their results by SMS/e-mail with appropriate self-isolation guidance in the event of a positive test. Over a 13-week period (from 3August to 31October2020) n=4,032 patients, largely representative of the population, were tested. Of these n=22 (0.5%; 95%CI 0.5%, 0.8%) tested positive for SARS-CoV-2. The positivity rate increased over the period, commensurate with uptick in community prevalence identified across all national testing monitoring data streams. All positive cases were successfully followed up by the national contact tracing program. To the best of our knowledge this is the first report of a COVID-19 testing survey in asymptomatic-screened patients presenting in a dental setting. The positivity rate in this patient group reflects the underlying prevalence in community at the time. These data are a salient reminder, particularly when community infection levels are rising, of the importance of appropriate ongoing Infection Prevention Control and PPE vigilance, which is relevant as healthcare team fatigue increases as the pandemic continues. Dental settings are a valuable location for public health surveillance.",dentistry and oral medicine,fuzzy,100,100 medRxiv,10.1101/2020.12.24.20248822,2020-12-26,https://medrxiv.org/cgi/content/short/2020.12.24.20248822,Estimated transmissibility and severity of novel SARS-CoV-2 Variant of Concern 202012/01 in England,Nicholas G Davies; Sam Abbott; Rosanna C. Barnard; Christopher I. Jarvis; Adam J. Kucharski; James D Munday; Carl A. B. Pearson; Timothy Russell; Damien Tully; Alex D. Washburne; Tom Wenseleers; Amy Gimma; William Waites; Kerry L. M. Wong; Kevin van Zandvoort; Justin D. Silverman; - CMMID COVID-19 Working Group; - The COVID-19 Genomics UK (COG-UK) Consortium; Karla Diaz-Ordaz; Ruth H Keogh; Rosalind M Eggo; Sebastian Funk; Mark Jit; Katherine E. Atkins; W. John Edmunds,"London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Selva Analytics LLC; KU Leuven; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; College of Information Science and Technology, Pennsylvania State University; ; ; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine","A novel SARS-CoV-2 variant, VOC 202012/01 (lineage B.1.1.7), emerged in southeast England in November 2020 and is rapidly spreading towards fixation. Using a variety of statistical and dynamic modelling approaches, we estimate that this variant has a 43-90% (range of 95% credible intervals 38-130%) higher reproduction number than preexisting variants. A fitted two-strain dynamic transmission model shows that VOC 202012/01 will lead to large resurgences of COVID-19 cases. Without stringent control measures, including limited closure of educational institutions and a greatly accelerated vaccine roll-out, COVID-19 hospitalisations and deaths across England in 2021 will exceed those in 2020. Concerningly, VOC 202012/01 has spread globally and exhibits a similar transmission increase (59-74%) in Denmark, Switzerland, and the United States.",epidemiology,fuzzy,100,100 bioRxiv,10.1101/2020.12.23.424229,2020-12-25,https://biorxiv.org/cgi/content/short/2020.12.23.424229,Patterns of within-host genetic diversity in SARS-CoV-2,Gerry Tonkin-Hill; Inigo Martincorena; Roberto Amato; Andrew R J Lawson; Moritz Gerstung; Ian Johnston; David K Jackson; Naomi R Park; Stefanie V Lensing; Michael A Quail; Sónia Gonçalves; Cristina Ariani; Michael Spencer Chapman; William L Hamilton; Luke W Meredith; Grant Hall; Aminu S Jahun; Yasmin Chaudhry; Myra Hosmillo; Malte L Pinckert; Iliana Georgana; Anna Yakovleva; Laura G Caller; Sarah L Caddy; Theresa Feltwell; Fahad A Khokhar; Charlotte J Houldcroft; Martin D Curran; Surendra Parmar; - The COVID-19 Genomics UK (COG-UK) Consortium; Alex Alderton; Rachel Nelson; Ewan Harrison; John Sillitoe; Stephen D Bentley; Jeffrey C Barrett; M. Estee Torok; Ian G Goodfellow; Cordelia Langford; Dominic Kwiatkowski; - Wellcome Sanger Institute COVID-19 Surveillance Team,"Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; European Bioinformatics Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge and The Francis Crick Institute; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Department of Medicine, University of Cambridge and Cambridge Institute of Therapeutic Immunology and Infectious Disease; Department of Medicine, University of Cambridge; Public Health England; Public Health England; COG-UK; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute and European Bioinformatics Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Wellcome Sanger Institute; Wellcome Sanger Institute and Oxford University; ","Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1,181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within and between host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.",genomics,fuzzy,100,100 @@ -4643,24 +4621,32 @@ The decline from rounds 1 to 3 was largest in those who did not report a history DiscussionThese findings provide evidence of variable waning in antibody positivity over time such that, at the start of the second wave of infection in England, only 4.4% of adults had detectable IgG antibodies using an LFIA. Antibody positivity was greater in those who reported a positive PCR and lower in older people and those with asymptomatic infection. These data suggest the possibility of decreasing population immunity and increasing risk of reinfection as detectable antibodies decline in the population.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.10.26.20219485,2020-10-27,https://medrxiv.org/cgi/content/short/2020.10.26.20219485,Predicting the impact of COVID-19 interruptions on transmission of gambiense human African trypanosomiasis in two health zones of the Democratic Republic of Congo,Maryam Aliee; Soledad Castano; Christopher Davis; Swati Patel; Erick Mwamba Miaka; Simon EF Spencer; Matt J Keeling; Nakul Chitnis; Kat S Rock,"University of Warwick; Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute; University of Warwick; University of Warwick; Programme National de Lutte contre la Trypanosomiase Humaine Africaine, Kinshasa, the Democratic Republic of the Congo; University of Warwick; University of Warwick; Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Warwick","Many control programmes against neglected tropical diseases have been interrupted due to COVID-19 pandemic, including those that rely on active case finding. In this study we focus on gambiense human African trypanosomiasis (gHAT), where active screening was suspended in the Democratic Republic of Congo (DRC) due to the pandemic. We use two independent mathematical models to predict the impact of COVID-19 interruptions on transmission and reporting, and the achievement of 2030 elimination of transmission (EOT) goal for gHAT in two moderate-risk regions of DRC. We consider different interruption scenarios, including reduced passive surveillance in fixed health facilities, and whether this suspension lasts until the end of 2020 or 2021. Our models predict an increase in the number of new infections in the interruption period only if both active screening and passive surveillance were suspended, and with slowed reduction - but no increase - if passive surveillance remains fully functional. In all scenarios, the EOT may be slightly pushed back if no mitigation such as increased screening coverage is put in place. However, we emphasise that the biggest challenge will remain in the higher prevalence regions where EOT is already predicted to be behind schedule without interruptions unless interventions are bolstered.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.10.19.20214494,2020-10-21,https://medrxiv.org/cgi/content/short/2020.10.19.20214494,Attributes and predictors of Long-COVID: analysis of COVID cases and their symptoms collected by the Covid Symptoms Study App,Carole H Sudre; Benjamin Murray; Thomas Varsavsky; Mark S Graham; Rose S Penfold; Ruth C.E Bowyer; Joan Capdevila Pujol; Kerstin Klaser; Michela Antonelli; Liane S Canas; Erika Molteni; Marc Modat; M. Jorge Cardoso; Anna May; Sajaysurya Ganesh; Richard Davies; Long H Nguyen; David Alden Drew; Christina M Astley; Amit D. Joshi; Jordi Merino; Neli Tsereteli; Tove Fall; Maria F Gomez; Emma Duncan; Christina Menni; Frances MK Williams; Paul W Franks; Andrew T Chan; Jonathan Wolf; Sebastien Ourselin; Timothy Spector; Claire J Steves,KCL; King's College London; King's College London; King's College London; King's College London; King's College London; Zoe Global Limited; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; Zoe Global Limited; Zoe Global Limited; Zoe Global Limited; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital; Boston Children's Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Lund University; Uppsala University; Lund University; King's College London; King's College London; King's College London; Lund University; Massachusetts General Hospital; Zoe Global Limited; King's College London; King's College London; King's College London,"Reports of ""Long-COVID"", are rising but little is known about prevalence, risk factors, or whether it is possible to predict a protracted course early in the disease. We analysed data from 4182 incident cases of COVID-19 who logged their symptoms prospectively in the COVID Symptom Study app. 558 (13.3%) had symptoms lasting >=28 days, 189 (4.5%) for >=8 weeks and 95 (2.3%) for >=12 weeks. Long-COVID was characterised by symptoms of fatigue, headache, dyspnoea and anosmia and was more likely with increasing age, BMI and female sex. Experiencing more than five symptoms during the first week of illness was associated with Long-COVID, OR=3.53 [2.76;4.50]. A simple model to distinguish between short and long-COVID at 7 days, which gained a ROC-AUC of 76%, was replicated in an independent sample of 2472 antibody positive individuals. This model could be used to identify individuals for clinical trials to reduce long-term symptoms and target education and rehabilitation services.",infectious diseases,fuzzy,94,100 -medRxiv,10.1101/2020.10.15.20208454,2020-10-18,https://medrxiv.org/cgi/content/short/2020.10.15.20208454,Modelling SARS-CoV-2 transmission in a UK university setting,Edward M Hill; Benjamin D Atkins; Matt J Keeling; Michael Tildesley; Louise Dyson,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"Around 40% of school leavers in the UK attend university and individual universities generally host thousands of students each academic year. Bringing together these student communities during the COVID-19 pandemic may require strong interventions to control transmission. Prior modelling analyses of SARS-CoV-2 transmission within universities using compartmental modelling approaches suggest that outbreaks are almost inevitable. +medRxiv,10.1101/2020.10.15.20213108,2020-10-20,https://medrxiv.org/cgi/content/short/2020.10.15.20213108,FebriDx point-of-care test in patients with suspected COVID-19: a pooled diagnostic accuracy study,Samuel G Urwin; B Clare Lendrem; Jana Suklan; Kile Green; Sara Graziadio; Peter Buckle; Paul M Dark; Adam L Gordon; Daniel S Lasserson; Brian Nicholson; D Ashley Price; Charles Reynard; Mark H Wilcox; Gail Hayward; Graham Prestwich; Valerie Tate; Tristan W Clark; Raja V Reddy; Hamish Houston; Ankur Gupta-Wright; Laurence John; Richard Body; A Joy Allen,"NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne Hospitals Foundation Trust, Newcastle-upon-Tyne, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne Hospitals Foundation Trust, Newcastle-upon-Tyne, UK; Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, UK; Division of Infection, Immunity & Respiratory Medicine, University of Manchester, UK; School of Medicine, University of Nottingham, UK; NIHR Applied Research Collaboration East Midlands (ARC-EM), Nottingham, UK; NIHR Community Healthcare MedTech and In Vitro Diagnostics Cooperative, Oxford Health NHS Foundation Trust, Oxford, UK; Division of Health Sciences, University ; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne Hospitals Foundation Trust, Newcastle-upon-Tyne, UK; NIHR Doctoral Research Fellowship Programme, UK; Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK; Healthcare Associated Infections Research Group, NIHR Leeds In Vitro Diagnostics Co-operative, Leeds Teaching Hospitals NHS Trust and University of Leeds, Leeds; NIHR Community Healthcare MedTech and In Vitro Diagnostics Co-operative, Oxford Health NHS Foundation Trust, Oxford, UK; Nuffield Department of Primary Care Hea; Yorkshire and Humber Academic Health Science Network, Wakefield, UK; Patient Public Involvement (PPI) Member, Precision Antimicrobial Prescribing PPI Group, NIHR Community Healthcare MedTech and In Vitro Diagnostics Cooperative, ; School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Department of Infection, University Hospital Sout; Department of Respiratory Medicine, Kettering General Hospital NHS Foundation Trust, Kettering, UK; Northwick Park Hospital, London North West University Healthcare NHS Trust, Harrow, UK; Institute for Global Health, University College London, London, UK; Ealing Hospital, London North West University Healthcare NHS Trust, London, UK; Clinical Res; Northwick Park Hospital, London North West University Healthcare NHS Trust, Harrow, UK; Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK; Emergency Department, Manchester Royal Infirmary, Ma; NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK","BackgroundWe conducted a systematic review and individual patient data (IPD) meta-analysis to evaluate the diagnostic accuracy of a commercial point-of-care test, the FebriDx lateral flow device (LFD), in adult patients with suspected COVID-19. The FebriDx LFD is designed to distinguish between viral and bacterial respiratory infection. -We constructed a network-based model to capture the interactions of a student population in different settings (housing, social and study). For a single academic term of a representative campus-based university, we ran a susceptible-latent-infectious-recovered type epidemic process, parameterised according to available estimates for SARS-CoV-2. We investigated the impact of: adherence to (or effectiveness of) isolation and test and trace measures; room isolation of symptomatic students; and supplementary mass testing. +MethodsWe searched MEDLINE, EMBASE, PubMed, Google Scholar, LitCovid, ClinicalTrials.gov and preprint servers on the 13th of January 2021 to identify studies reporting diagnostic accuracy of FebriDx (myxovirus resistance protein A component) versus real time reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 in adult patients suspected of COVID-19. IPD were sought from studies meeting the eligibility criteria. Studies were screened for risk of bias using the QUADAS-2 tool. A bivariate linear mixed model was fitted to the data to obtain a pooled estimate of sensitivity and specificity with 95% confidence intervals (95% CIs). A summary receiver operating characteristic (SROC) curve of the model was constructed. A sub-group analysis was performed by meta-regression using the same modelling approach to compare pooled estimates of sensitivity and specificity between patients with a symptom duration of 0 to 7 days and >7 days, and patients aged between 16 to 73 years and >73 years. -With all adhering to test, trace and isolation measures, we found that 22% (7% - 41%) of the student population could be infected during the autumn term, compared to 69% (56% - 76%) when assuming zero adherence to such measures. Irrespective of the adherence to isolation measures, on average a higher proportion of students resident on-campus became infected compared to students resident off-campus. Room isolation generated minimal benefits. Regular mass testing, together with high adherence to isolation and test and trace measures, could substantially reduce the proportion infected during the term compared to having no testing. +ResultsTen studies were screened, and three studies with a total of 1481 patients receiving hospital care were included. FebriDx produced an estimated pooled sensitivity of 0.911 (95% CI: 0.855-0.946) and specificity of 0.868 (95% CI: 0.802-0.915) compared to RT-PCR. There were no significant differences between the sub-groups of 0 to 7 days and >7 days in estimated pooled sensitivity (p = 0.473) or specificity (p = 0.853). There were also no significant differences between the sub-groups of 16 to 73 years of age and >73 years of age in estimated pooled sensitivity (p = 0.946) or specificity (p = 0.486). -Our findings suggest SARS-CoV-2 may readily transmit in a university setting if there is limited adherence to nonpharmaceutical interventions and/or there are delays in receiving test results. Following isolation guidance and effective contact tracing curbed transmission and reduced the expected time an adhering student would spend in isolation.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2020.10.14.20212555,2020-10-16,https://medrxiv.org/cgi/content/short/2020.10.14.20212555,Multi-organ impairment in low-risk individuals with long COVID,Andrea Dennis; Malgorzata Wamil; Sandeep Kapur; Johann Alberts; Andrew Badley; Gustav Anton Decker; Stacey A Rizza; Rajarshi Banerjee; Amitava Banerjee,Perspectum; Great Western Hospitals NHS Foundation Trust; Mayo Clinic Healthcare; Alliance Medical; Mayo Clinic; Mayo Clinic International; Mayo Clinic; Perspectum; University College London,"BackgroundSevere acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection has disproportionately affected older individuals and those with underlying medical conditions. Research has focused on short-term outcomes in hospital, and single organ involvement. Consequently, impact of long COVID (persistent symptoms three months post-infection) across multiple organs in low-risk individuals is yet to be assessed. +ConclusionsBased on the results of three studies, the FebriDx LFD had high diagnostic accuracy for COVID-19 in a hospital setting, however, the pooled estimates of sensitivity and specificity should be interpreted with caution due to the small number of studies included, risk of bias, and inconsistent reference standards. Further research is required to confirm these findings, and determine how FebriDx would perform in different healthcare settings and patient populations. + +Trial registrationThis study was conducted at pace as part of the COVID-19 National Diagnostic Research and Evaluation Platform (CONDOR) national test evaluation programme (https://www.condor-platform.org), and as a result, no protocol was developed, and the study was not registered. -MethodsAn ongoing prospective, longitudinal, two-centre, observational study was performed in individuals symptomatic after recovery from acute SARS-CoV-2 infection. Symptoms and organ function (heart, lungs, kidneys, liver, pancreas, spleen) were assessed by standardised questionnaires (EQ-5D-5L, Dyspnoea-12), blood investigations and quantitative magnetic resonance imaging, defining single and multi-organ impairment by consensus definitions. +Lay summaryTests to diagnose COVID-19 are crucial to help control the spread of the disease and to guide treatment. Over the last few months, tests have been developed to diagnose COVID-19 either by detecting the presence of the virus or by detecting specific markers linked to the virus being active in the body. These tests use complex machines in laboratories accepting samples from large geographical areas. Sometimes it takes days for test results to come back. So, to reduce the wait for results, new portable tests are being developed. These point-of-care (POC) tests are designed to work close to where patients require assessment and care such as hospital emergency departments, GP surgeries or care homes. For these new POC tests to be useful, they should ideally be as good as standard laboratory tests. -FindingsBetween April and September 2020, 201 individuals (mean age 44 (SD 11.0) years, 70% female, 87% white, 31% healthcare workers) completed assessments following SARS-CoV-2 infection (median 140, IQR 105-160 days after initial symptoms). The prevalence of pre-existing conditions (obesity: 20%, hypertension: 6%; diabetes: 2%; heart disease: 4%) was low, and only 18% of individuals had been hospitalised with COVID-19. Fatigue (98%), muscle aches (88%), breathlessness (87%), and headaches (83%) were the most frequently reported symptoms. Ongoing cardiorespiratory (92%) and gastrointestinal (73%) symptoms were common, and 42% of individuals had ten or more symptoms. +In this study we looked at published research into a new test called FebriDx. FebriDx is a POC test that detects the bodys response to infection, and is claimed to be able to detect the presence of any viral infection, including infections due to the SARS-CoV-2 virus which causes COVID-19, as well as bacterial infections which can have similar symptoms. The FebriDx result was compared with standard laboratory tests for COVID-19 performed on the same patients throat and nose swab sample. We were able to analyse data from three studies with a total of 1481 adult patients who were receiving hospital care with symptoms of COVID-19 during the UK pandemic. Approximately one fifth of the patients were diagnosed as positive for SARS-CoV-2 virus using standard laboratory tests for COVID-19. -There was evidence of mild organ impairment in heart (32%), lungs (33%), kidneys (12%), liver (10%), pancreas (17%), and spleen (6%). Single (66%) and multi-organ (25%) impairment was observed, and was significantly associated with risk of prior COVID-19 hospitalisation (p<0.05). +Our analysis demonstrated that FebriDx correctly identified 91 out of 100 patients who had COVID-19 according to the standard laboratory test. FebriDx also correctly identified 87 out of 100 patients who did not have COVID-19 according to the standard laboratory test. These results have important implications for how these tests could be used. As there were slightly fewer FebriDx false results when the results of the standard laboratory test were positive (9 out of 100) than when the results of the standard laboratory test were negative (13 out of 100), we can have slightly more confidence in a positive test result using FebriDx than a negative FebriDx result. -InterpretationIn a young, low-risk population with ongoing symptoms, almost 70% of individuals have impairment in one or more organs four months after initial symptoms of SARS-CoV-2 infection. There are implications not only for burden of long COVID but also public health approaches which have assumed low risk in young people with no comorbidities. +Overall, we have shown that the FebriDx POC test performed well during the UK COVID-19 pandemic when compared with laboratory tests, especially when COVID-19 was indicated. For the future, this means that the FebriDx POC test might be helpful in making a quick clinical decision on whether to isolate a patient with COVID-19-like symptoms arriving in a busy emergency department. However, our results indicate it would not completely replace the need to conduct a laboratory test in certain cases to confirm COVID-19. -FundingThis work was supported by the UKs National Consortium of Intelligent Medical Imaging through the Industry Strategy Challenge Fund, Innovate UK Grant 104688, and also through the European Unions Horizon 2020 research and innovation programme under grant agreement No 719445.",health policy,fuzzy,100,100 +There are limitations to our findings. For example, we do not know if FebriDx will work in a similar way with patients in different settings such as in the community or care homes. Similarly, we do not know whether other viral and bacterial infections which cause similar COVID-19 symptoms, and are more common in the autumn and winter months, could influence the FebriDx test accuracy. Our findings are also only based on three studies.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2020.10.15.20208454,2020-10-18,https://medrxiv.org/cgi/content/short/2020.10.15.20208454,Modelling SARS-CoV-2 transmission in a UK university setting,Edward M Hill; Benjamin D Atkins; Matt J Keeling; Michael Tildesley; Louise Dyson,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"Around 40% of school leavers in the UK attend university and individual universities generally host thousands of students each academic year. Bringing together these student communities during the COVID-19 pandemic may require strong interventions to control transmission. Prior modelling analyses of SARS-CoV-2 transmission within universities using compartmental modelling approaches suggest that outbreaks are almost inevitable. + +We constructed a network-based model to capture the interactions of a student population in different settings (housing, social and study). For a single academic term of a representative campus-based university, we ran a susceptible-latent-infectious-recovered type epidemic process, parameterised according to available estimates for SARS-CoV-2. We investigated the impact of: adherence to (or effectiveness of) isolation and test and trace measures; room isolation of symptomatic students; and supplementary mass testing. + +With all adhering to test, trace and isolation measures, we found that 22% (7% - 41%) of the student population could be infected during the autumn term, compared to 69% (56% - 76%) when assuming zero adherence to such measures. Irrespective of the adherence to isolation measures, on average a higher proportion of students resident on-campus became infected compared to students resident off-campus. Room isolation generated minimal benefits. Regular mass testing, together with high adherence to isolation and test and trace measures, could substantially reduce the proportion infected during the term compared to having no testing. + +Our findings suggest SARS-CoV-2 may readily transmit in a university setting if there is limited adherence to nonpharmaceutical interventions and/or there are delays in receiving test results. Following isolation guidance and effective contact tracing curbed transmission and reduced the expected time an adhering student would spend in isolation.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.10.12.20211342,2020-10-14,https://medrxiv.org/cgi/content/short/2020.10.12.20211342,Network Graph Representation of COVID-19 Scientific Publications to Aid Knowledge Discovery,George Cernile; Trevor Heritage; Neil Sebire; Ben Gordon; Taralyn Schwering; Shana Kazemlou; Yulia Borecki,Inspirata Ltd; Inspirata Ltd; HDRUK London UK; HDRUK London UK; Inspirata Ltd; Inspirata Ltd; Inspirata Ltd,"IntroductionNumerous scientific journal articles have been rapidly published related to COVID-19 making navigation and understanding of relationships difficult. MethodsA graph network was constructed from the publicly available CORD-19 database of COVID-19-related publications using an engine leveraging medical knowledgebases to identify discrete medical concepts and an open source tool (Gephi) used to visualise the network. @@ -4775,6 +4761,15 @@ Main outcome measuresWe explored associations between COVID-19 diagnosis and pre ResultsIn covariate adjusted analyses, ACEIs were associated with lower odds of COVID-19 diagnosis (0.82, 95% confidence interval 0.77 to 0.88) as were ARBs, 0.87 (0.80 to 0.95) with little attenuation from adjustment for consultation frequency. In fully adjusted analyses, C and D were also associated with lower odds of COVID-19. Increased odds of COVID-19 for B (1.19, 1.12 to 1.26), were attenuated after adjustment for consultation frequency (1.01, 0.95 to 1.08). In adjusted analyses, patients treated with ACEIs or ARBs had similar mortality to patients treated with classes B, C, D or O (1.00, 0.83 to 1.20) or patients receiving no antihypertensive therapy (0.99, 0.83 to 1.18). ConclusionsAssociations were sensitive to adjustment for confounding and healthcare seeking, but there was no evidence that antihypertensive therapy is associated with increased risk of COVID-19 diagnosis or mortality; most classes of antihypertensive therapy showed negative associations with COVID-19 diagnosis.",primary care research,fuzzy,100,100 +medRxiv,10.1101/2020.09.24.20200048,2020-09-25,https://medrxiv.org/cgi/content/short/2020.09.24.20200048,Genetic mechanisms of critical illness in Covid-19,Erola Pairo-Castineira; Sara Clohisey; Lucija Klaric; Andrew Bretherick; Konrad Rawlik; Nicholas Parkinson; Dorota Pasko; Susan Walker; Anne Richmond; Max Head Fourman; Andy Law; James Furniss; Elvina Gountouna; Nicola Wrobel; Clark D Russell; Loukas Moutsianas; Bo Wang; Alison Meynert; Zhijian Yang; Ranran Zhai; Chenqing Zheng; Fiona Griffith; Wilna Oosthuyzen; Barbara Shih; Seán Keating; Marie Zechner; Chris Haley; David J Porteous; Caroline Hayward; Julian Knight; Charlotte Summers; Manu Shankar-Hari; Lance Turtle; Antonia Ho; Charles Hinds; Peter Horby; Alistair Nichol; David Maslove; Lowell Ling; Paul Klenerman; Danny McAuley; Hugh Montgomery; Timothy Walsh; - The GenOMICC Investigators; - The ISARIC4C Investigators; - The Covid-19 Human Genetics Initiative; Xia Shen; Kathy Rowan; Angie Fawkes; Lee Murphy; Chris P Ponting; Albert Tenesa; Mark Caulfield; Richard Scott; Peter JM Openshaw; Malcolm G Semple; Veronique Vitart; James F Wilson; J Kenneth Baillie,"Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; The Roslin Institute; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Genomics England; Genomics England; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; University of Edinburgh Centre for Inflammation Research, The Queen's Medical Research Institute, Edinburgh, UK; Genomics England; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.; Department of Medicine, University of Cambridge, Cambridge, UK.; Department of Intensive Care Medicine, Guy's and St. Thomas NHS Foundation Trust, London, UK; School of Immunology and Microbial Sciences, King's College London; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences University of Liverpool, L; MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, Univer; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7FZ, UK.; Clinical Research Centre at St Vincent's University Hospital, University College Dublin, Dublin, Ireland; Australian and New Zealand Intensive Care Research Cen; Department of Critical Care Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, ON, Canada.; Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.; University of Oxford; Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, Northern Ireland, UK; Department of Intensive Care Medicine, Royal Vi; UCL Centre for Human Health and Performance, London, W1T 7HA, UK.; Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK.; -; -; -; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.; Intensive Care National Audit & Research Centre, London, UK.; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Genomics England; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK; Genomics England; National Heart & Lung Institute, Imperial College London (St Mary's Campus), Norfolk Place, Paddington, London W2 1PG, UK.; University of Liverpool, Liverpool, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK; Ce; Roslin Institute, University of Edinburgh","The subset of patients who develop critical illness in Covid-19 have extensive inflammation affecting the lungs1 and are strikingly different from other patients: immunosuppressive therapy benefits critically-ill patients, but may harm some non-critical cases.2 Since susceptibility to life-threatening infections and immune-mediated diseases are both strongly heritable traits, we reasoned that host genetic variation may identify mechanistic targets for therapeutic development in Covid-19.3 + +GenOMICC (Genetics Of Mortality In Critical Care, genomicc.org) is a global collaborative study to understand the genetic basis of critical illness. Here we report the results of a genome-wide association study (GWAS) in 2244 critically-ill Covid-19 patients from 208 UK intensive care units (ICUs), representing >95% of all ICU beds. Ancestry-matched controls were drawn from the UK Biobank population study and results were confirmed in GWAS comparisons with two other population control groups: the 100,000 genomes project and Generation Scotland. + +We identify and replicate three novel genome-wide significant associations, at chr19p13.3 (rs2109069, p = 3.98 x 10-12), within the gene encoding dipeptidyl peptidase 9 (DPP9), at chr12q24.13 (rs10735079, p =1.65 x 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), and at chr21q22.1 (rs2236757, p = 4.99 x 10-8) in the interferon receptor gene IFNAR2. Consistent with our focus on extreme disease in younger patients with less comorbidity, we detect a stronger signal at the known 3p21.31 locus than previous studies (rs73064425, p = 4.77 x 10-30). + +We identify potential targets for repurposing of licensed medications. Using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease. Transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19. + +Our results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice.",intensive care and critical care medicine,fuzzy,100,100 medRxiv,10.1101/2020.09.22.20194183,2020-09-24,https://medrxiv.org/cgi/content/short/2020.09.22.20194183,Modelling optimal vaccination strategy for SARS-CoV-2.,Sam Moore; Edward M Hill; Louise Dyson; Michael Tildesley; Matt J Keeling,University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick,"The COVID-19 outbreak has highlighted our vulnerability to novel infections. Faced with this threat and no effective treatment, in line with many other countries, the UK adopted enforced social distancing (lockdown) to reduce transmission- successfully reducing the reproductive number, R, below one. However, given the large pool of susceptible individuals that remain, complete relaxation of controls is likely to generate a substantial second wave. Vaccination remains the only foreseeable means of both containing the infection and returning to normal interactions and behaviour. Here, we consider the optimal targeting of vaccination within the UK, with the aim of minimising future deaths or quality adjusted life year (QALY) losses. We show that, for a range of assumptions on the action and efficacy of the vaccine, targeting older age groups first is optimal and can avoid a second wave if the vaccine prevents transmission as well as disease.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.09.22.20199661,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.22.20199661,Risk of adverse COVID-19 outcomes for people living with HIV: a rapid review and meta-analysis,Maya Mellor; Anne Bast; Nicholas Jones; Nia Roberts; Jose Ordonez-Mena; Alastair Reith; Christopher C Butler; Philippa C Matthews; Jienchi Dorward,"Medical Sciences Division, University of Oxford, Oxford, UK; Medical Sciences Division, University of Oxford, Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; Outreach Librarian Knowledge Centre, Bodleian Health Care Libraries, Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK and NIHR Biomedical Research Centre, Oxford University Hospitals NHS Found; Medical Sciences Division, University of Oxford, Oxford, UK; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK.; Nuffield Department of Medicine, University of Oxford, Oxford, UK and Department of Infectious Diseases and Microbiology, Oxford University Hospitals NHS Founda; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK and Centre for the AIDS Programme of Research in South Africa, University ","ObjectiveTo assess whether people living with HIV (PLWH) are at increased risk of COVID-19 mortality or adverse outcomes, and whether antiretroviral therapy (ART) influences this risk. @@ -4817,9 +4812,9 @@ There were no significant differences in non-COVID-related intensive care admiss ConclusionIn this large, single-centre study, there was a change in hospitalised case-mix when comparing April 2019 with April 2020: an increase in conditions which potentially reflect social isolation (falls, drug and alcohol misuse and psychiatric illness) and a decrease in conditions which rarely require in-patient hospital treatment (musculoskeletal pain and non-cardiac chest pain) especially among younger adults. These results highlight two areas for further research; the impact of social isolation on health and whether younger adults could be offered alternative health services to avoid potentially unnecessary hospital assessment.",emergency medicine,fuzzy,100,100 medRxiv,10.1101/2020.09.17.20196469,2020-09-18,https://medrxiv.org/cgi/content/short/2020.09.17.20196469,Renin-angiotensin system inhibitors and susceptibility to COVID-19 in patients with hypertension: a propensity score-matched cohort study in primary care,Shamil Haroon; Anuradhaa Subramanian; Jennifer Cooper; Astha Anand; Krishna Gokhale; Nathan Byne; Samir Dhalla; Dionisio Acosta-Mena; Thomas Taverner; Kelvin Okoth; Jingya Wang; Joht Singh Chandan; Christopher Sainsbury; Dawit Tefra Zemedikun; G Neil Thomas; Dhruv Parekh; Tom Marshall; Elizabeth Sapey; Nicola J Adderley; Krishnarajah Nirantharakumar,"University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; Cegedim Health Data, Cegedim Rx, London, UK; Cegedim Health Data, Cegedim Rx, London, UK; Cegedim Health Data, Cegedim Rx, London, UK; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham and Department of Diabetes, Gartnavel General Hospital, NHS Greater Glasgow and Clyde, UK; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham; University of Birmingham","Introduction A significant proportion of patients with Coronavirus Disease-19 (COVID-19) have hypertension and are treated with renin-angiotensin system (RAS) inhibitors, namely angiotensin-converting enzyme I inhibitors (ACE inhibitors) or angiotensin II type-1 receptor blockers (ARBs). These medications have been postulated to influence susceptibility to Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The objective of this study was to assess a possible association between prescription of RAS inhibitors and the incidence of COVID-19 and all-cause mortality. Methods We conducted a propensity-score matched cohort study to assess the incidence of COVID-19 among patients with hypertension who were prescribed ACE inhibitors or ARBs compared to patients treated with calcium channel blockers (CCBs) in a large UK-based primary care database (The Health Improvement Network). We estimated crude incidence rates for confirmed/suspected COVID-19 among those prescribed ACE inhibitors, ARBs and CCBs. We used a Cox proportional hazards model to produce adjusted hazard ratios for COVID-19 comparing patients prescribed ACE inhibitors or ARBs to those prescribed CCBs. We further assessed all-cause mortality as a secondary outcome and a composite of accidents, trauma or fractures as a negative control outcome to assess for residual confounding. Results In the propensity score matched analysis, 83 of 18,895 users (0.44%) of ACE inhibitors developed COVID-19 over 8,923 person-years, an incidence rate of 9.3 per 1000 person-years. 85 of 18,895 (0.45%) users of CCBs developed COVID-19 over 8,932 person-years, an incidence rate of 9.5 per 1000 person-years. The adjusted hazard ratio for suspected/confirmed COVID-19 for users of ACE inhibitors compared to CCBs was 0.92 (95% CI 0.68 to 1.26). 79 out of 10,623 users (0.74%) of ARBs developed COVID-19 over 5010 person-years, an incidence rate of 15.8 per 1000 person-years, compared to 11.6 per 1000 person-years among users of CCBs. The adjusted hazard ratio for suspected/confirmed COVID-19 for users of ARBs compared to CCBs was 1.38 (95% CI 0.98 to 1.95). There were no significant associations between use of ACE inhibitors or ARBs and all-cause mortality, compared to use of CCBs. We found no evidence of significant residual confounding with the negative control analysis. Conclusion Current use of ACE inhibitors was not associated with the risk of suspected or confirmed COVID-19 whereas use of ARBs was associated with a statistically non-significant 38% relative increase in risk compared to use of CCBs. However, no significant associations were observed between prescription of either ACE inhibitors or ARBs and all-cause mortality during the peak of the pandemic.",infectious diseases,fuzzy,100,100 +bioRxiv,10.1101/2020.09.16.297945,2020-09-16,https://biorxiv.org/cgi/content/short/2020.09.16.297945,Characterisation of protease activity during SARS-CoV-2 infection identifies novel viral cleavage sites and cellular targets for drug repurposing,Bjoern Meyer; Jeanne Chiaravalli; Stacy Gellenoncourt; Philip Brownridge; Dominic P. Bryne; Leonard A. Daly; Arturas Grauslys; Marius Walter; Fabrice Agou; Lisa A. Chakrabarti; Charles S. Craik; Claire E. Eyers; Patrick A. Eyers; Yann Gambin; Andrew R Jones; Emma Sierecki; Eric Verdin; Marco Vignuzzi; Edward Emmott,Institut Pasteur; Institut Pasteur; Institut Pasteur; University of Liverpool; University of Liverpool; University of Liverpool; University of Liverpool; Buck Institute for Aging; Institut Pasteur; Institut Pasteur; UCSF; University of Liverpool; University of Liverpool; UNSW; University of Liverpool; UNSW; Buck Institute for Aging; Institut Pasteur; University of Liverpool,"SARS-CoV-2 is the causative agent behind the COVID-19 pandemic, and responsible for over 170 million infections, and over 3.7 million deaths worldwide. Efforts to test, treat and vaccinate against this pathogen all benefit from an improved understanding of the basic biology of SARS-CoV-2. Both viral and cellular proteases play a crucial role in SARS-CoV-2 replication, and inhibitors targeting proteases have already shown success at inhibiting SARS-CoV-2 in cell culture models. Here, we study proteolytic cleavage of viral and cellular proteins in two cell line models of SARS-CoV-2 replication using mass spectrometry to identify protein neo-N-termini generated through protease activity. We identify previously unknown cleavage sites in multiple viral proteins, including major antigenic proteins S and N, which are the main targets for vaccine and antibody testing efforts. We discovered significant increases in cellular cleavage events consistent with cleavage by SARS-CoV-2 main protease, and identify 14 potential high-confidence substrates of the main and papain-like proteases, validating a subset with in vitro assays. We showed that siRNA depletion of these cellular proteins inhibits SARS-CoV-2 replication, and that drugs targeting two of these proteins: the tyrosine kinase SRC and Ser/Thr kinase MYLK, showed a dose-dependent reduction in SARS-CoV-2 titres. Overall, our study provides a powerful resource to understand proteolysis in the context of viral infection, and to inform the development of targeted strategies to inhibit SARS-CoV-2 and treat COVID-19.",microbiology,fuzzy,100,100 medRxiv,10.1101/2020.09.12.20191973,2020-09-14,https://medrxiv.org/cgi/content/short/2020.09.12.20191973,Inequality in access to health and care services during lockdown - Findings from the COVID-19 survey in five UK national longitudinal studies,Constantin-Cristian Topriceanu; Andrew Wong; James C Moon; Alun Hughes; David Bann; Nishi Chaturvedi; Praveetha Patalay; Gabriella Conti; Gabriella Captur,University College London; UCL; UCL; UCL; University College London; UCL; University College London; UCL; University College London,"Background: Access to health services and adequate care is influenced by sex, ethnicity, socio-economic position (SEP) and burden of co-morbidities. However, it is unknown whether the COVID-19 pandemic further deepened these already existing health inequalities. Methods: Participants were from five longitudinal age-homogenous British cohorts (born in 2001, 1990, 1970, 1958 and 1946). A web and telephone-based survey provided data on cancelled surgical or medical appointments, and the number of care hours received during the UK COVID-19 national lockdown. Using binary or ordered logistic regression, we evaluated whether these outcomes differed by sex, ethnicity, SEP and having a chronic illness. Adjustment was made for study-design, non-response weights, psychological distress, presence of children or adolescents in the household, keyworker status, and whether participants had received a shielding letter. Meta-analyses were performed across the cohorts and meta-regression evaluated the effect of age as a moderator. Findings: 14891 participants were included. Females (OR 1.40, 95% confidence interval [1.27,1.55]) and those with a chronic illness (OR 1.84 [1.65-2.05]) experienced significantly more cancellations during lockdown (all p<0.0001). Ethnic minorities and those with a chronic illness required a higher number of care hours during the lockdown (both OR approx. 2.00, all p<0.002). Age was not independently associated with either outcome in meta-regression. SEP was not associated with cancellation or care hours. Interpretation: The UK government's lockdown approach during the COVID-19 pandemic appears to have deepened existing health inequalities, impacting predominantly females, ethnic-minorities and those with chronic illnesses. Public health authorities need to implement urgent policies to ensure equitable access to health and care for all in preparation for a second wave.",public and global health,fuzzy,100,100 medRxiv,10.1101/2020.09.13.20193730,2020-09-14,https://medrxiv.org/cgi/content/short/2020.09.13.20193730,Mental health service activity during COVID-19 lockdown among individuals with Personality Disorders: South London and Maudsley data on services and mortality from January to May 2020,Eleanor Nuzum; Evangelia Martin; Matthew Broadbent; Robert Stewart,South London and Maudsley NHS Foundation Trust; South London and Maudsley NHS Foundation Trust; South London and Maudsley NHS Foundation Trust; King's College London,"The lockdown and social distancing policy imposed due to the COVID-19 pandemic is likely to have a widespread impact on mental healthcare for both services themselves and the people accessing those services. Previous reports from the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in South London) highlighted a shift to virtual contacts among those accessing community mental health and home treatment teams and an increase in deaths over the pandemics first wave. However, there is a need to understand this further for specific groups, including those diagnosed with a personality disorder who might have particular vulnerabilities. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for individuals with personality disorders across community, specialist, crisis and inpatient services. The report focussed on the period 1st January to 31st May 2020. We also report on daily accepted and discharged trust referrals, total trust caseloads and daily inpatient admissions and discharges for individuals with personality disorders. In addition, daily deaths are described for all current and previous SLaM service users with personality disorder over this period. In summary, comparing periods before and after 16th March 2020 there was a shift from face-to-face contacts to virtual contacts across all teams. Liaison and Older Adult teams showed the largest drop in caseloads, whereas Early Intervention in Psychosis service caseloads remained the same. Reduced accepted referrals and inpatient admissions were observed and there was a 28% increase in average daily deaths in the period after 16th March, compared to the period 1st January to 15th March.",psychiatry and clinical psychology,fuzzy,100,100 -medRxiv,10.1101/2020.09.10.20191841,2020-09-11,https://medrxiv.org/cgi/content/short/2020.09.10.20191841,The King's College London Coronavirus Health and Experiences of Colleagues at King's Study: SARS-CoV-2 antibody response in an occupational sample,Daniel Leightley; Valentina Vitiello; Gabriella Bergin-Cartwright; Alice Wickersham; Katrina A S Davis; Sharon Stevelink; Matthew Hotopf; Reza Razavi; - On behalf of the KCL CHECK research team,"Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London; ","We report test results for SARS-CoV-2 antibodies in an occupational group of postgraduate research students and current members of staff at Kings College London. Between June and July 2020, antibody testing kits were sent to n=2296 participants; n=2004 (86.3%) responded, of whom n=1882 (93.9%) returned valid test results. Of those that returned valid results, n=124 (6.6%) tested positive for SARS-CoV-2 antibodies, with initial comparisons showing variation by age group and clinical exposure.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.09.11.20192492,2020-09-11,https://medrxiv.org/cgi/content/short/2020.09.11.20192492,Resurgence of SARS-CoV-2 in England: detection by community antigen surveillance,Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London","Background Based on cases and deaths, transmission of SARS-CoV-2 in England peaked in late March and early April 2020 and then declined until the end of June. Since the start of July, cases have increased, while deaths have continued to decrease. Methods We report results from 594,000 swabs tested for SARS-CoV-2 virus obtained from a representative sample of people in England over four rounds collected regardless of symptoms, starting in May 2020 and finishing at the beginning of September 2020. Swabs for the most recent two rounds were taken between 24th July and 11th August and for round 4 between 22nd August and 7th September. We estimate weighted overall prevalence, doubling times between and within rounds and associated reproduction numbers. We obtained unweighted prevalence estimates by sub-groups: age, sex, region, ethnicity, key worker status, household size, for which we also estimated odds of infection. We identified clusters of swab-positive participants who were closer, on average, to other swab-positive participants than would be expected. Findings Over all four rounds of the study, we found that 72% (67%, 76%) of swab-positive individuals were asymptomatic at the time of swab and in the week prior. The epidemic declined between rounds 1 and 2, and rounds 2 and 3. However, the epidemic was increasing between rounds 3 and 4, with a doubling time of 17 (13, 23) days corresponding to an R value of 1.3 (1.2, 1.4). When analysing round 3 alone, we found that the epidemic had started to grow again with 93% probability. Using only the most recent round 4 data, we estimated a doubling time of 7.7 (5.5, 12.7) days, corresponding to an R value of 1.7 (1.4, 2.0). Cycle threshold values were lower (viral loads were higher) for rounds 1 and 4 than they were for rounds 2 and 3. In round 4, we observed the highest prevalence in participants aged 18 to 24 years at 0.25% (0.16%, 0.41%), increasing from 0.08% (0.04%, 0.18%) in round 3. We observed the lowest prevalence in those aged 65 and older at 0.04% (0.02%, 0.06%) which was stable compared with round 3. Participants of Asian ethnicity had elevated odds of infection. We identified clusters in and around London, transient clusters in the Midlands, and an expanding area of clustering in the North West and more recently in Yorkshire and the Humber. Interpretation Although low levels of transmission persisted in England through to mid-summer 2020, the prevalence of SARS-CoV-2 is now increasing. We found evidence of accelerating transmission at the end of August and beginning of September. Representative community antigen sampling can increase situational awareness and help improve public health decision making even at low prevalence.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.09.04.20187781,2020-09-09,https://medrxiv.org/cgi/content/short/2020.09.04.20187781,Hydroxychloroquine for prevention of COVID-19 mortality: a population-based cohort study,Christopher T Rentsch; Nicholas J DeVito; Brian MacKenna; Caroline E Morton; Krishnan Bhaskaran; Jeremy P Brown; Anna Schultze; William J Hulme; Richard Croker; Alex J Walker; Elizabeth J Williamson; Chris Bates; Seb Bacon; Amir Mehrkar; Helen J Curtis; David Evans; Kevin Wing; Peter Inglesby; Rohini Mathur; Henry Drysdale; Angel YS Wong; Helen I McDonald; Jonathan Cockburn; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Liam Smeeth; Ian J Douglas; William G Dixon; Stephen JW Evans; Laurie Tomlinson; Ben Goldacre,London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; The Phoenix Partnership; University of Oxford; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Medicine and Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The University of Manchester; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundHydroxychloroquine has been shown to inhibit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro, but early clinical studies found no benefit treating patients with coronavirus disease 2019 (COVID-19). We set out to evaluate the effectiveness of hydroxychloroquine for prevention, as opposed to treatment, of COVID-19 mortality. @@ -5035,26 +5030,6 @@ FindingsWe find a 0{middle dot}5% (95% credible interval: -0{middle dot}2%-1{mid InterpretationOur study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2{middle dot}5 remains more uncertain. FundingMedical Research Council, Wellcome Trust, Environmental Protection Agency and National Institutes of Health.",public and global health,fuzzy,100,100 -medRxiv,10.1101/2020.08.10.20171033,2020-08-11,https://medrxiv.org/cgi/content/short/2020.08.10.20171033,Post-exertion oxygen saturation as a prognostic factor for adverse outcome in patients attending the emergency department with suspected COVID-19: Observational cohort study,Steve Goodacre; Ben Thomas; Ellen Lee; Laura Sutton; Katie Biggs; Carl Marincowitz; Amanda Loban; Simon Waterhouse; Richard Simmonds; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter,"University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust, Wythenshawe Hospital; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust","BackgroundMeasurement of post-exertion oxygen saturation has been proposed to assess illness severity in suspected COVID-19 infection. We aimed to determine the accuracy of post-exertional oxygen saturation for predicting adverse outcome in suspected COVID-19. - -MethodsWe undertook an observational cohort study across 70 emergency departments during first wave of the COVID-19 pandemic in the United Kingdom. We collected data prospectively, using a standardised assessment form, and retrospectively, using hospital records, from patients with suspected COVID-19, and reviewed hospital records at 30 days for adverse outcome (death or receiving organ support). Patients with post-exertion oxygen saturation recorded were selected for this analysis. - -ResultsWe analysed data from 817 patients with post-exertion oxygen saturation recorded after excluding 54 in whom measurement appeared unfeasible. The c-statistic for post-exertion change in oxygen saturation was 0.589 (95% confidence interval 0.465 to 0.713), and the positive and negative likelihood ratios of a 3% or more desaturation were respectively 1.78 (1.25 to 2.53) and 0.67 (0.46 to 0.98). Multivariable analysis showed that post-exertion oxygen saturation was not a significant predictor of adverse outcome when baseline clinical assessment was taken into account (p=0.368). Secondary analysis excluding patients in whom post-exertion measurement appeared inappropriate resulted in a c-statistic of 0.699 (0.581 to 0.817), likelihood ratios of 1.98 (1.26 to 3.10) and 0.61 (0.35 to 1.07), and some evidence of additional prognostic value on multivariable analysis (p=0.019). - -ConclusionsPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19. - -RegistrationISRCTN registry, ISRCTN56149622, http://www.isrctn.com/ISRCTN28342533 - -Key messagesWhat is already known on this subject? - -O_LIPost exertional decrease in oxygen saturation can be used to predict prognosis in chronic lung diseases -C_LIO_LIPost exertional desaturation has been proposed as a way of predicting adverse outcome in people with suspected COVID-19 -C_LI - -What this study adds: - -O_LIPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19 -C_LI",emergency medicine,fuzzy,100,100 medRxiv,10.1101/2020.08.07.20169490,2020-08-07,https://medrxiv.org/cgi/content/short/2020.08.07.20169490,HIV infection and COVID-19 death: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform,Krishnan Bhaskaran; Christopher T Rentsch; Brian MacKenna; Anna Schultz; Amir Mehrkar; Chris Bates; Rosalind M Eggo; Caroline E Morton; Seb Bacon; Peter Inglesby; Ian J Douglas; Alex J Walker; Helen I McDonald; Jonathan Cockburn; Elizabeth J Williamson; David Evans; Harriet J Forbes; Helen J Curtis; William Hulme; John Parry; Frank Hester; Sam Harper; Stephen JW Evans; Liam Smeeth; Ben Goldacre,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; TPP; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundIt is unclear whether HIV infection is associated with risk of COVID-19 death. We aimed to investigate this in a large-scale population-based study in England. MethodsWorking on behalf of NHS England, we used the OpenSAFELY platform to analyse routinely collected electronic primary care data linked to national death registrations. People with a primary care record for HIV infection were compared to people without HIV. COVID-19 death was defined by ICD-10 codes U07.1 or U07.2 anywhere on the death certificate. Cox regression models were used to estimate the association between HIV infection and COVID-19 death, initially adjusted for age and sex, then adding adjustment for index of multiple deprivation and ethnicity, and finally for a broad range of comorbidities. Interaction terms were added to assess effect modification by age, sex, ethnicity, comorbidities and calendar time. @@ -5336,23 +5311,6 @@ What is already known on this topic- Unprecedented control measures, such as nat What this study adds- The percentage of individuals from the general community in England testing positive for SARS-CoV-2 clearly declined between 26 April and 28 June 2020 from around one in three 300 to around one in a thousand. - Risk factors for testing positive included having a job with direct patient contact, having had (indirect) contact with a hospital in the past 2 weeks, and working outside your home. - Positive tests commonly occurred without symptoms being reported and the percentage of individuals with a positive test that reported no symptoms was stable over time.",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2020.07.03.20145912,2020-07-06,https://medrxiv.org/cgi/content/short/2020.07.03.20145912,Ultraviolet A Radiation and COVID-19 Deaths: A Multi Country Study,Mark Cherrie; Tom Clemens; Claudio Colandrea; Zhiqiang Feng; David Webb; Chris Dibben; Richard B Weller,University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh,"ObjectivesTo determine whether UVA exposure might be associated with COVID-19 deaths - -DesignEcological regression, with replication in two other countries and pooled estimation - -Setting2,474 counties of the contiguous USA, 6,755 municipalities in Italy, 6,274 small areas in England. Only small areas in their Vitamin D winter (monthly mean UVvitd of under 165 KJ/m2) from Jan to April 2020. - -Participants - -The at-risk population is the total small area population, with measures to incorporate spatial infection into the model. The model is adjusted for potential confounders including long-term winter temperature and humidity. - -Main outcome measuresWe derive UVA measures for each area from remote sensed data and estimate their relationship with COVID-19 mortality with a random effect for States, in a multilevel zero-inflated negative binomial model. In the USA and England death certificates had to record COVID-19. In Italy excess deaths in 2020 over expected from 2015-19. - -Data sourcesSatellite derived mean daily UVA dataset from Japan Aerospace Exploration Agency. Data on deaths compiled by Center for Disease Control (USA), Office for National Statistics (England) and Italian Institute of Statistics. - -ResultsDaily mean UVA (January-April 2020) varied between 450 to 1,000 KJ/m2 across the three countries. Our fully adjusted model showed an inverse correlation between UVA and COVID-19 mortality with a Mortality Risk Ratio (MRR) of 0.71 (0.60 to 0.85) per 100KJ/m2 increase UVA in the USA, 0.81 (0.71 to 0.93) in Italy and 0.49 (0.38 to 0.64) in England. Pooled MRR was 0.68 (0.52 to 0.88). - -ConclusionsOur analysis, replicated in 3 independent national datasets, suggests ambient UVA exposure is associated with lower COVID-19 specific mortality. This effect is independent of vitamin D, as it occurred at irradiances below that likely to induce significant cutaneous vitamin D3 synthesis. Causal interpretations must be made cautiously in observational studies. Nonetheless this study suggests strategies for reduction of COVID-19 mortality.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.07.03.20145839,2020-07-04,https://medrxiv.org/cgi/content/short/2020.07.03.20145839,"The Impact of COVID-19 on Adjusted Mortality Risk in Care Homes for Older Adults in Wales, United Kingdom: A retrospective population-based cohort study for mortality in 2016-2020",Joe Hollinghurst; Jane Lyons; Richard Fry; Ashley Akbari; Mike Gravenor; Alan Watkins; Fiona Verity; Ronan A Lyons,Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University,"BackgroundMortality in care homes has had a prominent focus during the COVID-19 outbreak. Multiple and interconnected challenges face the care home sector in the prevention and management of outbreaks of COVID-19, including adequate supply of personal protective equipment, staff shortages, and insufficient or lack of timely COVID-19 testing. Care homes are particularly vulnerable to infectious diseases. AimTo analyse the mortality of older care home residents in Wales during COVID-19 lockdown and compare this across the population of Wales and the previous 4-years. @@ -5450,13 +5408,6 @@ FindingsWe identified 148,588 people with COPD and 817,973 people with asthma re InterpretationThese results do not support a major role of ICS in protecting against COVID-19 related deaths. Observed increased risks of COVID-19 related death among people with COPD and asthma receiving ICS can be plausibly explained by unmeasured confounding due to disease severity. FundingThis work was supported by the Medical Research Council MR/V015737/1.",respiratory medicine,fuzzy,100,100 -medRxiv,10.1101/2020.06.18.20134742,2020-06-20,https://medrxiv.org/cgi/content/short/2020.06.18.20134742,Racial and ethnic determinants of Covid-19 risk,Chun-Han Lo; Long H. Nguyen; David A. Drew; Mark S. Graham; Erica T. Warner; Amit D. Joshi; Christina M. Astley; Chuan-Guo Guo; Wenjie Ma; Raaj S. Mehta; Sohee Kwon; Mingyang Song; Richard Davies; Joan Capdevila; Karla A. Lee; Mary Ni Lochlainn; Thomas Varsavsky; Carole H. Sudre; Jonathan Wolf; Yvette C. Cozier; Lynn Rosenberg; Lynne R. Wilkens; Christopher A. Haiman; Loic Le Marchand; Julie R. Palmer; Tim D. Spector; Sebastien Ourselin; Claire J. Steves; Andrew T. Chan; - COPE Consortium,"Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Computational Epidemiology Lab and Division of Endocrinology, Boston Children's Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Zoe Global Limited, London, U.K.; Zoe Global Limited, London, U.K.; Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K.; Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K.; School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K.; School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K.; Zoe Global Limited, London, U.K.; Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A.; Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A.; Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, U.S.A.; Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, California, U.; Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, U.S.A.; Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A.; Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K.; School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K.; Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; ","BackgroundRacial and ethnic minorities have disproportionately high hospitalization rates and mortality related to the novel coronavirus disease 2019 (Covid-19). There are comparatively scant data on race and ethnicity as determinants of infection risk. - -MethodsWe used a smartphone application (beginning March 24, 2020 in the United Kingdom [U.K.] and March 29, 2020 in the United States [U.S.]) to recruit 2,414,601 participants who reported their race/ethnicity through May 25, 2020 and employed logistic regression to determine the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for a positive Covid-19 test among racial and ethnic groups. - -ResultsWe documented 8,858 self-reported cases of Covid-19 among 2,259,841 non-Hispanic white; 79 among 9,615 Hispanic; 186 among 18,176 Black; 598 among 63,316 Asian; and 347 among 63,653 other racial minority participants. Compared with non-Hispanic white participants, the risk for a positive Covid-19 test was increased across racial minorities (aORs ranging from 1.24 to 3.51). After adjustment for socioeconomic indices and Covid-19 exposure risk factors, the associations (aOR [95% CI]) were attenuated but remained significant for Hispanic (1.58 [1.24-2.02]) and Black participants (2.56 [1.93-3.39]) in the U.S. and South Asian (1.52 [1.38-1.67]) and Middle Eastern participants (1.56 [1.25-1.95]) in the U.K. A higher risk of Covid-19 and seeking or receiving treatment was also observed for several racial/ethnic minority subgroups. - -ConclusionsOur results demonstrate an increase in Covid-19 risk among racial and ethnic minorities not completely explained by other risk factors for Covid-19, comorbidities, and sociodemographic characteristics. Further research investigating these disparities are needed to inform public health measures.",public and global health,fuzzy,100,100 medRxiv,10.1101/2020.06.17.20133959,2020-06-20,https://medrxiv.org/cgi/content/short/2020.06.17.20133959,A downscaling approach to compare COVID-19 count data from databases aggregated at different spatial scales,Andre Python; Andreas Bender; Marta Blangiardo; Janine B Illian; Ying Lin; Baoli Liu; Tim C D Lucas; Siwei Tan; Yingying Wen; Davit Svanidze; Jianwei Yin,University of Oxford; LMU Munich; Imperial College London; Glasgow University; Fuzhou University; Oxford University; University of Oxford; Zhejiang University; Zhejiang University; Goettingen University; Zhejiang University,"As the COVID-19 pandemic continues to threaten various regions around the world, obtaining accurate and reliable COVID-19 data is crucial for governments and local communities aiming at rigorously assessing the extent and magnitude of the virus spread and deploying efficient interventions. Using data reported between January and February 2020 in China, we compared counts of COVID-19 from near-real time spatially disaggregated data (city-level) with fine-spatial scale predictions from a Bayesian downscaling regression model applied to a reference province-level dataset. The results highlight discrepancies in the counts of coronavirus-infected cases at district level and identify districts that may require further investigation.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.06.16.20133116,2020-06-18,https://medrxiv.org/cgi/content/short/2020.06.16.20133116,Mental health during the COVID-19 pandemic in two longitudinal UK population cohorts,Alex Siu Fung Kwong; Rebecca M Pearson; Mark J Adams; Kate Northstone; Kate Tilling; Daniel Smith; Chloe Fawns-Ritchie; Helen Bould; Naomi Warne; Stan Zammit; David J Gunnell; Paul Moran; Nadia Micali; Abraham Reichenberg; Matthew Hickman; Dheeraj Rai; Simon Haworth; Archie Campbell; Drew Altschul; Robin Flaig; Andrew M McIntosh; Deborah A Lawlor; David Porteous; Nicholas J Timpson,University of Bristol; University of Bristol; University of Edinburgh; University of Bristol; University of Bristol; University of Bristol; University of Edinburgh; University of Bristol; University of Bristol; Cardiff University; University of Bristol; University of Bristol; UCL; Mount Sinai; University of Bristol; University of Bristol; University of Bristol; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Bristol; University of Edinburgh; University of Bristol,"BackgroundThe impact of COVID-19 on mental health is unclear. Evidence from longitudinal studies with pre pandemic data are needed to address (1) how mental health has changed from pre-pandemic levels to during the COVID-19 pandemic and (2), whether there are groups at greater risk of poorer mental health during the pandemic? @@ -5489,7 +5440,6 @@ MethodsMultivariate logistic regression analysis performed on age-matched sample ResultsHospital cohort: significantly higher prevalence of delirium in the frail sample, with no difference in fever or cough. Community-based cohort :significantly higher prevalence of probable delirium in frailer, older adults, and fatigue and shortness of breath. ConclusionsThis is the first study demonstrating higher prevalence of delirium as a COVID-19 symptom in older adults with frailty compared to other older adults. This emphasises need for systematic frailty assessment and screening for delirium in acutely ill older patients in hospital and community settings. Clinicians should suspect COVID-19 in frail adults with delirium.",geriatric medicine,fuzzy,94,100 -medRxiv,10.1101/2020.06.13.20130419,2020-06-16,https://medrxiv.org/cgi/content/short/2020.06.13.20130419,Mental health service activity during COVID-19 lockdown: South London and Maudsley data on working age community and home treatment team services and mortality from February to mid-May 2020,Robert Stewart; Evangelia Martin; Matthew Broadbent,King's College London; King's College London; South London and Maudsley NHS Foundation Trust,"The lockdown and social distancing policy response to the COVID-19 pandemic in the UK has a potentially important impact on provision of mental healthcare; however, there has been relatively little quantification of this. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for home treatment teams (HTTs) and working age adult community mental health teams (CMHTs) from 1st February to 15th May 2020 at the South London and Maudsley NHS Trust (SLaM), a large mental health service provider for 1.2m residents in south London. In addition daily deaths are described for all current and previous SLaM service users over this period and the same dates in 2019. In summary, comparing periods before and after 16th March 2020 the CMHT sector showed relatively stable caseloads and total contact numbers, but a substantial shift from face-to-face to virtual contacts, while HTTs showed the same changeover but reductions in caseloads and total contacts (although potentially an activity rise again during May). Number of deaths for the two months between 16th March and 15th May were 2.4-fold higher in 2020 than 2019, with 958 excess deaths.",psychiatry and clinical psychology,fuzzy,100,100 medRxiv,10.1101/2020.06.12.20129056,2020-06-16,https://medrxiv.org/cgi/content/short/2020.06.12.20129056,Symptom clusters in Covid19: A potential clinical prediction tool from the COVID Symptom study app,Carole H Sudre; Karla Lee; Mary Ni Lochlainn; Thomas Varsavsky; Benjamin Murray; Mark S. Graham; Cristina Menni; Marc Modat; Ruth C.E. Bowyer; Long H Nguyen; David Alden Drew; Amit D Joshi; Wenjie Ma; Chuan Guo Guo; Chun Han Lo; Sajaysurya Ganesh; Abubakar Buwe; Joan Capdevila Pujol; Julien Lavigne du Cadet; Alessia Visconti; Maxim Freydin; Julia S. El Sayed Moustafa; Mario Falchi; Richard Davies; Maria F. Gomez; Tove Fall; M. Jorge Cardoso; Jonathan Wolf; Paul W Franks; Andrew T Chan; Timothy D Spector; Claire J Steves; Sebastien Ourselin,King's College London; Department of Twin Research and Genetic Epidemiology; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Zoe Global Limited; Zoe Global Limited; Zoe Global Limited; Zoe Global Limited; King's College London; King's College London; King's College London; King's College London; Zoe Global Limited; Lund University; Lund University; King's College London; Zoe Global Limited; Lund University; Massachusetts General Hospital; King's College London; King's College London; King's College London,"As no one symptom can predict disease severity or the need for dedicated medical support in COVID-19, we asked if documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between May 1-May 28th, 2020. Using the first 5 days of symptom logging, the ROC-AUC of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required. One sentence summaryLongitudinal clustering of symptoms can predict the need for respiratory support in severe COVID-19.",health informatics,fuzzy,94,100 @@ -5508,6 +5458,24 @@ MethodsWe used an individual based model for a synthetic population similar to t ResultsClustering contacts outside the household into exclusive social bubbles is an effective strategy of increasing contacts while limiting some of the associated increase in epidemic risk. In the base case scenario social bubbles reduced cases and fatalities by 17% compared to an unclustered increase of contacts. We find that if all households were to form social bubbles the reproduction number would likely increase to 1.1 and therefore beyond the epidemic threshold of one. However, strategies that allow households with young children or single occupancy households to form social bubbles only increased the reproduction number by less than 10%. The corresponding increase in morbidity and mortality is proportional to the increase in the epidemic risk but is largely focussed in older adults independently of whether these are included in the social bubbles. ConclusionsSocial bubbles can be an effective way of extending contacts beyond the household limiting the increase in epidemic risk, if managed appropriately.",infectious diseases,fuzzy,100,100 +medRxiv,10.1101/2020.06.10.20127563,2020-06-12,https://medrxiv.org/cgi/content/short/2020.06.10.20127563,"Multimorbidity, Polypharmacy, and COVID-19 infection within the UK Biobank cohort.",Ross McQueenie; Hamish Foster; Bhautesh D Jani; Srinivasa Vittal Katikireddi; Naveed Sattar; Jill P Pell; Frederick K Ho; Claire L Niedzwiedz; Claire E Hastie; Jana Anderson; Patrick B Mark; Michael Sullivan; Frances S Mair; Barbara I Nicholl,"University of Glasgow, Instutute of Health and Wellbeing; University of Glasgow, Instutute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Cardiovascular and Medical Sciences; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Cardiovascular and Medical Sciences; University of Glasgow, Institute of Cardiovascular and Medical Sciences; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing","BACKGROUNDIt is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity ([≥]2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. + +METHODS AND FINDINGSWe studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with [≥]2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and [≥]2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response increased risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI [≥]40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. + +CONCLUSIONSIncreasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19. + +Author summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIMultimorbidity is a growing global challenge, but thus far LTC prognostic factors for severe COVID-19 primarily involve single conditions and there is a lack of data on the influence of multimorbidity on the risk of COVID-19. +C_LIO_LIAs countries move from the lockdown phase of COVID-19, clinicians need more information about risk stratification to appropriately advise patients with multimorbidity about risk prevention steps. +C_LI + +What did the researchers do and find?O_LIParticipants with multimorbidity ([≥]2 LTCs) had a 48% higher risk of a positive COVID-19 test, those with cardiometabolic multimorbidity had a 77% higher risk, than those without that type of multimorbidity. +C_LIO_LIThose from non-white ethnicities with multimorbidity had nearly three times the risk of having COVID-19 infection compared to those of white ethnicity +C_LIO_LIPeople with multimorbidity with the highest risk of COVID-19 infection were the most socioeconomically deprived, those with BMI [≥]40 kg/m2, and those with reduced renal function. +C_LI + +What do these findings mean?O_LIIndividuals with [≥]2 LTCs, especially if these are cardiometabolic in nature, should be particularly stringent in adhering to preventive measures, such as physical distancing and hand hygiene. +C_LIO_LIOur findings have implications for clinicians, occupational health and employers when considering work-place environments, appropriate advice for patients, and adaptations that might be required to protect such staff, identified here, as higher risk. +C_LI",epidemiology,fuzzy,100,91 medRxiv,10.1101/2020.06.10.20127175,2020-06-11,https://medrxiv.org/cgi/content/short/2020.06.10.20127175,Excess deaths in people with cardiovascular diseases during the COVID-19 pandemic.,Amitava Banerjee; Suliang Chen; Laura Pasea; Alvina Lai; Michail Katsoulis; Spiros Denaxas; Vahe Nafilyan; Bryan Williams; Wai Keong Wong; Ameet Bakhai; Kamlesh Khunti; Deenan Pillay; Mahdad Noursadeghi; Honghan Wu; Nilesh Pareek; Daniel Bromage; Theresa Mcdonagh; Jonathan Byrne; James T Teo; Ajay Shah; Ben Humberstone; Liang V Tang; Anoop SV Shah; Andrea Rubboli; Yutao Guo; Yu Hu; Cathie LM Sudlow; Gregory YH Lip; Harry Hemingway,"University College London; University College London; University College London; University College London; UCL; University College London; Office for National Statistics; UCL; University College London Hospitals NHS Trust; Royal Free Hospitals NHS Trust; University of Leicester; UCL; UCL; UCL; King's College Hospital; Kings College London; Kings College London; Kings London NHS Trust; Kings College Hospital NHS Foundation Trust; King's College London; Office for National Statistics; Huazhong University of Science and Technology, Wuhan, China; University of Edinburgh; Ospedale S. Maria delle Croci, Ravenna, Italy; PLA General Hospital, Beijing, China.; Huazhong University of Science and Technology, Wuhan, China.; University of Edinburgh; University of Liverpool; UCL","BackgroundCardiovascular diseases(CVD) increase mortality risk from coronavirus infection(COVID-19), but there are concerns that the pandemic has affected supply and demand of acute cardiovascular care. We estimated excess mortality in specific CVDs, both ""direct"", through infection, and ""indirect"", through changes in healthcare. MethodsWe used population-based electronic health records from 3,862,012 individuals in England to estimate pre- and post-COVID-19 mortality risk(""direct"" effect) for people with incident and prevalent CVD. We incorporated: (i)pre-COVID-19 risk by age, sex and comorbidities, (ii)estimated population COVID-19 prevalence, and (iii)estimated relative impact of COVID-19 on mortality(relative risk, RR: 1.5, 2.0 and 3.0). For ""indirect"" effects, we analysed weekly mortality and emergency department data for England/Wales and monthly hospital data from England(n=2), China(n=5) and Italy(n=1) for CVD referral, diagnosis and treatment until 1 May 2020. @@ -5546,19 +5514,6 @@ ResultsThere were 56,961 excess deaths and 8,986 were non-COVID excess deaths. E ConclusionsContinuous monitoring of excess mortality trends and further integration of age- and gender-stratified and underlying cause of death data beyond COVID-19 will allow dynamic assessment of the impacts of indirect and direct mortality of the COVID-19 pandemic.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.06.05.20122226,2020-06-07,https://medrxiv.org/cgi/content/short/2020.06.05.20122226,"Different adiposity measures across sex, age, ethnicity, and COVID-19",Naveed Sattar; Frederick K Ho; Jason MR Gill; Nazim Ghouri; Stuart R Gray; Carlos A Celis-Morales; Srinivasa Vittal Katikireddi; Colin Berry; Jill P Pell; John JV McMurray; Paul Welsh,University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University of Glasgow; University Of Glasgow,"We examined the link between BMI and risk of a positive test for SARS-CoV-2 and risk of COVID-19-related death among UK Biobank participants. Among 4855 participants tested for SARS-CoV-2 in hospital, 839 were positive and of these 189 died from COVID-19. Poisson models with penalised thin plate splines were run relating exposures of interest to test positivity and case-fatality, adjusting for confounding factors. BMI was associated strongly with positive test, and risk of death related to COVID-19. The gradient of risk in relation to BMI was steeper in those under 70, compared with those aged 70 years or older for COVID-19 related death (Pinteraction=0.03). BMI was more strongly related to test positivity (Pinteraction=0.010) and death (Pinteraction=0.002) in non-whites, compared with whites. These data add support for adiposity being more strongly linked to COVID-19-related deaths in younger people and non-white ethnicities. If future studies confirm causality, lifestyle interventions to improve adiposity status may be important to reduce the risk of COVID-19 in all, but perhaps particularly, non-white communities.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2020.06.02.20120642,2020-06-05,https://medrxiv.org/cgi/content/short/2020.06.02.20120642,Estimating excess visual loss in people with neovascular age-related macular degeneration during the COVID-19 pandemic,Darren S Thomas; Alasdair Warwick; Abraham Olvera-Barrios; Catherine Egan; Roy Schwartz; Sudeshna Patra; Haralabos Eleftheriadis; Anthony P Khawaja; Andrew Lotery; Philipp L Mueller; Robin Hamilton; Ella Preston; Paul Taylor; Adnan Tufail; - UK EMR Users Group,"Institute of Health Informatics, University College London, London, UK; Institute of Cardiovascular Science, University College London, London, UK & Moorfields Eye Hospital NHS Foundation Trust, London, UK.; Moorfields Eye Hospital NHS Turst & Institute of Ophthalmology UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Health Informatics, University College London, London, UK; Bart's Health NHS Trust, London, UK; King's College Hospital NHS Trust, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Faculty of Medicine, University of Southampton, Southampton, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK; Institute of Health Informatics, University College London, London, UK; Moorfields Eye Hospital NHS Trust & Institute of Ophthalmology UCL; ","ObjectivesTo report the reduction in new neovascular age-related macular degeneration (nAMD) referrals during the COVID-19 pandemic and estimate the impact of delayed treatment on visual outcomes at one year. - -DesignRetrospective clinical audit and simulation model. - -SettingMultiple UK NHS ophthalmology centres. - -ParticipantsData on the reduction in new nAMD referrals was obtained from four NHS Trusts in England comparing April 2020 to April 2019. To estimate the potential impact on one-year visual outcomes, a stratified bootstrap simulation model was developed drawing on an electronic medical records dataset of 20,825 nAMD eyes from 27 NHS Trusts. - -Main outcome measuresSimulated mean visual acuity and proportions of eyes with vision [≤]6/60, [≤]6/24 and [≥]6/12 at one year under four hypothetical scenarios: no treatment delay, 3, 6 and 9-month treatment delays. Estimated additional number of eyes with vision [≤]6/60 at one year nationally. - -ResultsThe number of nAMD referrals at four major eye treatment hospital groups based in England dropped on average by 72% (range 65 to 87%) in April 2020 compared to April 2019. Simulated one-year visual outcomes for 1000 nAMD eyes with a 3-month treatment delay suggested an increase in the proportion of eyes with vision [≤]6/60 from 15.5% (13.2 to 17.9) to 23.3% (20.7 to25.9), and a decrease in the proportion of eyes with vision [≥]6/12 (driving vision) from 35.1% (32.1 to 38.1) to 26.4% (23.8 to29.2). Outcomes worsened incrementally with longer modelled delays. Assuming nAMD referrals are reduced to this level at the national level for only one month, these simulated results suggest an additional 186-365 eyes with vision [≤]6/60 at one-year with even a short treatment delay. - -ConclusionsWe report a large decrease in nAMD referrals during the first month of COVID-19 lockdown and provide an important public health message regarding the risk of delayed treatment. As a conservative estimate, a treatment delay of 3 months could lead to a >50% relative increase in the number of eyes with vision [≤]6/60 and 25% relative decrease in the number of eyes with driving vision at one year.",ophthalmology,fuzzy,100,100 medRxiv,10.1101/2020.06.02.20118489,2020-06-05,https://medrxiv.org/cgi/content/short/2020.06.02.20118489,Development and implementation of a customised rapid syndromic diagnostic test for severe pneumonia,Vilas Navapurkar; Josefin Bartholdson-Scott; Mailis Maes; Thomas P Hellyer; Ellen Higginson; Sally Forrest; Joana Pereira Dias; Surendra Parmar; Emma Heasman-Hunt; Petra Polgarova; Joanne Brown; Lissamma Titti; William PW Smith; Jonathan Scott; Anthony Rostron; Matthew Routledge; David Sapsford; M. Estee Torok; Ronan McMullan; David Enoch; Vanessa Wong; - VAPrapid investigators; Martin D Curran; Nicholas Brown; A John Simpson; Jurgen Herre; Gordon Dougan; Andrew Conway Morris,"Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; University of Cambridge; Translational and Clinical Research Institute, Newcastle University, United Kingdom; University of Cambridge; University of Cambridge; University of Cambridge; Public Health England Microbiology Laboratory, Addenbrooke's Hospital, Cambridge; Public Health England Microbiology Laboratory, Addenbrooke's Hospital, Cambridge; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; Translational and Clinical Research Institute, Newcastle University, United Kingdom; Translational and Clinical Research Institute, Newcastle University, United Kingdom; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS FoundationTrust; Wellcome-Wolfson Institute for Experimental Medicine, Queens University Belfast, United Kingdom; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; ; Public Health England Microbiology Laboratory, Addenbrookes Hospital, Cambridge; Public Health England Microbiology Laboratory, Addenbrooke's Hospital, Cambridge; Translational and Clinical Research Institute, Newcastle University, United Kingdom; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; University of Cambridge","BackgroundMicrobial cultures for the diagnosis of pneumonia take several days to return a result, and are frequently negative, compromising antimicrobial stewardship. The objective of this study was to establish the performance of a syndromic molecular diagnostic approach, using a custom TaqMan array card (TAC) covering 52 respiratory pathogens, and assess its impact on antimicrobial prescribing. MethodsThe TAC was validated against a retrospective multi-centre cohort of broncho-alveolar lavage samples. The TAC was assessed prospectively in patients undergoing investigation for suspected pneumonia, with a comparator cohort formed of patients investigated when the TAC laboratory team were unavailable. @@ -5642,6 +5597,13 @@ Main outcome measuresAll-cause mortality, and mortality attributed to COVID-19 o ResultsOverall, 26% (95% confidence interval 22 to 31) of residents died over the two-month period. All-cause mortality increased by 203% (95% CI 70 to 336). Systematic testing identified 40% (95% CI 35 to 46) of residents, of whom 43% (95% CI 34 to 52) were asymptomatic and 18% (95% CI 11 to 24) had atypical symptoms, as well as 4% (95% CI -1 to 9) of asymptomatic staff who tested positive for SARS-CoV-2. ConclusionsThe SARS-CoV-2 outbreak was associated with a very high mortality rate in residents of nursing homes. Systematic testing of all residents and a representative sample of staff identified high rates of SARS-CoV-2 positivity across the four nursing homes, highlighting a potential for regular screening to prevent future outbreaks.",public and global health,fuzzy,96,100 +medRxiv,10.1101/2020.05.19.20106641,2020-05-26,https://medrxiv.org/cgi/content/short/2020.05.19.20106641,Study Data Element Mapping: Feasibility of Defining Common Data Elements Across COVID-19 Studies,Priscilla Mathewson; Ben Gordon; Kay Snowley; Clara Fennessy; Alastair Denniston; Neil Sebire,University of Birmingham; HDRUK; HDRUK; HDRUK; HDRUK; Great Ormond Street Hospital and ICH London,"BackgroundNumerous clinical studies are now underway investigating aspects of COVID-19. The aim of this study was to identify a selection of national and/or multicentre clinical COVID-19 studies in the United Kingdom to examine the feasibility and outcomes of documenting the most frequent data elements common across studies to rapidly inform future study design and demonstrate proof-of-concept for further subject-specific study data element mapping to improve research data management. + +Methods25 COVID-19 studies were included. For each, information regarding the specific data elements being collected was recorded. Data elements collated were arbitrarily divided into categories for ease of visualisation. Elements which were most frequently and consistently recorded across studies are presented in relation to their relative commonality. + +ResultsAcross the 25 studies, 261 data elements were recorded in total. The most frequently recorded 100 data elements were identified across all studies and are presented with relative frequencies. Categories with the largest numbers of common elements included demographics, admission criteria, medical history and investigations. Mortality and need for specific respiratory support were the most common outcome measures, but with specific studies including a range of other outcome measures. + +ConclusionThe findings of this study have demonstrated that it is feasible to collate specific data elements recorded across a range of studies investigating a specific clinical condition in order to identify those elements which are most common among studies. These data may be of value for those establishing new studies and to allow researchers to rapidly identify studies collecting data of potential use hence minimising duplication and increasing data re-use and interoperability",health informatics,fuzzy,100,100 medRxiv,10.1101/2020.05.19.20106781,2020-05-26,https://medrxiv.org/cgi/content/short/2020.05.19.20106781,Hypertension and renin-angiotensin system blockers are not associated with expression of Angiotensin Converting Enzyme 2 (ACE2) in the kidney,Xiao Jiang; James M. Eales; David Scannali; Alicja Nazgiewicz; Priscilla Prestes; Michelle Maier; Matthew J. Denniff; Xiaoguang Xu; Sushant Saluja; Eddie Cano-Gamez; Wojciech Wystrychowski; Monika Szulinska; Andrzej Antczak; Sean Byars; Maciej Glyda; Robert Krol; Joanna Zywiec; Ewa Zukowska-Szczechowska; Louise M. Burrell; Adrian S. Woolf; Adam Greenstein; Pawel Bogdanski; Bernard Keavney; Andrew P. Morris; Anthony Heagerty; Bryan Williams; Stephen B. Harrap; Gosia Trynka; Nilesh J. Samani; Tomasz J. Guzik; Fadi J. Charchar; Maciej Tomaszewski,"University of Manchester, Manchester, UK; University of Manchester, Manchester, UK; University of Manchester, Manchester, UK; University of Manchester, Manchester, UK; Federation University Australia, Ballarat, Victoria, Australia; Federation University Australia, Ballarat, Victoria, Australia; University of Leicester, Leicester, UK; University of Manchester, Manchester, UK; University of Manchester, Manchester, UK; Wellcome Sanger Institute, Cambridge, UK; Medical University of Silesia, Katowice, Poland; Poznan University of Medical Sciences, Poznan, Poland.; Karol Marcinkowski University of Medical Sciences, Poznan, Poland; The University of Melbourne, Parkville, Victoria, Australia; Nicolaus Copernicus University, Bydgoszcz, Poland; Medical University of Silesia, Katowice, Poland; Medical University of Silesia, Zabrze, Poland; Silesian Medical College, Katowice, Poland; University of Melbourne, Melbourne, Victoria, Australia; University of Manchester, Manchester, UK; University of Manchester, Manchester, UK; Poznan University of Medical Sciences, Poznan, Poland; University of Manchester, Manchester, UK; University of Manchester, Manchester, UK; University of Manchester, Manchester, UK; University College London, London, UK; University of Melbourne, Melbourne, Victoria, Australia; Wellcome Sanger Institute, Cambridge, UK; University of Leicester, Leicester, UK; University of Glasgow, Glasgow, UK; Federation University Australia, Ballarat, Victoria, Australia; University of Manchester, Manchester, UK","Angiotensin converting enzyme 2 (ACE2) is the cellular entry point for severe acute respiratory syndrome coronavirus (SARS-CoV-2) - the cause of COVID-19 disease. It has been hypothesized that use of renin-angiotensin system (RAS) inhibiting medications in patients with hypertension, increases the expression of ACE2 and thereby increases the risk of COVID-19 infection and severe outcomes or death. However, the effect of RAS-inhibition on ACE2 expression in human tissues of key relevance to blood pressure regulation and COVID-19 infection has not previously been reported. We examined how hypertension, its major metabolic co-phenotypes and antihypertensive medications relate to ACE2 renal expression using information from up to 436 patients whose kidney transcriptomes were characterised by RNA-sequencing. We further validated some of the key observations in other human tissues and/or a controlled experimental model. Our data reveal increasing expression of ACE2 with age in both human lungs and the kidney. We show no association between renal expression of ACE2 and either hypertension or common types of RAS inhibiting drugs. We demonstrate that renal abundance of ACE2 is positively associated with a biochemical index of kidney function and show a strong enrichment for genes responsible for kidney health and disease in ACE2 co-expression analysis. @@ -5718,17 +5680,6 @@ FindingsWe screened 270 studies and included 6. The pooled estimate for the asym InterpretationThe asymptomatic proportion of SARS-CoV-2 infections is relatively low when estimated from methodologically-appropriate studies. Further investigation into the degree and duration of infectiousness for asymptomatic infections is warranted. FundingMedical Research Council",infectious diseases,fuzzy,100,100 -medRxiv,10.1101/2020.05.18.20086157,2020-05-22,https://medrxiv.org/cgi/content/short/2020.05.18.20086157,COVID-19 in Great Britain: epidemiological and clinical characteristics of the first few hundred (FF100) cases: a descriptive case series and case control analysis,Nicola L Boddington; Andre Charlett; Suzanne Elgohari; Jemma L Walker; Helen Mcdonald; Chloe Byers; Laura Coughlan; Tatiana Garcia Vilaplana; Rosie Whillock; Mary Sinnathamby; Nikolaos Panagiotopoulos; Louise Letley; Pauline MacDonald; Roberto Vivancos; Obaghe Edeghere; Joseph Shingleton; Emma Bennett; Daniel J Grint; Helen Strongman; Kathryn E Mansfield; Christopher Rentsch; Caroline Minassian; Ian J Douglas; Rohini Mathur; Maria Peppa; Simon Cottrell; Jim McMenamin; Maria Zambon; Mary Ramsay; Gavin Dabrera; Vanessa Saliba; Jamie Lopez Bernal,Public Health England; Public Health England; Public Health England; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Public Health Wales; Public Health Scotland; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England,"ObjectivesFollowing detection of the first virologically-confirmed cases of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and underlying health conditions associated with infection of the first few hundred cases. - -MethodsInformation was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity, specificity and predictive value of symptoms and underlying health conditions associated with infection were conducted. Point prevalences of underlying health conditions among the UK general population were presented. - -FindingsThe majority of FF100 cases were imported (51.4%), of which the majority had recent travel to Italy (71.4%). 24.7% were secondary cases acquired mainly through household contact (40.4%). Children had lower odds of COVID-19 infection compared with the general population. - -The clinical presentation of cases was dominated by cough, fever and fatigue. Non-linear relationships with age were observed for fever, and sensitivity and specificity of symptoms varied by age. - -Conditions associated with higher odds of COVID-19 infection (after adjusting for age and sex) were chronic heart disease, immunosuppression and multimorbidity. - -ConclusionThis study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study characterized underlying health conditions associated with infection and set relative risks in context with population prevalence estimates. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.05.18.20105288,2020-05-21,https://medrxiv.org/cgi/content/short/2020.05.18.20105288,Current tobacco smoking and risk from COVID-19: results from a population symptom app in over 2.4 million people,Nicholas S Hopkinson; Niccolo Rossi; Julia El-Sayed Moustafa; Anthony A Laverty; Jennifer K Quint; Maxim B Freydin; Alessia Visconti; Benjamin Murray; Marc Modat; Sebastien Ourselin; Kerrin Small; Richard Davies; Jonathan Wolf; Timothy Spector; Claire J Steves; Mario Falchi,"Imperial College London; King's College London; King's College London; Imperial College London; Imperial College, London; King's College London; King's College, London; King's College, London; King's College, London; King's College, London; King's College, London; Zoe Global Ltd; Zoe Global Ltd; King's College London; King's College London; King's College, London","BackgroundThe association between current tobacco smoking, the risk of developing COVID-19 and the severity of illness is an important information gap. MethodsUK users of the COVID Symptom Study app provided baseline data including demographics, anthropometrics, smoking status and medical conditions, were asked to log symptoms daily from 24th March 2020 to 23rd April 2020. Participants reporting that they did not feel physically normal were taken through a series of questions, including 14 potential COVID-19 symptoms and any hospital attendance. The main study outcome was the association between current smoking and the development of ""classic"" symptoms of COVID-19 during the pandemic defined as fever, new persistent cough and breathlessness. The number of concurrent COVID-19 symptoms was used as a proxy for severity. In addition, association of subcutaneous adipose tissue expression of ACE2, both the receptor for SARS-CoV-2 and a potential mediator of disease severity, with smoking status was assessed in a subset of 541 twins from the TwinsUK cohort. @@ -6064,13 +6015,19 @@ MethodsWe used a stochastic, individual-based model to simulate SARS-CoV-2 trans ResultsIn the baseline scenario, randomly introducing SARS-CoV-2 into a 170-bed LTCF led to large outbreaks, with a cumulative 86 (6-224) infections after three weeks of unmitigated transmission. Efficacy of symptom-based screening was limited by (i) lags between infection and symptom onset, and (ii) silent transmission from asymptomatic and pre-symptomatic infections. Testing upon admission detected up to 66% of patients silently infected upon LTCF entry, but missed potential introductions from staff. Random daily testing was more effective when targeting patients than staff, but was overall an inefficient use of limited resources. At high testing capacity (>1 test/10 beds/day), cascades were most effective, with a 22-52% probability of detecting outbreaks prior to any nosocomial transmission, and 38-63% prior to first onset of COVID-19 symptoms. Conversely, at low capacity (<1 test/85 beds/day), pooling randomly selected patients in a daily group test was most effective (9-15% probability of detecting outbreaks prior to transmission; 30-44% prior to symptoms). The most efficient strategy compared to the reference was to pool individuals with any COVID-like symptoms, requiring only 5-7 additional tests and 17-24 additional swabs to detect outbreaks 5-6 days earlier, prior to an additional 14-18 infections. ConclusionsGroup testing is an effective and efficient COVID-19 surveillance strategy for resource-limited LTCFs. Cascades are even more effective given ample testing resources. Increasing testing capacity and updating surveillance protocols accordingly could facilitate earlier detection of emerging outbreaks, informing a need for urgent intervention in settings with ongoing nosocomial transmission.",epidemiology,fuzzy,100,100 -medRxiv,10.1101/2020.04.15.20066407,2020-04-20,https://medrxiv.org/cgi/content/short/2020.04.15.20066407,Evaluation of antibody testing for SARS-Cov-2 using ELISA and lateral flow immunoassays,Emily R Adams; Mark Ainsworth; Rekha Anand; Monique I Andersson; Kathryn Auckland; J Kenneth Baillie; Eleanor Barnes; Sally Beer; John Bell; Tamsin Berry; Sagida Bibi; Miles Carroll; Senthil Chinnakannan; Elizabeth Clutterbuck; Richard J Cornall; Derrick W Crook; Thushan De Silva; Wanwisa Dejnirattisai; Kate E Dingle; Christina Dold; Alexis Espinosa; David W Eyre; Helen Farmer; Maria Fernandez Mendoza; Dominique Georgiou; Sarah J Hoosdally; Alistair Hunter; Katie Jeffrey; Paul Klenerman; Julian Knight; Clarice Knowles; Andrew J Kwok; Ullrich Leuschner; Robert Levin; Chang Liu; Cesar Lopez-Camacho; Jose Carlos Martinez Garrido; Philippa C Matthews; Hannah McGivern; Alexander J Mentzer; Jonathan Milton; Juthathip Mongkolsapaya; Shona C Moore; Marta S Oliveira; Fiona Pereira; Elena Perez Lopez; Timothy Peto; Rutger J Ploeg; Andrew Pollard; Tessa Prince; David J Roberts; Justine K Rudkin; Veronica Sanchez; Gavin R Screaton; Malcolm G Semple; Donal T Skelly; Jose Slon-Campos; Elliot Nathan Smith; Alberto Jose Sobrino Diaz; Julie Staves; David Stuart; Piyada Supasa; Tomas Surik; Hannah Thraves; Pat Tsang; Lance Turtle; A Sarah Walker; Beibei Wang; Charlotte Washington; Nicholas Watkins; James Whitehouse,"Liverpool School of Tropical Medicine; Oxford University Hospitals NHS Foundation Trust; NHSBT Birmingham,; Department of Microbiology, Oxford University Hospital NHS Foundation Trust; The Wellcome Centre for Human Genetics, University of Oxford; Roslin Institute, University of Edinburgh; Nuffield Department of Medicine, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Department of Medicine, University of Oxford; Department of Health and Social Care, University of Oxford; Oxford Vaccine group, Department of Pediatrics, University of Oxford; Nuffield Department of Medicine, Centre of Tropical Medicine and Global Health and Public Health England; Nuffield Department of Medicine, University of Oxford; Oxford Vaccine Group, Department of Paediatrics, University of Oxford; Nuffield Department of Medicine, University of Oxford; NIHR Oxford Biomedical Research Centre; Department of Infection, Immunity and Cardiovascular, Disease, The Medical School, University of Sheffield; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; NIHR Oxford Biomedical Research Centre, University of Oxford; Oxford Vaccine Group, Department of Paediatrics, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Big Data Institute, University of Oxford; Department of Health and Social Care, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Oxford University Hospitals NHS Foundation Trust; Nuffield Department of Medicine, University of Oxford; NHSBT Basildon; Department of Clinical Medicine, Oxford University Hospitals NHS Foundation Trusts; Nuffield Department so Medicine, University of Oxford; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; Department of Health and Social Care, University of Oxford; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; NHSBT Oxford; Worthing Hospital, Worthing, West Sussex; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; Wellcome Centre of Genetics, Nuffield Department of Medicine, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Nuffield Department of Medicine, University of Medicine; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Wellcome Centre for Human Genetics, University of Oxford; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, University of Liverpool; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Imperial College London; Oxford University Hospitals NHS Foundation Trust; NIHR Oxford Biomedical Research centre, University of Oxford; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Department of Paediatrics, University of Oxford; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, University of Liverpool; NHSBT Oxford; Nuffield Department of Population Health & Big Data Institute, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; Health Protection Unit In Emerging and Zoonotic Infection, University of Liverpool; Nuffield Department of Clinical Neurosciences, University of Oxford; University of Oxford; Department of Health and Social Care, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Oxford University Hospitals,; Wellcome Centre for Human Genetics, Nuffield Department of Medicine; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Oxford University Hospitals NHS Foundation Trust; NHSBT Oxford; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, University of Liverpool; Nuffield Department of Medicine, University of Oxford; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; NHSBT, Birmingham; NHSBT, Cambridge; Department of Health and Social Care, University of Oxford","BackgroundThe COVID-19 pandemic caused >1 million infections during January-March 2020. There is an urgent need for reliable antibody detection approaches to support diagnosis, vaccine development, safe release of individuals from quarantine, and population lock-down exit strategies. We set out to evaluate the performance of ELISA and lateral flow immunoassay (LFIA) devices. +medRxiv,10.1101/2020.04.16.20067504,2020-04-21,https://medrxiv.org/cgi/content/short/2020.04.16.20067504,"The effect of inter-city travel restrictions on geographical spread of COVID-19: Evidence from Wuhan, China",Billy J Quilty; Charlie Diamond; Yang Liu; Hamish Gibbs; Timothy W Russell; Christopher I Jarvis; Kiesha Prem; Carl A B Pearson; Samuel J Clifford; Stefan Flasche; CMMID COVID-19 working group; Petra Klepac; Rosalind M Eggo; Mark Jit,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine,"BackgroundTo contain the spread of COVID-19, a cordon sanitaire was put in place in Wuhan prior to the Lunar New Year, on 23 January 2020, restricting travel to other parts of China. We assess the efficacy of the cordon sanitaire to delay the introduction and onset of local transmission of COVID-19 in other major cities in mainland China. + +MethodsWe estimated the number of infected travellers from Wuhan to other major cities in mainland China from November 2019 to March 2020 using previously estimated COVID-19 prevalence in Wuhan and publicly available mobility data. We focused on Beijing, Chongqing, Hangzhou, and Shenzhen as four representative major cities to identify the potential independent contribution of the cordon sanitaire and holiday travel. To do this, we simulated outbreaks generated by infected arrivals in these destination cities using stochastic branching processes. We also modelled the effect of the cordon sanitaire in combination with reduced transmissibility scenarios representing the effect of local non-pharmaceutical interventions. + +FindingsIn the four cities, given the potentially high prevalence of COVID-19 in Wuhan between Dec 2019 and early Jan 2020, local transmission may have been seeded as early as 2 - 8 January 2020. By the time the cordon sanitaire was imposed, simulated case counts were likely in the hundreds. The cordon sanitaire alone did not substantially affect the epidemic progression in these cities, although it may have had some effect in smaller cities. + +InterpretationOur results indicate that the cordon sanitaire may not have prevented COVID-19 spread in major Chinese cities; local non-pharmaceutical interventions were likely more important for this. -MethodsWe tested plasma for COVID (SARS-CoV-2) IgM and IgG antibodies by ELISA and using nine different LFIA devices. We used a panel of plasma samples from individuals who have had confirmed COVID infection based on a PCR result (n=40), and pre-pandemic negative control samples banked in the UK prior to December-2019 (n=142). +Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSIn late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected in Wuhan, China. In response to the outbreak, authorities enacted a cordon sanitaire in order to limit spread. Several studies have sought to determine the efficacy of the policy; a search of PubMed for ""coronavirus AND (travel restrictions OR travel ban OR shutdown OR cordon sanitaire) AND (Wuhan OR China)"" returned 24 results. However other studies have relied on reported cases to determine efficacy, which are likely subject to reporting and testing biases. Early outbreak dynamics are also subject to a significant degree of stochastic uncertainty due to small numbers of cases. -ResultsELISA detected IgM or IgG in 34/40 individuals with a confirmed history of COVID infection (sensitivity 85%, 95%CI 70-94%), vs. 0/50 pre-pandemic controls (specificity 100% [95%CI 93-100%]). IgG levels were detected in 31/31 COVID-positive individuals tested [≥]10 days after symptom onset (sensitivity 100%, 95%CI 89-100%). IgG titres rose during the 3 weeks post symptom onset and began to fall by 8 weeks, but remained above the detection threshold. Point estimates for the sensitivity of LFIA devices ranged from 55-70% versus RT-PCR and 65-85% versus ELISA, with specificity 95-100% and 93-100% respectively. Within the limits of the study size, the performance of most LFIA devices was similar. +Added value of this studyHere we use publicly-available mobility data and a stochastic branching process model to evaluate the efficacy of the cordon sanitaire to limiting the spread of COVID-19 from Wuhan to other cities in mainland China, while accounting for underreporting and uncertainty. We find that although travel restrictions led to a significant decrease in the number of individuals leaving Wuhan during the busy post-Lunar New Year holiday travel period, local transmission was likely already established in major cities. Thus, the travel restrictions likely did not affect the epidemic trajectory substantially in these cities. -ConclusionsCurrently available commercial LFIA devices do not perform sufficiently well for individual patient applications. However, ELISA can be calibrated to be specific for detecting and quantifying SARS-CoV-2 IgM and IgG and is highly sensitive for IgG from 10 days following first symptoms.",infectious diseases,fuzzy,100,100 +Implications of all the available evidenceA cordon sanitaire around the epicentre alone may not be able to reduce COVID-19 incidence when implemented after local transmission has occurred in highly connected neighbors. Local non-pharmaceutical interventions to reduce transmissibility (e.g., school and workplace closures) may have contributed more to the observed decrease in incidence in mainland China.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.04.14.20065417,2020-04-17,https://medrxiv.org/cgi/content/short/2020.04.14.20065417,Clinical academic research in the time of Corona: a simulation study in England and a call for action,Amitava Banerjee; Michail Katsoulis; Alvina G Lai; Laura Pasea; Thomas A Treibel; Charlotte Manisty; Spiros Denaxas; Giovanni Quarta; Harry Hemingway; Joao Cavalcante; Mahdad Nousardeghi; James C Moon,"University College London; University College London; University College London; University College London; University College London; University College London; University College London; Ospedale Papa Giovanni XXIII, Bergamo, Italy; University College London; Minneapolis Heart Institute, Minneapolis, Minnesota. USA; University College London; University College London","BackgroundCoronavirus (COVID-19) poses health system challenges in every country. As with any public health emergency, a major component of the global response is timely, effective science. However, particular factors specific to COVID-19 must be overcome to ensure that research efforts are optimised. We aimed to model the impact of COVID-19 on the clinical academic response in the UK, and to provide recommendations for COVID-related research. MethodsWe constructed a simple stochastic model to determine clinical academic capacity in the UK in four policy approaches to COVID-19 with differing population infection rates: ""Italy model"" (6%), ""mitigation"" (10%), ""relaxed mitigation"" (40%) and ""do-nothing"" (80%) scenarios. The ability to conduct research in the COVID-19 climate is affected by the following key factors: (i) infection growth rate and population infection rate (from UK COVID-19 statistics and WHO); (ii) strain on the healthcare system (from published model); and (iii) availability of clinical academic staff with appropriate skillsets affected by frontline clinical activity and sickness (from UK statistics). @@ -6078,6 +6035,11 @@ MethodsWe constructed a simple stochastic model to determine clinical academic c FindingsIn ""Italy model"", ""mitigation"", ""relaxed mitigation"" and ""do-nothing"" scenarios, from 5 March 2020 the duration (days) and peak infection rates (%) are 95(2.4%), 115(2.5%), 240(5.3%) and 240(16.7%) respectively. Near complete attrition of academia (87% reduction, <400 clinical academics) occurs 35 days after pandemic start for 11, 34, 62, 76 days respectively - with no clinical academics at all for 37 days in the ""do-nothing"" scenario. Restoration of normal academic workforce (80% of normal capacity) takes 11,12, 30 and 26 weeks respectively. InterpretationPandemic COVID-19 crushes the science needed at system level. National policies mitigate, but the academic community needs to adapt. We highlight six key strategies: radical prioritisation (eg 3-4 research ideas per institution), deep resourcing, non-standard leadership (repurposing of key non-frontline teams), rationalisation (profoundly simple approaches), careful site selection (eg protected sites with large academic backup) and complete suspension of academic competition with collaborative approaches.",health systems and quality improvement,fuzzy,100,100 +medRxiv,10.1101/2020.04.09.20059865,2020-04-14,https://medrxiv.org/cgi/content/short/2020.04.09.20059865,Forecasting the scale of the COVID-19 epidemic in Kenya,Samuel P C Brand; Rabia Aziza; Ivy K Kombe; Charles N Agoti; Joe Hilton; Kat S Rock; Andrea Parisi; D James Nokes; Matt Keeling; Edwine Barasa,"University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme; Kenya Medical Research Institute, Wellcome Trust Research Programme; University of Warwick; University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme and University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme","BackgroundThe first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya. + +MethodsWe developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak. + +ResultsWe find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 -2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.",infectious diseases,fuzzy,100,100 medRxiv,10.1101/2020.04.10.20059121,2020-04-14,https://medrxiv.org/cgi/content/short/2020.04.10.20059121,"ACE inhibition and cardiometabolic risk factors, lung ACE2 and TMPRSS2 gene expression, and plasma ACE2 levels: a Mendelian randomization study",Dipender Gill; Marios Arvanitis; Paul Carter; Ana I Hernandez Cordero; Brian Jo; Ville Karhunen; Susanna C Larsson; Xuan Li; Sam M Lockhart; Amy M Mason; Evanthia Pashos; Ashis Saha; Vanessa Tan; Verena Zuber; Yohan Bosse; Sarah Fahle; Ke Hao; Tao Jiang; Philippe Joubert; Alan C Lunt; Willem hendrik Ouwehand; David J Roberts; Wim Timens; Maarten van den Berge; Nicholas A Watkins; Alexis Battle; Adam S Butterworth; John Danesh; Barbara E Engelhard; James E Peters; Don Sin; Stephen Burgess,"Imperial College London; Johns Hopkins University; University of Cambridge; The University of British Columbia Center for Heart Lung Innovation; Lewis Sigler Institute for Integrative Biology; Imperial College London; Karolinska Institutet; The University of British Columbia Center for Heart Lung Innovation; University of Cambridge; University of Cambridge; Pfizer; Johns Hopkins University; University of Bristol; Imperial College London; Laval University, Quebec; University of Cambridge; School of Medicine at Mount Sinai; University of Cambridge; Laval University, Quebec; Imperial College London; University of Cambridge; University of Oxford; University of Groningen; University of Groningen; University of Cambridge; Johns Hopkins University; University of Cambridge; University of Cambridge; Princeton University; Imperial College London; University of British Columbia; University of Cambridge","ObjectivesTo use human genetic variants that proxy angiotensin-converting enzyme (ACE) inhibitor drug effects and cardiovascular risk factors to provide insight into how these exposures affect lung ACE2 and TMPRSS2 gene expression and circulating ACE2 levels. DesignTwo-sample Mendelian randomization (MR) analysis. @@ -6201,6 +6163,13 @@ medRxiv,10.1101/2020.03.05.20031773,2020-03-08,https://medrxiv.org/cgi/content/s AimTo estimate the infection and case fatality ratio of COVID-19, using data from passengers of the Diamond Princess cruise ship while correcting for delays between confirmation-and-death, and age-structure of the population.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.02.26.20028167,2020-02-27,https://medrxiv.org/cgi/content/short/2020.02.26.20028167,Estimation of country-level basic reproductive ratios for novel Coronavirus (COVID-19) using synthetic contact matrices,Joe Hilton; Matt J Keeling,University of Warwick; University of Warwick,"The outbreak of novel coronavirus (COVID-19) has the potential for global spread, infecting large numbers in all countries. In this case, estimating the country-specific basic reproductive ratio is a vital first step in public-health planning. The basic reproductive ratio (R0) is determined by both the nature of pathogen and the network of contacts through which the disease can spread - with this network determined by socio-demographics including age-structure and household composition. Here we focus on the age-structured transmission within the population, using data from China to inform age-dependent susceptibility and synthetic age-mixing matrices to inform the contact network. This allows us to determine the country-specific basic reproductive ratio as a multiplicative scaling of the value from China. We predict that R0 will be highest across Eastern Europe and Japan, and lowest across Africa, Central America and South-Western Asia. This pattern is largely driven by the ratio of children to older adults in each country and the observed propensity of clinical cases in the elderly.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.02.14.20023036,2020-02-17,https://medrxiv.org/cgi/content/short/2020.02.14.20023036,The Efficacy of Contact Tracing for the Containment of the 2019 Novel Coronavirus (COVID-19).,Matt J Keeling; T. Deirdre Hollingsworth; Jonathan M Read,University of Warwick; Oxford University; Lancaster University,"Contact tracing is a central public health response to infectious disease outbreaks, especially in the early stages of an outbreak when specific treatments are limited. Importation of novel Coronavirus (COVID-19) from China and elsewhere into the United Kingdom highlights the need to understand the impact of contact tracing as a control measure. Using detailed survey information on social encounters coupled to predictive models, we investigate the likely efficacy of the current UK definition of a close contact (within 2 meters for 15 minutes or more) and the distribution of secondary cases that may go untraced. Taking recent estimates for COVID-19 transmission, we show that less than 1 in 5 cases will generate any subsequent untraced cases, although this comes at a high logistical burden with an average of 36.1 individuals (95th percentiles 0-182) traced per case. Changes to the definition of a close contact can reduce this burden, but with increased risk of untraced cases; we estimate that any definition where close contact requires more than 4 hours of contact is likely to lead to uncontrolled spread.",public and global health,fuzzy,100,100 +medRxiv,10.1101/2020.02.12.20022566,2020-02-14,https://medrxiv.org/cgi/content/short/2020.02.12.20022566,A spatial model of CoVID-19 transmission in England and Wales: early spread and peak timing,Leon Danon; Ellen Brooks-Pollock; Mick Bailey; Matt J Keeling,University of Exeter; University of Bristol; University of Bristol; University of Warwick,"BackgroundAn outbreak of a novel coronavirus, named CoVID-19, was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable cases of human-to-human transmission in England. + +MethodsWe adapted an existing national-scale metapopulation model to capture the spread of CoVID-19 in England and Wales. We used 2011 census data to capture population sizes and population movement, together with parameter estimates from the current outbreak in China. + +ResultsWe predict that a CoVID-19 outbreak will peak 126 to 147 days ([~]4 months) after the start of person-to-person transmission in England and Wales in the absence of controls, assuming biological parameters remain unchanged. Therefore, if person-to-person transmission persists from February, we predict the epidemic peak would occur in June. The starting location has minimal impact on peak timing, and model stochasticity varies peak timing by 10 days. Incorporating realistic parameter uncertainty leads to estimates of peak time ranging from 78 days to 241 days after person-to-person transmission has been established. Seasonal changes in transmission rate substantially impact the timing and size of the epidemic peak, as well as the total attack rate. + +DiscussionWe provide initial estimates of the potential course of CoVID-19 in England and Wales in the absence of control measures. These results can be refined with improved estimates of epidemiological parameters, and permit investigation of control measures and cost effectiveness analyses. Seasonal changes in transmission rate could shift the timing of the peak into winter months, which will have important implications for health-care capacity planning.",epidemiology,fuzzy,100,100 medRxiv,10.1101/2020.02.12.20022426,2020-02-13,https://medrxiv.org/cgi/content/short/2020.02.12.20022426,Interventions targeting air travellers early in the pandemic may delay local outbreaks of SARS-CoV-2,Samuel J Clifford; Carl A B Pearson; Petra Klepac; Kevin Van Zandvoort; Billy J Quilty; - CMMID COVID-19 working group; Rosalind M Eggo; Stefan Flasche,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; -; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine,"BackgroundWe evaluated if interventions aimed at air travellers can delay local SARS-CoV-2 community transmission in a previously unaffected country. MethodsWe simulated infected air travellers arriving into countries with no sustained SARS-CoV-2 transmission or other introduction routes from affected regions. We assessed the effectiveness of syndromic screening at departure and/or arrival & traveller sensitisation to the COVID-2019-like symptoms with the aim to trigger rapid self-isolation and reporting on symptom onset to enable contact tracing. We assumed that syndromic screening would reduce the number of infected arrivals and that traveller sensitisation reduces the average number of secondary cases. We use stochastic simulations to account for uncertainty in both arrival and secondary infections rates, and present sensitivity analyses on arrival rates of infected travellers and the effectiveness of traveller sensitisation. We report the median expected delay achievable in each scenario and an inner 50% interval. diff --git a/data/covid/preprints.exact.csv b/data/covid/preprints.exact.csv index 0650467d..1a299f24 100644 --- a/data/covid/preprints.exact.csv +++ b/data/covid/preprints.exact.csv @@ -34,20 +34,6 @@ MethodData were from 5,630 individuals participating in Virus Watch, a prospecti ResultsPredicted probability of long-term sequelae was greater following SARS-CoV-2 infection during the Wild Type (adjusted predicted probability (PP) 0.28, 95% confidence interval (CI) =0.14-0.43), Alpha (PP= 0.28, 95% CI =0.14-0.42), Delta (PP= 0.34, 95% CI=0.25-0.43) and Omicron BA.1 periods (PP= 0.27, 95% CI =0.22-0.33) compared to later Omicron sub-variants (PP range from 0.11, 95% CI 0.08-0.15 to 0.14, 95% CI 0.10-0.18). While differences between SARS-CoV-2 and other ARIs (PP range 0.08, 95% CI 0.04-0.11 to 0.23, 95% CI 0.18-0.28) varied by period, estimates for long-term symptoms following both infection types substantially exceeded those for non-infected participants (PP range 0.01, 95% CI 0.00,0.02 to 0.03, 95% CI 0.01-0.06) across all variant periods. ConclusionsBetween-variant differences influenced the likelihood of post-infection sequelae for SARS-CoV-2, with lower predicted probabilities for recent Omicron sub-variants similar to those for other contemporaneous ARIs. Both SARS-CoV-2 and other ARIs were associated with long-term symptom development, and further aetiological investigation including between-pathogen comparison is recommended.",epidemiology,exact,100,100 -medRxiv,10.1101/2023.12.07.23299429,2023-12-09,https://medrxiv.org/cgi/content/short/2023.12.07.23299429,Mechanisms underlying exercise intolerance in Long COVID: an accumulation of multi-system dysfunction,Alexandra Jamieson; Lamia Al Saikhan; Lamis Alghamdi; Lee Hamill Howes; Helen Purcell; Toby Hillman; Melissa J Heightman; Thomas A. Treibel; Michele Orini; Robert Midgley Bell; Marie Scully; Mark Hamer; Nishi Chaturvedi; Alun Hughes; Ronan Astin; Siana Jones,"University College London; Imam Abdulrahman Bin Faisal University; University College London; University College London; University College London Hospitals NHS Foundation Trust; University College London Hospitals NHS Foundation Trust; UCLH; University College London; University College London; The Hatter Cardiovascular Institute, University College London; University College London Hospitals NHS Foundation Trust; UCL; University College London; UCL; University College London Hospitals NHS Foundation Trust; University College London","The pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood. - -Cases were recruited from a Long COVID clinic (N=32; 44{+/-}12y; 10(31%)men), and age/sex- matched healthy controls (HC) (N=19; 40{+/-}13y; 6(32%)men) from University College London staff and students. We assessed exercise performance, lung and cardiac function, vascular health, skeletal muscle oxidative capacity and autonomic nervous system (ANS) function. Key outcome measures for each physiological system were compared between groups using potential outcome means(95% confidence intervals) adjusted for potential confounders. Long COVID participant outcomes were compared to normative values. - -When compared to HC, cases exhibited reduced Oxygen Uptake Efficiency Slope (1847(1679,2016) vs (2176(1978,2373) ml/min, p=0.002) and Anaerobic Threshold (13.2(12.2,14.3) vs 15.6(14.4,17.2) ml/Kg/min, p<0.001), and lower oxidative capacity on near infrared spectroscopy ({tau}: 38.7(31.9,45.6) vs 24.6(19.1,30.1) seconds, p=0.001). In cases, ANS measures fell below normal limits in 39%. - -Long COVID is associated with reduced measures of exercise performance and skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology. There was evidence of attendant ANS dysregulation in a significant proportion. These multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers. - -Key PointsO_LIThe pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood. -C_LIO_LIWe show that Long COVID is associated with reduced measures of exercise performance in line with previous work. -C_LIO_LIIn Long COVID cases, we observed reduced skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology. -C_LIO_LIWe also observed evidence of attendant autonomic nervous system (ANS) dysregulation in a significant proportion of Long COVID cases. -C_LIO_LIThese multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers. -C_LI",cardiovascular medicine,exact,100,100 medRxiv,10.1101/2023.12.06.23299601,2023-12-07,https://medrxiv.org/cgi/content/short/2023.12.06.23299601,The impact of Long COVID on Health-Related Quality-of-life using OpenPROMPT,Oliver Carlile; Andrew Briggs; Alasdair Henderson; Ben Butler-Cole; John Tazare; Laurie Tomlinson; Michael Marks; Mark Jit; Liang-Yu Lin; Chris Bates; John Parry; Sebastian Bacon; Iain Dillingham; William Dennison; Ruth Costello; Alex Walker; William J Hulme; Ben Goldacre; Amir Mehrkar; Brian MacKenna; - The OpenSAFELY Collaborative; Emily Herrett; Rosalind Eggo,"London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; TPP; TPP; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Patient and Public Involvement Steering Committee; London School of Hygiene and Tropical Medicine; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; Bennett Institute for Applied Data Science, Nuffield Department of Primary Care Health Sciences, University of Oxford; -; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine","BackgroundLong COVID is a major problem affecting patient health, the health service, and the workforce. To optimise the design of future interventions against COVID-19, and to better plan and allocate health resources, it is critical to quantify the health and economic burden of this novel condition. MethodsWith the approval of NHS England, we developed OpenPROMPT, a UK cohort study measuring the impact of long COVID on health-related quality-of-life (HRQoL). OpenPROMPT invited responses to Patient Reported Outcome Measures (PROMs) using a smartphone application and recruited between November 2022 and October 2023. We used the validated EuroQol EQ-5D questionnaire with the UK Value Set to develop disutility scores (1-utility) for respondents with and without Long COVID using linear mixed models, and we calculated subsequent Quality-Adjusted Life-Months (QALMs) for long COVID. @@ -150,6 +136,13 @@ Added value of this studyThis study is the first to quantify changes in fit note Implications of all the available evidenceWhile we have likely underestimated the fit note rate due to overcounting of people in the workforce and misclassification of COVID-19 status, we still identified a substantial increased risk of receiving a fit note in people with COVID-19 compared with the general population over all years, even after adjusting for demographics and a wide range of clinical characteristics. The increased risk persisted into 2022, in an era where most people are vaccinated and the severity of COVID-19 illness is lessened. Given the high infection rates still occurring, these findings provide evidence for a substantial impact of COVID-19 on productivity and further evidence of the long-term impacts of COVID-19.",epidemiology,exact,100,100 medRxiv,10.1101/2023.08.02.23293519,2023-08-04,https://medrxiv.org/cgi/content/short/2023.08.02.23293519,Real-time epidemiological modelling during the COVID-19 emergency in Wales,Michael Gravenor; Mark Dawson; Ed Bennett; Ben Thorpe; Carla White; Alma Rahat; Daniel Archambault; Noemi Picco; Gibin Powathil; Biagio Lucini,Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University,"The sudden outbreak of the COVID-19 pandemic presented governments, policy makers and health services with an unprecedented challenge of taking real-time decisions that could keep the disease under control with non-pharmaceutical interventions, while at the same time limit as much as possible severe consequences of a very strict lockdown. Mathematical modelling has proved to be a crucial element for informing those decisions. Here we report on the rapid development and application of the Swansea Model, a mathematical model of disease spread in real time, to inform policy decisions during the COVID-19 pandemic in Wales.",epidemiology,exact,100,100 medRxiv,10.1101/2023.06.29.23292056,2023-07-01,https://medrxiv.org/cgi/content/short/2023.06.29.23292056,Genome-wide Association Study of Long COVID,Vilma Lammi; Tomoko Nakanishi; Samuel E Jones; Shea J Andrews; Juha Karjalainen; Beatriz Cortes; Heath E O'Brien; Brian E Fulton-Howard; Hele H Haapaniemi; Axel Schmidt; Ruth E Mitchell; Abdou Mousas; Massimo Mangino; Alicia Huerta-Chagoya; Nasa Sinnott-Armstrong; Elizabeth T Cirulli; Marc Vaudel; Alex SF Kwong; Amit K Maiti; Minttu M Marttila; Chiara Batini; Francesca Minnai; Anna R Dearman; CA Robert Warmerdam; Celia B Sequeros; Thomas W Winkler; Daniel M Jordan; Lindsay Guare; Ekaterina Vergasova; Eirini Marouli; Pasquale Striano; Ummu Afeera Zainulabid; Ashutosh Kumar; Hajar Fauzan Ahmad; Ryuya Edahiro; Shuhei Azekawa; - Long COVID Host Genetics Initiative; - FinnGen; - DBDS Genomic Consortium; - GEN-COVID Multicenter Study; Joseph J Grzymski; Makoto Ishii; Yukinori Okada; Noam D Beckmann; Meena Kumari; Ralf Wagner; Iris M Heid; Catherine John; Patrick J Short; Per Magnus; Karina Banasik; Frank Geller; Lude H Franke; Alexander Rakitko; Emma L Duncan; Alessandra Renieri; Konstantinos K Tsilidis; Rafael de Cid; Ahmadreza Niavarani; Teresa Tusie-Luna; Shefali S Verma; George Davey Smith; Nicholas J Timpson; Mark J Daly; Andrea Ganna; Eva C Schulte; J Brent Richards; Kerstin U Ludwig; Michael Hultstrom; Hugo Zeberg; Hanna M Ollila,Institute for Molecular Medicine Finland (FIMM); Department of Human Genetics; Institute for Molecular Medicine Finland (FIMM); University of California San Francisco; Institute for Molecular Medicine Finland (FIMM); Genomes for Life-GCAT lab; Sano Genetics Limited; Genetics and Genomic Sciences; Institute for Molecular Medicine Finland (FIMM); Institute of Human Genetics; Centre for Clinical Brain Sciences; Department of Hygiene and Epidemiology; Department of Twin Research; Departamento de Medicina Genomica y Toxicologia Ambiental; Herbold Computational Biology Program; Helix; Mohn Center for Diabetes Precision Medicine; University of Bristol; Department of Genetics and Genomics; University of Helsinki; Department of Population Health Sciences; Institute for Biomedical Technologies - National Research Council; Institute for Social and Economic Research; Department of Genetics; Novo Nordisk Foundation Center for Protein Research; Department of Genetic Epidemiology; Charles Bronfman Institute for Personalized Medicine; Department of Pathology and Laboratory Medicine; Genotek Ltd.; William Harvey Research Institute; IRCCS G; Department of Internal Medicine; Department of Anatomy; Faculty of Industrial Sciences and Technology; Department of Statistical Genetics; Division of Pulmonary Medicine; ; ; ; ; Center for Genomic Medicine; Division of Pulmonary Medicine; Department of Statistical Genetics; Charles Bronfman Institute for Personalized Medicine; Institute for Social and Economic Research; Institute of Medical Microbiology & Hygiene; Department of Genetic Epidemiology; Department of Population Health Sciences; Sano Genetics Limited; Centre for Fertility and Health; Novo Nordisk Foundation Center for Protein Research; Statens Serum Institute; Department of Genetics; Genotek Ltd.; Department of Twin Research and Genetic Epidemiology; Medical Genetics; Department of Hygiene and Epidemiology; Genomes for Life-GCAT lab; Digestive Oncology Research Center; Instituto de Investigaciones Biomedicas Unam/ Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran; Department of Pathology and Laboratory Medicine; MRC Integrative Epidemiology Unit at the University of Bristol; MRC Integrative Epidemiology Unit at the University of Bristol; Institute for Molecular Medicine Finland (FIMM); Institute for Molecular Medicine Finland (FIMM); Institute of Psychiatric Phenomics & Genomics; Department of Human Genetics; Institute of Human Genetics; Anaesthesiology and Intensive Care Medicine; Department of Evolutionary Genetics; Institute for Molecular Medicine Finland (FIMM),"Infections can lead to persistent or long-term symptoms and diseases such as shingles after varicella zoster, cancers after human papillomavirus, or rheumatic fever after streptococcal infections1, 2. Similarly, infection by SARS-CoV-2 can result in Long COVID, a condition characterized by symptoms of fatigue and pulmonary and cognitive dysfunction3-5. The biological mechanisms that contribute to the development of Long COVID remain to be clarified. We leveraged the COVID-19 Host Genetics Initiative6, 7 to perform a genome-wide association study for Long COVID including up to 6,450 Long COVID cases and 1,093,995 population controls from 24 studies across 16 countries. We identified the first genome-wide significant association for Long COVID at the FOXP4 locus. FOXP4 has been previously associated with COVID-19 severity6, lung function8, and cancers9, suggesting a broader role for lung function in the pathophysiology of Long COVID. While we identify COVID-19 severity as a causal risk factor for Long COVID, the impact of the genetic risk factor located in the FOXP4 locus could not be solely explained by its association to severe COVID-19. Our findings further support the role of pulmonary dysfunction and COVID-19 severity in the development of Long COVID.",genetic and genomic medicine,exact,100,100 +medRxiv,10.1101/2023.06.30.23292079,2023-06-30,https://medrxiv.org/cgi/content/short/2023.06.30.23292079,Synthesis and new evidence from the PROTECT UK National Core Study: Determining occupational risks of SARS-CoV-2 infection and COVID-19 mortality,Sarah Rhodes; Sarah Beale; Mark Cherrie; William Mueller; Fiona Holland; Melissa Matz; Ioannis Basinas; Jack D Wilkinson; Matthew Gittins; Bernardine Farrell; Andrew Hayward; Neil Pearce; Martie van Tongeren,University of Manchester; University College London; Institute of Occupational Medicine; Institute of Occupational Medicine; University of Manchester; London School of Hygiene and Tropical Medicine; University of Manchester; University of Manchester; University of Manchester; University of Manchester; UCL; London School of Hygiene and Tropical Medicine; University of Manchester,"IntroductionThe PROTECT National Core Study was funded by the UK Health and Safety Executive (HSE) to investigate routes of transmission for SARS-CoV-2 and variation between settings. + +MethodsA workshop was organised in Oct 2022.We brought together evidence from five published epidemiological studies that compared risks of SARS-CoV-2 infection or COVID-19 mortality by occupation or sector funded by PROTECT relating to three non-overlapping data sets, plus additional unpublished analyses relating to the Omicron period. We extracted descriptive study level data and model results. We investigated risk across four pandemic waves using forest plots for key occupational groups by time-period. + +ResultsResults were largely consistent across different studies with different expected biases. Healthcare and social care sectors saw elevated risks of SARS-CoV-2 infection and COVID-19 mortality early in the pandemic, but thereafter this declined and varied by specific occupational subgroup. The education sector saw sustained elevated risks of infection after the initial lockdown period with little evidence of elevated mortality. + +ConclusionsIncreased in risk of infection and mortality were consistently observed for occupations in high risk sectors particularly during the early stage of the pandemic. The education sector showed a different pattern compared to the other high risk sectors, as relative risk of infections remained high in the later phased of the pandemic, although no increased in COVID-19 mortality (compared to low-risk occupations) was observed in this sector in any point during the pandemic.",occupational and environmental health,exact,100,100 medRxiv,10.1101/2023.06.29.23292043,2023-06-30,https://medrxiv.org/cgi/content/short/2023.06.29.23292043,Risk of SARS-CoV-2 reinfection during multiple Omicron variant waves in the UK general population,Jia Wei; Nicole Stoesser; Philippa Matthews; Tarnjit Khera; Owen Gethings; Ian Diamond; Ruth Studley; Nick Taylor; tim E peto; Ann Sarah Walker; Koen Pouwels; David W Eyre,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; oxford university; University of Oxford; University of Oxford; University of Oxford,"SARS-CoV-2 reinfections increased substantially after Omicron variants emerged. Large-scale community-based comparisons across multiple Omicron waves of reinfection characteristics, risk factors, and protection afforded by previous infection and vaccination, are limited, especially after widespread national testing stopped. We studied 245,895 adults [≥]18y in the UKs national COVID-19 Infection Survey with at least one infection (identified from positive swab tests done within the study, linked from national testing programmes, or self-reported by participants, up to their last study assessment). We quantified the risk of reinfection in multiple infection waves, including those driven by BA.1, BA.2, BA.4/5, and most recently BQ.1/CH.1.1/XBB.1.5 variants, in which most reinfections occurred. Reinfections had higher cycle threshold (Ct) values (lower viral load) and lower percentages self-reporting symptoms compared with first infections. Across multiple Omicron waves, protection against reinfection was significantly higher in those previously infected with more recent than earlier variants, even at the same time from previous infection. Protection against Omicron reinfections decreased over time from the most recent infection if this was the previous or penultimate variant (generally within the preceding year), but did not change or even slightly increased over time if this was with an even earlier variant (generally >1 year previously). Those 14-180 days after receiving their most recent vaccination had a lower risk of reinfection with all Omicron variants except BA.2 than those >180 days from their most recent vaccination. Reinfection risk was independently higher in those aged 30-45 years, and with either low or high Ct values in their most recent previous infection. Overall, the risk of Omicron reinfection is high, but with lower severity than first infections; reinfection risk is likely driven as much by viral evolution as waning immunity.",infectious diseases,exact,100,100 medRxiv,10.1101/2023.06.23.23291776,2023-06-29,https://medrxiv.org/cgi/content/short/2023.06.23.23291776,Patient characteristics associated with clinically coded long COVID: an OpenSAFELY study using electronic health records,Yinghui Wei; Elsie M F Horne; Rochelle Knight; Genevieve Cezard; Alex J Walker; Louis Fisher; Rachel Denholm; Kurt Taylor; Venexia Walker; Stephanie Riley; Dylan M Williams; Robert John Willans; Simon Davy; Sebastian Bacon; Ben John Goldacre; Amir-Reza Mehrkar-Asl; Spiros Denaxas; Felix Greaves; Richard Silverwood; Aziz Sheikh; Nish Chaturvedi; Angela Wood; John Macleod; Claire Steves; Jonathan A C Sterne,"University of Plymouth; University of Bristol; University of Bristol; University of Cambridge; University of Oxford; University of Oxford; University of Bristol; University of Bristol; University of Bristol; University of Plymouth; UCL; National Institute of Health and Care Excellence; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University College London; Imperial College London; University College London; The University of Edinburgh; University College London; Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, United Kingdom; University of Bristol; King's College London; University of Bristol","Despite reports of post-COVID-19 syndromes (long COVID) are rising, clinically coded long COVID cases are incomplete in electronic health records. It is unclear how patient characteristics may be associated with clinically coded long COVID. With the approval of NHS England, we undertook a cohort study using electronic health records within the OpenSAFELY-TPP platform in England, to study patient characteristics associated with clinically coded long COVID from 29 January 2020 to 31 March 2022. We estimated age-sex adjusted hazard ratios and fully adjusted hazard ratios for coded long COVID. Patient characteristics included demographic factors, and health behavioural and clinical factors. Among 17,986,419 adults, 36,886 (0.21%) were clinically coded with long COVID. Patient characteristics associated with coded long COVID included female sex, younger age (under 60 years), obesity, living in less deprived areas, ever smoking, greater consultation frequency, and history of diagnosed asthma, mental health conditions, pre-pandemic post-viral fatigue, or psoriasis. The strength of these associations was attenuated following two-dose vaccination compared to before vaccination. The incidence of coded long COVID was higher after hospitalised than non-hospitalised COVID-19. These results should be interpreted with caution given that long COVID was likely under-recorded in electronic health records.",epidemiology,exact,100,100 medRxiv,10.1101/2023.06.23.23291820,2023-06-29,https://medrxiv.org/cgi/content/short/2023.06.23.23291820,Impact of the Covid-19 Pandemic on Audiology Service Delivery: Observational Study of the Role of Social Media in Patient Communication,Adeel Hussain; Zain Hussain; Mandar Gogate; Kia Dashtipour; Adele Goman; Aziz Sheikh; Amir Hussain,Edinburgh Napier University; The University of Edinburgh; Edinburgh Napier University School of Computing: Edinburgh Napier University School of Computing Engineering and the Built Environment; Edinburgh Napier University School of Computing: Edinburgh Napier University School of Computing Engineering and the Built Environment; Edinburgh Napier University School of Life Sciences: Edinburgh Napier University School of Health and Social Care; The University of Edinburgh Edinburgh Medical School; Edinburgh Napier University School of Computing: Edinburgh Napier University School of Computing Engineering and the Built Environment,"The Covid-19 pandemic has highlighted an era in hearing health care that necessitates a comprehensive rethinking of audiology service delivery. There has been a significant increase in the number of individuals with hearing loss who seek information online. An estimated 430 million individuals worldwide suffer from hearing loss, including 11 million in the United Kingdom. The objective of this study was to identify NHS audiology service social media posts and understand how they were used to communicate service changes within audiology departments at the onset of the Covid-19 pandemic.Facebook and Twitter posts relating to audiology were extracted over a six week period (March 23 to April 30 2020) from the United Kingdom. We manually filtered the posts to remove those not directly linked to NHS audiology service communication. The extracted data was then geospatially mapped, and themes of interest were identified via a manual review. We also calculated interactions (likes, shares, comments) per post to determine the posts efficacy. A total of 981 Facebook and 291 Twitter posts were initially mined using our keywords, and following filtration, 174 posts related to NHS audiology change of service were included for analysis. The results were then analysed geographically, along with an assessment of the interactions within the included posts. NHS Trusts and Boards should consider incorporating and promoting social media to communicate service changes. Users would be notified of service modifications in real-time, and different modalities could be used (e.g. videos), resulting in a more efficient service.",health informatics,exact,100,100 @@ -286,6 +279,17 @@ Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched Ovid ME Added value of this studyWe conducted age-standardised time series analyses using comprehensive, linked, anonymised, individual-level routinely-collected, population-scale health data for the population of Wales, UK. By accounting for seasonal variations in prescribing and mortality, we demonstrated that the absolute increase in antipsychotic prescribing in people with dementia of any cause during the COVID-19 pandemic was small. In contrast, antipsychotic prescribing in the youngest age group (60-64 years) and in people with a subtype diagnosis of Alzheimers disease increased throughout the five-year study period. Accounting for seasonal variation, all-cause mortality rates in people with dementia began to increase in late 2019 and increased sharply during the first few months of the pandemic. COVID-19 became the leading non-dementia cause of death in people with dementia from 2020 to 2021. Stroke mortality increased during the pandemic, following a similar pattern to that of all-cause mortality, whereas myocardial infarction rates decreased. Implications of all the available evidenceDuring COVID-19 we observed a large increase in all-cause and stroke mortality in people with dementia. When seasonal variations are accounted for, antipsychotic prescribing rates in all-cause dementia increased by a small amount before and during the pandemic in the UK. The increased prescribing rates in younger age groups and in people with Alzheimers disease warrants further investigation.",neurology,exact,100,100 +medRxiv,10.1101/2023.02.16.23286017,2023-02-18,https://medrxiv.org/cgi/content/short/2023.02.16.23286017,Long-term outdoor air pollution and COVID-19 mortality in London: an individual-level analysis,Loes Charlton; Chris Gale; Jasper Morgan; Myer Glickman; Sean Beevers; Anna L Hansell; Vahé Nafilyan,Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Imperial College London; University of Leicester; Office for National Statistics,"BackgroundThe risk of COVID-19 severity and mortality differs markedly by age, socio-demographic characteristics and pre-existing health status. Various studies have suggested that higher air pollution exposures also increase the likelihood of dying from COVID-19. + +Objectives: To assess the association between long-term outdoor air pollution (NO2, NOx, PM10 and PM2.5) concentrations and the risk of death involving COVID-19, using a large individual-level dataset. + +MethodsWe used comprehensive individual-level data from the Office for National Statistics Public Health Data Asset for September 2020 to January 2022 and London Air Quality Network modelled air pollution concentrations available for 2016. Using Cox proportional hazard regression models, we adjusted for potential confounders including age, sex, vaccination status, dominant virus variants, geographical factors (such as population density), ethnicity, area and household-level deprivation, and health comorbidities. + +ResultsThere were 737,356 confirmed COVID-19 cases including 9,315 COVID-related deaths. When only adjusting for age, sex, and vaccination status, there was an increased risk of dying from COVID-19 with increased exposure to all air pollutants studied (NO2: HR 1.07 [95% confidence interval: 1.04-1.12] per 10 g/m3; NOx: 1.05[1.02-1.09] per 20 g/m3; PM10: 1.32[1.15-1.51] per 10 g/m3; PM2.5: 1.29[1.12-1.49] per 5 g/m3). However, after adjustment including ethnicity and socio-economic factors the HRs were close to unity (NO2: 0.98[0.90-1.06]; NOx: 0.99[0.94-1.04]; PM10: 0.95[0.74-1.22]; PM2.5: 0.90[0.67-1.20]). Additional adjustment for dominant variant or pre-existing health comorbidities did not alter the results. + +ConclusionsObserved associations between long-term outdoor air pollution exposure and COVID-19 mortality in London are strongly confounded by geography, ethnicity and deprivation. + +SummaryUsing a large individual-level dataset, we found that a positive association between long-term outdoor air pollution and COVID-19 mortality in London did not persist after adjusting for confounders including population density, ethnicity and deprivation.",respiratory medicine,exact,100,100 medRxiv,10.1101/2023.02.09.23285649,2023-02-14,https://medrxiv.org/cgi/content/short/2023.02.09.23285649,"Antibody prevalence after 3 or more COVID-19 vaccine doses in 23,000 immunosuppressed individuals: a cross-sectional study from MELODY",Fiona A Pearce; Sean Hua Lim; Mary Bythell; Peter Lanyon; Rachel Hog; Adam Taylor; Gillian Powter; Graham Cooke; Helen Ward; Joseph Chilcot; Helen Thomas; Lisa Mumford; Stephen P McAdoo; Gavin J Pettigrew; Liz Lightstone; Michelle Willicombe,"Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, UK; Centre for Cancer Immunology, University of Southampton, Southampton, UK; National Disease Registration Service, NHS Digital; Department of Rheumatology, Nottingham University Hospitals NHS Trust, Nottingham, UK; Statistics and Clinical Research, NHS Blood and Transplant, Bristol, UK; Lifespan and Population Health, School of Medicine, University of Nottingham, Nottingham, UK; NHS Blood and Transplant Clinical Trials Unit, Oxford, UK; Imperial College; Imperial College London; Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; Statistics and Clinical Research, NHS Blood and Transplant, Bristol, UK; Statistics and Clinical Research, NHS Blood and Transplant, Bristol, UK; Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, Hammersmith Campus, Du Cane Road, London, UK.; Department of Surgery, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK; Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, Hammersmith Campus, Du Cane Road, London, UK.; Centre for Inflammatory Disease, Department of Immunology and Inflammation, Imperial College London, Hammersmith Campus, Du Cane Road, London, UK.","ObjectivesTo investigate the prevalence of spike-protein antibodies following at least 3 COVID-19 vaccine doses in immunocompromised individuals. DesignCross-sectional study using UK national disease registries of individuals with solid organ transplants (SOT), rare autoimmune rheumatic diseases (RAIRD) and lymphoid malignancies (LM). @@ -549,9 +553,6 @@ MethodsParticipants (n=1,154) who had received the first dose of a COVID-19 vacc Results457/1,154 (39.60%) participants reported non-household contacts post-vaccination compared with 371/1,154 (32.15%) participants pre-vaccination. 100/1,154 (8.67%) participants reported use of non-essential shops or services post-vaccination compared with 74/1,154 (6.41%) participants pre-vaccination. Post-vaccination status was associated with increased odds of reporting non-household contacts (OR 1.65, 95% CI 1.31-2.06, p<0.001) and use of non-essential shops or services (OR 1.50, 95% CI 1.03-2.17, p=0.032). This effect varied between men and women and different age groups. ConclusionParticipants had higher odds of reporting non-household contacts and use of non-essential shops or services within 14 days of their first COVID-19 vaccine compared to pre-vaccination. Public health emphasis on maintaining protective behaviours during this post-vaccination time period when individuals have yet to develop full protection from vaccination could reduce risk of SARS-CoV-2 infection.",public and global health,exact,100,100 -medRxiv,10.1101/2022.08.17.22278893,2022-08-18,https://medrxiv.org/cgi/content/short/2022.08.17.22278893,Uptake of Sotrovimab for prevention of severe COVID-19 and its safety in the community in England,Martina Patone; Holly Tibble; Andrew JHL Snelling; Carol Coupland; Aziz Sheikh; Julia Hippisley-Cox,University of Oxford; University of Edinburgh; University of Oxford; University of Oxford; University of Edinburgh; University of Oxford,"Sotrovimab is a neutralising monoclonal antibody (nMAB), currently administrated in England to treat extremely clinically vulnerable COVID-19 patients. Trials have shown it to have mild or moderate side effects, however safety in real-world settings has not been yet evaluated. We used national databases to investigate its uptake and safety in community patients across England. We used a cohort study to describe uptake and a self-controlled case series design to evaluate the risks of 49 pre-specified suspected adverse events in the 2-28 days post-treatment. Between December 11, 2021 and May 24, 2022, there were 172,860 COVID-19 patients eligible for treatment. Of the 22,815 people who received Sotrovimab, 21,487 (94.2%) had a positive SARS-CoV-2 test and 5,999 (26.3%) were not on the eligible list. Between treated and untreated eligible individuals, the mean age (54.6, SD: 16.1 vs 54.1, SD: 18.3) and sex distribution (women: 60.9% vs 58.1%; men: 38.9% vs 41.1%) were similar. There were marked variations in uptake between ethnic groups, which was higher amongst Indian (15.0%; 95%CI 13.8, 16.3), Other Asian (13.7%; 95%CI 11.9, 15.8), White (13.4%; 95%CI 13.3, 13.6), and Bangladeshi (11.4%; 95%CI 8.8, 14.6); and lower amongst Black Caribbean individuals (6.4%; 95%CI 5.4, 7.5) and Black Africans (4.7%; 95%CI 4.1, 5.4). We found no increased risk of any of the suspected adverse events in the overall period of 2-28 days post-treatment, but an increased risk of rheumatoid arthritis (IRR 3.08, 95% CI 1.44, 6.58) and of systematic lupus erythematosus (IRR 5.15, 95% CI 1.60, 16.60) in the 2-3 days post-treatment, when we narrowed the risk period. - -FundingNational Institute of Health Research (Grant reference 135561)",epidemiology,exact,100,100 medRxiv,10.1101/2022.08.13.22278733,2022-08-16,https://medrxiv.org/cgi/content/short/2022.08.13.22278733,QCovid 4 - Predicting risk of death or hospitalisation from COVID-19 in adults testing positive for SARS-CoV-2 infection during the Omicron wave in England,Julia Hippisley-Cox; Kamlesh Khunti; Aziz Sheikh; Jonathan Nguyen-Van-Tam; Carol Coupland,University of Oxford; University of Leicester; University of Edinburgh; University of Nottingham; University of Oxford,"ObjectivesTo (a) derive and validate risk prediction algorithms (QCovid4) to estimate risk of COVID-19 mortality and hospitalisation in UK adults with a SARS-CoV-2 positive test during the Omicron pandemic wave in England and (b) evaluate performance with earlier versions of algorithms developed in previous pandemic waves and the high-risk cohort identified by NHS Digital in England. DesignPopulation-based cohort study using the QResearch database linked to national data on COVID-19 vaccination, high risk patients prioritised for COVID-19 therapeutics, SARS-CoV-2 results, hospitalisation, cancer registry, systemic anticancer treatment, radiotherapy and the national death registry. @@ -592,13 +593,6 @@ Results14175 residents and 19973 staff were included. In residents without prior ConclusionsBooster vaccination provides sustained protection against severe outcomes following infection with the Omicron variant, but no protection against infection from 3 months onwards. Ongoing surveillance for SARS-CoV-2 in LTCFs is crucial. SummaryThe COVID-19 pandemic has severely impacted residents in long-term care facilities (LTCFs). Booster vaccination provides sustained moderate protection against severe outcomes, but no protection against infection was apparent from around 3 months onwards. Ongoing surveillance in LTCFs is crucial.",infectious diseases,exact,100,100 -medRxiv,10.1101/2022.08.07.22278510,2022-08-09,https://medrxiv.org/cgi/content/short/2022.08.07.22278510,Metabolomic and gut microbiome profiles across the spectrum of community-based COVID and non-COVID disease: A COVID-19 Biobank study.,Marc F Österdahl; Ronan Whiston; Carole H Sudre; Francesco Asnicar; Nathan J Cheetham; Aitor Blanco Miguez; Vicky Bowyer; Michela Antonelli; Olivia Snell; Liane dos Santos Canas; Christina Hu; Jonathan Wolf; Cristina Menni; Michael Malim; Deborah Hart; Tim Spector; Sarah Berry; Nicola Segata; Katie Doores; Sebastien Ourselin; Emma L Duncan; Claire J Steves,King's College London; King's College London; King's College London; University of Trento; King's College London; University of Trento; King's College London; King's College London; King's College London; King's College London; ZOE Global Ltd.; ZOE Global Ltd.; King's College London; King's College London; King's College London; King's College London; King's College London; University of Trento; King's College London; King's College London; King's College London; King's College London,"Whilst many with SARS-CoV-2 infection have mild disease, managed in the community, individuals with cardiovascular risk factors experienced often more severe acute disease, requiring hospitalisation. Increasing concern has also developed over long symptom duration in many individuals, including the majority who managed acutely in the community. Risk factors for long symptom duration, including biological variables, are still poorly defined. - -We examine post-illness metabolomic and gut-microbiome profiles, in community-dwelling participants with SARS-CoV-2, ranging from asymptomatic illness to Post-COVID Syndrome, and participants with prolonged non-COVID-19 illnesses. We also assess a pre-established metabolomic biomarker score for its association with illness duration. - -We found an atherogenic-dyslipidaemic metabolic profile, and greater biomarker scores, associated with longer illness, both in individuals with and without SARS-CoV-2 infection. We found no association between illness duration and gut microbiome in convalescence. - -Findings highlight the potential role of cardiometabolic dysfunction to the experience of long illness duration, including after COVID-19.",epidemiology,exact,100,100 medRxiv,10.1101/2022.07.28.22278152,2022-07-31,https://medrxiv.org/cgi/content/short/2022.07.28.22278152,"Confirmed SARS-CoV-2 infection in Scottish neonates 2020-2022: a national, population-based cohort study",Anna Goulding; Fiona McQuaid; Laura Lindsay; Utkarsh Agrawal; Bonnie Auyeung; Clara Calvert; Jade Carruthers; Cheryl Denny; Jack Donaghy; Sam Hillman; Lisa Hopcroft; Leanne Hopkins; Colin McCowan; Terry Mclaughlin; Emily Moore; Lewis Ritchie; Colin R Simpson; Bob Taylor; Lynda Fenton; Louisa Pollock; Christopher Gale; Jenny J Kurinczuk; Chris Robertson; Aziz Sheikh; Sarah Stock; Rachael Wood,Public Health Scotland; University of Edinburgh; Public Health Scotland; University of St Andrews; University of Edinburgh; University of Edinburgh; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Oxford; University of Edinburgh; University of St Andrews; Public Health Scotland; Public Health Scotland; University of Aberdeen; Victoria University of Wellington; Public Health Scotland; Public Health Scotland; University of Glasgow; Imperial College London; University of Oxford; University of Strathclyde; University of Edinburgh; University of Edinburgh; Public Health Scotland,"ObjectiveTo examine infants in Scotland aged 0-27 days with confirmed SARS-CoV-2 infection; the risk of neonatal infection by factors including maternal infection status and gestation at birth; and the need for hospital admission among infected neonates. DesignPopulation-based cohort study. @@ -634,6 +628,13 @@ ResultsThe study was launched on 1st May 2020 and closed to recruitment on 6th O ConclusionsThe COVIDENCE UK dataset represents a valuable resource containing granular information on factors influencing susceptibility to, and impacts of, COVID-19 in UK adults. Researchers wishing to access anonymised participant-level data should contacting the corresponding author for further information.",epidemiology,exact,100,100 medRxiv,10.1101/2022.06.20.22275994,2022-06-20,https://medrxiv.org/cgi/content/short/2022.06.20.22275994,Characterising patterns of COVID-19 and long COVID symptoms: Evidence from nine UK longitudinal studies,Ruth C E Bowyer; Charlotte Huggins; Renin Toms; Richard John Shaw; Bo Hou; Ellen J Thompson; Alex Siu Fung Kwong; Dylan M Williams; Milla Kibble; George B Ploubidis; Nicholas J Timpson; Jonathan A C Sterne; Nishi Chaturvedi; Claire J Steves; Kate Tilling; Richard J Silverwood,King's College London; University of Edinburgh; University of Bristol; University of Glasgow; Bradford Institute for Health Research; King's College London; University of Bristol; UCL; King's College London; University College London; University of Bristol; University of Bristol; University College London; King's College London; University of Bristol; University College London,"Multiple studies across global populations have established the primary symptoms characterising COVID-19 (Coronavirus Disease 2019) and long COVID. However, as symptoms may also occur in the absence of COVID-19, a lack of appropriate controls has often meant that specificity of symptoms to acute COVID-19 or long COVID could not be examined. We aimed to characterise patterns of COVID-19 and long COVID symptoms across nine UK longitudinal studies, totalling over 42,000 participants. Conducting latent class analyses separately in three groups ( no COVID-19, COVID-19 in last 12 weeks, COVID-19 > 12 weeks ago), the data did not support the presence of more than two distinct symptom patterns, representing high and low symptom burden, in each group. Comparing the high symptom burden classes between the COVID-19 in last 12 weeks and no COVID-19 groups we identified symptoms characteristic of acute COVID-19, including loss of taste and smell, fatigue, cough, shortness of breath and muscle pains or aches. Comparing the high symptom burden classes between the COVID-19 > 12 weeks ago and no COVID-19 groups we identified symptoms characteristic of long COVID, including fatigue, shortness of breath, muscle pain or aches, difficulty concentrating and chest tightness. The identified symptom patterns among individuals with COVID-19 > 12 weeks ago were strongly associated with self-reported length of time unable to function as normal due to COVID-19 symptoms, suggesting that the symptom pattern identified corresponds to long COVID. Building the evidence base regarding typical long COVID symptoms will improve diagnosis of this condition and the ability to elicit underlying biological mechanisms, leading to better patient access to treatment and services.",epidemiology,exact,100,100 +medRxiv,10.1101/2022.06.18.22276437,2022-06-19,https://medrxiv.org/cgi/content/short/2022.06.18.22276437,A patient-centric characterization of systemic recovery from SARS-CoV-2 infection,Hélène Ruffieux; Aimee Hanson; Samantha Lodge; Nathan Lawler; Luke Whiley; Nicola Gray; Tui Nolan; Laura Bergamaschi; Federica Mescia; - CITIID-NIHR COVID BioResource Collaboration; Nathalie Kingston; John Bradley; Elaine Holmes; Julien Wist; Jeremy Nicholson; Paul Lyons; Kenneth Smith; Sylvia Richardson; Glenn Bantug; Christoph Hess,University of Cambridge; University of Cambridge; Murdoch University; Murdoch University; Murdoch University; Murdoch University; University of Cambridge; University of Cambridge; University of Cambridge; ; University of Cambridge; University of Cambridge; Murdoch University; Murdoch University; Murdoch University; University of Cambridge; University of Cambridge; University of Cambridge; University and University Hospital Basel; University of Cambridge,"The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data, covering a year post disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct ""systemic recovery"" profiles with specific progression and resolution of the inflammatory, immune, metabolic and clinical responses, over weeks to several months after infection. In particular, we found a strong intra-patient temporal covariation of innate immune cell numbers, kynurenine- and host lipid-metabolites, which suggested candidate immunometabolic pathways putatively influencing restoration of homeostasis, the risk of death and of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery on the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-systemic-recovery-prediction-app, designed to test our findings prospectively. + +Graphical abstract + +O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=""FIGDIR/small/22276437v1_ufig1.gif"" ALT=""Figure 1""> +View larger version (38K): +org.highwire.dtl.DTLVardef@12b0afborg.highwire.dtl.DTLVardef@ddf3b2org.highwire.dtl.DTLVardef@1aa670forg.highwire.dtl.DTLVardef@5415ec_HPS_FORMAT_FIGEXP M_FIG C_FIG",infectious diseases,exact,100,100 medRxiv,10.1101/2022.06.17.22276433,2022-06-17,https://medrxiv.org/cgi/content/short/2022.06.17.22276433,It hurts your heart: frontline healthcare worker experiences of moral injury during the COVID-19 pandemic,Siobhan Hegarty; Danielle Lamb; Sharon Stevelink; Rupa Bhundia; Rosalind Raine; Mary Jane Docherty; Hannah Rachel Scott; Anne Marie Rafferty; Victoria Williamson; Sarah Dorrington; Matthew hotopf; Reza Razavi; Neil Greenberg; Simon Wessely,King's College London; UCL; King's College London; King's College London; University College London; South London and Maudsley NHS Foundation Trust; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London; King's College London,"BackgroundMoral injury is defined as the strong emotional and cognitive reactions following events which clash with someones moral code, values or expectations. During the COVID-19 pandemic, increased exposure to potentially morally injurious events (PMIEs) has placed healthcare workers (HCWs) at risk of moral injury. Yet little is known about the lived experience of cumulative PMIE exposure and how NHS staff respond to this. ObjectiveWe sought to rectify this knowledge gap by qualitatively exploring the lived experiences and perspectives of clinical frontline NHS staff who responded to COVID-19. @@ -761,13 +762,6 @@ Methods and analysisThis mixed-method, multi-site study is informed by the princ Ethics and disseminationLOCOMOTION is sponsored by the University of Leeds and approved by Yorkshire & The Humber - Bradford Leeds Research Ethics Committee (ref: 21/YH/0276). Dissemination plans include academic and lay publications, and partnerships with national and regional policymakers to influence service specifications and targeted funding streams. Study registrationClinicalTrials.gov: NCT05057260; ISRCTN15022307.",health systems and quality improvement,exact,100,100 -medRxiv,10.1101/2022.04.03.22272610,2022-04-04,https://medrxiv.org/cgi/content/short/2022.04.03.22272610,Cardiac impairment in Long Covid 1-year post-SARS-CoV-2 infection,Adriana Roca-Fernandez; Malgorzata Wamil; Alison Telford; Valentina Carapella; Alessandra Borlotti; David Monteiro; Helena Thomaides-Brears; Matthew D Kelly; Andrea Dennis; Rajarshi Banerjee; Matthew Robson; Michael Brady; Gregory Lip; Sacha Bull; Melissa J Heightman; Ntobeko Ntusi; Amitava Banerjee,"Perspectum Diagnostics; Great Western Hospital Foundation NHS Trust, Swindon, UK; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; University of Liverpool; Royal Berkshire Hospital, Reading; UCLH; University of Cape Town, Cape Town, South Africa; University College London","BackgroundLong Covid is associated with multiple symptoms and impairment in multiple organs. Cardiac impairment has been reported to varying degrees by varying methodologies in cross-sectional studies. Using cardiac magnetic resonance (CMR), we investigated the 12-month trajectory of cardiac impairment in individuals with Long Covid. - -Methods534 individuals with Long Covid underwent baseline CMR (T1 and T2 mapping, cardiac mass, volumes, function, and strain) and multi-organ MRI at 6 months (IQR 4.3,7.3) since first post-COVID-19 symptoms and 330 were rescanned at 12.6 (IQR 11.4, 14.2) months if abnormal findings were reported at baseline. Symptoms, standardised questionnaires, and blood samples were collected at both timepoints. Cardiac impairment was defined as one or more of: low left or right ventricular ejection fraction (LVEF and RVEF), high left or right ventricular end diastolic volume (LVEDV and RVEDV), low 3D left ventricular global longitudinal strain (GLS), or elevated native T1 in [≥]3 cardiac segments. A significant change over time was reported by comparison with 92 healthy controls. - -ResultsThe technical success of this multiorgan assessment in non-acute settings was 99.1% at baseline, and 98.3% at follow up, with 99.6% and 98.8% for CMR respectively. Of individuals with Long Covid, 102/534 [19%] had cardiac impairment at baseline; 71/102 had complete paired data at 12 months. Of those, 58% presented with ongoing cardiac impairment at 12 months. High sensitivity cardiac troponin I and B-type natriuretic peptide were not predictive of CMR findings, symptoms, or clinical outcomes. At baseline, low LVEF, high RVEDV and low GLS were associated with cardiac impairment. Low LVEF at baseline was associated with persistent cardiac impairment at 12 months. - -ConclusionCardiac impairment, other than myocarditis, is present in 1 in 5 individuals with Long Covid at 6 months, persisting in over half of those at 12 months. Cardiac-related blood biomarkers are unable to identify cardiac impairment in Long COVID. Subtypes of disease (based on symptoms, examination, and investigations) and predictive biomarkers are yet to be established. Interventional trials with pre-specified subgroup analyses are required to inform therapeutic options.",cardiovascular medicine,exact,100,100 medRxiv,10.1101/2022.03.29.22273042,2022-04-04,https://medrxiv.org/cgi/content/short/2022.03.29.22273042,The new normal? Dynamics and scale of the SARS-CoV-2 variant Omicron epidemic in England,Oliver Eales; Leonardo de Oliveira Martins; Andrew Page; Haowei Wang; Barbara Bodinier; David Tang; David Haw; Jakob Jonnerby; Christina Atchison; Deborah Ashby; Wendy Barclay; Graham Taylor; Graham Cooke; Helen Ward; Ara Darzi; Steven Riley; Paul Elliott; Christl A Donnelly; Marc Chadeau-Hyam,"Imperial College London; Quadram Institute, Norwich, UK; Quadram Institute, Norwich, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Environment and Health, School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Environment and Health, School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedic; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Research Centre, UK Institute of Global Health Innovation a; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK Imperial College Healthcare NHS Trust, UK National Institute for Health Research Imperial Biomedical Resear; School of Public Health, Imperial College London, UK MRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergenc; School of Public Health, Imperial College London, UK MRC Centre for Environment and Health, School of Public Health, Imperial College London, UK","The SARS-CoV-2 pandemic has been characterised by the regular emergence of genomic variants which have led to substantial changes in the epidemiology of the virus. With natural and vaccine-induced population immunity at high levels, evolutionary pressure favours variants better able to evade SARS-CoV-2 neutralising antibodies. The Omicron variant was first detected in late November 2021 and exhibited a high degree of immune evasion, leading to increased infection rates in many countries. However, estimates of the magnitude of the Omicron wave have relied mainly on routine testing data, which are prone to several biases. Here we infer the dynamics of the Omicron wave in England using PCR testing and genomic sequencing obtained by the REal-time Assessment of Community Transmission-1 (REACT-1) study, a series of cross-sectional surveys testing random samples of the population of England. We estimate an initial peak in national Omicron prevalence of 6.89% (5.34%, 10.61%) during January 2022, followed by a resurgence in SARS-CoV-2 infections in England during February-March 2022 as the more transmissible Omicron sub-lineage, BA.2 replaced BA.1 and BA.1.1. Assuming the emergence of further distinct genomic variants, intermittent epidemics of similar magnitude as the Omicron wave may become the new normal.",infectious diseases,exact,100,100 medRxiv,10.1101/2022.03.22.22271707,2022-03-23,https://medrxiv.org/cgi/content/short/2022.03.22.22271707,Vitamin D Supplements for Prevention of Covid-19 or other Acute Respiratory Infections: a Phase 3 Randomized Controlled Trial (CORONAVIT),David Jolliffe; Hayley Holt; Matthew Greenig; Mohammad Talaei; Natalia Perdek; Paul Pfeffer; Giulia Vivaldi; Sheena Maltby; Jane Symons; Nicola Barlow; Alexa Normandale; Rajvinder Garcha; Alex Richter; Sian Faustini; Christopher Orton; David Ford; Ronan Lyons; Gwyneth Davies; Frank Kee; Christopher Griffiths; John Norrie; Aziz Sheikh; Seif Shaheen; Clare Relton; Adrian Martineau,Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Queen Mary University of London; Jane Symons Media; City Hospital Birmingham; City Hospital Birmingham; City Hospital Birmingham; University of Birmingham; University of Birmingham; Swansea University; Swansea University; Swansea University; Swansea University; Queen's University Belfast; Queen Mary University of London; University of Edinburgh; University of Edinburgh; Queen Mary University of London; Queen Mary University of London; Queen Mary University of London,"OBJECTIVESTo determine whether population-level implementation of a test-and- treat approach to correction of sub-optimal vitamin D status (25-hydroxyvitamin D [25(OH)D] <75 nmol/L) influences risk of all-cause acute respiratory infection (ARI) or coronavirus disease 2019 (COVID-19). @@ -906,6 +900,21 @@ MethodsWe conducted a prospective non-randomised trial of sequencing at 14 acute ResultsA total of 2170 HOCI cases were recorded from October 2020-April 2021, with sequence reports returned for 650/1320 (49.2%) during intervention phases. We did not detect a statistically significant change in weekly incidence of HAIs in longer-turnaround (IRR 1.60, 95%CI 0.85-3.01; P=0.14) or rapid (0.85, 0.48-1.50; P=0.54) intervention phases compared to baseline phase. However, IPC practice was changed in 7.8% and 7.4% of all HOCI cases in rapid and longer-turnaround phases, respectively, and 17.2% and 11.6% of cases where the report was returned. In a per-protocol sensitivity analysis there was an impact on IPC actions in 20.7% of HOCI cases when the SRT report was returned within 5 days. ConclusionWhile we did not demonstrate a direct impact of sequencing on the incidence of nosocomial transmission, our results suggest that sequencing can inform IPC response to HOCIs, particularly when returned within 5 days.",infectious diseases,exact,100,100 +medRxiv,10.1101/2022.02.04.22270479,2022-02-06,https://medrxiv.org/cgi/content/short/2022.02.04.22270479,Comparative effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections: A time-varying cohort analysis using trial emulation in the Virus Watch community cohort,Vincent Nguyen; Alexei Yavlinsky; Sarah Beale; Susan J Hoskins; Vasileios J Lampos; Isobel Braithwaite; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan Mathew Dwight Navaratnam; Parth Patel; Madhumita Shrotri; Sophie Weber; Andrew Hayward; Robert W Aldridge,"University College London; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London, London School of Hygiene &Tropical Medicine; UCL, London School of Hygiene & Tropical Medicine; University College London; University College London; University College London; University College London; Univeristy College London; University College London; University College London; University College London","ImportanceThe Omicron (B.1.1.529) variant has increased SARs-CoV-2 infections in double vaccinated individuals globally, particularly in ChAdOx1 recipients. To tackle rising infections, the UK accelerated booster vaccination programmes used mRNA vaccines irrespective of an individuals primary course vaccine type with booster doses rolled out according to clinical priority. There is limited understanding of the effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections and how time-varying confounders can impact the evaluations comparing different vaccines as primary courses for mRNA boosters. + +ObjectiveTo evaluate the comparative effectiveness of ChAdOx1 versus BNT162b2 as primary doses against SARs-CoV-2 in booster vaccine recipients whilst accounting for time-varying confounders. + +DesignTrial emulation was used to reduce time-varying confounding-by-indication driven by prioritising booster vaccines based upon age, vulnerability and exposure status e.g. healthcare worker. Trial emulation was conducted by meta-analysing eight cohort results whose booster vaccinations were staggered between 16/09/2021 to 05/01/2022 and followed until 23/01/2022. Time from booster vaccination until SARS-CoV-2 infection, loss of follow-up or end-of-study was modelled using Cox proportional hazards models for each cohort and adjusted for age, sex, minority ethnic status, clinically vulnerability, and deprivation. + +SettingProspective observational study using the Virus Watch community cohort in England and Wales. + +ParticipantsPeople over the age of 18 years who had their booster vaccination between 16/09/2021 to 05/01/2022 without prior natural immunity. + +ExposuresChAdOx1 versus BNT162b2 as a primary dose, and an mRNA booster vaccine. + +ResultsAcross eight cohorts, 19,692 mRNA vaccine boosted participants were analysed with 12,036 ChAdOx1 and 7,656 BNT162b2 primary courses with a median follow-up time of 73 days (IQR:54-90). Median age, clinical vulnerability status and infection rates fluctuate through time. 7.2% (n=864) of boosted adults with ChAdOx1 primary course experienced a SARS-CoV-2 infection compared to 7.6% (n=582) of those with BNT162b2 primary course during follow-up. The pooled adjusted hazard ratio was 0.99 [95%CI:0.88-1.11], demonstrating no difference between the incidence of SARs-CoV-2 infections based upon the primary vaccine course. + +Conclusion and RelevanceIn mRNA boosted individuals, we found no difference in protection comparing those with a primary course of BNT162b2 to those with aChAdOx1 primary course. This contrasts with pre-booster findings where previous research shows greater effectiveness of BNT162b2 than ChAdOx1 in preventing infection.",epidemiology,exact,100,100 medRxiv,10.1101/2022.01.31.22269194,2022-02-01,https://medrxiv.org/cgi/content/short/2022.01.31.22269194,"An outbreak of SARS-CoV-2 in a public-facing office in England, 2021",Barry Atkinson; Karin van Veldhoven; Ian Nicholls; Matthew Coldwell; Adam Clarke; Gillian Frost; Christina J Atchison; Amber I Raja; Allan M Bennett; Derek Morgan; Neil Pearce; Tony Fletcher; Elizabeth B Brickley; Yiqun Chen,UK Health Security Agency; London School of Hygiene & Tropical Medicine; UK Health Security Agency; Health and Safety Executive; Health and Safety Executive; Health and Safety Executive; UK Health Security Agency; London School of Hygiene & Tropical Medicine; UK Health Security Agency; Health and Safety Executive; London School of Hygiene & Tropical Medicine; UK Health Security Agency; London School of Hygiene & Tropical Medicine; Health and Safety Executive,"Between August-September 2021, an outbreak of SARS-CoV-2, with an attack rate of 55% (22/40 workers), occurred in a public-facing office in England. To identify workplace and worker-related risk factors, a comprehensive investigation involving surface sampling, environmental assessment, molecular and serological testing, and worker questionnaires was performed in September - October 2021. The results affirm the utility of surface sampling to identify SARS-CoV-2 control deficiencies and the importance of evolving, site-specific risk assessments with layered COVID-19 mitigation strategies.",epidemiology,exact,100,100 medRxiv,10.1101/2022.01.26.22269901,2022-01-28,https://medrxiv.org/cgi/content/short/2022.01.26.22269901,The impact of the COVID-19 pandemic on health service utilisation following self-harm: a systematic review,Sarah Steeg; Ann John; David Gunnell; Nav Kapur; Dana Dekel; Lena Schmidt; Duleeka Kniipe; Ella Arensman; Keith Hawton; Julian PT Higgins; Emily Eyles; Catherine Macleod-Hall; Luke A McGuinness; Roger T Webb,University of Manchester; Swansea University; University of Bristol; University of Manchester; University of Swansea; University of Bristol; University of Bristol; University College Cork; University of Oxford; University of Bristol; University of Bristol; University of Bristol; University of Bristol; University of Manchester,"BackgroundEvidence on the impacts of the pandemic on healthcare presentations for self-harm has accumulated rapidly. However, existing reviews do not include studies published beyond 2020. @@ -990,9 +999,6 @@ RESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed, Added value of this studyWe used national databases of COVID-19 case surveillance, laboratory testing, and vaccination from Brazil to investigate effectiveness of CoronaVac, ChAdOx1, Ad26.COV2.S and BNT162b2 among individuals with a prior, laboratory-confirmed SARS-CoV-2 infection. We matched >22,000 RT-PCR-confirmed re-infections with >145,000 RT-PCR-negative controls using a test-negative design. All four vaccines were effective against symptomatic SARS-CoV-2 infections, with effectiveness from 14 days after series completion ranging from 39-65%. For vaccines with two-dose regimens, the second dose provided significantly increased effectiveness compared with one dose. Effectiveness against COVID-19-associated hospitalization or death from 14 days after series completion was >80% for CoronaVac, ChAdOx1and BNT162b2. Implications of all the available evidenceWe find evidence that four vaccines, using three different platforms, all provide protection to previously infected individuals against symptomatic SARS-CoV-2 infection and severe outcomes, with a second dose conferring significant additional benefits. These results support the provision of a full vaccine series among individuals with prior SARS-CoV-2 infection.",infectious diseases,exact,100,100 -medRxiv,10.1101/2021.12.23.21268276,2021-12-25,https://medrxiv.org/cgi/content/short/2021.12.23.21268276,Risk of myocarditis following sequential COVID-19 vaccinations by age and sex,Martina Patone; Winnie Xue Mei; Lahiru Handunnetthi; Sharon Dixon; Francesco Zaccardi; Manu Shankar-Hari; Peter Watkinson; Kamlesh Khunti; Anthony Harnden; Carol AC Coupland; Keith M. Channon; Nicholas L Mills; Aziz Sheikh; Julia Hippisley-Cox,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Leicester; University of Edinburgh; University of Oxford; University of Leicester; University of Oxford; University of Oxford; University of Oxford; University of Edinburgh; University of Edinburgh; University of Oxford,"In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy. - -FundingHealth Data Research UK.",epidemiology,exact,100,100 medRxiv,10.1101/2021.12.22.21268252,2021-12-24,https://medrxiv.org/cgi/content/short/2021.12.22.21268252,Rapid increase in Omicron infections in England during December 2021: REACT-1 study,Paul Elliott; Barbara Bodinier; Oliver Eales; Haowei Wang; David Haw; Joshua Elliott; Matthew Whitaker; Jakob Jonnerby; David Tang; Caroline E. Walters; Christina Atchinson; Peter J. Diggle; Andrew J. Page; Alex Trotter; Deborah Ashby; Wendy Barclay; Graham Taylor; Helen Ward; Ara Darzi; Graham Cooke; Marc Chadeau-Hyam; Christl A Donnelly,"School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; Imperial College London; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency; School of Public Health, Imperial College London, UK; CHICAS, Lancaster Medical School, Lancaster University, UK and Health Data Research, UK; Quadram Institute, Norwich, UK; Quadram Institute Bioscience; School of Public Health, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; Department of Infectious Disease, Imperial College London, UK; School of Public Health, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research; Imperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical Research Centre, UKInstitute of Global Health Innovation at ; Department of Infectious Disease, Imperial College London, UKImperial College Healthcare NHS Trust, UKNational Institute for Health Research Imperial Biomedical; School of Public Health, Imperial College London, UK; School of Public Health, Imperial College London, UKMRC Centre for Global infectious Disease Analysis and Abdul Latif Jameel Institute for Disease and Emergency","BackgroundThe highest-ever recorded numbers of daily severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections in England has been observed during December 2021 and have coincided with a rapid rise in the highly transmissible Omicron variant despite high levels of vaccination in the population. Although additional COVID-19 measures have been introduced in England and internationally to contain the epidemic, there remains uncertainty about the spread and severity of Omicron infections among the general population. MethodsThe REal-time Assessment of Community Transmission-1 (REACT-1) study has been monitoring the prevalence of SARS-CoV-2 infection in England since May 2020. REACT-1 obtains self-administered throat and nose swabs from a random sample of the population of England at ages 5 years and over. Swabs are tested for SARS-CoV-2 infection by reverse transcription polymerase chain reaction (RT-PCR) and samples testing positive are sent for viral genome sequencing. To date 16 rounds have been completed, each including [~]100,000 or more participants with data collected over a period of 2 to 3 weeks per month. Socio-demographic, lifestyle and clinical information (including previous history of COVID-19 and symptoms prior to swabbing) is collected by online or telephone questionnaire. Here we report results from round 14 (9-27 September 2021), round 15 (19 October - 05 November 2021) and round 16 (23 November - 14 December 2021) for a total of 297,728 participants with a valid RT-PCR test result, of whom 259,225 (87.1%) consented for linkage to their NHS records including detailed information on vaccination (vaccination status, date). We used these data to estimate community prevalence and trends by age and region, to evaluate vaccine effectiveness against infection in children ages 12 to 17 years, and effect of a third (booster) dose in adults, and to monitor the emergence of the Omicron variant in England. @@ -1077,13 +1083,6 @@ Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe systematically s Added value of this studyIn a diverse population of adults post-hospital admission with COVID-19, our large UK prospective multi-centre study reports several novel findings: the minority felt fully recovered at one year with minimal recovery from five months across any health domain; female sex and obesity are associated with being less likely to feel fully recovered at one year; several inflammatory mediators were increased in individuals with the most severe physical, mental health, and cognitive impairments compared to individuals with milder ongoing impairments. Implications of all the available evidenceBoth pharmacological and non-pharmacological interventions are urgently needed to improve the ongoing burden following hospitalisation for COVID-19 both for individuals and healthcare systems; our findings support the use of a precision medicine approach with potential treatable traits of systemic inflammation and obesity.",infectious diseases,exact,100,100 -medRxiv,10.1101/2021.12.14.21267460,2021-12-15,https://medrxiv.org/cgi/content/short/2021.12.14.21267460,Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales,Sarah Beale; Susan J Hoskins; Thomas Edward Byrne; Erica Wing Lam Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan MD Navaratnam; Vincent Nguyen; Parth Patel; Alexei Yavlinsky; Anne Johnson; Martie Van Tongeren; Robert W Aldridge; Andrew Hayward,University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University of Manchester; University College London; University College London,"BackgroundWorkers differ in their risk of SARS-CoV-2 infection according to their occupation, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase. - -MethodsData from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR). - -FindingsIncreased risk was seen in nurses (aRR=1.44, 1.25-1.65; AF=30%, 20-39%), doctors (aRR=1.33, 1.08-1.65; AF=25%, 7-39%), carers (1.45, 1.19-1.76; AF=31%, 16-43%), primary school teachers (aRR=1.67, 1.42-1.96; AF=40%, 30-49%), secondary school teachers (aRR=1.48, 1.26-1.72; AF=32%, 21-42%), and teaching support occupations (aRR=1.42, 1.23-1.64; AF=29%, 18-39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020 - May 2021) and attenuated later (June - October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves. - -InterpretationOccupational differentials in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.",epidemiology,exact,100,100 medRxiv,10.1101/2021.12.08.21267353,2021-12-08,https://medrxiv.org/cgi/content/short/2021.12.08.21267353,The challenge of limited vaccine supplies: impact of prior infection on anti-spike IgG antibody trajectories after a single COVID-19 vaccination,Jia Wei; Philippa Matthews; Nicole Stoesser; Ian Diamond; Ruth Studley; Emma Rourke; Duncan Cook; John Bell; John Newton; Jeremy Farrar; Alison Howarth; Brian Marsden; Sarah Hoosdally; Yvonne Jones; David Stuart; Derrick W Crook; tim E peto; Ann Sarah Walker; David W Eyre; Koen B Pouwels; - COVID-19 Infection Survey team,University of Oxford; University of Oxford; University of Oxford; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Public Health England; Wellcome Trust; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; NIHR Oxford Biomedical Research Centre; oxford university; University of Oxford; University of Oxford; University of Oxford; ,"Given high SARS-CoV-2 incidence, coupled with slow and inequitable vaccine roll-out, there is an urgent need for evidence to underpin optimum vaccine deployment, aiming to maximise global population immunity at speed. We evaluate whether a single vaccination in previously infected individuals generates similar initial and subsequent antibody responses to two vaccinations in those without prior infection. We compared anti-spike IgG antibody responses after a single dose of ChAdOx1, BNT162b2, or mRNA-1273 SARS-CoV-2 vaccines in the COVID-19 Infection Survey in the UK general population. In 100,849 adults who received at least one vaccination, 13,404 (13.3%) had serological and/or PCR evidence of prior infection. Prior infection significantly boosted antibody responses for all three vaccines, producing a higher peak level and longer half-life, and a response comparable to those without prior infection receiving two vaccinations. In those with prior infection, median time above the positivity threshold was estimated to last for >1 year after the first dose. Single-dose vaccination targeted to those previously infected may provide protection in populations with high rates of previous infection faced with limited vaccine supply, as an interim measure while vaccine campaigns are scaled up.",infectious diseases,exact,100,100 medRxiv,10.1101/2021.11.24.21266818,2021-12-01,https://medrxiv.org/cgi/content/short/2021.11.24.21266818,Trends and associated factors for Covid-19 hospitalisation and fatality risk in 2.3 million adults in England,Thomas Beaney; Ana Luisa Neves; Ahmed Alboksmaty; Kelsey Flott; Aidan Fowler; Jonathan R Benger; Paul Aylin; Sarah Elkin; Ara Darzi; Jonathan Clarke,Imperial College London; Imperial College London; Imperial College London; Imperial College London; NHS England and Improvement; NHS Digital; Imperial College London; Imperial College London; Imperial College London; Imperial College London,"BackgroundThe Covid-19 case fatality ratio varies between countries and over time but it is unclear whether variation is explained by the underlying risk in those infected. This study aims to describe the trends and risk factors for admission and mortality rates over time in England. @@ -1343,6 +1342,15 @@ MethodsPopulation-level birth outcomes in Wales: Stillbirths, prematurity, birth FindingsThere was no significant difference between annual outcomes including gestation and birth weight, stillbirths, and Caesarean sections for infants born in 2020 compared to 2016-2019. There was an increase in late term births ([≥]42 weeks gestation) during the first lockdown (OR: 1.28, p=0.019) and a decrease in moderate to late preterm births (32-36 weeks gestation) during the second lockdown (OR: 0.74, p=0.001). Fewer babies were born in 2020 (N=29,031) compared to 2016-2019 (average N=32,582). All babies received their immunisations in 2020, but there were minor delays in the timings of vaccines. Those due at 8-weeks were 8% less likely to be on time (within 28-days) and at 16-weeks, they were 19% less likely to be on time. The pandemic had a negative impact on the mental health of 71% of survey respondents, who reported anxiety, stress and loneliness; this was associated with attending scans without their partner, giving birth alone, and minimal contact with midwives. InterpretationThe pandemic had a negative impact on mothers experiences of pregnancy; however, population-level data suggests that this did not translate to adverse birth outcomes for babies born during the pandemic.",public and global health,exact,100,100 +medRxiv,10.1101/2021.08.17.21262196,2021-08-22,https://medrxiv.org/cgi/content/short/2021.08.17.21262196,Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY disease (CLARITY): Statistical analysis plan for a randomised controlled Bayesian adaptive sample size trial,James McGree; Carinna Hockham; Sradha Kotwal; Arlen Wilcox; Abhinav Bassi; Carol Pollock; Louise M Burrell; Tom Snelling; Vivek Jha; Meg Jardine; Mark Jones,Queensland University of Technology; Imperial College London; University of New South Wales; University of New South Wales; The George Institute for Global Health; Royal North Shore Hospital; University of Melbourne; The University of Sydney; University of New South Wales; University of New South Wales; The University of Sydney,"The CLARITY trial (Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY Disease) investigates the effectiveness of angiotensin receptor blockers in addition to standard care compared to placebo (in Indian sites) with standard care in reducing the duration and severity of lung failure in patients with COVID-19. The CLARITY trial is a multi-centre, randomised controlled Bayesian adaptive trial with regular planned analyses where pre-specified decision rules will be assessed to determine whether the trial should be stopped due to sufficient evidence of treatment effectiveness or futility. Here we describe the statistical analysis plan for the trial, and define the pre-specified decision rules, including those that could lead to the trial being halted. The primary outcome is clinical status on a 7-point ordinal scale adapted from the WHO Clinical Progression scale assessed at Day 14. The primary analysis will follow the intention-to-treat principle. A Bayesian adaptive trial design was selected because there is considerable uncertainty about the extent of potential benefit of this treatment. + +Trial registrationClinicalTrials.gov, NCT04394117. Registered on 19 May 2020. + +https://clinicaltrials.gov/ct2/show/NCT04394117 + +Clinical Trial Registry of India: CTRI/2020/07/026831 + +Version and revisionsVersion 1.0. No revisions.",respiratory medicine,exact,100,100 medRxiv,10.1101/2021.08.13.21261889,2021-08-18,https://medrxiv.org/cgi/content/short/2021.08.13.21261889,Robust SARS-CoV-2-specific and heterologous immune responses after natural infection in elderly residents of Long-Term Care Facilities,Gokhan Tut; Tara Lancaster; Megan S Butler; Panagiota Sylla; Eliska Spalkova; David Bone; Nayandeep Kaur; Christopher Bentley; Umayr Amin; Azar T Jadir; Samuel Hulme; Morenike Ayodele; Alexander C Dowell; Hayden Pearce; Sandra Margielewska-Davies; Kriti Verma; Samantha Nicol; Jusnara Begum; Elizabeth Jinks; Elif Tut; Rachel Bruton; Maria Krutikov; Madhumita Shrotri; Rebecca Giddings; Borscha Azmi; Chris Fuller; Aidan Irwin-Singer; Andrew Hayward; Andrew Copas; Laura Shallcross; Paul Moss,"Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; UCL Institute of Health Informatics, London, UK; Department of Health and Social Care, London, UK; Health Data Research UK; UCL Institute for Global Health, London, UK; UCL Institute of Health Informatics, London, UK; Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK","Long term care facilities (LTCF) provide residential and/or nursing care support for frail and elderly people and many have suffered from a high prevalence of SARS-CoV-2 infection. Although mortality rates have been high in LTCF residents there is little information regarding the features of SARS-CoV-2-specific immunity after infection in this setting or how this may influence immunity to other infections. We studied humoral and cellular immunity against SARS-CoV-2 in 152 LTCF staff and 124 residents over a prospective 4-month period shortly after the first wave of infection and related viral serostatus to heterologous immunity to other respiratory viruses and systemic inflammatory markers. LTCF residents developed high levels of antibodies against spike protein and RBD domain which were stable over 4 months of follow up. Nucleocapsid-specific responses were also elevated in elderly donors but showed waning across all populations. Antibodies showed stable and equivalent levels of functional inhibition against spike-ACE2 binding in all age groups with comparable activity against viral variants of concern. SARS-CoV-2 seropositive donors showed high levels of antibodies to other beta-coronaviruses but serostatus did not impact humoral immunity to influenza or RSV. SARS-CoV-2-specific cellular responses were equivalent across the life course but virus-specific populations showed elevated levels of activation in older donors. LTCF residents who are survivors of SARS-CoV-2 infection thus show robust and stable immunity which does not impact responses to other seasonal viruses. These findings augur well for relative protection of LTCF residents to re-infection. Furthermore, they underlie the potent influence of previous infection on the immune response to Covid-19 vaccine which may prove to be an important determinant of future vaccine strategy. One sentence summeryCare home residents show waning of nucleocapsid specific antibodies and enhanced expression of activation markers on SARS-CoV-2 specific cells",infectious diseases,exact,100,100 @@ -1776,6 +1784,7 @@ MethodsA national record linkage study determined documented COVID-19 cases and ResultsThe cohort comprised of 194,362 household members (mean age 31{middle dot}1 {+/-} 20{middle dot}9 years) and 144,525 healthcare workers (mean age 44{middle dot}4 {+/-} 11{middle dot}4 years). 113,253 (78{middle dot}3%) of healthcare workers received at least one dose of the BNT162b2 mRNA or ChAdOx1 nCoV-19 vaccine and 36,227 (25{middle dot}1%) received a second dose. There were 3,123 and 4,343 documented COVID-19 cases and 175 and 177 COVID-19 hospitalisations in household members of healthcare workers and healthcare workers respectively. Household members of vaccinated healthcare workers had a lower risk of COVID-19 case compared to household members of unvaccinated healthcare worker (rate per 100 person-years 9{middle dot}40 versus 5{middle dot}93; HR 0{middle dot}70, 95% confidence interval [CI] 0{middle dot}63 to 0{middle dot}78). The effect size for COVID-19 hospitalisation was similar, with the confidence interval crossing the null (HR 0{middle dot}77 [95% CI 0{middle dot}53 to 1{middle dot}10]). The rate per 100 person years was lower in vaccinated compared to unvaccinated healthcare workers for documented (20{middle dot}13 versus 8{middle dot}51; HR 0{middle dot}45 [95% CI 0{middle dot}42 to 0{middle dot}49]) and hospitalized COVID-19 (0{middle dot}97 versus 0{middle dot}14; HR 0{middle dot}16 [95% CI 0{middle dot}09 to 0{middle dot}27]). Compared to the period before the first dose, the risk of documented COVID-19 case was lower at [≥] 14 days after the second dose for household members (HR 0{middle dot}46 [95% CI 0{middle dot}30to 0{middle dot}70]) and healthcare workers (HR 0{middle dot}08 [95% CI 0{middle dot}04 to 0{middle dot}17]). InterpretationVaccination of health care workers was associated with a substantial reduction in COVID-19 cases in household contacts consistent with an effect of vaccination on transmission.",public and global health,exact,100,100 +medRxiv,10.1101/2021.03.17.21253853,2021-03-20,https://medrxiv.org/cgi/content/short/2021.03.17.21253853,"Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest optimal policies varies with rural-urban settings",Xilin Jiang; Wenfeng Gong; Zlatina Dobreva; Ya Gao; Matthew Quaife; Christophe Fraser; Chris Holmes,"University of Oxford; Bill & Melinda Gates Foundation; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; Department of International Health, Johns Hopkins University; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; University of Oxford; University of Oxford","Low- and middle-income countries (LMICs) remain of high potential for hotspots for COVID-19 deaths and emerging variants given the inequality of vaccine distribution and their vulnerable healthcare systems. We aim to evaluate containment strategies that are sustainable and effective for LMICs. We constructed synthetic populations with varying contact and household structures to capture LMIC demographic characteristics that vary across communities. Using an agent- based model, we explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic tests, symptom screening, contact tracing and physical distancing. In low-density rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. In urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In high density communities that resemble slums and squatter settlements, physical distancing is less effective compared to rural and urban communities. Lastly, we demonstrated contact tracing is essential for effective containment. Our findings suggested that rapid diagnostic tests could be prioritised for control and monitor COVID-19 transmission and highlighted that contact survey data could guide strategy design to save resources for LMICs. An accompanying open source R package is available for simulating COVID-19 transmission based on contact network models.",epidemiology,exact,100,100 medRxiv,10.1101/2021.03.18.21253443,2021-03-20,https://medrxiv.org/cgi/content/short/2021.03.18.21253443,Intensity of COVID-19 in care homes following Hospital Discharge in the early stages of the UK epidemic,Joe Hollinghurst; Laura North; Chris Emmerson; Ashley Akbari; Fatemeh Torabi; Ronan A Lyons; Alan G Hawkes; Ed Bennett; Mike B Gravenor; Richard Fry,Swansea University; Swansea University; Public Health Wales; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University; Swansea University,"BackgroundA defining feature of the COVID-19 pandemic in many countries was the tragic extent to which care home residents were affected, and the difficulty preventing introduction and subsequent spread of infection. Management of risk in care homes requires good evidence on the most important transmission pathways. One hypothesised route at the start of the pandemic, prior to widespread testing, was transfer of patients from hospitals, which were experiencing high levels of nosocomial events. MethodsWe tested the hypothesis that hospital discharge events increased the intensity of care home cases using a national individually linked health record cohort in Wales, UK. We monitored 186,772 hospital discharge events over the period March to July 2020, tracking individuals to 923 care homes and recording the daily case rate in the homes populated by 15,772 residents. We estimated the risk of an increase in cases rates following exposure to a hospital discharge using multi-level hierarchical logistic regression, and a novel stochastic Hawkes process outbreak model. @@ -1787,25 +1796,6 @@ medRxiv,10.1101/2021.03.04.21252931,2021-03-08,https://medrxiv.org/cgi/content/s TMPRSS2 rs12329760 is a common variant associated with a significantly decreased risk of severe COVID19. Further studies are needed to assess the expression of the TMPRSS2 across different age groups. Moreover, our results identify TMPRSS2 as a promising drug target, with a potential role for camostat mesilate, a drug approved for the treatment of chronic pancreatitis and postoperative reflux esophagitis, in the treatment of COVID19. Clinical trials are needed to confirm this.",genetic and genomic medicine,exact,100,100 medRxiv,10.1101/2021.03.02.21252444,2021-03-03,https://medrxiv.org/cgi/content/short/2021.03.02.21252444,An overview of the National COVID-19 Chest Imaging Database: data quality and cohort analysis,Dominic Cushnan; Oscar Bennett; Rosalind Berka; Ottavia Bertolli; Ashwin Chopra; Samie Dorgham; Alberto Favaro; Tara Ganepola; Mark Halling-Brown; Gergely Imreh; Joseph Jacob; Emily Jefferson; François Lemarchand; Daniel Schofield; Jeremy C Wyatt; - NCCID Collaborative,"AI Lab, NHSX, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Faculty, London, UK; Scientific Computing, Royal Surrey NHS Foundation Trust, Guildford, UK; Faculty, London, UK; Centre for Medical Image Computing, University College London, London, UK; Health Informatics Centre (HIC), School of Medicine, University of Dundee, UK; AI Lab, NHSX, London, UK; AI Lab, NHSX, London, UK; University of Southampton, Southampton, UK; ","The National COVID-19 Chest Imaging Database (NCCID) is a centralised database containing chest X-rays, chest Computed Tomography (CT) scans and cardiac Magnetic Resonance Images (MRI) from patients across the UK, jointly established by NHSX, the British Society of Thoracic Imaging (BSTI), Royal Surrey NHS Foundation Trust (RSNFT) and Faculty. The objective of the initiative is to support a better understanding of the coronavirus SARS-CoV-2 disease (COVID-19) and development of machine learning (ML) technologies that will improve care for patients hospitalised with a severe COVID-19 infection. The NCCID is now accumulating data from 20 NHS Trusts and Health Boards across England and Wales, with a total contribution of approximately 25,000 imaging studies in the training set (at time of writing) and is actively being used as a research tool by several organisations. This paper introduces the training dataset, including a snapshot analysis performed by NHSX covering: the completeness of clinical data, the availability of image data for the various use-cases (diagnosis, prognosis and longitudinal risk) and potential model confounders within the imaging data. The aim is to inform both existing and potential data users of the NCCIDs suitability for developing diagnostic/prognostic models. In addition, a cohort analysis was performed to measure the representativeness of the NCCID to the wider COVID-19 affected population. Three major aspects were included: geographic, demographic and temporal coverage, revealing good alignment in some categories, e.g., sex and identifying areas for improvements to data collection methods, particularly with respect to geographic coverage. All analyses and discussions are focused on the implications for building ML tools that will generalise well to the clinical use cases.",radiology and imaging,exact,100,100 -medRxiv,10.1101/2021.02.27.21252593,2021-03-01,https://medrxiv.org/cgi/content/short/2021.02.27.21252593,Surgical activity in England and Wales during the COVID-19 pandemic: a nationwide observational cohort study,Thomas D Dobbs; John A G Gibson; Alexander J Fowler; Tom E Abbott; Tasnin Shahid; Fatemeh Torabi; Rowena Griffiths; Ronan A Lyons; Rupert M Pearse; Iain S Whitaker,"Swansea University Medical School; Swansea University Medical School; Queen Mary, University of London; Queen Mary University of London; Queen Mary University of London; Swansea University; Swansea University; Swansea University; Queen Mary University of London; Swansea University Medical School","ObjectivesTo report the volume of surgical activity and the number of cancelled surgical procedures during the COVID-19 pandemic. - -Design and settingAnalysis of electronic health record data from the National Health Service (NHS) in England and Wales. - -MethodsWe used hospital episode statistics for all adult patients undergoing surgery between 1st January 2020 and 31st December 2020. We identified surgical procedures using a previously published list of procedure codes. Procedures were stratified by urgency of surgery as defined by NHS England. We calculated the deficit of surgical activity by comparing the expected number of procedures from the years 2016-2019 with the actual number of procedures in 2020. We estimated the cumulative number of cancelled procedures by 31st December 2021 according patterns of activity in 2020. - -ResultsThe total number of surgical procedures carried out in England and Wales in 2020 was 3,102,674 compared to the predicted number of 4,671,338. This represents a 33.6% reduction in the national volume of surgical activity. There were 763,730 emergency surgical procedures (13.4% reduction), compared to 2,338,944 elective surgical procedures (38.6% reduction). The cumulative number of cancelled or postponed procedures was 1,568,664. We estimate that this will increase to 2,358,420 by 31st December 2021. - -ConclusionsThe volume of surgical activity in England and Wales was reduced by 33.6% in 2020, resulting in over 1,568,664 cancelled operations. This deficit will continue to grow in 2021. - -Summary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIThe COVID-19 pandemic necessitated a rapid change in the provision of care, including the suspension of a large proportion of surgical activity -C_LIO_LISurgical activity has yet to return to normal and has been further impacted by subsequent waves of the pandemic -C_LIO_LIThis will lead to a large backlog of cases -C_LI - -What this study addsO_LI3,102,674 surgical procedures were performed in England and Wales during 2020, a 33.6% reduction on the expected yearly surgical activity -C_LIO_LIOver 1.5 million procedures were not performed, with this deficit likely to continue to grow to 2.3 million by the end of 2021 -C_LIO_LIThis deficit is the equivalent of more than 6 months of pre-pandemic surgical activity, requiring a monumental financial and logistic challenge to manage -C_LI",surgery,exact,100,100 medRxiv,10.1101/2021.02.23.21251975,2021-02-25,https://medrxiv.org/cgi/content/short/2021.02.23.21251975,The United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers (UK-REACH): Protocol for a prospective longitudinal cohort study of healthcare and ancillary workers in UK healthcare settings,Katherine Woolf; Carl Melbourne; Luke Bryant; Anna Louise Guyatt; Ian Christopher McManus; Amit Gupta; Robert C Free; Laura Nellums; Sue Carr; Catherine John; Christopher A Martin; Louise V Wain; Laura J Gray; Claire Garwood; Vishant Modhwadia; Keith Abrams; Martin D Tobin; Kamlesh Khunti; Manish Pareek; - UK-REACH Study Collaborative Group,"University College London; University of Leicester; University of Leicester; University of Leicester; University College London; University Hospitals Oxford NHS Foundation Trust; University of Leicester; University of Nottingham; General Medical Council, University Hospitals Leicester NHS Trust; University of Leicester; University of Leicester; University of Leicester; University of Leicester; University of Leicester; University of Leicester; University of York; University of Leicester; University of Leicester; University of Leicester; ","IntroductionThe COVID-19 pandemic has resulted in significant morbidity and mortality, and has devastated economies in many countries. Amongst the groups identified as being at increased risk from COVID-19 are healthcare workers (HCWs) and ethnic minority groups. Emerging evidence suggests HCWs from ethnic minority groups are at increased risk of adverse COVID-19-related physical and mental health outcomes. To date there has been no large-scale analysis of these risks in UK healthcare workers or ancillary workers in healthcare settings, stratified by ethnicity or occupation type, and adjusted for potential confounders. This paper reports the protocol for a prospective longitudinal questionnaire study of UK HCWs, as part of the UK-REACH programme (The United Kingdom Research study into Ethnicity And COVID-19 outcomes in Healthcare workers). Methods and analysisA baseline questionnaire with follow-up questionnaires at 4 and 8 months will be administered to a national cohort of UK healthcare workers and ancillary workers in healthcare settings, and those registered with UK healthcare regulators. With consent, data will be linked to health records, and participants followed up for 25 years. @@ -1959,6 +1949,15 @@ MethodsWorking on behalf of NHS England we analysed 57.9 million patient records Results20,852,692 patients (36%) received a COVID-19 vaccine between December 8th 2020 and March 17th 2021. Of patients aged [≥]80 not in a care home (JCVI group 2) 94.7% received a vaccine, but with substantial variation by ethnicity (White 96.2% vaccinated, Black 68.3%) and deprivation (least deprived 96.6%, most deprived 90.7%). Overall, patients with pre-existing medical conditions were equally or more likely to be vaccinated with two exceptions: severe mental illness (89.5% vaccinated) and learning disability (91.4%). 275,205 vaccine recipients were identified as care home residents (priority group 1; 91.2% coverage). 1,257,914 (6.0%) recipients have had a second dose. Detailed characteristics of recipients in all cohorts are reported. ConclusionsThe NHS in England has rapidly delivered mass vaccination. We were able to deploy a data monitoring framework using publicly auditable methods and a secure, in-situ processing model, using linked but pseudonymised patient-level NHS data on 57.9 million patients with very short delays from vaccine administration to completed analysis. Targeted activity may be needed to address lower vaccination coverage observed among certain key groups: ethnic minorities, those living in deprived areas, and people with severe mental illness or learning disabilities.",public and global health,exact,100,100 +medRxiv,10.1101/2021.01.22.21250304,2021-01-25,https://medrxiv.org/cgi/content/short/2021.01.22.21250304,Rates of serious clinical outcomes in survivors of hospitalisation with COVID-19: a descriptive cohort study within the OpenSAFELY platform,John Tazare; Alex J Walker; Laurie Tomlinson; George Hickman; Christopher T Rentsch; Elizabeth J Williamson; Krishnan Bhaskaran; David Evans; Kevin Wing; Rohini Mathur; Angel YS Wong; Anna Schultze; Sebastian CJ Bacon; Christopher Bates; Caroline E Morton; Helen J Curtis; Emily Nightingale; Helen I McDonald; Amir Mehrkar; Peter Inglesby; Simon Davy; Brian MacKenna; Jonathan Cockburn; William J Hulme; Charlotte Warren-Gash; Ketaki Bhate; Emma Powell; Any Mulick; Harriet Forbes; Caroline Minassian; Richard Croker; John Parry; Frank Hester; Sam Harper; Rosalind M Eggo; Stephen JW Evans; Liam Smeeth; Ian J Douglas; Ben Goldacre,London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundPatients with COVID-19 are thought to be at higher risk of cardiometabolic and pulmonary complications, but quantification of that risk is limited. We aimed to describe the overall burden of these complications in survivors of severe COVID-19. + +MethodsWorking on behalf of NHS England, we used linked primary care records, death certificate and hospital data from the OpenSAFELY platform. We constructed three cohorts: patients discharged following hospitalisation with COVID-19, patients discharged following hospitalisation with pneumonia in 2019, and a frequency-matched cohort from the general population in 2019. We studied eight cardiometabolic and pulmonary outcomes. Absolute rates were measured in each cohort and Cox regression models were fitted to estimate age/sex adjusted hazard ratios comparing outcome rates between discharged COVID-19 patients and the two comparator cohorts. + +ResultsAmongst the population of 31,716 patients discharged following hospitalisation with COVID-19, rates for majority of outcomes peaked in the first month post-discharge, then declined over the following four months. Patients in the COVID-19 population had markedly increased risk of all outcomes compared to matched controls from the 2019 general population, especially for pulmonary embolism (HR 12.86; 95% CI: 11.23 - 14.74). Outcome rates were more similar when comparing patients discharged with COVID-19 to those discharged with pneumonia in 2019, although COVID-19 patients had increased risk of type 2 diabetes (HR 1.23; 95% CI: 1.05 - 1.44). + +InterpretationCardiometabolic and pulmonary adverse outcomes are markedly raised following hospitalisation for COVID-19 compared to the general population. However, the excess risks were more comparable to those seen following hospitalisation with pneumonia. Identifying patients at particularly high risk of outcomes would inform targeted preventive measures. + +FundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, UK Research and Innovation, Health and Safety Executive.",epidemiology,exact,100,100 medRxiv,10.1101/2021.01.22.21249968,2021-01-25,https://medrxiv.org/cgi/content/short/2021.01.22.21249968,An external validation of the QCovid risk prediction algorithm for risk of mortality from COVID-19 in adults: national validation cohort study in England,Vahe Nafilyan; Ben Humberstone; Nisha Metha; Ian Diamond; Luke Lorenzi; Piotr Pawelek; Ryan Schofield; Jasper Morgan; Paul Brown; Ronan Lyons; Aziz Sheikh; Julia Hippisley-Cox,Office for National Statistics; Office for National Statistics; Office of the Chief Medical Officer; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Swansea University; University of Edinburgh; University of Oxford,"BackgroundTo externally validate a risk prediction algorithm (QCovid) to estimate mortality outcomes from COVID-19 in adults in England. MethodsPopulation-based cohort study using the ONS Public Health Linked Data Asset, a cohort based on the 2011 Census linked to Hospital Episode Statistics, the General Practice Extraction Service Data for pandemic planning and research, radiotherapy and systemic chemotherapy records. The primary outcome was time to COVID-19 death, defined as confirmed or suspected COVID-19 death as per death certification. Two time periods were used: (a) 24th January to 30th April 2020; and (b) 1st May to 28th July 2020. We evaluated the performance of the QCovid algorithms using measures of discrimination and calibration for each validation time period. @@ -2052,6 +2051,15 @@ What is already known on this topicPre-pandemic, higher occupancy of intensive c What this study addsThe results of this study suggest that survival rates for patients with COVID-19 in intensive care settings appears to deteriorate as the occupancy of (surge capacity) beds compatible with mechanical ventilation (a proxy for operational pressure), increases. Moreover, this risk doesnt occur above a specific threshold, but rather appears linear; whereby going from 0% occupancy to 100% occupancy increases risk of mortality by 69% (after adjusting for relevant individual-level factors). Furthermore, risk of mortality based on occupancy on the date of recorded outcome is even higher; OR 2.98 (95% posterior credible interval: 2.33 - 3.83). As such, this national-level cohort study of England provides compelling evidence for a relationship between occupancy and critical care mortality, and highlights the needs for decisive action to control the incidence and prevalence of COVID-19. C_TEXTBOX",intensive care and critical care medicine,exact,100,100 +medRxiv,10.1101/2021.01.06.21249352,2021-01-08,https://medrxiv.org/cgi/content/short/2021.01.06.21249352,OpenSAFELY NHS Service Restoration Observatory 1: describing trends and variation in primary care clinical activity for 23.3 million patients in England during the first wave of COVID-19,Helen J Curtis; Brian MacKenna; Richard Croker; Alex J Walker; Peter Inglesby; Jessica Morley; Amir Mehrkar; Caroline E Morton; Seb Bacon; George Hickman; Chris Bates; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan T. Bhaskaran; Anna Schultze; Christopher T. Rentsch; Elizabeth J Williamson; Will Hulme; Helen I McDonald; Laurie Tomlinson; Kevin Wing; Rohini I Mathur; Harriet Forbes; Angel Wong; Rosalind M Eggo; Henry Drysdale; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Stephen Evans; Liam Smeeth; Ben Goldacre,"University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; LSHTM; US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine; LSHTM; University of Oxford; London School of Medicine and Tropical Medicine; LSHTM; LSHTM; London School of Hygiene and Tropical Medicine; LSHTM; London School of Hygiene and Tropical Medicine; LSHTM; University of Oxford; TPP; TPP; TPP; LSHTM; LSHTM; LSHTM; University of Oxford","BackgroundThe COVID-19 pandemic has disrupted healthcare activity globally. The NHS in England stopped most non-urgent work by March 2020, but later recommended that services should be restored to near-normal levels before winter where possible. The authors are developing the OpenSAFELY NHS Service Restoration Observatory, using data to describe changes in service activity during COVID-19, and reviewing signals for action with commissioners, researchers and clinicians. Here we report phase one: generating, managing, and describing the data. + +ObjectiveTo describe the volume and variation of coded clinical activity in English primary care across 23.8 million patients records, taking respiratory disease and laboratory procedures as key examples. + +MethodsWorking on behalf of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care EHR data on 23.8 million patients; and conducted a population cohort-based study to describe activity using CTV3 coding hierarchy and keyword searches from January 2019-September 2020. + +ResultsMuch activity recorded in general practice declined to some extent during the pandemic, but largely recovered by September 2020, with some exceptions. There was a large drop in coded activity for commonly used laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was blood coagulation tests such as International Normalised Ratio (INR), with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 7.0). The overall pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as ""no change"" from the previous year. Respiratory tract infections exhibited a sustained drop compared with pre-pandemic levels, not returning to pre-pandemic levels by September 2020. Various COVID-19 codes increased through the period. We observed a small decline associated with high level codes for long-term respiratory conditions such as chronic obstructive pulmonary disease (COPD) and asthma. Asthma annual reviews experienced a small drop but since recovered, while COPD annual reviews remain below baseline. + +ConclusionsWe successfully delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September 2020, with some important tests less affected. Records of respiratory infections decreased with the exception of codes related to COVID-19, whilst activity of other respiratory disease codes was mixed. We are expanding the NHS Service Restoration Observatory in collaboration with clinicians, commissioners and researchers and welcome feedback.",health systems and quality improvement,exact,100,100 medRxiv,10.1101/2020.12.30.20248603,2021-01-01,https://medrxiv.org/cgi/content/short/2020.12.30.20248603,SARS-CoV-2 positivity in asymptomatic-screened dental patients,David I Conway; Shauna Culshaw; Maura Edwards; Claire Clark; Chris Watling; Chris Robertson; Raymond Braid; Emma O'Keefe; Niall McGoldrick; Jacky Burns; Stacey Provan; Harper VanSteenhouse; Jodie Hay; Rory Gunson; - Dental COVID-19 Surveillance Survey Group,University of Glasgow and Public Health Scotland; University of Glasgow; NHS Ayrshire and Arran; Public Health Scotland; Public Health Scotland; Strathclyde University and Public Health Scotland; Public Health Scotland; NHS Fife; NHS Fife; NHS Fife; NHS Greater Glasgow & Clyde; BioClavis Ltd; University of Glasgow; NHS Greater Glasgow & Clyde; ,"Enhanced community surveillance is a key pillar of the public health response to COVID-19. Asymptomatic carriage of SARS-CoV-2 is a potentially significant source of transmission, yet remains relatively poorly understood. Disruption of dental services continues with significantly reduced capacity. Ongoing precautions include pre- and/or at appointment COVID-19 symptom screening and use of enhanced personal protective equipment (PPE). This study aimed to investigate SARS-CoV-2 infection in dental patients to inform community surveillance and improve understanding of risks in the dental setting. Thirty-one dental care centres across Scotland invited asymptomatic screened patients over 5-years-old to participate. Following verbal consent and completion of sociodemographic and symptom history questionnaire, trained dental teams took a combined oropharyngeal and nasal swab sample using standardised VTM-containing testkits. Samples were processed by the Lighthouse Lab and patients informed of their results by SMS/e-mail with appropriate self-isolation guidance in the event of a positive test. Over a 13-week period (from 3August to 31October2020) n=4,032 patients, largely representative of the population, were tested. Of these n=22 (0.5%; 95%CI 0.5%, 0.8%) tested positive for SARS-CoV-2. The positivity rate increased over the period, commensurate with uptick in community prevalence identified across all national testing monitoring data streams. All positive cases were successfully followed up by the national contact tracing program. To the best of our knowledge this is the first report of a COVID-19 testing survey in asymptomatic-screened patients presenting in a dental setting. The positivity rate in this patient group reflects the underlying prevalence in community at the time. These data are a salient reminder, particularly when community infection levels are rising, of the importance of appropriate ongoing Infection Prevention Control and PPE vigilance, which is relevant as healthcare team fatigue increases as the pandemic continues. Dental settings are a valuable location for public health surveillance.",dentistry and oral medicine,exact,100,100 bioRxiv,10.1101/2020.12.23.424229,2020-12-25,https://biorxiv.org/cgi/content/short/2020.12.23.424229,Patterns of within-host genetic diversity in SARS-CoV-2,Gerry Tonkin-Hill; Inigo Martincorena; Roberto Amato; Andrew R J Lawson; Moritz Gerstung; Ian Johnston; David K Jackson; Naomi R Park; Stefanie V Lensing; Michael A Quail; Sónia Gonçalves; Cristina Ariani; Michael Spencer Chapman; William L Hamilton; Luke W Meredith; Grant Hall; Aminu S Jahun; Yasmin Chaudhry; Myra Hosmillo; Malte L Pinckert; Iliana Georgana; Anna Yakovleva; Laura G Caller; Sarah L Caddy; Theresa Feltwell; Fahad A Khokhar; Charlotte J Houldcroft; Martin D Curran; Surendra Parmar; - The COVID-19 Genomics UK (COG-UK) Consortium; Alex Alderton; Rachel Nelson; Ewan Harrison; John Sillitoe; Stephen D Bentley; Jeffrey C Barrett; M. Estee Torok; Ian G Goodfellow; Cordelia Langford; Dominic Kwiatkowski; - Wellcome Sanger Institute COVID-19 Surveillance Team,"Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; European Bioinformatics Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge; Department of Pathology, University of Cambridge and The Francis Crick Institute; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Department of Medicine, University of Cambridge and Cambridge Institute of Therapeutic Immunology and Infectious Disease; Department of Medicine, University of Cambridge; Public Health England; Public Health England; COG-UK; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute and European Bioinformatics Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Wellcome Sanger Institute; Department of Medicine, University of Cambridge; Department of Pathology, University of Cambridge; Wellcome Sanger Institute; Wellcome Sanger Institute and Oxford University; ","Monitoring the spread of SARS-CoV-2 and reconstructing transmission chains has become a major public health focus for many governments around the world. The modest mutation rate and rapid transmission of SARS-CoV-2 prevents the reconstruction of transmission chains from consensus genome sequences, but within-host genetic diversity could theoretically help identify close contacts. Here we describe the patterns of within-host diversity in 1,181 SARS-CoV-2 samples sequenced to high depth in duplicate. 95% of samples show within-host mutations at detectable allele frequencies. Analyses of the mutational spectra revealed strong strand asymmetries suggestive of damage or RNA editing of the plus strand, rather than replication errors, dominating the accumulation of mutations during the SARS-CoV-2 pandemic. Within and between host diversity show strong purifying selection, particularly against nonsense mutations. Recurrent within-host mutations, many of which coincide with known phylogenetic homoplasies, display a spectrum and patterns of purifying selection more suggestive of mutational hotspots than recombination or convergent evolution. While allele frequencies suggest that most samples result from infection by a single lineage, we identify multiple putative examples of co-infection. Integrating these results into an epidemiological inference framework, we find that while sharing of within-host variants between samples could help the reconstruction of transmission chains, mutational hotspots and rare cases of superinfection can confound these analyses.",genomics,exact,100,100 medRxiv,10.1101/2020.12.18.20248477,2020-12-20,https://medrxiv.org/cgi/content/short/2020.12.18.20248477,Face covering adherence is positively associated with better mental health and wellbeing: a longitudinal analysis of the CovidLife surveys,Drew M Altschul; Chloe Fawns-Ritchie; Alex Kwong; Louise Hartley; Clifford Nangle; Rachel Edwards; Rebecca Dawson; Christie Levein; Archie Campbell; Robin Flaig; Andrew McIntosh; Ian Deary; Riccardo Marioni; Caroline Hayward; Cathie Sudlow; Elaine Douglas; David Bell; David Porteous,The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; The University of Edinburgh; University of Stirling; University of Stirling; The University of Edinburgh,"Face masks or coverings are effective at reducing airborne infection rates, yet pandemic mitigation measures, including wearing face coverings, have been suggested to contribute to reductions in quality of life and poorer mental health. Longitudinal analyses of more than 11,000 participants across the UK found no association between lower adherence to face covering guidelines and poorer mental health. The opposite appears to be true. Even after controlling for behavioral, social, and psychological confounds, including measures of pre-pandemic mental health, individuals who wore face coverings ""most of the time"" or ""always"" had better mental health and wellbeing than those who did not. These results suggest that wearing face coverings more often will not negatively impact mental health.",psychiatry and clinical psychology,exact,100,100 @@ -2214,17 +2222,6 @@ ResultsThere were 17,576 positive tests over the three rounds. Antibody prevalen The decline from rounds 1 to 3 was largest in those who did not report a history of COVID-19, (-64.0% [-75.6, -52.3]), compared to -22.3% ([-27.0, -17.7]) in those with SARS-CoV-2 infection confirmed on PCR. DiscussionThese findings provide evidence of variable waning in antibody positivity over time such that, at the start of the second wave of infection in England, only 4.4% of adults had detectable IgG antibodies using an LFIA. Antibody positivity was greater in those who reported a positive PCR and lower in older people and those with asymptomatic infection. These data suggest the possibility of decreasing population immunity and increasing risk of reinfection as detectable antibodies decline in the population.",infectious diseases,exact,100,100 -medRxiv,10.1101/2020.10.14.20212555,2020-10-16,https://medrxiv.org/cgi/content/short/2020.10.14.20212555,Multi-organ impairment in low-risk individuals with long COVID,Andrea Dennis; Malgorzata Wamil; Sandeep Kapur; Johann Alberts; Andrew Badley; Gustav Anton Decker; Stacey A Rizza; Rajarshi Banerjee; Amitava Banerjee,Perspectum; Great Western Hospitals NHS Foundation Trust; Mayo Clinic Healthcare; Alliance Medical; Mayo Clinic; Mayo Clinic International; Mayo Clinic; Perspectum; University College London,"BackgroundSevere acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection has disproportionately affected older individuals and those with underlying medical conditions. Research has focused on short-term outcomes in hospital, and single organ involvement. Consequently, impact of long COVID (persistent symptoms three months post-infection) across multiple organs in low-risk individuals is yet to be assessed. - -MethodsAn ongoing prospective, longitudinal, two-centre, observational study was performed in individuals symptomatic after recovery from acute SARS-CoV-2 infection. Symptoms and organ function (heart, lungs, kidneys, liver, pancreas, spleen) were assessed by standardised questionnaires (EQ-5D-5L, Dyspnoea-12), blood investigations and quantitative magnetic resonance imaging, defining single and multi-organ impairment by consensus definitions. - -FindingsBetween April and September 2020, 201 individuals (mean age 44 (SD 11.0) years, 70% female, 87% white, 31% healthcare workers) completed assessments following SARS-CoV-2 infection (median 140, IQR 105-160 days after initial symptoms). The prevalence of pre-existing conditions (obesity: 20%, hypertension: 6%; diabetes: 2%; heart disease: 4%) was low, and only 18% of individuals had been hospitalised with COVID-19. Fatigue (98%), muscle aches (88%), breathlessness (87%), and headaches (83%) were the most frequently reported symptoms. Ongoing cardiorespiratory (92%) and gastrointestinal (73%) symptoms were common, and 42% of individuals had ten or more symptoms. - -There was evidence of mild organ impairment in heart (32%), lungs (33%), kidneys (12%), liver (10%), pancreas (17%), and spleen (6%). Single (66%) and multi-organ (25%) impairment was observed, and was significantly associated with risk of prior COVID-19 hospitalisation (p<0.05). - -InterpretationIn a young, low-risk population with ongoing symptoms, almost 70% of individuals have impairment in one or more organs four months after initial symptoms of SARS-CoV-2 infection. There are implications not only for burden of long COVID but also public health approaches which have assumed low risk in young people with no comorbidities. - -FundingThis work was supported by the UKs National Consortium of Intelligent Medical Imaging through the Industry Strategy Challenge Fund, Innovate UK Grant 104688, and also through the European Unions Horizon 2020 research and innovation programme under grant agreement No 719445.",health policy,exact,100,100 medRxiv,10.1101/2020.10.12.20211227,2020-10-14,https://medrxiv.org/cgi/content/short/2020.10.12.20211227,High and increasing prevalence of SARS-CoV-2 swab positivity in England during end September beginning October 2020: REACT-1 round 5 updated report,Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London School of Public Health","BackgroundREACT-1 is quantifying prevalence of SARS-CoV-2 infection among random samples of the population in England based on PCR testing of self-administered nose and throat swabs. Here we report results from the fifth round of observations for swabs collected from the 18th September to 5th October 2020. This report updates and should be read alongside our round 5 interim report. MethodsRepresentative samples of the population aged 5 years and over in England with sample size ranging from 120,000 to 175,000 people at each round. Prevalence of PCR-confirmed SARS-CoV-2 infection, estimation of reproduction number (R) and time trends between and within rounds using exponential growth or decay models. @@ -2278,6 +2275,15 @@ ResultsOver the 9 days for which data are available, we find 363 positives from ConclusionRapid growth has led to high prevalence of SARS-CoV-2 virus in England among all regions and age groups, including those age groups at highest risk. Although there is evidence of a recent deceleration in the epidemic, current levels of prevalence will inevitably result in additional hospitalisations and mortality in coming weeks. A re-doubling of public health efforts is needed to return to a declining phase of the epidemic.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.09.28.20202929,2020-09-29,https://medrxiv.org/cgi/content/short/2020.09.28.20202929,T cell assays differentiate clinical and subclinical SARS-CoV-2 infections from cross-reactive antiviral responses,Ane Ogbe; Barbara Kronsteiner; Donal T Skelly; Matthew Pace; Anthony Brown; Emily Adland; Kareena Adair; Hossain Delowar Akhter; Mohammad Ali; Serat-E Ali; Adrienn Angyal; M. Azim Ansari; Carolina V Arancibia-Carcamo; Helen Brown; Senthil Chinnakannan; Christopher P Conlon; Catherine de Lara; Thushan de Silva; Christina Dold; Tao Dong Dong; Timothy Donnison; David W Eyre; Amy Flaxman; Helen A Fletcher; Joshua Gardner; James T Grist; Carl-Philipp Hackstein; Kanoot Jaruthamsophon; Katie Jeffrey; Teresa Lambe; Lian Lee; Wenqin Li; Nicholas Lim; Philippa C Matthews; Alexander J Mentzer; Shona C Moore; Dean J Naisbitt; Monday Ogese; Graham Ogg; Peter Openshaw; Munir Pirmohamed; Andrew J Pollard; Narayan Ramamurthy; Patpong Rongkard; Sarah Rowland-Jones; Oliver L Sampson; Gavin Screaton; Alessandro Sette; Lizzie Stafford; Craig Thompson; Paul J Thomson; Ryan Thwaites; Vinicius Vieira; Daniela Weiskopf; Panagiota Zacharopoulou; - Oxford Immunology Network Covid-19 Response T cell Consortium; - Oxford Protective T cell Immunology for COVID-19 (OPTIC) Clinical team; Lance Turtle; Paul Klenerman; Philip Goulder; John Frater; Eleanor Barnes; Susanna Dunachie,University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Liverpool; University of Oxford; University of Oxford; University of Liverpool; University of Sheffield; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Sheffield; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Liverpool; University of Oxford; University of Oxford; University of Liverpool; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Liverpool; University of Liverpool; University of Liverpool; University of Oxford; Imperial College; University of Liverpool; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; La Jolla Institute for Immunology; Oxford University Hospitals NHS Foundation Trust; University of Oxford; University of Liverpool; Imperial College; University of Oxford; La Jolla Institute for Immunology; University of Oxford; ; ; University of Liverpool; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford,"A major issue in identification of protective T cell responses against SARS-CoV-2 lies in distinguishing people infected with SARS-CoV-2 from those with cross-reactive immunity generated by exposure to other coronaviruses. We characterised SARS-CoV-2 T cell immune responses in 168 PCR-confirmed SARS-CoV-2 infected subjects and 118 seronegative subjects without known SARS-CoV-2 exposure using a range of T cell assays that differentially capture immune cell function. Strong ex vivo ELISpot and proliferation responses to multiple antigens (including M, NP and ORF3) were found in those who had been infected by SARS-CoV-2 but were rare in pre-pandemic and unexposed seronegative subjects. However, seronegative doctors with high occupational exposure and recent COVID-19 compatible illness showed patterns of T cell responses characteristic of infection, indicating that these readouts are highly sensitive. By contrast, over 90% of convalescent or unexposed people showed proliferation and cellular lactate responses to spike subunits S1/S2, indicating pre-existing cross-reactive T cell populations. The detection of T cell responses to SARS-CoV-2 is therefore critically dependent on the choice of assay and antigen. Memory responses to specific non-spike proteins provides a method to distinguish recent infection from pre-existing immunity in exposed populations.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.09.26.20202150,2020-09-28,https://medrxiv.org/cgi/content/short/2020.09.26.20202150,Comparison of mental health service activity before and shortly after UK social distancing responses to the COVID-19 pandemic: February-March 2020,Robert Stewart; Evangelia Martin; Ioannis Bakolis; Matthew Broadbent; Nicola Byrne; Sabine Landau,King's College London; South London and Maudsley NHS Foundation Trust; King's College London; King's College London; South London and Maudsley NHS Foundation Trust; King's College London,"This study sought to provide an early description of mental health service activity before and after national implementation of social distancing for COVID-19. A time series analysis was carried out of daily service-level activity on data from a large mental healthcare provider in southeast London, from 01.02.2020 to 31.03.2020, comparing activity before and after 16.03.2020: i) inpatient admissions, discharges and numbers, ii) contact numbers and daily caseloads (Liaison, Home Treatment Teams, Community Mental Health Teams); iii) numbers of deaths for past and present patients. Daily face-to-face contact numbers fell for liaison, home treatment and community services with incomplete compensatory rises in non-face-to-face contacts. Daily caseloads fell for all services, apart from working age and child/adolescent community teams. Inpatient numbers fell 13.6% after 16th March, and daily numbers of deaths increased by 61.8%.",psychiatry and clinical psychology,exact,100,100 +medRxiv,10.1101/2020.09.24.20200048,2020-09-25,https://medrxiv.org/cgi/content/short/2020.09.24.20200048,Genetic mechanisms of critical illness in Covid-19,Erola Pairo-Castineira; Sara Clohisey; Lucija Klaric; Andrew Bretherick; Konrad Rawlik; Nicholas Parkinson; Dorota Pasko; Susan Walker; Anne Richmond; Max Head Fourman; Andy Law; James Furniss; Elvina Gountouna; Nicola Wrobel; Clark D Russell; Loukas Moutsianas; Bo Wang; Alison Meynert; Zhijian Yang; Ranran Zhai; Chenqing Zheng; Fiona Griffith; Wilna Oosthuyzen; Barbara Shih; Seán Keating; Marie Zechner; Chris Haley; David J Porteous; Caroline Hayward; Julian Knight; Charlotte Summers; Manu Shankar-Hari; Lance Turtle; Antonia Ho; Charles Hinds; Peter Horby; Alistair Nichol; David Maslove; Lowell Ling; Paul Klenerman; Danny McAuley; Hugh Montgomery; Timothy Walsh; - The GenOMICC Investigators; - The ISARIC4C Investigators; - The Covid-19 Human Genetics Initiative; Xia Shen; Kathy Rowan; Angie Fawkes; Lee Murphy; Chris P Ponting; Albert Tenesa; Mark Caulfield; Richard Scott; Peter JM Openshaw; Malcolm G Semple; Veronique Vitart; James F Wilson; J Kenneth Baillie,"Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; The Roslin Institute; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Genomics England; Genomics England; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; University of Edinburgh Centre for Inflammation Research, The Queen's Medical Research Institute, Edinburgh, UK; Genomics England; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.; Department of Medicine, University of Cambridge, Cambridge, UK.; Department of Intensive Care Medicine, Guy's and St. Thomas NHS Foundation Trust, London, UK; School of Immunology and Microbial Sciences, King's College London; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences University of Liverpool, L; MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, Univer; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7FZ, UK.; Clinical Research Centre at St Vincent's University Hospital, University College Dublin, Dublin, Ireland; Australian and New Zealand Intensive Care Research Cen; Department of Critical Care Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, ON, Canada.; Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.; University of Oxford; Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, Northern Ireland, UK; Department of Intensive Care Medicine, Royal Vi; UCL Centre for Human Health and Performance, London, W1T 7HA, UK.; Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK.; -; -; -; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.; Intensive Care National Audit & Research Centre, London, UK.; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Genomics England; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK; Genomics England; National Heart & Lung Institute, Imperial College London (St Mary's Campus), Norfolk Place, Paddington, London W2 1PG, UK.; University of Liverpool, Liverpool, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK; Ce; Roslin Institute, University of Edinburgh","The subset of patients who develop critical illness in Covid-19 have extensive inflammation affecting the lungs1 and are strikingly different from other patients: immunosuppressive therapy benefits critically-ill patients, but may harm some non-critical cases.2 Since susceptibility to life-threatening infections and immune-mediated diseases are both strongly heritable traits, we reasoned that host genetic variation may identify mechanistic targets for therapeutic development in Covid-19.3 + +GenOMICC (Genetics Of Mortality In Critical Care, genomicc.org) is a global collaborative study to understand the genetic basis of critical illness. Here we report the results of a genome-wide association study (GWAS) in 2244 critically-ill Covid-19 patients from 208 UK intensive care units (ICUs), representing >95% of all ICU beds. Ancestry-matched controls were drawn from the UK Biobank population study and results were confirmed in GWAS comparisons with two other population control groups: the 100,000 genomes project and Generation Scotland. + +We identify and replicate three novel genome-wide significant associations, at chr19p13.3 (rs2109069, p = 3.98 x 10-12), within the gene encoding dipeptidyl peptidase 9 (DPP9), at chr12q24.13 (rs10735079, p =1.65 x 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), and at chr21q22.1 (rs2236757, p = 4.99 x 10-8) in the interferon receptor gene IFNAR2. Consistent with our focus on extreme disease in younger patients with less comorbidity, we detect a stronger signal at the known 3p21.31 locus than previous studies (rs73064425, p = 4.77 x 10-30). + +We identify potential targets for repurposing of licensed medications. Using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease. Transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19. + +Our results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice.",intensive care and critical care medicine,exact,100,100 medRxiv,10.1101/2020.09.22.20198754,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.22.20198754,"Ethnic differences in COVID-19 infection, hospitalisation, and mortality: an OpenSAFELY analysis of 17 million adults in England",Rohini Mathur; Christopher T. Rentsch; Caroline Morton; William J Hulme; Anna Schultze; Brian MacKenna; Rosalind M Eggo; Krishnan Bhaskaran; Angel YS Wong; Elizabeth J Williamson; Harriet Forbes; Kevin Wing; Helen I McDonald; Chris Bates; Seb Bacon; Alex J Walker; David Evans; Peter Inglesby; Amir Mehrkar; Helen J Curtis; Nicholas J DeVito; Richard Croker; Henry Drysdale; Jonathan Cockburn; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Laurie Tomlinson; Stephen Evans; Richard Grieve; David Harrison; Kathy Rowan; Kamlesh Khunti; Nish Chaturvedi; Liam Smeeth; Ben Goldacre,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene & Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Medicine and Tropical Medicine; The Phoenix Partnership; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Intensive Care National Audit and Research Centre; Intensive Care National Audit and Research Centre; University of Leicester; University College London; London School of Hygiene and Tropical Medicine; University of Oxford,"Background: COVID-19 has had a disproportionate impact on ethnic minority populations, both in the UK and internationally. To date, much of the evidence has been derived from studies within single healthcare settings, mainly those hospitalised with COVID-19. Working on behalf of NHS England, the aim of this study was to identify ethnic differences in the risk of COVID-19 infection, hospitalisation and mortality using a large general population cohort in England. Methods: We conducted an observational cohort study using linked primary care records of 17.5 million adults between 1 February 2020 and 3 August 2020. Exposure was self-reported ethnicity collapsed into the 5 and 16 ethnicity categories of the English Census. Multivariable Cox proportional hazards regression was used to identify ethnic differences in the risk of being tested and testing positive for SARS-CoV-2 infection, COVID-19 related intensive care unit (ICU) admission, and COVID-19 mortality, adjusted for socio-demographic factors, clinical co-morbidities, geographic region, care home residency, and household size. Results: A total of 17,510,002 adults were included in the study; 63% white (n=11,030,673), 6% south Asian (n=1,034,337), 2% black (n=344,889), 2% other (n=324,730), 1% mixed (n=172,551), and 26% unknown (n=4,602,822). After adjusting for measured explanatory factors, south Asian, black, and mixed groups were marginally more likely to be tested (south Asian HR 1.08, 95%CI 1.07-1.09; black HR 1.08; 95%CI 1.06-1.09, mixed HR 1.03, 95%CI 1.01-1.05), and substantially more likely to test positive for SARS-CoV-2 compared with white adults (south Asian HR 2.02. 95% CI 1.97-2.07; black HR 1.68, 95%CI 1.61-1.76; mixed HR 1.46, 95%CI 1.36-1.56). The risk of being admitted to ICU for COVID-19 was substantially increased in all ethnic minority groups compared with white adults (south Asian HR 2.22, 95%CI 1.96-2.52; black HR 3.07, 95%CI 2.61-3.61; mixed HR 2.86, 95%CI 2.19-3.75, other HR 2.86, 95%CI 2.31-3.63). Risk of COVID-19 mortality was increased by 25-56% in ethnic minority groups compared with white adults (south Asian HR 1.27, 95%CI 1.17-1.38; black HR 1.55, 95%CI 1.38-1.75; mixed HR 1.40, 95%CI 1.12-1.76; other HR 1.25, 95%CI 1.05-1.49). We observed heterogeneity of associations after disaggregation into detailed ethnic groupings; Indian and African groups were at higher risk of all outcomes; Pakistani, Bangladeshi and Caribbean groups were less or equally likely to be tested for SARS-CoV-2, but at higher risk of all other outcomes, Chinese groups were less likely to be tested for and test positive for SARS-CoV-2, more likely to be admitted to ICU, and equally likely to die from COVID-19. Conclusions: We found evidence of substantial ethnic inequalities in the risk of testing positive for SARS-CoV-2, ICU admission, and mortality, which persisted after accounting for explanatory factors, including household size. It is likely that some of this excess risk is related to factors not captured in clinical records such as occupation, experiences of structural discrimination, or inequitable access to health and social services. Prioritizing linkage between health, social care, and employment data and engaging with ethnic minority communities to better understand their lived experiences is essential for generating evidence to prevent further widening of inequalities in a timely and actionable manner.",epidemiology,exact,100,100 medRxiv,10.1101/2020.09.21.20194019,2020-09-23,https://medrxiv.org/cgi/content/short/2020.09.21.20194019,Putting (Big) Data in Action: Saving Lives with Countrywide Population Movement Monitoring Using Mobile Devices during the COVID-19 Crisis,Miklos Karoly Szocska; Peter Pollner; Istvan Schiszler; Tamas Joo; Tamas Palicz; Martin McKee; - Magyar Telekom Nyrt.; - Telenor Magyarorszag Zrt.; Adam Sohonyai; Jozsef Szoke; Adam Toth; Peter Gaal,"Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team; University of London, London School of Hygiene and Tropical Medicine, Department of Health Services Research and Policy; ; ; Vodafone Hungary; Vodafone Hungary; Vodafone Hungary; Semmelweis University, Faculty of Health and Public Administration, Health Services Management Training Centre, Digital Health and Data Utilisation Team","Many countries have implemented strict social distancing measures in the hope of reducing transmission of SARS-CoV-2 but the effectiveness of these measures is determined by the willingness of populations to comply with restrictions. Consequently, a system of monitoring population movement using existing data sources can inform those making decisions about policy responses to the COVID-19 pandemic. We describe a collaboration with all 3 major domestic telecommunication companies in Hungary to use aggregated anonymous mobile phone usage data to calculate two indices for assessing the effect of movement restrictions: a ""mobility-index"" and a ""stay-at-home (or resting) index"". The strengths and weaknesses of this approach are compared with the smartphone-based, COVID-19 Community Mobility Reports from Google. Data generated by mobile phones have long been identified as a potential means to analyse mass population movement, but its operationalisation raises several technical questions, such as making sense of Call Detail Records, collation of data from different mobile network providers, and personal data protection concerns. The method described here addresses these issues and offers an effective and inexpensive tool to monitor the impact of social distancing measures, achieving high levels of accuracy and resolution. Especially in populations where uptake of smartphones is modest, this method has certain advantages over app-based solutions, with greater population coverage, but it is not an alternative to smartphone-based solutions used for contact tracing and quarantine monitoring. We believe that this method can easily be adapted by other countries.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.09.21.20196428,2020-09-22,https://medrxiv.org/cgi/content/short/2020.09.21.20196428,"Sharing a household with children and risk of COVID-19: a study of over 300,000 adults living in healthcare worker households in Scotland",Rachael Wood; Emma C Thomson; Robert Galbraith; Ciara Gribben; David Caldwell; Jennifer Bishop; Martin Reid; Anoop Shah; Kate Templeton; David Goldberg; Chris Robertson; Sharon Hutchinson; Helen M Colhoun; Paul M McKeigue; David McAllister,"University of Edinburgh, Public Heath Scotland; University of Glasgow; Retired; Public Health Scotland; Public Health Scotland; Public Health Scotland; Public Health Scotland; London School of Hygiene and Tropical Medicine; University of Edinburgh; Public Health Scotland; Public Health Scotland; Public Health Scotland; University of Edinburgh; University of Edinburgh; University of Glasgow","ObjectiveChildren are relatively protected from COVID-19, possibly due to cross-protective immunity. We investigated if contact with children also affords adults a degree of protection from COVID-19. @@ -2308,7 +2314,6 @@ There were no significant differences in non-COVID-related intensive care admiss ConclusionIn this large, single-centre study, there was a change in hospitalised case-mix when comparing April 2019 with April 2020: an increase in conditions which potentially reflect social isolation (falls, drug and alcohol misuse and psychiatric illness) and a decrease in conditions which rarely require in-patient hospital treatment (musculoskeletal pain and non-cardiac chest pain) especially among younger adults. These results highlight two areas for further research; the impact of social isolation on health and whether younger adults could be offered alternative health services to avoid potentially unnecessary hospital assessment.",emergency medicine,exact,100,100 medRxiv,10.1101/2020.09.12.20191973,2020-09-14,https://medrxiv.org/cgi/content/short/2020.09.12.20191973,Inequality in access to health and care services during lockdown - Findings from the COVID-19 survey in five UK national longitudinal studies,Constantin-Cristian Topriceanu; Andrew Wong; James C Moon; Alun Hughes; David Bann; Nishi Chaturvedi; Praveetha Patalay; Gabriella Conti; Gabriella Captur,University College London; UCL; UCL; UCL; University College London; UCL; University College London; UCL; University College London,"Background: Access to health services and adequate care is influenced by sex, ethnicity, socio-economic position (SEP) and burden of co-morbidities. However, it is unknown whether the COVID-19 pandemic further deepened these already existing health inequalities. Methods: Participants were from five longitudinal age-homogenous British cohorts (born in 2001, 1990, 1970, 1958 and 1946). A web and telephone-based survey provided data on cancelled surgical or medical appointments, and the number of care hours received during the UK COVID-19 national lockdown. Using binary or ordered logistic regression, we evaluated whether these outcomes differed by sex, ethnicity, SEP and having a chronic illness. Adjustment was made for study-design, non-response weights, psychological distress, presence of children or adolescents in the household, keyworker status, and whether participants had received a shielding letter. Meta-analyses were performed across the cohorts and meta-regression evaluated the effect of age as a moderator. Findings: 14891 participants were included. Females (OR 1.40, 95% confidence interval [1.27,1.55]) and those with a chronic illness (OR 1.84 [1.65-2.05]) experienced significantly more cancellations during lockdown (all p<0.0001). Ethnic minorities and those with a chronic illness required a higher number of care hours during the lockdown (both OR approx. 2.00, all p<0.002). Age was not independently associated with either outcome in meta-regression. SEP was not associated with cancellation or care hours. Interpretation: The UK government's lockdown approach during the COVID-19 pandemic appears to have deepened existing health inequalities, impacting predominantly females, ethnic-minorities and those with chronic illnesses. Public health authorities need to implement urgent policies to ensure equitable access to health and care for all in preparation for a second wave.",public and global health,exact,100,100 medRxiv,10.1101/2020.09.13.20193730,2020-09-14,https://medrxiv.org/cgi/content/short/2020.09.13.20193730,Mental health service activity during COVID-19 lockdown among individuals with Personality Disorders: South London and Maudsley data on services and mortality from January to May 2020,Eleanor Nuzum; Evangelia Martin; Matthew Broadbent; Robert Stewart,South London and Maudsley NHS Foundation Trust; South London and Maudsley NHS Foundation Trust; South London and Maudsley NHS Foundation Trust; King's College London,"The lockdown and social distancing policy imposed due to the COVID-19 pandemic is likely to have a widespread impact on mental healthcare for both services themselves and the people accessing those services. Previous reports from the South London and Maudsley NHS Trust (SLaM; a large mental health service provider for 1.2m residents in South London) highlighted a shift to virtual contacts among those accessing community mental health and home treatment teams and an increase in deaths over the pandemics first wave. However, there is a need to understand this further for specific groups, including those diagnosed with a personality disorder who might have particular vulnerabilities. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for individuals with personality disorders across community, specialist, crisis and inpatient services. The report focussed on the period 1st January to 31st May 2020. We also report on daily accepted and discharged trust referrals, total trust caseloads and daily inpatient admissions and discharges for individuals with personality disorders. In addition, daily deaths are described for all current and previous SLaM service users with personality disorder over this period. In summary, comparing periods before and after 16th March 2020 there was a shift from face-to-face contacts to virtual contacts across all teams. Liaison and Older Adult teams showed the largest drop in caseloads, whereas Early Intervention in Psychosis service caseloads remained the same. Reduced accepted referrals and inpatient admissions were observed and there was a 28% increase in average daily deaths in the period after 16th March, compared to the period 1st January to 15th March.",psychiatry and clinical psychology,exact,100,100 -medRxiv,10.1101/2020.09.10.20191841,2020-09-11,https://medrxiv.org/cgi/content/short/2020.09.10.20191841,The King's College London Coronavirus Health and Experiences of Colleagues at King's Study: SARS-CoV-2 antibody response in an occupational sample,Daniel Leightley; Valentina Vitiello; Gabriella Bergin-Cartwright; Alice Wickersham; Katrina A S Davis; Sharon Stevelink; Matthew Hotopf; Reza Razavi; - On behalf of the KCL CHECK research team,"Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London; ","We report test results for SARS-CoV-2 antibodies in an occupational group of postgraduate research students and current members of staff at Kings College London. Between June and July 2020, antibody testing kits were sent to n=2296 participants; n=2004 (86.3%) responded, of whom n=1882 (93.9%) returned valid test results. Of those that returned valid results, n=124 (6.6%) tested positive for SARS-CoV-2 antibodies, with initial comparisons showing variation by age group and clinical exposure.",epidemiology,exact,100,100 medRxiv,10.1101/2020.09.11.20192492,2020-09-11,https://medrxiv.org/cgi/content/short/2020.09.11.20192492,Resurgence of SARS-CoV-2 in England: detection by community antigen surveillance,Steven Riley; Kylie E. C. Ainslie; Oliver Eales; Caroline E Walters; Haowei Wang; Christina J Atchison; Claudio Fronterre; Peter J Diggle; Deborah Ashby; Christl A. Donnelly; Graham Cooke; Wendy Barclay; Helen Ward; Ara Darzi; Paul Elliott,"Dept Inf Dis Epi, Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Imperial College London; Lancaster University; Lancaster University; Imperial College London; Imperial College London; Imperial College; Imperial College London; Imperial College London; Imperial College London; Imperial College London","Background Based on cases and deaths, transmission of SARS-CoV-2 in England peaked in late March and early April 2020 and then declined until the end of June. Since the start of July, cases have increased, while deaths have continued to decrease. Methods We report results from 594,000 swabs tested for SARS-CoV-2 virus obtained from a representative sample of people in England over four rounds collected regardless of symptoms, starting in May 2020 and finishing at the beginning of September 2020. Swabs for the most recent two rounds were taken between 24th July and 11th August and for round 4 between 22nd August and 7th September. We estimate weighted overall prevalence, doubling times between and within rounds and associated reproduction numbers. We obtained unweighted prevalence estimates by sub-groups: age, sex, region, ethnicity, key worker status, household size, for which we also estimated odds of infection. We identified clusters of swab-positive participants who were closer, on average, to other swab-positive participants than would be expected. Findings Over all four rounds of the study, we found that 72% (67%, 76%) of swab-positive individuals were asymptomatic at the time of swab and in the week prior. The epidemic declined between rounds 1 and 2, and rounds 2 and 3. However, the epidemic was increasing between rounds 3 and 4, with a doubling time of 17 (13, 23) days corresponding to an R value of 1.3 (1.2, 1.4). When analysing round 3 alone, we found that the epidemic had started to grow again with 93% probability. Using only the most recent round 4 data, we estimated a doubling time of 7.7 (5.5, 12.7) days, corresponding to an R value of 1.7 (1.4, 2.0). Cycle threshold values were lower (viral loads were higher) for rounds 1 and 4 than they were for rounds 2 and 3. In round 4, we observed the highest prevalence in participants aged 18 to 24 years at 0.25% (0.16%, 0.41%), increasing from 0.08% (0.04%, 0.18%) in round 3. We observed the lowest prevalence in those aged 65 and older at 0.04% (0.02%, 0.06%) which was stable compared with round 3. Participants of Asian ethnicity had elevated odds of infection. We identified clusters in and around London, transient clusters in the Midlands, and an expanding area of clustering in the North West and more recently in Yorkshire and the Humber. Interpretation Although low levels of transmission persisted in England through to mid-summer 2020, the prevalence of SARS-CoV-2 is now increasing. We found evidence of accelerating transmission at the end of August and beginning of September. Representative community antigen sampling can increase situational awareness and help improve public health decision making even at low prevalence.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.09.04.20187781,2020-09-09,https://medrxiv.org/cgi/content/short/2020.09.04.20187781,Hydroxychloroquine for prevention of COVID-19 mortality: a population-based cohort study,Christopher T Rentsch; Nicholas J DeVito; Brian MacKenna; Caroline E Morton; Krishnan Bhaskaran; Jeremy P Brown; Anna Schultze; William J Hulme; Richard Croker; Alex J Walker; Elizabeth J Williamson; Chris Bates; Seb Bacon; Amir Mehrkar; Helen J Curtis; David Evans; Kevin Wing; Peter Inglesby; Rohini Mathur; Henry Drysdale; Angel YS Wong; Helen I McDonald; Jonathan Cockburn; Harriet Forbes; John Parry; Frank Hester; Sam Harper; Liam Smeeth; Ian J Douglas; William G Dixon; Stephen JW Evans; Laurie Tomlinson; Ben Goldacre,London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; The Phoenix Partnership; University of Oxford; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Medicine and Tropical Medicine; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; The Phoenix Partnership; The Phoenix Partnership; The Phoenix Partnership; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; The University of Manchester; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundHydroxychloroquine has been shown to inhibit severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in vitro, but early clinical studies found no benefit treating patients with coronavirus disease 2019 (COVID-19). We set out to evaluate the effectiveness of hydroxychloroquine for prevention, as opposed to treatment, of COVID-19 mortality. @@ -2430,26 +2435,6 @@ FindingsWe find a 0{middle dot}5% (95% credible interval: -0{middle dot}2%-1{mid InterpretationOur study provides some evidence of an effect of long-term NO2 exposure on COVID-19 mortality, while the effect of PM2{middle dot}5 remains more uncertain. FundingMedical Research Council, Wellcome Trust, Environmental Protection Agency and National Institutes of Health.",public and global health,exact,100,100 -medRxiv,10.1101/2020.08.10.20171033,2020-08-11,https://medrxiv.org/cgi/content/short/2020.08.10.20171033,Post-exertion oxygen saturation as a prognostic factor for adverse outcome in patients attending the emergency department with suspected COVID-19: Observational cohort study,Steve Goodacre; Ben Thomas; Ellen Lee; Laura Sutton; Katie Biggs; Carl Marincowitz; Amanda Loban; Simon Waterhouse; Richard Simmonds; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter,"University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust, Wythenshawe Hospital; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust","BackgroundMeasurement of post-exertion oxygen saturation has been proposed to assess illness severity in suspected COVID-19 infection. We aimed to determine the accuracy of post-exertional oxygen saturation for predicting adverse outcome in suspected COVID-19. - -MethodsWe undertook an observational cohort study across 70 emergency departments during first wave of the COVID-19 pandemic in the United Kingdom. We collected data prospectively, using a standardised assessment form, and retrospectively, using hospital records, from patients with suspected COVID-19, and reviewed hospital records at 30 days for adverse outcome (death or receiving organ support). Patients with post-exertion oxygen saturation recorded were selected for this analysis. - -ResultsWe analysed data from 817 patients with post-exertion oxygen saturation recorded after excluding 54 in whom measurement appeared unfeasible. The c-statistic for post-exertion change in oxygen saturation was 0.589 (95% confidence interval 0.465 to 0.713), and the positive and negative likelihood ratios of a 3% or more desaturation were respectively 1.78 (1.25 to 2.53) and 0.67 (0.46 to 0.98). Multivariable analysis showed that post-exertion oxygen saturation was not a significant predictor of adverse outcome when baseline clinical assessment was taken into account (p=0.368). Secondary analysis excluding patients in whom post-exertion measurement appeared inappropriate resulted in a c-statistic of 0.699 (0.581 to 0.817), likelihood ratios of 1.98 (1.26 to 3.10) and 0.61 (0.35 to 1.07), and some evidence of additional prognostic value on multivariable analysis (p=0.019). - -ConclusionsPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19. - -RegistrationISRCTN registry, ISRCTN56149622, http://www.isrctn.com/ISRCTN28342533 - -Key messagesWhat is already known on this subject? - -O_LIPost exertional decrease in oxygen saturation can be used to predict prognosis in chronic lung diseases -C_LIO_LIPost exertional desaturation has been proposed as a way of predicting adverse outcome in people with suspected COVID-19 -C_LI - -What this study adds: - -O_LIPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19 -C_LI",emergency medicine,exact,100,100 medRxiv,10.1101/2020.08.07.20169490,2020-08-07,https://medrxiv.org/cgi/content/short/2020.08.07.20169490,HIV infection and COVID-19 death: population-based cohort analysis of UK primary care data and linked national death registrations within the OpenSAFELY platform,Krishnan Bhaskaran; Christopher T Rentsch; Brian MacKenna; Anna Schultz; Amir Mehrkar; Chris Bates; Rosalind M Eggo; Caroline E Morton; Seb Bacon; Peter Inglesby; Ian J Douglas; Alex J Walker; Helen I McDonald; Jonathan Cockburn; Elizabeth J Williamson; David Evans; Harriet J Forbes; Helen J Curtis; William Hulme; John Parry; Frank Hester; Sam Harper; Stephen JW Evans; Liam Smeeth; Ben Goldacre,London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; TPP; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford,"BackgroundIt is unclear whether HIV infection is associated with risk of COVID-19 death. We aimed to investigate this in a large-scale population-based study in England. MethodsWorking on behalf of NHS England, we used the OpenSAFELY platform to analyse routinely collected electronic primary care data linked to national death registrations. People with a primary care record for HIV infection were compared to people without HIV. COVID-19 death was defined by ICD-10 codes U07.1 or U07.2 anywhere on the death certificate. Cox regression models were used to estimate the association between HIV infection and COVID-19 death, initially adjusted for age and sex, then adding adjustment for index of multiple deprivation and ethnicity, and finally for a broad range of comorbidities. Interaction terms were added to assess effect modification by age, sex, ethnicity, comorbidities and calendar time. @@ -2684,7 +2669,6 @@ InterpretationThese results do not support a major role of ICS in protecting aga FundingThis work was supported by the Medical Research Council MR/V015737/1.",respiratory medicine,exact,100,100 medRxiv,10.1101/2020.06.17.20133959,2020-06-20,https://medrxiv.org/cgi/content/short/2020.06.17.20133959,A downscaling approach to compare COVID-19 count data from databases aggregated at different spatial scales,Andre Python; Andreas Bender; Marta Blangiardo; Janine B Illian; Ying Lin; Baoli Liu; Tim C D Lucas; Siwei Tan; Yingying Wen; Davit Svanidze; Jianwei Yin,University of Oxford; LMU Munich; Imperial College London; Glasgow University; Fuzhou University; Oxford University; University of Oxford; Zhejiang University; Zhejiang University; Goettingen University; Zhejiang University,"As the COVID-19 pandemic continues to threaten various regions around the world, obtaining accurate and reliable COVID-19 data is crucial for governments and local communities aiming at rigorously assessing the extent and magnitude of the virus spread and deploying efficient interventions. Using data reported between January and February 2020 in China, we compared counts of COVID-19 from near-real time spatially disaggregated data (city-level) with fine-spatial scale predictions from a Bayesian downscaling regression model applied to a reference province-level dataset. The results highlight discrepancies in the counts of coronavirus-infected cases at district level and identify districts that may require further investigation.",epidemiology,exact,100,100 -medRxiv,10.1101/2020.06.13.20130419,2020-06-16,https://medrxiv.org/cgi/content/short/2020.06.13.20130419,Mental health service activity during COVID-19 lockdown: South London and Maudsley data on working age community and home treatment team services and mortality from February to mid-May 2020,Robert Stewart; Evangelia Martin; Matthew Broadbent,King's College London; King's College London; South London and Maudsley NHS Foundation Trust,"The lockdown and social distancing policy response to the COVID-19 pandemic in the UK has a potentially important impact on provision of mental healthcare; however, there has been relatively little quantification of this. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for home treatment teams (HTTs) and working age adult community mental health teams (CMHTs) from 1st February to 15th May 2020 at the South London and Maudsley NHS Trust (SLaM), a large mental health service provider for 1.2m residents in south London. In addition daily deaths are described for all current and previous SLaM service users over this period and the same dates in 2019. In summary, comparing periods before and after 16th March 2020 the CMHT sector showed relatively stable caseloads and total contact numbers, but a substantial shift from face-to-face to virtual contacts, while HTTs showed the same changeover but reductions in caseloads and total contacts (although potentially an activity rise again during May). Number of deaths for the two months between 16th March and 15th May were 2.4-fold higher in 2020 than 2019, with 958 excess deaths.",psychiatry and clinical psychology,exact,100,100 medRxiv,10.1101/2020.06.12.20129494,2020-06-14,https://medrxiv.org/cgi/content/short/2020.06.12.20129494,Impact on mental health care and on mental health service users of the COVID-19 pandemic: a mixed methods survey of UK mental health care staff,Sonia Johnson; Christian Dalton-Locke; Norha Vera San Juan; Una Foye; Sian Oram; Alexandra Papamichail; Sabine Landau; Rachel Rowan Olive; Tamar Jeynes; Prisha Shah; Luke Sheridan Rains; Brynmor Lloyd-Evans; Sarah Carr; Helen Killaspy; Steve Gillard; Alan Simpson; - The COVID-19 Mental Health Policy Research Unit Group,"NIHR Mental Health Policy Research Unit, Division of Psychiatry, University College London, London, UK; NIHR Mental Health Policy Research Unit, Division of Psychiatry, University College London, London, UK; NIHR Mental Health Policy Research Unit, Institute of Psychiatry, Psychology & Neuroscience, King s College London, London, UK; NIHR Mental Health Policy Research Unit, Institute of Psychiatry, Psychology & Neuroscience, King s College London, London, UK; NIHR Mental Health Policy Research Unit, Institute of Psychiatry, Psychology & Neuroscience, King s College London, London, UK; NIHR Mental Health Policy Research Unit, Institute of Psychiatry, Psychology & Neuroscience, King s College London, London, UK; NIHR Mental Health Policy Research Unit, Institute of Psychiatry, Psychology & Neuroscience, King s College London, London, UK; Division of Psychiatry (NIHR Mental Health Policy Research Unit COVID-19 Co-Production Group), University College London, London, UK; Division of Psychiatry (NIHR Mental Health Policy Research Unit COVID-19 Co-Production Group), University College London, London, UK; Division of Psychiatry (NIHR Mental Health Policy Research Unit COVID-19 Co-Production Group), University College London, London, UK; NIHR Mental Health Policy Research Unit, Division of Psychiatry, University College London, London, UK; NIHR Mental Health Policy Research Unit, Division of Psychiatry, University College London, London, UK; School of Social Policy/ Institute for Mental Health, University of Birmingham, Birmingham, UK; 1. NIHR Mental Health Policy Research Unit, Division of Psychiatry, University College London, London, UK; Population Health Research Institute, St George s, University of London, London, UK; NIHR Mental Health Policy Research Unit, Institute of Psychiatry, Psychology & Neuroscience, King s College London, London, UK; ","PurposeThe COVID-19 pandemic has potential to disrupt and burden the mental health care system, and to magnify inequalities experienced by mental health service users. MethodsWe investigated staff reports regarding the impact of the COVID-19 pandemic in its early weeks on mental health care and mental health service users in the UK using a mixed methods online survey. Recruitment channels included professional associations and networks, charities and social media. Quantitative findings were reported with descriptive statistics, and content analysis conducted for qualitative data. @@ -2721,19 +2705,6 @@ Main outcome measuresAll-cause mortality weekly rates for each municipality, bas ResultsThere was strong evidence of excess mortality for Northern Italy; Lombardia showed higher mortality rates than expected from the end of February, with 23,946 (23,013 to 24,786) total excess deaths. North-West and North-East regions showed higher mortality from the beginning of March, with 6,942 (6,142 to 7,667) and 8,033 (7,061 to 9,044) total excess deaths respectively. After discounting for the number of COVID-19-confirmed deaths, Lombardia still registered 10,197 (9,264 to 11,037) excess deaths, while regions in the North-West and North-East had 2,572 (1,772 to 3,297) and 2,047 (1,075 to 3,058) extra deaths, respectively. We observed marked geographical differences at municipality level. The city of Bergamo (Lombardia) showed the largest percent excess 88.9% (81.9% to 95.2%) at the peak of the pandemic. An excess of 84.2% (73.8% to 93.4%) was also estimated at the same time for the city of Pesaro (Central Italy), in stark contrast with the rest of the region, which does not show evidence of excess deaths. ConclusionsOur study gives a comprehensive picture of the evolution of all-cause mortality in Italy from 2016 to 2020 and describes the spatio-temporal differences in excess mortality during the COVID-19 pandemic. Our model shows heterogeneous impact of COVID-19, and it can be used to help policy- makers target measures to limit the burden on the health-care system as well as reducing social and economic consequences. Our probabilistic methodology is useful for real-time mortality surveillance, continuously monitoring local temporal trends and flagging where and when mortality rates deviate from the expected range, which might suggest a second wave of the pandemic.",public and global health,exact,100,100 -medRxiv,10.1101/2020.06.02.20120642,2020-06-05,https://medrxiv.org/cgi/content/short/2020.06.02.20120642,Estimating excess visual loss in people with neovascular age-related macular degeneration during the COVID-19 pandemic,Darren S Thomas; Alasdair Warwick; Abraham Olvera-Barrios; Catherine Egan; Roy Schwartz; Sudeshna Patra; Haralabos Eleftheriadis; Anthony P Khawaja; Andrew Lotery; Philipp L Mueller; Robin Hamilton; Ella Preston; Paul Taylor; Adnan Tufail; - UK EMR Users Group,"Institute of Health Informatics, University College London, London, UK; Institute of Cardiovascular Science, University College London, London, UK & Moorfields Eye Hospital NHS Foundation Trust, London, UK.; Moorfields Eye Hospital NHS Turst & Institute of Ophthalmology UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Health Informatics, University College London, London, UK; Bart's Health NHS Trust, London, UK; King's College Hospital NHS Trust, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Faculty of Medicine, University of Southampton, Southampton, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK; Institute of Health Informatics, University College London, London, UK; Moorfields Eye Hospital NHS Trust & Institute of Ophthalmology UCL; ","ObjectivesTo report the reduction in new neovascular age-related macular degeneration (nAMD) referrals during the COVID-19 pandemic and estimate the impact of delayed treatment on visual outcomes at one year. - -DesignRetrospective clinical audit and simulation model. - -SettingMultiple UK NHS ophthalmology centres. - -ParticipantsData on the reduction in new nAMD referrals was obtained from four NHS Trusts in England comparing April 2020 to April 2019. To estimate the potential impact on one-year visual outcomes, a stratified bootstrap simulation model was developed drawing on an electronic medical records dataset of 20,825 nAMD eyes from 27 NHS Trusts. - -Main outcome measuresSimulated mean visual acuity and proportions of eyes with vision [≤]6/60, [≤]6/24 and [≥]6/12 at one year under four hypothetical scenarios: no treatment delay, 3, 6 and 9-month treatment delays. Estimated additional number of eyes with vision [≤]6/60 at one year nationally. - -ResultsThe number of nAMD referrals at four major eye treatment hospital groups based in England dropped on average by 72% (range 65 to 87%) in April 2020 compared to April 2019. Simulated one-year visual outcomes for 1000 nAMD eyes with a 3-month treatment delay suggested an increase in the proportion of eyes with vision [≤]6/60 from 15.5% (13.2 to 17.9) to 23.3% (20.7 to25.9), and a decrease in the proportion of eyes with vision [≥]6/12 (driving vision) from 35.1% (32.1 to 38.1) to 26.4% (23.8 to29.2). Outcomes worsened incrementally with longer modelled delays. Assuming nAMD referrals are reduced to this level at the national level for only one month, these simulated results suggest an additional 186-365 eyes with vision [≤]6/60 at one-year with even a short treatment delay. - -ConclusionsWe report a large decrease in nAMD referrals during the first month of COVID-19 lockdown and provide an important public health message regarding the risk of delayed treatment. As a conservative estimate, a treatment delay of 3 months could lead to a >50% relative increase in the number of eyes with vision [≤]6/60 and 25% relative decrease in the number of eyes with driving vision at one year.",ophthalmology,exact,100,100 medRxiv,10.1101/2020.06.01.20116608,2020-06-03,https://medrxiv.org/cgi/content/short/2020.06.01.20116608,Is death from Covid-19 a multistep process?,Neil Pearce; Giovenale Moirano; Milena Maule; Manolis Kogevinas; Xavier Rodo; Deborah Lawlor; Jan Vandenbroucke; Christina Vandenbroucke-Grauls; Fernando P Polack; Adnan Custovic,"London School of Hygiene and Tropical Medicine; University of Turin, Italy; University of Turin, Italy; ISGlobal; ISGlobal; University of Bristol; Leiden University Medical Center; Amsterdam UMC; Vanderbilt Unversity; Imperial College London","Covid-19 death has a different relationship with age than is the case for other severe respiratory pathogens. The Covid-19 death rate increases exponentially with age, and the main risk factors are age itself, as well as having underlying conditions such as hypertension, diabetes, cardiovascular disease, severe chronic respiratory disease and cancer. Furthermore, the almost complete lack of deaths in children suggests that infection alone is not sufficient to cause death; rather, one must have gone through a number of changes, either as a result of undefined aspects of aging, or as a result of chronic disease. These characteristics of Covid-19 death are consistent with the multistep model of disease, a model which has primarily been used for cancer, and more recently for amyotrophic lateral sclerosis (ALS). We applied the multi-step model to data on Covid-19 case fatality rates (CFRs) from China, South Korea, Italy, Spain and Japan. In all countries we found that a plot of ln (CFR) against ln (age) was approximately linear with a slope of about 5. As a comparison, we also conducted similar analyses for selected other respiratory diseases. SARS showed a similar log-log age-pattern to that of Covid-19, albeit with a lower slope, whereas seasonal and pandemic influenza showed quite different age-patterns. Thus, death from Covid-19 and SARS appears to follow a distinct age-pattern, consistent with a multistep model of disease that in the case of Covid-19 is probably defined by comorbidities and age producing immune-related susceptibility. Identification of these steps would be potentially important for prevention and therapy for SARS-COV-2 infection.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.05.27.20083287,2020-06-01,https://medrxiv.org/cgi/content/short/2020.05.27.20083287,Estimating excess mortality in people with cancer and multimorbidity in the COVID-19 emergency,Alvina G Lai; Laura Pasea; Amitava Banerjee; Spiros Denaxas; Michail Katsoulis; Wai Hoong Chang; Bryan Williams; Deenan Pillay; Mahdad Noursadeghi; David Linch; Derralynn Hughes; Martin D Forster; Clare Turnbull; Natalie K Fitzpatrick; Kathryn Boyd; Graham R Foster; Matt Cooper; Monica Jones; Kathy Pritchard-Jones; Richard Sullivan; Geoff Hall; Charlie Davie; Mark Lawler; Harry Hemingway,"University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; Royal Free NHS Foundation Trust; University College London; Institute of Cancer Research; University College London; Northern Ireland Cancer Network; Queen Mary University of London; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; Kings College London; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; DATA-CAN, Health Data Research UK hub for cancer hosted by UCLPartners; University College London","BackgroundCancer and multiple non-cancer conditions are considered by the Centers for Disease Control and Prevention (CDC) as high risk conditions in the COVID-19 emergency. Professional societies have recommended changes in cancer service provision to minimize COVID-19 risks to cancer patients and health care workers. However, we do not know the extent to which cancer patients, in whom multi-morbidity is common, may be at higher overall risk of mortality as a net result of multiple factors including COVID-19 infection, changes in health services, and socioeconomic factors. @@ -2742,6 +2713,13 @@ MethodsWe report multi-center, weekly cancer diagnostic referrals and chemothera ResultsWeekly data until April 2020 demonstrate significant falls in admissions for chemotherapy (45-66% reduction) and urgent referrals for early cancer diagnosis (70-89% reduction), compared to pre-emergency levels. Under conservative assumptions of the emergency affecting only people with newly diagnosed cancer (incident cases) at COVID-19 PAE of 40%, and an RIE of 1.5, the model estimated 6,270 excess deaths at 1 year in England and 33,890 excess deaths in the US. In England, the proportion of patients with incident cancer with [≥]1 comorbidity was 65.2%. The number of comorbidities was strongly associated with cancer mortality risk. Across a range of model assumptions, and across incident and prevalent cancer cases, 78% of excess deaths occur in cancer patients with Harry [≥]1 comorbidity. ConclusionWe provide the first estimates of potential excess mortality among people with cancer and multimorbidity due to the COVID-19 emergency and demonstrate dramatic changes in cancer services. To better inform prioritization of cancer care and guide policy change, there is an urgent need for weekly data on cause-specific excess mortality, cancer diagnosis and treatment provision and better intelligence on the use of effective treatments for comorbidities.",oncology,exact,100,100 +medRxiv,10.1101/2020.05.19.20106641,2020-05-26,https://medrxiv.org/cgi/content/short/2020.05.19.20106641,Study Data Element Mapping: Feasibility of Defining Common Data Elements Across COVID-19 Studies,Priscilla Mathewson; Ben Gordon; Kay Snowley; Clara Fennessy; Alastair Denniston; Neil Sebire,University of Birmingham; HDRUK; HDRUK; HDRUK; HDRUK; Great Ormond Street Hospital and ICH London,"BackgroundNumerous clinical studies are now underway investigating aspects of COVID-19. The aim of this study was to identify a selection of national and/or multicentre clinical COVID-19 studies in the United Kingdom to examine the feasibility and outcomes of documenting the most frequent data elements common across studies to rapidly inform future study design and demonstrate proof-of-concept for further subject-specific study data element mapping to improve research data management. + +Methods25 COVID-19 studies were included. For each, information regarding the specific data elements being collected was recorded. Data elements collated were arbitrarily divided into categories for ease of visualisation. Elements which were most frequently and consistently recorded across studies are presented in relation to their relative commonality. + +ResultsAcross the 25 studies, 261 data elements were recorded in total. The most frequently recorded 100 data elements were identified across all studies and are presented with relative frequencies. Categories with the largest numbers of common elements included demographics, admission criteria, medical history and investigations. Mortality and need for specific respiratory support were the most common outcome measures, but with specific studies including a range of other outcome measures. + +ConclusionThe findings of this study have demonstrated that it is feasible to collate specific data elements recorded across a range of studies investigating a specific clinical condition in order to identify those elements which are most common among studies. These data may be of value for those establishing new studies and to allow researchers to rapidly identify studies collecting data of potential use hence minimising duplication and increasing data re-use and interoperability",health informatics,exact,100,100 medRxiv,10.1101/2020.05.20.20108126,2020-05-24,https://medrxiv.org/cgi/content/short/2020.05.20.20108126,Susceptibility to and transmission of COVID-19 amongst children and adolescents compared with adults: a systematic review and meta-analysis,Russell M Viner; Oliver T Mytton; Chris Bonell; G.J. Melendez-Torres; Joseph L Ward; Lee Hudson; Claire Waddington; James Thomas; Simon Russell; Fiona van der Klis; Archana Koiral; Shamez Ladhani; Jasmina Panovska-Griffiths; Nicholas G Davies; Robert Booy; Rosalind Eggo,"UCL Great Ormond St. Institute of Child Health; University of Cambridge; London School of Hygiene and Tropical Medicine; College of Medicine and Health, University of Exeter, UK; UCL Great Ormond St. Institute of Child Health; UCL Great Ormond St. Institute of Child Health; Addenbrookes Hospital, Cambridge; UCL Institute of Education; UCL Great Ormond St. Institute of Child Health; National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands; University of Sydney; Public Health England; UCL; London School of Hygiene and Tropical Medicine; University of Sydney; London School of Hygiene and Tropical Medicine","ImportanceThe degree to which children and young people are infected by and transmit the SARS-CoV-2 virus is unclear. The role of children and young people in transmission of SARS-CoV-2 is dependent on susceptibility, symptoms, viral load, social contact patterns and behaviour. ObjectiveWe undertook a rapid systematic review to address the question ""What is the susceptibility to and transmission of SARS-CoV-2 by children and adolescents compared with adults?"" @@ -2772,17 +2750,6 @@ FindingsWe screened 270 studies and included 6. The pooled estimate for the asym InterpretationThe asymptomatic proportion of SARS-CoV-2 infections is relatively low when estimated from methodologically-appropriate studies. Further investigation into the degree and duration of infectiousness for asymptomatic infections is warranted. FundingMedical Research Council",infectious diseases,exact,100,100 -medRxiv,10.1101/2020.05.18.20086157,2020-05-22,https://medrxiv.org/cgi/content/short/2020.05.18.20086157,COVID-19 in Great Britain: epidemiological and clinical characteristics of the first few hundred (FF100) cases: a descriptive case series and case control analysis,Nicola L Boddington; Andre Charlett; Suzanne Elgohari; Jemma L Walker; Helen Mcdonald; Chloe Byers; Laura Coughlan; Tatiana Garcia Vilaplana; Rosie Whillock; Mary Sinnathamby; Nikolaos Panagiotopoulos; Louise Letley; Pauline MacDonald; Roberto Vivancos; Obaghe Edeghere; Joseph Shingleton; Emma Bennett; Daniel J Grint; Helen Strongman; Kathryn E Mansfield; Christopher Rentsch; Caroline Minassian; Ian J Douglas; Rohini Mathur; Maria Peppa; Simon Cottrell; Jim McMenamin; Maria Zambon; Mary Ramsay; Gavin Dabrera; Vanessa Saliba; Jamie Lopez Bernal,Public Health England; Public Health England; Public Health England; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Public Health Wales; Public Health Scotland; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England,"ObjectivesFollowing detection of the first virologically-confirmed cases of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and underlying health conditions associated with infection of the first few hundred cases. - -MethodsInformation was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity, specificity and predictive value of symptoms and underlying health conditions associated with infection were conducted. Point prevalences of underlying health conditions among the UK general population were presented. - -FindingsThe majority of FF100 cases were imported (51.4%), of which the majority had recent travel to Italy (71.4%). 24.7% were secondary cases acquired mainly through household contact (40.4%). Children had lower odds of COVID-19 infection compared with the general population. - -The clinical presentation of cases was dominated by cough, fever and fatigue. Non-linear relationships with age were observed for fever, and sensitivity and specificity of symptoms varied by age. - -Conditions associated with higher odds of COVID-19 infection (after adjusting for age and sex) were chronic heart disease, immunosuppression and multimorbidity. - -ConclusionThis study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study characterized underlying health conditions associated with infection and set relative risks in context with population prevalence estimates. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms.",epidemiology,exact,100,100 medRxiv,10.1101/2020.05.11.20098269,2020-05-18,https://medrxiv.org/cgi/content/short/2020.05.11.20098269,Accessibility and allocation of public parks and gardens during COVID-19 social distancing in England and Wales,Niloofar Shoari; Majid Ezzati; Jill Baumgartner; Diego Malacarne; Daniela Fecht,Imperial College London; Imperial College London; McGill University; Imperial College London; Imperial College London,"Visiting parks and gardens may attenuate the adverse physical and mental health impacts of social distancing implemented to reduce the spread of COVID-19. We quantified access to public parks and gardens in urban areas of England and Wales, and the potential for park crowdedness during periods of high use. We combined data from the Office for National Statistics and Ordnance Survey to quantify (i) the number of parks within 500 and 1,000 metres of urban postcodes (i.e., availability), (ii) the distance of postcodes to the nearest park (i.e., accessibility), and (iii) per-capita space in each park for people living within 1,000m. We examined how these measures vary by city and share of homes that are flats. Around 25.4 million people can access public parks or gardens within a ten-minute walk, while 3.8 million residents live farther away; of these 21% are children and 13% are elderly. Areas with a higher share of flats on average are closer to a park but people living in these areas are potentially less able to meet social distancing requirements while in parks during periods of high use. Cities in England and Wales can provide residents with access to green space that enables outdoor exercise and play during social distancing. Cities aiming to facilitate social distancing while keeping public green spaces open might require implementing measures such as dedicated park times for different age groups or entry allocation systems that, combined with smartphone apps or drones, can monitor and manage the total number of people using the park.",public and global health,exact,100,100 medRxiv,10.1101/2020.05.08.20095687,2020-05-14,https://medrxiv.org/cgi/content/short/2020.05.08.20095687,Rapid implementation of real-time SARS-CoV-2 sequencing to investigate healthcare-associated COVID-19 infections,Luke W Meredith; William L Hamilton; Ben Warne; Charlotte J Houldcroft; Myra Hosmillo; Aminu Jahun; Martin D Curran; Surendra Parmar; Laura Caller; Sarah L Caddy; Fahad A Khokhar; Anna Yakovleva; Grant R Hall; Theresa Feltwell; Sally N Forret; Sushmita Sridhar; Michael p Weekes; Stephen Baker; Nicholas Brown; Elinor Moore; Theodore Gouliouris; Ashley Popay; Iain Roddick; Mark Reacher; Sharon Peacock; Gordon Dougan; M. Estee Torok; Ian Goodfellow,University of Cambridge; University of Cambridge; Cambridge University Hospitals NHS Foundation Trust; University of Cambridge; University of Cambridge; University of Cambridge; Public Health England; Public Health England; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge; Cambridge University; Cambridge University; Public Health England; Cambridge University Hospitals NHS Foundation Trust; Cambridge University Hospitals NHS Foundation Trust; Public Health England; Public Health England; Public Health England; University of Cambridge; University of Cambridge; University of Cambridge; University of Cambridge,"BackgroundThe burden and impact of healthcare-associated COVID-19 infections is unknown. We aimed to examine the utility of rapid sequencing of SARS-CoV-2 combined with detailed epidemiological analysis to investigate healthcare-associated COVID-19 infections and to inform infection control measures. @@ -2905,6 +2872,11 @@ MethodsWe constructed a simple stochastic model to determine clinical academic c FindingsIn ""Italy model"", ""mitigation"", ""relaxed mitigation"" and ""do-nothing"" scenarios, from 5 March 2020 the duration (days) and peak infection rates (%) are 95(2.4%), 115(2.5%), 240(5.3%) and 240(16.7%) respectively. Near complete attrition of academia (87% reduction, <400 clinical academics) occurs 35 days after pandemic start for 11, 34, 62, 76 days respectively - with no clinical academics at all for 37 days in the ""do-nothing"" scenario. Restoration of normal academic workforce (80% of normal capacity) takes 11,12, 30 and 26 weeks respectively. InterpretationPandemic COVID-19 crushes the science needed at system level. National policies mitigate, but the academic community needs to adapt. We highlight six key strategies: radical prioritisation (eg 3-4 research ideas per institution), deep resourcing, non-standard leadership (repurposing of key non-frontline teams), rationalisation (profoundly simple approaches), careful site selection (eg protected sites with large academic backup) and complete suspension of academic competition with collaborative approaches.",health systems and quality improvement,exact,100,100 +medRxiv,10.1101/2020.04.09.20059865,2020-04-14,https://medrxiv.org/cgi/content/short/2020.04.09.20059865,Forecasting the scale of the COVID-19 epidemic in Kenya,Samuel P C Brand; Rabia Aziza; Ivy K Kombe; Charles N Agoti; Joe Hilton; Kat S Rock; Andrea Parisi; D James Nokes; Matt Keeling; Edwine Barasa,"University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme; Kenya Medical Research Institute, Wellcome Trust Research Programme; University of Warwick; University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme and University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme","BackgroundThe first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya. + +MethodsWe developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak. + +ResultsWe find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 -2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.",infectious diseases,exact,100,100 medRxiv,10.1101/2020.04.10.20059121,2020-04-14,https://medrxiv.org/cgi/content/short/2020.04.10.20059121,"ACE inhibition and cardiometabolic risk factors, lung ACE2 and TMPRSS2 gene expression, and plasma ACE2 levels: a Mendelian randomization study",Dipender Gill; Marios Arvanitis; Paul Carter; Ana I Hernandez Cordero; Brian Jo; Ville Karhunen; Susanna C Larsson; Xuan Li; Sam M Lockhart; Amy M Mason; Evanthia Pashos; Ashis Saha; Vanessa Tan; Verena Zuber; Yohan Bosse; Sarah Fahle; Ke Hao; Tao Jiang; Philippe Joubert; Alan C Lunt; Willem hendrik Ouwehand; David J Roberts; Wim Timens; Maarten van den Berge; Nicholas A Watkins; Alexis Battle; Adam S Butterworth; John Danesh; Barbara E Engelhard; James E Peters; Don Sin; Stephen Burgess,"Imperial College London; Johns Hopkins University; University of Cambridge; The University of British Columbia Center for Heart Lung Innovation; Lewis Sigler Institute for Integrative Biology; Imperial College London; Karolinska Institutet; The University of British Columbia Center for Heart Lung Innovation; University of Cambridge; University of Cambridge; Pfizer; Johns Hopkins University; University of Bristol; Imperial College London; Laval University, Quebec; University of Cambridge; School of Medicine at Mount Sinai; University of Cambridge; Laval University, Quebec; Imperial College London; University of Cambridge; University of Oxford; University of Groningen; University of Groningen; University of Cambridge; Johns Hopkins University; University of Cambridge; University of Cambridge; Princeton University; Imperial College London; University of British Columbia; University of Cambridge","ObjectivesTo use human genetic variants that proxy angiotensin-converting enzyme (ACE) inhibitor drug effects and cardiovascular risk factors to provide insight into how these exposures affect lung ACE2 and TMPRSS2 gene expression and circulating ACE2 levels. DesignTwo-sample Mendelian randomization (MR) analysis. diff --git a/data/covid/preprints.exact.json b/data/covid/preprints.exact.json index 93b35106..a746ab72 100644 --- a/data/covid/preprints.exact.json +++ b/data/covid/preprints.exact.json @@ -55,20 +55,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2023.12.07.23299429", - "date": "2023-12-09", - "link": "https://medrxiv.org/cgi/content/short/2023.12.07.23299429", - "title": "Mechanisms underlying exercise intolerance in Long COVID: an accumulation of multi-system dysfunction", - "authors": "Alexandra Jamieson; Lamia Al Saikhan; Lamis Alghamdi; Lee Hamill Howes; Helen Purcell; Toby Hillman; Melissa J Heightman; Thomas A. Treibel; Michele Orini; Robert Midgley Bell; Marie Scully; Mark Hamer; Nishi Chaturvedi; Alun Hughes; Ronan Astin; Siana Jones", - "affiliations": "University College London; Imam Abdulrahman Bin Faisal University; University College London; University College London; University College London Hospitals NHS Foundation Trust; University College London Hospitals NHS Foundation Trust; UCLH; University College London; University College London; The Hatter Cardiovascular Institute, University College London; University College London Hospitals NHS Foundation Trust; UCL; University College London; UCL; University College London Hospitals NHS Foundation Trust; University College London", - "abstract": "The pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood.\n\nCases were recruited from a Long COVID clinic (N=32; 44{+/-}12y; 10(31%)men), and age/sex- matched healthy controls (HC) (N=19; 40{+/-}13y; 6(32%)men) from University College London staff and students. We assessed exercise performance, lung and cardiac function, vascular health, skeletal muscle oxidative capacity and autonomic nervous system (ANS) function. Key outcome measures for each physiological system were compared between groups using potential outcome means(95% confidence intervals) adjusted for potential confounders. Long COVID participant outcomes were compared to normative values.\n\nWhen compared to HC, cases exhibited reduced Oxygen Uptake Efficiency Slope (1847(1679,2016) vs (2176(1978,2373) ml/min, p=0.002) and Anaerobic Threshold (13.2(12.2,14.3) vs 15.6(14.4,17.2) ml/Kg/min, p<0.001), and lower oxidative capacity on near infrared spectroscopy ({tau}: 38.7(31.9,45.6) vs 24.6(19.1,30.1) seconds, p=0.001). In cases, ANS measures fell below normal limits in 39%.\n\nLong COVID is associated with reduced measures of exercise performance and skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology. There was evidence of attendant ANS dysregulation in a significant proportion. These multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers.\n\nKey PointsO_LIThe pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood.\nC_LIO_LIWe show that Long COVID is associated with reduced measures of exercise performance in line with previous work.\nC_LIO_LIIn Long COVID cases, we observed reduced skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology.\nC_LIO_LIWe also observed evidence of attendant autonomic nervous system (ANS) dysregulation in a significant proportion of Long COVID cases.\nC_LIO_LIThese multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers.\nC_LI", - "category": "cardiovascular medicine", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2023.12.06.23299601", @@ -251,6 +237,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2023.06.30.23292079", + "date": "2023-06-30", + "link": "https://medrxiv.org/cgi/content/short/2023.06.30.23292079", + "title": "Synthesis and new evidence from the PROTECT UK National Core Study: Determining occupational risks of SARS-CoV-2 infection and COVID-19 mortality", + "authors": "Sarah Rhodes; Sarah Beale; Mark Cherrie; William Mueller; Fiona Holland; Melissa Matz; Ioannis Basinas; Jack D Wilkinson; Matthew Gittins; Bernardine Farrell; Andrew Hayward; Neil Pearce; Martie van Tongeren", + "affiliations": "University of Manchester; University College London; Institute of Occupational Medicine; Institute of Occupational Medicine; University of Manchester; London School of Hygiene and Tropical Medicine; University of Manchester; University of Manchester; University of Manchester; University of Manchester; UCL; London School of Hygiene and Tropical Medicine; University of Manchester", + "abstract": "IntroductionThe PROTECT National Core Study was funded by the UK Health and Safety Executive (HSE) to investigate routes of transmission for SARS-CoV-2 and variation between settings.\n\nMethodsA workshop was organised in Oct 2022.We brought together evidence from five published epidemiological studies that compared risks of SARS-CoV-2 infection or COVID-19 mortality by occupation or sector funded by PROTECT relating to three non-overlapping data sets, plus additional unpublished analyses relating to the Omicron period. We extracted descriptive study level data and model results. We investigated risk across four pandemic waves using forest plots for key occupational groups by time-period.\n\nResultsResults were largely consistent across different studies with different expected biases. Healthcare and social care sectors saw elevated risks of SARS-CoV-2 infection and COVID-19 mortality early in the pandemic, but thereafter this declined and varied by specific occupational subgroup. The education sector saw sustained elevated risks of infection after the initial lockdown period with little evidence of elevated mortality.\n\nConclusionsIncreased in risk of infection and mortality were consistently observed for occupations in high risk sectors particularly during the early stage of the pandemic. The education sector showed a different pattern compared to the other high risk sectors, as relative risk of infections remained high in the later phased of the pandemic, although no increased in COVID-19 mortality (compared to low-risk occupations) was observed in this sector in any point during the pandemic.", + "category": "occupational and environmental health", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2023.06.29.23292043", @@ -489,6 +489,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2023.02.16.23286017", + "date": "2023-02-18", + "link": "https://medrxiv.org/cgi/content/short/2023.02.16.23286017", + "title": "Long-term outdoor air pollution and COVID-19 mortality in London: an individual-level analysis", + "authors": "Loes Charlton; Chris Gale; Jasper Morgan; Myer Glickman; Sean Beevers; Anna L Hansell; Vah\u00e9 Nafilyan", + "affiliations": "Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Imperial College London; University of Leicester; Office for National Statistics", + "abstract": "BackgroundThe risk of COVID-19 severity and mortality differs markedly by age, socio-demographic characteristics and pre-existing health status. Various studies have suggested that higher air pollution exposures also increase the likelihood of dying from COVID-19.\n\nObjectives: To assess the association between long-term outdoor air pollution (NO2, NOx, PM10 and PM2.5) concentrations and the risk of death involving COVID-19, using a large individual-level dataset.\n\nMethodsWe used comprehensive individual-level data from the Office for National Statistics Public Health Data Asset for September 2020 to January 2022 and London Air Quality Network modelled air pollution concentrations available for 2016. Using Cox proportional hazard regression models, we adjusted for potential confounders including age, sex, vaccination status, dominant virus variants, geographical factors (such as population density), ethnicity, area and household-level deprivation, and health comorbidities.\n\nResultsThere were 737,356 confirmed COVID-19 cases including 9,315 COVID-related deaths. When only adjusting for age, sex, and vaccination status, there was an increased risk of dying from COVID-19 with increased exposure to all air pollutants studied (NO2: HR 1.07 [95% confidence interval: 1.04-1.12] per 10 g/m3; NOx: 1.05[1.02-1.09] per 20 g/m3; PM10: 1.32[1.15-1.51] per 10 g/m3; PM2.5: 1.29[1.12-1.49] per 5 g/m3). However, after adjustment including ethnicity and socio-economic factors the HRs were close to unity (NO2: 0.98[0.90-1.06]; NOx: 0.99[0.94-1.04]; PM10: 0.95[0.74-1.22]; PM2.5: 0.90[0.67-1.20]). Additional adjustment for dominant variant or pre-existing health comorbidities did not alter the results.\n\nConclusionsObserved associations between long-term outdoor air pollution exposure and COVID-19 mortality in London are strongly confounded by geography, ethnicity and deprivation.\n\nSummaryUsing a large individual-level dataset, we found that a positive association between long-term outdoor air pollution and COVID-19 mortality in London did not persist after adjusting for confounders including population density, ethnicity and deprivation.", + "category": "respiratory medicine", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2023.02.09.23285649", @@ -839,20 +853,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.08.17.22278893", - "date": "2022-08-18", - "link": "https://medrxiv.org/cgi/content/short/2022.08.17.22278893", - "title": "Uptake of Sotrovimab for prevention of severe COVID-19 and its safety in the community in England", - "authors": "Martina Patone; Holly Tibble; Andrew JHL Snelling; Carol Coupland; Aziz Sheikh; Julia Hippisley-Cox", - "affiliations": "University of Oxford; University of Edinburgh; University of Oxford; University of Oxford; University of Edinburgh; University of Oxford", - "abstract": "Sotrovimab is a neutralising monoclonal antibody (nMAB), currently administrated in England to treat extremely clinically vulnerable COVID-19 patients. Trials have shown it to have mild or moderate side effects, however safety in real-world settings has not been yet evaluated. We used national databases to investigate its uptake and safety in community patients across England. We used a cohort study to describe uptake and a self-controlled case series design to evaluate the risks of 49 pre-specified suspected adverse events in the 2-28 days post-treatment. Between December 11, 2021 and May 24, 2022, there were 172,860 COVID-19 patients eligible for treatment. Of the 22,815 people who received Sotrovimab, 21,487 (94.2%) had a positive SARS-CoV-2 test and 5,999 (26.3%) were not on the eligible list. Between treated and untreated eligible individuals, the mean age (54.6, SD: 16.1 vs 54.1, SD: 18.3) and sex distribution (women: 60.9% vs 58.1%; men: 38.9% vs 41.1%) were similar. There were marked variations in uptake between ethnic groups, which was higher amongst Indian (15.0%; 95%CI 13.8, 16.3), Other Asian (13.7%; 95%CI 11.9, 15.8), White (13.4%; 95%CI 13.3, 13.6), and Bangladeshi (11.4%; 95%CI 8.8, 14.6); and lower amongst Black Caribbean individuals (6.4%; 95%CI 5.4, 7.5) and Black Africans (4.7%; 95%CI 4.1, 5.4). We found no increased risk of any of the suspected adverse events in the overall period of 2-28 days post-treatment, but an increased risk of rheumatoid arthritis (IRR 3.08, 95% CI 1.44, 6.58) and of systematic lupus erythematosus (IRR 5.15, 95% CI 1.60, 16.60) in the 2-3 days post-treatment, when we narrowed the risk period.\n\nFundingNational Institute of Health Research (Grant reference 135561)", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.08.13.22278733", @@ -881,20 +881,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.08.07.22278510", - "date": "2022-08-09", - "link": "https://medrxiv.org/cgi/content/short/2022.08.07.22278510", - "title": "Metabolomic and gut microbiome profiles across the spectrum of community-based COVID and non-COVID disease: A COVID-19 Biobank study.", - "authors": "Marc F \u00d6sterdahl; Ronan Whiston; Carole H Sudre; Francesco Asnicar; Nathan J Cheetham; Aitor Blanco Miguez; Vicky Bowyer; Michela Antonelli; Olivia Snell; Liane dos Santos Canas; Christina Hu; Jonathan Wolf; Cristina Menni; Michael Malim; Deborah Hart; Tim Spector; Sarah Berry; Nicola Segata; Katie Doores; Sebastien Ourselin; Emma L Duncan; Claire J Steves", - "affiliations": "King's College London; King's College London; King's College London; University of Trento; King's College London; University of Trento; King's College London; King's College London; King's College London; King's College London; ZOE Global Ltd.; ZOE Global Ltd.; King's College London; King's College London; King's College London; King's College London; King's College London; University of Trento; King's College London; King's College London; King's College London; King's College London", - "abstract": "Whilst many with SARS-CoV-2 infection have mild disease, managed in the community, individuals with cardiovascular risk factors experienced often more severe acute disease, requiring hospitalisation. Increasing concern has also developed over long symptom duration in many individuals, including the majority who managed acutely in the community. Risk factors for long symptom duration, including biological variables, are still poorly defined.\n\nWe examine post-illness metabolomic and gut-microbiome profiles, in community-dwelling participants with SARS-CoV-2, ranging from asymptomatic illness to Post-COVID Syndrome, and participants with prolonged non-COVID-19 illnesses. We also assess a pre-established metabolomic biomarker score for its association with illness duration.\n\nWe found an atherogenic-dyslipidaemic metabolic profile, and greater biomarker scores, associated with longer illness, both in individuals with and without SARS-CoV-2 infection. We found no association between illness duration and gut microbiome in convalescence.\n\nFindings highlight the potential role of cardiometabolic dysfunction to the experience of long illness duration, including after COVID-19.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.07.28.22278152", @@ -965,6 +951,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.06.18.22276437", + "date": "2022-06-19", + "link": "https://medrxiv.org/cgi/content/short/2022.06.18.22276437", + "title": "A patient-centric characterization of systemic recovery from SARS-CoV-2 infection", + "authors": "H\u00e9l\u00e8ne Ruffieux; Aimee Hanson; Samantha Lodge; Nathan Lawler; Luke Whiley; Nicola Gray; Tui Nolan; Laura Bergamaschi; Federica Mescia; - CITIID-NIHR COVID BioResource Collaboration; Nathalie Kingston; John Bradley; Elaine Holmes; Julien Wist; Jeremy Nicholson; Paul Lyons; Kenneth Smith; Sylvia Richardson; Glenn Bantug; Christoph Hess", + "affiliations": "University of Cambridge; University of Cambridge; Murdoch University; Murdoch University; Murdoch University; Murdoch University; University of Cambridge; University of Cambridge; University of Cambridge; ; University of Cambridge; University of Cambridge; Murdoch University; Murdoch University; Murdoch University; University of Cambridge; University of Cambridge; University of Cambridge; University and University Hospital Basel; University of Cambridge", + "abstract": "The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data, covering a year post disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct \"systemic recovery\" profiles with specific progression and resolution of the inflammatory, immune, metabolic and clinical responses, over weeks to several months after infection. In particular, we found a strong intra-patient temporal covariation of innate immune cell numbers, kynurenine- and host lipid-metabolites, which suggested candidate immunometabolic pathways putatively influencing restoration of homeostasis, the risk of death and of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery on the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-systemic-recovery-prediction-app, designed to test our findings prospectively.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/22276437v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (38K):\norg.highwire.dtl.DTLVardef@12b0afborg.highwire.dtl.DTLVardef@ddf3b2org.highwire.dtl.DTLVardef@1aa670forg.highwire.dtl.DTLVardef@5415ec_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "category": "infectious diseases", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.06.17.22276433", @@ -1189,20 +1189,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.04.03.22272610", - "date": "2022-04-04", - "link": "https://medrxiv.org/cgi/content/short/2022.04.03.22272610", - "title": "Cardiac impairment in Long Covid 1-year post-SARS-CoV-2 infection", - "authors": "Adriana Roca-Fernandez; Malgorzata Wamil; Alison Telford; Valentina Carapella; Alessandra Borlotti; David Monteiro; Helena Thomaides-Brears; Matthew D Kelly; Andrea Dennis; Rajarshi Banerjee; Matthew Robson; Michael Brady; Gregory Lip; Sacha Bull; Melissa J Heightman; Ntobeko Ntusi; Amitava Banerjee", - "affiliations": "Perspectum Diagnostics; Great Western Hospital Foundation NHS Trust, Swindon, UK; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; University of Liverpool; Royal Berkshire Hospital, Reading; UCLH; University of Cape Town, Cape Town, South Africa; University College London", - "abstract": "BackgroundLong Covid is associated with multiple symptoms and impairment in multiple organs. Cardiac impairment has been reported to varying degrees by varying methodologies in cross-sectional studies. Using cardiac magnetic resonance (CMR), we investigated the 12-month trajectory of cardiac impairment in individuals with Long Covid.\n\nMethods534 individuals with Long Covid underwent baseline CMR (T1 and T2 mapping, cardiac mass, volumes, function, and strain) and multi-organ MRI at 6 months (IQR 4.3,7.3) since first post-COVID-19 symptoms and 330 were rescanned at 12.6 (IQR 11.4, 14.2) months if abnormal findings were reported at baseline. Symptoms, standardised questionnaires, and blood samples were collected at both timepoints. Cardiac impairment was defined as one or more of: low left or right ventricular ejection fraction (LVEF and RVEF), high left or right ventricular end diastolic volume (LVEDV and RVEDV), low 3D left ventricular global longitudinal strain (GLS), or elevated native T1 in [≥]3 cardiac segments. A significant change over time was reported by comparison with 92 healthy controls.\n\nResultsThe technical success of this multiorgan assessment in non-acute settings was 99.1% at baseline, and 98.3% at follow up, with 99.6% and 98.8% for CMR respectively. Of individuals with Long Covid, 102/534 [19%] had cardiac impairment at baseline; 71/102 had complete paired data at 12 months. Of those, 58% presented with ongoing cardiac impairment at 12 months. High sensitivity cardiac troponin I and B-type natriuretic peptide were not predictive of CMR findings, symptoms, or clinical outcomes. At baseline, low LVEF, high RVEDV and low GLS were associated with cardiac impairment. Low LVEF at baseline was associated with persistent cardiac impairment at 12 months.\n\nConclusionCardiac impairment, other than myocarditis, is present in 1 in 5 individuals with Long Covid at 6 months, persisting in over half of those at 12 months. Cardiac-related blood biomarkers are unable to identify cardiac impairment in Long COVID. Subtypes of disease (based on symptoms, examination, and investigations) and predictive biomarkers are yet to be established. Interventional trials with pre-specified subgroup analyses are required to inform therapeutic options.", - "category": "cardiovascular medicine", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.03.29.22273042", @@ -1357,6 +1343,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.02.04.22270479", + "date": "2022-02-06", + "link": "https://medrxiv.org/cgi/content/short/2022.02.04.22270479", + "title": "Comparative effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections: A time-varying cohort analysis using trial emulation in the Virus Watch community cohort", + "authors": "Vincent Nguyen; Alexei Yavlinsky; Sarah Beale; Susan J Hoskins; Vasileios J Lampos; Isobel Braithwaite; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan Mathew Dwight Navaratnam; Parth Patel; Madhumita Shrotri; Sophie Weber; Andrew Hayward; Robert W Aldridge", + "affiliations": "University College London; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London, London School of Hygiene &Tropical Medicine; UCL, London School of Hygiene & Tropical Medicine; University College London; University College London; University College London; University College London; Univeristy College London; University College London; University College London; University College London", + "abstract": "ImportanceThe Omicron (B.1.1.529) variant has increased SARs-CoV-2 infections in double vaccinated individuals globally, particularly in ChAdOx1 recipients. To tackle rising infections, the UK accelerated booster vaccination programmes used mRNA vaccines irrespective of an individuals primary course vaccine type with booster doses rolled out according to clinical priority. There is limited understanding of the effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections and how time-varying confounders can impact the evaluations comparing different vaccines as primary courses for mRNA boosters.\n\nObjectiveTo evaluate the comparative effectiveness of ChAdOx1 versus BNT162b2 as primary doses against SARs-CoV-2 in booster vaccine recipients whilst accounting for time-varying confounders.\n\nDesignTrial emulation was used to reduce time-varying confounding-by-indication driven by prioritising booster vaccines based upon age, vulnerability and exposure status e.g. healthcare worker. Trial emulation was conducted by meta-analysing eight cohort results whose booster vaccinations were staggered between 16/09/2021 to 05/01/2022 and followed until 23/01/2022. Time from booster vaccination until SARS-CoV-2 infection, loss of follow-up or end-of-study was modelled using Cox proportional hazards models for each cohort and adjusted for age, sex, minority ethnic status, clinically vulnerability, and deprivation.\n\nSettingProspective observational study using the Virus Watch community cohort in England and Wales.\n\nParticipantsPeople over the age of 18 years who had their booster vaccination between 16/09/2021 to 05/01/2022 without prior natural immunity.\n\nExposuresChAdOx1 versus BNT162b2 as a primary dose, and an mRNA booster vaccine.\n\nResultsAcross eight cohorts, 19,692 mRNA vaccine boosted participants were analysed with 12,036 ChAdOx1 and 7,656 BNT162b2 primary courses with a median follow-up time of 73 days (IQR:54-90). Median age, clinical vulnerability status and infection rates fluctuate through time. 7.2% (n=864) of boosted adults with ChAdOx1 primary course experienced a SARS-CoV-2 infection compared to 7.6% (n=582) of those with BNT162b2 primary course during follow-up. The pooled adjusted hazard ratio was 0.99 [95%CI:0.88-1.11], demonstrating no difference between the incidence of SARs-CoV-2 infections based upon the primary vaccine course.\n\nConclusion and RelevanceIn mRNA boosted individuals, we found no difference in protection comparing those with a primary course of BNT162b2 to those with aChAdOx1 primary course. This contrasts with pre-booster findings where previous research shows greater effectiveness of BNT162b2 than ChAdOx1 in preventing infection.", + "category": "epidemiology", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.01.31.22269194", @@ -1483,20 +1483,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.23.21268276", - "date": "2021-12-25", - "link": "https://medrxiv.org/cgi/content/short/2021.12.23.21268276", - "title": "Risk of myocarditis following sequential COVID-19 vaccinations by age and sex", - "authors": "Martina Patone; Winnie Xue Mei; Lahiru Handunnetthi; Sharon Dixon; Francesco Zaccardi; Manu Shankar-Hari; Peter Watkinson; Kamlesh Khunti; Anthony Harnden; Carol AC Coupland; Keith M. Channon; Nicholas L Mills; Aziz Sheikh; Julia Hippisley-Cox", - "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Leicester; University of Edinburgh; University of Oxford; University of Leicester; University of Oxford; University of Oxford; University of Oxford; University of Edinburgh; University of Edinburgh; University of Oxford", - "abstract": "In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy.\n\nFundingHealth Data Research UK.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.22.21268252", @@ -1623,20 +1609,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.14.21267460", - "date": "2021-12-15", - "link": "https://medrxiv.org/cgi/content/short/2021.12.14.21267460", - "title": "Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales", - "authors": "Sarah Beale; Susan J Hoskins; Thomas Edward Byrne; Erica Wing Lam Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan MD Navaratnam; Vincent Nguyen; Parth Patel; Alexei Yavlinsky; Anne Johnson; Martie Van Tongeren; Robert W Aldridge; Andrew Hayward", - "affiliations": "University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University of Manchester; University College London; University College London", - "abstract": "BackgroundWorkers differ in their risk of SARS-CoV-2 infection according to their occupation, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase.\n\nMethodsData from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR).\n\nFindingsIncreased risk was seen in nurses (aRR=1.44, 1.25-1.65; AF=30%, 20-39%), doctors (aRR=1.33, 1.08-1.65; AF=25%, 7-39%), carers (1.45, 1.19-1.76; AF=31%, 16-43%), primary school teachers (aRR=1.67, 1.42-1.96; AF=40%, 30-49%), secondary school teachers (aRR=1.48, 1.26-1.72; AF=32%, 21-42%), and teaching support occupations (aRR=1.42, 1.23-1.64; AF=29%, 18-39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020 - May 2021) and attenuated later (June - October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves.\n\nInterpretationOccupational differentials in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.08.21267353", @@ -2071,6 +2043,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.08.17.21262196", + "date": "2021-08-22", + "link": "https://medrxiv.org/cgi/content/short/2021.08.17.21262196", + "title": "Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY disease (CLARITY): Statistical analysis plan for a randomised controlled Bayesian adaptive sample size trial", + "authors": "James McGree; Carinna Hockham; Sradha Kotwal; Arlen Wilcox; Abhinav Bassi; Carol Pollock; Louise M Burrell; Tom Snelling; Vivek Jha; Meg Jardine; Mark Jones", + "affiliations": "Queensland University of Technology; Imperial College London; University of New South Wales; University of New South Wales; The George Institute for Global Health; Royal North Shore Hospital; University of Melbourne; The University of Sydney; University of New South Wales; University of New South Wales; The University of Sydney", + "abstract": "The CLARITY trial (Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY Disease) investigates the effectiveness of angiotensin receptor blockers in addition to standard care compared to placebo (in Indian sites) with standard care in reducing the duration and severity of lung failure in patients with COVID-19. The CLARITY trial is a multi-centre, randomised controlled Bayesian adaptive trial with regular planned analyses where pre-specified decision rules will be assessed to determine whether the trial should be stopped due to sufficient evidence of treatment effectiveness or futility. Here we describe the statistical analysis plan for the trial, and define the pre-specified decision rules, including those that could lead to the trial being halted. The primary outcome is clinical status on a 7-point ordinal scale adapted from the WHO Clinical Progression scale assessed at Day 14. The primary analysis will follow the intention-to-treat principle. A Bayesian adaptive trial design was selected because there is considerable uncertainty about the extent of potential benefit of this treatment.\n\nTrial registrationClinicalTrials.gov, NCT04394117. Registered on 19 May 2020.\n\nhttps://clinicaltrials.gov/ct2/show/NCT04394117\n\nClinical Trial Registry of India: CTRI/2020/07/026831\n\nVersion and revisionsVersion 1.0. No revisions.", + "category": "respiratory medicine", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.08.13.21261889", @@ -2799,6 +2785,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.03.17.21253853", + "date": "2021-03-20", + "link": "https://medrxiv.org/cgi/content/short/2021.03.17.21253853", + "title": "Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest optimal policies varies with rural-urban settings", + "authors": "Xilin Jiang; Wenfeng Gong; Zlatina Dobreva; Ya Gao; Matthew Quaife; Christophe Fraser; Chris Holmes", + "affiliations": "University of Oxford; Bill & Melinda Gates Foundation; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; Department of International Health, Johns Hopkins University; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; University of Oxford; University of Oxford", + "abstract": "Low- and middle-income countries (LMICs) remain of high potential for hotspots for COVID-19 deaths and emerging variants given the inequality of vaccine distribution and their vulnerable healthcare systems. We aim to evaluate containment strategies that are sustainable and effective for LMICs. We constructed synthetic populations with varying contact and household structures to capture LMIC demographic characteristics that vary across communities. Using an agent- based model, we explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic tests, symptom screening, contact tracing and physical distancing. In low-density rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. In urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In high density communities that resemble slums and squatter settlements, physical distancing is less effective compared to rural and urban communities. Lastly, we demonstrated contact tracing is essential for effective containment. Our findings suggested that rapid diagnostic tests could be prioritised for control and monitor COVID-19 transmission and highlighted that contact survey data could guide strategy design to save resources for LMICs. An accompanying open source R package is available for simulating COVID-19 transmission based on contact network models.", + "category": "epidemiology", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.03.18.21253443", @@ -2841,20 +2841,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.02.27.21252593", - "date": "2021-03-01", - "link": "https://medrxiv.org/cgi/content/short/2021.02.27.21252593", - "title": "Surgical activity in England and Wales during the COVID-19 pandemic: a nationwide observational cohort study", - "authors": "Thomas D Dobbs; John A G Gibson; Alexander J Fowler; Tom E Abbott; Tasnin Shahid; Fatemeh Torabi; Rowena Griffiths; Ronan A Lyons; Rupert M Pearse; Iain S Whitaker", - "affiliations": "Swansea University Medical School; Swansea University Medical School; Queen Mary, University of London; Queen Mary University of London; Queen Mary University of London; Swansea University; Swansea University; Swansea University; Queen Mary University of London; Swansea University Medical School", - "abstract": "ObjectivesTo report the volume of surgical activity and the number of cancelled surgical procedures during the COVID-19 pandemic.\n\nDesign and settingAnalysis of electronic health record data from the National Health Service (NHS) in England and Wales.\n\nMethodsWe used hospital episode statistics for all adult patients undergoing surgery between 1st January 2020 and 31st December 2020. We identified surgical procedures using a previously published list of procedure codes. Procedures were stratified by urgency of surgery as defined by NHS England. We calculated the deficit of surgical activity by comparing the expected number of procedures from the years 2016-2019 with the actual number of procedures in 2020. We estimated the cumulative number of cancelled procedures by 31st December 2021 according patterns of activity in 2020.\n\nResultsThe total number of surgical procedures carried out in England and Wales in 2020 was 3,102,674 compared to the predicted number of 4,671,338. This represents a 33.6% reduction in the national volume of surgical activity. There were 763,730 emergency surgical procedures (13.4% reduction), compared to 2,338,944 elective surgical procedures (38.6% reduction). The cumulative number of cancelled or postponed procedures was 1,568,664. We estimate that this will increase to 2,358,420 by 31st December 2021.\n\nConclusionsThe volume of surgical activity in England and Wales was reduced by 33.6% in 2020, resulting in over 1,568,664 cancelled operations. This deficit will continue to grow in 2021.\n\nSummary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIThe COVID-19 pandemic necessitated a rapid change in the provision of care, including the suspension of a large proportion of surgical activity\nC_LIO_LISurgical activity has yet to return to normal and has been further impacted by subsequent waves of the pandemic\nC_LIO_LIThis will lead to a large backlog of cases\nC_LI\n\nWhat this study addsO_LI3,102,674 surgical procedures were performed in England and Wales during 2020, a 33.6% reduction on the expected yearly surgical activity\nC_LIO_LIOver 1.5 million procedures were not performed, with this deficit likely to continue to grow to 2.3 million by the end of 2021\nC_LIO_LIThis deficit is the equivalent of more than 6 months of pre-pandemic surgical activity, requiring a monumental financial and logistic challenge to manage\nC_LI", - "category": "surgery", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.02.23.21251975", @@ -3009,6 +2995,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.01.22.21250304", + "date": "2021-01-25", + "link": "https://medrxiv.org/cgi/content/short/2021.01.22.21250304", + "title": "Rates of serious clinical outcomes in survivors of hospitalisation with COVID-19: a descriptive cohort study within the OpenSAFELY platform", + "authors": "John Tazare; Alex J Walker; Laurie Tomlinson; George Hickman; Christopher T Rentsch; Elizabeth J Williamson; Krishnan Bhaskaran; David Evans; Kevin Wing; Rohini Mathur; Angel YS Wong; Anna Schultze; Sebastian CJ Bacon; Christopher Bates; Caroline E Morton; Helen J Curtis; Emily Nightingale; Helen I McDonald; Amir Mehrkar; Peter Inglesby; Simon Davy; Brian MacKenna; Jonathan Cockburn; William J Hulme; Charlotte Warren-Gash; Ketaki Bhate; Emma Powell; Any Mulick; Harriet Forbes; Caroline Minassian; Richard Croker; John Parry; Frank Hester; Sam Harper; Rosalind M Eggo; Stephen JW Evans; Liam Smeeth; Ian J Douglas; Ben Goldacre", + "affiliations": "London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford", + "abstract": "BackgroundPatients with COVID-19 are thought to be at higher risk of cardiometabolic and pulmonary complications, but quantification of that risk is limited. We aimed to describe the overall burden of these complications in survivors of severe COVID-19.\n\nMethodsWorking on behalf of NHS England, we used linked primary care records, death certificate and hospital data from the OpenSAFELY platform. We constructed three cohorts: patients discharged following hospitalisation with COVID-19, patients discharged following hospitalisation with pneumonia in 2019, and a frequency-matched cohort from the general population in 2019. We studied eight cardiometabolic and pulmonary outcomes. Absolute rates were measured in each cohort and Cox regression models were fitted to estimate age/sex adjusted hazard ratios comparing outcome rates between discharged COVID-19 patients and the two comparator cohorts.\n\nResultsAmongst the population of 31,716 patients discharged following hospitalisation with COVID-19, rates for majority of outcomes peaked in the first month post-discharge, then declined over the following four months. Patients in the COVID-19 population had markedly increased risk of all outcomes compared to matched controls from the 2019 general population, especially for pulmonary embolism (HR 12.86; 95% CI: 11.23 - 14.74). Outcome rates were more similar when comparing patients discharged with COVID-19 to those discharged with pneumonia in 2019, although COVID-19 patients had increased risk of type 2 diabetes (HR 1.23; 95% CI: 1.05 - 1.44).\n\nInterpretationCardiometabolic and pulmonary adverse outcomes are markedly raised following hospitalisation for COVID-19 compared to the general population. However, the excess risks were more comparable to those seen following hospitalisation with pneumonia. Identifying patients at particularly high risk of outcomes would inform targeted preventive measures.\n\nFundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, UK Research and Innovation, Health and Safety Executive.", + "category": "epidemiology", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.01.22.21249968", @@ -3135,6 +3135,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.01.06.21249352", + "date": "2021-01-08", + "link": "https://medrxiv.org/cgi/content/short/2021.01.06.21249352", + "title": "OpenSAFELY NHS Service Restoration Observatory 1: describing trends and variation in primary care clinical activity for 23.3 million patients in England during the first wave of COVID-19", + "authors": "Helen J Curtis; Brian MacKenna; Richard Croker; Alex J Walker; Peter Inglesby; Jessica Morley; Amir Mehrkar; Caroline E Morton; Seb Bacon; George Hickman; Chris Bates; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan T. Bhaskaran; Anna Schultze; Christopher T. Rentsch; Elizabeth J Williamson; Will Hulme; Helen I McDonald; Laurie Tomlinson; Kevin Wing; Rohini I Mathur; Harriet Forbes; Angel Wong; Rosalind M Eggo; Henry Drysdale; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Stephen Evans; Liam Smeeth; Ben Goldacre", + "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; LSHTM; US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine; LSHTM; University of Oxford; London School of Medicine and Tropical Medicine; LSHTM; LSHTM; London School of Hygiene and Tropical Medicine; LSHTM; London School of Hygiene and Tropical Medicine; LSHTM; University of Oxford; TPP; TPP; TPP; LSHTM; LSHTM; LSHTM; University of Oxford", + "abstract": "BackgroundThe COVID-19 pandemic has disrupted healthcare activity globally. The NHS in England stopped most non-urgent work by March 2020, but later recommended that services should be restored to near-normal levels before winter where possible. The authors are developing the OpenSAFELY NHS Service Restoration Observatory, using data to describe changes in service activity during COVID-19, and reviewing signals for action with commissioners, researchers and clinicians. Here we report phase one: generating, managing, and describing the data.\n\nObjectiveTo describe the volume and variation of coded clinical activity in English primary care across 23.8 million patients records, taking respiratory disease and laboratory procedures as key examples.\n\nMethodsWorking on behalf of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care EHR data on 23.8 million patients; and conducted a population cohort-based study to describe activity using CTV3 coding hierarchy and keyword searches from January 2019-September 2020.\n\nResultsMuch activity recorded in general practice declined to some extent during the pandemic, but largely recovered by September 2020, with some exceptions. There was a large drop in coded activity for commonly used laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was blood coagulation tests such as International Normalised Ratio (INR), with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 7.0). The overall pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as \"no change\" from the previous year. Respiratory tract infections exhibited a sustained drop compared with pre-pandemic levels, not returning to pre-pandemic levels by September 2020. Various COVID-19 codes increased through the period. We observed a small decline associated with high level codes for long-term respiratory conditions such as chronic obstructive pulmonary disease (COPD) and asthma. Asthma annual reviews experienced a small drop but since recovered, while COPD annual reviews remain below baseline.\n\nConclusionsWe successfully delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September 2020, with some important tests less affected. Records of respiratory infections decreased with the exception of codes related to COVID-19, whilst activity of other respiratory disease codes was mixed. We are expanding the NHS Service Restoration Observatory in collaboration with clinicians, commissioners and researchers and welcome feedback.", + "category": "health systems and quality improvement", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.12.30.20248603", @@ -3443,20 +3457,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.10.14.20212555", - "date": "2020-10-16", - "link": "https://medrxiv.org/cgi/content/short/2020.10.14.20212555", - "title": "Multi-organ impairment in low-risk individuals with long COVID", - "authors": "Andrea Dennis; Malgorzata Wamil; Sandeep Kapur; Johann Alberts; Andrew Badley; Gustav Anton Decker; Stacey A Rizza; Rajarshi Banerjee; Amitava Banerjee", - "affiliations": "Perspectum; Great Western Hospitals NHS Foundation Trust; Mayo Clinic Healthcare; Alliance Medical; Mayo Clinic; Mayo Clinic International; Mayo Clinic; Perspectum; University College London", - "abstract": "BackgroundSevere acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection has disproportionately affected older individuals and those with underlying medical conditions. Research has focused on short-term outcomes in hospital, and single organ involvement. Consequently, impact of long COVID (persistent symptoms three months post-infection) across multiple organs in low-risk individuals is yet to be assessed.\n\nMethodsAn ongoing prospective, longitudinal, two-centre, observational study was performed in individuals symptomatic after recovery from acute SARS-CoV-2 infection. Symptoms and organ function (heart, lungs, kidneys, liver, pancreas, spleen) were assessed by standardised questionnaires (EQ-5D-5L, Dyspnoea-12), blood investigations and quantitative magnetic resonance imaging, defining single and multi-organ impairment by consensus definitions.\n\nFindingsBetween April and September 2020, 201 individuals (mean age 44 (SD 11.0) years, 70% female, 87% white, 31% healthcare workers) completed assessments following SARS-CoV-2 infection (median 140, IQR 105-160 days after initial symptoms). The prevalence of pre-existing conditions (obesity: 20%, hypertension: 6%; diabetes: 2%; heart disease: 4%) was low, and only 18% of individuals had been hospitalised with COVID-19. Fatigue (98%), muscle aches (88%), breathlessness (87%), and headaches (83%) were the most frequently reported symptoms. Ongoing cardiorespiratory (92%) and gastrointestinal (73%) symptoms were common, and 42% of individuals had ten or more symptoms.\n\nThere was evidence of mild organ impairment in heart (32%), lungs (33%), kidneys (12%), liver (10%), pancreas (17%), and spleen (6%). Single (66%) and multi-organ (25%) impairment was observed, and was significantly associated with risk of prior COVID-19 hospitalisation (p<0.05).\n\nInterpretationIn a young, low-risk population with ongoing symptoms, almost 70% of individuals have impairment in one or more organs four months after initial symptoms of SARS-CoV-2 infection. There are implications not only for burden of long COVID but also public health approaches which have assumed low risk in young people with no comorbidities.\n\nFundingThis work was supported by the UKs National Consortium of Intelligent Medical Imaging through the Industry Strategy Challenge Fund, Innovate UK Grant 104688, and also through the European Unions Horizon 2020 research and innovation programme under grant agreement No 719445.", - "category": "health policy", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.10.12.20211227", @@ -3583,6 +3583,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.09.24.20200048", + "date": "2020-09-25", + "link": "https://medrxiv.org/cgi/content/short/2020.09.24.20200048", + "title": "Genetic mechanisms of critical illness in Covid-19", + "authors": "Erola Pairo-Castineira; Sara Clohisey; Lucija Klaric; Andrew Bretherick; Konrad Rawlik; Nicholas Parkinson; Dorota Pasko; Susan Walker; Anne Richmond; Max Head Fourman; Andy Law; James Furniss; Elvina Gountouna; Nicola Wrobel; Clark D Russell; Loukas Moutsianas; Bo Wang; Alison Meynert; Zhijian Yang; Ranran Zhai; Chenqing Zheng; Fiona Griffith; Wilna Oosthuyzen; Barbara Shih; Se\u00e1n Keating; Marie Zechner; Chris Haley; David J Porteous; Caroline Hayward; Julian Knight; Charlotte Summers; Manu Shankar-Hari; Lance Turtle; Antonia Ho; Charles Hinds; Peter Horby; Alistair Nichol; David Maslove; Lowell Ling; Paul Klenerman; Danny McAuley; Hugh Montgomery; Timothy Walsh; - The GenOMICC Investigators; - The ISARIC4C Investigators; - The Covid-19 Human Genetics Initiative; Xia Shen; Kathy Rowan; Angie Fawkes; Lee Murphy; Chris P Ponting; Albert Tenesa; Mark Caulfield; Richard Scott; Peter JM Openshaw; Malcolm G Semple; Veronique Vitart; James F Wilson; J Kenneth Baillie", + "affiliations": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; The Roslin Institute; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Genomics England; Genomics England; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; University of Edinburgh Centre for Inflammation Research, The Queen's Medical Research Institute, Edinburgh, UK; Genomics England; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.; Department of Medicine, University of Cambridge, Cambridge, UK.; Department of Intensive Care Medicine, Guy's and St. Thomas NHS Foundation Trust, London, UK; School of Immunology and Microbial Sciences, King's College London; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences University of Liverpool, L; MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, Univer; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7FZ, UK.; Clinical Research Centre at St Vincent's University Hospital, University College Dublin, Dublin, Ireland; Australian and New Zealand Intensive Care Research Cen; Department of Critical Care Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, ON, Canada.; Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.; University of Oxford; Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, Northern Ireland, UK; Department of Intensive Care Medicine, Royal Vi; UCL Centre for Human Health and Performance, London, W1T 7HA, UK.; Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK.; -; -; -; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.; Intensive Care National Audit & Research Centre, London, UK.; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Genomics England; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK; Genomics England; National Heart & Lung Institute, Imperial College London (St Mary's Campus), Norfolk Place, Paddington, London W2 1PG, UK.; University of Liverpool, Liverpool, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK; Ce; Roslin Institute, University of Edinburgh", + "abstract": "The subset of patients who develop critical illness in Covid-19 have extensive inflammation affecting the lungs1 and are strikingly different from other patients: immunosuppressive therapy benefits critically-ill patients, but may harm some non-critical cases.2 Since susceptibility to life-threatening infections and immune-mediated diseases are both strongly heritable traits, we reasoned that host genetic variation may identify mechanistic targets for therapeutic development in Covid-19.3\n\nGenOMICC (Genetics Of Mortality In Critical Care, genomicc.org) is a global collaborative study to understand the genetic basis of critical illness. Here we report the results of a genome-wide association study (GWAS) in 2244 critically-ill Covid-19 patients from 208 UK intensive care units (ICUs), representing >95% of all ICU beds. Ancestry-matched controls were drawn from the UK Biobank population study and results were confirmed in GWAS comparisons with two other population control groups: the 100,000 genomes project and Generation Scotland.\n\nWe identify and replicate three novel genome-wide significant associations, at chr19p13.3 (rs2109069, p = 3.98 x 10-12), within the gene encoding dipeptidyl peptidase 9 (DPP9), at chr12q24.13 (rs10735079, p =1.65 x 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), and at chr21q22.1 (rs2236757, p = 4.99 x 10-8) in the interferon receptor gene IFNAR2. Consistent with our focus on extreme disease in younger patients with less comorbidity, we detect a stronger signal at the known 3p21.31 locus than previous studies (rs73064425, p = 4.77 x 10-30).\n\nWe identify potential targets for repurposing of licensed medications. Using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease. Transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19.\n\nOur results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice.", + "category": "intensive care and critical care medicine", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.09.22.20198754", @@ -3667,20 +3681,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.09.10.20191841", - "date": "2020-09-11", - "link": "https://medrxiv.org/cgi/content/short/2020.09.10.20191841", - "title": "The King's College London Coronavirus Health and Experiences of Colleagues at King's Study: SARS-CoV-2 antibody response in an occupational sample", - "authors": "Daniel Leightley; Valentina Vitiello; Gabriella Bergin-Cartwright; Alice Wickersham; Katrina A S Davis; Sharon Stevelink; Matthew Hotopf; Reza Razavi; - On behalf of the KCL CHECK research team", - "affiliations": "Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London; ", - "abstract": "We report test results for SARS-CoV-2 antibodies in an occupational group of postgraduate research students and current members of staff at Kings College London. Between June and July 2020, antibody testing kits were sent to n=2296 participants; n=2004 (86.3%) responded, of whom n=1882 (93.9%) returned valid test results. Of those that returned valid results, n=124 (6.6%) tested positive for SARS-CoV-2 antibodies, with initial comparisons showing variation by age group and clinical exposure.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.09.11.20192492", @@ -3877,20 +3877,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.08.10.20171033", - "date": "2020-08-11", - "link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171033", - "title": "Post-exertion oxygen saturation as a prognostic factor for adverse outcome in patients attending the emergency department with suspected COVID-19: Observational cohort study", - "authors": "Steve Goodacre; Ben Thomas; Ellen Lee; Laura Sutton; Katie Biggs; Carl Marincowitz; Amanda Loban; Simon Waterhouse; Richard Simmonds; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter", - "affiliations": "University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust, Wythenshawe Hospital; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust", - "abstract": "BackgroundMeasurement of post-exertion oxygen saturation has been proposed to assess illness severity in suspected COVID-19 infection. We aimed to determine the accuracy of post-exertional oxygen saturation for predicting adverse outcome in suspected COVID-19.\n\nMethodsWe undertook an observational cohort study across 70 emergency departments during first wave of the COVID-19 pandemic in the United Kingdom. We collected data prospectively, using a standardised assessment form, and retrospectively, using hospital records, from patients with suspected COVID-19, and reviewed hospital records at 30 days for adverse outcome (death or receiving organ support). Patients with post-exertion oxygen saturation recorded were selected for this analysis.\n\nResultsWe analysed data from 817 patients with post-exertion oxygen saturation recorded after excluding 54 in whom measurement appeared unfeasible. The c-statistic for post-exertion change in oxygen saturation was 0.589 (95% confidence interval 0.465 to 0.713), and the positive and negative likelihood ratios of a 3% or more desaturation were respectively 1.78 (1.25 to 2.53) and 0.67 (0.46 to 0.98). Multivariable analysis showed that post-exertion oxygen saturation was not a significant predictor of adverse outcome when baseline clinical assessment was taken into account (p=0.368). Secondary analysis excluding patients in whom post-exertion measurement appeared inappropriate resulted in a c-statistic of 0.699 (0.581 to 0.817), likelihood ratios of 1.98 (1.26 to 3.10) and 0.61 (0.35 to 1.07), and some evidence of additional prognostic value on multivariable analysis (p=0.019).\n\nConclusionsPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19.\n\nRegistrationISRCTN registry, ISRCTN56149622, http://www.isrctn.com/ISRCTN28342533\n\nKey messagesWhat is already known on this subject?\n\nO_LIPost exertional decrease in oxygen saturation can be used to predict prognosis in chronic lung diseases\nC_LIO_LIPost exertional desaturation has been proposed as a way of predicting adverse outcome in people with suspected COVID-19\nC_LI\n\nWhat this study adds:\n\nO_LIPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19\nC_LI", - "category": "emergency medicine", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.08.07.20169490", @@ -4283,20 +4269,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.13.20130419", - "date": "2020-06-16", - "link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130419", - "title": "Mental health service activity during COVID-19 lockdown: South London and Maudsley data on working age community and home treatment team services and mortality from February to mid-May 2020", - "authors": "Robert Stewart; Evangelia Martin; Matthew Broadbent", - "affiliations": "King's College London; King's College London; South London and Maudsley NHS Foundation Trust", - "abstract": "The lockdown and social distancing policy response to the COVID-19 pandemic in the UK has a potentially important impact on provision of mental healthcare; however, there has been relatively little quantification of this. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for home treatment teams (HTTs) and working age adult community mental health teams (CMHTs) from 1st February to 15th May 2020 at the South London and Maudsley NHS Trust (SLaM), a large mental health service provider for 1.2m residents in south London. In addition daily deaths are described for all current and previous SLaM service users over this period and the same dates in 2019. In summary, comparing periods before and after 16th March 2020 the CMHT sector showed relatively stable caseloads and total contact numbers, but a substantial shift from face-to-face to virtual contacts, while HTTs showed the same changeover but reductions in caseloads and total contacts (although potentially an activity rise again during May). Number of deaths for the two months between 16th March and 15th May were 2.4-fold higher in 2020 than 2019, with 958 excess deaths.", - "category": "psychiatry and clinical psychology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.12.20129494", @@ -4353,20 +4325,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.02.20120642", - "date": "2020-06-05", - "link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120642", - "title": "Estimating excess visual loss in people with neovascular age-related macular degeneration during the COVID-19 pandemic", - "authors": "Darren S Thomas; Alasdair Warwick; Abraham Olvera-Barrios; Catherine Egan; Roy Schwartz; Sudeshna Patra; Haralabos Eleftheriadis; Anthony P Khawaja; Andrew Lotery; Philipp L Mueller; Robin Hamilton; Ella Preston; Paul Taylor; Adnan Tufail; - UK EMR Users Group", - "affiliations": "Institute of Health Informatics, University College London, London, UK; Institute of Cardiovascular Science, University College London, London, UK & Moorfields Eye Hospital NHS Foundation Trust, London, UK.; Moorfields Eye Hospital NHS Turst & Institute of Ophthalmology UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Health Informatics, University College London, London, UK; Bart's Health NHS Trust, London, UK; King's College Hospital NHS Trust, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Faculty of Medicine, University of Southampton, Southampton, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK; Institute of Health Informatics, University College London, London, UK; Moorfields Eye Hospital NHS Trust & Institute of Ophthalmology UCL; ", - "abstract": "ObjectivesTo report the reduction in new neovascular age-related macular degeneration (nAMD) referrals during the COVID-19 pandemic and estimate the impact of delayed treatment on visual outcomes at one year.\n\nDesignRetrospective clinical audit and simulation model.\n\nSettingMultiple UK NHS ophthalmology centres.\n\nParticipantsData on the reduction in new nAMD referrals was obtained from four NHS Trusts in England comparing April 2020 to April 2019. To estimate the potential impact on one-year visual outcomes, a stratified bootstrap simulation model was developed drawing on an electronic medical records dataset of 20,825 nAMD eyes from 27 NHS Trusts.\n\nMain outcome measuresSimulated mean visual acuity and proportions of eyes with vision [≤]6/60, [≤]6/24 and [≥]6/12 at one year under four hypothetical scenarios: no treatment delay, 3, 6 and 9-month treatment delays. Estimated additional number of eyes with vision [≤]6/60 at one year nationally.\n\nResultsThe number of nAMD referrals at four major eye treatment hospital groups based in England dropped on average by 72% (range 65 to 87%) in April 2020 compared to April 2019. Simulated one-year visual outcomes for 1000 nAMD eyes with a 3-month treatment delay suggested an increase in the proportion of eyes with vision [≤]6/60 from 15.5% (13.2 to 17.9) to 23.3% (20.7 to25.9), and a decrease in the proportion of eyes with vision [≥]6/12 (driving vision) from 35.1% (32.1 to 38.1) to 26.4% (23.8 to29.2). Outcomes worsened incrementally with longer modelled delays. Assuming nAMD referrals are reduced to this level at the national level for only one month, these simulated results suggest an additional 186-365 eyes with vision [≤]6/60 at one-year with even a short treatment delay.\n\nConclusionsWe report a large decrease in nAMD referrals during the first month of COVID-19 lockdown and provide an important public health message regarding the risk of delayed treatment. As a conservative estimate, a treatment delay of 3 months could lead to a >50% relative increase in the number of eyes with vision [≤]6/60 and 25% relative decrease in the number of eyes with driving vision at one year.", - "category": "ophthalmology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.01.20116608", @@ -4395,6 +4353,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.05.19.20106641", + "date": "2020-05-26", + "link": "https://medrxiv.org/cgi/content/short/2020.05.19.20106641", + "title": "Study Data Element Mapping: Feasibility of Defining Common Data Elements Across COVID-19 Studies", + "authors": "Priscilla Mathewson; Ben Gordon; Kay Snowley; Clara Fennessy; Alastair Denniston; Neil Sebire", + "affiliations": "University of Birmingham; HDRUK; HDRUK; HDRUK; HDRUK; Great Ormond Street Hospital and ICH London", + "abstract": "BackgroundNumerous clinical studies are now underway investigating aspects of COVID-19. The aim of this study was to identify a selection of national and/or multicentre clinical COVID-19 studies in the United Kingdom to examine the feasibility and outcomes of documenting the most frequent data elements common across studies to rapidly inform future study design and demonstrate proof-of-concept for further subject-specific study data element mapping to improve research data management.\n\nMethods25 COVID-19 studies were included. For each, information regarding the specific data elements being collected was recorded. Data elements collated were arbitrarily divided into categories for ease of visualisation. Elements which were most frequently and consistently recorded across studies are presented in relation to their relative commonality.\n\nResultsAcross the 25 studies, 261 data elements were recorded in total. The most frequently recorded 100 data elements were identified across all studies and are presented with relative frequencies. Categories with the largest numbers of common elements included demographics, admission criteria, medical history and investigations. Mortality and need for specific respiratory support were the most common outcome measures, but with specific studies including a range of other outcome measures.\n\nConclusionThe findings of this study have demonstrated that it is feasible to collate specific data elements recorded across a range of studies investigating a specific clinical condition in order to identify those elements which are most common among studies. These data may be of value for those establishing new studies and to allow researchers to rapidly identify studies collecting data of potential use hence minimising duplication and increasing data re-use and interoperability", + "category": "health informatics", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.05.20.20108126", @@ -4423,20 +4395,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.05.18.20086157", - "date": "2020-05-22", - "link": "https://medrxiv.org/cgi/content/short/2020.05.18.20086157", - "title": "COVID-19 in Great Britain: epidemiological and clinical characteristics of the first few hundred (FF100) cases: a descriptive case series and case control analysis", - "authors": "Nicola L Boddington; Andre Charlett; Suzanne Elgohari; Jemma L Walker; Helen Mcdonald; Chloe Byers; Laura Coughlan; Tatiana Garcia Vilaplana; Rosie Whillock; Mary Sinnathamby; Nikolaos Panagiotopoulos; Louise Letley; Pauline MacDonald; Roberto Vivancos; Obaghe Edeghere; Joseph Shingleton; Emma Bennett; Daniel J Grint; Helen Strongman; Kathryn E Mansfield; Christopher Rentsch; Caroline Minassian; Ian J Douglas; Rohini Mathur; Maria Peppa; Simon Cottrell; Jim McMenamin; Maria Zambon; Mary Ramsay; Gavin Dabrera; Vanessa Saliba; Jamie Lopez Bernal", - "affiliations": "Public Health England; Public Health England; Public Health England; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Public Health Wales; Public Health Scotland; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England", - "abstract": "ObjectivesFollowing detection of the first virologically-confirmed cases of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and underlying health conditions associated with infection of the first few hundred cases.\n\nMethodsInformation was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity, specificity and predictive value of symptoms and underlying health conditions associated with infection were conducted. Point prevalences of underlying health conditions among the UK general population were presented.\n\nFindingsThe majority of FF100 cases were imported (51.4%), of which the majority had recent travel to Italy (71.4%). 24.7% were secondary cases acquired mainly through household contact (40.4%). Children had lower odds of COVID-19 infection compared with the general population.\n\nThe clinical presentation of cases was dominated by cough, fever and fatigue. Non-linear relationships with age were observed for fever, and sensitivity and specificity of symptoms varied by age.\n\nConditions associated with higher odds of COVID-19 infection (after adjusting for age and sex) were chronic heart disease, immunosuppression and multimorbidity.\n\nConclusionThis study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study characterized underlying health conditions associated with infection and set relative risks in context with population prevalence estimates. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms.", - "category": "epidemiology", - "match_type": "exact", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.05.11.20098269", @@ -4633,6 +4591,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.04.09.20059865", + "date": "2020-04-14", + "link": "https://medrxiv.org/cgi/content/short/2020.04.09.20059865", + "title": "Forecasting the scale of the COVID-19 epidemic in Kenya", + "authors": "Samuel P C Brand; Rabia Aziza; Ivy K Kombe; Charles N Agoti; Joe Hilton; Kat S Rock; Andrea Parisi; D James Nokes; Matt Keeling; Edwine Barasa", + "affiliations": "University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme; Kenya Medical Research Institute, Wellcome Trust Research Programme; University of Warwick; University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme and University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme", + "abstract": "BackgroundThe first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya.\n\nMethodsWe developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak.\n\nResultsWe find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 -2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.", + "category": "infectious diseases", + "match_type": "exact", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.04.10.20059121", diff --git a/data/covid/preprints.json b/data/covid/preprints.json index 93f5f363..ae6b768f 100644 --- a/data/covid/preprints.json +++ b/data/covid/preprints.json @@ -167,20 +167,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2023.12.07.23299429", - "date": "2023-12-09", - "link": "https://medrxiv.org/cgi/content/short/2023.12.07.23299429", - "title": "Mechanisms underlying exercise intolerance in Long COVID: an accumulation of multi-system dysfunction", - "authors": "Alexandra Jamieson; Lamia Al Saikhan; Lamis Alghamdi; Lee Hamill Howes; Helen Purcell; Toby Hillman; Melissa J Heightman; Thomas A. Treibel; Michele Orini; Robert Midgley Bell; Marie Scully; Mark Hamer; Nishi Chaturvedi; Alun Hughes; Ronan Astin; Siana Jones", - "affiliations": "University College London; Imam Abdulrahman Bin Faisal University; University College London; University College London; University College London Hospitals NHS Foundation Trust; University College London Hospitals NHS Foundation Trust; UCLH; University College London; University College London; The Hatter Cardiovascular Institute, University College London; University College London Hospitals NHS Foundation Trust; UCL; University College London; UCL; University College London Hospitals NHS Foundation Trust; University College London", - "abstract": "The pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood.\n\nCases were recruited from a Long COVID clinic (N=32; 44{+/-}12y; 10(31%)men), and age/sex- matched healthy controls (HC) (N=19; 40{+/-}13y; 6(32%)men) from University College London staff and students. We assessed exercise performance, lung and cardiac function, vascular health, skeletal muscle oxidative capacity and autonomic nervous system (ANS) function. Key outcome measures for each physiological system were compared between groups using potential outcome means(95% confidence intervals) adjusted for potential confounders. Long COVID participant outcomes were compared to normative values.\n\nWhen compared to HC, cases exhibited reduced Oxygen Uptake Efficiency Slope (1847(1679,2016) vs (2176(1978,2373) ml/min, p=0.002) and Anaerobic Threshold (13.2(12.2,14.3) vs 15.6(14.4,17.2) ml/Kg/min, p<0.001), and lower oxidative capacity on near infrared spectroscopy ({tau}: 38.7(31.9,45.6) vs 24.6(19.1,30.1) seconds, p=0.001). In cases, ANS measures fell below normal limits in 39%.\n\nLong COVID is associated with reduced measures of exercise performance and skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology. There was evidence of attendant ANS dysregulation in a significant proportion. These multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers.\n\nKey PointsO_LIThe pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood.\nC_LIO_LIWe show that Long COVID is associated with reduced measures of exercise performance in line with previous work.\nC_LIO_LIIn Long COVID cases, we observed reduced skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology.\nC_LIO_LIWe also observed evidence of attendant autonomic nervous system (ANS) dysregulation in a significant proportion of Long COVID cases.\nC_LIO_LIThese multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers.\nC_LI", - "category": "cardiovascular medicine", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2023.12.06.23299601", @@ -573,6 +559,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2023.06.30.23292079", + "date": "2023-06-30", + "link": "https://medrxiv.org/cgi/content/short/2023.06.30.23292079", + "title": "Synthesis and new evidence from the PROTECT UK National Core Study: Determining occupational risks of SARS-CoV-2 infection and COVID-19 mortality", + "authors": "Sarah Rhodes; Sarah Beale; Mark Cherrie; William Mueller; Fiona Holland; Melissa Matz; Ioannis Basinas; Jack D Wilkinson; Matthew Gittins; Bernardine Farrell; Andrew Hayward; Neil Pearce; Martie van Tongeren", + "affiliations": "University of Manchester; University College London; Institute of Occupational Medicine; Institute of Occupational Medicine; University of Manchester; London School of Hygiene and Tropical Medicine; University of Manchester; University of Manchester; University of Manchester; University of Manchester; UCL; London School of Hygiene and Tropical Medicine; University of Manchester", + "abstract": "IntroductionThe PROTECT National Core Study was funded by the UK Health and Safety Executive (HSE) to investigate routes of transmission for SARS-CoV-2 and variation between settings.\n\nMethodsA workshop was organised in Oct 2022.We brought together evidence from five published epidemiological studies that compared risks of SARS-CoV-2 infection or COVID-19 mortality by occupation or sector funded by PROTECT relating to three non-overlapping data sets, plus additional unpublished analyses relating to the Omicron period. We extracted descriptive study level data and model results. We investigated risk across four pandemic waves using forest plots for key occupational groups by time-period.\n\nResultsResults were largely consistent across different studies with different expected biases. Healthcare and social care sectors saw elevated risks of SARS-CoV-2 infection and COVID-19 mortality early in the pandemic, but thereafter this declined and varied by specific occupational subgroup. The education sector saw sustained elevated risks of infection after the initial lockdown period with little evidence of elevated mortality.\n\nConclusionsIncreased in risk of infection and mortality were consistently observed for occupations in high risk sectors particularly during the early stage of the pandemic. The education sector showed a different pattern compared to the other high risk sectors, as relative risk of infections remained high in the later phased of the pandemic, although no increased in COVID-19 mortality (compared to low-risk occupations) was observed in this sector in any point during the pandemic.", + "category": "occupational and environmental health", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2023.06.29.23292043", @@ -937,6 +937,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2023.02.16.23286017", + "date": "2023-02-18", + "link": "https://medrxiv.org/cgi/content/short/2023.02.16.23286017", + "title": "Long-term outdoor air pollution and COVID-19 mortality in London: an individual-level analysis", + "authors": "Loes Charlton; Chris Gale; Jasper Morgan; Myer Glickman; Sean Beevers; Anna L Hansell; Vah\u00e9 Nafilyan", + "affiliations": "Office for National Statistics; Office for National Statistics; Office for National Statistics; Office for National Statistics; Imperial College London; University of Leicester; Office for National Statistics", + "abstract": "BackgroundThe risk of COVID-19 severity and mortality differs markedly by age, socio-demographic characteristics and pre-existing health status. Various studies have suggested that higher air pollution exposures also increase the likelihood of dying from COVID-19.\n\nObjectives: To assess the association between long-term outdoor air pollution (NO2, NOx, PM10 and PM2.5) concentrations and the risk of death involving COVID-19, using a large individual-level dataset.\n\nMethodsWe used comprehensive individual-level data from the Office for National Statistics Public Health Data Asset for September 2020 to January 2022 and London Air Quality Network modelled air pollution concentrations available for 2016. Using Cox proportional hazard regression models, we adjusted for potential confounders including age, sex, vaccination status, dominant virus variants, geographical factors (such as population density), ethnicity, area and household-level deprivation, and health comorbidities.\n\nResultsThere were 737,356 confirmed COVID-19 cases including 9,315 COVID-related deaths. When only adjusting for age, sex, and vaccination status, there was an increased risk of dying from COVID-19 with increased exposure to all air pollutants studied (NO2: HR 1.07 [95% confidence interval: 1.04-1.12] per 10 g/m3; NOx: 1.05[1.02-1.09] per 20 g/m3; PM10: 1.32[1.15-1.51] per 10 g/m3; PM2.5: 1.29[1.12-1.49] per 5 g/m3). However, after adjustment including ethnicity and socio-economic factors the HRs were close to unity (NO2: 0.98[0.90-1.06]; NOx: 0.99[0.94-1.04]; PM10: 0.95[0.74-1.22]; PM2.5: 0.90[0.67-1.20]). Additional adjustment for dominant variant or pre-existing health comorbidities did not alter the results.\n\nConclusionsObserved associations between long-term outdoor air pollution exposure and COVID-19 mortality in London are strongly confounded by geography, ethnicity and deprivation.\n\nSummaryUsing a large individual-level dataset, we found that a positive association between long-term outdoor air pollution and COVID-19 mortality in London did not persist after adjusting for confounders including population density, ethnicity and deprivation.", + "category": "respiratory medicine", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2023.02.10.23285717", @@ -1581,20 +1595,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.08.17.22278893", - "date": "2022-08-18", - "link": "https://medrxiv.org/cgi/content/short/2022.08.17.22278893", - "title": "Uptake of Sotrovimab for prevention of severe COVID-19 and its safety in the community in England", - "authors": "Martina Patone; Holly Tibble; Andrew JHL Snelling; Carol Coupland; Aziz Sheikh; Julia Hippisley-Cox", - "affiliations": "University of Oxford; University of Edinburgh; University of Oxford; University of Oxford; University of Edinburgh; University of Oxford", - "abstract": "Sotrovimab is a neutralising monoclonal antibody (nMAB), currently administrated in England to treat extremely clinically vulnerable COVID-19 patients. Trials have shown it to have mild or moderate side effects, however safety in real-world settings has not been yet evaluated. We used national databases to investigate its uptake and safety in community patients across England. We used a cohort study to describe uptake and a self-controlled case series design to evaluate the risks of 49 pre-specified suspected adverse events in the 2-28 days post-treatment. Between December 11, 2021 and May 24, 2022, there were 172,860 COVID-19 patients eligible for treatment. Of the 22,815 people who received Sotrovimab, 21,487 (94.2%) had a positive SARS-CoV-2 test and 5,999 (26.3%) were not on the eligible list. Between treated and untreated eligible individuals, the mean age (54.6, SD: 16.1 vs 54.1, SD: 18.3) and sex distribution (women: 60.9% vs 58.1%; men: 38.9% vs 41.1%) were similar. There were marked variations in uptake between ethnic groups, which was higher amongst Indian (15.0%; 95%CI 13.8, 16.3), Other Asian (13.7%; 95%CI 11.9, 15.8), White (13.4%; 95%CI 13.3, 13.6), and Bangladeshi (11.4%; 95%CI 8.8, 14.6); and lower amongst Black Caribbean individuals (6.4%; 95%CI 5.4, 7.5) and Black Africans (4.7%; 95%CI 4.1, 5.4). We found no increased risk of any of the suspected adverse events in the overall period of 2-28 days post-treatment, but an increased risk of rheumatoid arthritis (IRR 3.08, 95% CI 1.44, 6.58) and of systematic lupus erythematosus (IRR 5.15, 95% CI 1.60, 16.60) in the 2-3 days post-treatment, when we narrowed the risk period.\n\nFundingNational Institute of Health Research (Grant reference 135561)", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.08.13.22278733", @@ -1623,20 +1623,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.08.07.22278510", - "date": "2022-08-09", - "link": "https://medrxiv.org/cgi/content/short/2022.08.07.22278510", - "title": "Metabolomic and gut microbiome profiles across the spectrum of community-based COVID and non-COVID disease: A COVID-19 Biobank study.", - "authors": "Marc F \u00d6sterdahl; Ronan Whiston; Carole H Sudre; Francesco Asnicar; Nathan J Cheetham; Aitor Blanco Miguez; Vicky Bowyer; Michela Antonelli; Olivia Snell; Liane dos Santos Canas; Christina Hu; Jonathan Wolf; Cristina Menni; Michael Malim; Deborah Hart; Tim Spector; Sarah Berry; Nicola Segata; Katie Doores; Sebastien Ourselin; Emma L Duncan; Claire J Steves", - "affiliations": "King's College London; King's College London; King's College London; University of Trento; King's College London; University of Trento; King's College London; King's College London; King's College London; King's College London; ZOE Global Ltd.; ZOE Global Ltd.; King's College London; King's College London; King's College London; King's College London; King's College London; University of Trento; King's College London; King's College London; King's College London; King's College London", - "abstract": "Whilst many with SARS-CoV-2 infection have mild disease, managed in the community, individuals with cardiovascular risk factors experienced often more severe acute disease, requiring hospitalisation. Increasing concern has also developed over long symptom duration in many individuals, including the majority who managed acutely in the community. Risk factors for long symptom duration, including biological variables, are still poorly defined.\n\nWe examine post-illness metabolomic and gut-microbiome profiles, in community-dwelling participants with SARS-CoV-2, ranging from asymptomatic illness to Post-COVID Syndrome, and participants with prolonged non-COVID-19 illnesses. We also assess a pre-established metabolomic biomarker score for its association with illness duration.\n\nWe found an atherogenic-dyslipidaemic metabolic profile, and greater biomarker scores, associated with longer illness, both in individuals with and without SARS-CoV-2 infection. We found no association between illness duration and gut microbiome in convalescence.\n\nFindings highlight the potential role of cardiometabolic dysfunction to the experience of long illness duration, including after COVID-19.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.08.08.22278493", @@ -1708,17 +1694,17 @@ "affiliation_similarity": 100 }, { - "site": "medRxiv", - "doi": "10.1101/2022.07.20.22277838", - "date": "2022-07-21", - "link": "https://medrxiv.org/cgi/content/short/2022.07.20.22277838", - "title": "National and regional prevalence of SARS-CoV-2 antibodies in primary and secondary school children in England: the School Infection Survey, a national open cohort study, November 2021", - "authors": "Annabel A Powell; Georgina Ireland; Rebecca Leeson; Andrea Lacey; Ben Ford; John Poh; Samreen Ijaz; Justin Shute; Peter Cherepanov; Richard Tedder; Christian Bottomley; Fiona Dawe; Punam Mangtani; Peter Jones; Patrick Nguipdop-Djomo; Shamez Ladhani", - "affiliations": "UK Health Security Agency; UK Health Security Agency; Office for National Statistics; Office for National Statistics; Office for National Statistics; UK Health Security Agency; UK Health Security Agency; UK Health Security Agency; Imperial College London; Francis Crick Institute; London School of Hygiene & Tropical Medicine; Office for National Statistics; London School of Hygiene & Tropical Medicine; Office for National Statistics; London School of Hygiene & Tropical Medicine; UK Health Security Agency", - "abstract": "BackgroundRisk factors for infection and, therefore, antibody positivity rates will be different in children compared to adults. We aim to estimate national and regional prevalence of SARS-CoV-2 antibodies in primary (4-11-year-olds) and secondary (11-15-year-olds) school children between 10 November and 10 December 2021.\n\nMethodsCross-sectional surveillance in England using two stage sampling, firstly stratifying into regions and selecting local authorities, then selecting schools according to a stratified sample within selected local authorities. Participants were sampled using a novel oral fluid validated assay for SARS-CoV-2 spike and nucleocapsid IgG antibodies.\n\nResults4,980 students from 117 state-funded schools (2,706 from 83 primary schools, 2,274 from 34 secondary schools) provided a valid sample. After weighting for age, sex and ethnicity, and adjusting for assay accuracy, the national prevalence of SARS-CoV-2 antibodies in primary school students, who were all unvaccinated, was 40.1% (95%CI; 37.3-43.0). Antibody prevalence increased with age (p<0.001) and were higher in urban than rural schools (p=0.01). In secondary school students, the adjusted, weighted national prevalence of SARS-CoV-2 antibodies was 82.4% (95%CI; 79.5-85.1); including 57.5% (95%CI; 53.9-61.1) in unvaccinated and 97.5% (95%CI; 96.1-98.5) in vaccinated students. Antibody prevalence increased with age (p<0.001), and was not significantly different in urban versus rural students (p=0.1).\n\nConclusionsUsing a validated oral fluid assay, we estimated national and regional seroprevalence of SARS-CoV-2 antibodies in primary and secondary school students. In November 2021, 40% of primary school students and nearly all secondary school students in England had SARS-CoV2 antibodies through a combination of natural infection and vaccination.", - "category": "epidemiology", + "site": "bioRxiv", + "doi": "10.1101/2022.07.26.501570", + "date": "2022-07-26", + "link": "https://biorxiv.org/cgi/content/short/2022.07.26.501570", + "title": "Primary Omicron infection elicits weak antibody response but robust cellularimmunity in children", + "authors": "Alexander C Dowell; Tara Lancaster; Rachel Bruton; Georgina Ireland; Christopher Bentley; Panagiota Sylla; Jianmin Zuo; Sam Scott; Azar Jardin; Jusnara Begum; Thomas Roberts; Christine Stephens; Shabana Ditta; Rebecca Shepherdson; Annable Powell; Andrew Brent; Bernadette Brent; Frances Baawuah; Ifeanyichukwu Okike; Joanna Beckmann; Shazaad Ahmad; Felicity Aiano; Joanna Garstang; Mary Ramsay; Rafaq Azad; Dagmar Waiblinger; Brian Willet; John Wright; Shamez Ladhani; Paul Moss", + "affiliations": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE; Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; East London NHS Foundation Trust, 9 Allie Street, London E1 8DE, UK; Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Birmingham Community Healthcare NHS Trust, Holt Street, Aston B7 4BN, UK; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK; Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK.; Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom; Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK", + "abstract": "Omicron variants of SARS-CoV-2 are globally dominant and infection rates are very high in children. We determined immune responses following Omicron BA.1/2 infection in children aged 6-14 years and related this to prior and subsequent SARS-CoV-2 infection or vaccination. Primary Omicron infection elicited a weak antibody response with poor functional neutralizing antibodies. Subsequent Omicron reinfection or COVID-19 vaccination elicited increased antibody titres with broad neutralisation of Omicron subvariants. Prior pre-Omicron SARS-CoV-2 virus infection or vaccination primed for robust antibody responses following Omicron infection but these remained primarily focussed against ancestral variants. Primary Omicron infection thus elicits a weak antibody response in children which is boosted after reinfection or vaccination. Cellular responses were robust and broadly equivalent in all groups, providing protection against severe disease irrespective of SARS-CoV-2 variant. Immunological imprinting is likely to act as an important determinant of long-term humoral immunity, the future clinical importance of which is unknown.", + "category": "immunology", "match_type": "fuzzy", - "author_similarity": 92, + "author_similarity": 100, "affiliation_similarity": 100 }, { @@ -1805,6 +1791,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.06.18.22276437", + "date": "2022-06-19", + "link": "https://medrxiv.org/cgi/content/short/2022.06.18.22276437", + "title": "A patient-centric characterization of systemic recovery from SARS-CoV-2 infection", + "authors": "H\u00e9l\u00e8ne Ruffieux; Aimee Hanson; Samantha Lodge; Nathan Lawler; Luke Whiley; Nicola Gray; Tui Nolan; Laura Bergamaschi; Federica Mescia; - CITIID-NIHR COVID BioResource Collaboration; Nathalie Kingston; John Bradley; Elaine Holmes; Julien Wist; Jeremy Nicholson; Paul Lyons; Kenneth Smith; Sylvia Richardson; Glenn Bantug; Christoph Hess", + "affiliations": "University of Cambridge; University of Cambridge; Murdoch University; Murdoch University; Murdoch University; Murdoch University; University of Cambridge; University of Cambridge; University of Cambridge; ; University of Cambridge; University of Cambridge; Murdoch University; Murdoch University; Murdoch University; University of Cambridge; University of Cambridge; University of Cambridge; University and University Hospital Basel; University of Cambridge", + "abstract": "The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data, covering a year post disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct \"systemic recovery\" profiles with specific progression and resolution of the inflammatory, immune, metabolic and clinical responses, over weeks to several months after infection. In particular, we found a strong intra-patient temporal covariation of innate immune cell numbers, kynurenine- and host lipid-metabolites, which suggested candidate immunometabolic pathways putatively influencing restoration of homeostasis, the risk of death and of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery on the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-systemic-recovery-prediction-app, designed to test our findings prospectively.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/22276437v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (38K):\norg.highwire.dtl.DTLVardef@12b0afborg.highwire.dtl.DTLVardef@ddf3b2org.highwire.dtl.DTLVardef@1aa670forg.highwire.dtl.DTLVardef@5415ec_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.06.17.22276433", @@ -1903,20 +1903,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.06.08.22276134", - "date": "2022-06-14", - "link": "https://medrxiv.org/cgi/content/short/2022.06.08.22276134", - "title": "Implementation of a digital early warning score (NEWS2) in a cardiac specialist and general hospital settings in the COVID-19 pandemic: A qualitative study.", - "authors": "Baneen Alhmoud; Timothy Bonicci; Riyaz Patel; Daniel Melley; Louise Hicks; Amitava Banerjee", - "affiliations": "University College London, University College London Hospital, Barts Health Trust.; University College London, University College London Hospital; University College London, University College London Hospital.; Barts Health Trust; Barts Health Trust; University College London, University College London Hospital, Barts Health Trust.", - "abstract": "ObjectivesTo evaluate implementation of EHR-integrated NEWS2 in a cardiac care setting and a general hospital setting in the COVID-19 pandemic.\n\nDesignThematic analysis of qualitative semi-structured interviews with purposefully sampled nurses and managers, as well as online surveys.\n\nSettingsSpecialist cardiac hospital (St Bartholomews Hospital) and General teaching hospital (University College London Hospital).\n\nParticipantsEleven nurses and managers from cardiology, cardiac surgery, oncology, and intensive care wards (St Bartholomews) and medical, haematology and intensive care wards (UCLH) were interviewed and sixty-seven were surveyed online.\n\nResultsThree main themes emerged: (i) Implementing NEWS2 challenges and supports; (ii) Value of NEWS2 to alarm, escalate, particularly during the pandemic; and (iii) Digitalisation: EHR integration and automation. The value of NEWS2 was partly positive in escalation, yet there were concerns by nurses who undervalued NEWS2 particularly in cardiac care. Challenges, like clinicians behaviours, lack of resources and training and the perception of NEWS2 value, limit the success of this implementation. Changes in guidelines in the pandemic have led to overlooking NEWS2. EHR integration and automated monitoring are improvement solutions that are not fully employed yet.\n\nConclusionWhether in specialist or general medical settings, the health professionals implementing EWS in healthcare face cultural and systems related challenges to adopting NEWS2 and digital solutions. The validity of NEWS2 in specialised settings and complex conditions is not yet apparent and requires comprehensive validation. EHRs integration and automation are powerful tools to facilitate NEWS2 if its principles are reviewed and rectified, and resources and training are accessible. Further examination of implementation from the cultural and automation domains are needed.", - "category": "health informatics", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.06.13.22276316", @@ -2379,20 +2365,6 @@ "author_similarity": 100, "affiliation_similarity": 91 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.04.03.22272610", - "date": "2022-04-04", - "link": "https://medrxiv.org/cgi/content/short/2022.04.03.22272610", - "title": "Cardiac impairment in Long Covid 1-year post-SARS-CoV-2 infection", - "authors": "Adriana Roca-Fernandez; Malgorzata Wamil; Alison Telford; Valentina Carapella; Alessandra Borlotti; David Monteiro; Helena Thomaides-Brears; Matthew D Kelly; Andrea Dennis; Rajarshi Banerjee; Matthew Robson; Michael Brady; Gregory Lip; Sacha Bull; Melissa J Heightman; Ntobeko Ntusi; Amitava Banerjee", - "affiliations": "Perspectum Diagnostics; Great Western Hospital Foundation NHS Trust, Swindon, UK; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; Perspectum Ltd; University of Liverpool; Royal Berkshire Hospital, Reading; UCLH; University of Cape Town, Cape Town, South Africa; University College London", - "abstract": "BackgroundLong Covid is associated with multiple symptoms and impairment in multiple organs. Cardiac impairment has been reported to varying degrees by varying methodologies in cross-sectional studies. Using cardiac magnetic resonance (CMR), we investigated the 12-month trajectory of cardiac impairment in individuals with Long Covid.\n\nMethods534 individuals with Long Covid underwent baseline CMR (T1 and T2 mapping, cardiac mass, volumes, function, and strain) and multi-organ MRI at 6 months (IQR 4.3,7.3) since first post-COVID-19 symptoms and 330 were rescanned at 12.6 (IQR 11.4, 14.2) months if abnormal findings were reported at baseline. Symptoms, standardised questionnaires, and blood samples were collected at both timepoints. Cardiac impairment was defined as one or more of: low left or right ventricular ejection fraction (LVEF and RVEF), high left or right ventricular end diastolic volume (LVEDV and RVEDV), low 3D left ventricular global longitudinal strain (GLS), or elevated native T1 in [≥]3 cardiac segments. A significant change over time was reported by comparison with 92 healthy controls.\n\nResultsThe technical success of this multiorgan assessment in non-acute settings was 99.1% at baseline, and 98.3% at follow up, with 99.6% and 98.8% for CMR respectively. Of individuals with Long Covid, 102/534 [19%] had cardiac impairment at baseline; 71/102 had complete paired data at 12 months. Of those, 58% presented with ongoing cardiac impairment at 12 months. High sensitivity cardiac troponin I and B-type natriuretic peptide were not predictive of CMR findings, symptoms, or clinical outcomes. At baseline, low LVEF, high RVEDV and low GLS were associated with cardiac impairment. Low LVEF at baseline was associated with persistent cardiac impairment at 12 months.\n\nConclusionCardiac impairment, other than myocarditis, is present in 1 in 5 individuals with Long Covid at 6 months, persisting in over half of those at 12 months. Cardiac-related blood biomarkers are unable to identify cardiac impairment in Long COVID. Subtypes of disease (based on symptoms, examination, and investigations) and predictive biomarkers are yet to be established. Interventional trials with pre-specified subgroup analyses are required to inform therapeutic options.", - "category": "cardiovascular medicine", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.03.29.22272997", @@ -2589,20 +2561,6 @@ "author_similarity": 94, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2022.03.10.22272081", - "date": "2022-03-12", - "link": "https://medrxiv.org/cgi/content/short/2022.03.10.22272081", - "title": "Interstitial lung damage following COVID-19 hospitalisation: an interim analysis of the UKILD Post-COVID study.", - "authors": "I Stewart; J Jacob; PM George; PL Molyneaux; JC Porter; RJ Allen; JK Baillie; SL Barratt; P Beirne; SM Bianchi; JF Blaikley; J Chalmers; RC Chambers; N Chadhuri; C Coleman; G Collier; EK Denneny; A Docherty; O Elneima; RA Evans; L Fabbri; MA Gibbons; FV Gleeson; B Gooptu; NJ Greening; B Guillen Guio; IP Hall; NA Hanley; V Harris; E Harrison; M Heightman; TE Hillman; A Horsley; L Houchen-Wolloff; I Jarrold; SR Johnson; MG Jones; F Khan; R Lawson; OC Leavy; N Lone; M Marks; H McAuley; P Mehta; E Omer; D Parekh; K Piper Hanley; M Plate; J Pearl; K Poinasamy; JK Quint; B Raman; M Richardson; P Rivera-Ortega; L Saunders; R Saunders; MG Semple; M Sereno; A Shikotra; AJ Simpson; A Singapuri; DJF Smith; M Spears; LG Spencer; S Stanel; D Thickett; AAR Thompson; M Thorpe; R Thwaites; SLF Walsh; S Walker; ND Weatherley; M Weeks; JM Wild; DG Wootton; CE Brightling; LP Ho; LV Wain; RG Jenkins", - "affiliations": "National Heart & Lung Institute, Imperial College London; Respiratory Medicine, University College London; Royal Brompton and Harefield NHS Foundation Trust; National Heart & Lung Institute, Imperial College London; University College London; University of Leicester; University of Edinburgh; North Bristol NHS Trust; Leeds Teaching Hospitals & University of Leeds; Sheffield Teaching Hospitals NHS Foundation Trust; University of Manchester; University of Dundee; Respiratory Medicine, University College London; University of Manchester; University of Nottingham; University of Sheffield; University College London; University of Edinburgh; University Hospitals of Leicester NHS Trust; University Hospitals of Leicester NHS Trust; National Heart & Lung Institute, Imperial College London; Royal Devon and Exeter NHS Foundation Trust; Oxford University Hospitals NHS Foundation Trust; University of Leicester; University of Leicester; University of Leicester; University of Nottingham; University of Manchester; University Hospitals of Leicester NHS Trust; University of Edinburgh; University College London Hospital; University College London Hospital; University of Manchester; University Hospitals of Leicester NHS Trust; Asthma UK British Lung Foundation; University of Nottingham; Faculty of Medicine, University of Southampton; University of Nottingham; Sheffield Teaching Hospitals NHS Foundation Trust; University of Leicester; Usher Institute, University of Edinburgh; University College London Hospital; University of Leicester; University College London Hospital; University of Leicester; University of Birmingham; University of Manchester; University College London Hospital; University of Leicester; British Lung Foundation; National Heart & Lung Institute, Imperial College London; University of Oxford; University of Leicester; University of Manchester; University of Sheffield; University of Leicester; Liverpool University; University of Leicester; University Hospitals of Leicester NHS Trust; Newcastle University; University of Leicester; Royal Brompton and Harefield NHS Foundation Trust; Perth Royal Infirmary, NHS Tayside; Liverpool University Hospitals NHS Foundation Trust; University of Manchester; University of Birmingham; University of Sheffield; University of Edinburgh; National Heart & Lung Institute, Imperial College London; National Heart & Lung Institute, Imperial College London; Sheffield Teaching NHS Foundation Trust; Sheffield Teaching NHS Foundation Trust; National Heart & Lung Institute, Imperial College London; Sheffield Teaching NHS Foundation Trust; University of Liverpool; University Hospitals of Leicester NHS Trust; University of Oxford; University of Leicester; National Heart & Lung Institute, Imperial College London", - "abstract": "IntroductionShared characteristics between COVID-19 and pulmonary fibrosis, including symptoms, genetic architecture, and circulating biomarkers, suggests interstitial lung disease (ILD) development may be associated with SARS-CoV-2 infection.\n\nMethodsThe UKILD Post-COVID study planned interim analysis was designed to stratify risk groups and estimate the prevalence of Post-COVID Interstitial Lung Damage (ILDam) using the Post-HOSPitalisation COVID-19 (PHOSP-COVID) Study. Demographics, radiological patterns and missing data were assessed descriptively. Bayes binomial regression was used to estimate the risk ratio of persistent lung damage >10% involvement in linked, clinically indicated CT scans. Indexing thresholds of percent predicted DLco, chest X-ray findings and severity of admission were used to generate risk strata. Number of cases within strata were used to estimate the amount of suspected Post-COVID ILDam.\n\nResultsA total 3702 people were included in the UKILD interim cohort, 2406 completed an early follow-up research visit within 240 days of discharge and 1296 had follow-up through routine clinical review. We linked the cohort to 87 clinically indicated CTs with visually scored radiological patterns (median 119 days from discharge; interquartile range 83 to 155, max 240), of which 74 people had ILDam. ILDam was associated with abnormal chest X-ray (RR 1.21 95%CrI 1.05; 1.40), percent predicted DLco<80% (RR 1.25 95%CrI 1.00; 1.56) and severe admission (RR 1.27 95%CrI 1.07; 1.55). A risk index based on these features suggested 6.9% of the interim cohort had moderate to very-high risk of Post-COVID ILDam. Comparable radiological patterns were observed in repeat scans >90 days in a subset of participants.\n\nConclusionThese interim data highlight that ILDam was not uncommon in clinically indicated thoracic CT up to 8 months following SARS-CoV-2 hospitalisation. Whether the ILDam will progress to ILD is currently unknown, however health services should radiologically and physiologically monitor individuals who have Post-COVID ILDam risk factors.", - "category": "respiratory medicine", - "match_type": "fuzzy", - "author_similarity": 91, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2022.03.09.22272098", @@ -2785,6 +2743,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.02.04.22270479", + "date": "2022-02-06", + "link": "https://medrxiv.org/cgi/content/short/2022.02.04.22270479", + "title": "Comparative effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections: A time-varying cohort analysis using trial emulation in the Virus Watch community cohort", + "authors": "Vincent Nguyen; Alexei Yavlinsky; Sarah Beale; Susan J Hoskins; Vasileios J Lampos; Isobel Braithwaite; Thomas Edward Byrne; Wing Lam Erica Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan Mathew Dwight Navaratnam; Parth Patel; Madhumita Shrotri; Sophie Weber; Andrew Hayward; Robert W Aldridge", + "affiliations": "University College London; University College London; University College London; Univerity College London; University College London; University College London; University College London; University College London, London School of Hygiene &Tropical Medicine; UCL, London School of Hygiene & Tropical Medicine; University College London; University College London; University College London; University College London; Univeristy College London; University College London; University College London; University College London", + "abstract": "ImportanceThe Omicron (B.1.1.529) variant has increased SARs-CoV-2 infections in double vaccinated individuals globally, particularly in ChAdOx1 recipients. To tackle rising infections, the UK accelerated booster vaccination programmes used mRNA vaccines irrespective of an individuals primary course vaccine type with booster doses rolled out according to clinical priority. There is limited understanding of the effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections and how time-varying confounders can impact the evaluations comparing different vaccines as primary courses for mRNA boosters.\n\nObjectiveTo evaluate the comparative effectiveness of ChAdOx1 versus BNT162b2 as primary doses against SARs-CoV-2 in booster vaccine recipients whilst accounting for time-varying confounders.\n\nDesignTrial emulation was used to reduce time-varying confounding-by-indication driven by prioritising booster vaccines based upon age, vulnerability and exposure status e.g. healthcare worker. Trial emulation was conducted by meta-analysing eight cohort results whose booster vaccinations were staggered between 16/09/2021 to 05/01/2022 and followed until 23/01/2022. Time from booster vaccination until SARS-CoV-2 infection, loss of follow-up or end-of-study was modelled using Cox proportional hazards models for each cohort and adjusted for age, sex, minority ethnic status, clinically vulnerability, and deprivation.\n\nSettingProspective observational study using the Virus Watch community cohort in England and Wales.\n\nParticipantsPeople over the age of 18 years who had their booster vaccination between 16/09/2021 to 05/01/2022 without prior natural immunity.\n\nExposuresChAdOx1 versus BNT162b2 as a primary dose, and an mRNA booster vaccine.\n\nResultsAcross eight cohorts, 19,692 mRNA vaccine boosted participants were analysed with 12,036 ChAdOx1 and 7,656 BNT162b2 primary courses with a median follow-up time of 73 days (IQR:54-90). Median age, clinical vulnerability status and infection rates fluctuate through time. 7.2% (n=864) of boosted adults with ChAdOx1 primary course experienced a SARS-CoV-2 infection compared to 7.6% (n=582) of those with BNT162b2 primary course during follow-up. The pooled adjusted hazard ratio was 0.99 [95%CI:0.88-1.11], demonstrating no difference between the incidence of SARs-CoV-2 infections based upon the primary vaccine course.\n\nConclusion and RelevanceIn mRNA boosted individuals, we found no difference in protection comparing those with a primary course of BNT162b2 to those with aChAdOx1 primary course. This contrasts with pre-booster findings where previous research shows greater effectiveness of BNT162b2 than ChAdOx1 in preventing infection.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.02.01.22270269", @@ -2967,6 +2939,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2022.01.13.22268948", + "date": "2022-01-14", + "link": "https://medrxiv.org/cgi/content/short/2022.01.13.22268948", + "title": "Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: Insights from Rapid COVID-19 Diagnosis by Adversarial Learning", + "authors": "Jenny Yang; Andrew AS Soltan; Yang Yang; David A Clifton", + "affiliations": "The University of Oxford; University of Oxford; The University of Oxford; The University of Oxford", + "abstract": "Machine learning is becoming increasingly prominent in healthcare. Although its benefits are clear, growing attention is being given to how machine learning may exacerbate existing biases and disparities. In this study, we introduce an adversarial training framework that is capable of mitigating biases that may have been acquired through data collection or magnified during model development. For example, if one class is over-presented or errors/inconsistencies in practice are reflected in the training data, then a model can be biased by these. To evaluate our adversarial training framework, we used the statistical definition of equalized odds. We evaluated our model for the task of rapidly predicting COVID-19 for patients presenting to hospital emergency departments, and aimed to mitigate regional (hospital) and ethnic biases present. We trained our framework on a large, real-world COVID-19 dataset and demonstrated that adversarial training demonstrably improves outcome fairness (with respect to equalized odds), while still achieving clinically-effective screening performances (NPV>0.98). We compared our method to the benchmark set by related previous work, and performed prospective and external validation on four independent hospital cohorts. Our method can be generalized to any outcomes, models, and definitions of fairness.", + "category": "health informatics", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2022.01.05.21268323", @@ -3037,20 +3023,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.23.21268276", - "date": "2021-12-25", - "link": "https://medrxiv.org/cgi/content/short/2021.12.23.21268276", - "title": "Risk of myocarditis following sequential COVID-19 vaccinations by age and sex", - "authors": "Martina Patone; Winnie Xue Mei; Lahiru Handunnetthi; Sharon Dixon; Francesco Zaccardi; Manu Shankar-Hari; Peter Watkinson; Kamlesh Khunti; Anthony Harnden; Carol AC Coupland; Keith M. Channon; Nicholas L Mills; Aziz Sheikh; Julia Hippisley-Cox", - "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Leicester; University of Edinburgh; University of Oxford; University of Leicester; University of Oxford; University of Oxford; University of Oxford; University of Edinburgh; University of Edinburgh; University of Oxford", - "abstract": "In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy.\n\nFundingHealth Data Research UK.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.23.21268279", @@ -3247,20 +3219,6 @@ "author_similarity": 100, "affiliation_similarity": 92 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.12.14.21267460", - "date": "2021-12-15", - "link": "https://medrxiv.org/cgi/content/short/2021.12.14.21267460", - "title": "Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales", - "authors": "Sarah Beale; Susan J Hoskins; Thomas Edward Byrne; Erica Wing Lam Fong; Ellen Fragaszy; Cyril Geismar; Jana Kovar; Annalan MD Navaratnam; Vincent Nguyen; Parth Patel; Alexei Yavlinsky; Anne Johnson; Martie Van Tongeren; Robert W Aldridge; Andrew Hayward", - "affiliations": "University College London; Univerity College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University of Manchester; University College London; University College London", - "abstract": "BackgroundWorkers differ in their risk of SARS-CoV-2 infection according to their occupation, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase.\n\nMethodsData from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR).\n\nFindingsIncreased risk was seen in nurses (aRR=1.44, 1.25-1.65; AF=30%, 20-39%), doctors (aRR=1.33, 1.08-1.65; AF=25%, 7-39%), carers (1.45, 1.19-1.76; AF=31%, 16-43%), primary school teachers (aRR=1.67, 1.42-1.96; AF=40%, 30-49%), secondary school teachers (aRR=1.48, 1.26-1.72; AF=32%, 21-42%), and teaching support occupations (aRR=1.42, 1.23-1.64; AF=29%, 18-39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020 - May 2021) and attenuated later (June - October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves.\n\nInterpretationOccupational differentials in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.12.13.21267723", @@ -3277,14 +3235,14 @@ }, { "site": "medRxiv", - "doi": "10.1101/2021.12.09.21267516", - "date": "2021-12-09", - "link": "https://medrxiv.org/cgi/content/short/2021.12.09.21267516", - "title": "Changes in the trajectory of Long Covid symptoms following COVID-19 vaccination: community-based cohort study", - "authors": "Daniel Ayoubkhani; Charlotte Bermingham; Koen B Pouwels; Myer Glickman; Vahe Nafilyan; Francesco Zaccardi; Kamlesh Khunti; Nisreen A Alwan; Ann Sarah Walker", - "affiliations": "Office for National Statistics; Office for National Statistics; University of Oxford; Office for National Statistics; Office for National Statistics; University of Leicester; University of Leicester; University of Southampton; University of Oxford", - "abstract": "ObjectiveTo estimate associations between COVID-19 vaccination and Long Covid symptoms in adults who were infected with SARS-CoV-2 prior to vaccination.\n\nDesignObservational cohort study using individual-level interrupted time series analysis.\n\nSettingRandom sample from the community population of the UK.\n\nParticipants28,356 COVID-19 Infection Survey participants (mean age 46 years, 56% female, 89% white) aged 18 to 69 years who received at least their first vaccination after test-confirmed infection.\n\nMain outcome measuresPresence of long Covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021.\n\nResultsMedian follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (84% of participants). First vaccination was associated with an initial 12.8% decrease (95% confidence interval: -18.6% to -6.6%) in the odds of Long Covid, but increasing by 0.3% (-0.6% to +1.2%) per week after the first dose. Second vaccination was associated with an 8.8% decrease (-14.1% to -3.1%) in the odds of Long Covid, with the odds subsequently decreasing by 0.8% (-1.2% to -0.4%) per week. There was no statistical evidence of heterogeneity in associations between vaccination and Long Covid by socio-demographic characteristics, health status, whether hospitalised with acute COVID-19, vaccine type (adenovirus vector or mRNA), or duration from infection to vaccination.\n\nConclusionsThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second dose. Vaccination may contribute to a reduction in the population health burden of Long Covid, though longer follow-up time is needed.\n\nSummary boxWhat is already known on this topic\n\nO_LICOVID-19 vaccines are effective at reducing rates of SARS-CoV-2 infection, transmission, hospitalisation, and death\nC_LIO_LIThe incidence of Long Covid may be reduced if infected after vaccination, but the relationship between vaccination and pre-existing long COVID symptoms is unclear, as published studies are generally small and with self-selected participants\nC_LI\n\nWhat this study adds\n\nO_LIThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second dose\nC_LIO_LIThere was no evidence of differences in this relationship by socio-demographic characteristics, health-related factors, vaccine type, or duration from infection to vaccination\nC_LIO_LIAlthough causality cannot be inferred from this observational evidence, vaccination may contribute to a reduction in the population health burden of Long Covid; further research is needed to understand the biological mechanisms that may ultimately contribute to the development of therapeutics for Long Covid\nC_LI", - "category": "epidemiology", + "doi": "10.1101/2021.12.08.21267458", + "date": "2021-12-08", + "link": "https://medrxiv.org/cgi/content/short/2021.12.08.21267458", + "title": "Relative contribution of leaving home for work or education, transport, shopping and other activities on risk of acquiring COVID-19 infection outside the household in the second wave of the pandemic in England and Wales", + "authors": "Susan J Hoskins; Sarah Beale; Robert W Aldridge; Colette Smith; Clare French; Alex Yavlinksky; Vincent Nguyen; Thomas Edward Byrne; Jana Kovar; Ellen Fragaszy; W Fong; Cyril Geismar; Parth Patel; Ann Johnson; Andrew Edward Hayward", + "affiliations": "Univerity College London; University College London; UCL; University College London; University of Bristol; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; University College London; UCL", + "abstract": "BackgroundWith the potential for and emergence of new COVID-19 variants, such as the reportedly more infectious Omicron, and their potential to escape the existing vaccines, understanding the relative importance of which non-household activities increase risk of acquisition of COVID-19 infection is vital to inform mitigation strategies.\n\nMethodsWithin an adult subset of the Virus Watch community cohort study, we sought to identify which non-household activities increased risk of acquisition of COVID-19 infection and which accounted for the greatest proportion of non-household acquired COVID-19 infections during the second wave of the pandemic. Among participants who were undertaking antibody tests and self-reporting PCR and lateral flow tests taken through the national testing programme, we identified those who were thought to be infected outside the household during the second wave of the pandemic. We used exposure data on attending work, using public or shared transport, using shops and other non-household activities taken from monthly surveys during the second wave of the pandemic. We used multivariable logistic regression models to assess the relative independent contribution of these exposures on risk of acquiring infection outside the household. We calculated Adjusted Population Attributable Fractions (APAF - the proportion of non-household transmission in the cohort thought to be attributable to each exposure) based on odds ratios and frequency of exposure in cases.\n\nResultsBased on analysis of 10475 adult participants including 874 infections acquired outside the household, infection was independently associated with: leaving home for work (AOR 1.20 (1.02 - 1.42) p=0.0307, APAF 6.9%); public transport use (AOR for use more than once per week 1.82 (1.49 - 2.23) p<0.0001, APAF for public transport 12.42%); and shopping (AOR for shopping more than once per week 1.69 (1.29 - 2.21) P=0.0003, APAF for shopping 34.56%). Other non-household activities such as use of hospitality and leisure venues were rare due to restrictions and there were no significant associations with infection risk.\n\nConclusionsA high proportion of the second wave of the pandemic was spent under conditions where people were being advised to work from home where possible, and to minimize exposure to shops, and a wide range of other businesses were subject to severe restrictions. Vaccines were being rolled out to high-risk groups. During this time, going to work was an important risk factor for infection but public transport use likely accounted for a lot of this risk. Only a minority of the cohort left home for work or used public or shared transport. By contrast, the majority of participants visited shops and this activity accounted for about one-third of non-household transmission.", + "category": "infectious diseases", "match_type": "fuzzy", "author_similarity": 100, "affiliation_similarity": 100 @@ -3555,6 +3513,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.11.05.21265977", + "date": "2021-11-09", + "link": "https://medrxiv.org/cgi/content/short/2021.11.05.21265977", + "title": "Waning, Boosting and a Path to Endemicity for SARS-CoV-2.", + "authors": "Matt J Keeling; Amy C Thomas; Edward M Hill; Robin N Thompson; Louise Dyson; Michael Tildesley; Sam Moore", + "affiliations": "University of Warwick; University of Bristol; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick", + "abstract": "In many countries, an extensive vaccination programme has substantially reduced the public-health impact of SARS-CoV-2, limiting the number of hospital admissions and deaths compared to an unmitigated epidemic. Ensuring a low-risk transition from the current situation to one in which SARS-CoV-2 is endemic requires maintenance of high levels of population immunity. The observed waning of vaccine efficacy over time suggests that booster doses may be required to maintain population immunity especially in the most vulnerable groups. Here, using data and models for England, we consider the dynamics of COVID-19 over a two-year time-frame, and the role that booster vaccinations can play in mitigating the worst effects. We find that boosters are necessary to suppress the imminent wave of infections that would be generated by waning vaccine efficacy. Projecting further into the future, the optimal deployment of boosters is highly sensitive to their long-term action. If protection from boosters wanes slowly (akin to protection following infection) then a single booster dose to the over 50s may be all that is needed over the next two-years. However, if protection wanes more rapidly (akin to protection following second dose vaccination) then annual or even biannual boosters are required to limit subsequent epidemic peaks an reduce the pressure on public health services.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.11.05.21264590", @@ -3919,6 +3891,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.09.13.21262360", + "date": "2021-09-16", + "link": "https://medrxiv.org/cgi/content/short/2021.09.13.21262360", + "title": "Efficacy of two doses of COVID-19 vaccine against severe COVID-19 in those with risk conditions and residual risk to the clinically extremely vulnerable: the REACT-SCOT case-control study", + "authors": "Paul M McKeigue; David McAllister; Chris Robertson; Sharon J Hutchinson; Stuart McGurnaghan; Diane Stockton; Helen M Colhoun", + "affiliations": "University of Edinburgh; University of Glasgow; University of Strathclyde; Glasgow Caledonian University; University of Edinburgh; Public Health Scotland; University of Edinburgh", + "abstract": "ObjectivesTo determine whether COVID-19 efficacy varies with clinical risk category and to investigate risk factors for severe COVID-19 in those who have received two doses of vaccine.\n\nDesignMatched case-control study (REACT-SCOT).\n\nSettingPopulation of Scotland from 1 December 2020 to 8 September 2021.\n\nMain outcome measureSevere COVID-19, defined as cases with entry to critical care or fatal outcome.\n\nResultsEfficacy against severe COVID-19 of two doses of vaccine was 94% (95 percent CI 93% to 96%) in those without designated risk conditions, 89% (95 percent CI 86% to 91%) in those with moderate risk conditions, but only 73% (95 percent CI 64% to 79%) in those designated as clinically extremely vulnerable (CEV) and eligible for shielding. Of the 641 cases of severe COVID-19 in double-vaccinated individuals, 47% had moderate risk conditions and 38% were CEV. In the double-vaccinated CEV group, the rate ratio for severe disease (with no risk condition as reference category) was highest in solid organ transplants at 101 (95% CI 47 to 214) but even in this subgroup the absolute risk of severe COVID-19 was low (35 cases in 23678 person-months of follow-up).\n\nConclusionsTwo doses of vaccine protect against severe COVID-19 in CEV individuals but the residual risk in double-vaccinated individuals remains far higher in those who are CEV than in those who are not. These results lay a basis for determining eligibility for additional measures including passive immunization to protect those at highest risk.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.09.10.21263372", @@ -4143,6 +4129,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.08.17.21262196", + "date": "2021-08-22", + "link": "https://medrxiv.org/cgi/content/short/2021.08.17.21262196", + "title": "Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY disease (CLARITY): Statistical analysis plan for a randomised controlled Bayesian adaptive sample size trial", + "authors": "James McGree; Carinna Hockham; Sradha Kotwal; Arlen Wilcox; Abhinav Bassi; Carol Pollock; Louise M Burrell; Tom Snelling; Vivek Jha; Meg Jardine; Mark Jones", + "affiliations": "Queensland University of Technology; Imperial College London; University of New South Wales; University of New South Wales; The George Institute for Global Health; Royal North Shore Hospital; University of Melbourne; The University of Sydney; University of New South Wales; University of New South Wales; The University of Sydney", + "abstract": "The CLARITY trial (Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY Disease) investigates the effectiveness of angiotensin receptor blockers in addition to standard care compared to placebo (in Indian sites) with standard care in reducing the duration and severity of lung failure in patients with COVID-19. The CLARITY trial is a multi-centre, randomised controlled Bayesian adaptive trial with regular planned analyses where pre-specified decision rules will be assessed to determine whether the trial should be stopped due to sufficient evidence of treatment effectiveness or futility. Here we describe the statistical analysis plan for the trial, and define the pre-specified decision rules, including those that could lead to the trial being halted. The primary outcome is clinical status on a 7-point ordinal scale adapted from the WHO Clinical Progression scale assessed at Day 14. The primary analysis will follow the intention-to-treat principle. A Bayesian adaptive trial design was selected because there is considerable uncertainty about the extent of potential benefit of this treatment.\n\nTrial registrationClinicalTrials.gov, NCT04394117. Registered on 19 May 2020.\n\nhttps://clinicaltrials.gov/ct2/show/NCT04394117\n\nClinical Trial Registry of India: CTRI/2020/07/026831\n\nVersion and revisionsVersion 1.0. No revisions.", + "category": "respiratory medicine", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.08.13.21261889", @@ -4479,20 +4479,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.07.12.21260360", - "date": "2021-07-15", - "link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260360", - "title": "The impact of hypoxia on B cells in COVID-19", - "authors": "Prasanti Kotagiri; Federica Mescia; Aimee Hanson; Lorinda Turner; Laura Bergamaschi; Ana Penalver; Nathan Richoz; Stephen Moore; Brian Ortmann; Benjamin Dunmore; Helene Ruffieux; Michael Morgan; Zewen Kelvin Tuong; Rachael Bashford Rogers; Myra Hosmillo; Stephen Baker; Anne Elmer; Ian Goodfellow; Ravindra Gupta; Nathalie Kingston; Paul Lehner; Nicholas Matheson; Sylvia Richardson; Caroline Saunders; Michael Weekes; Berthold Gottgens; Mark Toshner; Christoph Hess; Patrick Maxwell; Menna Clatworthy; James A Nathan; John Bradley; Paul Lyons; Natalie Burrows; Kenneth G C Smith", - "affiliations": "Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Oxford University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University; Cambridge University", - "abstract": "Prominent early features of COVID-19 include severe, often clinically silent, hypoxia and a pronounced reduction in B cells, the latter important in defence against SARS-CoV-2. This brought to mind the phenotype of mice with VHL-deficient B cells, in which Hypoxia-Inducible Factors are constitutively active, suggesting hypoxia might drive B cell abnormalities in COVID-19. We demonstrated the breadth of early and persistent defects in B cell subsets in moderate/severe COVID-19, including reduced marginal zone-like, memory and transitional B cells, changes we also observed in B cell VHL-deficient mice. This was corroborated by hypoxia-related transcriptional changes in COVID-19 patients, and by similar B cell abnormalities in mice kept in hypoxic conditions, including reduced marginal zone and germinal center B cells. Thus hypoxia might contribute to B cell pathology in COVID-19, and in other hypoxic states. Through this mechanism it may impact on COVID-19 outcome, and be remediable through early oxygen therapy.", - "category": "infectious diseases", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.07.07.21253295", @@ -4871,6 +4857,20 @@ "author_similarity": 97, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.06.07.21258476", + "date": "2021-06-10", + "link": "https://medrxiv.org/cgi/content/short/2021.06.07.21258476", + "title": "Possible future waves of SARS-CoV-2 infection generated by variants of concern with a range of characteristics", + "authors": "Louise Dyson; Edward M Hill; Sam Moore; Jacob Curran-Sebastian; Michael J Tildesley; Katrina A Lythgoe; Thomas House; Lorenzo Pellis; Matt J Keeling", + "affiliations": "The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C; The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C; The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C; Department of Mathematics, University of Manchester, Manchester, United Kingdom; The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C; Big Data Institute, Old Road Campus, University of Oxford, United Kingdom.; Department of Mathematics, University of Manchester, Manchester, United Kingdom.; Department of Mathematics, University of Manchester, Manchester, United Kingdom.; The Zeeman Institute for Systems Biology \\& Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, ", + "abstract": "Viral reproduction of SARS-CoV-2 provides opportunities for the acquisition of advantageous mutations, altering viral transmissibility, disease severity, and/or allowing escape from natural or vaccine-derived immunity. We use three mathematical models: a parsimonious deterministic model with homogeneous mixing; an age-structured model; and a stochastic importation model to investigate the effect of potential variants of concern (VOCs). Calibrating to the situation in England in May 2021, we find epidemiological trajectories for putative VOCs are wide-ranging and dependent on their transmissibility, immune escape capability, and the introduction timing of a postulated VOC-targeted vaccine. We demonstrate that a VOC with a substantial transmission advantage over resident variants, or with immune escape properties, can generate a wave of infections and hospitalisations comparable to the winter 2020-2021 wave. Moreover, a variant that is less transmissible, but shows partial immune-escape could provoke a wave of infection that would not be revealed until control measures are further relaxed.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.06.08.21258535", @@ -4983,6 +4983,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.05.24.21257738", + "date": "2021-05-26", + "link": "https://medrxiv.org/cgi/content/short/2021.05.24.21257738", + "title": "Post-vaccination SARS-CoV-2 infection: risk factors and illness profile in a prospective, observational community-based case-control study", + "authors": "Michela Antonelli; Rose S Penfold; Jordi Merino; Carole H Sudre; Erika Molteni; Sarah Berry; Liane S Canas; Mark S Graham; Kerstin Klaser; Marc Modat; Benjamin Murray; Eric Kerfoot; Liyuan Chen; Jie Deng; Marc F \u00d6sterdahl; Nathan J Cheetham; David Alden Drew; Long Alden Nguyen; Joan Capdeila; Christina Hu; Somesh Selvachandran; Lorenzo Polidori; Anna May; Jonathan Wolf; Andrew T Chan; Alexander Hammers; Emma Duncan; Timothy Spector; Sebastien Ourselin; Claire J Steves", + "affiliations": "King's College London; King's College London; Department of Medicine, Harvard Medical School, Boston, MA, USA; Centre for Medical Image Computing, University College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; King's College London; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK; Massachusetts General Hospital; Massachusetts General Hospital and Harvard Medical School; Zoe Global, London, UK; Zoe Global, London, UK; Zoe Global, London, UK; Lorenzo Polidori; Zoe Global, London, UK; Zoe Global, London, UK; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK; King's College London; School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK; Department of Twin Research and Genetic Epidemiology, King's College London, UK", + "abstract": "BackgroundCOVID-19 vaccines show excellent efficacy in clinical trials and real-world data, but some people still contract SARS-CoV-2 despite vaccination. This study sought to identify risk factors associated with SARS-CoV-2 infection post-vaccination and describe characteristics of post-vaccination illness.\n\nMethodsAmongst 1,102,192 vaccinated UK adults from the COVID Symptom Study, 2394 (0.2%) cases of post-vaccination SARS-CoV-2 infection were identified between 8th December 2020 and 1st May 2021. Using a control group of vaccinated individuals testing negative, we assessed the associations of age, frailty, comorbidity, area-level deprivation and lifestyle factors with infection. Illness profile post-vaccination was assessed using a second control group of unvaccinated cases.\n\nFindingsOlder adults with frailty (OR=2.78, 95% CI=[1.98-3.89], p-value<0.0001) and individuals living in most deprived areas (OR=1.22 vs. intermediate group, CI[1.04-1.43], p-value=0.01) had increased odds of post-vaccination infection. Risk was lower in individuals without obesity (OR=0.6, CI[0.44-0.82], p-value=0.001) and those reporting healthier diet (OR=0.73, CI[0.62-0.86], p-value<0.0001). Vaccination was associated with reduced odds of hospitalisation (OR=0.36, CI[0.28-0.46], p-value<0.0001), and high acute-symptom burden (OR=0.51, CI[0.42-0.61], p-value<0.0001). In older adults, risk of [≥]28 days illness was lower following vaccination (OR=0.72, CI[0.51-1.00], p-value=0.05). Symptoms were reported less in positive-vaccinated vs. positive-unvaccinated individuals, except sneezing, which was more common post-vaccination (OR=1.24, CI[1.05-1.46], p-value=0.01).\n\nInterpretationOur findings suggest that older individuals with frailty and those living in most deprived areas are at increased risk of infection post-vaccination. We also showed reduced symptom burden and duration in those infected post-vaccination. Efforts to boost vaccine effectiveness in at-risk populations, and to targeted infection control measures, may still be appropriate to minimise SARS-CoV-2 infection.\n\nFundingThis work is supported by UK Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre (BRC) award to Guys & St Thomas NHS Foundation Trust in partnership with Kings College London and Kings College Hospital NHS Foundation Trust and via a grant to ZOE Global; the Wellcome Engineering and Physical Sciences Research Council (EPSRC) Centre for Medical Engineering at Kings College London (WT 203148/Z/16/Z). Investigators also received support from the Chronic Disease Research Foundation, the Medical Research Council (MRC), British Heart Foundation, the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, the Wellcome Flagship Programme (WT213038/Z/18/Z and Alzheimers Society (AS-JF-17-011), and the Massachusetts Consortium on Pathogen Readiness (MassCPR).\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify existing evidence for risk factors and characteristics of SARS-CoV-2 infection post-vaccination, we searched PubMed for peer-reviewed articles published between December 1, 2020 and May 18, 2021 using keywords (\"COVID-19\" OR \"SARS-CoV-2\") AND (\"Vaccine\" OR \"vaccination\") AND (\"infection\") AND (\"risk factor*\" OR \"characteristic*\"). We did not restrict our search by language or type of publication. Of 202 articles identified, we found no original studies on individual risk and protective factors for COVID-19 infection following vaccination nor on nature and duration of symptoms in vaccinated, community-based individuals. Previous studies in unvaccinated populations have shown that social and occupational factors influence risk of SARS-CoV-2infection, and that personal factors (age, male sex, multiple morbidities and frailty) increased risk for adverse outcomes in COVID-19. Phase III clinical trials have demonstrated good efficacy of BNT162b2 and ChAdOx1 vaccines against SARS-CoV-2 infection, confirmed in published real-world data, which additionally showed reduced risk of adverse outcomes including hospitalisation and death.\n\nAdded value of this studyThis is the first observational study investigating characteristics of and factors associated with SARS-CoV-2 infection after COVID-19 vaccination. We found that vaccinated individuals with frailty had higher rates of infection after vaccination than those without. Adverse determinants of health such as increased social deprivation, obesity, or a less healthy diet were associated with higher likelihood of infection after vaccination. In comparison with unvaccinated individuals, those with post-vaccination infection had fewer symptoms of COVID-19, and more were entirely asymptomatic. Fewer vaccinated individuals experienced five or more symptoms, required hospitalisation, and, in the older adult group, fewer had prolonged illness duration (symptoms lasting longer than 28 days).\n\nImplications of all the available evidenceSome individuals still contract COVID-19 after vaccination and our data suggest that frail older adults and those living in more deprived areas are at higher risk. However, in most individuals illness appears less severe, with reduced need for hospitalisation and lower risk of prolonged illness duration. Our results are relevant for health policy post-vaccination and highlight the need to prioritise those most at risk, whilst also emphasising the balance between the importance of personal protective measures versus adverse effects from ongoing social restrictions. Strategies such as timely prioritisation of booster vaccination and optimised infection control could be considered for at-risk groups. Research is also needed on how to enhance the immune response to vaccination in those at higher risk.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 94, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.05.25.21257505", @@ -5123,20 +5137,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.05.13.21257146", - "date": "2021-05-17", - "link": "https://medrxiv.org/cgi/content/short/2021.05.13.21257146", - "title": "Sociodemographic inequality in COVID-19 vaccination coverage amongst elderly adults in England: a national linked data study", - "authors": "Vahe Nafilyan; Ted Dolby; Cameron Razieh; Charlotte Gaughan; Jasper Morgan; Daniel Ayoubkhani; Ann Sarah Walker; Kamlesh Khunti; Myer Glickman; Thomas Yates", - "affiliations": "Office for National Statistics; Office for National Statistics; Diabetes Research Centre, University of Leicester; Office for National Statistics; Office for National Statistics; Office for National Statistics; University of Oxford; Diabetes Research Centre, University of Leicester; Office for National Statistics; Diabetes Research Centre, University of Leicester", - "abstract": "ObjectiveTo examine inequalities in COVID-19 vaccination rates amongst elderly adults in England\n\nDesignCohort study\n\nSettingPeople living in private households and communal establishments in England\n\nParticipants6,829,643 adults aged [≥] 70 years (mean 78.7 years, 55.2% female) who were alive on 15 March 2021.\n\nMain outcome measuresHaving received the first dose of a vaccine against COVID-19 by 15 March 2021. We calculated vaccination rates and estimated unadjusted and adjusted odds ratios using logistic regression models.\n\nResultsBy 15 March 2021, 93.2% of people living in England aged 70 years and over had received at least one dose of a COVID-19 vaccine. While vaccination rates differed across all factors considered apart from sex, the greatest disparities were seen between ethnic and religious groups. The lowest rates were in people of Black African and Black Caribbean ethnic backgrounds, where only 67.2% and 73.9% had received a vaccine, with adjusted odds of not being vaccinated at 5.01 (95% CI 4.86 - 5.16) and 4.85 (4.75 - 4.96) times greater than the White British group. The proportion of individuals self-identifying as Muslim and Buddhist who had received a vaccine was 79.1% and 84.1%, respectively. Older age, greater area deprivation, less advantaged socio-economic position (proxied by living in a rented home), being disabled and living either alone or in a multi-generational household were also associated with higher odds of not having received the vaccine.\n\nConclusionPeople disproportionately affected seem most hesitant to COVID-19 vaccinations. Policy Interventions to improve these disparities are urgently needed.\n\nSummary BoxO_ST_ABSWhat is already known on this subject?C_ST_ABSThe UK began an ambitious vaccination programme to combat the COVID-19 pandemic on 8th December 2020. Existing evidence suggests that COVID-19 vaccination rates differ by level of area deprivation, ethnicity and certain underlying health conditions, such as learning disability and mental health problems.\n\nWhat does this study add?Our study shows that first dose vaccination rates in adults aged 70 or over differed markedly by ethnic group and self-reported religious affiliation, even after adjusting for geography, socio-demographic factors and underlying health conditions. Our study also highlights differences in vaccination rates by deprivation, household composition, and disability status, factors disproportionately associated with SARS-CoV-2 infection. Public health policy and community engagement aimed at promoting vaccination uptake is these groups are urgently needed.\n\nStrengths and limitations of this studyO_LIUsing nationwide linked population-level data from clinical records and the 2011 Census, we examined a wide range of socio-demographic characteristics not available n electronic health records\nC_LIO_LIMost demographic and socio-economic characteristics are derived from the 2011 Census and therefore are 10 years old. However, we focus primarily on characteristics that are unlikely to change over time, such as ethnicity or religion, or likely to be stable for our population\nC_LIO_LIBecause the data are based on the 2011 Census, it excluded people living in England in 2011 but not taking part in the 2011 Census; respondents who could not be linked to the 2011-2013 NHS patients register; recent migrants. Consequently, we excluded 5.4% of vaccinated people who could not be linked\nC_LI", - "category": "public and global health", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.05.12.21257102", @@ -5263,6 +5263,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.04.28.21256261", + "date": "2021-05-02", + "link": "https://medrxiv.org/cgi/content/short/2021.04.28.21256261", + "title": "Aspirin and NSAID use and the risk of COVID-19", + "authors": "David Alden Drew; Chuan-Guo Guo; Karla Lee; Long Nguyen; Amit D Joshi; Chun-Han Lo; Wenjie Ma; Raaj S Mehta; Sohee Kwon; Christina M Astley; Mingyang Song; Richard Davies; Joan Capdevila; Mary M Ni Lochlainn; Carole Sudre; Mark S Graham; Thomas Varsavsky; Maria F. Gomez; Beatrice Kennedy; Hugo Fitipaldi; Jonathan Wolf; Timothy Spector; Sebastien Ourselin; Claire Steves; Andrew T. Chan", + "affiliations": "Massachusetts General Hospital; Massachusetts General Hospital; Department of Twin Research and Genetic Epidemiology; Massachusetts General Hospital and Harvard Medical School; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Massachusetts General Hospital; Boston Children's Hospital; Massachusetts General Hospital; Zoe Global Ltd.; Zoe Global Ltd; King's College London; Kings College London; King's College London; Kings College London; Lund University; Uppsala University; Lund University; Zoe Global Ltd.; King's College London; King's College London; King's College London; Massachusetts General Hospital", + "abstract": "Early reports raised concern that use of non-steroidal anti-inflammatory drugs (NSAIDs) may increase risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19). Users of the COVID Symptom Study smartphone application reported use of aspirin and other NSAIDs between March 24 and May 8, 2020. Users were queried daily about symptoms, COVID-19 testing, and healthcare seeking behavior. Cox proportional hazards regression was used to determine the risk of COVID-19 among according to aspirin or non-aspirin NSAID users. Among 2,736,091 individuals in the U.S., U.K., and Sweden, we documented 8,966 incident reports of a positive COVID-19 test over 60,817,043 person-days of follow-up. Compared to non-users and after stratifying by age, sex, country, day of study entry, and race/ethnicity, non-aspirin NSAID use was associated with a modest risk for testing COVID-19 positive (HR 1.23 [1.09, 1.32]), but no significant association was observed among aspirin users (HR 1.13 [0.92, 1.38]). After adjustment for lifestyle factors, comorbidities and baseline symptoms, any NSAID use was not associated with risk (HR 1.02 [0.94, 1.10]). Results were similar for those seeking healthcare for COVID-19 and were not substantially different according to lifestyle and sociodemographic factors or after accounting for propensity to receive testing. Our results do not support an association of NSAID use, including aspirin, with COVID-19 infection. Previous reports of a potential association may be due to higher rates of comorbidities or use of NSAIDs to treat symptoms associated with COVID-19.\n\nOne Sentence SummaryNSAID use is not associated with COVID-19 risk.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 94, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.04.30.21256119", @@ -5753,6 +5767,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.03.17.21253853", + "date": "2021-03-20", + "link": "https://medrxiv.org/cgi/content/short/2021.03.17.21253853", + "title": "Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest optimal policies varies with rural-urban settings", + "authors": "Xilin Jiang; Wenfeng Gong; Zlatina Dobreva; Ya Gao; Matthew Quaife; Christophe Fraser; Chris Holmes", + "affiliations": "University of Oxford; Bill & Melinda Gates Foundation; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; Department of International Health, Johns Hopkins University; Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK; University of Oxford; University of Oxford", + "abstract": "Low- and middle-income countries (LMICs) remain of high potential for hotspots for COVID-19 deaths and emerging variants given the inequality of vaccine distribution and their vulnerable healthcare systems. We aim to evaluate containment strategies that are sustainable and effective for LMICs. We constructed synthetic populations with varying contact and household structures to capture LMIC demographic characteristics that vary across communities. Using an agent- based model, we explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic tests, symptom screening, contact tracing and physical distancing. In low-density rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. In urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In high density communities that resemble slums and squatter settlements, physical distancing is less effective compared to rural and urban communities. Lastly, we demonstrated contact tracing is essential for effective containment. Our findings suggested that rapid diagnostic tests could be prioritised for control and monitor COVID-19 transmission and highlighted that contact survey data could guide strategy design to save resources for LMICs. An accompanying open source R package is available for simulating COVID-19 transmission based on contact network models.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.03.18.21253443", @@ -6033,20 +6061,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2021.02.27.21252593", - "date": "2021-03-01", - "link": "https://medrxiv.org/cgi/content/short/2021.02.27.21252593", - "title": "Surgical activity in England and Wales during the COVID-19 pandemic: a nationwide observational cohort study", - "authors": "Thomas D Dobbs; John A G Gibson; Alexander J Fowler; Tom E Abbott; Tasnin Shahid; Fatemeh Torabi; Rowena Griffiths; Ronan A Lyons; Rupert M Pearse; Iain S Whitaker", - "affiliations": "Swansea University Medical School; Swansea University Medical School; Queen Mary, University of London; Queen Mary University of London; Queen Mary University of London; Swansea University; Swansea University; Swansea University; Queen Mary University of London; Swansea University Medical School", - "abstract": "ObjectivesTo report the volume of surgical activity and the number of cancelled surgical procedures during the COVID-19 pandemic.\n\nDesign and settingAnalysis of electronic health record data from the National Health Service (NHS) in England and Wales.\n\nMethodsWe used hospital episode statistics for all adult patients undergoing surgery between 1st January 2020 and 31st December 2020. We identified surgical procedures using a previously published list of procedure codes. Procedures were stratified by urgency of surgery as defined by NHS England. We calculated the deficit of surgical activity by comparing the expected number of procedures from the years 2016-2019 with the actual number of procedures in 2020. We estimated the cumulative number of cancelled procedures by 31st December 2021 according patterns of activity in 2020.\n\nResultsThe total number of surgical procedures carried out in England and Wales in 2020 was 3,102,674 compared to the predicted number of 4,671,338. This represents a 33.6% reduction in the national volume of surgical activity. There were 763,730 emergency surgical procedures (13.4% reduction), compared to 2,338,944 elective surgical procedures (38.6% reduction). The cumulative number of cancelled or postponed procedures was 1,568,664. We estimate that this will increase to 2,358,420 by 31st December 2021.\n\nConclusionsThe volume of surgical activity in England and Wales was reduced by 33.6% in 2020, resulting in over 1,568,664 cancelled operations. This deficit will continue to grow in 2021.\n\nSummary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIThe COVID-19 pandemic necessitated a rapid change in the provision of care, including the suspension of a large proportion of surgical activity\nC_LIO_LISurgical activity has yet to return to normal and has been further impacted by subsequent waves of the pandemic\nC_LIO_LIThis will lead to a large backlog of cases\nC_LI\n\nWhat this study addsO_LI3,102,674 surgical procedures were performed in England and Wales during 2020, a 33.6% reduction on the expected yearly surgical activity\nC_LIO_LIOver 1.5 million procedures were not performed, with this deficit likely to continue to grow to 2.3 million by the end of 2021\nC_LIO_LIThis deficit is the equivalent of more than 6 months of pre-pandemic surgical activity, requiring a monumental financial and logistic challenge to manage\nC_LI", - "category": "surgery", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2021.02.26.21252512", @@ -6201,6 +6215,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.02.10.21251484", + "date": "2021-02-16", + "link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251484", + "title": "An analysis of school absences in England during the Covid-19 pandemic", + "authors": "Emma R Southall; Alex Holmes; Edward M Hill; Benjamin D Atkins; Trystan Leng; Robin N Thompson; Louise J Dyson; Matt J Keeling; Michael Tildesley", + "affiliations": "University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick", + "abstract": "The introduction of SARS-CoV-2, the virus that causes COVID-19 infection, in the UK in early 2020, resulted in the UK government introducing several control policies in order to reduce the spread of disease. As part of these restrictions, schools were closed to all pupils in March (except for vulnerable and key worker children), before re-opening to certain year groups in June. Finally all school children returned to the classroom in September. In this paper, we analyse the data on school absences from September 2020 to December 2020 as a result of COVID-19 infection and how that varied through time as other measures in the community were introduced. We utilise data from the Educational Settings database compiled by the Department for Education and examine how pupil and teacher absences change in both primary and secondary schools.\n\nOur results show that absences as a result of COVID-19 infection rose steadily following the re-opening of schools in September. Cases in teachers were seen to decline during the November lockdown, particularly in those regions that had previously been in tier 3, the highest level of control at the time. Cases in secondary school pupils increased for the first two weeks of the November lockdown, before decreasing. Since the introduction of the tier system, the number of absences owing to confirmed infection in primary schools was observed to be significantly lower than in secondary schools across all regions and tiers.\n\nIn December, we observed a large rise in the number of absences per school in secondary school settings in the South East and Greater London, but such rises were not observed in other regions or in primary school settings. We conjecture that the increased transmissibility of the new variant in these regions may have contributed to this rise in cases in secondary schools. Finally, we observe a positive correlation between cases in the community and cases in schools in most regions, with weak evidence suggesting that cases in schools lag behind cases in the surrounding community. We conclude that there is not significant evidence to suggest that schools are playing a significant role in driving spread in the community and that careful monitoring may be required as schools re-open to determine the effect associated with open schools upon community incidence.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.02.10.21251480", @@ -6343,14 +6371,14 @@ }, { "site": "medRxiv", - "doi": "10.1101/2021.02.03.21250974", - "date": "2021-02-05", - "link": "https://medrxiv.org/cgi/content/short/2021.02.03.21250974", - "title": "Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US", - "authors": "Estee Y Cramer; Evan L Ray; Velma K Lopez; Johannes Bracher; Andrea Brennen; Alvaro J Castro Rivadeneira; Aaron Gerding; Tilmann Gneiting; Katie H House; Yuxin Huang; Dasuni Jayawardena; Abdul H Kanji; Ayush Khandelwal; Khoa Le; Anja Muehlemann; Jarad Niemi; Apurv Shah; Ariane Stark; Yijin Wang; Nutcha Wattanachit; Martha W Zorn; Youyang Gu; Sansiddh Jain; Nayana Bannur; Ayush Deva; Mihir Kulkarni; Srujana Merugu; Alpan Raval; Siddhant Shingi; Avtansh Tiwari; Jerome White; Neil F Abernethy; Spencer Woody; Maytal Dahan; Spencer Fox; Kelly Gaither; Michael Lachmann; Lauren Ancel Meyers; James G Scott; Mauricio Tec; Ajitesh Srivastava; Glover E George; Jeffrey C Cegan; Ian D Dettwiller; William P England; Matthew W Farthing; Robert H Hunter; Brandon Lafferty; Igor Linkov; Michael L Mayo; Matthew D Parno; Michael A Rowland; Benjamin D Trump; Yanli Zhang-James; Samuel Chen; Stephen V Faraone; Jonathan Hess; Christopher P Morley; Asif Salekin; Dongliang Wang; Sabrina M Corsetti; Thomas M Baer; Marisa C Eisenberg; Karl Falb; Yitao Huang; Emily T Martin; Ella McCauley; Robert L Myers; Tom Schwarz; Daniel Sheldon; Graham Casey Gibson; Rose Yu; Liyao Gao; Yian Ma; Dongxia Wu; Xifeng Yan; Xiaoyong Jin; Yu-Xiang Wang; YangQuan Chen; Lihong Guo; Yanting Zhao; Quanquan Gu; Jinghui Chen; Lingxiao Wang; Pan Xu; Weitong Zhang; Difan Zou; Hannah Biegel; Joceline Lega; Steve McConnell; VP Nagraj; Stephanie L Guertin; Christopher Hulme-Lowe; Stephen D Turner; Yunfeng Shi; Xuegang Ban; Robert Walraven; Qi-Jun Hong; Stanley Kong; Axel van de Walle; James A Turtle; Michal Ben-Nun; Steven Riley; Pete Riley; Ugur Koyluoglu; David DesRoches; Pedro Forli; Bruce Hamory; Christina Kyriakides; Helen Leis; John Milliken; Michael Moloney; James Morgan; Ninad Nirgudkar; Gokce Ozcan; Noah Piwonka; Matt Ravi; Chris Schrader; Elizabeth Shakhnovich; Daniel Siegel; Ryan Spatz; Chris Stiefeling; Barrie Wilkinson; Alexander Wong; Sean Cavany; Guido Espana; Sean Moore; Rachel Oidtman; Alex Perkins; David Kraus; Andrea Kraus; Zhifeng Gao; Jiang Bian; Wei Cao; Juan Lavista Ferres; Chaozhuo Li; Tie-Yan Liu; Xing Xie; Shun Zhang; Shun Zheng; Alessandro Vespignani; Matteo Chinazzi; Jessica T Davis; Kunpeng Mu; Ana Pastore y Piontti; Xinyue Xiong; Andrew Zheng; Jackie Baek; Vivek Farias; Andreea Georgescu; Retsef Levi; Deeksha Sinha; Joshua Wilde; Georgia Perakis; Mohammed Amine Bennouna; David Nze-Ndong; Divya Singhvi; Ioannis Spantidakis; Leann Thayaparan; Asterios Tsiourvas; Arnab Sarker; Ali Jadbabaie; Devavrat Shah; Nicolas Della Penna; Leo A Celi; Saketh Sundar; Russ Wolfinger; Dave Osthus; Lauren Castro; Geoffrey Fairchild; Isaac Michaud; Dean Karlen; Matt Kinsey; Luke C. Mullany; Kaitlin Rainwater-Lovett; Lauren Shin; Katharine Tallaksen; Shelby Wilson; Elizabeth C Lee; Juan Dent; Kyra H Grantz; Alison L Hill; Joshua Kaminsky; Kathryn Kaminsky; Lindsay T Keegan; Stephen A Lauer; Joseph C Lemaitre; Justin Lessler; Hannah R Meredith; Javier Perez-Saez; Sam Shah; Claire P Smith; Shaun A Truelove; Josh Wills; Maximilian Marshall; Lauren Gardner; Kristen Nixon; John C. Burant; Lily Wang; Lei Gao; Zhiling Gu; Myungjin Kim; Xinyi Li; Guannan Wang; Yueying Wang; Shan Yu; Robert C Reiner; Ryan Barber; Emmanuela Gaikedu; Simon Hay; Steve Lim; Chris Murray; David Pigott; Heidi L Gurung; Prasith Baccam; Steven A Stage; Bradley T Suchoski; B. Aditya Prakash; Bijaya Adhikari; Jiaming Cui; Alexander Rodriguez; Anika Tabassum; Jiajia Xie; Pinar Keskinocak; John Asplund; Arden Baxter; Buse Eylul Oruc; Nicoleta Serban; Sercan O Arik; Mike Dusenberry; Arkady Epshteyn; Elli Kanal; Long T Le; Chun-Liang Li; Tomas Pfister; Dario Sava; Rajarishi Sinha; Thomas Tsai; Nate Yoder; Jinsung Yoon; Leyou Zhang; Sam Abbott; Nikos I Bosse; Sebastian Funk; Joel Hellewell; Sophie R Meakin; Katharine Sherratt; Mingyuan Zhou; Rahi Kalantari; Teresa K Yamana; Sen Pei; Jeffrey Shaman; Michael L Li; Dimitris Bertsimas; Omar Skali Lami; Saksham Soni; Hamza Tazi Bouardi; Turgay Ayer; Madeline Adee; Jagpreet Chhatwal; Ozden O Dalgic; Mary A Ladd; Benjamin P Linas; Peter Mueller; Jade Xiao; Yuanjia Wang; Qinxia Wang; Shanghong Xie; Donglin Zeng; Alden Green; Jacob Bien; Logan Brooks; Addison J Hu; Maria Jahja; Daniel McDonald; Balasubramanian Narasimhan; Collin Politsch; Samyak Rajanala; Aaron Rumack; Noah Simon; Ryan J Tibshirani; Rob Tibshirani; Valerie Ventura; Larry Wasserman; Eamon B O'Dea; John M Drake; Robert Pagano; Quoc T Tran; Lam Si Tung Ho; Huong Huynh; Jo W Walker; Rachel B Slayton; Michael A Johansson; Matthew Biggerstaff; Nicholas G Reich", - "affiliations": "University of Massachusetts, Amherst; University of Massachusetts, Amherst; Centers for Disease Control and Prevention; Chair of Econometrics and Statistics, Karlsruhe Institute of Technology; Computational Statistics Group, Heidelberg Institute for Theoretical Studies; IQT; University of Massachusetts, Amherst; University of Massachusetts, Amherst; Institute of Stochastics, Karlsruhe Institute of Technology; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; Institute of Mathematical Statistics and Actuarial Science, University of Bern; Iowa State University; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; University of Massachusetts, Amherst; Unaffiliated; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; Wadhwani Institute of Artificial Intelligence; University of Washington; University of Texas at Austin; Texas Advanced Computing Center; University of Texas at Austin; Texas Advanced Computing Center; Santa Fe Institute; University of Texas at Austin; University of Texas at Austin; University of Texas at Austin; University of Southern California; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; US Army Engineer Research and Development Center; State University of New York Upstate Medical University; State University of New York Upstate Medical University; State University of New York Upstate Medical University; State University of New York Upstate Medical University; State University of New York Upstate Medical University; Syracuse University; State University of New York Upstate Medical University; University of Michigan - Ann Arbor; Trinity University, San Antonio; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Michigan - Ann Arbor; University of Massachusetts, Amherst; University of Massachusetts, Amherst; Northeastern University; University of California, San Diego; University of Washington; University of California, San Diego; University of California, San Diego; University of California at Santa Barbara; University of California at Santa Barbara; University of California at Santa Barbara; University of California, Merced; Jilin University; University of Science and Technology of China; University of California, Los Angeles; University of California, Los Angeles; University of California, Los Angeles; University of California, Los Angeles; University of California, Los Angeles; University of California, Los Angeles; University of Arizona; University of Arizona; Construx; Signature Science, LLC; Signature Science, LLC; Signature Science, LLC; Signature Science, LLC; Rensselaer Polytechnic Institute; University of Washington; Unaffiliated; Arizona State University; Brown University; Manhasset Secondary School; Brown University; Predictive Science, Inc; Predictive Science, Inc; Imperial College, London; Predictive Science, Inc; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; Oliver Wyman; University of Notre Dame; University of Notre Dame; University of Notre Dame; University of Chicago; University of Notre Dame; University of Notre Dame; Masaryk University; Masaryk University; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; Microsoft; ISI Foundation; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University; Operations Research Center, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Sloan School of Management, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Sloan School of Management, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Massachusetts Institute of Technology; Massachusetts Institute of Technology; Massachusetts Institute of Technology; New York University; Massachusetts Institute of Technology; Massachusetts Institute of Technology; Massachusetts Institute of Technology; Institute for Data, Systems, and Society, Massachusetts Institute of Technology; Institute for Data, Systems, and Society, Massachusetts Institute of Technology; Institute for Data, Systems, and Society, Massachusetts Institute of Technology; Laboratory for Computational Physiology, Massachusetts Institute of Technology; Laboratory for Computational Physiology, Massachusetts Institute of Technology; River Hill High School; SAS Institute Inc; Los Alamos National Laboratory; Los Alamos National Laboratory; Los Alamos National Laboratory; Los Alamos National Laboratory; TRIUMF; University of Victoria; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins University Applied Physics Lab; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins University; Johns Hopkins Bloomberg School of Public Health; Unaffiliated; University of Utah; Johns Hopkins Bloomberg School of Public Health; Ecole Polytechnique Federale de Lausanne; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Unaffiliated; Johns Hopkins Bloomberg School of Public Health; Johns Hopkins Bloomberg School of Public Health; Unaffiliated; Johns Hopkins University; Johns Hopkins University; Johns Hopkins University; Unaffiliated; Iowa State University; Iowa State University; Iowa State University; Iowa State University; Clemson University; College of William & Mary; Iowa State University; University of Virginia; University of Washington; University of Washington; University of Washington; University of Washington; University of Washington; University of Washington; University of Washington; IEM, Inc.; IEM, Inc.; IEM, Inc.; IEM, Inc.; Georgia Institute of Technology; University of Iowa; Georgia Institute of Technology; Georgia Institute of Technology; Georgia Institute of Technology; Virginia Tech; Georgia Institute of Technology; Georgia Insitute of Technology; Metron, Inc.; Georgia Insitute of Technology; Georgia Insitute of Technology; Georgia Insitute of Technology; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Google Cloud; Harvard University; Google Cloud; Google Cloud; Google Cloud; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; London School of Hygiene & Tropical Medicine; The University of Texas at Austin; The University of Texas at Austin; Columbia University; Columbia University; Columbia University; Operations Research Center, Massachusetts Institute of Technology; Sloan School of Management, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Operations Research Center, Massachusetts Institute of Technology; Emory University Medical School; Georgia Insitute of Technology; MGH; MGH; Value Analytics Labs; MGH; Boston University School of Medicine; MGH; Georgia Insitute of Technology; Columbia University; Columbia University; Columbia University; UNC Chapel Hill; Carnegie Mellon University; University of Southern California; Carnegie Mellon University; Carnegie Mellon University; Carnegie Mellon University; University of British Columbia; Stanford University; Carnegie Mellon University; Stanford University; Carnegie Mellon University; University of Washington; Carnegie Mellon University; Stanford University; Carnegie Mellon University; Carnegie Mellon University; University of Georgia; University of Georgia; Unaffiliated; Walmart Inc.; Dalhousie University; Virtual Power System Inc.; Centers for Disease Control and Prevention; Centers for Disease Control and Prevention; Centers for Disease Control and Prevention; Centers for Disease Control and Prevention; University of Massachusetts, Amherst", - "abstract": "Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naive baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.\n\nSignificance StatementThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.", - "category": "epidemiology", + "doi": "10.1101/2021.02.01.21250839", + "date": "2021-02-03", + "link": "https://medrxiv.org/cgi/content/short/2021.02.01.21250839", + "title": "Extremely high SARS-CoV-2 seroprevalence in a strictly-Orthodox Jewish community in the UK", + "authors": "Katherine M Gaskell; Marina Johnson; Victoria Gould; Adam Hunt; Neil RH Stone; William Waites; Ben Kasstan; Tracey Chantler; Sham Lal; Chrissy h. Roberts; David Goldblatt; Rosalind M Eggo; Michael M Marks", + "affiliations": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK & Hospital for Tropical Diseases, University C; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Centre for Health, Law and Society, University of Bristol Law School, Bristol. BS1 1RJ; Department of Global Health and Development, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London; Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK; Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK & Hospital for Tropical Diseases, University C", + "abstract": "BackgroundEthnic and religious minorities have been disproportionately affected by SARS-CoV-2 worldwide. The UK strictly-Orthodox Jewish community has been severely affected by the pandemic. This group shares characteristics with other ethnic minorities including larger family sizes, higher rates of household crowding and relative socioeconomic deprivation. We studied a UK strictly-Orthodox Jewish population to understand how COVID-19 had spread within this community.\n\nMethodsWe performed a household-focused cross-sectional SARS-CoV-2 serosurvey specific to three antigen targets. Randomly-selected households completed a standardised questionnaire and underwent serological testing with a multiplex assay for SARS-CoV-2 IgG antibodies. We report clinical illness and testing before the serosurvey, seroprevalence stratified by age and gender. We used random-effects models to identify factors associated with infection and antibody titres.\n\nFindingsA total of 343 households, consisting of 1,759 individuals, were recruited. Serum was available for 1,242 participants. The overall seroprevalence for SARS-CoV-2 was 64.3% (95% CI 61.6-67.0%). The lowest seroprevalence was 27.6% in children under 5 years and rose to 73.8% in secondary school children and 74% in adults. Antibody titres were higher in symptomatic individuals and declined over time since reported COVID-19 symptoms, with the decline more marked for nucleocapsid titres.\n\nInterpretationIn this tight-knit religious minority population in the UK, we report one of the highest SARS-CoV-2 seroprevalence levels in the world to date. In the context of this high force of infection, all age groups experienced a high burden of infection. Actions to reduce the burden of disease in this and other minority populations are urgently required.\n\nFundingThis work was jointly funded by UKRI and NIHR [COV0335; MR/V027956/1], a donation from the LSHTM Alumni COVID-19 response fund, HDR UK, the MRC and the Wellcome Trust. The funders had no role in the design, conduct or analysis of the study or the decision to publish. The authors have no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.\n\nResearch In ContextO_ST_ABSEvidence before the studyC_ST_ABSIn January 2020, we searched PubMed for articles on rates of SARS-CoV-2 infection amongst ethnic minority groups and amongst the Jewish population. Search teams included \"COVID-19\", \"SARS-CoV-2\", seroprevalence, \"ethnic minority\", and \"Jewish\" with no language restrictions. We also searched UK government documents on SARS-CoV-2 infection amongst minority groups. By January 2020, a large number of authors had reported that ethnic minority groups experienced higher numbers of cases and increased hospitalisations due to COVID-19. A small number of articles provided evidence that strictly-Orthodox Jewish populations had experienced a high rate of SARS-CoV-2 infection but extremely limited data was available on overall population level rates of infection amongst specific ethnic minority population groups. There was also extremely limited data on rates of infection amongst young children from ethnic minority groups.\n\nAdded value of the studyWe report findings from a population representative, household survey of SARS-CoV-2 infection amongst a UK strictly Orthodox Jewish population. We demonstrate an extremely high seroprevalence rate of SARS-CoV-2 in this population which is more than five times the estimated seroprevalence nationally and five times the estimated seroprevalence in London. In addition the large number of children in our survey, reflective of the underlying population structure, allows us to demonstrate that in this setting there is a significant burden of disease in all age groups with secondary school aged children having an equivalent seroprevalence to adults.\n\nImplications of the available evidenceOur data provide clear evidence of the markedly disproportionate impact of SARS-CoV-2 in minority populations. In this setting infection occurs at high rates across all age groups including pre-school, primary school and secondary school-age children. Contextually appropriate measures to specifically reduce the impact of SARS-CoV-2 amongst minority populations are urgently required.", + "category": "infectious diseases", "match_type": "fuzzy", "author_similarity": 100, "affiliation_similarity": 100 @@ -6467,6 +6495,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2021.01.22.21250304", + "date": "2021-01-25", + "link": "https://medrxiv.org/cgi/content/short/2021.01.22.21250304", + "title": "Rates of serious clinical outcomes in survivors of hospitalisation with COVID-19: a descriptive cohort study within the OpenSAFELY platform", + "authors": "John Tazare; Alex J Walker; Laurie Tomlinson; George Hickman; Christopher T Rentsch; Elizabeth J Williamson; Krishnan Bhaskaran; David Evans; Kevin Wing; Rohini Mathur; Angel YS Wong; Anna Schultze; Sebastian CJ Bacon; Christopher Bates; Caroline E Morton; Helen J Curtis; Emily Nightingale; Helen I McDonald; Amir Mehrkar; Peter Inglesby; Simon Davy; Brian MacKenna; Jonathan Cockburn; William J Hulme; Charlotte Warren-Gash; Ketaki Bhate; Emma Powell; Any Mulick; Harriet Forbes; Caroline Minassian; Richard Croker; John Parry; Frank Hester; Sam Harper; Rosalind M Eggo; Stephen JW Evans; Liam Smeeth; Ian J Douglas; Ben Goldacre", + "affiliations": "London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; University of Oxford; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford; TPP; TPP; TPP; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; University of Oxford", + "abstract": "BackgroundPatients with COVID-19 are thought to be at higher risk of cardiometabolic and pulmonary complications, but quantification of that risk is limited. We aimed to describe the overall burden of these complications in survivors of severe COVID-19.\n\nMethodsWorking on behalf of NHS England, we used linked primary care records, death certificate and hospital data from the OpenSAFELY platform. We constructed three cohorts: patients discharged following hospitalisation with COVID-19, patients discharged following hospitalisation with pneumonia in 2019, and a frequency-matched cohort from the general population in 2019. We studied eight cardiometabolic and pulmonary outcomes. Absolute rates were measured in each cohort and Cox regression models were fitted to estimate age/sex adjusted hazard ratios comparing outcome rates between discharged COVID-19 patients and the two comparator cohorts.\n\nResultsAmongst the population of 31,716 patients discharged following hospitalisation with COVID-19, rates for majority of outcomes peaked in the first month post-discharge, then declined over the following four months. Patients in the COVID-19 population had markedly increased risk of all outcomes compared to matched controls from the 2019 general population, especially for pulmonary embolism (HR 12.86; 95% CI: 11.23 - 14.74). Outcome rates were more similar when comparing patients discharged with COVID-19 to those discharged with pneumonia in 2019, although COVID-19 patients had increased risk of type 2 diabetes (HR 1.23; 95% CI: 1.05 - 1.44).\n\nInterpretationCardiometabolic and pulmonary adverse outcomes are markedly raised following hospitalisation for COVID-19 compared to the general population. However, the excess risks were more comparable to those seen following hospitalisation with pneumonia. Identifying patients at particularly high risk of outcomes would inform targeted preventive measures.\n\nFundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, UK Research and Innovation, Health and Safety Executive.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2021.01.22.21249968", @@ -6651,14 +6693,14 @@ }, { "site": "medRxiv", - "doi": "10.1101/2020.12.27.20248896", - "date": "2021-01-02", - "link": "https://medrxiv.org/cgi/content/short/2020.12.27.20248896", - "title": "Vaccination and Non-Pharmaceutical Interventions: when can the UK relax about COVID-19?", - "authors": "Sam Moore; Edward M Hill; Michael Tildesley; Louise M Dyson; Matt J Keeling", - "affiliations": "University of Warwick; University of Warwick; University of Warwick; University of Warwick; University of Warwick", - "abstract": "BackgroundThe announcement of efficacious vaccine candidates against SARS-CoV-2 has been met with worldwide acclaim and relief. Many countries already have detailed plans for vaccine targeting based on minimising severe illness, death and healthcare burdens. Normally, relatively simple relationships between epidemiological parameters, vaccine efficacy and vaccine uptake predict the success of any immunisation programme. However, the dynamics of vaccination against SARS-CoV-2 is made more complex by age-dependent factors, changing levels of infection and the potential relaxation of non-pharmaceutical interventions (NPIs) as the perceived risk declines.\n\nMethodsIn this study we use an age-structured mathematical model, matched to a range of epidemiological data in the UK, that also captures the roll-out of a two-dose vaccination programme targeted at specific age groups.\n\nFindingsWe consider the interaction between the UK vaccination programme and future relaxation (or removal) of NPIs. Our predictions highlight the population-level risks of early relaxation leading to a pronounced wave of infection, hospital admissions and deaths. Only vaccines that offer high infection-blocking efficacy with high uptake in the general population allow relaxation of NPIs without a huge surge in deaths.\n\nInterpretationWhile the novel vaccines against SARS-CoV-2 offer a potential exit strategy for this outbreak, this is highly contingent on the infection-blocking (or transmission-blocking) action of the vaccine and the population uptake, both of which need to be carefully monitored as vaccine programmes are rolled out in the UK and other countries.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSVaccination has been seen as a key tool in the fight against SARS-CoV-2. The vaccines already developed represent a major technological achievement and have been shown to generate significant immune responses, as well as offering considerable protection against disease. However, to date there is limited information on the degree of infection-blocking these vaccines are likely to induce. Mathematical models have already successfully been used to consider age- and risk-structured targeting of vaccination, highlighting the importance of prioritising older and high-risk individuals.\n\nAdded value of this studyTranslating current knowledge and uncertainty of vaccine behaviour into meaningful public health messages requires models that fully capture the within-country epidemiology as well as the complex roll-out of a two-dose vaccination programme. We show that under reasonable assumptions for vaccine efficacy and uptake the UK is unlikely to reach herd immunity, which means that non-pharmaceutical interventions cannot be released without generating substantial waves of infection.\n\nImplications of all the available evidenceVaccination is likely to provide substantial individual protection to those receiving two doses, but the degree of protection to the wider population is still uncertain. While substantial immunisation of the most vulnerable groups will allow for some relaxation of controls, this must be done gradually to prevent large scale public health consequences.", - "category": "infectious diseases", + "doi": "10.1101/2021.01.06.21249352", + "date": "2021-01-08", + "link": "https://medrxiv.org/cgi/content/short/2021.01.06.21249352", + "title": "OpenSAFELY NHS Service Restoration Observatory 1: describing trends and variation in primary care clinical activity for 23.3 million patients in England during the first wave of COVID-19", + "authors": "Helen J Curtis; Brian MacKenna; Richard Croker; Alex J Walker; Peter Inglesby; Jessica Morley; Amir Mehrkar; Caroline E Morton; Seb Bacon; George Hickman; Chris Bates; David Evans; Tom Ward; Jonathan Cockburn; Simon Davy; Krishnan T. Bhaskaran; Anna Schultze; Christopher T. Rentsch; Elizabeth J Williamson; Will Hulme; Helen I McDonald; Laurie Tomlinson; Kevin Wing; Rohini I Mathur; Harriet Forbes; Angel Wong; Rosalind M Eggo; Henry Drysdale; John Parry; Frank Hester; Sam Harper; Ian J Douglas; Stephen Evans; Liam Smeeth; Ben Goldacre", + "affiliations": "University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; University of Oxford; TPP; University of Oxford; University of Oxford; TPP; University of Oxford; London School of Hygiene and Tropical Medicine; LSHTM; US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine; LSHTM; University of Oxford; London School of Medicine and Tropical Medicine; LSHTM; LSHTM; London School of Hygiene and Tropical Medicine; LSHTM; London School of Hygiene and Tropical Medicine; LSHTM; University of Oxford; TPP; TPP; TPP; LSHTM; LSHTM; LSHTM; University of Oxford", + "abstract": "BackgroundThe COVID-19 pandemic has disrupted healthcare activity globally. The NHS in England stopped most non-urgent work by March 2020, but later recommended that services should be restored to near-normal levels before winter where possible. The authors are developing the OpenSAFELY NHS Service Restoration Observatory, using data to describe changes in service activity during COVID-19, and reviewing signals for action with commissioners, researchers and clinicians. Here we report phase one: generating, managing, and describing the data.\n\nObjectiveTo describe the volume and variation of coded clinical activity in English primary care across 23.8 million patients records, taking respiratory disease and laboratory procedures as key examples.\n\nMethodsWorking on behalf of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care EHR data on 23.8 million patients; and conducted a population cohort-based study to describe activity using CTV3 coding hierarchy and keyword searches from January 2019-September 2020.\n\nResultsMuch activity recorded in general practice declined to some extent during the pandemic, but largely recovered by September 2020, with some exceptions. There was a large drop in coded activity for commonly used laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was blood coagulation tests such as International Normalised Ratio (INR), with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 7.0). The overall pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as \"no change\" from the previous year. Respiratory tract infections exhibited a sustained drop compared with pre-pandemic levels, not returning to pre-pandemic levels by September 2020. Various COVID-19 codes increased through the period. We observed a small decline associated with high level codes for long-term respiratory conditions such as chronic obstructive pulmonary disease (COPD) and asthma. Asthma annual reviews experienced a small drop but since recovered, while COPD annual reviews remain below baseline.\n\nConclusionsWe successfully delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September 2020, with some important tests less affected. Records of respiratory infections decreased with the exception of codes related to COVID-19, whilst activity of other respiratory disease codes was mixed. We are expanding the NHS Service Restoration Observatory in collaboration with clinicians, commissioners and researchers and welcome feedback.", + "category": "health systems and quality improvement", "match_type": "fuzzy", "author_similarity": 100, "affiliation_similarity": 100 @@ -7559,6 +7601,20 @@ "author_similarity": 94, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.10.15.20213108", + "date": "2020-10-20", + "link": "https://medrxiv.org/cgi/content/short/2020.10.15.20213108", + "title": "FebriDx point-of-care test in patients with suspected COVID-19: a pooled diagnostic accuracy study", + "authors": "Samuel G Urwin; B Clare Lendrem; Jana Suklan; Kile Green; Sara Graziadio; Peter Buckle; Paul M Dark; Adam L Gordon; Daniel S Lasserson; Brian Nicholson; D Ashley Price; Charles Reynard; Mark H Wilcox; Gail Hayward; Graham Prestwich; Valerie Tate; Tristan W Clark; Raja V Reddy; Hamish Houston; Ankur Gupta-Wright; Laurence John; Richard Body; A Joy Allen", + "affiliations": "NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne Hospitals Foundation Trust, Newcastle-upon-Tyne, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne Hospitals Foundation Trust, Newcastle-upon-Tyne, UK; Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, UK; Division of Infection, Immunity & Respiratory Medicine, University of Manchester, UK; School of Medicine, University of Nottingham, UK; NIHR Applied Research Collaboration East Midlands (ARC-EM), Nottingham, UK; NIHR Community Healthcare MedTech and In Vitro Diagnostics Cooperative, Oxford Health NHS Foundation Trust, Oxford, UK; Division of Health Sciences, University ; Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK; NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne Hospitals Foundation Trust, Newcastle-upon-Tyne, UK; NIHR Doctoral Research Fellowship Programme, UK; Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK; Healthcare Associated Infections Research Group, NIHR Leeds In Vitro Diagnostics Co-operative, Leeds Teaching Hospitals NHS Trust and University of Leeds, Leeds; NIHR Community Healthcare MedTech and In Vitro Diagnostics Co-operative, Oxford Health NHS Foundation Trust, Oxford, UK; Nuffield Department of Primary Care Hea; Yorkshire and Humber Academic Health Science Network, Wakefield, UK; Patient Public Involvement (PPI) Member, Precision Antimicrobial Prescribing PPI Group, NIHR Community Healthcare MedTech and In Vitro Diagnostics Cooperative, ; School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Department of Infection, University Hospital Sout; Department of Respiratory Medicine, Kettering General Hospital NHS Foundation Trust, Kettering, UK; Northwick Park Hospital, London North West University Healthcare NHS Trust, Harrow, UK; Institute for Global Health, University College London, London, UK; Ealing Hospital, London North West University Healthcare NHS Trust, London, UK; Clinical Res; Northwick Park Hospital, London North West University Healthcare NHS Trust, Harrow, UK; Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK; Emergency Department, Manchester Royal Infirmary, Ma; NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK", + "abstract": "BackgroundWe conducted a systematic review and individual patient data (IPD) meta-analysis to evaluate the diagnostic accuracy of a commercial point-of-care test, the FebriDx lateral flow device (LFD), in adult patients with suspected COVID-19. The FebriDx LFD is designed to distinguish between viral and bacterial respiratory infection.\n\nMethodsWe searched MEDLINE, EMBASE, PubMed, Google Scholar, LitCovid, ClinicalTrials.gov and preprint servers on the 13th of January 2021 to identify studies reporting diagnostic accuracy of FebriDx (myxovirus resistance protein A component) versus real time reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 in adult patients suspected of COVID-19. IPD were sought from studies meeting the eligibility criteria. Studies were screened for risk of bias using the QUADAS-2 tool. A bivariate linear mixed model was fitted to the data to obtain a pooled estimate of sensitivity and specificity with 95% confidence intervals (95% CIs). A summary receiver operating characteristic (SROC) curve of the model was constructed. A sub-group analysis was performed by meta-regression using the same modelling approach to compare pooled estimates of sensitivity and specificity between patients with a symptom duration of 0 to 7 days and >7 days, and patients aged between 16 to 73 years and >73 years.\n\nResultsTen studies were screened, and three studies with a total of 1481 patients receiving hospital care were included. FebriDx produced an estimated pooled sensitivity of 0.911 (95% CI: 0.855-0.946) and specificity of 0.868 (95% CI: 0.802-0.915) compared to RT-PCR. There were no significant differences between the sub-groups of 0 to 7 days and >7 days in estimated pooled sensitivity (p = 0.473) or specificity (p = 0.853). There were also no significant differences between the sub-groups of 16 to 73 years of age and >73 years of age in estimated pooled sensitivity (p = 0.946) or specificity (p = 0.486).\n\nConclusionsBased on the results of three studies, the FebriDx LFD had high diagnostic accuracy for COVID-19 in a hospital setting, however, the pooled estimates of sensitivity and specificity should be interpreted with caution due to the small number of studies included, risk of bias, and inconsistent reference standards. Further research is required to confirm these findings, and determine how FebriDx would perform in different healthcare settings and patient populations.\n\nTrial registrationThis study was conducted at pace as part of the COVID-19 National Diagnostic Research and Evaluation Platform (CONDOR) national test evaluation programme (https://www.condor-platform.org), and as a result, no protocol was developed, and the study was not registered.\n\nLay summaryTests to diagnose COVID-19 are crucial to help control the spread of the disease and to guide treatment. Over the last few months, tests have been developed to diagnose COVID-19 either by detecting the presence of the virus or by detecting specific markers linked to the virus being active in the body. These tests use complex machines in laboratories accepting samples from large geographical areas. Sometimes it takes days for test results to come back. So, to reduce the wait for results, new portable tests are being developed. These point-of-care (POC) tests are designed to work close to where patients require assessment and care such as hospital emergency departments, GP surgeries or care homes. For these new POC tests to be useful, they should ideally be as good as standard laboratory tests.\n\nIn this study we looked at published research into a new test called FebriDx. FebriDx is a POC test that detects the bodys response to infection, and is claimed to be able to detect the presence of any viral infection, including infections due to the SARS-CoV-2 virus which causes COVID-19, as well as bacterial infections which can have similar symptoms. The FebriDx result was compared with standard laboratory tests for COVID-19 performed on the same patients throat and nose swab sample. We were able to analyse data from three studies with a total of 1481 adult patients who were receiving hospital care with symptoms of COVID-19 during the UK pandemic. Approximately one fifth of the patients were diagnosed as positive for SARS-CoV-2 virus using standard laboratory tests for COVID-19.\n\nOur analysis demonstrated that FebriDx correctly identified 91 out of 100 patients who had COVID-19 according to the standard laboratory test. FebriDx also correctly identified 87 out of 100 patients who did not have COVID-19 according to the standard laboratory test. These results have important implications for how these tests could be used. As there were slightly fewer FebriDx false results when the results of the standard laboratory test were positive (9 out of 100) than when the results of the standard laboratory test were negative (13 out of 100), we can have slightly more confidence in a positive test result using FebriDx than a negative FebriDx result.\n\nOverall, we have shown that the FebriDx POC test performed well during the UK COVID-19 pandemic when compared with laboratory tests, especially when COVID-19 was indicated. For the future, this means that the FebriDx POC test might be helpful in making a quick clinical decision on whether to isolate a patient with COVID-19-like symptoms arriving in a busy emergency department. However, our results indicate it would not completely replace the need to conduct a laboratory test in certain cases to confirm COVID-19.\n\nThere are limitations to our findings. For example, we do not know if FebriDx will work in a similar way with patients in different settings such as in the community or care homes. Similarly, we do not know whether other viral and bacterial infections which cause similar COVID-19 symptoms, and are more common in the autumn and winter months, could influence the FebriDx test accuracy. Our findings are also only based on three studies.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.10.15.20208454", @@ -7573,20 +7629,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.10.14.20212555", - "date": "2020-10-16", - "link": "https://medrxiv.org/cgi/content/short/2020.10.14.20212555", - "title": "Multi-organ impairment in low-risk individuals with long COVID", - "authors": "Andrea Dennis; Malgorzata Wamil; Sandeep Kapur; Johann Alberts; Andrew Badley; Gustav Anton Decker; Stacey A Rizza; Rajarshi Banerjee; Amitava Banerjee", - "affiliations": "Perspectum; Great Western Hospitals NHS Foundation Trust; Mayo Clinic Healthcare; Alliance Medical; Mayo Clinic; Mayo Clinic International; Mayo Clinic; Perspectum; University College London", - "abstract": "BackgroundSevere acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection has disproportionately affected older individuals and those with underlying medical conditions. Research has focused on short-term outcomes in hospital, and single organ involvement. Consequently, impact of long COVID (persistent symptoms three months post-infection) across multiple organs in low-risk individuals is yet to be assessed.\n\nMethodsAn ongoing prospective, longitudinal, two-centre, observational study was performed in individuals symptomatic after recovery from acute SARS-CoV-2 infection. Symptoms and organ function (heart, lungs, kidneys, liver, pancreas, spleen) were assessed by standardised questionnaires (EQ-5D-5L, Dyspnoea-12), blood investigations and quantitative magnetic resonance imaging, defining single and multi-organ impairment by consensus definitions.\n\nFindingsBetween April and September 2020, 201 individuals (mean age 44 (SD 11.0) years, 70% female, 87% white, 31% healthcare workers) completed assessments following SARS-CoV-2 infection (median 140, IQR 105-160 days after initial symptoms). The prevalence of pre-existing conditions (obesity: 20%, hypertension: 6%; diabetes: 2%; heart disease: 4%) was low, and only 18% of individuals had been hospitalised with COVID-19. Fatigue (98%), muscle aches (88%), breathlessness (87%), and headaches (83%) were the most frequently reported symptoms. Ongoing cardiorespiratory (92%) and gastrointestinal (73%) symptoms were common, and 42% of individuals had ten or more symptoms.\n\nThere was evidence of mild organ impairment in heart (32%), lungs (33%), kidneys (12%), liver (10%), pancreas (17%), and spleen (6%). Single (66%) and multi-organ (25%) impairment was observed, and was significantly associated with risk of prior COVID-19 hospitalisation (p<0.05).\n\nInterpretationIn a young, low-risk population with ongoing symptoms, almost 70% of individuals have impairment in one or more organs four months after initial symptoms of SARS-CoV-2 infection. There are implications not only for burden of long COVID but also public health approaches which have assumed low risk in young people with no comorbidities.\n\nFundingThis work was supported by the UKs National Consortium of Intelligent Medical Imaging through the Industry Strategy Challenge Fund, Innovate UK Grant 104688, and also through the European Unions Horizon 2020 research and innovation programme under grant agreement No 719445.", - "category": "health policy", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.10.12.20211342", @@ -7839,6 +7881,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.09.24.20200048", + "date": "2020-09-25", + "link": "https://medrxiv.org/cgi/content/short/2020.09.24.20200048", + "title": "Genetic mechanisms of critical illness in Covid-19", + "authors": "Erola Pairo-Castineira; Sara Clohisey; Lucija Klaric; Andrew Bretherick; Konrad Rawlik; Nicholas Parkinson; Dorota Pasko; Susan Walker; Anne Richmond; Max Head Fourman; Andy Law; James Furniss; Elvina Gountouna; Nicola Wrobel; Clark D Russell; Loukas Moutsianas; Bo Wang; Alison Meynert; Zhijian Yang; Ranran Zhai; Chenqing Zheng; Fiona Griffith; Wilna Oosthuyzen; Barbara Shih; Se\u00e1n Keating; Marie Zechner; Chris Haley; David J Porteous; Caroline Hayward; Julian Knight; Charlotte Summers; Manu Shankar-Hari; Lance Turtle; Antonia Ho; Charles Hinds; Peter Horby; Alistair Nichol; David Maslove; Lowell Ling; Paul Klenerman; Danny McAuley; Hugh Montgomery; Timothy Walsh; - The GenOMICC Investigators; - The ISARIC4C Investigators; - The Covid-19 Human Genetics Initiative; Xia Shen; Kathy Rowan; Angie Fawkes; Lee Murphy; Chris P Ponting; Albert Tenesa; Mark Caulfield; Richard Scott; Peter JM Openshaw; Malcolm G Semple; Veronique Vitart; James F Wilson; J Kenneth Baillie", + "affiliations": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; The Roslin Institute; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Genomics England; Genomics England; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; University of Edinburgh Centre for Inflammation Research, The Queen's Medical Research Institute, Edinburgh, UK; Genomics England; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.; Department of Medicine, University of Cambridge, Cambridge, UK.; Department of Intensive Care Medicine, Guy's and St. Thomas NHS Foundation Trust, London, UK; School of Immunology and Microbial Sciences, King's College London; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences University of Liverpool, L; MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, Univer; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK.; Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7FZ, UK.; Clinical Research Centre at St Vincent's University Hospital, University College Dublin, Dublin, Ireland; Australian and New Zealand Intensive Care Research Cen; Department of Critical Care Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, ON, Canada.; Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.; University of Oxford; Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, Northern Ireland, UK; Department of Intensive Care Medicine, Royal Vi; UCL Centre for Human Health and Performance, London, W1T 7HA, UK.; Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK.; -; -; -; Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.; Intensive Care National Audit & Research Centre, London, UK.; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK.; Genomics England; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK; Genomics England; National Heart & Lung Institute, Imperial College London (St Mary's Campus), Norfolk Place, Paddington, London W2 1PG, UK.; University of Liverpool, Liverpool, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK.; MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK; Ce; Roslin Institute, University of Edinburgh", + "abstract": "The subset of patients who develop critical illness in Covid-19 have extensive inflammation affecting the lungs1 and are strikingly different from other patients: immunosuppressive therapy benefits critically-ill patients, but may harm some non-critical cases.2 Since susceptibility to life-threatening infections and immune-mediated diseases are both strongly heritable traits, we reasoned that host genetic variation may identify mechanistic targets for therapeutic development in Covid-19.3\n\nGenOMICC (Genetics Of Mortality In Critical Care, genomicc.org) is a global collaborative study to understand the genetic basis of critical illness. Here we report the results of a genome-wide association study (GWAS) in 2244 critically-ill Covid-19 patients from 208 UK intensive care units (ICUs), representing >95% of all ICU beds. Ancestry-matched controls were drawn from the UK Biobank population study and results were confirmed in GWAS comparisons with two other population control groups: the 100,000 genomes project and Generation Scotland.\n\nWe identify and replicate three novel genome-wide significant associations, at chr19p13.3 (rs2109069, p = 3.98 x 10-12), within the gene encoding dipeptidyl peptidase 9 (DPP9), at chr12q24.13 (rs10735079, p =1.65 x 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), and at chr21q22.1 (rs2236757, p = 4.99 x 10-8) in the interferon receptor gene IFNAR2. Consistent with our focus on extreme disease in younger patients with less comorbidity, we detect a stronger signal at the known 3p21.31 locus than previous studies (rs73064425, p = 4.77 x 10-30).\n\nWe identify potential targets for repurposing of licensed medications. Using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease. Transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19.\n\nOur results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice.", + "category": "intensive care and critical care medicine", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.09.22.20194183", @@ -7951,6 +8007,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "bioRxiv", + "doi": "10.1101/2020.09.16.297945", + "date": "2020-09-16", + "link": "https://biorxiv.org/cgi/content/short/2020.09.16.297945", + "title": "Characterisation of protease activity during SARS-CoV-2 infection identifies novel viral cleavage sites and cellular targets for drug repurposing", + "authors": "Bjoern Meyer; Jeanne Chiaravalli; Stacy Gellenoncourt; Philip Brownridge; Dominic P. Bryne; Leonard A. Daly; Arturas Grauslys; Marius Walter; Fabrice Agou; Lisa A. Chakrabarti; Charles S. Craik; Claire E. Eyers; Patrick A. Eyers; Yann Gambin; Andrew R Jones; Emma Sierecki; Eric Verdin; Marco Vignuzzi; Edward Emmott", + "affiliations": "Institut Pasteur; Institut Pasteur; Institut Pasteur; University of Liverpool; University of Liverpool; University of Liverpool; University of Liverpool; Buck Institute for Aging; Institut Pasteur; Institut Pasteur; UCSF; University of Liverpool; University of Liverpool; UNSW; University of Liverpool; UNSW; Buck Institute for Aging; Institut Pasteur; University of Liverpool", + "abstract": "SARS-CoV-2 is the causative agent behind the COVID-19 pandemic, and responsible for over 170 million infections, and over 3.7 million deaths worldwide. Efforts to test, treat and vaccinate against this pathogen all benefit from an improved understanding of the basic biology of SARS-CoV-2. Both viral and cellular proteases play a crucial role in SARS-CoV-2 replication, and inhibitors targeting proteases have already shown success at inhibiting SARS-CoV-2 in cell culture models. Here, we study proteolytic cleavage of viral and cellular proteins in two cell line models of SARS-CoV-2 replication using mass spectrometry to identify protein neo-N-termini generated through protease activity. We identify previously unknown cleavage sites in multiple viral proteins, including major antigenic proteins S and N, which are the main targets for vaccine and antibody testing efforts. We discovered significant increases in cellular cleavage events consistent with cleavage by SARS-CoV-2 main protease, and identify 14 potential high-confidence substrates of the main and papain-like proteases, validating a subset with in vitro assays. We showed that siRNA depletion of these cellular proteins inhibits SARS-CoV-2 replication, and that drugs targeting two of these proteins: the tyrosine kinase SRC and Ser/Thr kinase MYLK, showed a dose-dependent reduction in SARS-CoV-2 titres. Overall, our study provides a powerful resource to understand proteolysis in the context of viral infection, and to inform the development of targeted strategies to inhibit SARS-CoV-2 and treat COVID-19.", + "category": "microbiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.09.12.20191973", @@ -7979,20 +8049,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.09.10.20191841", - "date": "2020-09-11", - "link": "https://medrxiv.org/cgi/content/short/2020.09.10.20191841", - "title": "The King's College London Coronavirus Health and Experiences of Colleagues at King's Study: SARS-CoV-2 antibody response in an occupational sample", - "authors": "Daniel Leightley; Valentina Vitiello; Gabriella Bergin-Cartwright; Alice Wickersham; Katrina A S Davis; Sharon Stevelink; Matthew Hotopf; Reza Razavi; - On behalf of the KCL CHECK research team", - "affiliations": "Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London.; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London; The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London; ", - "abstract": "We report test results for SARS-CoV-2 antibodies in an occupational group of postgraduate research students and current members of staff at Kings College London. Between June and July 2020, antibody testing kits were sent to n=2296 participants; n=2004 (86.3%) responded, of whom n=1882 (93.9%) returned valid test results. Of those that returned valid results, n=124 (6.6%) tested positive for SARS-CoV-2 antibodies, with initial comparisons showing variation by age group and clinical exposure.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.09.11.20192492", @@ -8385,20 +8441,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.08.10.20171033", - "date": "2020-08-11", - "link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171033", - "title": "Post-exertion oxygen saturation as a prognostic factor for adverse outcome in patients attending the emergency department with suspected COVID-19: Observational cohort study", - "authors": "Steve Goodacre; Ben Thomas; Ellen Lee; Laura Sutton; Katie Biggs; Carl Marincowitz; Amanda Loban; Simon Waterhouse; Richard Simmonds; Jose Schutter; Sarah Connelly; Elena Sheldon; Jamie Hall; Emma Young; Andrew Bentley; Kirsty Challen; Chris Fitzsimmons; Tim Harris; Fiona Lecky; Andrew Lee; Ian Maconochie; Darren Walter", - "affiliations": "University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; University of Sheffield; Manchester University NHS Foundation Trust, Wythenshawe Hospital; Lancashire Teaching Hospitals NHS Foundation Trust; Sheffield Children's NHS Foundation Trust; Barts Health NHS Trust; University of Sheffield; University of Sheffield; Imperial College Healthcare NHS Trust; Manchester University NHS Foundation Trust", - "abstract": "BackgroundMeasurement of post-exertion oxygen saturation has been proposed to assess illness severity in suspected COVID-19 infection. We aimed to determine the accuracy of post-exertional oxygen saturation for predicting adverse outcome in suspected COVID-19.\n\nMethodsWe undertook an observational cohort study across 70 emergency departments during first wave of the COVID-19 pandemic in the United Kingdom. We collected data prospectively, using a standardised assessment form, and retrospectively, using hospital records, from patients with suspected COVID-19, and reviewed hospital records at 30 days for adverse outcome (death or receiving organ support). Patients with post-exertion oxygen saturation recorded were selected for this analysis.\n\nResultsWe analysed data from 817 patients with post-exertion oxygen saturation recorded after excluding 54 in whom measurement appeared unfeasible. The c-statistic for post-exertion change in oxygen saturation was 0.589 (95% confidence interval 0.465 to 0.713), and the positive and negative likelihood ratios of a 3% or more desaturation were respectively 1.78 (1.25 to 2.53) and 0.67 (0.46 to 0.98). Multivariable analysis showed that post-exertion oxygen saturation was not a significant predictor of adverse outcome when baseline clinical assessment was taken into account (p=0.368). Secondary analysis excluding patients in whom post-exertion measurement appeared inappropriate resulted in a c-statistic of 0.699 (0.581 to 0.817), likelihood ratios of 1.98 (1.26 to 3.10) and 0.61 (0.35 to 1.07), and some evidence of additional prognostic value on multivariable analysis (p=0.019).\n\nConclusionsPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19.\n\nRegistrationISRCTN registry, ISRCTN56149622, http://www.isrctn.com/ISRCTN28342533\n\nKey messagesWhat is already known on this subject?\n\nO_LIPost exertional decrease in oxygen saturation can be used to predict prognosis in chronic lung diseases\nC_LIO_LIPost exertional desaturation has been proposed as a way of predicting adverse outcome in people with suspected COVID-19\nC_LI\n\nWhat this study adds:\n\nO_LIPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19\nC_LI", - "category": "emergency medicine", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.08.07.20169490", @@ -8875,20 +8917,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.07.03.20145912", - "date": "2020-07-06", - "link": "https://medrxiv.org/cgi/content/short/2020.07.03.20145912", - "title": "Ultraviolet A Radiation and COVID-19 Deaths: A Multi Country Study", - "authors": "Mark Cherrie; Tom Clemens; Claudio Colandrea; Zhiqiang Feng; David Webb; Chris Dibben; Richard B Weller", - "affiliations": "University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh; University of Edinburgh", - "abstract": "ObjectivesTo determine whether UVA exposure might be associated with COVID-19 deaths\n\nDesignEcological regression, with replication in two other countries and pooled estimation\n\nSetting2,474 counties of the contiguous USA, 6,755 municipalities in Italy, 6,274 small areas in England. Only small areas in their Vitamin D winter (monthly mean UVvitd of under 165 KJ/m2) from Jan to April 2020.\n\nParticipants\n\nThe at-risk population is the total small area population, with measures to incorporate spatial infection into the model. The model is adjusted for potential confounders including long-term winter temperature and humidity.\n\nMain outcome measuresWe derive UVA measures for each area from remote sensed data and estimate their relationship with COVID-19 mortality with a random effect for States, in a multilevel zero-inflated negative binomial model. In the USA and England death certificates had to record COVID-19. In Italy excess deaths in 2020 over expected from 2015-19.\n\nData sourcesSatellite derived mean daily UVA dataset from Japan Aerospace Exploration Agency. Data on deaths compiled by Center for Disease Control (USA), Office for National Statistics (England) and Italian Institute of Statistics.\n\nResultsDaily mean UVA (January-April 2020) varied between 450 to 1,000 KJ/m2 across the three countries. Our fully adjusted model showed an inverse correlation between UVA and COVID-19 mortality with a Mortality Risk Ratio (MRR) of 0.71 (0.60 to 0.85) per 100KJ/m2 increase UVA in the USA, 0.81 (0.71 to 0.93) in Italy and 0.49 (0.38 to 0.64) in England. Pooled MRR was 0.68 (0.52 to 0.88).\n\nConclusionsOur analysis, replicated in 3 independent national datasets, suggests ambient UVA exposure is associated with lower COVID-19 specific mortality. This effect is independent of vitamin D, as it occurred at irradiances below that likely to induce significant cutaneous vitamin D3 synthesis. Causal interpretations must be made cautiously in observational studies. Nonetheless this study suggests strategies for reduction of COVID-19 mortality.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.07.03.20145839", @@ -9057,20 +9085,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.18.20134742", - "date": "2020-06-20", - "link": "https://medrxiv.org/cgi/content/short/2020.06.18.20134742", - "title": "Racial and ethnic determinants of Covid-19 risk", - "authors": "Chun-Han Lo; Long H. Nguyen; David A. Drew; Mark S. Graham; Erica T. Warner; Amit D. Joshi; Christina M. Astley; Chuan-Guo Guo; Wenjie Ma; Raaj S. Mehta; Sohee Kwon; Mingyang Song; Richard Davies; Joan Capdevila; Karla A. Lee; Mary Ni Lochlainn; Thomas Varsavsky; Carole H. Sudre; Jonathan Wolf; Yvette C. Cozier; Lynn Rosenberg; Lynne R. Wilkens; Christopher A. Haiman; Loic Le Marchand; Julie R. Palmer; Tim D. Spector; Sebastien Ourselin; Claire J. Steves; Andrew T. Chan; - COPE Consortium", - "affiliations": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Computational Epidemiology Lab and Division of Endocrinology, Boston Children's Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; Zoe Global Limited, London, U.K.; Zoe Global Limited, London, U.K.; Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K.; Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K.; School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K.; School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K.; Zoe Global Limited, London, U.K.; Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A.; Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A.; Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, U.S.A.; Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, California, U.; Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, U.S.A.; Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A.; Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K.; School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K.; Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K.; Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A.; ", - "abstract": "BackgroundRacial and ethnic minorities have disproportionately high hospitalization rates and mortality related to the novel coronavirus disease 2019 (Covid-19). There are comparatively scant data on race and ethnicity as determinants of infection risk.\n\nMethodsWe used a smartphone application (beginning March 24, 2020 in the United Kingdom [U.K.] and March 29, 2020 in the United States [U.S.]) to recruit 2,414,601 participants who reported their race/ethnicity through May 25, 2020 and employed logistic regression to determine the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for a positive Covid-19 test among racial and ethnic groups.\n\nResultsWe documented 8,858 self-reported cases of Covid-19 among 2,259,841 non-Hispanic white; 79 among 9,615 Hispanic; 186 among 18,176 Black; 598 among 63,316 Asian; and 347 among 63,653 other racial minority participants. Compared with non-Hispanic white participants, the risk for a positive Covid-19 test was increased across racial minorities (aORs ranging from 1.24 to 3.51). After adjustment for socioeconomic indices and Covid-19 exposure risk factors, the associations (aOR [95% CI]) were attenuated but remained significant for Hispanic (1.58 [1.24-2.02]) and Black participants (2.56 [1.93-3.39]) in the U.S. and South Asian (1.52 [1.38-1.67]) and Middle Eastern participants (1.56 [1.25-1.95]) in the U.K. A higher risk of Covid-19 and seeking or receiving treatment was also observed for several racial/ethnic minority subgroups.\n\nConclusionsOur results demonstrate an increase in Covid-19 risk among racial and ethnic minorities not completely explained by other risk factors for Covid-19, comorbidities, and sociodemographic characteristics. Further research investigating these disparities are needed to inform public health measures.", - "category": "public and global health", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.17.20133959", @@ -9127,20 +9141,6 @@ "author_similarity": 94, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.13.20130419", - "date": "2020-06-16", - "link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130419", - "title": "Mental health service activity during COVID-19 lockdown: South London and Maudsley data on working age community and home treatment team services and mortality from February to mid-May 2020", - "authors": "Robert Stewart; Evangelia Martin; Matthew Broadbent", - "affiliations": "King's College London; King's College London; South London and Maudsley NHS Foundation Trust", - "abstract": "The lockdown and social distancing policy response to the COVID-19 pandemic in the UK has a potentially important impact on provision of mental healthcare; however, there has been relatively little quantification of this. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for home treatment teams (HTTs) and working age adult community mental health teams (CMHTs) from 1st February to 15th May 2020 at the South London and Maudsley NHS Trust (SLaM), a large mental health service provider for 1.2m residents in south London. In addition daily deaths are described for all current and previous SLaM service users over this period and the same dates in 2019. In summary, comparing periods before and after 16th March 2020 the CMHT sector showed relatively stable caseloads and total contact numbers, but a substantial shift from face-to-face to virtual contacts, while HTTs showed the same changeover but reductions in caseloads and total contacts (although potentially an activity rise again during May). Number of deaths for the two months between 16th March and 15th May were 2.4-fold higher in 2020 than 2019, with 958 excess deaths.", - "category": "psychiatry and clinical psychology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.12.20129056", @@ -9197,6 +9197,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.06.10.20127563", + "date": "2020-06-12", + "link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127563", + "title": "Multimorbidity, Polypharmacy, and COVID-19 infection within the UK Biobank cohort.", + "authors": "Ross McQueenie; Hamish Foster; Bhautesh D Jani; Srinivasa Vittal Katikireddi; Naveed Sattar; Jill P Pell; Frederick K Ho; Claire L Niedzwiedz; Claire E Hastie; Jana Anderson; Patrick B Mark; Michael Sullivan; Frances S Mair; Barbara I Nicholl", + "affiliations": "University of Glasgow, Instutute of Health and Wellbeing; University of Glasgow, Instutute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Cardiovascular and Medical Sciences; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Cardiovascular and Medical Sciences; University of Glasgow, Institute of Cardiovascular and Medical Sciences; University of Glasgow, Institute of Health and Wellbeing; University of Glasgow, Institute of Health and Wellbeing", + "abstract": "BACKGROUNDIt is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity ([≥]2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors.\n\nMETHODS AND FINDINGSWe studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with [≥]2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and [≥]2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response increased risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI [≥]40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population.\n\nCONCLUSIONSIncreasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19.\n\nAuthor summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIMultimorbidity is a growing global challenge, but thus far LTC prognostic factors for severe COVID-19 primarily involve single conditions and there is a lack of data on the influence of multimorbidity on the risk of COVID-19.\nC_LIO_LIAs countries move from the lockdown phase of COVID-19, clinicians need more information about risk stratification to appropriately advise patients with multimorbidity about risk prevention steps.\nC_LI\n\nWhat did the researchers do and find?O_LIParticipants with multimorbidity ([≥]2 LTCs) had a 48% higher risk of a positive COVID-19 test, those with cardiometabolic multimorbidity had a 77% higher risk, than those without that type of multimorbidity.\nC_LIO_LIThose from non-white ethnicities with multimorbidity had nearly three times the risk of having COVID-19 infection compared to those of white ethnicity\nC_LIO_LIPeople with multimorbidity with the highest risk of COVID-19 infection were the most socioeconomically deprived, those with BMI [≥]40 kg/m2, and those with reduced renal function.\nC_LI\n\nWhat do these findings mean?O_LIIndividuals with [≥]2 LTCs, especially if these are cardiometabolic in nature, should be particularly stringent in adhering to preventive measures, such as physical distancing and hand hygiene.\nC_LIO_LIOur findings have implications for clinicians, occupational health and employers when considering work-place environments, appropriate advice for patients, and adaptations that might be required to protect such staff, identified here, as higher risk.\nC_LI", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 91 + }, { "site": "medRxiv", "doi": "10.1101/2020.06.10.20127175", @@ -9281,20 +9295,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.06.02.20120642", - "date": "2020-06-05", - "link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120642", - "title": "Estimating excess visual loss in people with neovascular age-related macular degeneration during the COVID-19 pandemic", - "authors": "Darren S Thomas; Alasdair Warwick; Abraham Olvera-Barrios; Catherine Egan; Roy Schwartz; Sudeshna Patra; Haralabos Eleftheriadis; Anthony P Khawaja; Andrew Lotery; Philipp L Mueller; Robin Hamilton; Ella Preston; Paul Taylor; Adnan Tufail; - UK EMR Users Group", - "affiliations": "Institute of Health Informatics, University College London, London, UK; Institute of Cardiovascular Science, University College London, London, UK & Moorfields Eye Hospital NHS Foundation Trust, London, UK.; Moorfields Eye Hospital NHS Turst & Institute of Ophthalmology UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Health Informatics, University College London, London, UK; Bart's Health NHS Trust, London, UK; King's College Hospital NHS Trust, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Faculty of Medicine, University of Southampton, Southampton, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL; Moorfields Eye Hospital NHS Foundation Trust, London, UK; Institute of Health Informatics, University College London, London, UK; Moorfields Eye Hospital NHS Trust & Institute of Ophthalmology UCL; ", - "abstract": "ObjectivesTo report the reduction in new neovascular age-related macular degeneration (nAMD) referrals during the COVID-19 pandemic and estimate the impact of delayed treatment on visual outcomes at one year.\n\nDesignRetrospective clinical audit and simulation model.\n\nSettingMultiple UK NHS ophthalmology centres.\n\nParticipantsData on the reduction in new nAMD referrals was obtained from four NHS Trusts in England comparing April 2020 to April 2019. To estimate the potential impact on one-year visual outcomes, a stratified bootstrap simulation model was developed drawing on an electronic medical records dataset of 20,825 nAMD eyes from 27 NHS Trusts.\n\nMain outcome measuresSimulated mean visual acuity and proportions of eyes with vision [≤]6/60, [≤]6/24 and [≥]6/12 at one year under four hypothetical scenarios: no treatment delay, 3, 6 and 9-month treatment delays. Estimated additional number of eyes with vision [≤]6/60 at one year nationally.\n\nResultsThe number of nAMD referrals at four major eye treatment hospital groups based in England dropped on average by 72% (range 65 to 87%) in April 2020 compared to April 2019. Simulated one-year visual outcomes for 1000 nAMD eyes with a 3-month treatment delay suggested an increase in the proportion of eyes with vision [≤]6/60 from 15.5% (13.2 to 17.9) to 23.3% (20.7 to25.9), and a decrease in the proportion of eyes with vision [≥]6/12 (driving vision) from 35.1% (32.1 to 38.1) to 26.4% (23.8 to29.2). Outcomes worsened incrementally with longer modelled delays. Assuming nAMD referrals are reduced to this level at the national level for only one month, these simulated results suggest an additional 186-365 eyes with vision [≤]6/60 at one-year with even a short treatment delay.\n\nConclusionsWe report a large decrease in nAMD referrals during the first month of COVID-19 lockdown and provide an important public health message regarding the risk of delayed treatment. As a conservative estimate, a treatment delay of 3 months could lead to a >50% relative increase in the number of eyes with vision [≤]6/60 and 25% relative decrease in the number of eyes with driving vision at one year.", - "category": "ophthalmology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.06.02.20118489", @@ -9449,6 +9449,20 @@ "author_similarity": 96, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.05.19.20106641", + "date": "2020-05-26", + "link": "https://medrxiv.org/cgi/content/short/2020.05.19.20106641", + "title": "Study Data Element Mapping: Feasibility of Defining Common Data Elements Across COVID-19 Studies", + "authors": "Priscilla Mathewson; Ben Gordon; Kay Snowley; Clara Fennessy; Alastair Denniston; Neil Sebire", + "affiliations": "University of Birmingham; HDRUK; HDRUK; HDRUK; HDRUK; Great Ormond Street Hospital and ICH London", + "abstract": "BackgroundNumerous clinical studies are now underway investigating aspects of COVID-19. The aim of this study was to identify a selection of national and/or multicentre clinical COVID-19 studies in the United Kingdom to examine the feasibility and outcomes of documenting the most frequent data elements common across studies to rapidly inform future study design and demonstrate proof-of-concept for further subject-specific study data element mapping to improve research data management.\n\nMethods25 COVID-19 studies were included. For each, information regarding the specific data elements being collected was recorded. Data elements collated were arbitrarily divided into categories for ease of visualisation. Elements which were most frequently and consistently recorded across studies are presented in relation to their relative commonality.\n\nResultsAcross the 25 studies, 261 data elements were recorded in total. The most frequently recorded 100 data elements were identified across all studies and are presented with relative frequencies. Categories with the largest numbers of common elements included demographics, admission criteria, medical history and investigations. Mortality and need for specific respiratory support were the most common outcome measures, but with specific studies including a range of other outcome measures.\n\nConclusionThe findings of this study have demonstrated that it is feasible to collate specific data elements recorded across a range of studies investigating a specific clinical condition in order to identify those elements which are most common among studies. These data may be of value for those establishing new studies and to allow researchers to rapidly identify studies collecting data of potential use hence minimising duplication and increasing data re-use and interoperability", + "category": "health informatics", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.05.19.20106781", @@ -9533,20 +9547,6 @@ "author_similarity": 100, "affiliation_similarity": 100 }, - { - "site": "medRxiv", - "doi": "10.1101/2020.05.18.20086157", - "date": "2020-05-22", - "link": "https://medrxiv.org/cgi/content/short/2020.05.18.20086157", - "title": "COVID-19 in Great Britain: epidemiological and clinical characteristics of the first few hundred (FF100) cases: a descriptive case series and case control analysis", - "authors": "Nicola L Boddington; Andre Charlett; Suzanne Elgohari; Jemma L Walker; Helen Mcdonald; Chloe Byers; Laura Coughlan; Tatiana Garcia Vilaplana; Rosie Whillock; Mary Sinnathamby; Nikolaos Panagiotopoulos; Louise Letley; Pauline MacDonald; Roberto Vivancos; Obaghe Edeghere; Joseph Shingleton; Emma Bennett; Daniel J Grint; Helen Strongman; Kathryn E Mansfield; Christopher Rentsch; Caroline Minassian; Ian J Douglas; Rohini Mathur; Maria Peppa; Simon Cottrell; Jim McMenamin; Maria Zambon; Mary Ramsay; Gavin Dabrera; Vanessa Saliba; Jamie Lopez Bernal", - "affiliations": "Public Health England; Public Health England; Public Health England; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; Public Health Wales; Public Health Scotland; Public Health England; Public Health England; Public Health England; Public Health England; Public Health England", - "abstract": "ObjectivesFollowing detection of the first virologically-confirmed cases of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and underlying health conditions associated with infection of the first few hundred cases.\n\nMethodsInformation was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity, specificity and predictive value of symptoms and underlying health conditions associated with infection were conducted. Point prevalences of underlying health conditions among the UK general population were presented.\n\nFindingsThe majority of FF100 cases were imported (51.4%), of which the majority had recent travel to Italy (71.4%). 24.7% were secondary cases acquired mainly through household contact (40.4%). Children had lower odds of COVID-19 infection compared with the general population.\n\nThe clinical presentation of cases was dominated by cough, fever and fatigue. Non-linear relationships with age were observed for fever, and sensitivity and specificity of symptoms varied by age.\n\nConditions associated with higher odds of COVID-19 infection (after adjusting for age and sex) were chronic heart disease, immunosuppression and multimorbidity.\n\nConclusionThis study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study characterized underlying health conditions associated with infection and set relative risks in context with population prevalence estimates. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms.", - "category": "epidemiology", - "match_type": "fuzzy", - "author_similarity": 100, - "affiliation_similarity": 100 - }, { "site": "medRxiv", "doi": "10.1101/2020.05.18.20105288", @@ -10039,14 +10039,14 @@ }, { "site": "medRxiv", - "doi": "10.1101/2020.04.15.20066407", - "date": "2020-04-20", - "link": "https://medrxiv.org/cgi/content/short/2020.04.15.20066407", - "title": "Evaluation of antibody testing for SARS-Cov-2 using ELISA and lateral flow immunoassays", - "authors": "Emily R Adams; Mark Ainsworth; Rekha Anand; Monique I Andersson; Kathryn Auckland; J Kenneth Baillie; Eleanor Barnes; Sally Beer; John Bell; Tamsin Berry; Sagida Bibi; Miles Carroll; Senthil Chinnakannan; Elizabeth Clutterbuck; Richard J Cornall; Derrick W Crook; Thushan De Silva; Wanwisa Dejnirattisai; Kate E Dingle; Christina Dold; Alexis Espinosa; David W Eyre; Helen Farmer; Maria Fernandez Mendoza; Dominique Georgiou; Sarah J Hoosdally; Alistair Hunter; Katie Jeffrey; Paul Klenerman; Julian Knight; Clarice Knowles; Andrew J Kwok; Ullrich Leuschner; Robert Levin; Chang Liu; Cesar Lopez-Camacho; Jose Carlos Martinez Garrido; Philippa C Matthews; Hannah McGivern; Alexander J Mentzer; Jonathan Milton; Juthathip Mongkolsapaya; Shona C Moore; Marta S Oliveira; Fiona Pereira; Elena Perez Lopez; Timothy Peto; Rutger J Ploeg; Andrew Pollard; Tessa Prince; David J Roberts; Justine K Rudkin; Veronica Sanchez; Gavin R Screaton; Malcolm G Semple; Donal T Skelly; Jose Slon-Campos; Elliot Nathan Smith; Alberto Jose Sobrino Diaz; Julie Staves; David Stuart; Piyada Supasa; Tomas Surik; Hannah Thraves; Pat Tsang; Lance Turtle; A Sarah Walker; Beibei Wang; Charlotte Washington; Nicholas Watkins; James Whitehouse", - "affiliations": "Liverpool School of Tropical Medicine; Oxford University Hospitals NHS Foundation Trust; NHSBT Birmingham,; Department of Microbiology, Oxford University Hospital NHS Foundation Trust; The Wellcome Centre for Human Genetics, University of Oxford; Roslin Institute, University of Edinburgh; Nuffield Department of Medicine, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Department of Medicine, University of Oxford; Department of Health and Social Care, University of Oxford; Oxford Vaccine group, Department of Pediatrics, University of Oxford; Nuffield Department of Medicine, Centre of Tropical Medicine and Global Health and Public Health England; Nuffield Department of Medicine, University of Oxford; Oxford Vaccine Group, Department of Paediatrics, University of Oxford; Nuffield Department of Medicine, University of Oxford; NIHR Oxford Biomedical Research Centre; Department of Infection, Immunity and Cardiovascular, Disease, The Medical School, University of Sheffield; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; NIHR Oxford Biomedical Research Centre, University of Oxford; Oxford Vaccine Group, Department of Paediatrics, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Big Data Institute, University of Oxford; Department of Health and Social Care, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Oxford University Hospitals NHS Foundation Trust; Nuffield Department of Medicine, University of Oxford; NHSBT Basildon; Department of Clinical Medicine, Oxford University Hospitals NHS Foundation Trusts; Nuffield Department so Medicine, University of Oxford; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; Department of Health and Social Care, University of Oxford; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; NHSBT Oxford; Worthing Hospital, Worthing, West Sussex; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; Wellcome Centre of Genetics, Nuffield Department of Medicine, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Nuffield Department of Medicine, University of Medicine; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Wellcome Centre for Human Genetics, University of Oxford; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, University of Liverpool; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Imperial College London; Oxford University Hospitals NHS Foundation Trust; NIHR Oxford Biomedical Research centre, University of Oxford; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Department of Paediatrics, University of Oxford; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, University of Liverpool; NHSBT Oxford; Nuffield Department of Population Health & Big Data Institute, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; Health Protection Unit In Emerging and Zoonotic Infection, University of Liverpool; Nuffield Department of Clinical Neurosciences, University of Oxford; University of Oxford; Department of Health and Social Care, University of Oxford; Oxford University Hospitals NHS Foundation Trust; Oxford University Hospitals,; Wellcome Centre for Human Genetics, Nuffield Department of Medicine; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium; Oxford University Hospitals NHS Foundation Trust; NHSBT Oxford; NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, University of Liverpool; Nuffield Department of Medicine, University of Oxford; Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford; NHSBT, Birmingham; NHSBT, Cambridge; Department of Health and Social Care, University of Oxford", - "abstract": "BackgroundThe COVID-19 pandemic caused >1 million infections during January-March 2020. There is an urgent need for reliable antibody detection approaches to support diagnosis, vaccine development, safe release of individuals from quarantine, and population lock-down exit strategies. We set out to evaluate the performance of ELISA and lateral flow immunoassay (LFIA) devices.\n\nMethodsWe tested plasma for COVID (SARS-CoV-2) IgM and IgG antibodies by ELISA and using nine different LFIA devices. We used a panel of plasma samples from individuals who have had confirmed COVID infection based on a PCR result (n=40), and pre-pandemic negative control samples banked in the UK prior to December-2019 (n=142).\n\nResultsELISA detected IgM or IgG in 34/40 individuals with a confirmed history of COVID infection (sensitivity 85%, 95%CI 70-94%), vs. 0/50 pre-pandemic controls (specificity 100% [95%CI 93-100%]). IgG levels were detected in 31/31 COVID-positive individuals tested [≥]10 days after symptom onset (sensitivity 100%, 95%CI 89-100%). IgG titres rose during the 3 weeks post symptom onset and began to fall by 8 weeks, but remained above the detection threshold. Point estimates for the sensitivity of LFIA devices ranged from 55-70% versus RT-PCR and 65-85% versus ELISA, with specificity 95-100% and 93-100% respectively. Within the limits of the study size, the performance of most LFIA devices was similar.\n\nConclusionsCurrently available commercial LFIA devices do not perform sufficiently well for individual patient applications. However, ELISA can be calibrated to be specific for detecting and quantifying SARS-CoV-2 IgM and IgG and is highly sensitive for IgG from 10 days following first symptoms.", - "category": "infectious diseases", + "doi": "10.1101/2020.04.16.20067504", + "date": "2020-04-21", + "link": "https://medrxiv.org/cgi/content/short/2020.04.16.20067504", + "title": "The effect of inter-city travel restrictions on geographical spread of COVID-19: Evidence from Wuhan, China", + "authors": "Billy J Quilty; Charlie Diamond; Yang Liu; Hamish Gibbs; Timothy W Russell; Christopher I Jarvis; Kiesha Prem; Carl A B Pearson; Samuel J Clifford; Stefan Flasche; CMMID COVID-19 working group; Petra Klepac; Rosalind M Eggo; Mark Jit", + "affiliations": "London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; ; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine; London School of Hygiene and Tropical Medicine", + "abstract": "BackgroundTo contain the spread of COVID-19, a cordon sanitaire was put in place in Wuhan prior to the Lunar New Year, on 23 January 2020, restricting travel to other parts of China. We assess the efficacy of the cordon sanitaire to delay the introduction and onset of local transmission of COVID-19 in other major cities in mainland China.\n\nMethodsWe estimated the number of infected travellers from Wuhan to other major cities in mainland China from November 2019 to March 2020 using previously estimated COVID-19 prevalence in Wuhan and publicly available mobility data. We focused on Beijing, Chongqing, Hangzhou, and Shenzhen as four representative major cities to identify the potential independent contribution of the cordon sanitaire and holiday travel. To do this, we simulated outbreaks generated by infected arrivals in these destination cities using stochastic branching processes. We also modelled the effect of the cordon sanitaire in combination with reduced transmissibility scenarios representing the effect of local non-pharmaceutical interventions.\n\nFindingsIn the four cities, given the potentially high prevalence of COVID-19 in Wuhan between Dec 2019 and early Jan 2020, local transmission may have been seeded as early as 2 - 8 January 2020. By the time the cordon sanitaire was imposed, simulated case counts were likely in the hundreds. The cordon sanitaire alone did not substantially affect the epidemic progression in these cities, although it may have had some effect in smaller cities.\n\nInterpretationOur results indicate that the cordon sanitaire may not have prevented COVID-19 spread in major Chinese cities; local non-pharmaceutical interventions were likely more important for this.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSIn late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected in Wuhan, China. In response to the outbreak, authorities enacted a cordon sanitaire in order to limit spread. Several studies have sought to determine the efficacy of the policy; a search of PubMed for \"coronavirus AND (travel restrictions OR travel ban OR shutdown OR cordon sanitaire) AND (Wuhan OR China)\" returned 24 results. However other studies have relied on reported cases to determine efficacy, which are likely subject to reporting and testing biases. Early outbreak dynamics are also subject to a significant degree of stochastic uncertainty due to small numbers of cases.\n\nAdded value of this studyHere we use publicly-available mobility data and a stochastic branching process model to evaluate the efficacy of the cordon sanitaire to limiting the spread of COVID-19 from Wuhan to other cities in mainland China, while accounting for underreporting and uncertainty. We find that although travel restrictions led to a significant decrease in the number of individuals leaving Wuhan during the busy post-Lunar New Year holiday travel period, local transmission was likely already established in major cities. Thus, the travel restrictions likely did not affect the epidemic trajectory substantially in these cities.\n\nImplications of all the available evidenceA cordon sanitaire around the epicentre alone may not be able to reduce COVID-19 incidence when implemented after local transmission has occurred in highly connected neighbors. Local non-pharmaceutical interventions to reduce transmissibility (e.g., school and workplace closures) may have contributed more to the observed decrease in incidence in mainland China.", + "category": "epidemiology", "match_type": "fuzzy", "author_similarity": 100, "affiliation_similarity": 100 @@ -10065,6 +10065,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.04.09.20059865", + "date": "2020-04-14", + "link": "https://medrxiv.org/cgi/content/short/2020.04.09.20059865", + "title": "Forecasting the scale of the COVID-19 epidemic in Kenya", + "authors": "Samuel P C Brand; Rabia Aziza; Ivy K Kombe; Charles N Agoti; Joe Hilton; Kat S Rock; Andrea Parisi; D James Nokes; Matt Keeling; Edwine Barasa", + "affiliations": "University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme; Kenya Medical Research Institute, Wellcome Trust Research Programme; University of Warwick; University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme and University of Warwick; University of Warwick; Kenya Medical Research Institute, Wellcome Trust Research Programme", + "abstract": "BackgroundThe first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya.\n\nMethodsWe developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak.\n\nResultsWe find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 -2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.", + "category": "infectious diseases", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.04.10.20059121", @@ -10303,6 +10317,20 @@ "author_similarity": 100, "affiliation_similarity": 100 }, + { + "site": "medRxiv", + "doi": "10.1101/2020.02.12.20022566", + "date": "2020-02-14", + "link": "https://medrxiv.org/cgi/content/short/2020.02.12.20022566", + "title": "A spatial model of CoVID-19 transmission in England and Wales: early spread and peak timing", + "authors": "Leon Danon; Ellen Brooks-Pollock; Mick Bailey; Matt J Keeling", + "affiliations": "University of Exeter; University of Bristol; University of Bristol; University of Warwick", + "abstract": "BackgroundAn outbreak of a novel coronavirus, named CoVID-19, was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable cases of human-to-human transmission in England.\n\nMethodsWe adapted an existing national-scale metapopulation model to capture the spread of CoVID-19 in England and Wales. We used 2011 census data to capture population sizes and population movement, together with parameter estimates from the current outbreak in China.\n\nResultsWe predict that a CoVID-19 outbreak will peak 126 to 147 days ([~]4 months) after the start of person-to-person transmission in England and Wales in the absence of controls, assuming biological parameters remain unchanged. Therefore, if person-to-person transmission persists from February, we predict the epidemic peak would occur in June. The starting location has minimal impact on peak timing, and model stochasticity varies peak timing by 10 days. Incorporating realistic parameter uncertainty leads to estimates of peak time ranging from 78 days to 241 days after person-to-person transmission has been established. Seasonal changes in transmission rate substantially impact the timing and size of the epidemic peak, as well as the total attack rate.\n\nDiscussionWe provide initial estimates of the potential course of CoVID-19 in England and Wales in the absence of control measures. These results can be refined with improved estimates of epidemiological parameters, and permit investigation of control measures and cost effectiveness analyses. Seasonal changes in transmission rate could shift the timing of the peak into winter months, which will have important implications for health-care capacity planning.", + "category": "epidemiology", + "match_type": "fuzzy", + "author_similarity": 100, + "affiliation_similarity": 100 + }, { "site": "medRxiv", "doi": "10.1101/2020.02.12.20022426", diff --git a/data/covid/raw-preprints.json b/data/covid/raw-preprints.json index 4b0a0a6e..4a9736cd 100644 --- a/data/covid/raw-preprints.json +++ b/data/covid/raw-preprints.json @@ -1,4 +1,51 @@ [ + { + "rel_doi": "10.1101/2024.02.25.581989", + "rel_title": "TISSUE-SPECIFIC METABOLOMIC REPROGRAMMING DETERMINES THE DISEASE PATHOPHYSIOLOGY OF SARS-COV-2 VARIANTS IN HAMSTER MODEL", + "rel_date": "2024-02-27", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2024.02.25.581989", + "rel_abs": "Despite significant effort, a clear understanding of host tissue-specific responses and their implications for immunopathogenicity against the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant infection has remained poorly defined. To shed light on the interaction between organs and specific SARS-CoV-2 variants, we sought to characterize the complex relationship among acute multisystem manifestations, dysbiosis of the gut microbiota, and the resulting implications for SARS-CoV-2 variant-specific immunopathogenesis in the Golden Syrian Hamster (GSH) model using multi-omics approaches. Our investigation revealed increased viremia in diverse tissues of delta-infected GSH compared to the omicron variant. Multi-omics analyses uncovered distinctive metabolic responses between the delta and omicron variants, with the former demonstrating dysregulation in synaptic transmission proteins associated with neurocognitive disorders. Additionally, delta-infected GSH exhibited an altered fecal microbiota composition, marked by increased inflammation-associated taxa and reduced commensal bacteria compared to the omicron variant. These findings underscore the SARS-CoV-2-mediated tissue insult, characterized by modified host metabolites, neurological protein dysregulation, and gut dysbiosis, highlighting the compromised gut-lung-brain axis during acute infection.", + "rel_num_authors": 8, + "rel_authors": [ + { + "author_name": "Urvinder Kaur Sardarni", + "author_inst": "University of Nebraska Medical Center" + }, + { + "author_name": "Anoop Ambikan", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Arpan Acharya", + "author_inst": "University of Nebraska Medical Center" + }, + { + "author_name": "Samuel D Johnson", + "author_inst": "University of Nebraska Medical Center" + }, + { + "author_name": "Sean N Avedissian", + "author_inst": "UNMC" + }, + { + "author_name": "Akos Vegvari", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Ujjwal Neogi", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Siddappa Byrareddy", + "author_inst": "University of Nebraska Medical Center" + } + ], + "version": "1", + "license": "cc_no", + "type": "new results", + "category": "systems biology" + }, { "rel_doi": "10.1101/2024.02.24.581855", "rel_title": "Biochemical characterization of naturally occurring mutations in SARS-CoV-2 RNA-dependent RNA polymerase", @@ -56,7 +103,7 @@ "rel_date": "2024-02-26", "rel_site": "bioRxiv", "rel_link": "https://biorxiv.org/cgi/content/short/2024.02.24.581861", - "rel_abs": "Protein nanoparticles are effective platforms for antigen presentation and targeting effector immune cells in vaccine development. Encapsulins are a class of protein-based microbial nanocompartments that self-assemble into icosahedral structures with external diameters ranging from 24 to 42 nm. Encapsulins from Mxyococcus xanthus were designed to package bacterial RNA when produced in E. coli and were shown to have immunogenic and self-adjuvanting properties enhanced by this RNA. We genetically incorporated a 20-mer peptide derived from a mutant strain of the SARS-CoV-2 receptor binding domain (RBD) into the encapsulin protomeric coat protein for presentation on the exterior surface of the particle. This immunogen elicited conformationally-relevant humoral responses to the SARS-CoV-2 RBD. Immunological recognition was enhanced when the same peptide was presented in a heterologous prime/boost vaccination strategy using the engineered encapsulin and a previously reported variant of the PP7 virus-like particle, leading to the development of a selective antibody response against a SARS-CoV-2 RBD point mutant. While generating epitope-focused antibody responses is an interplay between inherent vaccine properties and B/T cells, here we demonstrate the use of orthogonal nanoparticles to fine-tune the control of epitope focusing.", + "rel_abs": "Protein nanoparticles are effective platforms for antigen presentation and targeting effector immune cells in vaccine development. Encapsulins are a class of protein-based microbial nanocompartments that self-assemble into icosahedral structures with external diameters ranging from 24 to 42 nm. Encapsulins from Mxyococcus xanthus were designed to package bacterial RNA when produced in E. coli and were shown to have immunogenic and self-adjuvanting properties enhanced by this RNA. We genetically incorporated a 20-mer peptide derived from a mutant strain of the SARS-CoV-2 receptor binding domain (RBD) into the encapsulin protomeric coat protein for presentation on the exterior surface of the particle. This immunogen elicited conformationally-relevant humoral responses to the SARS-CoV-2 RBD. Immunological recognition was enhanced when the same peptide was presented in a heterologous prime/boost vaccination strategy using the engineered encapsulin and a previously reported variant of the PP7 virus-like particle, leading to the development of a selective antibody response against a SARS-CoV-2 RBD point mutant. While generating epitope-focused antibody responses is an interplay between inherent vaccine properties and B/T cells, here we demonstrate the use of orthogonal nanoparticles to fine-tune the control of epitope focusing.\n\nTable of Contents graphic\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=121 SRC=\"FIGDIR/small/581861v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (21K):\norg.highwire.dtl.DTLVardef@274ba9org.highwire.dtl.DTLVardef@1d86212org.highwire.dtl.DTLVardef@10ec207org.highwire.dtl.DTLVardef@1e499b5_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 10, "rel_authors": [ { @@ -111,7 +158,7 @@ "rel_date": "2024-02-26", "rel_site": "bioRxiv", "rel_link": "https://biorxiv.org/cgi/content/short/2024.02.23.581160", - "rel_abs": "Plasma proteomic is a precious tool in human disease research, but requires extensive sample preparation in order to perform in-depth analysis and biomarker discovery using traditional Data-Dependent Acquisition (DDA). Here, we highlight the efficacy of combining moderate plasma prefractionation and Data-Independent Acquisition (DIA) to significantly improve proteome coverage and depth, while remaining cost- and time-efficient. Using human plasma collected from a 20-patient COVID-19 cohort, our method utilises commonly available solutions for depletion, sample preparation, and fractionation, followed by 3 LC-MS/MS injections for a 360-minutes DIA run time. DIA-NN software was then used for precursor identification, and the QFeatures R package was used for protein aggregation. We detect 1,321 proteins on average per patient, and 2,031 unique proteins across the cohort. Filtering precursors present in under 25% of patients, we still detect 1,230 average proteins and 1,590 unique proteins, indicating robust protein identification. Differential analysis further demonstrates the applicability of this method for plasma proteomic research and clinical biomarker identification. In summary, this study introduces a streamlined, cost- and time-effective approach to deep plasma proteome analysis, expanding its utility beyond classical research environments and enabling larger-scale multi-omics investigations in clinical settings.", + "rel_abs": "Plasma proteomic is a precious tool in human disease research, but requires extensive sample preparation in order to perform in-depth analysis and biomarker discovery using traditional Data-Dependent Acquisition (DDA). Here, we highlight the efficacy of combining moderate plasma prefractionation and Data-Independent Acquisition (DIA) to significantly improve proteome coverage and depth, while remaining cost- and time-efficient.\n\nUsing human plasma collected from a 20-patient COVID-19 cohort, our method utilises commonly available solutions for depletion, sample preparation, and fractionation, followed by 3 LC-MS/MS injections for a 360-minutes DIA run time. DIA-NN software was then used for precursor identification, and the QFeatures R package was used for protein aggregation.\n\nWe detect 1,321 proteins on average per patient, and 2,031 unique proteins across the cohort. Filtering precursors present in under 25% of patients, we still detect 1,230 average proteins and 1,590 unique proteins, indicating robust protein identification. Differential analysis further demonstrates the applicability of this method for plasma proteomic research and clinical biomarker identification.\n\nIn summary, this study introduces a streamlined, cost- and time-effective approach to deep plasma proteome analysis, expanding its utility beyond classical research environments and enabling larger-scale multi-omics investigations in clinical settings.", "rel_num_authors": 15, "rel_authors": [ { @@ -2319,57 +2366,37 @@ "category": "sexual and reproductive health" }, { - "rel_doi": "10.1101/2024.02.17.24302973", - "rel_title": "Increased reproductive tract infections among secondary school girls during the COVID-19 pandemic: associations with pandemic related stress, mental health, and domestic safety", + "rel_doi": "10.1101/2024.02.12.24302535", + "rel_title": "RISK OF THROMBOEMBOLISM AFTER COVID-19 VACCINATION AND COVID-19 INFECTION.", "rel_date": "2024-02-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2024.02.17.24302973", - "rel_abs": "BackgroundKenya, like many countries, shuttered schools during COVID-19, with subsequent increases in poor mental health, sexual activity, and pregnancy. We sought to understand how the COVID-19 pandemic may mediate risk of reproductive tract infections. We hypothesized that greater COVID-19 related stress would mediate risk via mental health, feeling safe inside the home, and sexual exposure, given the pandemic mitigation-related impacts of school closures on these factors.\n\nMethodsWe analyzed data from a cohort of 436 girls enrolled in secondary school in rural western Kenya. Baseline, 6-, 12-, and 18-month study visits occurred April 2018 - December 2019 (pre-COVID), and 30-, 36-, and 48-month study visits occurred September 2020 - July 2022 (COVID period). At study visits, participants self-completed a survey for sociodemographics and sexual practices, and provided self-collected vaginal swabs for Bacterial vaginosis (BV) testing, with STI testing at annual visits. COVID-related stress was measured with a standardized scale and dichotomized at highest quartile. Mixed effects modeling quantified how BV and STI changed over time, and longitudinal mediation analysis quantified how the relationship between COVID-19 stress and increased BV was mediated.\n\nFindingsBV and STI prevalence increased from 12.1% and 10.7% pre-COVID to 24.5% and 18.1% during COVID, respectively. This equated to a 26% (95% CI 1.00 - 1.59) and 36% (95% CI 0.98 - 1.88) increased relative prevalence of BV and STIs, respectively, in the COVID-19 period compared to pre-COVID, adjusted for numerous sociodemographic and behavioral factors. Higher COVID-related stress was associated with elevated depressive symptoms and feeling less safe inside the home, which were each associated with increased likelihood of having a boyfriend. In longitudinal mediation analyses, the direct effect of COVID-related stress on BV was small and non-significant, indicating increased BV was due to the constellation of factors that were impacted during the COVID-pandemic.\n\nConclusionsIn this cohort of adolescent girls, BV and STIs increased following COVID-related school closures. These results highlight modifiable factors to help maintain sexual and reproductive health resiliency, such as anticipating and mitigating mental health impacts, domestic safety concerns, and maintaining sexual health services to prevent and treat reproductive tract infections.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2024.02.12.24302535", + "rel_abs": "BackgroundVaccine safety monitoring systems worldwide have reported cases of venous thromboembolism and arterial thromboembolism following a COVID-19 vaccination. However, evidence shows that the association between thromboembolism and SARS-CoV-2 infection is stronger, compared to SARS-CoV-2 vaccination. Hence, weighing the risks and benefits of vaccination should also encounter the roles of vaccination in reducing infection rate, and potentially indirectly lowering the risk of thromboembolism caused by infection.\n\nMethodsWe conducted a self-controlled case series study (SCCS) from Dec 1st 2020 to 31st August 2022 (before the bivalent vaccine was available) to examinate the association between the first two doses Pfizer/Moderna vaccination and thrombotic events among patients in Corewell Health East (CHE, formerly known as Beaumont Health) healthcare system. We also investigated the effect SARS-CoV-2 infection on the risk of thrombosis events and observed a significant increased risk using the SCCS design. However, because of misclassification bias, SCCS indeed overestimated incidence rate ratio (IRR) of acute event after infection, we then proposed a case-control study addressing this misclassification issues and obtained odd ratio comparing effect of exposure on thrombosis and a subset of controls group. Finally, we analyzed the risk of thromboembolism between vaccinated and unvaccinated groups by a simple diagram, explaining possible factors that affects the probability of experiencing an acute thromboembolism event after a COVID-19 vaccination.\n\nResultsUsing EHR data at Corewell East, we found an increased risk of thrombosis after the first two doses of COVID-19 vaccination, with incidence rate ratios after the first dose is 1.16 (CI: [1.04, 1.29]), and after the second dose of 1.19 (CI: [1.07,1.32]). The association between thromboembolism and SARS-Cov-2 infection depends on prior vaccination status, as the conditional OR among unvaccinated and vaccinated groups are 1.77 (CI: [1.48, 2.1]) and 1.34 (CI: [1.09, 1.66]) respectively. Encountering the vaccine efficacy (VE), receiving the COVID-19 vaccine decreases the risk of thromboembolism, and the benefits of COVID-19 vaccines are much stronger in the period of high infection rate.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Supriya D Mehta", - "author_inst": "Rush University Medical College, University of Illinois Chicago" - }, - { - "author_name": "Debarghya Nandi", - "author_inst": "University of Illinois Chicago" - }, - { - "author_name": "Fredrick Otieno", - "author_inst": "Nyanza Reproductive Health Society" - }, - { - "author_name": "Garazi Zulaika", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Elizabeth Nyothach", - "author_inst": "Kenya Medical Research Institute" - }, - { - "author_name": "Walter Agingu", - "author_inst": "Nyanza Reproductive Health Society" + "author_name": "Huong Tran", + "author_inst": "Corewell Health" }, { - "author_name": "Runa Bhaumik", - "author_inst": "University of Illinois at Chicago" + "author_name": "Malcolm Risk", + "author_inst": "University of Michigan" }, { - "author_name": "Linda Mason", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Yung-Chun Lee", + "author_inst": "Beaumont Research Institute, Corewell Health East" }, { - "author_name": "Anna M van Eijk", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Girish Nair.B", + "author_inst": "Corewell Health" }, { - "author_name": "Penelope A Phillips-Howard", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Lili Zhao", + "author_inst": "Corewell Health" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -2708,7 +2735,7 @@ "rel_date": "2024-02-16", "rel_site": "bioRxiv", "rel_link": "https://biorxiv.org/cgi/content/short/2024.02.15.580500", - "rel_abs": "SARS-CoV-2 genomes collected at the onset of the Covid-19 pandemic are valuable because they could help understand how the virus entered the human population. In 2021, Jesse Bloom reported on the recovery of a dataset of raw sequencing reads that had been removed from the NCBI SRA database at the request of the data generators, a scientific team at Wuhan University (Wang et al., 2020b). Bloom suggested that the data may have been removed in order to obfuscate the origin of SARS-CoV-2, and he questioned the generating authors' statements that the samples had been collected on and after January 30, 2020. Here, we show that sample collection dates were published in 2020 by Wang et al. together with the sequencing reads, and match the dates given by the authors in 2021. We examine mutations in these sequences and confirm that they are entirely consistent with the previously known genetic diversity of SARS-CoV-2 of late January 2020. Finally, we explain how an apparent phylogenetic rooting paradox described by Bloom was resolved by subsequent analysis. Our reanalysis demonstrates that allegations of cover-up or of metadata manipulation were unwarranted.", + "rel_abs": "SARS-CoV-2 genomes collected at the onset of the Covid-19 pandemic are valuable because they could help understand how the virus entered the human population. In 2021, Jesse Bloom reported on the recovery of a dataset of raw sequencing reads that had been removed from the NCBI SRA database at the request of the data generators, a scientific team at Wuhan University (Wang et al., 2020b). Bloom suggested that the data may have been removed in order to obfuscate the origin of SARS-CoV-2, and he questioned the generating authors statements that the samples had been collected on and after January 30, 2020. Here, we show that sample collection dates were published in 2020 by Wang et al. together with the sequencing reads, and match the dates given by the authors in 2021. We examine mutations in these sequences and confirm that they are entirely consistent with the previously known genetic diversity of SARS-CoV-2 of late January 2020. Finally, we explain how an apparent phylogenetic rooting paradox described by Bloom was resolved by subsequent analysis. Our reanalysis demonstrates that allegations of cover-up or of metadata manipulation were unwarranted.\n\nNote for bioRxiv readersThe automatically generated Full Text version of our manuscript is missing footnotes; they are available in the PDF version.", "rel_num_authors": 2, "rel_authors": [ { @@ -3977,47 +4004,103 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2024.02.12.579977", - "rel_title": "Identification of SARS-CoV-2 Mpro inhibitors through deep reinforcement learning for de novo drug design and computational chemistry approaches", + "rel_doi": "10.1101/2024.02.12.580004", + "rel_title": "SARS-CoV-2 Omicron lineage XBB spike structures, conformations, antigenicity, and receptor recognition", "rel_date": "2024-02-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2024.02.12.579977", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of coronavirus disease (COVID-19) since its emergence in December 2019. As of January 2024, there has been over 774 million reported cases and 7 million deaths worldwide.[1] While vaccination efforts have been successful in reducing the severity of the disease and decreasing the transmission rate, the development of effective therapeutics against SARS-CoV-2 remains a critical need.[2] The main protease (Mpro) of SARS-CoV-2 is an essential enzyme required for viral replication and has been identified as a promising target for drug development. In this study, we report the identification of novel Mpro inhibitors, using a combination of deep reinforcement learning for de novo drug design with 3D pharmacophore/shape-based alignment and privileged fragment match count scoring components followed by hit expansions and molecular docking approaches. Our experimentally validated results show that 3 novel series exhibit potent inhibitory activity against SARS-CoV-2 Mpro, with IC50 values ranging from 1.3 uM to 2.3 uM and a high degree of selectivity. These findings represent promising starting points for the development of new antiviral therapies against COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2024.02.12.580004", + "rel_abs": "A recombinant lineage of the SARS-CoV-2 Omicron variant, named XBB, appeared in late 2022 and evolved descendants that successively swept local and global populations. XBB lineage members were noted for their improved immune evasion and transmissibility. Here, we determine cryo-EM structures of XBB.1.5, XBB.1.16 and EG.5 spike (S) ectodomains to reveal enhanced occupancy of the receptor inaccessible closed state. Interprotomer receptor binding domain (RBD) interactions previously observed in BA.1 and BA.2 were retained to reinforce the 3-RBD-down state. Improved stability of XBB.1.5 and XBB.1.16 RBD compensated for loss of stability caused by early Omicron mutations, while the F456L substitution reduced EG.5 RBD stability. Long-range impacts of S1 subunit mutations affected conformation and epitope presentation in the S2 subunit. Taken together, our results feature a theme of iterative optimization of S protein stability as Omicron continues to evolve, while maintaining high affinity receptor binding and bolstering immune evasion.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Julien Hazemann", - "author_inst": "Idorsia Pharmaceuticals Ltd" + "author_name": "Qianyi E Zhang", + "author_inst": "Duke University" }, { - "author_name": "Thierry Kimmerlin", - "author_inst": "Idorsia Pharmaceuticals Ltd" + "author_name": "Jared Lindenberger", + "author_inst": "Duke University" }, { - "author_name": "Roland Lange", - "author_inst": "Idorisa Pharmaceuticals Ltd" + "author_name": "Ruth Parsons", + "author_inst": "Duke University" }, { - "author_name": "Aengus Mac Sweeney", - "author_inst": "Idorsia Pharmaceuticals Ltd" + "author_name": "Bhishem Thakur", + "author_inst": "Duke University" }, { - "author_name": "Geoffroy Bourquin", - "author_inst": "Idorsia Pharmaceuticals Ltd" + "author_name": "Rob Parks", + "author_inst": "Duke University" }, { - "author_name": "Daniel Ritz", - "author_inst": "Idorsia Pharmaceuticals Ltd" + "author_name": "Chan Soo Park", + "author_inst": "Duke University" + }, + { + "author_name": "Xiao Huang", + "author_inst": "Duke University" + }, + { + "author_name": "Salam Sammour", + "author_inst": "Duke University" + }, + { + "author_name": "Katarzyna Janowska", + "author_inst": "Duke University" + }, + { + "author_name": "Taylor N Spence", + "author_inst": "Duke University" + }, + { + "author_name": "Robert J. Edwards", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Mitchell Martin", + "author_inst": "Duke University" }, { - "author_name": "Paul Czodrowski", - "author_inst": "JGU Mainz" + "author_name": "Wilton B Williams", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Sophie Gobeil", + "author_inst": "Duke University" + }, + { + "author_name": "David C Montefiori", + "author_inst": "Duke University" + }, + { + "author_name": "Bette Korber", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Kevin O'Neil Saunders", + "author_inst": "Duke Human Vaccine Institute" + }, + { + "author_name": "Barton F Haynes", + "author_inst": "Duke University" + }, + { + "author_name": "Barton F. Haynes", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Rory Henderson", + "author_inst": "Duke University" + }, + { + "author_name": "Priyamvada Acharya", + "author_inst": "Duke University" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "molecular biology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2024.02.12.24302741", @@ -5959,59 +6042,63 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2024.02.05.578560", - "rel_title": "Building Blocks of Understanding: Constructing a Reverse Genetics Platform for studying determinants of SARS-CoV-2 replication.", + "rel_doi": "10.1101/2024.02.06.579075", + "rel_title": "Natural selection exerted by historical coronavirus epidemic(s): comparative genetic analysis in China Kadoorie Biobank and UK Biobank", "rel_date": "2024-02-06", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2024.02.05.578560", - "rel_abs": "To better understand viral pathogenesis, host-virus interactions, and potential therapeutic interventions, the development of robust reverse genetics systems for SARS-CoV-2 is crucial. Here, we present a reverse genetics platform that enables the efficient manipulation, assembly, and rescue of recombinant SARS-CoV-2. The versatility of our reverse genetics system was demonstrated by generating recombinant SARS-CoV-2 viruses. We used this system to generate N501Y and Y453F spike protein mutants. Characterization studies revealed distinct phenotypic effects, impact on viral fitness, cell binding, and replication kinetics. We also investigated a recently discovered priming site for NSP9, which is postulated to produce a short RNA antisense leader sequence. By introducing the U76G mutation into the 5UTR, we show that this priming site is necessary for the correct production of genomic and subgenomic RNAs, and also for efficient viral replication. In conclusion, our developed reverse genetics system provides a robust and adaptable platform for the efficient generation of recombinant SARS-CoV-2 viruses for their comprehensive characterization.\n\nSignificance statementIn this study, we present a versatile reverse genetics platform facilitating the efficient manipulation, assembly, and rescue of recombinant SARS-CoV-2. Demonstrating its adaptability, we successfully engineered N501Y and Y453F spike protein mutants, each exhibiting distinct phenotypic effects on viral fitness, cell binding, and replication kinetics. We also investigated a novel negative sense priming site for NSP9, demonstrating a role in RNA production and viral replication. This straightforward reverse genetic system is therefore a powerful tool to generate recombinant viruses for advancing our understanding of SARS-CoV-2 biology.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2024.02.06.579075", + "rel_abs": "BackgroundPathogens have been one of the primary sources of natural selection affecting modern humans. The footprints of historical selection events - \"selective sweeps\" - can be detected in the genomes of present-day individuals. Previous analyses of 629 samples from the 1000 Genomes Project suggested that an ancient coronavirus epidemic [~]20,000 years ago drove multiple selective sweeps in the ancestors of present-day East Asians, but not in other worldwide populations.\n\nResultsUsing a much larger genetic dataset of 76,719 unrelated individuals from each of the China Kadoorie Biobank (CKB) and UK Biobank (UKB) to identify regions of long-range linkage disequilibrium, we further investigated signatures of past selective sweeps and how they reflect previous viral epidemics. Using independently-curated lists of human host proteins which interact physically or functionally with viruses (virus-interacting proteins; VIPs), we found enrichment in CKB for regions of long-range linkage disequilibrium at genes encoding VIPs for coronaviruses, but not DNA viruses. By contrast, we found no clear evidence for any VIP enrichment in UKB. These findings were supported by additional analyses using saltiLASSi, a selection-scan method robust to false positives caused by demographic events. By contrast, for GWAS signals for SARS-Cov2 susceptibility (critical illness, hospitalisation, and reported infection), there was no difference between UKB and CKB in the number located at or near signals of selection, as expected for a novel virus which has had no opportunity to impact the CKB/UKB study populations.\n\nConclusionsTogether, these results provide evidence of selection events consistent with historical coronavirus epidemic(s) originating in East Asia. These results show how biobank-scale datasets and evolutionary genomics theory can provide insight into the study of past epidemics. The results also highlights how historic infectious diseases epidemics can shape the genetic architecture of present-day human populations.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Marco Olguin-Nava", - "author_inst": "Helmholtz-Institute for RNA-based Infection Research" + "author_name": "Sam C Morris", + "author_inst": "University of Oxford" }, { - "author_name": "Patrick Bohn", - "author_inst": "Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, 97080 Wuerzburg, Germany" + "author_name": "Kuang Lin", + "author_inst": "University of Oxford" }, { - "author_name": "Thomas Hennig", - "author_inst": "Institute of Virology and Immunology, University of Wuerzburg, 97080 Wuerzburg, Germany" + "author_name": "Iona Y Millwood", + "author_inst": "Oxford University" }, { - "author_name": "Charlene Boertlein", - "author_inst": "Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, 97080 Wuerzburg, Germany" + "author_name": "Canqing Yu", + "author_inst": "Peking University" }, { - "author_name": "Anne-Sophie Gribling-Burrer", - "author_inst": "Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, 97080 Wuerzburg, Germany" + "author_name": "Jun Lv", + "author_inst": "Peking University" }, { - "author_name": "Nora Schmidt", - "author_inst": "Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, 97080 Wuerzburg, Germany" + "author_name": "Pei Pei", + "author_inst": "Fuwai Hospital Chinese Academy of Medical Sciences, National Center for Cardiovascular Diseases, Beijing, China" }, { - "author_name": "Neva Caliskan", - "author_inst": "Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, 97080 Wuerzburg, Germany" + "author_name": "Liming Li", + "author_inst": "Peking University" }, { - "author_name": "Lars Doelken", - "author_inst": "Institute of Virology and Immunology, University of Wuerzburg, 97080 Wuerzburg, Germany" + "author_name": "Dianjianyi Sun", + "author_inst": "Peking University" }, { - "author_name": "Mathias Munschauer", - "author_inst": "Institute of Medical Virology, Goethe-University Frankfurt, 60596 Frankfurt am Main, Germany" + "author_name": "George Davey Smith", + "author_inst": "University of Bristol" }, { - "author_name": "Redmond P. Smyth", - "author_inst": "Helmholtz Institute for RNA-based Infection Research, Helmholtz Centre for Infection Research, 97080 Wuerzburg, Germany" + "author_name": "Zhengming Chen", + "author_inst": "Oxford University" + }, + { + "author_name": "Robin G Walters", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2024.02.05.24302352", @@ -7901,55 +7988,59 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2024.01.30.578038", - "rel_title": "A novel microporous biomaterial vaccine platform for long-lasting antibody mediated immunity against viral infection.", + "rel_doi": "10.1101/2024.01.30.24302040", + "rel_title": "Healthy lifestyle for the prevention of post-COVID-19 multisystem sequelae, hospitalization, and death: a prospective cohort study", "rel_date": "2024-01-31", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2024.01.30.578038", - "rel_abs": "Current antigen delivery platforms, such as alum and nanoparticles, are not readily tunable, thus may not generate optimal adaptive immune responses. We created an antigen delivery platform by loading lyophilized Microporous Annealed Particle (MAP) with aqueous solution containing target antigens. Upon administration of antigen loaded MAP (VaxMAP), the biomaterial reconstitution forms an instant antigen-loaded porous scaffold area with a sustained release profile to maximize humoral immunity. VaxMAP induced CD4+ T follicular helper (Tfh) cells and germinal center (GC) B cell responses in the lymph nodes similar to Alum. VaxMAP loaded with SARS-CoV-2 spike protein improved the magnitude and duration of anti-receptor binding domain antibodies compared to Alum and mRNA-vaccinated mice. A single injection of Influenza specific HA1-loaded-VaxMAP enhanced neutralizing antibodies and elicited greater protection against influenza virus challenge than HA1-loaded-Alum. Thus, VaxMAP is a platform that can be used to promote adaptive immune cell responses to generate more robust neutralizing antibodies, and better protection upon pathogen challenge.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2024.01.30.24302040", + "rel_abs": "BackgroundPost-COVID complications are emerging as a global public health crisis. Effective prevention strategies are needed to inform patients, clinicians and policy makers, and to reduce their cumulative burden. We aimed to investigate whether a habitual healthy lifestyle predated pandemic is associated with lower risks of multisystem sequelae and other adverse outcomes of COVID-19, and whether the potential protective effects are independent of pre-existing comorbidities.\n\nMethodsThe prospective population-based cohort study enrolled participants with SARS-CoV-2 infection confirmed by a positive polymerase chain reaction test result between March 1, 2020, and March 1, 2022. Participants with no history of the related outcome one year before infection were included and followed up for 210 days. Exposures included ten modifiable healthy lifestyle factors including past or never smoking, moderate alcohol intake ([≤]4 times week), body mass index <30 kg/m2, at least 150 minutes of moderate or 75 minutes of vigorous physical activity per week, less sedentary time (<4 hours per day), healthy sleep duration (7-9 hours per day), adequate intake of fruit and vegetables ([≥]400 g/day), adequate oily fish intake ([≥]1 portion/week), moderate intake of red meat ([≤]4 portions week) and processed meat ([≤]4 portions week). Outcomes included multisystem COVID-19 sequelae (consisting of 75 diseases/symptoms in 10 organ systems), death, and hospital admission following SARS-CoV-2 infection, confirmed by hospital inpatient and death records. Risk was reported in relative scale (hazard ratio [HR]) and absolute scale (absolute risk reduction [ARR]) during both the acute (the first 30 days) and post-acute (30-210 days) phases of infection using Cox models.\n\nFindingsA total of 68,896 participants (mean [SD] age, 66.6 [8.4]; 32,098 women [46.6%]) with COVID-19 were included. A favorable lifestyle (6-10 healthy lifestyle factors; 46.4%) was associated with a 36% lower risk of multisystem sequelae of COVID-19 (HR, 0.64; 95% CI, 0.58-0.69; ARR, 7.08%; 95% CI, 5.98-8.09), compared with unfavorable lifestyle (0-4 factors; 12.3%). Risk reductions were observed across all 10 prespecified organ systems including cardiovascular, coagulation, metabolic and endocrine, gastrointestinal, kidney, mental health, musculoskeletal, neurologic, and respiratory disorders, and general symptoms of fatigue and malaise. This beneficial effect was largely attributable to direct effects of healthy lifestyle, with mediation proportion ranging from 44% to 93% across organ systems. A favorable lifestyle was also associated with lower risk of post-COVID death (HR, 0.59; 95% CI, 0.52-0.66; ARR, 1.99%; 95% CI, 1.61-2.32) and hospitalization (HR, 0.78; 95% CI, 0.73-0.84; ARR, 6.14%; 95% CI, 4.48-7.68). These associations were observed after accounting for potential misclassification of lifestyle factors, and during acute and post-acute infection, in those tested positive in the hospital and community setting, and independent of vaccination status or SARS-CoV-2 variant.\n\nInterpretationAdherence to a healthy lifestyle predated pandemic was associated with substantially lower risk of complications across organ systems, death, and hospitalization following COVID-19, regardless of phases of infection, vaccination status, test setting, and SARS-CoV-2 variants, and independent of comorbidities. These findings illustrate the benefits of adhering to a healthy lifestyle to reduce the long-term adverse health consequences following SARS-CoV-2 infection.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed and MEDLINE for articles published between March 1, 2020, and December 1, 2023, using the search terms \"healthy lifestyle\", \"risk factor\", \"post-COVID condition\", \"long COVID\", \"post-acute sequelae\", \"prevention\", \"management\", and \"treatment\", with no language restrictions. Previous evidence on the prevention and management of long COVID has mainly focused on vaccination and pharmaceutical approaches, including antivirals (e.g., molnupiravir and nirmatrelvir) and other drugs (e.g., metformin). Vaccination before infection or use of antivirals in selected high-risk patients during acute infection only partially mediates the risk of COVID-19 sequelae. Evidence for the non-pharmaceutical prevention strategies are lacking. We identified only two publications on the association between healthy lifestyle and post-COVID condition, and one meta-analysis of the risk factors for long COVID symptoms. A cross-sectional study of 1981 women suggested an inverse association between healthy lifestyle factors and self-reported symptoms following infection of non-Omicron variants, which was mainly driven by BMI and sleep duration. Another study suggested an inverse prospective association between healthy lifestyle prior to infection and post-COVID cardiovascular events. High BMI and smoking are risk factors for long COVID mainly in hospitalized patients. We did not find any study that assessed the association between a composite healthy lifestyle and subsequent post-COVID complications or sequelae across organ systems, hospitalization, and death.\n\nAdded value of this studyIn a prospective, population-based cohort of 68,896 participants with COVID-19, adherence to a healthy lifestyle prior to infection was associated with a substantially lower risk of multisystem sequelae (by 20%-36%), death (by 26%-41%), and hospital admission (by 13%-22%) following COVID-19. The reduced risk of sequelae was evident across 10 prespecified organ systems, including cardiovascular, coagulation and hematologic, metabolic and endocrine, gastrointestinal, kidney, mental health, musculoskeletal, neurologic, and respiratory disorders, as well as general symptoms of fatigue and malaise. The reduced risk of multisystem sequelae, hospitalization, and death associated with a healthy lifestyle was consistently observed across participants, regardless of their vaccination status, disease severity, and major SARS-CoV-2 variants, and largely independent of relevant comorbidities. Adherence to a healthy lifestyle prior to infection was consistently and directly associated with reduced risk of sequelae and other adverse health outcomes following COVID-19.\n\nImplications of all the available evidenceThe inverse association of healthy lifestyle with multisystem sequelae was even larger than those observed in previous studies of pharmaceutical interventions in non-hospitalized patients. Considering the restricted scope of currently available therapies, such as antivirals (only selected patients at higher risk are qualified during the acute infection) and limited efficacy of vaccination in preventing long COVID, adherence to a healthy lifestyle, in combination with vaccination and, if necessary, potential medications, emerges as practical prevention and care strategies to mitigate the long-term health consequences of SARS-CoV-2 infection. These strategies are of significant clinical and public health importance in reducing the overall burden of post-COVID conditions and improving preparedness for future pandemics.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Daniel P Mayer", - "author_inst": "Rutgers New Jersey Medical School" + "author_name": "Yunhe Wang", + "author_inst": "University of Oxford" }, { - "author_name": "Mariah Nelson", - "author_inst": "Tempo Therapeutics" + "author_name": "Binbin Su", + "author_inst": "Chinese Academy of Medical Sciences/Peking Union Medical College" }, { - "author_name": "Daria Andriyanova", - "author_inst": "Tempo Therapeutics" + "author_name": "Marta Alcalde-Herraiz", + "author_inst": "University of Oxford" }, { - "author_name": "Olivia Q Antao", - "author_inst": "Rutgers New Jersey Medical School" + "author_name": "Nicola L. Barclay", + "author_inst": "University of Oxford" }, { - "author_name": "Jennifer S Chen", - "author_inst": "Yale University School of Medicine" + "author_name": "Yaohua Tian", + "author_inst": "Huazhong University of Science and Technology" }, { - "author_name": "Philip O Scumpia", - "author_inst": "Department of Medicine, Division of Dermatology, University of California Los Angeles" + "author_name": "Chunxiao Li", + "author_inst": "University of Cambridge" }, { - "author_name": "Westbrook M Weaver", - "author_inst": "Tempo Therapeutics" + "author_name": "Nicholas J. Wareham", + "author_inst": "University of Cambridge" }, { - "author_name": "Stephanie Deshayes", - "author_inst": "Tempo Therapeutics" + "author_name": "Roger Paredes", + "author_inst": "Hospital Universitari Germans Trias i Pujol" }, { - "author_name": "Jason S Weinstein", - "author_inst": "Rutgers New Jersey Medical School" + "author_name": "Junqing Xie", + "author_inst": "University of Oxford" + }, + { + "author_name": "DANIEL PRIETO-ALHAMBRA", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "immunology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2024.01.30.24301996", @@ -9777,95 +9868,27 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2024.01.23.576505", - "rel_title": "CD4+ and CD8+ T cells are required to prevent SARS-CoV-2 persistence in the nasal compartment", + "rel_doi": "10.1101/2024.01.22.24301520", + "rel_title": "Safety of BNT162b2 mRNA COVID-19 vaccine batches: A nationwide cohort study", "rel_date": "2024-01-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2024.01.23.576505", - "rel_abs": "SARS-CoV-2 is the causative agent of COVID-19 and continues to pose a significant public health threat throughout the world. Following SARS-CoV-2 infection, virus-specific CD4+ and CD8+ T cells are rapidly generated to form effector and memory cells and persist in the blood for several months. However, the contribution of T cells in controlling SARS-CoV-2 infection within the respiratory tract are not well understood. Using C57BL/6 mice infected with a naturally occurring SARS-CoV-2 variant (B.1.351), we evaluated the role of T cells in the upper and lower respiratory tract. Following infection, SARS-CoV-2-specific CD4+ and CD8+ T cells are recruited to the respiratory tract and a vast proportion secrete the cytotoxic molecule Granzyme B. Using antibodies to deplete T cells prior to infection, we found that CD4+ and CD8+ T cells play distinct roles in the upper and lower respiratory tract. In the lungs, T cells play a minimal role in viral control with viral clearance occurring in the absence of both CD4+ and CD8+ T cells through 28 days post-infection. In the nasal compartment, depletion of both CD4+ and CD8+ T cells, but not individually, results in persistent and culturable virus replicating in the nasal compartment through 28 days post-infection. Using in situ hybridization, we found that SARS-CoV-2 infection persisted in the nasal epithelial layer of tandem CD4+ and CD8+ T cell-depleted mice. Sequence analysis of virus isolates from persistently infected mice revealed mutations spanning across the genome, including a deletion in ORF6. Overall, our findings highlight the importance of T cells in controlling virus replication within the respiratory tract during SARS-CoV-2 infection.", - "rel_num_authors": 19, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2024.01.22.24301520", + "rel_abs": "BackgroundThe safety of the BNT162b2 mRNA COVID-19 vaccine has been extensively evaluated since the global rollout began. While serious adverse events are rare, safety issues continue to arise. This study evaluates the claim that earlier small vaccine batches were associated with higher rates of serious adverse events compared to later batches.\n\nMethodsA nationwide cohort study was conducted in Denmark, comprising individuals vaccinated with the BNT162b2 vaccine from 52 pre-defined batches classified into three pre-defined groups. Vaccinated individuals were matched 1:1 between batch groups on age, sex, and vaccination priority group. The study outcomes, included 27 serious adverse events, 2 negative control outcomes and all-cause mortality. Cox regression was used to estimate hazard ratios (HRs) comparing rates between batch groups in the 28-days following vaccination. We conducted two comparisons of the early small batches to two groups of larger batches used later in the pandemic.\n\nResultsIn the study period, 9,983,448 vaccinations were administered from batches in the three pre-defined groups. Slightly increased rates of arrhythmia were observed in both study comparisons, HRs 1.25 (95% CI,1.05-1.50) and 1.15 (1.00-1.31), respectively, but sensitivity analyses did not robustly support these associations. For the remaining outcomes, increased rates in both study comparisons were not observed.\n\nConclusionThis nationwide cohort study provides reassurance regarding the safety of the BNT162b2 vaccine across different batches used in Denmark. The findings support the overall safety of the vaccine, with no clinically relevant variations in serious adverse event rates between batches.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Meenakshi Kar", - "author_inst": "Emory University" - }, - { - "author_name": "Katherine E. E. Johnson", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Abigail Vanderheiden", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Elizabeth J. Elrod", - "author_inst": "Emory University" - }, - { - "author_name": "Katharine Floyd", - "author_inst": "Emory University" - }, - { - "author_name": "Elizabeth Geerling", - "author_inst": "St. Louis University School of Medicine" - }, - { - "author_name": "E. Taylor Stone", - "author_inst": "St. Louis University School of Medicine" - }, - { - "author_name": "Eduardo Salinas", - "author_inst": "Emory University" - }, - { - "author_name": "Stephanie Banakis", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Wei Wang", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Shruti Sathish", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Swathi Shrihari", - "author_inst": "Emory University" - }, - { - "author_name": "Meredith E. Davis-Gardner", - "author_inst": "Emory University" - }, - { - "author_name": "Jacob Kohlmeier", - "author_inst": "Emory University" - }, - { - "author_name": "Amelia Pinto", - "author_inst": "Saint Louis University" - }, - { - "author_name": "Robyn Klein", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Arash Grakoui", - "author_inst": "Emory University" - }, - { - "author_name": "Elodie Ghedin", - "author_inst": "National Institutes of Health" + "author_name": "Anders Hviid", + "author_inst": "Statens Serum Institut" }, { - "author_name": "Mehul S. Suthar", - "author_inst": "Emory University" + "author_name": "Ingrid Bech Svalgaard", + "author_inst": "Statens Serum Institut" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "immunology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2024.01.24.24301644", @@ -11823,31 +11846,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2024.01.17.24301326", - "rel_title": "Why did people not get vaccinated against COVID-19? Results from a nationwide survey among Mexican adults", - "rel_date": "2024-01-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2024.01.17.24301326", - "rel_abs": "ObjectiveTo explore the reasons for not getting vaccinated against COVID-19.\n\nMaterial and methodsIn October 2021, a nationwide structured telephone survey (disproportionate stratified sampling) was conducted regarding COVID-19 pandemics, including vaccination experience. To examine associations between inoculation and other characteristics, the chi-square test and logistic regression analysis were applied.\n\nResultsOut of 3 126 adults, 68% reported complete vaccination and 21% only the first dose, while 11% remained unvaccinated. Non-vaccination was associated with being younger, male, without a partner, low socioeconomic level, and no previous diagnosis of hypertension, obesity or diabetes. Furthermore, the non-vaccinated were less likely to have tested for COVID-19, and more likely to consider COVID-19 as low severe and not real compared with the vaccinated. Using logistic regression models: place of residence, marital status, educational level, age, BMI, testing for COVID-19, and the perception of COVID-19 (severe and real) were significant predictors of non-vaccination. The predominant reasons for not getting vaccinated were: 63% \"external barriers\" (e.g., not being able to attend an appointment), and 37% \"internal motives\" (e.g., \"vaccine does not work\").\n\nConclusionsThe causes of non-vaccination against COVID-19 are related to both social and geographical determinants. Addressing external barriers is necessary in order to promote equity in vaccination. Reviewing the results in the context of earlier studies on the willingness to vaccinate, the gap between intention and vaccination is notable.", - "rel_num_authors": 3, + "rel_doi": "10.1101/2024.01.15.575735", + "rel_title": "AnnoView enables large-scale analysis, comparison, and visualization of microbial gene neighborhoods", + "rel_date": "2024-01-16", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2024.01.15.575735", + "rel_abs": "The analysis and comparison of gene neighborhoods is a powerful approach for exploring microbial genome structure, function, and evolution. Although numerous tools exist for genome visualization and comparison, genome exploration across large genomic databases or user-generated datasets remains a challenge. Here, we introduce AnnoView, a web server designed for interactive exploration of gene neighborhoods across the bacterial and archaeal tree of life. Our server offers users the ability to identify, compare, and visualize gene neighborhoods of interest from 30,238 bacterial genomes and 1,672 archaeal genomes, through integration with the comprehensive GTDB and AnnoTree databases. Identified gene neighborhoods can be visualized using pre-computed functional annotations from different sources such as KEGG, Pfam, and TIGRFAM, or clustered based on similarity. Alternatively, users can upload and explore their own custom genomic datasets in GBK, GFF, or CSV format, or use AnnoView as a genome browser for relatively small genomes (e.g., viruses and plasmids). Ultimately, we anticipate that AnnoView will catalyze biological discovery by enabling user-friendly search, comparison, and visualization of genomic data. AnnoView is available at http://annoview.uwaterloo.ca", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Dagmara Wrzecionkowska", - "author_inst": "UNAM" + "author_name": "Xin Wei", + "author_inst": "University of Waterloo" }, { - "author_name": "Christopher R. Stephens", - "author_inst": "Universidad Nacional Autonoma de Mexico" + "author_name": "Huagang Tan", + "author_inst": "University of Waterloo" }, { - "author_name": "Juan Pablo Gutierrez Reyes", - "author_inst": "UNAM" + "author_name": "Briallen Lobb", + "author_inst": "University of Waterloo" + }, + { + "author_name": "William Zhen", + "author_inst": "University of Waterloo" + }, + { + "author_name": "Zijing Wu", + "author_inst": "University of Waterloo" + }, + { + "author_name": "Donovan H Parks", + "author_inst": "University of Queensland" + }, + { + "author_name": "Josh D Neufeld", + "author_inst": "University of Waterloo" + }, + { + "author_name": "Gabriel Moreno-Hagelsieb", + "author_inst": "Wilfrid Laurier University" + }, + { + "author_name": "Andrew C Doxey", + "author_inst": "University of Waterloo" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2024.01.15.575706", @@ -14053,51 +14100,83 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2024.01.10.574981", - "rel_title": "Variant-specific interactions at the plasma membrane: Heparan sulfate's impact on SARS-CoV-2 binding kinetics", + "rel_doi": "10.1101/2024.01.10.574801", + "rel_title": "scRNA-seq reveals persistent aberrant differentiation of nasal epithelium driven by TNF\u03b1 and TGF\u03b2 in post-COVID syndrome", "rel_date": "2024-01-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2024.01.10.574981", - "rel_abs": "The worldwide spread of SARS-CoV-2 has been characterised by the emergence of several variants of concern (VOCs) presenting an increasing number of mutations in the viral genome. The spike glycoprotein, responsible for engaging the viral receptor ACE2, exhibits the highest density of mutations, suggesting an ongoing evolution to optimize viral entry. However, previous studies focussed on isolated molecular interactions, neglecting the intricate composition of the plasma membrane and the interplay between viral attachment factors. Our study explores the role of avidity and of the complexity of the plasma membrane composition in modulating the virus-host binding kinetics during the early stages of viral entry for the original Wuhan strain and three VOCs: Omicron BA.1, Delta, and Alpha. We employ fluorescent liposomes decorated with spike from several VOCs as virion mimics in single-particle tracking studies on native supported lipid bilayers derived from pulmonary Calu-3 cells. Our findings reveal an increase in the affinity of the multivalent bond to the cell surface for Omicron driven by an increased association rate. We show that heparan sulfate (HS), a sulfated glycosaminoglycan commonly expressed on cells plasma membrane, plays a central role in modulating the interaction with the cell surface and we observe a shift in its role from screening the interaction with ACE2 in early VOCs to an important binding factor for Omicron. This is caused by a [~]10-fold increase in Omicrons affinity to HS compared to the original Wuhan strain, as shown using atomic force microscopy-based single-molecule force spectroscopy. Our results show the importance of coreceptors, particularly HS, and membrane complexity in the modulation of the attachment in SARS-CoV-2 VOCs. We highlight a transition in the variants attachment strategy towards the use of HS as an initial docking site, which likely plays a role in shaping Omicrons tropism towards infection of the upper airways, milder symptoms, and higher transmissibility.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2024.01.10.574801", + "rel_abs": "Post-COVID syndrome (PCS) currently affects approximately 3-17% of people following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and has the potential to become a significant global health burden. PCS presents with various symptoms, and methods for improved PCS assessment are presently developed to guide therapy. Nevertheless, there are few mechanistic insights and treatment options. Here, we performed single-cell RNA transcriptomics on nasal biopsies from 33 patients suffering from PCS with mild, moderate, or severe symptoms. We identified 17 different cell clusters representing 12 unique cell populations, including all major epithelial cell types of the conducting airways and basal, secretory, and ciliated cells. Severe PCS was associated with decreased numbers of ciliated cells and the presence of immune cells. Ensuing inflammatory signaling upregulated TGF{beta} and induced an epithelial-mesenchymal transition, which led to the high abundance of basal cells and a mis-stratified epithelium. We confirmed the results in vitro using an air-liquid interface culture and validated TNF as the causal inflammatory cytokine. In summary, our results show that one mechanism for sustained PCS is not through continued viral load, but through the presence of immune cells in nasal tissue leading to impaired mucosal barrier function and repeated infections. These findings could be further explored as a therapeutic option akin to other chronic inflammatory diseases by inhibiting the TNF-TGF{beta} axis, restoring the nasal epithelium, and reducing respiratory tract-related infections.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Dario Valter Conca", - "author_inst": "Department of Clinical Microbiology, Ume\u00e5 University, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Ume\u00e5 University, Sweden; Ume\u00e5 Centre for Microbia" + "author_name": "Anke Faehnrich", + "author_inst": "Institute of Experimental Dermatology, University of Luebeck" + }, + { + "author_name": "Karosham Reddy", + "author_inst": "Department of Pediatric Pneumology and Allergology, The University of Luebeck" + }, + { + "author_name": "Fabian Ott", + "author_inst": "Institute of Experimental Dermatology, University of Luebeck" + }, + { + "author_name": "Yamil Maluje", + "author_inst": "Institute of Experimental Dermatology, University of Luebeck" + }, + { + "author_name": "Rochi Saurabh", + "author_inst": "Institute of Experimental Dermatology, University of Luebeck" + }, + { + "author_name": "Ann-Cathrin Schaaf", + "author_inst": "Department of Pediatric Pneumology and Allergology, The University of Luebeck" + }, + { + "author_name": "Sanja Winkelmann", + "author_inst": "Department of Otorhinolaryngology, Head and Neck Surgery, Christian-Albrechts-University Kiel" + }, + { + "author_name": "Bettina Voss", + "author_inst": "Department of Otorhinolaryngology, Head and Neck Surgery, Christian-Albrechts-University Kiel" }, { - "author_name": "Fouzia Bano", - "author_inst": "Department of Clinical Microbiology, Ume\u00e5 University, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Ume\u00e5 University, Sweden; Ume\u00e5 Centre for Microbi" + "author_name": "Martin Laudien", + "author_inst": "Department of Otorhinolaryngology, Head and Neck Surgery, Christian-Albrechts-University Kiel" }, { - "author_name": "Julius von Wir\u00e9n", - "author_inst": "Department of Clinical Microbiology, Ume\u00e5 University, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Ume\u00e5 University, Sweden; Ume\u00e5 Centre for Microbi" + "author_name": "Thomas Bahmer", + "author_inst": "Internal Medicine Department I, University Hospital Schleswig-Holstein Campus Kiel" }, { - "author_name": "Lauriane Scherrer", - "author_inst": "Department of Clinical Microbiology, Ume\u00e5 University, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Ume\u00e5 University, Sweden; Ume\u00e5 Centre for Microbi" + "author_name": "Jan Heyckendorf", + "author_inst": "Internal Medicine Department I, University Hospital Schleswig-Holstein Campus Kiel" }, { - "author_name": "Justas Svirelis", - "author_inst": "Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Sweden" + "author_name": "Folke Brinkmann", + "author_inst": "Department of Pediatric Pneumology and Allergology, The University of Luebeck" }, { - "author_name": "Konrad Thorsteinsson", - "author_inst": "Department of Clinical Microbiology, Ume\u00e5 University, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Ume\u00e5 University, Sweden; Ume\u00e5 Centre for Microbi" + "author_name": "Stefan Schreiber", + "author_inst": "Internal Medicine Department I, University Hospital Schleswig-Holstein Campus Kiel" }, { - "author_name": "Andreas Dahlin", - "author_inst": "Department of Chemistry and Chemical Engineering, Chalmers University of Technology, Sweden" + "author_name": "Wolfgang Lieb", + "author_inst": "Institute of Epidemiology, Kiel University" }, { - "author_name": "Marta Bally", - "author_inst": "Department of Clinical Microbiology, Ume\u00e5 University, Sweden; Wallenberg Centre for Molecular Medicine (WCMM), Ume\u00e5 University, Sweden; Ume\u00e5 Centre for Microbi" + "author_name": "Markus Weckmann", + "author_inst": "Department of Pediatric Pneumology and Allergology, The University of Luebeck, Epigenetics of Chronic Lung Disease, Priority Research Area Chronic Lung Diseases" + }, + { + "author_name": "Hauke Busch", + "author_inst": "Institute of Experimental Dermatology, University of Luebeck" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2024.01.09.24301057", @@ -15791,79 +15870,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2024.01.03.574018", - "rel_title": "Prototype mRNA vaccines imprint broadly neutralizing human serum antibodies after Omicron variant-matched boosting", + "rel_doi": "10.1101/2024.01.03.574064", + "rel_title": "A Murine Model of Post-acute Neurological Sequelae Following SARS-CoV-2 Variant Infection", "rel_date": "2024-01-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2024.01.03.574018", - "rel_abs": "Immune imprinting is a phenomenon in which an individuals prior antigenic experiences influence responses to subsequent infection or vaccination. Here, using antibody depletion and multiplexed spike-binding assays, we characterized the type-specificity and cross-reactivity of serum antibody responses after mRNA vaccination in mice and human clinical trial participants. In mice, a single priming dose of a preclinical version of mRNA-1273 vaccine encoding Wuhan-1 spike minimally imprinted serum responses elicited by Omicron boosters, enabling a robust generation of type-specific antibodies. However, substantial imprinting was observed in mice receiving an Omicron booster after two priming doses of mRNA-1273, an effect that was mitigated by a second booster dose of Omicron mRNA vaccine. In humans who received two BA.5 or XBB.1.5 Omicron-matched boosters after two or more doses of the prototype mRNA-1273 vaccine, spike-binding and neutralizing serum antibodies cross-reacted with circulating Omicron variants as well as more distantly related sarbecoviruses. Because the serum neutralizing response against Omicron strains and other sarbecoviruses was completely abrogated after pre-clearing with the Wuhan-1 spike protein, antibodies induced by XBB.1.5 boosting in humans focus on conserved epitopes shaped and shared by the antecedent mRNA-1273 primary series. Our depletion analysis also identified cross-reactive neutralizing antibodies that recognize distinct epitopes in the receptor binding domain (RBD) and S2 proteins with differential inhibitory effects on members of the sarbecovirus subgenus. Thus, although the serum antibody response to Omicron-based boosters in humans is dominantly imprinted by prior immunizations with prototype mRNA-1273 vaccines, this outcome can be beneficial as it drives expansion of multiple classes of cross-neutralizing antibodies that inhibit infection of emerging SARS-CoV-2 variants and extend activity to distantly related sarbecoviruses.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2024.01.03.574064", + "rel_abs": "Viral variant is one known risk factor associated with post-acute sequelae of COVID-19 (PASC), yet the pathogenesis is largely unknown. Here, we studied SARS-CoV-2 Delta variant-induced PASC in K18-hACE2 mice. The virus replicated productively, induced robust inflammatory responses in lung and brain tissues, and caused weight loss and mortality during the acute infection. Longitudinal behavior studies in surviving mice up to 4 months post-acute infection revealed persistent abnormalities in neuropsychiatric state and motor behaviors, while reflex and sensory functions recovered over time. Surviving mice showed no detectable viral RNA in the brain and minimal neuroinflammation post-acute infection. Transcriptome analysis revealed persistent activation of immune pathways, including humoral responses, complement, and phagocytosis, and reduced levels of genes associated with ataxia telangiectasia, impaired cognitive function and memory recall, and neuronal dysfunction and degeneration. Furthermore, surviving mice maintained potent T helper 1 prone cellular immune responses and high neutralizing antibodies against Delta and Omicron variants in the periphery for months post-acute infection. Overall, infection in K18-hACE2 mice recapitulates the persistent clinical symptoms reported in long COVID patients and may be useful for future assessment of the efficacy of vaccines and therapeutics against SARS-CoV-2 variants.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Chieh-Yu Liang", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Saravanan Raju", - "author_inst": "Washington University in St. Louis" - }, - { - "author_name": "Zhuoming Liu", - "author_inst": "Washington University School of Medicine" + "author_name": "Ankita Singh", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "Yuhao Li", - "author_inst": "Washington University School of Medicine" + "author_name": "Awadalkareem Adam", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "Guha A. Arunkumar", - "author_inst": "Moderna Inc." + "author_name": "Aditi Aditi", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "James Brett Case", - "author_inst": "Washington University School of Medicine" + "author_name": "Bi-Hung Peng", + "author_inst": "The University of Texas Medical Branch at Galveston" }, { - "author_name": "Seth J. Zost", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Xiaoying Yu", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "Cory M. Acreman", - "author_inst": "The University of Texas at Austin" + "author_name": "Jing Zou", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "Deborah Carolina Carvalho dos Anjos", - "author_inst": "Washington University School of Medicine" + "author_name": "Vikram V Kulkarni", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "Jason S. McLellan", - "author_inst": "The University of Texas at Austin" + "author_name": "Peter Kan", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "James E. Crowe", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Wei Jiang", + "author_inst": "Medical University of South Carolina, Charleston, SC 29425, USA." }, { - "author_name": "Sean P. J. Whelan", - "author_inst": "Washington University in Saint Louis" + "author_name": "Pei-Yong Shi", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "Sayda M. Elbashir", - "author_inst": "Moderna Inc." + "author_name": "Parimal Samir", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "Darin K. Edwards", - "author_inst": "Moderna Inc" + "author_name": "Irma Cisneros", + "author_inst": "University of Texas Medical Branch, Galveston, TX, 77555, USA." }, { - "author_name": "Michael S. Diamond", - "author_inst": "Washington University School of Medicine" + "author_name": "Tian Wang", + "author_inst": "The University of Texas Medical Branch" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2024.01.03.574008", @@ -17593,29 +17664,89 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2023.12.22.23300471", - "rel_title": "Nowcasting Reported COVID-19 Hospitalizations Using De-Identified, Aggregated Medical Insurance Claims Data", + "rel_doi": "10.1101/2023.12.22.23300474", + "rel_title": "Mild and moderate COVID-19 during Alpha, Delta and Omikron pandemic waves in urban Maputo, Mozambique, December 2020-March 2022: a population-based surveillance study", "rel_date": "2023-12-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.12.22.23300471", - "rel_abs": "We propose, implement, and evaluate a method for nowcasting the daily number of new COVID-19 hospitalizations, at the level of individual US states, based on de-identified, aggregated medical insurance claims data. Our analysis proceeds under a hypothetical scenario in which, during the Delta wave, states only report data on the first day of each month, and on this day, report COVID-19 hospitalization counts for each day in the previous month. In this hypothetical scenario (just as in reality), medical insurance claims data continues to be available daily. At the beginning of each month, we train a regression model, using all data available thus far, to predict hospitalization counts from medical insurance claims. We then use this model to nowcast the (unseen) values of COVID-19 hospitalization counts from medical insurance claims, at each day in the following month. Our analysis uses properly-versioned data, which would have been available in real-time, at the time predictions are produced. In spite of the difficulties inherent to real-time estimation (e.g., latency and backfill) and the complex dynamics behind COVID-19 hospitalizations themselves, we find overall that medical insurance claims can be an accurate predictor of hospitalization reports, with mean absolute errors typically around 0.4 hospitalizations per 100,000 people, i.e., proportion of variance explained around 75%. Perhaps more importantly, we find that nowcasts made using medical insurance claims can qualitatively capture the dynamics (upswings and downswings) of hospitalization waves, which are key features that inform public health decision-making.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.12.22.23300474", + "rel_abs": "In sub-Saharan Africa, reported COVID-19 numbers have been lower than anticipated, even when considering populations younger age. The extent to which risk factors, established in industrialised countries, impact the risk of infection and of disease in populations in sub-Saharan Africa, remains unclear. We estimated the incidence of mild and moderate COVID-19 in urban Mozambique and analysed factors associated with infection and disease in a population-based surveillance study.\n\nDuring December 2020-March 2022, households of a population cohort in Polana Canico, Maputo, Mozambique, were contacted biweekly. Residents reporting any respiratory sign, anosmia, or ageusia, were asked to self-administer a nasal swab, for SARS-CoV-2 PCR testing. Of a subset of 1400 participants, dried blood spots were repeatedly collected three-monthly from finger pricks at home. Antibodies against SARS-CoV-2 spike glycoprotein and nucleocapsid protein were detected using an in-house developed multiplex antibody assay. We estimated the incidence of respiratory illness and COVID-19, and SARS-CoV-2 seroprevalence. We used Cox regression models, adjusting for age and sex, to identify factors associated with first symptomatic COVID-19 and with SARS-CoV-2 sero-conversion in the first six months.\n\nDuring 11925 household visits in 1561 households, covering 6049 participants (median 21 years, 54.8% female, 7.3% disclosed HIV positive), 1895.9 person-years were followed up. Per 1000 person-years, 364.5 (95%CI 352.8-376.1) respiratory illness episodes of which 72.2 (95%CI 60.6-83.9) COVID-19 confirmed, were reported. Of 1412 participants, 2185 blood samples were tested (median 30.6 years, 55.2% female). Sero-prevalence rose from 4.8% (95%CI 1.1-8.6%) in December 2020 to 34.7% (95%CI 20.2-49.3%) in June 2021, when 3.0% were vaccinated. Increasing age (strong gradient in hazard ratio, HR, up to 15.70 in [≥]70 year olds, 95%CI 3.74-65.97), leukaemia, chronic lung disease, hypertension, and overweight increased risk of COVID-19. We found no increased risk of COVID-19 in people with HIV or tuberculosis. Risk of COVID-19 was lower among residents in the lowest socio-economic quintile (HR 0.16, 95%CI 0.04-0.64), with no or limited handwashing facilities, and who shared bedrooms (HR 0.42, 95%CI 0.25-0.72). Older age also increased the risk of SARS-CoV-2 seroconversion (HR 1.57 in 60-69 year olds, 95%CI 1.03-2.39). We found no associations between SARS-CoV-2 infection risk and socio-economic, behavioural factors and comorbidities.\n\nActive surveillance in an urban population cohort confirmed frequent COVID-19 underreporting, yet indicated that the large majority of cases were mild and non-febrile. In contrast to industrialised countries, deprivation did not increase the risk of infection nor disease.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Xueda Shen", - "author_inst": "University of California, Berkeley" + "author_name": "Brecht Ingelbeen", + "author_inst": "Institute of Tropical Medicine" }, { - "author_name": "Aaron Rumack", - "author_inst": "Carnegie Mellon University" + "author_name": "Victoria Cumbane", + "author_inst": "Instituto Nacional de Saude, Ministry of Health (MISAU), Marracuene, Mozambique" }, { - "author_name": "Bryan Wilder", - "author_inst": "Carnegie Mellon University" + "author_name": "Ferao Mandlate", + "author_inst": "Instituto Nacional de Saude, Ministry of Health (MISAU), Marracuene, Mozambique" }, { - "author_name": "Ryan J. Tibshirani", - "author_inst": "University of California, Berkeley" + "author_name": "Barbara Barbe", + "author_inst": "Institute of Tropical Medicine" + }, + { + "author_name": "Sheila Nhachungue", + "author_inst": "Instituto Nacional de Saude, Ministry of Health (MISAU), Marracuene, Mozambique" + }, + { + "author_name": "Nilzio Cavele", + "author_inst": "Instituto Nacional de Saude, Ministry of Health (MISAU), Marracuene, Mozambique" + }, + { + "author_name": "Cremildo Manhica", + "author_inst": "Instituto Nacional de Saude, Ministry of Health (MISAU), Marracuene, Mozambique" + }, + { + "author_name": "Catildo Cubai", + "author_inst": "Instituto Nacional de Saude, Ministry of Health (MISAU), Marracuene, Mozambique" + }, + { + "author_name": "Neusa Guenha", + "author_inst": "Instituto Nacional de Saude, Ministry of Health (MISAU), Marracuene, Mozambique" + }, + { + "author_name": "Audrey Lacroix", + "author_inst": "TransVIHMI (Recherches Translationnelles sur VIH et Maladies Infectieuses), Universite de Montpellier, Institut de Recherche pour le Developpement, INSERM, Mont" + }, + { + "author_name": "Joachim Marien", + "author_inst": "Institute of Tropical Medicine" + }, + { + "author_name": "Anja de Weggheleire", + "author_inst": "MSF" + }, + { + "author_name": "Esther van Kleef", + "author_inst": "Institute of Tropical Medicine" + }, + { + "author_name": "Philippe Selhorst", + "author_inst": "Institute of Tropical Medicine" + }, + { + "author_name": "Marianne AB van der Sande", + "author_inst": "Utrecht University" + }, + { + "author_name": "Martine Peeters", + "author_inst": "Institut de recherche pour le developpement" + }, + { + "author_name": "Marc-Alain Widdowson", + "author_inst": "Institute of Tropical Medicine" + }, + { + "author_name": "Nalia Ismael", + "author_inst": "Instituto Nacional de Saude, Ministry of Health (MISAU), Marracuene, Mozambique" + }, + { + "author_name": "Ivalda Macicame", + "author_inst": "Instituto Nacional de Saude, Ministry of Health (MISAU), Marracuene, Mozambique" } ], "version": "1", @@ -19283,135 +19414,115 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.12.20.572494", - "rel_title": "Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19", + "rel_doi": "10.1101/2023.12.19.572339", + "rel_title": "Deep profiling of antigen-specific B cells from different pathogens identifies novel compartments in the IgG memory B cell and antibody-secreting cell lineages", "rel_date": "2023-12-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.12.20.572494", - "rel_abs": "The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 donor lungs with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage (DAD). We identify changes in cellular composition across progressive DAD, including waves of molecularly distinct macrophages and depleted epithelial and endothelial populations throughout different types of tissue damage. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early DAD, and fibrosis-related collagens in organised DAD. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early DAD. These results provide the first comprehensive, spatially resolved atlas of DAD stages, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways across alveolar damage progression.", - "rel_num_authors": 29, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.12.19.572339", + "rel_abs": "A better understanding of the bifurcation of human B cell differentiation into memory B cells (MBC) and antibody-secreting cells (ASC) and identification of MBC and ASC precursors is crucial to optimize vaccination strategies or block undesired antibody responses. To unravel the dynamics of antigen-induced B cell responses, we compared circulating B cells reactive to SARS-CoV-2 (Spike, RBD and Nucleocapsid) in COVID-19 convalescent individuals to B cells specific to Influenza-HA, RSV-F and TT, induced much longer ago. High-dimensional spectral flow cytometry indicated that the decision point between ASC- and MBC-formation lies in the CD43+CD71+IgG+ Activated B cell compartment, showing properties indicative of recent germinal center activity and recent antigen encounter. Within this Activated B cells compartment, CD86+ B cells exhibited close phenotypical similarity with ASC, while CD86- B cells were closely related to IgG+ MBCs. Additionally, different activation stages of the IgG+ MBC compartment could be further elucidated. The expression of CD73 and CD24, regulators of survival and cellular metabolic quiescence, discerned activated MBCs from resting MBCs. Activated MBCs (CD73-CD24lo) exhibited phenotypical similarities with CD86- IgG+ Activated B cells and were restricted to SARS-CoV-2 specificities, contrasting with the resting MBC compartment (CD73-/CD24hi) that exclusively encompassed antigen-specific B cells established long ago. Overall, these findings identify novel stages for IgG+ MBC and ASC formation and bring us closer in defining the decision point for MBC or ASC differentiation.\n\nImportanceIn this study, researchers aimed to better understand human B cell differentiation and their role in establishing long-lived humoral immunity. Using high-dimensional flow cytometry, they studied B cells reactive to three SARS-CoV-2 antigens in individuals convalescent for COVID-19, and compared their phenotypes to B cells reactive to three distinct protein antigens derived from vaccines or viruses encountered months to decades before. Their findings showed that Activated B cells reflect recent germinal center graduates that may have diverse fates; with some feeding the pool of antibody-secreting cells and others fueling the resting memory B cell compartment. Activated B cells gradually differentiate into resting memory B cells through an activated MBC phase. Increased expression of the cellular metabolic regulators CD73 and CD24 in resting memory B cells distinguishes them from the activated memory B cells phase, and is likely involved in sustaining a durable memory of humoral immunity. These findings are crucial for the development of vaccines that provide lifelong protection and may show potential to define reactive B cells in diseases where the cognate-antigen is still unknown such as in autoimmunity, cancers, or novel viral outbreaks.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Jimmy Tsz Hang Lee", - "author_inst": "Wellcome Sanger Institute, Hinxton, UK" - }, - { - "author_name": "Sam N. Barnett", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" - }, - { - "author_name": "Kenny Roberts", - "author_inst": "Wellcome Sanger Institute, Hinxton, UK" - }, - { - "author_name": "Helen Ashwin", - "author_inst": "York Biomedical Research Institute and Hull York Medical School, University of York, York, UK" - }, - { - "author_name": "Luke Milross", - "author_inst": "Newcastle University Translational and Clinical Research Institute, Newcastle upon Tyne, UK" + "author_name": "Mathieu Claireaux", + "author_inst": "Amsterdam UMC, University of Amsterdam, Department of Medical Microbiology and Infection prevention, Laboratory of Experimental Virology, Amsterdam, the Netherl" }, { - "author_name": "Jae-Won Cho", - "author_inst": "The Gene Lay Instititute of Immunology and Inflammation, Brigham and Women's Hospital and Harvard Medical School, Boston, USA" + "author_name": "George Elias", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Alik Huseynov", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" - }, - { - "author_name": "Benjamin Woodhams", - "author_inst": "Wellcome Sanger Institute, Hinxton, UK; European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL), Cambridge, UK" + "author_name": "Gius Kerster", + "author_inst": "Amsterdam UMC, University of Amsterdam, Department of Medical Microbiology and Infection prevention, Laboratory of Experimental Virology, Amsterdam, the Netherl" }, { - "author_name": "Alexander Aivazidis", - "author_inst": "Wellcome Sanger Institute, Hinxton, UK" + "author_name": "Lisan H Kuijper", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Tong Li", - "author_inst": "Wellcome Sanger Institute, Hinxton, UK" + "author_name": "Mariel C Duurland", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Joaquim Majo", - "author_inst": "Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + "author_name": "Alberta GA Paul", + "author_inst": "Application Department, Cytek Biosciences, Inc., Fremont, California, USA., Cytek Biosciences, Inc., Fremont, California, USA." }, { - "author_name": "Patricia Chaves Guerrero", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" + "author_name": "Judith A Burger", + "author_inst": "Amsterdam UMC, University of Amsterdam, Department of Medical Microbiology and Infection prevention, Laboratory of Experimental Virology, Amsterdam, the Netherl" }, { - "author_name": "Michael Lee", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" + "author_name": "Meliawati Poniman", + "author_inst": "Amsterdam UMC, University of Amsterdam, Department of Medical Microbiology and Infection prevention, Laboratory of Experimental Virology, Amsterdam, the Netherl" }, { - "author_name": "Antonio M. A. Miranda", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" + "author_name": "Wouter Olijhoek", + "author_inst": "Amsterdam UMC, University of Amsterdam, Department of Medical Microbiology and Infection prevention, Laboratory of Experimental Virology, Amsterdam, the Netherl" }, { - "author_name": "Zuzanna Jablonska", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" + "author_name": "Nina de Jong", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Vincenzo Arena", - "author_inst": "Istituto di Anatomia Patologica, Universit\u00e1 Cattolica Del Sacro Cuore, Rome, Italy" + "author_name": "Rivka de Jongh", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Brian Hanley", - "author_inst": "Northwest London Pathology, Imperial College London NHS Trust, London, UK" + "author_name": "Elke Wynberg", + "author_inst": "Department of Infectious Diseases, Public Health Service of Amsterdam, GGD, Amsterdam, the Netherlands" }, { - "author_name": "Michael Osborn", - "author_inst": "Northwest London Pathology, Imperial College London NHS Trust, London, UK" + "author_name": "Hugo DG van Willigen", + "author_inst": "Amsterdam UMC, University of Amsterdam, Department of Medical Microbiology and Infection prevention, Amsterdam, the Netherlands" }, { - "author_name": "Virginie Uhlmann", - "author_inst": "European Bioinformatics Institute, European Molecular Biology Laboratory (EMBL), Cambridge, UK" + "author_name": "Maria Prins", + "author_inst": "Department of Infectious Diseases, Public Health Service of Amsterdam, GGD, Amsterdam, the Netherlands" }, { - "author_name": "Xiao-Ning Xu", - "author_inst": "Imperial College London, London, UK" + "author_name": "Godelieve J de Bree", + "author_inst": "Department of Internal Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Gary R. McLean", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK; London Metropolitan University, London, UK" + "author_name": "Meno D de Jong", + "author_inst": "Amsterdam UMC, University of Amsterdam, Department of Medical Microbiology and Infection prevention, Amsterdam, the Netherlands" }, { - "author_name": "Sarah A. Teichmann", - "author_inst": "Wellcome Sanger Institute, Hinxton, UK" + "author_name": "Taco W Kuijpers", + "author_inst": "Department of Pediatric Immunology, Rheumatology and Infectious Disease, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Anna M. Randi", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK; British Heart Foundation Centre of Research Excellence, Imperial College London, London," + "author_name": "Filip Eftimov", + "author_inst": "Department of Neurology and Neurophysiology, Amsterdam Neuroscience, Amsterdam UMC, location AMC, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Andrew Filby", - "author_inst": "Biosciences Institute and Innovation Methodology and Application Research Theme, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, UK" + "author_name": "C Ellen van der Schoot", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Paul M. Kaye", - "author_inst": "York Biomedical Research Institute and Hull York Medical School, University of York, York, UK" + "author_name": "Theo Rispens", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Andrew J. Fisher", - "author_inst": "Newcastle University Translational and Clinical Research Institute, Newcastle upon Tyne, UK; Institute of Transplantation, Newcastle upon Tyne Hospitals NHS Fou" + "author_name": "Juan J Garcia-Vallejo", + "author_inst": "Department of Molecular Cell Biology & Immunology, Amsterdam University Medical Center (VUmc location), Amsterdam, the Netherlands" }, { - "author_name": "Martin Hemberg", - "author_inst": "The Gene Lay Instititute of Immunology and Inflammation, Brigham and Women's Hospital and Harvard Medical School, Boston, USA" + "author_name": "Anja ten Brinke", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, the Netherlands" }, { - "author_name": "Michela Noseda", - "author_inst": "National Heart and Lung Institute, Imperial College London, London, UK" + "author_name": "Marit J van Gils", + "author_inst": "Amsterdam UMC, University of Amsterdam, Department of Medical Microbiology and Infection prevention, Laboratory of Experimental Virology, Amsterdam, the Netherl" }, { - "author_name": "Omer Ali Bayraktar", - "author_inst": "Wellcome Sanger Institute, Hinxton, UK" + "author_name": "S Marieke van Ham", + "author_inst": "Department of Immunopathology, Sanquin Research and Landsteiner Laboratory, University of Amsterdam, Amsterdam, the Netherlands" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "pathology" + "category": "immunology" }, { "rel_doi": "10.1101/2023.12.19.572469", @@ -21241,107 +21352,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.12.14.23299967", - "rel_title": "Diagnostic Accuracy of the Abbot BinaxNOW COVID-19 Antigen Card Test, Puerto Rico", + "rel_doi": "10.1101/2023.12.14.23299928", + "rel_title": "PVT in patients presenting with post-acute sequelae of COVID-19", "rel_date": "2023-12-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.12.14.23299967", - "rel_abs": "BackgroundThe COVID-19 pandemic underscored the need for rapid and accurate diagnostic tools. In August 2020, the Abbot BinaxNOW COVID-19 Antigen Card test became available as a timely and affordable alternative for SARS-CoV-2 molecular testing, but its performance may vary due to factors including timing and symptomatology. This study evaluates BinaxNOW diagnostic performance in diverse epidemiological contexts.\n\nMethodsUsing RT-PCR as reference, we assessed performance of the BinaxNOW COVID-19 test for SARS-CoV-2 detection in anterior nasal swabs from participants of two studies in Puerto Rico from December 2020 to May 2023. Test performance was assessed by days post symptom onset, collection strategy, vaccination status, symptomatology, repeated testing, and RT-PCR cycle threshold (Ct) values.\n\nResultsBinaxNOW demonstrated an overall sensitivity of 84.1% and specificity of 98.8%. Sensitivity peaked within 1-6 days after symptom onset (93.2%) and was higher for symptomatic (86.3%) than asymptomatic (67.3%) participants. Sensitivity declined over the course of infection, dropping from 96.3% in the initial test to 48.4% in testing performed 7-14 days later. BinaxNOW showed 99.5% sensitivity in participants with low Ct values ([≤]25) but lower sensitivity (18.2%) for participants with higher Cts (36-40).\n\nConclusionsBinaxNOW demonstrated high sensitivity and specificity, particularly in early-stage infections and symptomatic participants. In situations where test sensitivity is crucial for clinical decision- making, nucleic acid amplification tests are preferred. These findings highlight the importance of considering clinical and epidemiological context when interpreting test results and emphasize the need for ongoing research to adapt testing strategies to emerging SARS-CoV-2 variants.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.12.14.23299928", + "rel_abs": "We investigated performance validity tests (PVTs) in patients presenting with new onset cognitive complaints associated with post-acute sequelae of COVID-19 infection (PASC). Retrospective data were obtained from IRB-approved registries. All patients completed the Victoria Symptom Validity Test (VSVT) in conjunction with a neuropsychological evaluation. A sub-analysis included 7 other PVT measures. The PASC sample was compared to an analogous multiple sclerosis (MS) sample with known PVT failure rates. The PASC sample consisted of 177 patients (49.4 {+/-} 11.2 years), educated (14.7 {+/-} 2.3 years), predominantly female (81.4%), and white, non-Hispanic (85.3%) patients. Seven percent of the PASC sample scored below the established VSVT hard item cut-off, and of those with invalid VSVT over 50% failed 3 or more additional PVTs. In comparison to a MS sample, the PASC sample reported comparable psychological symptoms, but were significantly less likely to produce invalid VSVT scores and seek disability benefits. This study provides a profile of PVTs in patients presenting with PASC. The general infrequence of invalid responding in this PASC sample (7%) is noteworthy compared to an MS sample and highlights the role of additional factors in non-credible response such as elevated psychological symptoms or pursuit of disability.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Zachary J. Madewell", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Chelsea G. Major", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Nathan Graff", - "author_inst": "Eagle Health Analytics, San Antonio, Texas, USA" - }, - { - "author_name": "Cameron Adams", - "author_inst": "Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, North Carolina, USA" - }, - { - "author_name": "Dania M. Rodriguez", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Tatiana Morales", - "author_inst": "Ponce Health Sciences University/Ponce Research Institute, Ponce, Puerto Rico" - }, - { - "author_name": "Nicole A. Medina Lopes", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Rafael Tosado", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Liliana Sanchez-Gonzalez", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Janice Perez-Padilla", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Hannah R. Volkman", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Jorge Bertran", - "author_inst": "Auxilio Mutuo Hospital, San Juan, Puerto Rico" - }, - { - "author_name": "Diego Sainz", - "author_inst": "Auxilio Mutuo Hospital, San Juan, Puerto Rico" - }, - { - "author_name": "Jorge Munoz-Jordan", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Gilberto A. Santiago", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Olga Lorenzi", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Vanessa Rivera-Amill", - "author_inst": "Ponce Health Sciences University/Ponce Research Institute, Ponce, Puerto Rico" - }, - { - "author_name": "Melissa A. Rolfes", - "author_inst": "Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Shinjon Chakrabarti", + "author_inst": "Case Western Reserve University, Cleveland OH USA" }, { - "author_name": "Gabriela Paz-Bailey", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Laura E. Adams", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" - }, - { - "author_name": "Joshua M. Wong", - "author_inst": "Division of Vector-Borne Diseases, Centers for Disease Control and Prevention, San Juan, Puerto Rico" + "author_name": "Kamini Krishnan", + "author_inst": "Cleveland clinic" }, { - "author_name": "- PRESCA Study Team", - "author_inst": "-" + "author_name": "Rachel Galioto", + "author_inst": "Department of Neurology, Cleveland Clinic, Cleveland, OH, USA, Mellen Center for Multiple Sclerosis, Cleveland Clinic, Cleveland, OH, USA, & Epilepsy Center, Cl" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2023.12.14.23299963", @@ -23019,83 +23054,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.12.07.23299429", - "rel_title": "Mechanisms underlying exercise intolerance in Long COVID: an accumulation of multi-system dysfunction", + "rel_doi": "10.1101/2023.12.08.23299660", + "rel_title": "COVID-19 vaccine effectiveness among South Asians in Ontario: A test-negative design population-based case-control study", "rel_date": "2023-12-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.12.07.23299429", - "rel_abs": "The pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood.\n\nCases were recruited from a Long COVID clinic (N=32; 44{+/-}12y; 10(31%)men), and age/sex- matched healthy controls (HC) (N=19; 40{+/-}13y; 6(32%)men) from University College London staff and students. We assessed exercise performance, lung and cardiac function, vascular health, skeletal muscle oxidative capacity and autonomic nervous system (ANS) function. Key outcome measures for each physiological system were compared between groups using potential outcome means(95% confidence intervals) adjusted for potential confounders. Long COVID participant outcomes were compared to normative values.\n\nWhen compared to HC, cases exhibited reduced Oxygen Uptake Efficiency Slope (1847(1679,2016) vs (2176(1978,2373) ml/min, p=0.002) and Anaerobic Threshold (13.2(12.2,14.3) vs 15.6(14.4,17.2) ml/Kg/min, p<0.001), and lower oxidative capacity on near infrared spectroscopy ({tau}: 38.7(31.9,45.6) vs 24.6(19.1,30.1) seconds, p=0.001). In cases, ANS measures fell below normal limits in 39%.\n\nLong COVID is associated with reduced measures of exercise performance and skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology. There was evidence of attendant ANS dysregulation in a significant proportion. These multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers.\n\nKey PointsO_LIThe pathogenesis of exercise intolerance and persistent fatigue which can follow an infection with the SARS-CoV-2 virus (Long COVID) is not fully understood.\nC_LIO_LIWe show that Long COVID is associated with reduced measures of exercise performance in line with previous work.\nC_LIO_LIIn Long COVID cases, we observed reduced skeletal muscle oxidative capacity in the absence of evidence of microvascular dysfunction, suggesting mitochondrial pathology.\nC_LIO_LIWe also observed evidence of attendant autonomic nervous system (ANS) dysregulation in a significant proportion of Long COVID cases.\nC_LIO_LIThese multi-system factors might contribute to impaired exercise tolerance in Long COVID sufferers.\nC_LI", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.12.08.23299660", + "rel_abs": "ObjectivesTo: 1) evaluate the effectiveness of COVID-19 vaccines among South Asians living in Ontario, Canada compared to non-South Asians, and 2) compare the odds of symptomatic COVID-19 infection and related hospitalizations and deaths among non-vaccinated South Asians and non-South Asians.\n\nDesignTest negative design study\n\nSettingOntario, Canada between Dec 14, 2020 and Nov 15, 2021\n\nParticipantsAll eligible individuals >18 years with symptoms of COVID-19 and subdivided by South Asian ethnicity versus other, and those who were vaccinated versus non-vaccinated.\n\nMain Outcome measuresThe primary outcome was vaccine effectiveness as defined by COVID-19 infections, hospitalizations, and deaths, and secondary outcome was the odds of COVID-19 infections, hospitalizations, and death comparing non-vaccinated South Asians to non-vaccinated non-South Asians.\n\nResults883,155 individuals were included. Among South Asians, two doses of COVID-19 vaccine prevented 93.8% (95% CI 93.2, 94.4) of COVID-19 infections and 97.5% (95% CI 95.2, 98.6) of hospitalizations and deaths. Among non-South Asians, vaccines prevented 86.6% (CI 86.3, 86.9) of COVID-19 infections and 93.1% (CI 92.2, 93.8) of hospitalizations and deaths. Non-vaccinated South Asians had higher odds of symptomatic SARS-CoV-2 infection compared to non-vaccinated non-South Asians (OR 2.35, 95% CI 2.3, 2.4), regardless of their immigration status.\n\nConclusionsCOVID-19 vaccines are effective in preventing infections, hospitalizations and deaths among South Asians living in Canada. The observation that non-vaccinated South Asians have higher odds of symptomatic COVID-19 infection warrants further investigation.\n\nWhat is already known?Some ethnic communities, such as South Asians, were disproportionately impacted during the COVID-19 pandemic. However, there are limited data on COVID-19 vaccine efficacy among this high-risk ethnic group.\n\nWhat this study adds?- In this large population-based study including close to 900,000 individuals in Canada, we show COVID-19 vaccines are effective in preventing symptomatic SARS CoV-2 infections, hospitalizations and deaths among both South Asians and non-South Asians.\n- We also demonstrate that, among non-vaccinated individuals, South Asians have higher odds of COVID-19 infection, and an increased risk of COVID-19 hospitalizations and deaths compared to non-South Asians.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Alexandra Jamieson", - "author_inst": "University College London" - }, - { - "author_name": "Lamia Al Saikhan", - "author_inst": "Imam Abdulrahman Bin Faisal University" + "author_name": "Rahul Chanchlani", + "author_inst": "McMaster University" }, { - "author_name": "Lamis Alghamdi", - "author_inst": "University College London" + "author_name": "Baiju Shah", + "author_inst": "ICES Central" }, { - "author_name": "Lee Hamill Howes", - "author_inst": "University College London" + "author_name": "Shrikant I Bangdiwala", + "author_inst": "Population Health Research Institute" }, { - "author_name": "Helen Purcell", - "author_inst": "University College London Hospitals NHS Foundation Trust" + "author_name": "Russell J de Souza", + "author_inst": "McMaster University" }, { - "author_name": "Toby Hillman", - "author_inst": "University College London Hospitals NHS Foundation Trust" + "author_name": "Jin Luo", + "author_inst": "Institute for Clinical and Evaluative Sciences" }, { - "author_name": "Melissa J Heightman", - "author_inst": "UCLH" - }, - { - "author_name": "Thomas A. Treibel", - "author_inst": "University College London" + "author_name": "Shelly Bolotin", + "author_inst": "Public Health Ontario" }, { - "author_name": "Michele Orini", - "author_inst": "University College London" + "author_name": "Dawn Bowdish", + "author_inst": "McMaster University" }, { - "author_name": "Robert Midgley Bell", - "author_inst": "The Hatter Cardiovascular Institute, University College London" + "author_name": "Dipika Desai", + "author_inst": "Population Health Research Institute" }, { - "author_name": "Marie Scully", - "author_inst": "University College London Hospitals NHS Foundation Trust" + "author_name": "Scott Lear", + "author_inst": "Simon Fraser Institute" }, { - "author_name": "Mark Hamer", - "author_inst": "UCL" + "author_name": "Mark Loeb", + "author_inst": "McMaster University" }, { - "author_name": "Nishi Chaturvedi", - "author_inst": "University College London" + "author_name": "Zubin Punthakee", + "author_inst": "McMaster University" }, { - "author_name": "Alun Hughes", - "author_inst": "UCL" + "author_name": "Diana Sherifali", + "author_inst": "McMaster University" }, { - "author_name": "Ronan Astin", - "author_inst": "University College London Hospitals NHS Foundation Trust" + "author_name": "Gita Wahi", + "author_inst": "McMaster University" }, { - "author_name": "Siana Jones", - "author_inst": "University College London" + "author_name": "Sonia S Anand", + "author_inst": "McMaster University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.12.07.570670", @@ -24865,41 +24892,69 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.12.04.23299370", - "rel_title": "Real-world effectiveness of sotrovimab for the treatment of SARS-CoV-2 infection during Omicron BA.2 and BA.5 subvariant predominance: a systematic literature review", + "rel_doi": "10.1101/2023.12.04.23299372", + "rel_title": "Epidemiological overlaps in COVID-19 and malaria within healthcare and community settings of Southern Ghana", "rel_date": "2023-12-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.12.04.23299370", - "rel_abs": "BackgroundEmerging SARS-CoV-2 variants have impacted the in vitro activity of sotrovimab, with variable fold changes in neutralization potency reported for Omicron BA.2 and subsequent variants. We performed a systematic literature review (SLR) to evaluate clinical outcomes associated with sotrovimab use during Omicron BA.2 and BA.5 predominance.\n\nMethodsElectronic databases were searched for observational studies published in peer-reviewed journals, preprint articles and conference abstracts from January 1, 2022-February 27, 2023.\n\nResultsThe 14 studies identified were heterogeneous in terms of study design, population, endpoints and definitions, and comprised >1.7 million high-risk patients with COVID-19, of whom approximately 41,000 received sotrovimab (range n=20- 5979 during BA.2 and n=76-1383 during BA.5 predominance). Studies were from the US, UK, Italy, Denmark, France, Qatar, and Japan. Four studies compared the effectiveness of sotrovimab with untreated or no monoclonal antibody treatment controls, two compared sotrovimab with other treatments, and three single-arm studies compared outcomes during BA.2 and/or BA.5 versus BA.1. The remaining five studies descriptively reported rates of clinical outcomes in patients treated with sotrovimab. Rates of COVID-19-related hospitalization or mortality among sotrovimab-treated patients were consistently low (0.95% to 4.0% during BA.2; 0.5% to 2.0% during BA.5). All-cause hospitalization or mortality was also low (1.7% to 2.0% during BA.2; 3.4% during combined BA.2 and BA.5 periods). During BA.2, a lower risk of all-cause hospitalization or mortality was reported across studies with sotrovimab versus untreated cohorts. Compared with other treatments, sotrovimab was associated with a lower (molnupiravir) or similar (nirmatrelvir/ritonavir) risk of COVID-19-related hospitalization or mortality during BA.2 and BA.5. There was no significant difference in outcomes between the BA.1, BA.2 and BA.5 periods.\n\nConclusionsThe studies included in this SLR suggest continued effectiveness of sotrovimab in preventing severe clinical outcomes during BA.2 and BA.5 predominance, both against an active/untreated comparator and compared with BA.1 predominance.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.12.04.23299372", + "rel_abs": "BackgroundCOVID-19 disruptions in Africa in 2020-2022 contributed to reductions in malaria control activities including antimalarial surveillance programs. This study investigated the malaria burden and distribution on the background of active transmission of SARS-CoV-2 in Southern Ghana. Specifically, it aimed to identify epidemiological factors that can maximise programmatic control for both diseases, utilising community health education and medical screening (CHEMS).\n\nMethodsBetween October-December 2022, prospective cross-sectional surveys, with CHEMS were conducted in Greater Accra and Central regions, where 994 participants enrolled either at a hospital or community setting provided demographic and clinical data including history of clinical malaria infection and antimalarial treatment in the past two weeks. Of this study population, 953 provided nasal/throat swabs for COVID-19 RT-PCR testing, with a subset of 136 participants also providing finger-prick blood for malaria RDT testing.\n\nResultsThe study population comprised of 73.6% adults, with 54.6% COVID-19 vaccination rate. Overall, 18.1% of participants had a history of clinical malaria, which was associated (adjusted odds ratio > 1.50, P-value [≤] 0.022) with COVID-19 symptoms and positivity, study area and hospital setting, suggestive of overlaps in the epidemiological risk for malaria. On a background of widespread SARS-CoV-2 infections (12-37%), malaria parasitaemia was detected in 6%, with 2% being co-infections. Among the malaria positives, 9.5% had a history of antimalarial treatment, which suggested that their infections were recrudescent parasitaemia.\n\nConclusionThe overlaps in the epidemiological risk for malaria and COVID-19 indicate that innovative surveillance programs, with community engagement are needed to maximise control interventions including treatment of asymptomatic malaria infections.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Myriam Drysdale", - "author_inst": "GlaxoSmithKline" + "author_name": "Gloria Amegatcher", + "author_inst": "1. West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gh" }, { - "author_name": "Mehmet Berktas", - "author_inst": "GSK" + "author_name": "Maame E Acquah", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" }, { - "author_name": "Daniel C Gibbons", - "author_inst": "GSK" + "author_name": "Deborah Tetteh", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" + }, + { + "author_name": "Rachael Obeng", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" + }, + { + "author_name": "Ethel Debrah", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" + }, + { + "author_name": "Bridget Quist", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" + }, + { + "author_name": "Priscilla Acquah-Jackson", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" + }, + { + "author_name": "Kyerewaa A Boateng", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" + }, + { + "author_name": "Gideon Twieku", + "author_inst": "3.Biomedical and Public Health Research Unit, Council for Scientific and Industrial Research , Water Research Institute, Accra, Ghana" }, { - "author_name": "Catherine Rolland", - "author_inst": "PPD Evidera" + "author_name": "Samuel Armoo", + "author_inst": "3.Biomedical and Public Health Research Unit, Council for Scientific and Industrial Research, Water Research Institute, Accra, Ghana" }, { - "author_name": "Louis Lavoie", - "author_inst": "PPD Evidera" + "author_name": "Gordon A Awandare", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" }, { - "author_name": "Emily J Lloyd", - "author_inst": "PPD Evidera" + "author_name": "Lydia Mosi", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" + }, + { + "author_name": "Charles A Narh", + "author_inst": "1.West African Centre for Cell Biology of Infectious Pathogens (WACBIP), Department of Biochemistry, Cell and Molecular Biology, University of Ghana, Accra, Gha" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -26495,59 +26550,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.11.28.23298927", - "rel_title": "Social determinants of adult COVID-19 vaccine acceptance and uptake in a Brazilian urban informal community: a longitudinal time-to-event study", + "rel_doi": "10.1101/2023.11.28.23299078", + "rel_title": "Psychological impact of COVID-19 on frontline healthcare workers during the early months of the pandemic and responses to reduce the burden, helping to prepare for Disease X: A systematic Review", "rel_date": "2023-11-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.11.28.23298927", - "rel_abs": "Residents of informal urban settlements have a high risk of COVID-19 exposure and have less access to medical care, making vaccine-driven prevention critical in this vulnerable population. Despite robust vaccination campaigns in Brazil, vaccine uptake and timing continue to be influenced by social factors and contribute to health disparities. To address this, we conducted a sequential survey in a cohort of 717 adults in an urban favela in Salvador, Brazil where participants were interviewed in 2020, before vaccines were rolled out, and in 2022, after primary and booster dose distribution. We collected data on demographics, social characteristics, and COVID-19 vaccination status and intent. Primary series uptake was high (91.10% for 1st dose and 94.74% for 2nd dose among eligible); however, booster uptake was lower (63.51% of eligible population) at the time of the second interview, suggesting a decreasing interest in vaccination. To account for both vaccine refusal and delays, we conducted a Cox time-to-event analysis of dose uptake using sequential independent outcomes. Exposure times were determined by dose eligibility date to account for age and comorbidities. Intent to vaccinate in 2020 (hazard ratio [HR]: 1.54, CI: [1.05, 1.98]) and age (HR: 1.27, CI: [1.01, 2.08]) were associated with higher vaccination rates for the 1st dose. Males were less likely to receive the 1st dose (HR: 0.61, CI: [0.35, 0.83]), and, compared to catholics, 2nd dose uptake was lower for those identifying with Pentecostalism (HR: 0.49, CI: [0.37, 0.66]) and without a religion (HR: 0.49, CI: [0.37, 0.66]), with the latter association disappearing after controlling by age. Risk perception was associated with 2nd dose uptake (HR: 1.15, CI: [1.08, 1.26]). The role of sex and religion in vaccination behavior highlights the need for targeted outreach and interfacing with local organizations. The data offers lessons to build a long-term COVID-19 vaccination strategy beyond availability.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.11.28.23299078", + "rel_abs": "ObjectiveThe COVID-19 pandemic placed enormous strain on healthcare workers (HCW) and systems. With currently over 766 million cases, a high risk of workplace-acquired infection and a constantly evolving disease trajectory, COVID-19 placed an incredible burden on frontline HCWs. Studies from previous pandemics highlight significant psychological distress in these workers, yet mental health remained a secondary consideration in many hospitals pandemic response. This review explores the psychological impact of COVID-19 on frontline HCWs during the early stages of the pandemic and describes responses implemented by health services to reduce this impact. Additionally, it aims to provide a framework for future evidence-based programs that support the wellbeing of frontline HCWs throughout the ongoing pandemic and into the future, helping to prepare for Disease X.\n\nMethodsA systematic review was completed using MEDLINE, CINHAL and Cochrane databases with bibliographic and grey literature searches.\n\nResults17 publications were included. Symptoms of psychological distress were reported in up to 70% of frontline HCWs, with as many as 50% suffering depression, 62% reporting anxiety and 45% of those requiring quarantine experiencing insomnia. Mindfulness training, safe rest areas, mental health practitioners and pandemic rostering are responses that have been implemented across health services during the pandemic, but their efficacy in reducing psychological burden has not been fully assessed.\n\nConclusionsThe impact of COVID-19 has been enormous; however, its final toll remains unknown. High rates of psychological distress amongst frontline HCWs means the impact will extend far beyond the virus itself. Health services must implement evidence-based resilience strategies to ensure the safety of their frontline staff now and into the future.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Murilo Dorion", - "author_inst": "Yale School of Public Health" - }, - { - "author_name": "Juan Pablo A. Ticona", - "author_inst": "Oswaldo Cruz Foundation, Brazilian Ministry of Health" - }, - { - "author_name": "Mariam O. Fofana", - "author_inst": "Yale University" - }, - { - "author_name": "Margaret L. Lind", - "author_inst": "Yale University" - }, - { - "author_name": "Nivison Nery Jr.", - "author_inst": "Institute of Collective Health, Federal University of Bahia" - }, - { - "author_name": "Renato Victoriano", - "author_inst": "Oswaldo Cruz Foundation, Brazilian Ministry of Health" - }, - { - "author_name": "Ananias S. Do Aragao Filho", - "author_inst": "Oswaldo Cruz Foundation, Brazilian Ministry of Health" - }, - { - "author_name": "Mitermayer G Reis", - "author_inst": "Institute of Collective Health, Federal University of Bahia & Oswaldo Cruz Foundation, Brazilian Ministry of Health" - }, - { - "author_name": "Federico Costa", - "author_inst": "Institute of Collective Health, Federal University of Bahia & Oswaldo Cruz Foundation, Brazilian Ministry of Health" - }, - { - "author_name": "Albert Icksang Ko", - "author_inst": "Yale School of Public Health" + "author_name": "Jarryd Ludski", + "author_inst": "University of Notre Dame" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2023.11.28.568860", @@ -28385,111 +28404,67 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.11.22.23298899", - "rel_title": "Quantitative susceptibility mapping at 7 Tesla in COVID-19: mechanistic and outcome associations", + "rel_doi": "10.1101/2023.11.22.23298851", + "rel_title": "Wastewater monitoring of SARS-CoV-2 gene for COVID-19 epidemiological surveillance in Tucuman Argentina", "rel_date": "2023-11-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.11.22.23298899", - "rel_abs": "Post mortem studies have shown that patients dying from severe SARS-CoV-2 infection frequently have pathological changes in their central nervous system, particularly in the brainstem. Many of these changes are proposed to result from para-infectious and/or post-infection immune responses. Clinical symptoms such as fatigue, breathlessness, and chest pain are frequently reported in post-hospitalized COVID-19 patients. We propose that these symptoms are in part due to damage to key neuromodulatory brainstem nuclei. While brainstem involvement has been demonstrated in the acute phase of the illness, the evidence of long-term brainstem change on magnetic resonance imaging (MRI) is inconclusive. We therefore used ultra-high field (7T) quantitative susceptibility mapping (QSM) to test the hypothesis that brainstem abnormalities persist in post-COVID patients and that these are associated with persistence of key symptoms.\n\nWe used 7T QSM data from 30 patients, scanned 93 - 548 days after hospital admission for COVID-19 and compared them to 51 age-matched controls without prior history of COVID-19 infection. We correlated the patients QSM signals with disease severity (duration of hospital admission and COVID-19 severity scale), inflammatory response during the acute illness (C-reactive protein, D-Dimer and platelet levels), functional recovery (modified Rankin scale; mRS), depression (PHQ-9) and anxiety (GAD-7).\n\nIn COVID-19 survivors the MR susceptibility increased in the medulla, pons and midbrain regions of the brainstem. Specifically, there was increased susceptibility in the inferior medullary reticular formation and the raphe pallidus and obscurus. In these regions, patients with higher tissue susceptibility had worse acute disease severity, higher acute inflammatory markers, and significantly worse functional recovery.\n\nUsing non-invasive ultra-high field 7T MRI, we show evidence of brainstem pathophysiological changes associated with inflammatory processes in post-hospitalized COVID-19 survivors. This study contributes to understanding the mechanisms of long-term effects of COVID-19 and recovery.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.11.22.23298851", + "rel_abs": "Epidemiology based on the detection of pathogens in wastewater is extremely useful in providing information about a populations health status. This study aimed to analyze and report the epidemiological dynamics of SARS-CoV-2 in the province of Tucuman, Argentina during the second and third surges of COVID-19 between April 2021 and March 2022. The study aimed to quantify SARS-CoV-2 RNA in wastewater, correlating it with clinically reported COVID-19 cases. Wastewater samples (n=72) were collected from 16 sampling points located in 3 cities of Tucuman (San Miguel de Tucuman, Yerba Buena y Banda del Rio Sali). Detection of viral nucleocapsid markers (N1 gene) was carried out using one-step RT-qPCR. Viral loads were determined for each positive sample using a standard curve. A positive correlation (p<0.05) was observed between viral load (copies/mL) and the clinically confirmed COVID-19 cases reported during the sampling period in San Miguel de Tucuman. Our research findings provided a crucial insight into the dynamics of SARS-CoV-2 infection during epidemic outbreaks. The implementation of wastewater monitoring has proven to be an invaluable epidemiological tool, facilitating early detection of potential surges in COVID-19 cases, and enabling a comprehensive tracking of the pandemic. Our study underscores the significance of incorporating SARS-CoV-2 genome-based surveillance as a standard practice which will contribute to anticipating any future spikes in infections.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Catarina Rua", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Betty Raman", - "author_inst": "University of Oxford" - }, - { - "author_name": "Christopher T Rodgers", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Virginia F J Newcombe", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Anne Manktelow", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Doris A Chatfield", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Stephen J Sawcer", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Joanne G Outtrim", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Victoria C Lupson", - "author_inst": "University of Cambridge" + "author_name": "Maria Cecilia DArpino", + "author_inst": "Lab of Molecular and Ultraestructural Microbiology, Centro Integral de Microscopia Electronica, (CIME-CONICET)" }, { - "author_name": "Emmanuel A Stamatakis", - "author_inst": "University of Cambridge" + "author_name": "Pedro Eugenio Sineli", + "author_inst": "Planta Piloto de Procesos Industriales Microbiologicos (PROIMI-CONICET), Tucuman, Argentina" }, { - "author_name": "Guy B Williams", - "author_inst": "University of Cambridge" - }, - { - "author_name": "William T Clarke", - "author_inst": "University of Oxford" + "author_name": "Gustavo Goroso", + "author_inst": "Laboratorio de Processamento de Sinais e Modelagem de Sistemas Biologicos. Nucleo de Pesquisas Tecnologicas. Universidade Mogi das Cruzes, Sao Paulo, Brasil." }, { - "author_name": "Lin Qiu", - "author_inst": "University of Oxford" + "author_name": "William Watanabe", + "author_inst": "Laboratorio de Processamento de Sinais e Modelagem de Sistemas Biologicos. Nucleo de Pesquisas Tecnologicas. Universidade Mogi das Cruzes, Sao Paulo, Brasil." }, { - "author_name": "Martyn Ezra", - "author_inst": "University of Oxford" + "author_name": "Maria Lucila Saavedra", + "author_inst": "Centro de Referencia para Lactobacilos (CERELA-CONICET), Tucuman, Argentina" }, { - "author_name": "Rory McDonald", - "author_inst": "University of Oxford" + "author_name": "Elvira Maria Hebert", + "author_inst": "Centro de Referencia para Lactobacilos (CERELA-CONICET), Tucuman, Argentina" }, { - "author_name": "Stuart Clare", - "author_inst": "University of Oxford" + "author_name": "Maria Alejandra Martinez", + "author_inst": "Planta Piloto de Procesos Industriales Microbiologicos (PROIMI-CONICET), Tucuman, Argentina" }, { - "author_name": "Mark Cassar", - "author_inst": "University of Oxford" + "author_name": "Julieta Migliavacca", + "author_inst": "Ministerio de Salud, Gobierno de Tucuman (SIPROSA). Tucuman, Argentina" }, { - "author_name": "Stefan Neubauer", - "author_inst": "University of Oxford" + "author_name": "Silvina Gerstenfeld", + "author_inst": "Ministerio de Salud, Gobierno de Tucuman (SIPROSA). Tucuman, Argentina" }, { - "author_name": "Karen D Ersche", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Edward T Bullmore", - "author_inst": "University of Cambridge" + "author_name": "Rossana Elena Chahla", + "author_inst": "Ministerio de Salud, Gobierno de Tucuman (SIPROSA). Tucuman, Argentina" }, { - "author_name": "David K Menon", - "author_inst": "University of Cambridge" + "author_name": "Augusto Bellomio", + "author_inst": "Instituto Superior de Investigaciones Biologicas (INSIBIO, CONICET-Universidad Nacional de Tucuman), Tucuman, Argentina" }, { - "author_name": "Kyle Pattinson", - "author_inst": "University of Oxford" - }, - { - "author_name": "James B Rowe", - "author_inst": "University of Cambridge" + "author_name": "Virginia Helena Albarracin", + "author_inst": "Electron Microscopy Research Center and Core Facility (CCT-CONICET and UNT)" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.11.20.567923", @@ -30195,35 +30170,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.11.20.23298741", - "rel_title": "Increased Severity of New-onset Type 1 Diabetes in Children and Adolescents during the COVID-19 Pandemic: Experience from a Tertiary Care Center in Serbia", + "rel_doi": "10.1101/2023.11.20.23298335", + "rel_title": "Associations between polygenic risk score and COVID-19 severity in Russian population using low-pass genome sequencing", "rel_date": "2023-11-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.11.20.23298741", - "rel_abs": "Background and objectivesPublic health measures, parental fear of infection, and redeployment of medical resources in response to the COVID-19 pandemic might have led to a decrease in pediatric healthcare access. As a result, a delay in type 1 diabetes diagnosis might have occurred, leading to the worsening of its clinical presentation in the pediatric population. This study aimed to examine the clinical and biochemical features of new-onset DM1 in children and adolescents during the COVID-19 pandemic, comparing it to the pre-pandemic period.\n\nMaterials and methodsThe clinical and biochemical features of diabetes observed during the COVID-19 period from April 1, 2020, until December 31, 2022, were compared with the period from April 1, 2017, until December 31, 2019. In the COVID-19 pandemic group, the clinical and biochemical features were compared between children with and without SARS-CoV-2 infection at diagnosis or before the diagnosis of DM1.\n\nResultsDuring the COVID-19 pandemic, observed frequencies of DKA and severe DKA at diagnosis were 47.6% and 20.7%, both significantly higher than during the pre-pandemic period (an absolute increase of 15% and 11.3%, respectively). In the COVID-19 group, blood pH levels were significantly lower than in the pre-pandemic group, while HbA1c levels were higher. Clinical and biochemical features of diabetes in children with SARS-CoV-2 infection at or before the diagnosis were not significantly different compared to children without an infection.\n\nConclusionWe report a significant worsening of the clinical presentation of new-onset type 1 diabetes and an increase in the frequency of DKA and severe DKA at diagnosis during the COVID-19 pandemic. Further studies are necessary to gain quantitative insight into pediatric healthcare availability in Serbia.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.11.20.23298335", + "rel_abs": "The course of COVID-19 is characterized by wide variability, with genetics playing a contributing role. Through large-scale genetic association studies, a significant link between genetic variants and disease severity was established. However, individual genetic variants identified thus far have shown modest effects, indicating a polygenic nature of this trait. To address this, a polygenic risk score (PRS) can be employed to aggregate the effects of multiple single nucleotide polymorphisms (SNPs) into a single number, allowing practical application to individuals within a population. In this work, we investigated the performance of a PRS model in the context of COVID-19 severity in 1,085 Russian participants using low-coverage NGS sequencing. By developing a genome-wide PRS model based on summary statistics from the COVID-19 Host Genetics Initiative consortium, we demonstrated that the PRS, which incorporates information from over a million common genetic variants, can effectively identify individuals at significantly higher risk for severe COVID-19. The findings revealed that individuals in the top 10% of the PRS distribution had a markedly elevated risk of severe COVID-19, with an odds ratio (OR) of 2.1 (95% confidence interval (CI): 1.4-3.2, p-value = 0.00046). Furthermore, incorporating the PRS into the prediction model significantly improved its accuracy compared to a model that solely relied on demographic information (p-value < 0.0001). This study highlights the potential of PRS as a valuable tool for identifying individuals at increased risk of severe COVID-19 based on their genetic profile.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Damjan Jovanovic", - "author_inst": "Faculty of Medicine, University of Belgrade, Serbia" + "author_name": "Arina Nostaeva", + "author_inst": "St. Petersburg State Budgetary Healthcare Institution City Hospital No. 40 of Kurortny District, Sestroretsk, Russia" }, { - "author_name": "Jelena Blagojevic", - "author_inst": "University Children's Hospital, Belgrade, Serbia" + "author_name": "Valentin Shimansky", + "author_inst": "St. Petersburg State Budgetary Healthcare Institution City Hospital No. 40 of Kurortny District, Sestroretsk, Russia" }, { - "author_name": "Dejana Stanisavljevic", - "author_inst": "Faculty of Medicine, University of Belgrade, Serbia" + "author_name": "Svetlana Apalko", + "author_inst": "St. Petersburg State Budgetary Healthcare Institution City Hospital No. 40 of Kurortny District, Sestroretsk, Russia" }, { - "author_name": "Maja Jesic", - "author_inst": "University Children's Hospital, Belgrade, Serbia" + "author_name": "Ivan Kuznetsov", + "author_inst": "Skolkovo Institute of Science and Technology, Moscow, Russia" + }, + { + "author_name": "Natalya Sushentseva", + "author_inst": "St. Petersburg State Budgetary Healthcare Institution City Hospital No. 40 of Kurortny District, Sestroretsk, Russia" + }, + { + "author_name": "Oleg Popov", + "author_inst": "St. Petersburg State Budgetary Healthcare Institution City Hospital No. 40 of Kurortny District, Sestroretsk, Russia" + }, + { + "author_name": "Anna Anisenkova", + "author_inst": "St. Petersburg State Budgetary Healthcare Institution City Hospital No. 40 of Kurortny District, Sestroretsk, Russia" + }, + { + "author_name": "Sergey Mosenko", + "author_inst": "St. Petersburg State Budgetary Healthcare Institution City Hospital No. 40 of Kurortny District, Sestroretsk, Russia" + }, + { + "author_name": "Lennart Karssen", + "author_inst": "PolyKnomics BV, The Netherlands" + }, + { + "author_name": "Yurii Aulchenko", + "author_inst": "Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia" + }, + { + "author_name": "Sergey Shcherbak", + "author_inst": "St. Petersburg State Budgetary Healthcare Institution City Hospital No. 40 of Kurortny District, Sestroretsk, Russia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2023.11.20.23298788", @@ -32013,25 +32016,29 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.11.13.23298463", - "rel_title": "A SOLUTION TO THE KERMACK AND MCKENDRICK INTEGRO-DIFFERENTIAL EQUATIONS WHICH ACCURATELY PROJECTS COVID-19 CASE DATA USING GOOGLE MOBILITY DATA AS AN INPUT", + "rel_doi": "10.1101/2023.11.13.23298464", + "rel_title": "Assessing the Impact of Mask Mandates on SARS-CoV-2 Transmission: A Case Study of Utah", "rel_date": "2023-11-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.11.13.23298463", - "rel_abs": "In this manuscript, we derive a closed form solution to the full Kermack and McKendrick integro-differential equations (Kermack and McKendrick 1927) which we call the KMES. We demonstrate the veracity of the KMES using the Google Residential Mobility Measure to accurately project case data from the Covid 19 pandemic and we derive many useful, but previously unknown, analytical expressions for characterizing and managing an epidemic. These include expressions for the viral load, the final size, the effective reproduction number, and the time to the peak in infections. The KMES can also be cast in the form of a step function system response to the input of new infections; and that response is the time series of total infections.\n\nSince the publication of Kermack and McKendricks seminal paper (1927), thousands of authors have utilized the Susceptible, Infected, and Recovered (SIR) approximations; expressions putatively derived from the integro-differential equations to model epidemic dynamics. Implicit in the use of the SIR approximation are the beliefs that there is no closed form solution to the integro-differential equations, and that the approximation is a special case which adequately reproduces the dynamics of the integro-differential equations mapped onto the physical world. However, the KMES demonstrates that the SIR approximations are not adequate representations of the integro-differential equations, and we therefore suggest that the KMES obsoletes the need for the SIR approximations by providing not only a new mathematical perspective, but a new understanding of epidemic dynamics.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.11.13.23298464", + "rel_abs": "BackgroundThroughout the COVID-19 pandemic, the effectiveness of face masks mandates has been intensely debated. Many methods have been used to demonstrate mask effectiveness, including one that compares the change in reproduction number following implementing and removing face mask mandates1.\n\nMethodsUsing data from Utah, we calculated the effect of mask mandates (EFm) in each local health district from before and after three key mandates: the Salt Lake and Summit County (SLSC) mask mandates enacted; the Utah statewide mask mandate enacted; and the Utah statewide mandate was lifted.\n\nResultsWe found that most counties had a reduction in the growth rate of cases following the mandates. There were reductions in EFm in many counties after the introduction of the SLSC mask mandates and a more widespread reduction in EFm across the state following the statewide mandate. Lifting the mandates, many counties across the states saw an increase in EFm.\n\nConclusionOur data show mask mandates were an effective way to reduce transmission both within the jurisdiction they were enacted and in neighboring jurisdictions. We provide evidence to support mask mandates as a way to prevent transmission to be better equipped to respond to future pandemics.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Theodore G Duclos", - "author_inst": "Ted Duclos Advisors" + "author_name": "Alicia C Horn", + "author_inst": "University of Utah" }, { - "author_name": "Thomas Reichert", - "author_inst": "Entropy Research Institute" + "author_name": "Holly E Shoemaker", + "author_inst": "University of Utah" + }, + { + "author_name": "Lindsay T Keegan", + "author_inst": "University of Utah" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -34059,55 +34066,63 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.11.06.565757", - "rel_title": "Allosteric modulation by the fatty acid site in the glycosylated SARS-CoV-2 spike", + "rel_doi": "10.1101/2023.11.07.566012", + "rel_title": "Predicting human and viral protein variants affecting COVID-19 susceptibility and repurposing therapeutics", "rel_date": "2023-11-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.11.06.565757", - "rel_abs": "The trimeric spike protein plays an essential role in the SARS-CoV-2 virus lifecycle, facilitating virus entry through binding to the cellular receptor angiotensin-converting enzyme 2 (ACE2) and mediating viral and host membrane fusion. The SARS-CoV-2 spike contains an allosteric fatty acid (FA) binding site at the interface between two neighbouring receptor-binding domains. This site, also found in some other coronaviruses, binds free fatty acids such as linoleic and oleic acid, and other small molecules. Understanding allostery and how this site modulates the behaviour of different regions in this protein could potentiate the development of promising alternative strategies for new coronavirus therapies. Here, we apply dynamical nonequilibrium molecular dynamics (D-NEMD) simulations to investigate allosteric effects and identify the communication pathways in the fully glycosylated spike in the original SARS-CoV-2 ancestral variant. The results reveal the allosteric networks that connect the FA site to important functional regions of the protein, including some more than 40 [A] away. These regions include the receptor binding motif, an antigenic supersite in the N-terminal domain, the furin cleavage site, the regions surrounding the fusion peptide and a second allosteric site known to bind heme and biliverdin. The networks identified here highlight the complexity of the allosteric modulation in this protein and reveal a striking and unexpected connection between different allosteric sites. Notably, 65% of amino acid substitutions, deletions and insertions in the Alpha, Beta, Delta, Gamma and Omicron variants map onto or close to the identified allosteric pathways.\n\nSignificance statementThe spike protein plays an essential role in the SARS-CoV-2 virus lifecycle, mediating viral and host membrane fusion. This protein contains several allosteric sites, including a fatty acid binding site at the interface between every two neighbouring receptor-binding domains. Here, we investigate how these sites modulate the structural and dynamical behaviour of the fully glycosylated protein. Our work revealed unexpected and complex patterns of communication between the fatty acid site and functionally important regions of the spike (including the receptor binding motif, the antigenic supersite in the N-terminal domain and the heme/biliverdin site) and shed new light on the roles of glycans in this protein. Understanding allosteric modulation can potentiate the development of alternative strategies for new COVID-19 therapies.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.11.07.566012", + "rel_abs": "The COVID-19 disease is an ongoing global health concern. Although vaccination provides some protection, people are still susceptible to re-infection. Ostensibly, certain populations or clinical groups may be more vulnerable. Factors causing these differences are unclear and whilst socioeconomic and cultural differences are likely to be important, human genetic factors could influence susceptibility. Experimental studies indicate SARS-CoV-2 uses innate immune suppression as a strategy to speed-up entry and replication into the host cell. Therefore, it is necessary to understand the impact of variants in immunity-associated human proteins on susceptibility to COVID-19.\n\nIn this work, we analysed missense coding variants in several SARS-CoV-2 proteins and its human protein interactors that could enhance binding affinity to SARS-CoV-2. We curated a dataset of 19 SARS-CoV-2: human protein 3D-complexes, from the experimentally determined structures in the Protein Data Bank and models built using AlphaFold2-multimer, and analysed impact of missense variants occurring in the protein-protein interface region. We analysed 468 missense variants from human proteins and 212 variants from SARS-CoV-2 proteins and computationally predicted their impacts on binding affinities to SARS-CoV-2 proteins, using 3D-complexes.\n\nWe predicted a total of 26 affinity-enhancing variants from 14 human proteins implicated in increased binding affinity to SARS-CoV-2. These include key-immunity associated genes (TOMM70, ISG15, IFIH1, IFIT2, RPS3, PALS1, NUP98, RAE1, AXL, ARF6, TRIMM, TRIM25) as well as important spike receptors (KREMEN1, AXL and ACE2). We report both common (e.g., Y13N in IFIH1) and rare variants in these proteins and discuss their likely structural and functional impact, using information on known and predicted functional sites. Potential mechanisms associated with immune suppression implicated by these variants are discussed.\n\nOccurrence of certain predicted affinity-enhancing variants should be monitored as they could lead to increased susceptibility and reduced immune response to SARS-CoV-2 infection in individuals/populations carrying them. Our analyses aid in understanding the potential impact of genetic variation in immunity-associated proteins on COVID-19 susceptibility and help guide drug-repurposing strategies.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "A Sofia F Oliveira", - "author_inst": "University of Bristol" + "author_name": "Vaishali P Waman", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" }, { - "author_name": "Fiona L Kearns", - "author_inst": "University of California San Diego" + "author_name": "Paul Ashford", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" }, { - "author_name": "Mia A Rosenfeld", - "author_inst": "University of California San Diego" + "author_name": "Su Datt Lam", + "author_inst": "Department of Applied Physics, Faculty of Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia" }, { - "author_name": "Lorenzo F Casalino", - "author_inst": "University of California San Diego" + "author_name": "Neeladri Sen", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" }, { - "author_name": "Imre Berger", - "author_inst": "University of Bristol" + "author_name": "Mahnaz Abbasian", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" }, { - "author_name": "Christiane Schaffitzel", - "author_inst": "University of Bristol" + "author_name": "Laurel Woodridge", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" }, { - "author_name": "Andrew D Davidson", - "author_inst": "University of Bristol" + "author_name": "Yonathan Goldtzvik", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" }, { - "author_name": "Rommie E Amaro", - "author_inst": "University of California, San Diego" + "author_name": "Nicola Bordin", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" }, { - "author_name": "Adrian J Mulholland", - "author_inst": "University of Bristol" + "author_name": "Jiaxin Wu", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" + }, + { + "author_name": "Ian Sillitoe", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" + }, + { + "author_name": "Christine Orengo", + "author_inst": "Institute of Structural and Molecular Biology, University College London, London, WC1E 6BT, UK" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "biochemistry" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2023.11.06.23298101", @@ -35893,47 +35908,71 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2023.10.31.565042", - "rel_title": "SARS-CoV-2 infection leads to sustained testicular injury and functional impairments in K18 hACE2 mice", + "rel_doi": "10.1101/2023.10.30.564631", + "rel_title": "Patient phenotypes and their relation to TNF\u03b1 signaling and immune cell composition in critical illness and autoimmune disease", "rel_date": "2023-11-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.31.565042", - "rel_abs": "Compromised male reproductive health is one of the symptoms of long COVID with a decrease in male fertility markers including testosterone levels and sperm count for months in recovering patients. However, the long-term impact of SARS-CoV-2 infection on testicular injury and underlying mechanisms remains unknown. We previously demonstrated a disrupted tissue architecture with no evidence of virus replication in the testis during the acute stage of the disease in K18-hACE2 mice. Here, we systematically delineate the consequences of SARS-CoV-2 infection on the testis injury and function both during the acute stage of the disease and up to 4 weeks after infection in survivor K18-hACE2 mice. The gross morphological defects included sloughing of healthy spermatids and spermatocytes into the lumen, lack of lumen, and increase in apoptotic cells that sustained for at least 2 weeks after infection. Testis injury correlated with systemic and testicular inflammation, and infiltration of immune cells in the interstitial space and seminiferous tubules. Transcriptomic analysis identified dysregulation of key pathways of testicular immune homeostasis, spermatogenesis, and cell death at the symptomatic and short-term recovery stages. Further, a significant reduction in testosterone levels was associated with transient reduction in sperm count and mouse fertility. Most of the testicular impairments except testosterone levels were resolved within 4 weeks, which is almost one spermatogenesis cycle in mice. These findings provide much-needed mechanistic insights beyond our current understanding of testicular pathogenesis, suggesting that recovering COVID-19 patients should be closely monitored to rescue the pathophysiological effects on male reproductive health.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.30.564631", + "rel_abs": "RationaleTNF inhibitors have shown promise in reducing mortality in hospitalized COVID-19 patients; one hypothesis explaining the limited clinical efficacy is patient heterogeneity in the TNF pathway.\n\nMethodsWe evaluated the effect of TNF inhibitors in a mouse model of LPS-induced acute lung injury. Using machine learning we attempted predictive enrichment of TNF signaling in patients with either ARDS or sepsis. We examined biological factors that drive heterogeneity in host responses to critical infection and their relation to clinical outcomes.\n\nResultsIn mice, LPS induced TNF-dependent neutrophilia, alveolar permeability and endothelial injury. In humans, TNF pathway activation was significantly increased in peripheral blood of patients with critical illnesses and associated with the presence of mature neutrophils across critical illnesses and several autoimmune conditions. Machine learning using a gene signature separated patients into 5 phenotypes; one was a hyper-inflammatory, interferon-associated phenotype enriched for increased TNF pathway activation and conserved across critical illnesses and autoimmune diseases. Cell subset profiles segregated severely ill patients into neutrophil-subset-dependent groups that were enriched for disease severity, demonstrating the importance of neutrophils in the immune response in critical illness.\n\nConclusionsTNF signaling and mature neutrophils are associated with a hyper-inflammatory phenotype of patients, shared across critical illness and autoimmune disease. This phenotyping provides a personalized medicine hypothesis to test anti-TNF therapy in severe respiratory illness.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC=\"FIGDIR/small/564631v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (36K):\norg.highwire.dtl.DTLVardef@1e25724org.highwire.dtl.DTLVardef@c708bcorg.highwire.dtl.DTLVardef@10e7531org.highwire.dtl.DTLVardef@3014b8_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Stefanos Giannakopoulos", - "author_inst": "Department of Cell and Molecular Biology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA" + "author_name": "Vinod Krishna", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, 1400 McKean Road, Spring House, PA 19477, USA" }, { - "author_name": "Monika A Ward", - "author_inst": "Institute for Biogenesis Research, John A Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA" + "author_name": "Homayon Banie", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, 1600 Sierra Point Parkway, Brisbane CA 94005, USA" }, { - "author_name": "Jackson Bakse", - "author_inst": "Institute for Biogenesis Research, John A Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA" + "author_name": "N\u00e1dia Concei\u00e7\u00e3o-Neto", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, Turnhoutseweg 30, 2340 Beerse, Belgium" }, { - "author_name": "Jin Hyuk Pak", - "author_inst": "Department of Tropical Medicine, Medical Microbiology, and Pharmacology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA" + "author_name": "Yoshihiko Murata", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, 1400 McKean Road, Spring House, PA 19477, USA" }, { - "author_name": "Vivek R Nerurkar", - "author_inst": "Department of Tropical Medicine, Medical Microbiology, and Pharmacology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA" + "author_name": "Inge Verbrugge", + "author_inst": "Infectious Diseases Clinical Microbiology and Immunology, Infectious Diseases and Vaccines, Janssen Research and Development, Turnhoutseweg 30, 2340 Beerse, Bel" }, { - "author_name": "Michelle D Tallquist", - "author_inst": "Center for Cardiovascular Research, John A. School of Medicine, University of Hawaii at Manoa, Honolulu, HI, USA" + "author_name": "Vladimir Trifonov", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, 3210 Merryfield Row, San Diego, CA 92121, USA" }, { - "author_name": "Saguna Verma", - "author_inst": "Department of Tropical Medicine, Medical Microbiology, and Pharmacology, John A. Burns School of Medicine, University of Hawaii at Manoa, Honolulu, Hawaii, USA" + "author_name": "Roxana Martinez", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, 1600 Sierra Point Parkway, Brisbane CA 94005, USA" + }, + { + "author_name": "Vasumathy Murali", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, 1600 Sierra Point Parkway, Brisbane CA 94005, USA" + }, + { + "author_name": "Yu-chi Lee", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, 1600 Sierra Point Parkway, Brisbane CA 94005, USA" + }, + { + "author_name": "Richard D May", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, UK" + }, + { + "author_name": "Isabel N\u00e1jera", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, 1600 Sierra Point Parkway, Brisbane CA 94005, USA" + }, + { + "author_name": "Andrew Fowler", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, UK" + }, + { + "author_name": "Chris Ka Fai Li", + "author_inst": "Infectious Diseases Discovery, Infectious Diseases and Vaccines, Janssen Research and Development, 1600 Sierra Point Parkway, Brisbane CA 94005, USA" } ], "version": "1", "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2023.10.30.23297594", @@ -37447,91 +37486,107 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2023.10.25.563967", - "rel_title": "Discovery of a novel inhibitor of macropinocytosis with antiviral activity", + "rel_doi": "10.1101/2023.10.25.564014", + "rel_title": "Early antiviral CD4 and CD8 T cell responses are associated with upper respiratory tract clearance of SARS-CoV-2", "rel_date": "2023-10-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.25.563967", - "rel_abs": "Several viruses hijack various forms of endocytosis in order to infect host cells. Here, we report the discovery of a new molecule with antiviral properties that we named virapinib, which limits viral entry by macropinocytosis. The identification of virapinib derives from a chemical screen using High-Throughput Microscopy, where we identified new chemical entities capable of preventing infection with a pseudotype virus expressing the spike (S) protein from SARS-CoV-2. Subsequent experiments confirmed the capacity of virapinib to inhibit infection by SARS-CoV-2, as well as by additional viruses, such as Monkeypox virus and TBEV. Mechanistic analyses revealed that the compound inhibited macropinocytosis, limiting this entry route for the viruses. Importantly, virapinib has no significant toxicity to host cells. In summary, we present a new molecule that inhibits viral entry via the endocytic route, offering a new alternative to prevent viral infection.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.25.564014", + "rel_abs": "T cells are involved in protective immunity against numerous viral infections. Limited data have been available regarding roles of human T cell responses controlling SARS-CoV-2 viral clearance in primary COVID-19. Here, we examined longitudinal SARS-CoV-2 upper respiratory tract viral RNA levels and early adaptive immune responses from 95 unvaccinated individuals with acute COVID-19. Acute SARS-CoV-2-specific CD4 and CD8 T cell responses were evaluated in addition to antibody responses. Most individuals with acute COVID-19 developed rapid SARS-CoV-2-specific T cell responses during infection, and both early CD4 T cell and CD8 T cell responses correlated with reduced upper respiratory tract SARS-CoV-2 viral RNA, independent of neutralizing antibody titers. Overall, our findings indicate a distinct protective role for SARS-CoV-2-specific T cells during acute COVID-19.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Bartlomiej Porebski", - "author_inst": "Karolinska Institute" + "author_name": "Sydney I Ramirez", + "author_inst": "La Jolla Institute for Immunology (LJI), University of California San Diego (UCSD)" }, { - "author_name": "Wanda Christ", - "author_inst": "Karolinska Institute" + "author_name": "Paul G Lopez", + "author_inst": "La Jolla Institute for Immunology (LJI)" }, { - "author_name": "Alba Corman", - "author_inst": "Karolinska Institute" + "author_name": "Farhoud Faraji", + "author_inst": "University of California San Diego (UCSD)" }, { - "author_name": "Martin Haraldsson", - "author_inst": "Karolinska Institute" + "author_name": "Urvi M Parikh", + "author_inst": "University of Pittsburgh School of Medicine" }, { - "author_name": "Myriam Barz", - "author_inst": "Karolinska Institute" + "author_name": "Amy Heaps", + "author_inst": "University of Pittsburgh School of Medicine" }, { - "author_name": "Louise Lidemalm", - "author_inst": "Karolinska Institute" + "author_name": "Justin Ritz", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Maria Haggblad", - "author_inst": "Karolinska Institute" + "author_name": "Carlee Moser", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Juliana Illmain", - "author_inst": "NYU" + "author_name": "Joseph J Eron", + "author_inst": "University of North Carolina at Chapel Hill School of Medicine" }, { - "author_name": "Shane Wright", - "author_inst": "Karolinska Institute" + "author_name": "David A Wohl", + "author_inst": "University of North Carolina at Chapel Hill School of Medicine" }, { - "author_name": "Matilde Murga", - "author_inst": "CNIO" + "author_name": "Judith S Currier", + "author_inst": "David Geffen School of Medicine at University of California Los Angeles" }, { - "author_name": "Jan Schlegel", - "author_inst": "Karolinska Institute" + "author_name": "Eric S Daar", + "author_inst": "8Lundquist Institute at Harbor-UCLA Medical Center" }, { - "author_name": "Erdinc Sezgin", - "author_inst": "Karolinska Institutet" + "author_name": "Alex L Greninger", + "author_inst": "University of Washington Medical Center" }, { - "author_name": "Gira Bhabha", - "author_inst": "NYU" + "author_name": "Paul Klekotka", + "author_inst": "Eli Lilly and Company" }, { - "author_name": "Volker M Lauschke", - "author_inst": "Karolinska Instituet" + "author_name": "Alba Grifoni", + "author_inst": "La Jolla Institute for Immunology (LJI)" }, { - "author_name": "Miguel Lafarga", - "author_inst": "University of Cantabria" + "author_name": "Daniela Weiskopf", + "author_inst": "La Jolla Institute for Immunology (LJI), University of California San Diego (UCSD)" }, { - "author_name": "Jonas Klingstrom", - "author_inst": "Center for Infectious Medicine, Department of Medicine, Karolinska Institutet, Karolinska University Hospital Huddinge, Stockholm, Sweden" + "author_name": "Alessandro Sette", + "author_inst": "La Jolla Institute for Immunology (LJI), University of California San Diego (UCSD)" }, { - "author_name": "Daniela Huhn", - "author_inst": "Karolinska Institute" + "author_name": "Bjoern Peters", + "author_inst": "La Jolla Institute for Immunology (LJI), University of California San Diego (UCSD)" }, { - "author_name": "Oscar Fernandez-Capetillo", - "author_inst": "CNIO/KI" + "author_name": "Michael D Hughes", + "author_inst": "Harvard T.H. Chan School of Public Health" + }, + { + "author_name": "Kara W Chew", + "author_inst": "David Geffen School of Medicine at University of California Los Angeles" + }, + { + "author_name": "Davey M Smith", + "author_inst": "University of California San Diego (UCSD)" + }, + { + "author_name": "Shane Crotty", + "author_inst": "La Jolla Institute For Immunology (LJI)" + }, + { + "author_name": "- ACTIV-2/A5401 Study Team", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "pharmacology and toxicology" + "category": "immunology" }, { "rel_doi": "10.1101/2023.10.24.563847", @@ -37657,7 +37712,7 @@ "rel_date": "2023-10-26", "rel_site": "bioRxiv", "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.25.564079", - "rel_abs": "Genetics-informed drug repositioning presents a streamlined and cost-efficient way to broaden therapeutic options. However, leveraging the full spectrum of molecular signatures remains underexplored. We introduce TReD (Transcriptome-informed Reversal Distance), integrating population-level disease signatures robust to reverse causality and cell-based drug-induced response profiles. TReD embeds the disease signature and drug profile in a high-dimensional normed space, quantifying the reversal potential of candidate drugs in a disease-related cell screen assay. For illustration, we apply TReD to COVID-19 and type 2 diabetes (T2D). We identify 37 potential drugs against COVID-19, over 70% (27/37) with prior associations, and eight supported by clinical trials. For T2D, we observe reversal signals for 86 compounds on multiple disease signatures, with more than 40% supported by published literature. In summary, we propose a comprehensive genetics-anchored framework integrating population-level signatures and cell-based screens that can accelerate the search for new therapeutic strategies.\n\nHighlightsO_LITReD is a genetics-informed framework that integrates population-level disease signatures and cell-based drug response profiles for drug repositioning.\nC_LIO_LIThe effectiveness of TReD is demonstrated by identifying established and new therapeutic candidates for COVID-19 and type 2 diabetes.\nC_LIO_LISingle-gene (TWAS and coloc-SuSiE) and multi-target (TReD) drug repositioning approaches are integrated to enable a comprehensive therapeutic search.\nC_LI\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC=\"FIGDIR/small/564079v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (44K):\norg.highwire.dtl.DTLVardef@10657f7org.highwire.dtl.DTLVardef@1793246org.highwire.dtl.DTLVardef@1d39db4org.highwire.dtl.DTLVardef@169f9d_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_abs": "Genetics-informed drug repositioning presents a streamlined and cost-efficient way to broaden therapeutic options. However, leveraging the full spectrum of molecular signatures remains underexplored. We introduce TReD (Transcriptome-informed Reversal Distance), integrating population-level disease signatures robust to reverse causality and cell-based drug-induced response profiles. TReD embeds the disease signature and drug profile in a high-dimensional normed space, quantifying the reversal potential of candidate drugs in a disease-related cell screen assay. For illustration, we apply TReD to COVID-19 and type 2 diabetes (T2D). We identify 37 potential drugs against COVID-19, over 70% (27/37) with prior associations, and eight supported by clinical trials. For T2D, we observe reversal signals for 86 compounds on multiple disease signatures, with more than 40% supported by published literature. In summary, we propose a comprehensive genetics-anchored framework integrating population-level signatures and cell-based screens that can accelerate the search for new therapeutic strategies.\n\nHighlightsO_LITReD is a genetics-informed framework that integrates population-level disease signatures and cell-based drug response profiles for drug repositioning.\nC_LIO_LIThe effectiveness of TReD is demonstrated by identifying established and new therapeutic candidates for COVID-19 and type 2 diabetes.\nC_LIO_LISingle-gene (TWAS and coloc-SuSiE) and multi-target (TReD) drug repositioning approaches are integrated to enable a comprehensive therapeutic search.\nC_LI\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC=\"FIGDIR/small/564079v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (44K):\norg.highwire.dtl.DTLVardef@1e93265org.highwire.dtl.DTLVardef@ebabd2org.highwire.dtl.DTLVardef@5d8636org.highwire.dtl.DTLVardef@166751_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 8, "rel_authors": [ { @@ -39601,75 +39656,43 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.10.23.563088", - "rel_title": "Nonspecific membrane bilayer perturbations by ivermectin underlie SARS-CoV-2 in vitro activity", + "rel_doi": "10.1101/2023.10.24.563721", + "rel_title": "Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders", "rel_date": "2023-10-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.23.563088", - "rel_abs": "Since it was proposed as a potential host-directed antiviral agent for SARS-CoV-2, the antiparasitic drug ivermectin has been investigated thoroughly in clinical trials, which have provided insufficient support for its clinical efficacy. To examine the potential for ivermectin to be repurposed as an antiviral agent, we therefore undertook a series of preclinical studies. Consistent with early reports, ivermectin decreased SARS-CoV-2 viral burden in in vitro models at low micromolar concentrations, five-to ten-fold higher than the reported toxic clinical concentration. At similar concentrations, ivermectin also decreased cell viability and increased biomarkers of cytotoxicity and apoptosis. Further mechanistic and profiling studies revealed that ivermectin nonspecifically perturbs membrane bilayers at the same concentrations where it decreases the SARS-CoV-2 viral burden, resulting in nonspecific modulation of membrane-based targets such as G-protein coupled receptors and ion channels. These results suggest that a primary molecular mechanism for the in vitro antiviral activity of ivermectin may be nonspecific membrane perturbation, indicating that ivermectin is unlikely to be translatable into a safe and effective antiviral agent. These results and experimental workflow provide a useful paradigm for performing preclinical studies on (pandemic-related) drug repurposing candidates.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=61 SRC=\"FIGDIR/small/563088v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (18K):\norg.highwire.dtl.DTLVardef@a21f94org.highwire.dtl.DTLVardef@1c76751org.highwire.dtl.DTLVardef@500930org.highwire.dtl.DTLVardef@8b6c05_HPS_FORMAT_FIGEXP M_FIG Graphical abstract C_FIG", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.24.563721", + "rel_abs": "The coronavirus disease of 2019 (COVID-19) pandemic is characterized by sequential emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants and lineages outcompeting previously circulating ones because of, among other factors, increased transmissibility and immune escape1-3. We devised an unsupervised deep learning AutoEncoder for viral genomes anomaly detection to predict future dominant lineages (FDLs), i.e., lineages or sublineages comprising [≥]10% of viral sequences added to the GISAID database on a given week4. The algorithm was trained and validated by assembling global and country-specific data sets from 16,187,950 Spike protein sequences sampled between December 24th, 2019, and November 8th, 2023. The AutoEncoder flags low frequency FDLs (0.01% - 3%), with median lead times of 4-16 weeks. Over time, positive predictive values oscillate, decreasing linearly with the number of unique sequences per data set, showing average performance up to 30 times better than baseline approaches. The B.1.617.2 vaccine reference strain was flagged as FDL when its frequency was only 0.01%, more than one year earlier of being considered for an updated COVID-19 vaccine. Our AutoEncoder, applicable in principle to any pathogen, also pinpoints specific mutations potentially linked to increased fitness, and may provide significant insights for the optimization of public health pre-emptive intervention strategies.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Richard T Eastman", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health" - }, - { - "author_name": "Radda Rusinova", - "author_inst": "Weill Cornell Medicine" - }, - { - "author_name": "Karl F Herold", - "author_inst": "Weill Cornell Medicine" - }, - { - "author_name": "Xi-Ping Huang", - "author_inst": "University of North Carolina School of Medicine" - }, - { - "author_name": "Patricia Dranchak", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health" - }, - { - "author_name": "Ty C Voss", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health" - }, - { - "author_name": "Sandeep Rana", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health" - }, - { - "author_name": "Jonathan H Shrimp", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health" - }, - { - "author_name": "Alex D White", - "author_inst": "University of California San Francisco" + "author_name": "Simone Rancati", + "author_inst": "University of Pavia" }, { - "author_name": "Hugh C Hemmings Jr.", - "author_inst": "Weill Cornell Medicine" + "author_name": "Giovanna Nicora", + "author_inst": "University of Pavia" }, { - "author_name": "Bryan L Roth", - "author_inst": "University of North Carolina School of Medicine" + "author_name": "Mattia Prosperi", + "author_inst": "University of Florida" }, { - "author_name": "James Inglese", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health" + "author_name": "Riccardo Bellazzi", + "author_inst": "University of Pavia" }, { - "author_name": "Olaf S Andersen", - "author_inst": "Weill Cornell Medicine" + "author_name": "Simone Marini", + "author_inst": "University of Florida" }, { - "author_name": "Jayme L Dahlin", - "author_inst": "National Center for Advancing Translational Sciences, National Institutes of Health" + "author_name": "Marco Salemi", + "author_inst": "University of Florida" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "new results", - "category": "pharmacology and toxicology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2023.10.16.23297124", @@ -41427,39 +41450,71 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.10.17.23297174", - "rel_title": "Persistent high mortality rates for Diabetes Mellitus and Hypertension after excluding deaths associated with COVID-19 in Brazil, 2020-2022", + "rel_doi": "10.1101/2023.10.17.23297146", + "rel_title": "The SHOW COVID-19 cohort: methods and rationale for examining the statewide impact of COVID-19 on the social determinants of health", "rel_date": "2023-10-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.17.23297174", - "rel_abs": "BackgroundThe outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) posed a significant public health challenge globally, with Brazil being no exception. Excess mortality during this period reached alarming levels. Cardiovascular diseases (CVD), Systemic Hypertension (HTN), and Diabetes Mellitus (DM) were associated with increased mortality. However, the specific impact of DM and HTN on mortality during the pandemic remains poorly understood.\n\nMethodsThis study analyzed mortality data from Brazils mortality system, covering the period from 2015 to 2022. Data included all causes of death as listed on death certificates, categorized by International Classification of Diseases 10th edition (ICD-10) codes. Population data were obtained from the Brazilian Census. Mortality ratios (MRs) were calculated by comparing death rates in 2020, 2021, and 2022 to the average rates from 2015 to 2019. Adjusted MRs were calculated using Poisson models.\n\nResultsBetween 2015 and 2022, Brazil recorded a total of 11,423,288 deaths. Death rates remained relatively stable until 2019 but experienced a sharp increase in 2020 and 2021. In 2022, although a decrease was observed, it did not return to pre-pandemic levels. This trend persisted even when analyzing records mentioning DM, HTN, or CVD. Excluding death certificates mentioning COVID-19 codes, the trends still showed increases from 2020 through 2022, though less pronounced.\n\nConclusionThis study highlights the persistent high mortality rates for DM and HTN in Brazil during the years 2020-2022, even after excluding deaths associated with COVID-19. These findings emphasize the need for continued attention to managing and preventing DM and HTN as part of public health strategies, both during and beyond the COVID-19 pandemic. There are complex interactions between these conditions and the pandemics impact on mortality rates.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.17.23297146", + "rel_abs": "BackgroundNational and large city mortality and morbidity data emerged during the early years of the COVID-19 pandemic, yet statewide data to assess the impact COVID-19 had across urban and rural landscapes on subpopulations was lacking. The SHOW COVID-19 cohort was established to provide descriptive and longitudinal data to examine the influence the social determinants of health had on COVID-19 related outcomes.\n\nMethodsParticipants were recruited from the 5,742 adults in the Survey of the Health of Wisconsin (SHOW) cohort who were all residents of Wisconsin, United States when they joined the cohort between 2008-2019. Online surveys were administered at three timepoints during 2020-2021. Survey topics included COVID-19 exposure, testing and vaccination, COVID-19 impact on economic wellbeing, healthcare access, mental and emotional health, caregiving, diet, lifestyle behaviors, social cohesion, and resilience.\n\nResultsA total of 2,304 adults completed at least one COVID-19 online survey, with n=1,090 completing all three survey timepoints. Non-Whites were 2-3 times more likely to report having had COVID-19 compared to Whites, females were more likely than males to experience disruptions in their employment, and those with children in the home were more likely to report moderate to high levels of stress compared to adults without children.\n\nConclusionLongitudinal, statewide cohorts are important for investigating how the social determinants of health affect peoples lives, health, and well-being during the first years of a pandemic and offer insight into future pandemic preparation. The data are available for researchers and cohort is active for continued and future follow-up.\n\nKey MessagesO_LIMortality and morbidity data emerged during the early years of the COVID-19 pandemic at the national scale and in large cities, yet comprehensive social, cultural, and economic population-level data at the state level was lacking for identifying sub-population trends.\nC_LIO_LICOVID-19 disrupted lives and affected people differently based on socio-economic status, demographics, family dynamics, geography, health status, and employment.\nC_LIO_LISHOW COVID-19 cohort is a unique non-clinical, non-hospital-based sample with pre-COVID-19 baseline survey data and biospecimen and three waves of COVID-19 data and specimen available to examine effects of COVID-19 on the social determinants of health.\nC_LI", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Rodrigo Moreira", - "author_inst": "Fundacao Oswaldo Cruz" + "author_name": "Amy A Schultz", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Leonardo S Bastos", - "author_inst": "FIOCRUZ: Fundacao Oswaldo Cruz" + "author_name": "Erin Nelson-Bakkum", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Luiz Max Carvalho", - "author_inst": "Funda\u00e7\u00e3o Get\u00falio Vargas: Fundacao Getulio Vargas" + "author_name": "Maria Nikodemova", + "author_inst": "University of Florida" }, { - "author_name": "La\u00eds Picinini Freitas", - "author_inst": "Universit\u00e9 de Montr\u00e9al \u00c9cole de Sant\u00e9 Publique: Universite de Montreal Ecole de Sante Publique" + "author_name": "Sarah Luongo", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Antonio Guilherme Pacheco", - "author_inst": "FIOCRUZ: Fundacao Oswaldo Cruz" + "author_name": "Jodi H Barnet", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Matthew C Walsh", + "author_inst": "University of Wisconsin - Madison" + }, + { + "author_name": "Andrew Bersch", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Lisa Cadmus-Bertram", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Corinne D Engelman", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Julia Lubsen", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Paul Peppard", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Ajay Sethi", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Kristen MC Malecki", + "author_inst": "University of Illinois-Chicago" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.10.17.562827", @@ -43225,135 +43280,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.10.11.23296808", - "rel_title": "Safety of SARS-CoV-2 test-to-stay in daycare: a regression discontinuity in time analysis", + "rel_doi": "10.1101/2023.10.10.23296845", + "rel_title": "Availability of Essential Medicines During the COVID-19 Pandemic: A Qualitative Study Examining Experiences and Level of Preparedness in Kenya", "rel_date": "2023-10-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.11.23296808", - "rel_abs": "Background and ObjectivesTest-to-stay concepts apply serial testing of children in daycare after exposure to SARS-CoV-2 without use of quarantine. This study aims to assess safety of a test-to-stay screening in daycare facilities.\n\nMethods714 daycare facilities and approximately 50,000 children [≤]6 years in Cologne, Germany participated in a SARS-CoV-2 Pool-PCR screening from March 2021 to April 2022. The screening initially comprised post-exposure quarantine and was adapted to a test-to-stay approach during its course. To assess safety of the test-to-stay approach, we explored potential changes in frequencies of infections among children following the adaptation to the test-to-stay approach by applying regression discontinuity in time (RDiT) analyses. To this end, PCR-test data were linked with routinely collected data on reported infections in children and analyzed using ordinary least squares regressions.\n\nResults219,885 Pool-PCRs and 352,305 Single-PCRs were performed. 6,440 (2.93%) Pool-PCRs tested positive, and 17,208 infections in children were reported. We estimated that during a period of 30 weeks, the test-to-stay concept avoided between 7 and 20 days of quarantine per eligible daycare child. RDiT revealed a 26% reduction (Exp. Coef: 0.74, CI:0.52;1.06) in infection frequency among children and indicated no significant increase attributable to the test-to-stay approach. This result was not sensitive to adjustments for 7-day incidence, season, SARS-CoV-2 variant, and socioeconomic status.\n\nConclusionOur analyses provide evidence that suggest safety of the test-to-stay approach compared to traditional quarantine measures. This approach offers a promising option to avoid use of quarantine after exposure to respiratory pathogens in daycare settings.", - "rel_num_authors": 29, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.10.23296845", + "rel_abs": "This study investigated the impact of the COVID-19 pandemic on essential medicine availability in Kenyas health system. Key informant interviews were conducted, and the data were analyzed using NVIVO software. Six themes emerged, aligning with the WHO health system building blocks. These themes provided insights into the experiences, challenges, and opportunities regarding essential medicine availability during the pandemic. The initial response involved reallocating resources, affecting the procurement of essential medicines at national and county levels. To enhance preparedness, investments are crucial in strengthening financial systems and policies, improving supply chain resilience, and promoting local production through regulatory enhancements. These strategies aim to build resilient health systems and self-reliance, particularly for countries transitioning from donor aid. The findings underscore the importance of effective preparedness to ensure the availability of essential medicines during emergencies like the COVID-19 pandemic", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Felix Dewald", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" - }, - { - "author_name": "Gertrud Steger", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" - }, - { - "author_name": "Irina Fish", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" - }, - { - "author_name": "Ivonne Torre-Lage", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" - }, - { - "author_name": "Christina Hellriegel", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" - }, - { - "author_name": "Esther Milz", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" - }, - { - "author_name": "Anja Kolb-Bastigkeit", - "author_inst": "Youth Welfare Office of Cologne, Cologne, Germany" - }, - { - "author_name": "Eva Heger", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + "author_name": "Joseph Onyango", + "author_inst": "Strathmore University Strathmore Business School" }, { - "author_name": "Mira Fries", - "author_inst": "Health department of Cologne, Cologne, Germany" - }, - { - "author_name": "Michael Buess", - "author_inst": "Health department of Cologne, Cologne, Germany" - }, - { - "author_name": "Niklas Marizy", - "author_inst": "Health department of Cologne, Cologne, Germany" - }, - { - "author_name": "Barabara Michaelis", - "author_inst": "Health department of Cologne, Cologne, Germany" - }, - { - "author_name": "Isabelle Suarez", - "author_inst": "Department I of Internal Medicine, Division of Infectious Diseases, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany" - }, - { - "author_name": "Gibran Horemheb Rubio Quintanares", - "author_inst": "Virus security, Paul Ehrlich Institute, Langen, Germany" - }, - { - "author_name": "Martin Pirkl", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" - }, - { - "author_name": "Annette Aigner", - "author_inst": "Institute of Biometry and Clinical Epidemiology, Charite - Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet " - }, - { - "author_name": "Max Obserste-Frielinghaus", - "author_inst": "Institute of Medical Statistics and Computational Biology, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany" - }, - { - "author_name": "Martin Hellmich", - "author_inst": "Institute of Medical Statistics and Computational Biology, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany" - }, - { - "author_name": "Anabelle Wong", - "author_inst": "Institute of Public Health, Charite - Universitaetsmedizin Berlin, Berlin, Germany" - }, - { - "author_name": "Juan Camilo Orduz", - "author_inst": "juanitorduz@gmail.com, https://juanitorduz.github.io/" - }, - { - "author_name": "Gerd Faetkenheuer", - "author_inst": "Department I of Internal Medicine, Division of Infectious Diseases, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany" - }, - { - "author_name": "Joerg Doetsch", - "author_inst": "Department of Pediatrics, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany" - }, - { - "author_name": "Annelene Kossow", - "author_inst": "Health department of Cologne, Cologne, Germany" - }, - { - "author_name": "Eva-Maria Moench", - "author_inst": "MVZ Labor Dr. Quade & Kollegen GmbH, Cologne, Germany" - }, - { - "author_name": "Gustav Quade", - "author_inst": "MVZ Labor Dr. Quade & Kollegen GmbH, Cologne, Germany" - }, - { - "author_name": "Udo Neumann", - "author_inst": "Youth Welfare Office of Cologne, Cologne, Germany" - }, - { - "author_name": "Rolf Kaiser", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" - }, - { - "author_name": "Madlen Schranz", - "author_inst": "Charite-Universitaetsmedizin Berlin, corporate member of Freie Universitaet Berlin and Humboldt Universitaet zu Berlin, Institute of Public Health, Berlin, Germ" + "author_name": "Dosila Ogira", + "author_inst": "Strathmore University" }, { - "author_name": "Florian Klein", - "author_inst": "Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + "author_name": "Gilbert Kokwaro", + "author_inst": "Strathmore University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2023.10.10.23296849", @@ -45279,67 +45230,35 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2023.10.05.561047", - "rel_title": "Fourth dose of Microneedle Array Patch of SARS-CoV-2 S1 Protein Subunit Vaccine Elicits Robust Long-lasting Humoral Responses in mice", + "rel_doi": "10.1101/2023.10.05.23296592", + "rel_title": "A mixed method study to assess behavioral and social predictors of parent/caregivers intention to vaccinate their children against COVID-19 disease in an Indian state marked by significant health disparities.", "rel_date": "2023-10-05", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.05.561047", - "rel_abs": "The COVID-19 pandemic has underscored the pressing need for safe and effective booster vaccines, particularly in considering the emergence of new SARS-CoV-2 variants and addressing vaccine distribution inequalities. Dissolving microneedle array patches (MAP) offer a promising delivery method, enhancing immunogenicity and improving accessibility through the skins immune potential. In this study, we evaluated a microneedle array patch-based S1 subunit protein COVID-19 vaccine candidate, which comprised a bivalent formulation targeting the Wuhan and Beta variant alongside a monovalent Delta variant spike proteins in a murine model. Notably, the second boost of homologous bivalent MAP-S1(WU+Beta) induced a 15.7-fold increase in IgG endpoint titer, while the third boost of heterologous MAP-S1RS09Delta yielded a more modest 1.6-fold increase. Importantly, this study demonstrated that the administration of four doses of the MAP vaccine induced robust and long-lasting immune responses, persisting for at least 80 weeks. These immune responses encompassed various IgG isotypes and remained statistically significant for one year. Furthermore, neutralizing antibodies against multiple SARS-CoV-2 variants were generated, with comparable responses observed against the Omicron variant. Overall, these findings emphasize the potential of MAP-based vaccines as a promising strategy to combat the evolving landscape of COVID-19 and to deliver a safe and effective booster vaccine worldwide.", - "rel_num_authors": 12, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.10.05.23296592", + "rel_abs": "BackgroundParents/caregivers are the key decision-makers for childs health care including vaccination. Vaccine hesitancy along with lagging full immunization coverage for childhood vaccination in India, affect child health outcome and will affect covid-19 vaccine uptake in children. It is important to understand behavioral and social factors surrounding childhood COVID-19 vaccination to design appropriate interventions to improve uptake.\n\nMethodsA mixed-method approach combining quantitative and qualitative method was undertaken. A cross sectional survey of parents/caregivers of children aged less than 18 years residing in the state was carried out to find the prevalence and predictors of parent/ caregivers intention to vaccinate against COVID-19 disease. Semi-structured interviews were carried out to find facilitating and barrier factors for childhood COVID-19 vaccination.\n\nResultOut of 9904 study participants, 73.4% had intention to vaccinate. Parent/caregivers education and occupation, marital status, family type, family income, co-morbidity and previous COVID-19 infection in family, childhood vaccination under NIS, were found to be significantly associated. The likelihood of intention to vaccinate children against COVID-19 disease was greater among parents/caregivers aged 18-29 years (OR=2.631, 95% CI [1.733- 3.995], illiterate parents/caregivers (OR=3.037, 95% CI [2.319-3.977], prior COVID-19 infection in family (OR=1.595, 95% CI [1.432-1.821], and childrens prior vaccinations under NIS (OR=1.251, 95% CI [1.218-1.289]. In qualitative part, forty-five semi-structured interviews were conducted. The majority of intending parents gave vaccine effectiveness, increased immunity, high infection risk, herd immunity, and medical recommendations as reasons. Parents who refused mentioned inadequate data, adverse effects, beliefs, safety, and inconvenience as reasons. Effectiveness, and safety, long-term effects, and the short testing period were among the concerns of hesitant parents.\n\nConclusionIn order to promote COVID-19 vaccination among children, we need to address barriers, facilitators and behavioral determinants of parents/caregivers identified in this study and have targeted strategies for them.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Eun Kim", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Juyeop Shin", - "author_inst": "Raphas Co., Ltd." - }, - { - "author_name": "Alessandro Ferrari", - "author_inst": "IRCCS Policlinico San Matteo" - }, - { - "author_name": "Shaohua Huang", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Eunjin An", - "author_inst": "Raphas Co., Ltd." + "author_name": "Tulika Singh", + "author_inst": "Indira Gandhi Institute of Medical Sciences" }, { - "author_name": "Donghoon Han", - "author_inst": "Raphas Co., Ltd." - }, - { - "author_name": "Muhammad Sohaib Khan", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Thomas W. Kenniston", - "author_inst": "University of Pittsburgh" - }, - { - "author_name": "Irene Cassaniti", - "author_inst": "IRCCS Policlinico San Matteo" - }, - { - "author_name": "Fausto Baldanti", - "author_inst": "Molecular Virology Unit, Microbiology and Virology Department, Foundation IRCCS Polyclinic San Matteo, Pavia, Italy" + "author_name": "Sanjay Kumar", + "author_inst": "Indira Gandhi Institute of Medical Sciences" }, { - "author_name": "Dohyeon Jeong", - "author_inst": "Raphas Co., Ltd." + "author_name": "Setu Sinha", + "author_inst": "Indira Gandhi Institute of Medical Sciences" }, { - "author_name": "Andrea Gambotto", - "author_inst": "University of Pittsburgh" + "author_name": "Varsha Singh", + "author_inst": "Indira Gandhi Institute of Medical Sciences" } ], "version": "1", - "license": "cc_by_nc", - "type": "new results", - "category": "immunology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2023.10.04.23296554", @@ -47085,87 +47004,63 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.10.01.560365", - "rel_title": "Neutralisation of SARS-CoV-2 Omicron subvariants BA.2.86 and EG.5.1 by antibodies induced by earlier infection or vaccination", - "rel_date": "2023-10-02", + "rel_doi": "10.1101/2023.09.28.559927", + "rel_title": "Plasma of COVID-19 patients does not alter electrical resistance of human endothelial blood-brain barrier in vitro.", + "rel_date": "2023-09-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.10.01.560365", - "rel_abs": "Highly mutated SARS-CoV-2 Omicron subvariant BA.2.86 emerged in July 2023. We investigated the neutralisation of isolated virus by antibodies induced by earlier infection or vaccination. The neutralisation titres for BA.2.86 were comparable to those for XBB.1 and EG.5.1, by antibodies induced by XBB.1.5 or BA.4/5 breakthrough infection or BA.4/5 vaccination.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.28.559927", + "rel_abs": "The pandemic of Coronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) instigated the most serious global health crisis. Clinical presentation of COVID-19 frequently includes severe neurological and neuropsychiatric symptoms. However, it is presently unknown whether and to which extent pathological impairment of blood-brain barrier (BBB) contributes to the development of neuropathology during COVID-19 progression.\n\nIn the present study we used human induced pluripotent stem cells-derived brain endothelial cells (iBECs) to study the effects of blood plasma derived from COVID-19 patients on the BBB integrity in vitro. We also performed a comprehensive analysis of the cytokine and chemokine profiles in the plasma of COVID-19 patients, healthy and recovered individuals.\n\nWe found significantly increased levels of interferon {gamma}-induced protein 10 kDa (IP-10), hepatocyte growth factor (HGF), and interleukin-18 (IL-18) in the plasma of COVID-19 patients. However, blood plasma from COVID-19 patients did not affect transendothelial electrical resistance (TEER) in iBEC monolayers.\n\nOur results demonstrate that COVID-19-associated blood plasma inflammatory factors do not impair BBB integrity directly and suggest that pathological remodelling of BBB during COVID-19 may occur through indirect mechanisms.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Ria Lassauniere", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Agn\u0117 Poci\u016bt\u0117", + "author_inst": "State Research Institute Centre for Innovative Medicine" }, { - "author_name": "Charlotta Polacek", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Karolina Kriau\u010di\u016bnait\u0117", + "author_inst": "State Research Institute Centre for Innovative Medicine" }, { - "author_name": "Sharmin Baig", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Aida Kau\u0161yl\u0117", + "author_inst": "State Research Institute Centre for Innovative Medicine" }, { - "author_name": "Kirsten Ellegaard", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" - }, - { - "author_name": "Leandro Andre Escobar-Herrera", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" - }, - { - "author_name": "Anders Fomsgaard", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" - }, - { - "author_name": "Katja Spiess", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" - }, - { - "author_name": "Olivier Schwartz", - "author_inst": "Institut Pasteur, Paris, France" + "author_name": "Birut\u0117 Zablockien\u0117", + "author_inst": "Vilnius University; Vilnius University Hospital Santaros Klinikos" }, { - "author_name": "Delphine Planas", - "author_inst": "Institut Pasteur, Paris, France" - }, - { - "author_name": "Etienne Simon-Loriere", - "author_inst": "Institut Pasteur, Paris, France" + "author_name": "Tadas Al\u010dauskas", + "author_inst": "Vilnius University" }, { - "author_name": "Uffe Vest Schneider", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "August\u0117 Jelinskait\u0117", + "author_inst": "Vilnius University Hospital Santaros Klinikos" }, { - "author_name": "Raphael Niklaus Sieber", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Akvil\u0117 Rud\u0117nait\u0117", + "author_inst": "Vilnius University Hospital Santaros Klinikos" }, { - "author_name": "Marc Stegger", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Ligita Jan\u010diorien\u0117", + "author_inst": "Vilnius University; Vilnius University Hospital Santaros Klinikos" }, { - "author_name": "Tyra Grove Krause", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Saulius Ro\u010dka", + "author_inst": "Vilnius University; Vilnius University Hospital Santaros Klinikos" }, { - "author_name": "Henrik Ullum", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Alexei Verkhratsky", + "author_inst": "State Research Institute Centre for Innovative Medicine; The University of Manchester; IKERBASQUE, Basque Foundation for Science; School of Forensic Medicine, C" }, { - "author_name": "Pikka Jokelainen", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" - }, - { - "author_name": "Morten Rasmussen", - "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + "author_name": "Augustas Pivori\u016bnas", + "author_inst": "State Research Institute Centre for Innovative Medicine" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "new results", - "category": "immunology" + "category": "neuroscience" }, { "rel_doi": "10.1101/2023.09.27.23296254", @@ -48671,103 +48566,107 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.09.25.23289158", - "rel_title": "Recruitment, Consent and DNA Sample Acquisition in a U.S. Precision Health Cohort During the COVID-19 Pandemic", - "rel_date": "2023-09-27", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.25.23289158", - "rel_abs": "AimThe Yale Generations Project (YGP) is a precision health cohort initiative that began enrollment in New Haven Connecticut USA in July 2019. In March 2020, after nine months of operation, pandemic restrictions prompted abrupt changes to staff availability as well as changes to the projects recruitment, consenting, and sample acquisition. This manuscript describes the successful addition of remote recruitment, consenting, and DNA sampling to YGP workflows during the initial 27-months of pandemic restrictions ending June 30, 2022.\n\nMethodsThe initial YGP protocol established face-to-face workflow for recruiting, consenting and peripheral blood collection. A telemedicine consent protocol was initiated in April of 2020, and a remote saliva collection was established in October of 2020. De-identified data was extracted from YGP dataset and reported here.\n\nResultsAt the completion of YGPs initial 36 months (9-months pre-pandemic and 27-months pandemic) YGP enrolled N=4949 volunteers. There were N=1,950 (216.7 per month) volunteers consented pre-pandemic and N=2,999 (111.1 per month) during pandemic. The peak consenting month was February 2020 with N=428. DNA sample acquisition peaked in the pre-pandemic month of February 2020 with N=291 peripheral blood draws, and in the pandemic period the peak DNA acquisition month was November 2020 with N=176 (N=68 peripheral blood draws and N=108 saliva samples).\n\nConclusionThe YGP successfully transitioned from pre-pandemic recruiting, consenting and sample acquisition model that was exclusively face-to-face, to pandemic model that was predominantly remote. The added value of remote recruiting, consenting, and sampling has led to plans for an optimized hybrid model post-pandemic.", - "rel_num_authors": 21, + "rel_doi": "10.1101/2023.09.26.559506", + "rel_title": "Metabolic and mitochondria alterations induced by SARS-CoV-2 accessory proteins ORF3a, ORF9b, ORF9c and ORF10", + "rel_date": "2023-09-26", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.26.559506", + "rel_abs": "Antiviral signaling, immune response and cell metabolism in human body are dysregulated by SARS-CoV-2, the causative agent of the COVID-19. Here, we show that SARS-CoV-2 accessory proteins ORF3a, ORF9b, ORF9c and ORF10 induce a significant mitochondrial and metabolic reprogramming in A549 lung epithelial cells. While all four ORFs caused mitochondrial fragmentation and altered mitochondrial function, only ORF3a and ORF9c induced a marked structural alteration in mitochondrial cristae. ORF9b, ORF9c and ORF10 induced largely overlapping transcriptomes. In contrast, ORF3a induced a distinct transcriptome, including the downregulation of numerous genes for proteins with critical mitochondrial functions and morphology. Genome-Scale Metabolic Models predicted common and private metabolic flux reprogramming, notably a depressed amino acid metabolism, and an enhanced metabolism of specific lipids distinctly induced by ORF3a. These findings reveal metabolic dependencies and vulnerabilities prompted by SARS-CoV-2 accessory proteins that may be exploited to identify new targets for intervention.\n\nOne-Sentence SummaryMitochondria and metabolic alterations induced by SARS- CoV-2 accessory proteins ORF3a, ORF9b, ORF9c, ORF10 in pulmonary cells unravel new targets of intervention.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Allyson M. Derry", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Blanca D. Lopez-Ayllon", + "author_inst": "CIB-CSIC" }, { - "author_name": "Yvette Strong", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Silvia Marin", + "author_inst": "University of Barcelona (UB)" }, { - "author_name": "Davia Schioppo", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Marcos Farinas Fernandez", + "author_inst": "University of Barcelona (UB)" }, { - "author_name": "Joni Cotter", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Transito Garcia-Garcia", + "author_inst": "University of Cordoba" }, { - "author_name": "Geisa M. Wilkins", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Raul Fernandez-Rodriguez", + "author_inst": "University of Cordoba" }, { - "author_name": "Laura I. Siquieros", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Ana de Lucas-Rius", + "author_inst": "CIB-CSIC" }, { - "author_name": "Andrea Ouyang", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Natalia Redondo", + "author_inst": "University Hospital 12 de Octubre" }, { - "author_name": "Kathleen Hulseman", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Laura Mendoza-Garcia", + "author_inst": "CIB-CSIC" }, { - "author_name": "Joseph Petrosino", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Carles Foguet", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Jouzas Grigas", + "author_inst": "Lithuanian University of Health Sciences" }, { - "author_name": "Lorrin Liang", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Alba Calvet", + "author_inst": "University of Barcelona (UB)" }, { - "author_name": "Megan Stevenson", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Jose Manuel Villalba", + "author_inst": "University of Cordoba" }, { - "author_name": "Tiffany Elianne Aguilera", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Maria Josefa Rodriguez Gomez", + "author_inst": "Instituto de Salud Carlos III" }, { - "author_name": "Alexandria L. Soto", - "author_inst": "Department of Neurology, Yale School of Medicine" + "author_name": "Diego Megias", + "author_inst": "Instituto de Salud Carlos III" }, { - "author_name": "Katherin Meurer", - "author_inst": "Department of Neurology, Yale School of Medicine" + "author_name": "Biagio Mandracchia", + "author_inst": "Instituto de Salud Carlos III" }, { - "author_name": "Alison L. Herman", - "author_inst": "Department of Neurology, Yale School of Medicine" + "author_name": "Daniel Luque", + "author_inst": "Instituto de Salud Carlos III" }, { - "author_name": "Inessa Cohen", - "author_inst": "Department of Neurology, Yale School of Medicine" + "author_name": "Juan Jose Lozano", + "author_inst": "IBMB-CSIC" }, { - "author_name": "Guido J. Falcone", - "author_inst": "Department of Neurology, Yale School of Medicine" + "author_name": "Cristina Calvo", + "author_inst": "IBMB-CSIC" }, { - "author_name": "Erin E. Longbrake", - "author_inst": "Department of Neurology, Yale School of Medicine" + "author_name": "Timothy M. Thomson", + "author_inst": "IBMB-CSIC" }, { - "author_name": "Cassius I. Ochoa Chaar", - "author_inst": "Division of Vascular Surgery, Department of Surgery Yale School of Medicine" + "author_name": "Juan Jose Garrido", + "author_inst": "University of Cordoba" }, { - "author_name": "Kelly M. Anastasio", - "author_inst": "Yale Center for Clinical Investigation, Yale School of Medicine" + "author_name": "Marta Cascante", + "author_inst": "University of Barcelona" }, { - "author_name": "Michael F. Murray", - "author_inst": "Department of Genetics, Yale School of Medicine" + "author_name": "Maria Montoya", + "author_inst": "CIB-CSIC" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2023.09.26.559465", @@ -49761,7 +49660,7 @@ "rel_date": "2023-09-25", "rel_site": "medRxiv", "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.22.23295541", - "rel_abs": "Our understanding of the quality of cellular and humoral immunity conferred by COVID-19 vaccination alone versus vaccination plus SARS-CoV-2 breakthrough (BT) infection remains incomplete. While the current (2023) SARS-CoV-2 immune landscape of Canadians is complex, in late 2021 most Canadians had either just received a third dose of COVID-19 vaccine, or had received their two dose primary series and then experienced an Omicron BT. Herein we took advantage of this coincident timing to contrast cellular and humoral immunity conferred by three doses of vaccine versus two doses plus BT. Our results show that mild BT infection induces cell-mediated immune responses to variants comparable to an intramuscular vaccine booster dose. In contrast, BT subjects had higher salivary IgG and IgA levels against the Omicron Spike and enhanced reactivity to the ancestral Spike for the IgA isotype, which also reacted with SARS-CoV-1. Serum neutralizing antibody levels against the ancestral strain and the variants were also higher after BT infection. Our results support the need for mucosal vaccines to emulate the enhanced mucosal and humoral immunity induced by Omicron without exposing individuals to the risks associated with SARS-CoV-2 infection.\n\nONE SENTENCE SUMMARYOmicron breakthrough elicits cross-reactive systemic and mucosal immune responses in fully vaccinated adults.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC=\"FIGDIR/small/23295541v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@1f64cborg.highwire.dtl.DTLVardef@112693corg.highwire.dtl.DTLVardef@1bb14f4org.highwire.dtl.DTLVardef@15cc70a_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_abs": "Our understanding of the quality of cellular and humoral immunity conferred by COVID-19 vaccination alone versus vaccination plus SARS-CoV-2 breakthrough (BT) infection remains incomplete. While the current (2023) SARS-CoV-2 immune landscape of Canadians is complex, in late 2021 most Canadians had either just received a third dose of COVID-19 vaccine, or had received their two dose primary series and then experienced an Omicron BT. Herein we took advantage of this coincident timing to contrast cellular and humoral immunity conferred by three doses of vaccine versus two doses plus BT. Our results show that mild BT infection induces cell-mediated immune responses to variants comparable to an intramuscular vaccine booster dose. In contrast, BT subjects had higher salivary IgG and IgA levels against the Omicron Spike and enhanced reactivity to the ancestral Spike for the IgA isotype, which also reacted with SARS-CoV-1. Serum neutralizing antibody levels against the ancestral strain and the variants were also higher after BT infection. Our results support the need for mucosal vaccines to emulate the enhanced mucosal and humoral immunity induced by Omicron without exposing individuals to the risks associated with SARS-CoV-2 infection.\n\nONE SENTENCE SUMMARYOmicron breakthrough elicits cross-reactive systemic and mucosal immune responses in fully vaccinated adults.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=119 SRC=\"FIGDIR/small/23295541v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@163dce9org.highwire.dtl.DTLVardef@13c6896org.highwire.dtl.DTLVardef@f65fdforg.highwire.dtl.DTLVardef@11045a9_HPS_FORMAT_FIGEXP M_FIG C_FIG", "rel_num_authors": 22, "rel_authors": [ { @@ -50529,35 +50428,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.09.19.23295768", - "rel_title": "COVID-19 VACCINE ACCEPTANCE AND HESITANCY IN GHANA: A SYSTEMATIC REVIEW", + "rel_doi": "10.1101/2023.09.20.558551", + "rel_title": "COVID-19 ORF3a Viroporin Influenced Common and Unique Cellular Signalling Cascades in Lung, Heart and Brain Choroid Plexus Organoids with Additional Enriched MicroRNA Network Analyses for Lung and Brain Tissues", "rel_date": "2023-09-21", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.19.23295768", - "rel_abs": "The propensity to accept vaccines and factors that affect vaccine acceptance and hesitancy will determine the overall success of the COVID-19 vaccination program. Therefore, it is essential for countries to understand the factors that influence vaccine acceptance and hesitancy in order to prevent further future shocks, and it is necessary to have a thorough understanding of these factors. This study, as a result, aims to review selected published works in the domain of study and conduct valuable analysis to determine the most influential factors in COVID-19 vaccine acceptance and hesitancy in Ghana. The review also explored the acceptance rate of COVID-19 vaccines in Ghana. We selected published works from 2021 to April 2023 and extracted, analyzed, and summarized the findings based on the key factors that influence COVID-19 vaccine acceptance and hesitancy in Ghana, the acceptance rate in Ghana, the demographic factors that are often examined, and the study approach used to examine these factors. The study found that positive vaccination perception, safety, belief in vaccine efficacy, knowledge of COVID-19, and a good vaccine attitude influence COVID-19 vaccine acceptance in Ghana. The negative side effects of the vaccines, mistrust in the vaccine, lack of confidence in the safety of the vaccines, fear, and spiritual and religious beliefs all played significant roles in the factors influencing COVID-19 vaccine hesitancy. The demographic parameters frequently included in these studies that have a significant impact include educational attainment, gender, religious affiliation, age, and marital status.", - "rel_num_authors": 4, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.20.558551", + "rel_abs": "Tissue specific implications of SARS-CoV-2 encoded accessory proteins are not fully understood. SARS-CoV-2 infection can severely affect three major organs - the heart, lung, and brain. We analysed SARS-CoV-2 ORF3a interacting host proteins in these three major organs. Further we identified common and unique interacting host proteins, their targeting miRNAs (lung and brain), and delineated associated biological processes reanalysing RNA-seq data from the brain (COVID-19 infected/uninfected Choroid Plexus Organoids study), lung tissue from COVID-19 patients/healthy subjects, and cardiomyocyte cells based transcriptomics analyses. Our in silico studies showed ORF3a interacting proteins could vary depending upon tissues. Number of unique ORF3a interacting proteins in brain, lung and heart were 10, 7 and 1 respectively. Though common pathways influenced by SARS-CoV-2 infection were more, unique 21 brain and 7 heart pathways were found. One unique pathway for heart was negative regulation of calcium ion transport. Reported observations of COVID-19 patients with the history of hypertension taking calcium channel blockers (CCBs) or dihydorpyridine CCBs had elevated rate of intubation or increased rate of intubation/death respectively. Also likelihood of hospitalization of chronic CCB users with COVID-19 was more in comparison to long term Angiotensin Converting Enzyme inhibitors/Angiotensin Receptor Blockers users. Further studies are necessary to confirm this. miRNA analysis of ORF3a interacting proteins in brain and lung revealed, 2 of 37 brain miRNAs and 1 of 25 lung miRNAs with high degree and betweenness indicating their significance as hubs in the interaction network. Our study could help in identifying potential tissue specific COVID-19 drug/drug repurposing targets.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Godwin Banafo Akrong", - "author_inst": "University of Electronic Science and Technology of China School of Economics and Management" + "author_name": "Soura Chakraborty", + "author_inst": "School of Biotechnology, Jawaharlal Nehru University, New Mehrauli Road, New Delhi, India - 110067" }, { - "author_name": "Rosemond Akpene Hiadzi", - "author_inst": "University of Ghana College of Humanities" + "author_name": "Shrabonti Chatterjee", + "author_inst": "Integrated Science Education and Research Centre (ISERC), Institute of Science (Siksha Bhavana), Visva Bharati (A Central University), Santiniketan (PO), Birbhu" }, { - "author_name": "Antonia Bernadette Donkor", - "author_inst": "University of Ghana Balme Library" + "author_name": "Subhashree Mardi", + "author_inst": "Integrated Science Education and Research Centre (ISERC), Institute of Science (Siksha Bhavana), Visva Bharati (A Central University), Santiniketan (PO), Birbhu" }, { - "author_name": "Daniel Kwasi Anafo", - "author_inst": "University of Ghana" + "author_name": "Joydeep Mahata", + "author_inst": "Integrated Science Education and Research Centre (ISERC), Institute of Science (Siksha Bhavana), Visva Bharati (A Central University), Santiniketan (PO), Birbhu" + }, + { + "author_name": "Suneel Kateriya", + "author_inst": "School of Biotechnology, Jawaharlal Nehru University, New Mehrauli Road, New Delhi, India - 110067" + }, + { + "author_name": "Pradeep Punnakkal", + "author_inst": "Department of Biophysics, Postgraduate Institute of Medical Education & Research (PGIMER), Chandigarh, India - 160012" + }, + { + "author_name": "Gireesh Anirudhan", + "author_inst": "Integrated Science Education and Research Centre (ISERC), Institute of Science (Siksha Bhavana), Visva Bharati (A Central University), Santiniketan (PO), Birbhu" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nd", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2023.09.21.23295669", @@ -52299,43 +52210,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.09.12.23294140", - "rel_title": "Effectiveness of Canadian travel restrictions in reducing burden of SARS-CoV-2 variants of concern", + "rel_doi": "10.1101/2023.09.13.557622", + "rel_title": "Proximal immune-epithelial progenitor interactions drive chronic tissue sequelae post COVID-19", "rel_date": "2023-09-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.12.23294140", - "rel_abs": "Evaluating travel restriction effectiveness in mitigating infectious disease burden is critical for informing public health policy. Here, we quantify where and when variants of SARS-CoV-2 were introduced into Canada to evaluate the extent to which travel restrictions averted viral introductions and COVID-19 case burden. Our results suggest that, across SARS-CoV-2 variants of concern subject to travel restrictions, at least 281 introductions were prevented, accounting for an averted burden of approximately 44,064 cases. This corresponds to approximately 441 averted hospitalizations, 24 averted deaths, and cost savings to Canadian health care systems of approximately 11.2 million Canadian dollars. Travel restrictions were found to be most effective when implemented rapidly during exponential case growth in the focal source and when global circulation was limited. Our analyses reveal that COVID-19 travel restrictions mitigated case burdens and highlight their value in future pandemic response.\n\nSummaryCOVID-19 travel restrictions against variants worked and were most effective when implemented rapidly and preceding new variants wider circulation.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.13.557622", + "rel_abs": "The long-term physiological consequences of SARS-CoV-2, termed Post-Acute Sequelae of COVID-19 (PASC), are rapidly evolving into a major public health concern. The underlying cellular and molecular etiology remain poorly defined but growing evidence links PASC to abnormal immune responses and/or poor organ recovery post-infection. Yet, the precise mechanisms driving non-resolving inflammation and impaired tissue repair in the context of PASC remain unclear. With insights from three independent clinical cohorts of PASC patients with abnormal lung function and/or viral infection-mediated pulmonary fibrosis, we established a clinically relevant mouse model of post-viral lung sequelae to investigate the pathophysiology of respiratory PASC. By employing a combination of spatial transcriptomics and imaging, we identified dysregulated proximal interactions between immune cells and epithelial progenitors unique to the fibroproliferation in respiratory PASC but not acute COVID-19 or idiopathic pulmonary fibrosis (IPF). Specifically, we found a central role for lung-resident CD8+ T cell-macrophage interactions in maintaining Krt8hi transitional and ectopic Krt5+ basal cell progenitors, thus impairing alveolar regeneration and driving fibrotic sequelae after acute viral pneumonia. Mechanistically, CD8+ T cell derived IFN-{gamma} and TNF stimulated lung macrophages to chronically release IL-1{beta}, resulting in the abnormal accumulation of dysplastic epithelial progenitors and fibrosis. Notably, therapeutic neutralization of IFN-{gamma} and TNF, or IL-1{beta} after the resolution of acute infection resulted in markedly improved alveolar regeneration and restoration of pulmonary function. Together, our findings implicate a dysregulated immune-epithelial progenitor niche in driving respiratory PASC. Moreover, in contrast to other approaches requiring early intervention, we highlight therapeutic strategies to rescue fibrotic disease in the aftermath of respiratory viral infections, addressing the current unmet need in the clinical management of PASC and post-viral disease.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Angela McLaughlin", - "author_inst": "Bioinformatics, University of British Columbia; British Columbia Centre for Excellence in HIV/AIDS" + "author_name": "Harish Narasimhan", + "author_inst": "University of Virginia" }, { - "author_name": "Vincent Montoya", - "author_inst": "British Columbia Centre for Excellence in HIV/AIDS" + "author_name": "In Su Cheon", + "author_inst": "University of Virginia" }, { - "author_name": "Rachel L Miller", - "author_inst": "British Columbia Centre for Excellence in HIV/AIDS" + "author_name": "Wei Qian", + "author_inst": "University of Virginia" }, { - "author_name": "- Canadian COVID-19 Genomics Network (CanCOGeN) Consortium", - "author_inst": "-" + "author_name": "Sheng'en Hu", + "author_inst": "University of Virginia" }, { - "author_name": "Michael Worobey", - "author_inst": "Department of Ecology and Evolutionary Biology, University of Arizona" + "author_name": "Tanyalak Parimon", + "author_inst": "Cedars Sinai" }, { - "author_name": "Jeffrey B Joy", - "author_inst": "Department of Medicine, University of British Columbia; British Columbia Centre for Excellence in HIV/AIDS" + "author_name": "Chongzhi Zang", + "author_inst": "University of Virginia" + }, + { + "author_name": "Peter Chen", + "author_inst": "Cedars Sinai" + }, + { + "author_name": "Jie Sun", + "author_inst": "University of Virginia" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2023.09.13.557637", @@ -53741,119 +53660,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.09.12.23295384", - "rel_title": "Determinants of de novo B cell responses to drifted epitopes in post-vaccination SARS-CoV-2 infections", + "rel_doi": "10.1101/2023.09.11.23295394", + "rel_title": "Sexual Gender-Based Violence among Adolescent Girls and Young Women during COVID-19 Pandemic, Mid-Eastern Uganda", "rel_date": "2023-09-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.12.23295384", - "rel_abs": "Vaccine-induced immunity may impact subsequent de novo responses to drifted epitopes in SARS-CoV-2 variants, but this has been difficult to quantify due to the challenges in recruiting unvaccinated control groups whose first exposure to SARS-CoV-2 is a primary infection. Through local, statewide, and national SARS-CoV-2 testing programs, we were able to recruit cohorts of individuals who had recovered from either primary or post-vaccination infections by either the Delta or Omicron BA.1 variants. Regardless of variant, we observed greater Spike-specific and neutralizing antibody responses in post-vaccination infections than in those who were infected without prior vaccination. Through analysis of variant-specific memory B cells as markers of de novo responses, we observed that Delta and Omicron BA.1 infections led to a marked shift in immunodominance in which some drifted epitopes elicited minimal responses, even in primary infections. Prior immunity through vaccination had a small negative impact on these de novo responses, but this did not correlate with cross-reactive memory B cells, arguing against competitive inhibition of naive B cells. We conclude that dampened de novo B cell responses against drifted epitopes are mostly a function of altered immunodominance hierarchies that are apparent even in primary infections, with a more modest contribution from pre-existing immunity, perhaps due to accelerated antigen clearance.", - "rel_num_authors": 25, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.11.23295394", + "rel_abs": "BackgroundGlobal studies indicate that sexual gender based violence (SGBV) may increase during pandemics including the COVID-19. The Mid-Eastern region in Uganda was of a concern due to high prevalence of intimate partner sexual violence among adolescent girls and young women (AGYW) (13% in 2016). Due to limited data, we investigated factors associated with SGBV among AGYW during the COVID-19 pandemic in Eastern Uganda, April 2022.\n\nMethodsWe line listed all AGYW 10-24 years who obtained SGBV services at ten high-volume health facilities from March 2020 to December 2021, the main COVID-19 period in Uganda. We conducted a case-control study among these AGYW. A case was [≥]1 SGBV episode experienced by an AGYW aged 10-24 years residing in Tororo and Busia Districts. For every randomly-selected case from the health facility line list, we identified two neighbourhood-matched AGYW controls who reported no SGBV. We interviewed 108 and 216 controls on socio-demographics, socio-economics, and SGBV experiences during COVID-19. We conducted logistic regression to obtain adjusted odds ratios and confidence intervals.\n\nResultsAmong 389 SGBV cases, the mean age was 16.4 (SD{+/-} 1.6: range 10-24) years, and 350 (90%) were 15-19 years. Among 108 cases interviewed, 79 (73%) reported forced sex. Most (73; 68%) knew the perpetrator. In multivariate analysis, self-reported SGBV before the COVID-19 period [aOR=5.8, 95%CI: 2.8-12] and having older siblings [aOR=1.9, 95%:CI 1.1-3.4] were associated with SGBV during the period. Living with a family that provided all the basic needs was protective [aOR=0.42, 95%: CI 0.23-0.78].\n\nConclusionPrevious SGBV experiences and family dynamics, such as having older siblings, increased the odds of SGBV during the COVID-19 pandemic in Uganda. Conversely, a supportive family environment was protective. Identifying, supporting, and enacting protective interventions for existing SGBV victims and socioeconomically vulnerable AGYW could reduce the burden of SGBV during similar events.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Grace Quirk", - "author_inst": "University of Arizona" - }, - { - "author_name": "Marta V Schoenle", - "author_inst": "University of Arizona" - }, - { - "author_name": "Kameron L Peyton", - "author_inst": "University of Arizona" - }, - { - "author_name": "Jennifer L Uhrlaub", - "author_inst": "University of Arizona" - }, - { - "author_name": "Branden Lau", - "author_inst": "University of Arizona" - }, - { - "author_name": "Jeffrey Burgess", - "author_inst": "University of Arizona" - }, - { - "author_name": "Katherine Ellingson", - "author_inst": "University of Arizona" - }, - { - "author_name": "Shawn Beitel", - "author_inst": "University of Arizona" - }, - { - "author_name": "James Romine", - "author_inst": "University of Arizona" - }, - { - "author_name": "Karen Lutrick", - "author_inst": "University of Arizona" - }, - { - "author_name": "Ashley Fowlkes", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Amadea Britton", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Harmony Tyner", - "author_inst": "St. Luke's Regional Health Care System" - }, - { - "author_name": "Alberto Caban-Martinez", - "author_inst": "University of Miami, Miller School of Medicine" + "author_name": "Patience Mwine", + "author_inst": "MOH: Republic of Uganda Ministry of Health" }, { - "author_name": "Allison Naleway", - "author_inst": "Kaiser Permanente Northwest Center for Health Research" - }, - { - "author_name": "Manjusha Gaglani", - "author_inst": "Baylor Scott & White Health and Texas A and M University College of Medicine" - }, - { - "author_name": "Sarang Yoon", - "author_inst": "University of Utah" - }, - { - "author_name": "Laura Edwards", - "author_inst": "Abt Associates" + "author_name": "Benon Kwesiga", + "author_inst": "National Institute of Public Health" }, { - "author_name": "Lauren Olsho", - "author_inst": "Abt Associates" + "author_name": "Richard Migisha", + "author_inst": "National Institute of Public Health" }, { - "author_name": "Michael D Dake", - "author_inst": "University of Arizona" + "author_name": "Juliet Cheptoris", + "author_inst": "Republic of Uganda Ministry of Health" }, { - "author_name": "Bonnie LaFleur", - "author_inst": "University of Arizona" + "author_name": "Daniel Kadobera", + "author_inst": "National Institute of Public Health" }, { - "author_name": "Janko Z Nikolich", - "author_inst": "University of Arizona" + "author_name": "Lilian Bulage", + "author_inst": "National Institute of Public Health" }, { - "author_name": "Ryan Sprissler", - "author_inst": "University of Arizona" + "author_name": "Edirisa J. Nsubuga", + "author_inst": "National Institute of Public Health" }, { - "author_name": "Michael Worobey", - "author_inst": "University of Arizona" + "author_name": "Peter Mudiope", + "author_inst": "MOH: Republic of Uganda Ministry of Health" }, { - "author_name": "Deepta Bhattacharya", - "author_inst": "University of Arizona" + "author_name": "Alex R. Ario", + "author_inst": "National Institute of Public Health" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "sexual and reproductive health" }, { "rel_doi": "10.1101/2023.09.09.23295208", @@ -55859,51 +55714,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.09.08.23295177", - "rel_title": "Systematical assessment of the impact of single spike mutations of SARS-CoV-2 Omicron sub-variants on the neutralization capacity of post-vaccination sera", + "rel_doi": "10.1101/2023.09.07.23295183", + "rel_title": "Comparison of Different PCR Methods for the Detection of SARS-CoV-2 RNA in Wastewater Based on the Reported Incidence of COVID-19 in Finland", "rel_date": "2023-09-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.08.23295177", - "rel_abs": "The evolution of novel SARS-CoV-2 variants significantly affects vaccine effectiveness. While these effects can only be studied retrospectively, neutralizing antibody titers are most used as correlates of protection. However, studies assessing neutralizing antibody titers often show heterogeneous data. To address this, we investigated assay variance and identified virus infection time and dose as factors affecting assay robustness. We next measured neutralization against Omicron sub-variants in cohorts with hybrid or vaccine induced immunity, identifying a gradient of immune escape potential. To evaluate the effect of individual mutations on this immune escape potential of Omicron variants, we systematically assessed the effect of each individual mutation specific to Omicron BA.1, BA.2, BA.2.12.1, and BA.4/5. We cloned a library of pseudo-viruses expressing spikes with single point mutations, and subjected it to pooled sera from vaccinated hosts, thereby identifying multiple mutations that independently affect neutralization potency. These data might help to predict antigenic features of novel viral variants carrying these mutations and support the development of broad monoclonal antibodies.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.07.23295183", + "rel_abs": "The spatial and temporal changes of the COVID-19 pandemic have been monitored with wastewater-based surveillance, which many countries have applied to their national public health monitoring measures. The most commonly used methods for the detection of SARS-CoV-2 in wastewater are RT-qPCR and RT-ddPCR. Previous comparisons of the two methods have produced conflicting results; some found RT-ddPCR to be more sensitive, one found RT-qPCR to be more sensitive, and others found them to be equal in sensitivity. This research was conducted to further study these two methods as well as two different RNA extraction methodologies and gene assays for the detection of SARS-CoV-2 in wastewater. We compared two RT-qPCR kits and RT-ddPCR based on sensitivity, variability, and the correlation of SARS-CoV-2 gene copy numbers in wastewater with the incidence of COVID-19. Our results indicate that the most sensitive and low-variance method to detect SARS-CoV-2 in wastewater was RT-ddPCR. However, we obtained the best correlation between COVID-19 incidence and SARS-CoV-2 gene copy number in wastewater using RT-qPCR (CC = 0.697, p < 0.001). We found a significant difference in sensitivity between the two RT-qPCR kits, one having a significantly lower limit of detection and a higher percentage of positive samples than the other. Furthermore, the CDC N1 primers and probe were the most sensitive for both RT-qPCR kits, while there was no significant difference between the tested gene targets using RT-ddPCR. For the most sensitive RT-qPCR, the use of different RNA extraction kits affected the result. All methods showed a trend between COVID-19 incidence and SARS-CoV-2 gene copy numbers in wastewater. In addition, we tested an isothermal amplification method for the detection of SARS-CoV-2 RNA in wastewater. It proved to be a viable option if results are expected quickly, resources are limited, and presence-absence information is sufficient.\n\nHighlightsO_LIUsing different RNA extraction kits, detection kits, and gene assays to detect SARS-CoV-2 in wastewater produces differing results.\nC_LIO_LISARS-CoV-2 gene copies in wastewater correlate with the reported incidence of COVID-19 in Finland.\nC_LIO_LIRT-ddPCR was the most sensitive and repeatable method to detect SARS-CoV-2 in wastewater, whereas RT-qPCR had the best correlation to the incidence of COVID-19.\nC_LIO_LIRT-SIBA is a viable option for the detection of SARS-CoV-2 in wastewater in low-resource settings.\nC_LIO_LIAll methods have high result variability when the amount of SARS-CoV-2 in wastewater is low.\nC_LI\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC=\"FIGDIR/small/23295183v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (23K):\norg.highwire.dtl.DTLVardef@11e89a2org.highwire.dtl.DTLVardef@1dded4eorg.highwire.dtl.DTLVardef@106a81forg.highwire.dtl.DTLVardef@7c21e_HPS_FORMAT_FIGEXP M_FIG Created with BioRender.com\n\nC_FIG", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Maeva Katzmarzyk", - "author_inst": "Department of Viral Immunology; Helmholtz Centre for Infection Research; Braunschweig, 38124, Germany" + "author_name": "Annika Ingrid L\u00e4nsivaara", + "author_inst": "Tampere University" }, { - "author_name": "Denise Christine Clesle", - "author_inst": "Department of Viral Immunology; Helmholtz Centre for Infection Research; Braunschweig, 38124, Germany" + "author_name": "Kirsi-Maarit Lehto", + "author_inst": "Tampere University" }, { - "author_name": "Joop van den Heuvel", - "author_inst": "Department of Recombinant Protein Expression; Helmholtz Centre for Infection Research; Braunschweig, 38124; Germany" + "author_name": "Rafiqul Hyder", + "author_inst": "Tampere University" }, { - "author_name": "Markus Hoffmann", - "author_inst": "Deutsches Primatenzentrum GmbH - Leibniz-Institut fur Primatenforschung" + "author_name": "Erja Janhonen", + "author_inst": "Tampere University" }, { - "author_name": "Henk Garritsen", - "author_inst": "Institute for Clinical Transfusion Medicine, Klinikum Braunschweig GmbH, Braunschweig, 38114 Germany and Fraunhofer Institute for Surface Engineering and Thin F" + "author_name": "Anssi Lipponen", + "author_inst": "Finnish Institute for Health and Welfare" }, { - "author_name": "Stefan Poehlmann", - "author_inst": "Deutsches Primatenzentrum GmbH - Leibniz-Institut fur Primatenforschung" + "author_name": "Annamari Heikinheimo", + "author_inst": "University of Helsinki" }, { - "author_name": "Henning Jacobsen", - "author_inst": "Department of Viral Immunology; Helmholtz Centre for Infection Research; Braunschweig, 38124, Germany" + "author_name": "Tarja Pitk\u00e4nen", + "author_inst": "Finnish Institute for Health and Welfare" }, { - "author_name": "Luka Cicin-Sain", - "author_inst": "Department of Viral Immunology; Helmholtz Centre for Infection Research; Braunschweig, 38124, Germany" + "author_name": "Sami Oikarinen", + "author_inst": "Tampere University" + }, + { + "author_name": "- WastPan study group", + "author_inst": "" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.09.06.23294426", @@ -57633,67 +57492,35 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.09.02.556038", - "rel_title": "Neutralization of SARS-CoV-2 EG.5/EG.5.1 by sera from ZF2001 RBD-dimer and its next-generation vaccines", + "rel_doi": "10.1101/2023.09.03.23295001", + "rel_title": "COVID-19 vaccines and autoimmune disorders: A scoping review protocol", "rel_date": "2023-09-04", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.09.02.556038", - "rel_abs": "SARS-CoV-2 Omicron EG.5 and EG.5.1 are surging in several areas of the world, including China. Compared with XBB.1, EG.5 contains additional mutations of F456L and S486P in the spike protein receptor binding domain (RBD) and its subvariant EG.5.1 carries a further spike mutation Q52H. The immune escape potential of EG.5/EG.5.1 is of great concern. In this study, we evaluated the neutralization activities of sera from participants who received COVID-19 inactivated vaccines, protein subunit vaccine ZF2001 or a booster vaccination of Delta-BA.5 RBD-heterodimer protein vaccine, and participants who had a breakthrough infection during a wave of BF.7/BA.5.2 circulation in December 2022. Neutralization profiles elicited by bivalent RBD-heterodimer vaccine candidates containing XBB.1.5 antigen were evaluated in a murine model. We found that EG.5 and EG.5.1 displayed similar immune evasion potential to XBB.1 and XBB.1.5. The Delta-BA.5 RBD-heterodimer booster induced higher neutralizing titers against the tested XBB subvariants, including EG.5 and EG.5.1, than breakthrough infection by BF.7 or BA.5.2. In addition, Delta-XBB.1.5 and BQ.1.1-XBB.1.5 RBD-heterodimer vaccines induced high neutralizing activities against XBB sub-variants in a murine model, suggesting that next-generation COVID-19 vaccines with updated components must be developed to enhance the protection efficacy against the circulating SARS-CoV-2 strains.", - "rel_num_authors": 12, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.09.03.23295001", + "rel_abs": "BackgroundTwo years into the global vaccination program, important questions about the association between COVID-19 vaccines and autoimmune diseases have arisen. A growing number of reports have documented associations between COVID-19 vaccination and autoimmunity, suggesting, for example, a causal link between vaccination and new-onset and/or relapsing autoimmune disorders such as type 1 diabetes mellitus, rheumatoid arthritis, multiple sclerosis, systemic lupus erythematosus, Graves disease, and Hashimotos thyroiditis. These autoimmune phenomena have occurred with various COVID-19 vaccines and research is required to elucidate the underlying mechanisms and causal directions, for example, whether persons with no history of autoimmune disorders may experience them upon vaccination or persons with autoimmune disorders may experience exacerbation or new adverse events post-vaccination.\n\nMethods and analysisSpecific objectives of this scoping review will address the following questions: Can COVID-19 vaccination trigger and/or exacerbate autoimmune disorders? Are persons with autoimmune disorders at higher risk of experiencing additional autoimmune disorders? What are the mechanisms connecting autoimmune disorders with COVID-19 vaccination? Can COVID-19 vaccination interact with immunosuppressive therapy in persons with autoimmune disorders? Does the risk of autoimmune disorders following COVID-19 vaccination differ by vaccine type, age, gender, or other still unidentified characteristics (e.g., SES)? What is the consensus of care concerning COVID-19 vaccination in persons with autoimmune disorders and what evidence informs it? Our review will follow Arksey and OMalleys (2005) framework, enhanced by Levac et al.s team-based approach (2010), and adhering to the recommendations of the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist. To capture the broadest range of perspectives on the phenomenon of interest, data will be synthesized through numerical summaries describing general characteristics of included studies and thematic analysis. Subgroup analysis of primary outcomes will be performed to compare findings according to 1) the previous existence of autoimmune disorder, 2) the presence of relevant co-morbidities, 3) vaccine type; and other relevant factors that we may encounter as the research proceeds.\n\nSignificanceCOVID-19 has triggered the largest vaccination campaign in history, targeting literally the global human community. Drug safety is a crucial aspect of any medical intervention, critical to a proper assessment of the balance of risks and benefits. Our investigation should yield information useful to improve medical and public health practice in multiple ways, including assisting in clinical decision-making, policy development, and ethical medical practice.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Yaling An", - "author_inst": "Savaid Medical School, University of Chinese Academy of Sciences" - }, - { - "author_name": "Xuemei Zhou", - "author_inst": "School of Life Sciences, Hebei University" - }, - { - "author_name": "Lifeng Tao", - "author_inst": "Anhui Zhifei Longcom Biopharmaceutical Co. Ltd" - }, - { - "author_name": "Haitang Xie", - "author_inst": "Yijishan Hospital of Wannan Medical College" - }, - { - "author_name": "Chenxi Yang", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" - }, - { - "author_name": "Dedong Li", - "author_inst": "College of Veterinary Medicine, China Agricultural University" - }, - { - "author_name": "Ruyue Wang", - "author_inst": "Anhui Zhifei Longcom Biopharmaceutical Co. Ltd" - }, - { - "author_name": "Hua Hu", - "author_inst": "Yijishan Hospital of Wannan Medical College" - }, - { - "author_name": "Kefang Liu", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" + "author_name": "Claudia Chaufan", + "author_inst": "York University" }, { - "author_name": "Lianpan Dai", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" + "author_name": "Laurie Manwell", + "author_inst": "Wilfred Laurier University" }, { - "author_name": "Kun Xu", - "author_inst": "Beijing Institutes of Life Science, Chinese Academy of Sciences" + "author_name": "Camila Heredia", + "author_inst": "York University" }, { - "author_name": "George F. Gao", - "author_inst": "Institute of Microbiology Chinese Academy of Sciences" + "author_name": "Jennifer McDonald", + "author_inst": "University of Central Lancashire Medical School" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "immunology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2023.09.03.23294865", @@ -59359,115 +59186,211 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.08.29.23293790", - "rel_title": "Outpatient treatment with concomitant vaccine-boosted convalescent plasma for patients with immunosuppression and COVID-19", + "rel_doi": "10.1101/2023.08.28.23294715", + "rel_title": "How much should we sequence? An analysis of the Swiss SARS- CoV-2 surveillance effort", "rel_date": "2023-08-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.29.23293790", - "rel_abs": "Although severe coronavirus disease 2019 (COVID-19) and hospitalization associated with COVID-19 are generally preventable among healthy vaccine recipients, patients with immunosuppression have poor immunogenic responses to COVID-19 vaccines and remain at high risk of infection with SARS-CoV-2 and hospitalization. Additionally, monoclonal antibody therapy is limited by the emergence of novel SARS-CoV-2 variants that have serially escaped neutralization. In this context, there is interest in understanding the clinical benefit associated with COVID-19 convalescent plasma collected from persons who have been both naturally infected with SARS-CoV-2 and vaccinated against SARS-CoV-2 (\"vax-plasma\"). Thus, we report the clinical outcome of 386 immunocompromised outpatients who were diagnosed with COVID-19 and who received contemporary COVID-19 specific therapeutics (standard of care group) and a subgroup who also received concomitant treatment with very high titer COVID-19 convalescent plasma (vax-plasma group) with a specific focus on hospitalization rates. The overall hospitalization rate was 2.2% (5 of 225 patients) in the vax-plasma group and 6.2% (10 of 161 patients) in the standard of care group, which corresponded to a relative risk reduction of 65% (P=0.046). Evidence of efficacy in nonvaccinated patients cannot be inferred from these data because 94% (361 of 386 patients) of patients were vaccinated. In vaccinated patients with immunosuppression and COVID-19, the addition of vax-plasma or very high titer COVID-19 convalescent plasma to COVID-19 specific therapies reduced the risk of disease progression leading to hospitalization.\n\nIMPORTANCEAs SARS-CoV-2 evolves, new variants of concern (VOCs) have emerged which evade available anti-spike monoclonal antibodies, particularly among immunosuppressed patients. However, high-titer COVID-19 convalescent plasma continues to be effective against VOCs because of its broad-spectrum immunomodulatory properties. Thus, we report clinical outcomes of 386 immunocompromised outpatients who were treated with COVID-19 specific therapeutics and a subgroup also treated with vaccine-boosted convalescent plasma. We found that administration of vaccine-boosted convalescent plasma was associated with a significantly decreased incidence of hospitalization among immunocompromised COVID-19 outpatients. Our data add to the contemporary data providing evidence to support the clinical utility of high-titer convalescent plasma as antibody replacement therapy in immunocompromised patients.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.28.23294715", + "rel_abs": "BackgroundDuring the SARS-CoV-2 pandemic, many countries directed substantial resources towards genomic surveillance to detect and track viral variants. There is a debate over how much sequencing effort is necessary in national surveillance programs for SARS-CoV-2 and future pandemic threats.\n\nAimWe aimed to investigate the effect of reduced sequencing on surveillance outcomes in a large genomic dataset from Switzerland, comprising more than 143k sequences.\n\nMethodsWe employed a uniform downsampling strategy using 100 iterations each to investigate the effects of fewer available sequences on the surveillance outcomes: (i) first detection of variants of concern (VOCs), (ii) speed of introduction of VOCs, (iii) diversity of lineages, (iv) first cluster detection of VOCs, (v) density of active clusters, and (vi) geographic spread of clusters.\n\nResultsThe impact of downsampling on VOC detection is disparate for the three VOC lineages, but many outcomes including introduction and cluster detection could be recapitulated even with only 35% of the original sequencing effort. The effect on the observed speed of introduction and first detection of clusters was more sensitive to reduced sequencing effort for some VOCs, in particular Omicron and Delta, respectively.\n\nConclusionA genomic surveillance program needs a balance between societal benefits and costs. While the overall national dynamics of the pandemic could be recapitulated by a reduced sequencing effort, the effect is strongly lineage dependent - something that is unknown at the time of sequencing - and comes at the cost of accuracy, in particular for tracking the emergence of potential VOCs.", + "rel_num_authors": 48, "rel_authors": [ { - "author_name": "Juan Ripoll Sanz", - "author_inst": "Mayo Clinic" + "author_name": "Fanny Wegner", + "author_inst": "Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland" }, { - "author_name": "Sidna Tulledge-Scheitel", - "author_inst": "Mayo Clinic" + "author_name": "Blanca Cabrera Gil", + "author_inst": "SIB Swiss Institute of Bioinformatics, Geneva, Switzerland" }, { - "author_name": "Anthony A Stephenson", - "author_inst": "Mayo Clinic" + "author_name": "Tanguy Araud", + "author_inst": "Genesupport, Geneva, Switzerland" }, { - "author_name": "Shane Ford", - "author_inst": "Mayo Clinic" + "author_name": "Christiane Beckmann", + "author_inst": "Viollier AG, Allschwil, Switzerland" }, { - "author_name": "Marsha Pike", - "author_inst": "Mayo Clinic" + "author_name": "Niko Beerenwinkel", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland & SIB Swiss Institute of Bioinformatics" }, { - "author_name": "Ellen K Gorman", - "author_inst": "Mayo Clinic" + "author_name": "Claire Bertelli", + "author_inst": "Clinical Microbiology, University Hospital Lausanne, Lausanne, Switzerland" }, { - "author_name": "Sara N Hanson", - "author_inst": "Mayo Clinic" + "author_name": "Matteo Carrara", + "author_inst": "NEXUS Personalized Health Technologies, ETH Zurich, Basel, Switzerland & SIB Swiss Institute of Bioinformatics" }, { - "author_name": "Justin E Juskewitch", - "author_inst": "Mayo Clinic" + "author_name": "Lorenzo Cerutti", + "author_inst": "Health2030 Genome Center, Geneva, Switzerland" }, { - "author_name": "Alex J Miller", - "author_inst": "Mayo Clinic" + "author_name": "Chaoran Chen", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland & SIB Swiss Institute of Bioinformatics" }, { - "author_name": "Solomiia Zaremba", - "author_inst": "Mayo Clinic" + "author_name": "Samuel Cordey", + "author_inst": "Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland" }, { - "author_name": "Erik A Ovrom", - "author_inst": "Mayo Clinic" + "author_name": "Alexis Dumoulin", + "author_inst": "Valais Hospital, Central Institute, Sion, Switzerland" }, { - "author_name": "Raymund R Razonable", - "author_inst": "Mayo Clinic" + "author_name": "Louis Du Plessis", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland & SIB Swiss Institute of Bioinformatics" }, { - "author_name": "Ravindra Ganesh", - "author_inst": "Mayo Clinic" + "author_name": "Marc Friedli", + "author_inst": "Health2030 Genome Center, Geneva, Switzerland" }, { - "author_name": "Ryan T Hurt", - "author_inst": "Mayo Clinic" + "author_name": "Yannick Gerth", + "author_inst": "Zentrum fuer Labormedizin St. Gall, St. Gall, Switzerland" }, { - "author_name": "Erin N Fischer", - "author_inst": "Mayo Clinic" + "author_name": "Gilbert Greub", + "author_inst": "Clinical Microbiology, University Hospital Lausanne, Lausanne, Switzerland" }, { - "author_name": "Amber N Derr", - "author_inst": "Mayo Clinic" + "author_name": "Adrian Haerri", + "author_inst": "Biolytix, Witterswil, Switzerland" }, { - "author_name": "Michelle R Eberle", - "author_inst": "Mayo Clinic" + "author_name": "Hans Hirsch", + "author_inst": "Clinical Virology, University Hospital Basel, Basel, Switzerland" }, { - "author_name": "Jennifer J Larsen", - "author_inst": "Mayo Clinic" + "author_name": "Cedric Howald", + "author_inst": "Health2030 Genome Center, Geneva, Switzerland" }, { - "author_name": "Christina M Carney", - "author_inst": "Mayo Clinic" + "author_name": "Michael Huber", + "author_inst": "Institute of Medical Virology, University of Zurich, Zurich, Switzerland" }, { - "author_name": "Elitza S Theel", - "author_inst": "Mayo Clinic" + "author_name": "Alexander Imhof", + "author_inst": "Spitalregion Oberaargau, Langenthal, Switzerland" }, { - "author_name": "Sameer A Parikh", - "author_inst": "Mayo Clinic" + "author_name": "Laurent Kaiser", + "author_inst": "Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland" }, { - "author_name": "Neil E Kay", - "author_inst": "Mayo Clinic" + "author_name": "Verena Kufner", + "author_inst": "Institute of Medical Virology, University of Zurich, Zurich, Switzerland" }, { - "author_name": "Michael J Joyner", - "author_inst": "Mayo Clinic" + "author_name": "Stephen Leib", + "author_inst": "Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland" }, { - "author_name": "Jonathon Senefeld", - "author_inst": "Mayo Clinic" + "author_name": "Karoline Leuzinger", + "author_inst": "Clinical Virology, University Hospital Basel, Basel, Switzerland" + }, + { + "author_name": "Etleva Lleshi", + "author_inst": "Synlab, Microbiology Department, Bioggio, Switzerland" + }, + { + "author_name": "Gladys Martinetti Lucchini", + "author_inst": "Department of Laboratory Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland" + }, + { + "author_name": "Mirjam Maeusezahl", + "author_inst": "Federal Office of Public Health, Bern, Switzerland" + }, + { + "author_name": "Milo Moraz", + "author_inst": "Valais Hospital, Central Institute, Sion, Switzerland" + }, + { + "author_name": "Richard Neher", + "author_inst": "Biozentrum, University of Basel, Basel, Switzerland & SIB Swiss Institute of Bioinformatics" + }, + { + "author_name": "Oliver Nolte", + "author_inst": "Zentrum fuer Labormedizin St. Gall, St. Gall, Switzerland" + }, + { + "author_name": "Alban Ramette", + "author_inst": "Institute for Infectious Diseases (IFIK), University of Bern, Bern, Switzerland" + }, + { + "author_name": "Maurice Redondo", + "author_inst": "Viollier AG, Allschwil, Switzerland" + }, + { + "author_name": "Lorenz Risch", + "author_inst": "Labor Dr. Risch, Buchs, Switzerland" + }, + { + "author_name": "Lionel Rohner", + "author_inst": "Federal Office of Public Health, Bern, Switzerland" + }, + { + "author_name": "Tim Roloff", + "author_inst": "Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland" + }, + { + "author_name": "Pascal Schlaepfer", + "author_inst": "Clinical Microbiology, University Hospital Basel, Basel, Switzerland" + }, + { + "author_name": "Katrin Schneider", + "author_inst": "Federal Office of Public Health, Bern, Switzerland" + }, + { + "author_name": "Franziska Singer", + "author_inst": "NEXUS Personalized Health Technologies, ETH Zurich, Basel, Switzerland & SIB Swiss Institute of Bioinformatics" + }, + { + "author_name": "Valeria Spina", + "author_inst": "Department of Laboratory Medicine, Ente Ospedaliero Cantonale, Bellinzona, Switzerland" + }, + { + "author_name": "Tanja Stadler", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland & SIB Swiss Institute of Bioinformatics" + }, + { + "author_name": "Erik Studer", + "author_inst": "Federal Office of Public Health, Bern, Switzerland" + }, + { + "author_name": "Ivan Topolsky", + "author_inst": "Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland & SIB Swiss Institute of Bioinformatics" + }, + { + "author_name": "Alexandra Trkola", + "author_inst": "Institute of Medical Virology, University of Zurich, Zurich, Switzerland" + }, + { + "author_name": "Daniel Walther", + "author_inst": "SIB Swiss Institute of Bioinformatics, Geneva, Switzerland" + }, + { + "author_name": "Nadia Wohlwend", + "author_inst": "Labor Dr. Risch, Buchs, Switzerland" + }, + { + "author_name": "Cinzia Zehnder", + "author_inst": "Synlab, Microbiology Department, Bioggio, Switzerland" + }, + { + "author_name": "Aitana Neves", + "author_inst": "SIB Swiss Institute of Bioinformatics, Geneva, Switzerland" + }, + { + "author_name": "Adrian Egli", + "author_inst": "Institute of Medical Microbiology, University of Zurich, Zurich, Switzerland" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.08.30.23294716", @@ -61265,51 +61188,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.08.24.554732", - "rel_title": "Mucosal antibody responses to SARS-CoV-2 booster vaccination and breakthrough infection", + "rel_doi": "10.1101/2023.08.24.554650", + "rel_title": "Efficient Sequence Embedding For SARS-CoV-2 Variants Classification", "rel_date": "2023-08-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.24.554732", - "rel_abs": "Coronavirus disease 2019 (COVID-19) vaccines have saved millions of lives. However, variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have emerged causing large numbers of breakthrough infections. These developments necessitated the rollout of COVID-19 vaccine booster doses. It has been reported that mucosal antibody levels in the upper respiratory tract, especially for secretory IgA (sIgA), correlate with protection from infection with SARS-CoV-2. However, it is still unclear how high levels of mucosal antibodies can be induced. In this study, we measured serum IgG, saliva IgG and saliva sIgA responses in individuals who received COVID-19 mRNA booster vaccinations or who experienced breakthrough infections. We found that mRNA booster doses could induce robust serum and saliva IgG responses, especially in individuals who had not experienced infections before, but saliva sIgA responses were weak. In contrast, breakthrough infections in individuals who had received the primary mRNA vaccination series induced robust serum and saliva IgG as well as saliva sIgA responses. Individuals who had received a booster dose and then had a breakthrough infection showed low IgG induction in serum and saliva but still responded with robust saliva sIgA induction. These data suggest that upper respiratory tract exposure to antigen is an efficient way of inducing mucosal sIgA while exposure via intramuscular injection is not.\n\nImportanceAntibodies on mucosal surfaces of the upper respiratory tract have been shown to be important for protection from infection with SARS-CoV-2. Here we investigate the induction of serum IgG, saliva IgG and saliva sIgA after COVID-19 mRNA booster vaccination or breakthrough infections.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.24.554650", + "rel_abs": "Kernel-based methods, such as Support Vector Machines (SVM), have demonstrated their utility in various machine learning (ML) tasks, including sequence classification. However, these methods face two primary challenges:(i) the computational complexity associated with kernel computation, which involves an exponential time requirement for dot product calculation, and (ii) the scalability issue of storing the large n x n matrix in memory when the number of data points(n) becomes too large. Although approximate methods can address the computational complexity problem, scalability remains a concern for conventional kernel methods. This paper presents a novel and efficient embedding method that overcomes both the computational and scalability challenges inherent in kernel methods. To address the computational challenge, our approach involves extracting the k-mers/nGrams (consecutive character substrings) from a given biological sequence, computing a sketch of the sequence, and performing dot product calculations using the sketch. By avoiding the need to compute the entire spectrum (frequency count) and operating with low-dimensional vectors (sketches) for sequences instead of the memory-intensive n x n matrix or full-length spectrum, our method can be readily scaled to handle a large number of sequences, effectively resolving the scalability problem. Furthermore, conventional kernel methods often rely on limited algorithms (e.g., kernel SVM) for underlying ML tasks. In contrast, our proposed fast and alignment-free spectrum method can serve as input for various distance-based (e.g., k-nearest neighbors) and non-distance-based (e.g., decision tree) ML methods used in classification and clustering tasks. We achieve superior prediction for coronavirus spike/Peplomer using our method on real biological sequences excluding full genomes. Moreover, our proposed method outperforms several state-of-the-art embedding and kernel methods in terms of both predictive performance and computational runtime.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Disha Bhavsar", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Gagandeep Singh", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Kaori Sano", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Charles Gleason", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Komal Srivastava", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Sarwan Ali", + "author_inst": "Georgia State University" }, { - "author_name": "Juan Manuel Carreno", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Usama Sardar", + "author_inst": "Lahore University of Management Sciences" }, { - "author_name": "Viviana Simon", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Imdadullah Khan", + "author_inst": "Lahore University of Management Sciences" }, { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Murray Patterson", + "author_inst": "Georgia State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2023.08.25.23294408", @@ -62859,91 +62766,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.08.24.554561", - "rel_title": "Rationally designed multimeric nanovaccines using icosahedral DNA origami for molecularly controlled display of SARS-CoV-2 receptor binding domain", - "rel_date": "2023-08-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.24.554561", - "rel_abs": "Multivalent antigen display on nanoparticles can enhance the immunogenicity of nanovaccines targeting viral moieties, such as the receptor binding domain (RBD) of SARS-CoV-2. However, particle morphology and size of current nanovaccines are significantly different from those of SARS-CoV-2. Additionally, surface antigen patterns are not controllable to enable the optimization of B cell activation. Herein, we employed an icosahedral DNA origami (ICO) as a display particle for SARS-CoV-2 RBD nanovaccines. The morphology and diameter of the particles were close to those of the virus (91 {+/-} 11 nm). The surface addressability of the DNA origami permitted facile modification of the ICO surface with numerous RBD antigen clusters (ICO-RBD) to form various antigen patterns. Using an in vitro screening system, we demonstrate that the antigen spacing, antigen copies within clusters and cluster number parameters of the surface antigen pattern all impact the ability of the nanovaccines to activate B cells. Importantly, the optimized ICO-RBD nanovaccines evoked stronger and more enduring humoral and T cell immune responses in mouse models compared to soluble RBD antigens. Our vaccines activated similar humoral immunity and slightly stronger cellular immunity compared to mRNA vaccines. These results provide reference principles for the rational design of nanovaccines and exemplify the utility of DNA origami as a display platform for vaccines against infectious disease.", - "rel_num_authors": 18, + "rel_doi": "10.1101/2023.08.17.23294204", + "rel_title": "High proportions of post-exertional malaise and orthostatic intolerance in people living with post-COVID-19 condition: the PRIME post-COVID study", + "rel_date": "2023-08-23", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.08.17.23294204", + "rel_abs": "BackgroundExercise-based treatments can be harmful in people who were SARS-CoV-2 positive and living with post-COVID-19 condition (PL-PCC) and who have post-exertional malaise (PEM) or orthostatic intolerance (OI). Nevertheless, PEM and OI are not routinely assessed by clinicians. We estimated PEM and OI proportions in PL-PCC, as well in people not living with PCC (PnL-PCC) and negatives (i.e., never reported a SARS-CoV-2 positive test), and identified associated factors.\n\nMethodsParticipants from the PRIME post-COVID study were included. PEM and OI were assessed using validated questionnaires. PCC was defined as feeling unrecovered after SARS-CoV-2 infection. Multivariable regression analyses to study PEM and OI were stratified for sex.\n\nResultsData from 3,783 participants was analyzed. In PL-PCC, proportion of PEM was 48.1% and 41.2%, and proportion of OI was 29.3% and 27.9% in women and in men, respectively. Proportions were higher in PL-PCC compared to negatives, for PEM in women OR=4.38 [95%CI:3.01-6.38]; in men OR=4.78 [95%CI:3.13-7.29]; for OI in women 3.06 [95%CI:1.97-4.76]; in men 2.71 [95%CI:1.75-4.21]. Associated factors were age [≤]60 years, [≥]1 comorbidities and living alone.\n\nConclusionsHigh proportions of PEM and OI are observed in PL-PCC. Standard screening for PEM and OI is recommended in PL-PCC, to promote appropriate therapies.\n\nTrial registration ClinicalTrials.gov identifier:NCT05128695", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Qingqing Feng", - "author_inst": "National Center for Nanoscience and Technology of China" - }, - { - "author_name": "Keman Cheng", - "author_inst": "National Center for Nanoscience and Technology of China" - }, - { - "author_name": "Lizhuo Zhang", - "author_inst": "National Center for Nanoscience and Technology of China" - }, - { - "author_name": "Xiaoyu Gao", - "author_inst": "National Center for Nanoscience and Technology of China" - }, - { - "author_name": "Jie Liang", - "author_inst": "National Center for Nanoscience and Technology of China" - }, - { - "author_name": "Guangna Liu", - "author_inst": "National Center for Nanoscience and Technology of China" - }, - { - "author_name": "Nana Ma", - "author_inst": "National Center for Nanoscience and Technology of China" - }, - { - "author_name": "Chen Xu", - "author_inst": "National Center for Nanoscience and Technology of China" - }, - { - "author_name": "Ming Tang", - "author_inst": "National Center for Nanoscience and Technology of China" - }, - { - "author_name": "Liting Chen", - "author_inst": "National Center for Nanoscience and Technology of China" + "author_name": "Demi ME Pagen", + "author_inst": "Public Health Service South Limburg" }, { - "author_name": "Xinwei Wang", - "author_inst": "National Center for Nanoscience and Technology of China" + "author_name": "Maarten Van Herck", + "author_inst": "Ciro" }, { - "author_name": "Xuehui Ma", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" + "author_name": "Celine JA van Bilsen", + "author_inst": "Public Health Service South Limburg" }, { - "author_name": "Jiajia Zou", - "author_inst": "Beijing Intell Nanomedicine" + "author_name": "Stephanie Brinkhues", + "author_inst": "Public Health Service South Limburg" }, { - "author_name": "Quanwei Shi", - "author_inst": "Beijing Intell Nanomedicine" + "author_name": "Kevin Konings", + "author_inst": "Public Health Service South Limburg" }, { - "author_name": "Pei Du", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" + "author_name": "Casper DJ den Heijer", + "author_inst": "Public Health Service South Limburg" }, { - "author_name": "Qihui Wang", - "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" + "author_name": "Martijn A Spruit", + "author_inst": "Ciro" }, { - "author_name": "Guangjun Nie", - "author_inst": "National Center for Nanoscience and Technology of China" + "author_name": "Christian JPA Hoebe", + "author_inst": "South Limburg Public Health Service" }, { - "author_name": "Xiao Zhao", - "author_inst": "National Center for Nanoscience and Technology of China" + "author_name": "Nicole HTM Dukers-Muijrers", + "author_inst": "Maastricht University/Public Health Service" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioengineering" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.08.22.23294400", @@ -64601,27 +64472,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.08.17.553661", - "rel_title": "Purification, crystallization, and preliminary structural analysis of multivalent immunogenic effector protein-anchored SARS-CoV-2 RBD", + "rel_doi": "10.1101/2023.08.17.553792", + "rel_title": "How reliable are estimates of key parameters in viral dynamic models?", "rel_date": "2023-08-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.17.553661", - "rel_abs": "The continuous spread of highly transmissible variants of concern and the potential diminished effectiveness of existing vaccines necessitate ongoing research and development of new vaccines. Immunogenic molecule-anchored antigen has demonstrated superior efficacy in subunit vaccination, primarily due to enhanced cellular uptake facilitated by the affinity between the surface of Immunogenic molecule and the cell membrane. Based on the Immunogenic recombinase B. malayi RecA (BmRecA), we have overexpressed the construct of BmRecA with SARS-CoV-2 RBD (BmRecA-RBD) that exists as a stable helical filament formation; it was purified and crystallized to obtain X-ray diffraction data at 2.7 [A], belonged to the hexagonal symmetry group P65 in the unit-cell parameters of a=b=122.12, c=75.55 and ={beta}=90{degrees}, {gamma}=120{degrees}. The Matthews coefficient was estimated to be 3.12 [A]3 Da-1, corresponding to solvent contents of 52.65.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.17.553792", + "rel_abs": "Mathematical models of viral infection have been developed and fit to data to gain insight into disease pathogenesis for a number of agents including HIV, hepatitis C and B virus. However, for acute infections such as influenza and SARS-CoV-2, as well as for infections such as hepatitis C and B that can be acute or progress to being chronic, viral load data are often collected after symptoms develop, usually around or after the peak viral load. Consequently, we frequently lack data in the exponential phase of viral growth, i.e., when most transmission events occur. Missing data may make estimation of the time of infection, the infectious period, and parameters in viral dynamic models, such as the cell infection rate, difficult. Here, we evaluated the reliability of estimates of key model parameters when viral load data prior to the viral load peak is missing. We estimated the time from infection to peak viral load by fitting non-linear mixed models to a dataset with frequent viral RNA measurements, including pre-peak. We quantified the reliability of estimated infection times, key model parameters, and the time to peak viral load. Although estimates of the time of infection are sensitive to the quality and amount of available data, other parameters important in understanding disease pathogenesis, such as the loss rate of infected cells, are less sensitive. We find a lack of data in the exponential growth phase underestimates the time to peak viral load by several days leading to a shorter predicted exponential growth phase. On the other hand, having an idea of the time of infection and fixing it, results in relatively good estimates of dynamical parameters even in the absence of early data.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Taek Hun Kwon", - "author_inst": "Baylor College of Medicine" + "author_name": "Carolin Zitzmann", + "author_inst": "Los Alamos National Laboratory" }, { - "author_name": "Tae Gyun Kim", - "author_inst": "Gyeongbuk Institute for Bio industry" + "author_name": "Ruian Ke", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Ruy M. Ribeiro", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Alan S. Perelson", + "author_inst": "Los Alamos National Laboratory" } ], "version": "1", - "license": "cc_no", + "license": "cc0", "type": "new results", - "category": "biophysics" + "category": "immunology" }, { "rel_doi": "10.1101/2023.08.09.23293915", @@ -66139,35 +66018,47 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.08.14.553219", - "rel_title": "Transmission bottleneck size estimation from de novo viral genetic variation", + "rel_doi": "10.1101/2023.08.12.553079", + "rel_title": "Pandemic preparedness through genomic surveillance: Overview of mutations in SARS-CoV-2 over the course of COVID-19 outbreak", "rel_date": "2023-08-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.14.553219", - "rel_abs": "Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, allele frequencies can change dramatically over the course of an individuals infection, such that sites that are polymorphic in the donor at the time of transmission may not be polymorphic in the donor at the time of sampling and allele frequencies at donor-polymorphic sites may change dramatically over the course of a recipients infection. Because of this, transmission bottleneck sizes estimated using allele frequencies observed at a donors polymorphic sites may be considerable underestimates of true bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arose de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these two respiratory viruses, using an approach that does not tend to underestimate transmission bottleneck sizes.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.12.553079", + "rel_abs": "Genomic surveillance is a vital strategy for preparedness against the spread of infectious diseases and to aid in development of new treatments. In an unprecedented effort, millions of samples from COVID-19 patients have been sequenced worldwide for SARS-CoV-2. Using more than 8 million sequences that are currently available in GenBanks SARS-CoV-2 database, we report a comprehensive overview of mutations in all 26 proteins and open reading frames (ORFs) from the virus. The results indicate that the spike protein, NSP6, nucleocapsid protein, envelope protein and ORF7b have shown the highest mutational propensities so far (in that order). In particular, the spike protein has shown rapid acceleration in mutations in the post-vaccination period. Monitoring the rate of non-synonymous mutations (Ka) provides a fairly reliable signal for genomic surveillance, successfully predicting surges in 2022. Further, the external proteins (spike, membrane, envelope, and nucleocapsid proteins) show a significant number of mutations compared to the NSPs. Interestingly, these four proteins showed significant changes in Ka typically 2 to 4 weeks before the increase in number of human infections (\"surges\"). Therefore, our analysis provides real time surveillance of mutations of SARS-CoV-2, accessible through the project website http://pandemics.okstate.edu/covid19/. Based on ongoing mutation trends of the virus, predictions of what proteins are likely to mutate next are also made possible by our approach. The proposed framework is general and is thus applicable to other pathogens. The approach is fully automated and provides the needed genomic surveillance to address a fast-moving pandemic such as COVID-19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Teresa Shi", - "author_inst": "Emory University" + "author_name": "Fares Z Najar", + "author_inst": "Oklahoma State University" }, { - "author_name": "Jeremy Harris", - "author_inst": "Emory University" + "author_name": "Chelsea L Murphy", + "author_inst": "Oklahoma State University" }, { - "author_name": "Michael A Martin", - "author_inst": "Emory University" + "author_name": "Evan Linde", + "author_inst": "Oklahoma State University" }, { - "author_name": "Katia Koelle", - "author_inst": "Emory University" + "author_name": "Veniamin A Borin", + "author_inst": "Oklahoma State University" + }, + { + "author_name": "Huan Wang", + "author_inst": "University College London" + }, + { + "author_name": "Shozeb Haider", + "author_inst": "University College London" + }, + { + "author_name": "Pratul K Agarwal", + "author_inst": "Oklahoma State University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", - "category": "evolutionary biology" + "category": "genomics" }, { "rel_doi": "10.1101/2023.08.14.553212", @@ -67537,63 +67428,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.08.08.552415", - "rel_title": "Antiviral efficacy of the SARS-CoV-2 XBB breakthrough infection sera against Omicron subvariants including EG.5", + "rel_doi": "10.1101/2023.08.08.552503", + "rel_title": "Within-host evolution of SARS-CoV-2: how often are mutations transmitted?", "rel_date": "2023-08-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.08.552415", - "rel_abs": "As of July 2023, EG.5.1 (a.k.a. XBB.1.9.2.5.1), a XBB subvariant bearing the S:Q52H and S:F456L substitutions, alongside the S:F486P substitution (Figure S1A), has rapidly spread in some countries. On July 19, 2023, the WHO classified EG.5 as a variant under monitoring. First, we showed that EG.5.1 exhibits a higher effective reproduction number compared with XBB.1.5, XBB.1.16, and its parental lineage (XBB.1.9.2), suggesting that EG.5.1 will spread globally and outcompete these XBB subvariants in the near future. We then addressed whether EG.5.1 evades from the antiviral effect of the humoral immunity induced by breakthrough infection (BTI) of XBB subvariants and performed a neutralization assay using XBB BTI sera. However, the 50% neutralization titer (NT50) of XBB BTI sera against EG.5.1 was comparable to those against XBB.1.5/1.9.2 and XBB.1.16. Moreover, the sensitivity of EG.5.1 to convalescent sera of XBB.1- and XBB.1.5-infected hamsters was similar to those of XBB.1.5/1.9 and XBB.1.16. These results suggest that the increased Re of EG.5.1 is attributed to neither increased infectivity nor immune evasion from XBB BTI, and the emergence and spread of EG.5 is driven by the other pressures. We previously demonstrated that Omicron BTI cannot efficiently induce antiviral humoral immunity against the variant infected. In fact, the NT50s of the BTI sera of Omicron BA.1, BA.2, and BA.5 against the variant infected were 3.0-, 2.2-, and 3.4-fold lower than that against the ancestral B.1.1 variant, respectively. However, strikingly, we found that the NT50 of the BTI sera of XBB1.5/1.9 and XBB.1.16 against the variant infected were 8.7- and 8.3-fold lower than that against the B.1.1 variant. These results suggest that XBB BTI cannot efficiently induce antiviral humoral immunity against XBB subvariants.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=147 SRC=\"FIGDIR/small/552415v1_figs1.gif\" ALT=\"Figure 1\">\nView larger version (39K):\norg.highwire.dtl.DTLVardef@f95376org.highwire.dtl.DTLVardef@d66fa8org.highwire.dtl.DTLVardef@3c8841org.highwire.dtl.DTLVardef@15824c_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure S1.C_FLOATNO Virological features of EG.5.1 and XBB BTI (A) Frequency of mutations of interest in the representative XBB sublineages. Only mutations with a frequency >0.5 in at least one but not all the representative sublineages are shown. Note that the S proteins of XBB.1.5 and XBB.1.9.2 are identical.\n\n(B) Estimated epidemic dynamics of the representative XBB sublineages in countries where >50 sequences of EG.5.1, XBB.1.5, XBB.1.9.2, and XBB.1.16 were detected from April 1, 2023 to July 13, 2023. Countries are ordered according to the number of detected sequences of EG.5.1. Line, posterior mean; ribbon, 95% Bayesian confidence interval. The dynamics for EG.5.1 is highlighted by a red arrowhead.\n\n(C) Estimated relative Re of the representative XBB sublineages in the six countries. The relative Re of XBB.1.5 is set to 1 (horizontal dashed line). Violin, posterior distribution; dot, posterior mean; line, 95% Bayesian confidence interval.\n\n(D) Lentivirus-based pseudovirus assay. HOS-ACE2-TMPRSS2 cells were infected with pseudoviruses bearing each S protein. The amount of input virus was normalized to the amount of HIV-1 p24 capsid protein. The percentage infectivity of XBB.1.5/1.9.2, XBB.1.5/1.9.2+Q52H, XBB.1.5/1.9.2+F456L, and EG.5.1 compared to that of XBB.1.5/1.9.2 are shown. The horizontal dash line indicates the mean value of the percentage infectivity of the XBB.1.5/1.9.2. Assays were performed in quadruplicate. The presented data are expressed as the average {+/-} SD. Each dot indicates the result of an individual replicate.\n\n(E-G) Neutralization assay. Assays were performed with pseudoviruses harboring the S proteins of B.1.1, BA.1, BA.2, BA.5, BQ.1.1, XBB.1, XBB.1.5/1.9.2, XBB.1.16, EG.5.1, XBB.1.5/1.9.2+Q52H, and XBB.1.5/1.9.2+F456L. The following sera were used: convalescent sera from fully vaccinated individuals who had been infected with XBB.1.5 (one 3-dose vaccinated. 1 donor in total), XBB.1.9 (one 3-dose vaccinated donor, one 4-dose vaccinated donor and one 5-dose vaccinated donor. 3 donors in total), and XBB.1.16 (one 2-dose vaccinated donor, two 3-dose vaccinated donors, and one 4-dose vaccinated donor. 4 donors in total) (E); sera from hamster infected with XBB.1 (left) or XBB.1.5 (right) (F); and convalescent sera from fully vaccinated individuals who had been infected with BA.1 (thirteen 2-dose vaccinated, 13 donors in total) (left)1, BA.2 (nine 2-dose vaccinated and four 3-dose vaccinated donors. 13 donors in total) (middle)19, and BA.5 (one 2-dose vaccinated, thirteen 3-dose vaccinated donors, and one 4-dose vaccinated. 15 donors in total) (right)19 (G). Each dot indicates the result of an individual replicate. Assays for each serum sample were performed in triplicate to determine the 50% neutralization titer (NT50). Each dot represents one NT50 value, and the geometric mean and 95% confidence interval are shown. The number in parenthesis indicates the mean of NT50 values. The horizontal dash line indicates the detection limit (120-fold).\n\nIn D, statistically significant differences (**, P < 0.001, ***, P < 0.0001) versus XBB.1.5/1.9.2 were determined by two-sided Students t tests. Blue asterisks indicate decreased percentage of infectivity.\n\nIn E and G, statistically significant differences versus B.1.1 were determined by two-sided Wilcoxon signed-rank tests. The fold change between B.1.1 and the variant indicated is shown in red. Background information on the convalescent donors is summarized in Table S1.\n\nIn F, statistically significant differences (*, P < 0.01, **, P < 0.001) between B.1.1 and XBB.1 (left) or XBB.1.5/1.9.2 (right) were determined by two-sided Wilcoxon signed-rank tests and indicated with asterisks. Red asterisks indicate decreased NT50s.\n\nC_FIG", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.08.552503", + "rel_abs": "Despite a relatively low mutation rate, the large number of SARS-CoV-2 infections has allowed for substantial genetic change, leading to a multitude of emerging variants. Using a recently determined mutation rate (per site replication), as well as parameter estimates for within-host SARS-CoV-2 infection, we apply a stochastic transmission-bottleneck model to describe the survival probability of de novo SARS-CoV-2 mutations. For narrow bottlenecks, we find mutations affecting pertarget-cell attachment rate (with phenotypes associated with fusogenicity and ACE2 binding), have similar transmission probabilities to mutations affecting viral load clearance (with phenotypes associated with humoral evasion). We further find that mutations affecting the eclipse rate (with phenotypes associated with reorganization of cellular metabolic processes and synthesis of viral budding precursor material) are highly favoured relative to all other traits examined. We find mutations leading to reduced removal rates of infected cells (with phenotypes associated with innate immune evasion) have limited transmission advantage relative to mutations leading to humoral evasion. Predicted transmission probabilities, however, for mutations affecting innate immune evasion are more consistent with the range of clinically-estimated household transmission probabilities for de novo mutations. This result suggests that although mutations affecting humoral evasion are more easily transmitted when they occur, mutations affecting innate immune evasion may occur more readily. We examine our predictions in the context of a number of previously characterized mutations in circulating strains of SARS-CoV-2. Our work offers both a null model for SARS-CoV-2 substitution rates and predicts which aspects of viral life history are most likely to successfully evolve, despite low mutation rates and repeated transmission bottlenecks.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Yu Kaku", - "author_inst": "The University of Tokyo" - }, - { - "author_name": "Yusuke Kosugi", - "author_inst": "The University of Tokyo" - }, - { - "author_name": "Keiya Uriu", - "author_inst": "The University of Tokyo" - }, - { - "author_name": "Jumpei Ito", - "author_inst": "The Institute of Medical Science, The University of Tokyo" - }, - { - "author_name": "Jin Kuramochi", - "author_inst": "Interpark Kuramochi Clinic" - }, - { - "author_name": "Kenji Sadamasu", - "author_inst": "Tokyo Metropolitan Institute of Public Health" - }, - { - "author_name": "Kazuhisa Yoshimura", - "author_inst": "Tokyo Metropolitan Institute of Public Health" - }, - { - "author_name": "Hiroyuki Asakura", - "author_inst": "Tokyo Metropolitan Institute of Public Health" - }, - { - "author_name": "Mami Nagashima", - "author_inst": "Tokyo Metropolitan Institute of Public Health" + "author_name": "Chapin S. Korosec", + "author_inst": "York University" }, { - "author_name": "- The Genotype to Phenotype Japan (G2P-Japan) Consortium", - "author_inst": "-" + "author_name": "Lindi M. Wahl", + "author_inst": "Western University" }, { - "author_name": "Kei Sato", - "author_inst": "Institute of Medical Science, The University of Tokyo" + "author_name": "Jane M. Heffernan", + "author_inst": "York University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "microbiology" + "category": "genetics" }, { "rel_doi": "10.1101/2023.08.07.552330", @@ -69083,47 +68942,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.07.28.23293338", - "rel_title": "Systematic Review and Meta-Analysis Protocol of the Efficacy and Safety of COVID-19 Drug Candidates Targeting Host Enzymes Involved in Immune Response", + "rel_doi": "10.1101/2023.07.29.23293334", + "rel_title": "CLINICAL AND SEROLOGICAL PREDICTORS OF POST COVID-19 CONDITION: FINDINGS FROM A CANADIAN PROSPECTIVE COHORT STUDY", "rel_date": "2023-08-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.28.23293338", - "rel_abs": "IntroductionCOVID-19 is a rapidly spreading infectious disease caused by the SARS-CoV-2 virus. Although several therapeutic interventions have been developed, the mortality rate of the disease remains high, and effective treatment options are urgently needed. Host-directed therapies targeting enzymes involved in the immune response represent a promising strategy for the development of novel therapeutics against COVID-19. This study aims to conduct a systematic review and meta-analysis of the literature to evaluate the potential of drug candidates targeting host enzymes involved in the immune response for the treatment of COVID-19.\n\nMethods and analysisWe will conduct a systematic search of electronic databases including PubMed, Embase, and Cochrane Library, as well as preprint servers and clinical trial registries for relevant studies. We will include randomized controlled trials, observational studies, and preclinical studies evaluating the efficacy of drug candidates targeting host enzymes involved in the immune response in COVID-19. Two reviewers will independently screen articles, extract data, and assess study quality. The primary outcome will be the effect of drug candidates on mortality, while secondary outcomes will include time to recovery, adverse events, and changes in immune markers. A meta-analysis will be performed to estimate pooled effect sizes of the interventions, and a narrative synthesis will be conducted for studies that are not amenable to quantitative analysis. This study will provide a comprehensive evaluation of the potential of host-directed therapies targeting enzymes involved in the immune response for the treatment of COVID-19. The results of this study may guide the development of novel therapeutics against COVID-19 and inform clinical practice.\n\nEthics and disseminationThis study will review published data, and thus it is unnecessary to obtain ethical approval. The findings of this systematic review will be published in a peer-reviewed journal.\n\nPROSPERO registration numberCRD42023415110.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.29.23293334", + "rel_abs": "IntroductionMore than three years into the pandemic, there is persisting uncertainty as to the etiology, biomarkers, and risk factors of Post COVID-19 Condition (PCC). Serological research data remain a largely untapped resource. Few studies have investigated the potential relationships between post-acute serology and PCC, while accounting for clinical covariates.\n\nMethodsWe compared clinical and serological predictors among COVID-19 survivors with (n=102 cases) and without (n=122 controls) persistent symptoms [≥]12 weeks post-infection. We selected four primary serological predictors (anti-nucleocapsid (N), anti-Spike, and anti-receptor binding domain (RBD) IgG titres, and neutralization efficiency), and specified clinical covariates a priori.\n\nResultsSimilar proportions of PCC-cases (66.7%, n=68) and infected-controls (71.3%, n=87) tested positive for anti-N IgG. More cases tested positive for anti-Spike (94.1%, n=96) and anti-RBD (95.1%, n=97) IgG, as compared with controls (anti-Spike: 89.3%, n=109; anti-RBD: 84.4%, n=103). Similar trends were observed among unvaccinated participants. Effects of IgG titres on PCC status were non-significant in univariate and multivariate analyses. Adjusting for age and sex, PCC-cases were more likely to be efficient neutralizers (OR 2.2, 95% CI 1.11 - 4.49), and odds was further increased among cases to report deterioration in quality of life (OR 3.4, 95% CI 1.64 - 7.31). Clinical covariates found to be significantly related to PCC included obesity (OR 2.3, p=0.02), number of months post COVID-19 (OR 1.1, p<0.01), allergies (OR 1.8, p=0.04), and need for medical support (OR 4.1, p<0.01).\n\nConclusionDespite past COVID-19 infection, approximately one third of PCC-cases and infected-controls were seronegative for anti-N IgG. Findings suggest higher neutralization efficiency among cases as compared with controls, and that this relationship is stronger among cases with more severe PCC. Cases also required more medical support for COVID-19 symptoms, and described complex, ongoing health sequelae. More data from larger cohorts are needed to substantiate results, permit subgroup analyses of IgG titres, and explore for differences between clusters of PCC symptoms. Future assessment of IgG subtypes may also elucidate new findings.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Aganze Gloire-Aime Mushebenge", - "author_inst": "University of KwaZulu-Natal" + "author_name": "Erin Collins", + "author_inst": "School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada" }, { - "author_name": "Samuel Chima Ugbaja", - "author_inst": "University of KwaZulu-Natal" + "author_name": "Yannick Galipeau", + "author_inst": "Department of Biochemistry, Microbiology & Immunology, University of Ottawa, Ottawa, Ontario, Canada" }, { - "author_name": "Nonkululeko Avril Mbatha", - "author_inst": "University f KwaZulu Natal" + "author_name": "Corey Arnold", + "author_inst": "Department of Biochemistry, Microbiology & Immunology, University of Ottawa, Ottawa, Ontario, Canada" }, { - "author_name": "Manimani Ghislain Riziki", - "author_inst": "University of KwaZulu-Natal" + "author_name": "Anne Bh\u00e9reur", + "author_inst": "Faculty of Medicine, University of Montreal, Montreal, Quebec, Canada" }, { - "author_name": "Tambwe Willy Muzumbukilwa", - "author_inst": "University of KwaZulu-Natal" + "author_name": "Ronald Booth", + "author_inst": "Department of Pathology and Laboratory Medicine, University of Ottawa, Ottawa, Ontario, Canada" }, { - "author_name": "Mukanda Gedeon Kadima", - "author_inst": "University of KwaZulu-Natal" + "author_name": "C Arianne Buchan", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada" }, { - "author_name": "Hezekiel M. Kumalo", - "author_inst": "University of KwaZulu-Natal" + "author_name": "Curtis Cooper", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada" + }, + { + "author_name": "Angela M Crawley", + "author_inst": "Chronic Disease Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada" + }, + { + "author_name": "Pauline Mccluskie", + "author_inst": "Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario Canada" + }, + { + "author_name": "Michaeline McGuinty", + "author_inst": "Division of Infectious Diseases, Department of Medicine, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada" + }, + { + "author_name": "Martin Pelchat", + "author_inst": "Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario Canada" + }, + { + "author_name": "Lynda Rocheleau", + "author_inst": "Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Ontario Canada" + }, + { + "author_name": "Raphael Saginur", + "author_inst": "Ottawa Health Science Network Research Ethics Board (OHSN-REB), Ottawa Hospital Research Institute, Ottawa, Ontario, Canada" + }, + { + "author_name": "Chris Gravel", + "author_inst": "School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada" + }, + { + "author_name": "Steven Hawken", + "author_inst": "Clinical Epidemiology, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada" + }, + { + "author_name": "Marc-Andr\u00e9 Langlois", + "author_inst": "Department of Biochemistry, Microbiology & Immunology, University of Ottawa, Ottawa, Ontario, Canada" + }, + { + "author_name": "Julian Little", + "author_inst": "School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.07.28.23293269", @@ -70805,103 +70704,79 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.08.01.551417", - "rel_title": "Phenotyping the virulence of SARS-CoV-2 variants in hamsters by digital pathology and machine learning", + "rel_doi": "10.1101/2023.07.28.551051", + "rel_title": "Targeted Amplification and Genetic Sequencing of the Severe Acute Respiratory Syndrome Coronavirus 2 Surface Glycoprotein", "rel_date": "2023-08-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.08.01.551417", - "rel_abs": "SARS-CoV-2 has continued to evolve throughout the COVID-19 pandemic, giving rise to multiple variants of concern (VOCs) with different biological properties. As the pandemic progresses, it will be essential to test in near real time the potential of any new emerging variant to cause severe disease. BA.1 (Omicron) was shown to be attenuated compared to the previous VOCs like Delta, but it is possible that newly emerging variants may regain a virulent phenotype. Hamsters have been proven to be an exceedingly good model for SARS-CoV-2 pathogenesis. Here, we aimed to develop robust quantitative pipelines to assess the virulence of SARS-CoV-2 variants in hamsters. We used various approaches including RNAseq, RNA in situ hybridization, immunohistochemistry, and digital pathology, including software assisted whole section imaging and downstream automatic analyses enhanced by machine learning, to develop methods to assess and quantify virus-induced pulmonary lesions in an unbiased manner. Initially, we used Delta and Omicron to develop our experimental pipelines. We then assessed the virulence of recent Omicron sub-lineages including BA.5, XBB, BQ.1.18, BA.2 and BA.2.75. We show that in experimentally infected hamsters, accurate quantification of alveolar epithelial hyperplasia and macrophage infiltrates represent robust markers for assessing the extent of virus-induced pulmonary pathology, and hence virus virulence. In addition, using these pipelines, we could reveal how some Omicron sub-lineages (e.g., BA.2.75) have regained virulence compared to the original BA.1. Finally, to maximise the utility of the digital pathology pipelines reported in our study, we developed an online repository containing representative whole organ histopathology sections that can be visualised at variable magnifications (https://covid-atlas.cvr.gla.ac.uk). Overall, this pipeline can provide unbiased and invaluable data for rapidly assessing newly emerging variants and their potential to cause severe disease.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.28.551051", + "rel_abs": "The SARS-CoV-2 spike protein is a highly immunogenic and mutable protein that is the target of vaccine prevention and antibody therapeutics. This makes the encoding S-gene an important sequencing target. The SARS-CoV-2 sequencing community overwhelmingly adopted tiling amplicon-based strategies for sequencing the entire genome. As the virus evolved, primer mismatches inevitably led to amplicon drop-out. Given the exposure of the spike protein to host antibodies, mutation occurred here most rapidly, leading to amplicon failure over the most insightful region of the genome. To mitigate this, we developed SpikeSeq, a targeted method to amplify and sequence the S-gene. We evaluated 20 distinct primer designs through iterative in silico and in vitro testing to select the optimal primer pairs and run conditions. Once selected, periodic in silico analysis monitor primer conservation as SARS-CoV-2 evolves. Despite being designed during the Beta wave, the selected primers remain > 99% conserved through Omicron as of 2023-04-14. To validate the final design, we compared SpikeSeq data and National SARS-CoV-2 Strain Surveillance whole-genome data for 321 matching samples. Consensus sequences for the two methods were highly identical (99.998%) across the S-gene. SpikeSeq can serve as a complement to whole-genome surveillance or be leveraged where only S-gene sequencing is of interest. While SpikeSeq is adaptable to other sequencing platforms, the Nanopore platform validated here is compatible with low to moderate throughputs, and its simplicity better enables users to achieve accurate results, even in low resource settings.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Gavin R Meehan", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Vanessa Herder", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Jay Allan", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Xinyi Huang", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Karen Kerr", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Diogo Correa Mendonca", - "author_inst": "University of Glasgow" + "author_name": "Matthew W Keller", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Georgios Ilia", - "author_inst": "University of Glasgow" + "author_name": "Lisa M Keong", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Derek Wright", - "author_inst": "University of Glasgow" + "author_name": "Benjamin L Rambo-Martin", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Kyriaki Nomikou", - "author_inst": "University of Glasgow" + "author_name": "Norman Hassell", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Quan Gu", - "author_inst": "University of Glasgow" + "author_name": "Kristine Lacek", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Sergi Molina Arias", - "author_inst": "University of Glasgow" + "author_name": "Malania M Wilson", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Giuditta De Lorenzo", - "author_inst": "University of Glasgow" + "author_name": "Marie K Kirby", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Vanessa Cowton", - "author_inst": "University of Glasgow" + "author_name": "Jimma Liddell", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Nicole Upfold", - "author_inst": "University of Glasgow" + "author_name": "D Collins Owuor", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Natasha Palmalux", - "author_inst": "University of Glasgow" + "author_name": "Mili Sheth", + "author_inst": "Biotechnology Core Facility Branch, Division of Scientific Resources, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control" }, { - "author_name": "Jonathan C Brown", - "author_inst": "Imperial College London" + "author_name": "Joseph Madden", + "author_inst": "Biotechnology Core Facility Branch, Division of Scientific Resources, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control" }, { - "author_name": "Wendy Barclay", - "author_inst": "Imperial College London" + "author_name": "Justin S Lee", + "author_inst": "Biotechnology Core Facility Branch, Division of Scientific Resources, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control" }, { - "author_name": "Ana Da Silva Filipe", - "author_inst": "University of Glasgow" + "author_name": "Rebecca J Kondor", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Wilhelm Furnon", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Arvind Patel", - "author_inst": "University of Glasgow" + "author_name": "David E Wentworth", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" }, { - "author_name": "Massimo Palmarini", - "author_inst": "MRC-University of Glasgow Centre for Virus Research" + "author_name": "John R Barnes", + "author_inst": "Influenza Division, National Center for Immunization and Respiratory Diseases (NCIRD), Centers for Disease Control and Prevention (CDC), Atlanta, Georgia, USA" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2023.08.01.551467", @@ -72739,83 +72614,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.07.25.550460", - "rel_title": "Non-neutralizing SARS-CoV-2 N-terminal domain antibodies protect mice against severe disease using Fc-mediated effector functions", + "rel_doi": "10.1101/2023.07.21.23292937", + "rel_title": "The Impact of the UK COVID-19 Lockdown on the Screening, Diagnostics and Incidence of Breast, Colorectal, Lung and Prostate Cancer in the UK: a Population-Based Cohort Study", "rel_date": "2023-07-26", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.25.550460", - "rel_abs": "Antibodies perform both neutralizing and non-neutralizing effector functions that protect against certain pathogen-induced diseases. A human antibody directed at the SARS-CoV-2 Spike N-terminal domain (NTD), DH1052, was recently shown to be non-neutralizing yet it protected mice and cynomolgus macaques from severe disease. The mechanisms of this non-neutralizing antibody-mediated protection are unknown. Here we show that Fc effector functions mediate non-neutralizing antibody (non-nAb) protection against SARS-CoV-2 MA10 viral challenge in mice. Though non-nAb infusion did not suppress infectious viral titers in the lung as potently as NTD neutralizing antibody (nAb) infusion, disease markers including gross lung discoloration were similar in nAb and non-nAb groups. Fc functional knockout substitutions abolished non-nAb protection and increased viral titers in the nAb group. Finally, Fc enhancement increased non-nAb protection relative to WT, supporting a positive association between Fc functionality and degree of protection in SARS-CoV-2 infection. This study demonstrates that non-nAbs can utilize Fc-mediated mechanisms to lower viral load and prevent lung damage due to coronavirus infection.\n\nAUTHOR SUMMARYCOVID-19 has claimed over 6.8 million lives worldwide and caused economic and social disruption globally. Preventing more deaths from COVID-19 is a principal goal of antibody biologic and vaccine developers. To guide design of such countermeasures, an understanding of how the immune system prevents severe COVID-19 disease is needed. We demonstrate here that antibody functions other than neutralization can contribute to protection from severe disease. Specifically, the functions of antibodies that rely on its Fc portion were shown to confer antibody-mediated protection of mice challenged with a mouse adapted version of SARS-CoV-2. Mice given an antibody that could not neutralize SARS-CoV-2 still showed a decrease in the amount of infectious virus in the lungs and less lung damage than mice given an irrelevant antibody. The decrease in infectious virus in the lungs was even larger when the non-neutralizing antibody was engineered to mediate non-neutralizing effector functions such as antibody-dependent cellular cytotoxicity more potently. Thus, in the absence of neutralization activity, non-neutralizing binding antibodies can contribute to the overall defense against SARS-CoV-2 infection and COVID-19 disease progression.", - "rel_num_authors": 16, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.21.23292937", + "rel_abs": "ObjectivesThis study aimed to assess the impact of the COVID-19 lockdown on the screening and diagnosis of breast, colorectal, lung, and prostate cancer. The study also investigated whether the rates returned to pre-pandemic levels by December 2021.\n\nDesignCohort study.\n\nSettingElectronic health records from UK primary care Clinical Practice Research Datalink (CPRD) GOLD database.\n\nParticipantsThe study included individuals registered with CPRD GOLD between January 2017 and December 2021, with at least 365 days of prior observation.\n\nMain outcome measuresThe study focused on screening, diagnostic tests, referrals and diagnoses of first-ever breast, colorectal, lung, and prostate cancer. Incidence rates (IR) were stratified by age, sex and region, and incidence rate ratios (IRR) were calculated to compare rates during and after lockdown with the reference period before lockdown. Forecasted rates were estimated using negative binomial regression models.\n\nResultsAmong 5,191,650 eligible participants, the initial lockdown resulted in reduced screening and diagnostic tests for all cancers, which remained dramatically reduced across the whole observation period for almost all tests investigated. For cancer incidence rates, there were significant IRR reductions in breast (0.69), colorectal (0.74), and prostate (0.71) cancers. However, the reduction in lung cancer incidence (0.92) was non-significant. Extrapolating to the entire UK population, an estimated 18,000 breast, 13,000 colorectal, 10,000 lung, and 21,000 prostate cancer diagnoses were missed from March 2020 to December 2021.\n\nConclusionThe national COVID-19 lockdown in the UK had a substantial impact on cancer screening, diagnostic tests, referrals and diagnoses. Although incidence rates started to recover after the lockdown, they remained significantly lower than pre-pandemic levels for breast and prostate cancers and associated tests. Delays in diagnosis are likely to have adverse consequences on cancer stage, treatment initiation, mortality rates, and years of life lost. Urgent strategies are needed to identify undiagnosed cases and address the long-term implications of delayed diagnoses.\n\nWHAT IS ALREADY KNOWN ON THIS TOPICO_LIBreast, colorectal, lung, and prostate cancer are the most common causes of cancer death in the UK.\nC_LIO_LIThe COVID-19 pandemic led to the postponement of cancer screening programs and reductions in diagnostic tests, resulting in delays in diagnosis and treatment initiation, impacting prognosis and mortality rates.\nC_LIO_LIComprehensive data on the impact of changing social restrictions and post-lockdown periods is lacking in the UK, along with an assessment of specific screening pathways and patient experiences within the healthcare system.\nC_LI\n\nWHAT THIS STUDY ADDSO_LIThe first UK national COVID-19 lockdown resulted in reductions in screening, diagnostic tests, and referrals, particularly for mammograms, colonoscopies, and visits to breast surgeons, leading to underdiagnosis of breast, colorectal, and prostate cancers. Despite some increase in rates after the lockdown, they remained significantly lower than pre- pandemic levels by December 2021, particularly for prostate cancer.\nC_LIO_LIMost affected populations were women aged 60-79 years for breast and colorectal cancer; men aged 60-79 years for lung cancer; and men aged 40-59 years for prostate cancer.\nC_LIO_LIDelays in diagnosis are likely to have consequences on cancer stage at diagnosis, treatment initiation, mortality rates, and total years of life lost. Strategies such as public awareness campaigns, targeted screening programs, and improved coordination between primary care and hospitals are needed to address the backlog and identify the potential [~]62,000 missed cancer cases in the UK.\nC_LI", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Camille N. Pierre", - "author_inst": "Duke University School of Medicine" - }, - { - "author_name": "Lily E. Adams", - "author_inst": "University of North Carolina Eshelman School of Pharmacy: The University of North Carolina at Chapel Hill Eshelman School of Pharmacy" - }, - { - "author_name": "Kara Anasti", - "author_inst": "Duke University School of Medicine" - }, - { - "author_name": "Derrick Goodman", - "author_inst": "Duke University School of Medicine" - }, - { - "author_name": "Sherry Stanfield-Oakley", - "author_inst": "Duke University School of Medicine" - }, - { - "author_name": "John M. Powers", - "author_inst": "University of North Carolina Eshelman School of Pharmacy: The University of North Carolina at Chapel Hill Eshelman School of Pharmacy" - }, - { - "author_name": "Dapeng Li", - "author_inst": "Duke University School of Medicine" + "author_name": "Nicola L Barclay", + "author_inst": "Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford" }, { - "author_name": "Wes Rountree", - "author_inst": "Duke University School of Medicine" + "author_name": "Marta L Pineda-Moncusi", + "author_inst": "Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford" }, { - "author_name": "Yunfei Wang", - "author_inst": "Duke University School of Medicine" + "author_name": "Annika M. Jodicke", + "author_inst": "Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford" }, { - "author_name": "Robert J. Edwards", - "author_inst": "Duke University School of Medicine" + "author_name": "Daniel Prieto-Alhambra", + "author_inst": "Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford" }, { - "author_name": "S. Munir Alam", - "author_inst": "Duke University School of Medicine" + "author_name": "Berta Raventos", + "author_inst": "Institut Universitari de Recerca en Atencio Primaria Jordi Gol i Gurina" }, { - "author_name": "Guido Ferrari", - "author_inst": "Duke University School of Medicine" + "author_name": "Danielle Newby", + "author_inst": "Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford" }, { - "author_name": "Georgia D. Tomaras", - "author_inst": "Duke University School of Medicine" + "author_name": "Antonella Delmestri", + "author_inst": "Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford" }, { - "author_name": "Barton F. Haynes", - "author_inst": "Duke University School of Medicine" + "author_name": "Wai Yi Man", + "author_inst": "Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford" }, { - "author_name": "Ralph S. Baric", - "author_inst": "University of North Carolina Eshelman School of Pharmacy: The University of North Carolina at Chapel Hill Eshelman School of Pharmacy" + "author_name": "Xihang Chen", + "author_inst": "Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford" }, { - "author_name": "Kevin Saunders", - "author_inst": "Duke Human Vaccine Institute" + "author_name": "Marti Catala", + "author_inst": "Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences (NDORMS), University of Oxford" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "immunology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.07.21.23292785", @@ -72831,7 +72682,7 @@ "author_inst": "Institute for Modeling Collaboration and Innovation, University of Idaho" }, { - "author_name": "Jennifer Johnson-Leung", + "author_name": "Benjamin J. Ridenhour", "author_inst": "Department of Mathematics and Statistical Science, University of Idaho" }, { @@ -72839,7 +72690,7 @@ "author_inst": "Department of Biological Sciences, University of Idaho" }, { - "author_name": "Benjamin J. Ridenhour", + "author_name": "Jennifer Johnson-Leung", "author_inst": "Department of Mathematics and Statistical Science, University of Idaho" } ], @@ -74309,43 +74160,23 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2023.07.21.23293001", - "rel_title": "Unraveling COVID-19 Relationship with Anxiety Disorders and Symptoms", + "rel_doi": "10.1101/2023.07.19.23292904", + "rel_title": "Social Cohesion and Covid-19: an integrative review", "rel_date": "2023-07-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.21.23293001", - "rel_abs": "BackgroundWhile COVID-19 outcomes are associated with increased anxiety, individuals affected by anxiety disorders are more likely to develop severe COVID-19 outcomes.\n\nMethodsWe used genome-wide data from UK Biobank (up to 420,531 participants), FinnGen Project (up to 329,077 participants), Million Veteran Program (175,163 participants), and COVID-19 Host Genetics Initiative (up to 122,616 cases and 2,475,240 controls) to investigate possible causal effects and shared genetic mechanisms linking COVID-19 outcomes to anxiety disorders and symptoms.\n\nResultsWe observed a strong genetic correlation of anxiety disorder with COVID-19 positive status (rg=0.35, p=2 x 10-4) and COVID-19 hospitalization (rg=0.31, p=7.2 x 10-4). Among anxiety symptoms, \"Tense, sore, or aching muscles during worst period of anxiety\" was genetically correlated with COVID-19 positive status (rg=0.33, p=0.001), while \"Frequent trouble falling or staying asleep during worst period of anxiety\" was genetically correlated with COVID-19 hospitalization (rg=0.24, p=0.004). Through a latent causal variable analysis, we observed that COVID-19 outcomes have statistically significant genetic causality proportion (gcp) on anxiety symptoms (e.g., COVID-19 positive status[->]\"Recent easy annoyance or irritability\" [boxv]gcp[boxv]=0.18, p=6.72 x 10-17). Conversely, anxiety disorders appear to have a possible causal effect on COVID-19 ([boxv]gcp[boxv]=0.38, p=3.17 x 10-9). Additionally, we also identified multiple loci with evidence of local genetic correlation between anxiety and COVID-19. These appear to be related to genetic effects shared with lung function, brain morphology, alcohol and tobacco use, and hematologic parameters.\n\nConclusionsThis study provided important insights into the relationship between COVID-19 and mental health, differentiating the dynamics linking anxiety disorders to COVID-19 from the effect of COVID-19 on anxiety symptoms.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.19.23292904", + "rel_abs": "BackgroundNations of considerable wealth and sophisticated healthcare infrastructures have seen high rates of illness and death from Covid-19. Others with limited economic means and less developed healthcare infrastructures have achieved much lower burdens. In order to build a full understanding, an appraisal of the contribution of social relationships is necessary. Social cohesion represents a promising conceptual tool.\n\nObjectiveThe aim was to examine scholarship on social cohesion during the Covid-19 pandemic: specifically - the constructions of social cohesion deployed, how it was measured, and the effects of and on social cohesion reported.\n\nMethodsThe Pubmed, Scopus and JSTOR databases were searched for relevant journal articles and grey literature. 66 studies met the inclusion criteria. Data were extracted and analysed from these using spreadsheet software.\n\nResultsSeveral constructions of social cohesion were found. These concerned interpersonal relationships; sameness and difference; collective action; perceptions/emotions of group members; structures and institutions of governance; local or cultural specificity; and hybrid/multidimensional models. Social cohesion was reported as influential on health outcomes, health behaviours, and resilience and emotional wellbeing; but also that there was some potential for it to drive undesirable outcomes. Scholarship reported increases or decreases in quantitative measures of social cohesion, a temporary rally round the flag effect early in the pandemic, the variable impacts of policy on cohesion, and changing interpersonal relationships due to pandemic conditions. There are numerous issues with the literature that reflect the well-documented limitations of popular versions of the social cohesion concept.\n\nConclusionsSocial cohesion has been used to express a range of different aspects of relationships during the pandemic. It is said to promote better health outcomes, more engagement with positive health behaviours, and greater resilience and emotional wellbeing. The literature presents a range of ways in which it has been altered by the pandemic conditions.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Zeynep Asgel", - "author_inst": "Yale University" - }, - { - "author_name": "Manuela Kouakou", - "author_inst": "Yale University" - }, - { - "author_name": "Dora Koller", - "author_inst": "Yale University" - }, - { - "author_name": "Gita A Pathak", - "author_inst": "Yale University" - }, - { - "author_name": "Brenda Cabrera-Mendoza", - "author_inst": "Yale University" - }, - { - "author_name": "Renato Polimanti", - "author_inst": "Yale University" + "author_name": "Paul Ware", + "author_inst": "The University of Auckland" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.07.21.23292988", @@ -75899,95 +75730,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.07.14.548971", - "rel_title": "Deep spatial proteomic exploration of severe COVID-19-related pulmonary injury in post-mortem specimens", + "rel_doi": "10.1101/2023.07.16.23292735", + "rel_title": "Causal association of COVID-19 with brain structure changes: Findings from a non-overlapping 2-sample Mendelian randomization study", "rel_date": "2023-07-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.07.14.548971", - "rel_abs": "The lung, as a primary target of SARS-CoV-2, exhibits heterogeneous microenvironment accompanied by various histopathological changes following virus infection. However, comprehensive insight into the protein basis of COVID-19-related pulmonary injury with spatial resolution is currently deficient. Here, we generated a region-resolved quantitative proteomic atlas of seven major pathological structures within the lungs of COVID-19 victims by integrating histological examination, laser microdissection, and ultrasensitive proteomic technologies. Over 10,000 proteins were quantified across 71 dissected FFPE post-mortem specimens. By comparison with control samples, we identified a spectrum of COVID-19-induced protein and pathway dysregulations in alveolar epithelium, bronchial epithelium, and pulmonary blood vessels, providing evidence for the proliferation of transitional-state pneumocytes. Additionally, we profiled the region-specific proteomes of hallmark COVID-19 pulmonary injuries, including bronchiole mucus plug, pulmonary fibrosis, airspace inflammation, and hyperplastic alveolar type 2 cells. Bioinformatic analysis revealed the enrichment of cell-type and functional markers in these regions (e.g. enriched TGFBI in fibrotic region). Furthermore, we identified the up-regulation of proteins associated with viral entry, host restriction, and inflammatory response in COVID-19 lungs, such as FURIN and HGF. Collectively, this study provides spatial proteomic insights for understanding COVID-19-caused pulmonary injury, and may serve as a valuable reference for improving therapeutic intervention for severe pneumonia.", - "rel_num_authors": 19, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.16.23292735", + "rel_abs": "Recent cohort studies suggested that SARS-CoV-2 infection is associated with changes in brain structure. However, the potential causal relationship remains unclear. We performed a two-sample Mendelian randomization analysis to determine whether genetic susceptibility of COVID-19 is causally associated with changes in cortical and subcortical areas of the brain. This 2-sample MR (Mendelian Randomization) study is an instrumental variable analysis of data from the COVID-19 Host Genetics Initiative (HGI) meta-analyses round 5 excluding UK Biobank participants (COVID-19 infection, N=1,348,701; COVID-19 severity, N=1,557,411), the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) Global and regional cortical measures, N=33,709; combined hemispheric subcortical volumes, N=38,851), and UK Biobank (left/right subcortical volumes, N=19,629). A replication analysis was performed on summary statistics from different COVID-19 GWAS study (COVID-19 infection, N=80,932; COVID-19 severity, N=72,733). We found that the genetic susceptibility of COVID-19 was not significantly associated with changes in brain structures, including cortical and subcortical brain structure. Similar results were observed for different (1) MR estimates, (2) COVID-19 GWAS summary statistics, and (3) definitions of COVID-19 infection and severity. This study suggests that the genetic susceptibility of COVID-19 is not causally associated with changes in cortical and subcortical brain structure.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Yiheng Mao", - "author_inst": "Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, Shenzhen" - }, - { - "author_name": "Ying Chen", - "author_inst": "CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430030, China." - }, - { - "author_name": "Yuan Li", - "author_inst": "Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, Shenzhen" - }, - { - "author_name": "Longda Ma", - "author_inst": "Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China" - }, - { - "author_name": "Xi Wang", - "author_inst": "Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, Shenzhen" - }, - { - "author_name": "Qi Wang", - "author_inst": "CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430030, China." - }, - { - "author_name": "An He", - "author_inst": "Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, Shenzhen" - }, - { - "author_name": "Xi Liu", - "author_inst": "CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430030, China." - }, - { - "author_name": "Tianyi Dong", - "author_inst": "CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430030, China." - }, - { - "author_name": "Weina Gao", - "author_inst": "Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, Shenzhen" - }, - { - "author_name": "Yanfen Xu", - "author_inst": "Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, Shenzhen" - }, - { - "author_name": "Liang Liu", - "author_inst": "Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China" - }, - { - "author_name": "Liang Ren", - "author_inst": "Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China" - }, - { - "author_name": "Qian Liu", - "author_inst": "CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430030, China." - }, - { - "author_name": "Peng Zhou", - "author_inst": "CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430030, China." - }, - { - "author_name": "Ben Hu", - "author_inst": "CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430030, China." - }, - { - "author_name": "Yiwu Zhou", - "author_inst": "Department of Forensic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China" - }, - { - "author_name": "Ruijun Tian", - "author_inst": "Department of Chemistry and Research Center for Chemical Biology and Omics Analysis, College of Science, Southern University of Science and Technology, Shenzhen" + "author_name": "Pingjian Ding", + "author_inst": "Case Western Reserve University" }, { - "author_name": "Zheng-Li Shi", - "author_inst": "CAS Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, 430030, China." + "author_name": "Rong Xu", + "author_inst": "Case Western Reserve University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "systems biology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.07.14.549113", @@ -77569,49 +77332,45 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2023.07.12.23292570", - "rel_title": "COVID-19 Case and Mortality Surveillance using Daily SARS-CoV-2 in Wastewater Samples adjusting for Meteorological Conditions and Sample pH", + "rel_doi": "10.1101/2023.07.12.23292559", + "rel_title": "Risk Factors for Admission into COVID-19 General Wards, Sub-Intensive and Intensive Care Units among SARS-CoV-2 Positive Subjects in the Municipality of Bologna, Italy", "rel_date": "2023-07-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.12.23292570", - "rel_abs": "BackgroundWastewater monitoring is increasingly used for community surveillance of infectious diseases, especially after the COVID-19 pandemic as the genomic footprints of pathogens shed by infected individuals can be traced in the environment. However, detection and concentration of pathogens in the environmental samples and their efficacy in predicting infectious diseases can be influenced by meteorological conditions and quality of samples.\n\nObjectivesThis research examines whether meteorological conditions and sample pH affect SARS-CoV-2 concentrations in wastewater samples, and whether the association of SARS-CoV-2 with COVID-19 cases and mortality improves when adjusted for meteorological conditions and sample pH value in Miami-Dade County, FL.\n\nMethodsDaily wastewater samples were collected from Miami-Dade Wastewater Treatment Plant in Key Biscayne, Florida from August 2021 to August 2022. The samples were analyzed for pH and spiked with OC43. RNA was extracted from the concentrated wastewater sample and SARS-CoV-2 was quantified using qPCR. COVID-19 and mortality data were acquired from the Centers for Disease Control and Prevention (CDC) and meteorological data from the National Climatic Data Center. COVID-19 case and mortality rates were modelled with respect to time-lagged wastewater SARS-CoV-2 adjusting for meteorological conditions, and sample pH value and OC43 recovery.\n\nResultsTemperature, dew point, pH values and OC43 recovery showed significant associations with wastewater SARS-CoV-2. Time-lagged wastewater SARS-CoV-2 showed significant associations with COVID-19 case and mortality incidence rates. This association improved when wastewater SARS-CoV-2 levels were adjusted for (or instrumented on) meteorological conditions, OC43 recovery, and sample pH. A 0.47% change in COVID-19 case incidence rate was associated with 1% change in wastewater SARS-CoV-2 ({beta} [~] 0.47; 95% CI = 0.29 - 0.64; p < 0.001). A 0.12 % change in COVID-19 mortality rate was associated with 1 % change in SARS-CoV-2 in wastewater 44 days prior. A 0.07% decline in COVID-19 mortality rate was associated with a unit increase in ambient temperature 28 days prior.\n\nDiscussionTime lagged wastewater SARS-CoV-2 (and its adjustment for sample pH and RNA recovery) and meteorological conditions can be used for the surveillance of COVID-19 case and mortality. These findings can be extrapolated to improve the surveillance of other infectious diseases by proactive measurements of infectious agent(s) in the wastewater samples, adjusting for meteorological conditions and sample pH value.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.12.23292559", + "rel_abs": "This is a retrospective cohort study aimed at identifying the risk factors for the hospitalization of patients with COVID-19 in the municipality of Bologna. A total of 32500 patients that tested positive for COVID-19 from February 28/2020 to October 13/2021 in the municipality of Bologna were included. The Kaplan-Meier method was used to estimate changes during time of ICU hospitalization for all patients as well as stratifying subjects by sex. A multi-state Coxs proportional hazard model was fitted to investigate predictors of ICU and non-ICU hospitalization. Age, sex, calendar period of diagnosis, comorbidities and vaccination status of patients at the time of diagnosis were considered as candidate predictors. In general, male sex and advanced age resulted to be poor prognostic factors of COVID-19 outcomes. An exception was found for the over 80 age group which showed a decrease in the risk of ICU hospitalization compared to 70-79 (HR 0.57 95% CI 0.36 - 0.90 for DIAG[->]ICU; HR 0.40 95% CI 0.28 - 0.58 for HOSP[->]ICU). Having contracted the disease during the first wave was associated with a significant greater risk of hospitalization than during the second wave, while no difference in the risk of ICU admission was found between the second and third waves. Fully immunized patients showed a significant decrease in the risk of ICU and non-ICU hospitalization compared to the unvaccinated patients (HR 0.23 95% CI 0.16 - 0.31 for DIAG[->]HOSP; HR 0.10 95% CI 0.01 - 0.73 for DIAG[->]ICU). Chronic kidney failure and asthma were risk factors for non-ICU hospitalization. Diabetes and embolism were risk factors for both direct ICU and non-ICU hospitalization. The study of factors associated with a negative course of the COVID-19 disease allows to prevent fatal outcomes, establish priorities in the treatment of the disease and improve the management of hospital resources and the pandemic itself.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Abelson Samantha", - "author_inst": "University of Miami" + "author_name": "Sofia Raponi", + "author_inst": "Department of Physics and Astronomy, University of Bologna, Bologna, Italy" }, { - "author_name": "Bader Alsuliman", - "author_inst": "University of Miami" + "author_name": "Francesco Durazzi", + "author_inst": "Department of Physics and Astronomy, University of Bologna, Bologna, Italy" }, { - "author_name": "Jonathon Penso", - "author_inst": "University of Miami" - }, - { - "author_name": "Kristina Babler", - "author_inst": "University of Miami" + "author_name": "Nicolas Riccardo Derus", + "author_inst": "University of Bologna" }, { - "author_name": "Mark Sharkey", - "author_inst": "University of Miami" + "author_name": "Enrico Giampieri", + "author_inst": "Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy" }, { - "author_name": "Christopher Mason", - "author_inst": "Cornell University" + "author_name": "Rossella Miglio", + "author_inst": "Department of Statistical Sciences, University of Bologna, Bologna, Italy" }, { - "author_name": "George S. Grills", - "author_inst": "University of Miami" + "author_name": "Gastone Castellani", + "author_inst": "Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy" }, { - "author_name": "Helena Solo-Gabriele", - "author_inst": "University of Miami" + "author_name": "Claudia Sala", + "author_inst": "Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy" }, { - "author_name": "Naresh Kumar", - "author_inst": "University of Miami" + "author_name": "- Bologna MODELS4COVID Study Group", + "author_inst": "-" } ], "version": "1", @@ -79311,79 +79070,119 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2023.07.05.23292278", - "rel_title": "Intracardiac Thrombus in COVID-19 Inpatients: A Nationwide Study of Incidence, Predictors and Outcomes", + "rel_doi": "10.1101/2023.07.05.23291954", + "rel_title": "Immunogenicity and safety of heterologous Omicron BA.1 and bivalent SARS-CoV-2 recombinant spike protein booster vaccines: a phase 3, randomized, clinical trial", "rel_date": "2023-07-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.05.23292278", - "rel_abs": "BackgroundCOronaVIrus Disease 2019 (COVID-19) has been observed to be associated with a hypercoagulable state. Intracardiac thrombosis is a serious complication but has seldom been evaluated in COVID-19 patients. We assessed the incidence, associated factors, and outcomes of COVID-19 patients with intracardiac thrombosis.\n\nMethodsCOVID-19 inpatients during 2020 were retrospectively identified from the national inpatient sample (NIS) database, and data retrieved regarding clinical characteristics, intracardiac thrombosis, and adverse outcomes. Multivariable logistic regression was performed to identify the clinical factors associated with intracardiac thrombosis and in-hospital mortality and morbidities.\n\nResultsA total of 1,683,785 COVID-19 inpatients were identified in 2020 from NIS, with a mean age of 63.8 {+/-} 1.6 years, and 32.2% females. Intracardiac thrombosis was present in 0.001% (1,830) patients. Overall, in-hospital outcomes include all-cause mortality 13.2% (222,695/1,683,785), cardiovascular mortality 3.5%, cardiac arrest 2.6%, acute coronary syndrome (ACS) 4.4%, heart failure 16.1%, stroke 1.3% and acute kidney injury (AKI) 28.3%. The main factors associated with intracardiac thrombosis were a history of congestive heart failure and coagulopathy. Intracardiac thrombosis was independently associated with a higher risk of in-hospital all-cause mortality (OR: 3.32, 95% CI: 2.42-4.54, p<0.001), cardiovascular mortality (OR: 2.95, 95% CI: 1.96-4.44, p<0.001), cardiac arrest (OR: 2.04, 95% CI: 1.22-3.43, p=0.006), ACS (OR: 1.62, 95% CI: 1.17-2.22, p=0.003), stroke (OR: 3.10, 95% CI: 2.11-4.56, p<0.001), and AKI (OR: 2.13 95% CI: 1.68-2.69, p<0.001), but not incident heart failure (p=0.27).\n\nConclusionAlthough intracardiac thrombosis is rare in COVID-19 inpatients, its presence was independently associated with higher risks of in-hospital mortality and most morbidities. Prompt investigations and treatments for intracardiac thrombosis are warranted when there is a high index of suspicion and a confirmed diagnosis respectively.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.07.05.23291954", + "rel_abs": "BackgroundMutations present in emerging SARS-CoV-2 variants permit evasion of neutralization with prototype vaccines. A novel Omicron BA.1 subvariant-specific vaccine (NVX-CoV2515) was tested alone, or as a bivalent preparation in combination with the prototype vaccine (NVX-CoV2373), to assess antibody responses to SARS-CoV-2.\n\nMethodsParticipants aged 18 to 64 years immunized with 3 doses of prototype mRNA vaccines were randomized 1:1:1 to receive a single dose of NVX-CoV2515, NVX-CoV2373, or bivalent mixture in a phase 3 study investigating heterologous boosting with SARS-CoV-2 recombinant spike protein vaccines. Immunogenicity was measured 14 and 28 days after vaccination for the SARS-CoV-2 Omicron BA.1 sublineage and ancestral strain. Safety profiles of vaccines were assessed.\n\nResultsOf participants who received trial vaccine (N=829), those administered NVX-CoV2515 (n=286) demonstrated superior neutralizing antibody response to BA.1 versus NVX-CoV2373 (n=274) at Day 14 (geometric mean titer ratio [95% CI]: 1.6 [1.33, 2.03]). Seroresponse rates [n/N; 95% CI] were 73.4% [91/124; 64.7, 80.9] for NVX-CoV2515 versus 50.9% [59/116; 41.4, 60.3] for NVX-CoV2373. All formulations were similarly well-tolerated.\n\nConclusionsNVX-CoV2515 elicited a superior neutralizing antibody response against the Omicron BA.1 subvariant compared with NVX-CoV2373 when administered as a fourth dose. Safety data were consistent with the established safety profile of NVX-CoV2373.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Ankit Agrawal", - "author_inst": "Cleveland Clinic" + "author_name": "Chijioke Bennett", + "author_inst": "Novavax, Inc." }, { - "author_name": "Suryansh Bajaj", - "author_inst": "University of Arkansas for Medical Sciences" + "author_name": "E. Joy Rivers", + "author_inst": "Novavax, Inc." }, { - "author_name": "Umesh Bhagat", - "author_inst": "Cleveland Clinic Foundation" + "author_name": "Wayne Woo", + "author_inst": "Novavax, Inc." }, { - "author_name": "Sanya Chandna", - "author_inst": "Cleveland Clinic Foundation" + "author_name": "Mark Bloch", + "author_inst": "Holdsworth House Medical Practice; University of New South Wales" }, { - "author_name": "Aro Daniela Arockiam", - "author_inst": "Cleveland Clinic Foundation" + "author_name": "King Cheung", + "author_inst": "Emeritus Research" }, { - "author_name": "Nicholas Chan", - "author_inst": "Columbia University Irving Medical Center, New York Presbyterian Hospital" + "author_name": "Paul Griffin", + "author_inst": "Mater Misericordiae Ltd; University of Queensland" }, { - "author_name": "Elio Haroun", - "author_inst": "Cleveland Clinic Foundation" + "author_name": "Rahul Mohan", + "author_inst": "Paratus Clinical Research Western Sydney" }, { - "author_name": "Rahul Gupta", - "author_inst": "Lehigh Valley Health Network" + "author_name": "Sachin Deshmukh", + "author_inst": "Griffith University" }, { - "author_name": "Osamah Badwan", - "author_inst": "Cleveland Clinic" + "author_name": "Mark Arya", + "author_inst": "Australian Clinical Research Network" }, { - "author_name": "Shashank Shekhar", - "author_inst": "Cleveland Clinic" + "author_name": "Oscar Cumming", + "author_inst": "Novatrials" }, { - "author_name": "Shivabalan Kathavarayan Ramu", - "author_inst": "Cleveland Clinic" + "author_name": "A. Munro Neville", + "author_inst": "AusTrials" }, { - "author_name": "Divya Nayar", - "author_inst": "University of Arkansas for Medical Sciences" + "author_name": "Toni McCallum Pardey", + "author_inst": "Novatrials" }, { - "author_name": "Wael A. Jaber", - "author_inst": "The Cleveland Clinic" + "author_name": "Joyce S. Plested", + "author_inst": "Novavax, Inc." }, { - "author_name": "Brian P. Griffin", - "author_inst": "Cleveland Clinic Foundation" + "author_name": "Shane Cloney-Clark", + "author_inst": "Novavax, Inc." }, { - "author_name": "Tom Kai Ming Wang", - "author_inst": "Cleveland Clinic" + "author_name": "Mingzhu Zhu", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Raj Kalkeri", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Nita Patel", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Agi Buchanan", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Alex Marcheschi", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Jennifer Swan", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Gale Smith", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Iksung Cho", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Gregory M. Glenn", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Robert Walker", + "author_inst": "Novavax, Inc." + }, + { + "author_name": "Raburn Mallory", + "author_inst": "Novavax, Inc." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.07.03.23292126", @@ -81533,127 +81332,71 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2023.06.29.546885", - "rel_title": "Interaction between host G3BP and viral nucleocapsid protein regulates SARS-CoV-2 replication", + "rel_doi": "10.1101/2023.06.30.23292079", + "rel_title": "Synthesis and new evidence from the PROTECT UK National Core Study: Determining occupational risks of SARS-CoV-2 infection and COVID-19 mortality", "rel_date": "2023-06-30", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.29.546885", - "rel_abs": "G3BP1/2 are paralogous proteins that promote stress granule formation in response to cellular stresses, including viral infection. G3BP1/2 are prominent interactors of the nucleocapsid (N) protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the functional consequences of the G3BP1-N interaction in the context of viral infection remain unclear. Here we used structural and biochemical analyses to define the residues required for G3BP1-N interaction, followed by structure-guided mutagenesis of G3BP1 and N to selectively and reciprocally disrupt their interaction. We found that mutation of F17 within the N protein led to selective loss of interaction with G3BP1 and consequent failure of the N protein to disrupt stress granule assembly. Introduction of SARS-CoV-2 bearing an F17A mutation resulted in a significant decrease in viral replication and pathogenesis in vivo, indicating that the G3BP1-N interaction promotes infection by suppressing the ability of G3BP1 to form stress granules.", - "rel_num_authors": 27, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.30.23292079", + "rel_abs": "IntroductionThe PROTECT National Core Study was funded by the UK Health and Safety Executive (HSE) to investigate routes of transmission for SARS-CoV-2 and variation between settings.\n\nMethodsA workshop was organised in Oct 2022.We brought together evidence from five published epidemiological studies that compared risks of SARS-CoV-2 infection or COVID-19 mortality by occupation or sector funded by PROTECT relating to three non-overlapping data sets, plus additional unpublished analyses relating to the Omicron period. We extracted descriptive study level data and model results. We investigated risk across four pandemic waves using forest plots for key occupational groups by time-period.\n\nResultsResults were largely consistent across different studies with different expected biases. Healthcare and social care sectors saw elevated risks of SARS-CoV-2 infection and COVID-19 mortality early in the pandemic, but thereafter this declined and varied by specific occupational subgroup. The education sector saw sustained elevated risks of infection after the initial lockdown period with little evidence of elevated mortality.\n\nConclusionsIncreased in risk of infection and mortality were consistently observed for occupations in high risk sectors particularly during the early stage of the pandemic. The education sector showed a different pattern compared to the other high risk sectors, as relative risk of infections remained high in the later phased of the pandemic, although no increased in COVID-19 mortality (compared to low-risk occupations) was observed in this sector in any point during the pandemic.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Zemin Yang", - "author_inst": "St. Jude Children's Research Hospital" - }, - { - "author_name": "Bryan A. Johnson", - "author_inst": "University of Texas Medical Branch, Galveston" - }, - { - "author_name": "Victoria A. Meliopoulos", - "author_inst": "St. Jude Children's Research Hospital" - }, - { - "author_name": "Xiaohui Ju", - "author_inst": "Tsinghua University" - }, - { - "author_name": "Peipei Zhang", - "author_inst": "St. Jude Children's Research Hospital" - }, - { - "author_name": "Michael P. Hughes", - "author_inst": "St. Jude Children's Research Hospital" - }, - { - "author_name": "Jinjun Wu", - "author_inst": "St. Jude Children's Research Hospital" - }, - { - "author_name": "Kaitlin P. Koreski", - "author_inst": "St. Jude Children's Research Hospital" - }, - { - "author_name": "Ti-Cheng Chang", - "author_inst": "St. Jude Children's Research Hospital" - }, - { - "author_name": "Gang Wu", - "author_inst": "St Jude Children's Research Hospital" - }, - { - "author_name": "Jeff Hixon", - "author_inst": "Faze Medicines" - }, - { - "author_name": "Jay Duffner", - "author_inst": "Faze Medicines" - }, - { - "author_name": "Kathy Wong", - "author_inst": "Faze Medicines" - }, - { - "author_name": "Rene Lemieux", - "author_inst": "Faze Medicines" - }, - { - "author_name": "Kumari G. Lokugamage", - "author_inst": "University of Texas Medical Branch, Galveston" + "author_name": "Sarah Rhodes", + "author_inst": "University of Manchester" }, { - "author_name": "Rojelio E. Alvardo", - "author_inst": "University of Texas Medical Branch, Galveston" + "author_name": "Sarah Beale", + "author_inst": "University College London" }, { - "author_name": "Patricia A. Crocquet-Valdes", - "author_inst": "University of Texas Medical Branch, Galveston" + "author_name": "Mark Cherrie", + "author_inst": "Institute of Occupational Medicine" }, { - "author_name": "David H. Walker", - "author_inst": "University of Texas Medical Branch, Galveston" + "author_name": "William Mueller", + "author_inst": "Institute of Occupational Medicine" }, { - "author_name": "Kenneth S. Plante", - "author_inst": "University of Texas Medical Branch, Galveston" + "author_name": "Fiona Holland", + "author_inst": "University of Manchester" }, { - "author_name": "Jessica A. Plante", - "author_inst": "University of Texas Medical Branch, Galveston" + "author_name": "Melissa Matz", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Scott C. Weaver", - "author_inst": "University of Texas Medical Branch, Galveston" + "author_name": "Ioannis Basinas", + "author_inst": "University of Manchester" }, { - "author_name": "Hong Joo Kim", - "author_inst": "St. Jude Children's Research Hospital" + "author_name": "Jack D Wilkinson", + "author_inst": "University of Manchester" }, { - "author_name": "Rachel Meyers", - "author_inst": "Faze Medicines" + "author_name": "Matthew Gittins", + "author_inst": "University of Manchester" }, { - "author_name": "Stacey Schultz-Cherry", - "author_inst": "St. Jude Children's Research Hospital" + "author_name": "Bernardine Farrell", + "author_inst": "University of Manchester" }, { - "author_name": "Qiang Ding", - "author_inst": "Tsinghua University" + "author_name": "Andrew Hayward", + "author_inst": "UCL" }, { - "author_name": "Vineet D Menachery", - "author_inst": "University of Texas Medical Branch" + "author_name": "Neil Pearce", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "J Paul Taylor", - "author_inst": "St. Jude Children's Research Hospital" + "author_name": "Martie van Tongeren", + "author_inst": "University of Manchester" } ], "version": "1", - "license": "cc_by_nd", - "type": "new results", - "category": "cell biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2023.06.29.23292043", @@ -83515,63 +83258,51 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2023.06.27.23291947", - "rel_title": "Examining the inter-relationships between social isolation and loneliness and their correlates among older British adults before and during the COVID-19 lockdown: evidence from four British longitudinal studies", + "rel_doi": "10.1101/2023.06.27.23291933", + "rel_title": "mRNA-1273 vaccine effectiveness against symptomatic SARS-CoV-2 infection and COVID-19-related hospitalization in children aged 6 months to 5 years", "rel_date": "2023-06-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.27.23291947", - "rel_abs": "Background and ObjectivesUnprecedented social restrictions during the COVID-19 pandemic have provided a new lens for considering the inter-relationship between social isolation and loneliness in later life. We present these inter-relationships before and during the COVID-19 restrictions and investigate to what extent demographic, socio-economic, and health factors associated with such experiences differed during the pandemic.\n\nResearch Design and MethodWe used data from four British longitudinal population-based studies (1946 MRC NSHD, 1958 NCDS, 1970 BCS, and ELSA). Rates, co-occurrences, and correlates of social isolation and loneliness are presented prior to and during the early stage of the COVID-19 pandemic and the inter-relationships between these experiences are elucidated in both periods.\n\nResultsAcross the four studies, pre-pandemic proportions reporting social isolation ranged from 15 to 54%, with higher rates in older ages (e.g., 32% of 70-79 and 54% of those over 80). During the pandemic, the percentage of older people reporting both social isolation and loneliness and isolation only slightly increased. The inter-relationship between social isolation and loneliness did not change. Associations between socio-demographic and health characteristics and social isolation and loneliness also remained consistent, with greater burden among those with greater economic precarity (females, non-homeowners, unemployed, illness and greater financial stress).\n\nDiscussion and ImplicationsThere were already large inequalities in experiences of social isolation and loneliness and the pandemic had a small impact on worsening these inequalities. The concepts of loneliness and social isolation are not transferable and clarity is needed in how they are conceptualised, operationalised, and interpreted.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.27.23291933", + "rel_abs": "ImportanceData on mRNA-1273 (Moderna) vaccine effectiveness in children aged 6 months to 5 years are limited.\n\nObjectiveTo assess mRNA-1273 vaccine effectiveness against symptomatic SARS-CoV-2 infection and COVID-19-related hospitalization among children aged 6 months to 5 years.\n\nDesign, Setting, and ParticipantsA test-negative study using linked health administrative data in Ontario, Canada. Participants included symptomatic children aged 6 months to 5 years who were tested by RT-PCR.\n\nExposuresmRNA-1273 vaccination.\n\nMain Outcomes and MeasuresSymptomatic SARS-CoV-2 infection and COVID-19-related hospitalization.\n\nResultsWe included 3467 test-negative controls and 572 test-positive cases. Receipt of mRNA-1273 was associated with reduced symptomatic SARS-CoV-2 infection (VE=90%; 95%CI: 53, 99%) and COVID-19-related hospitalization (VE=82%; 95%CI: 4, 99%) [≥]7 days after the second dose.\n\nConclusions and RelevanceOur findings suggest mRNA-1273 vaccine effectiveness is initially strong against symptomatic SARS-CoV-2 infection and hospitalization in children aged 6 months to 5 years. Further research is needed to understand long-term effectiveness and the need for booster doses.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Rosie Mansfield", - "author_inst": "University College London" - }, - { - "author_name": "Giorgio Di Gessa", - "author_inst": "University College London" - }, - { - "author_name": "Kishan Patel", - "author_inst": "MRC LHA" - }, - { - "author_name": "Eoin McElroy", - "author_inst": "Ulster University" + "author_name": "Mary Aglipay", + "author_inst": "Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Jacques Wels", - "author_inst": "University College London" + "author_name": "Jonathon L Maguire", + "author_inst": "Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Morag Henderson", - "author_inst": "University College London" + "author_name": "Sarah Swayze", + "author_inst": "ICES, Toronto, Ontario, Canada" }, { - "author_name": "Jane Maddock", - "author_inst": "UCL" + "author_name": "Ashleigh Tuite", + "author_inst": "Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Jean Stafford", - "author_inst": "University College London" + "author_name": "Muhammad Mamdani", + "author_inst": "Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Andrew Steptoe", - "author_inst": "UCL: University College London" + "author_name": "Charles Keown-Stoneman", + "author_inst": "Li Ka Shing Knowledge Institute, St. Michael's Hospital, Unity Health Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Marcus Richards", - "author_inst": "University College London" + "author_name": "Catherine S Birken", + "author_inst": "Child Health Evaluative Sciences, The Hospital for Sick Children Research Institute, Toronto, Ontario, Canada" }, { - "author_name": "Praveetha Patalay", - "author_inst": "University College London" + "author_name": "Jeffrey C Kwong", + "author_inst": "Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.06.27.545921", @@ -84949,33 +84680,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.06.16.23291442", - "rel_title": "Vaccines at Velocity: Evaluating Potential Lives Saved by Earlier Vaccination in the COVID-19 Pandemic", + "rel_doi": "10.1101/2023.06.19.23291622", + "rel_title": "Inpatient Antibacterial Drug Prescribing for Patients with COVID-19 in Hong Kong", "rel_date": "2023-06-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.16.23291442", - "rel_abs": "Fast development of COVID-19 vaccines likely averted millions of deaths. We estimate how many more lives could have been saved if safe and effective vaccines were available earlier in the pandemic, in particular, before the epidemic waves in winter of 2020. We fit an epidemiological model informed by retrospective data and simulate counterfactual vaccination scenarios for the United Kingdom and the United States in which vaccines are available between 30 and 90 days earlier. We find that up to 1 July 2021 reductions in mortality range from 10,000 to 48,000 in the UK and 53,000 to 130,000 in the US, depending on when vaccinations start. This corresponds to a maximum of 7.1 and 4 deaths averted per 10,000 people in the UK and US respectively, or a reduction in overall deaths of 50% and 32%. We find that our model is sensitive to uncertain vaccine parameters and benefits depend on the time horizon of the analysis. However, the large average reductions we estimate suggests that it is highly cost-effective to make large investments in strategies to expedite vaccine availability.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.19.23291622", + "rel_abs": "BackgroundHong Kong experienced four epidemic waves caused by the ancestral strain of SARS-CoV-2 in 2020-2021 and a large Omicron wave in 2022. Few studies have assessed antibacterial drug prescribing for COVID-19 inpatients throughout the pandemic.\n\nObjectivesTo describe inpatient antibacterial drug prescribing for COVID-19 patients throughout the pandemic and to determine factors associated with their prescription.\n\nMethodsThis cohort study used electronic health records of COVID-19 cases admitted to public hospitals in Hong Kong from 21 January 2020 to 30 September 2022. We assessed the prevalence and rates of inpatient antibacterial drug use, using days of therapy/1000 patient days (DOT/1000PD), and examined the association of baseline factors and disease severity with receipt of an inpatient antibacterial drug prescription.\n\nResultsAmong 65,810 inpatients, 54.0% were prescribed antibacterial drugs at a rate of 550.5 DOT/1000PD. Antibacterial use was lowest during wave 4 (28.0%; 246.9 DOT/1000PD), peaked in early wave 5 (64.6%; 661.2 DOT/1000PD), and then modestly declined in late wave 5 (43.2%; 464.1 DOT/1000PD) starting on 23 May 2022.\n\nOlder age, increased disease severity, and residing in an elderly care home were strongly associated with increased odds of prescription, while receiving [≥] 2 doses of COVID-19 vaccines and pre-admission use of coronavirus antivirals were associated with lower odds.\n\nConclusionsThe rate of inpatient antibacterial prescribing initially declined during the pandemic, but increased during the Omicron wave when hospital capacity was overwhelmed. Despite the availability of COVID-19 vaccines and antiviral drugs, antibacterial drug use among COVID-19 inpatients remained high into late 2022.\n\nHIGHLIGHTSO_LIThe prevalence of antibacterial drug use in hospitalized COVID-19 cases in Hong Kong declined gradually during the first four COVID-19 epidemic waves to 28.0%, but increased to 64.6% with the spread of the Omicron variant in early 2022.\nC_LIO_LIThe majority of antibacterial drug prescriptions were for Access and Watch drugs, with limited use of combination therapy or macrolides.\nC_LIO_LIOlder age and more severe disease were strongly associated with an inpatient antibacterial drug prescription, while vaccination and initiation of COVID-19-specific antivirals reduced the odds of antibacterial prescription.\nC_LIO_LIDespite moderate-to-high levels of vaccine coverage and the availability of antiviral drugs, 43% of COVID-19 inpatients still received antibacterial drugs in late 2022.\nC_LI", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Witold Wiecek", - "author_inst": "1Day Sooner, Delaware, United States" + "author_name": "Joseph E Blais", + "author_inst": "The University of Hong Kong" }, { - "author_name": "David Johnston", - "author_inst": "1Day Sooner, Delaware, United States" + "author_name": "Weixin Zhang", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Tomas Dulka", - "author_inst": "1Day Sooner, Delaware, United States" + "author_name": "Yun Lin", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Danny Toomey", - "author_inst": "1Day Sooner, Delaware, United States" + "author_name": "Celine S.L. Chui", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Vincent Chi-Chung Cheng", + "author_inst": "Department of Microbiology, Queen Mary Hospital" }, { - "author_name": "Enlli Lewis", - "author_inst": "1Day Sooner, Delaware, United States" + "author_name": "Benjamin J Cowling", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Peng Wu", + "author_inst": "The University of Hong Kong" } ], "version": "1", @@ -86871,163 +86610,31 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2023.06.14.544834", - "rel_title": "Immunogenicity of COVID-19 vaccines and their effect on the HIV reservoir in older people with HIV", + "rel_doi": "10.1101/2023.06.14.23291388", + "rel_title": "Association between vaccination rates and severe COVID-19 health outcomes in the United States: a population-level statistical analysis", "rel_date": "2023-06-15", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.14.544834", - "rel_abs": "Older individuals and people with HIV (PWH) were prioritized for COVID-19 vaccination, yet comprehensive studies of the immunogenicity of these vaccines and their effects on HIV reservoirs are not available. We followed 68 PWH aged 55 and older and 23 age-matched HIV-negative individuals for 48 weeks from the first vaccine dose, after the total of three doses. All PWH were on antiretroviral therapy (cART) and had different immune status, including immune responders (IR), immune non-responders (INR), and PWH with low-level viremia (LLV). We measured total and neutralizing Ab responses to SARS-CoV-2 spike and RBD in sera, total anti-spike Abs in saliva, frequency of anti-RBD/NTD B cells, changes in frequency of anti-spike, HIV gag/nef-specific T cells, and HIV reservoirs in peripheral CD4+ T cells. The resulting datasets were used to create a mathematical model for within-host immunization. Various regimens of BNT162b2, mRNA-1273, and ChAdOx1 vaccines elicited equally strong anti-spike IgG responses in PWH and HIV- participants in serum and saliva at all timepoints. These responses had similar kinetics in both cohorts and peaked at 4 weeks post-booster (third dose), while half-lives of plasma IgG also dramatically increased post-booster in both groups. Salivary spike IgA responses were low, especially in INRs. PWH had diminished live virus neutralizing titers after two vaccine doses which were rescued after a booster. Anti-spike T cell immunity was enhanced in IRs even in comparison to HIV- participants, suggesting Th1 imprinting from HIV, while in INRs it was the lowest. Increased frequency of viral blips in PWH were seen post-vaccination, but vaccines did not affect the size of the intact HIV reservoir in CD4+ T cells in most PWH, except in LLVs. Thus, older PWH require three doses of COVID-19 vaccine to maximize neutralizing responses against SARS-CoV-2, although vaccines may increase HIV reservoirs in PWH with persistent viremia.", - "rel_num_authors": 36, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.14.23291388", + "rel_abs": "Population-level vaccine efficacy is a critical component of understanding COVID-19 risk, informing public health policy, and mitigating disease impacts. Unlike individual-level clinical trials, population-level analysis characterizes how well vaccines worked in the face of real-world challenges like emerging variants, differing mobility patterns, and policy changes. In this study, we analyze the association between time-dependent vaccination rates and COVID-19 health outcomes for 48 U.S. states. We primarily focus on case-hospitalization risk (CHR) as the outcome of interest, using it as a population-level proxy for disease burden on healthcare systems. Performing the analysis using Generalized Additive Models (GAMs) allowed us to incorporate real-world nonlinearities and control for critical dynamic (time-changing) and static (temporally constant) factors. Dynamic factors include testing rates, activity-related engagement levels in the population, underlying population immunity, and policy. Static factors incorporate comorbidities, social vulnerability, race, and state healthcare expenditures. We used SARS-CoV-2 genomic surveillance data to model the different COVID-19 variant-driven waves separately, and evaluate if there is a changing role of the potential drivers of health outcomes across waves. Our study revealed a strong and statistically significant negative association between vaccine uptake and COVID-19 CHR across each variant wave, with boosters providing additional protection during the Omicron wave. Higher underlying population immunity is shown to be associated with reduced COVID-19 CHR. Additionally, more stringent government policies are generally associated with decreased CHR. However, the impact of activity-related engagement levels on COVID-19 health outcomes varied across different waves. Regarding static variables, the social vulnerability index consistently exhibits positive associations with CHR, while Medicaid spending per person consistently shows a negative association. However, the impacts of other static factors vary in magnitude and significance across different waves. This study concludes that despite the emergence of new variants, vaccines remain highly correlated with reduced COVID-19 harm. Therefore, given the ongoing threat posed by COVID-19, vaccines remain a critical line of defense for protecting the public and reducing the burden on healthcare systems.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Vitaliy A. Matveev", - "author_inst": "University of Toronto" - }, - { - "author_name": "Erik Z. Mihelic", - "author_inst": "University of Toronto" - }, - { - "author_name": "Erika Benko", - "author_inst": "Maple Leaf Medical Clinic" - }, - { - "author_name": "Patrick Budylowski", - "author_inst": "University of Toronto" - }, - { - "author_name": "Sebastian Grocott", - "author_inst": "McGill University" - }, - { - "author_name": "Terry Lee", - "author_inst": "CIHR Canadian HIV Trials Network (CTN)" - }, - { - "author_name": "Chapin S. Korosec", - "author_inst": "York University" - }, - { - "author_name": "Karen Colwill", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Henry Stephenson", - "author_inst": "McGill University" - }, - { - "author_name": "Ryan Law", - "author_inst": "University of Toronto" - }, - { - "author_name": "Lesley A. Ward", - "author_inst": "University of Toronto" - }, - { - "author_name": "Salma Sheikh-Mohamed", - "author_inst": "University of Toronto" - }, - { - "author_name": "Genevi\u00e8ve Mailhot", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Melanie Delgado-Brand", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Adrian Pasculescu", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Jenny H. Wang", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Freda Qi", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Tulunay Tursun", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" - }, - { - "author_name": "Lela Kardava", - "author_inst": "National Institute of Allergy and Infectious Diseases (NIAID)" - }, - { - "author_name": "Serena Chau", - "author_inst": "University of Toronto" - }, - { - "author_name": "Philip Samaan", - "author_inst": "University of Toronto" - }, - { - "author_name": "Annam Imran", - "author_inst": "University of Toronto" - }, - { - "author_name": "Dennis C. Copertino Jr.", - "author_inst": "Weill Cornell Medicine" - }, - { - "author_name": "Gary Chao", - "author_inst": "University of Toronto" - }, - { - "author_name": "Yoojin Choi", - "author_inst": "University of Toronto" - }, - { - "author_name": "Robert J. Reinhard", - "author_inst": "Independent Public/Global Health Consultant" - }, - { - "author_name": "Rupert Kaul", - "author_inst": "University of Toronto" - }, - { - "author_name": "Jane M. Heffernan", - "author_inst": "York University" - }, - { - "author_name": "R. Brad Jones", - "author_inst": "Weill Cornell Medical College" - }, - { - "author_name": "Tae-Wook Chun", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Susan Moir", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Joel Singer", - "author_inst": "The University of British Columbia" - }, - { - "author_name": "Jen Gommerman", - "author_inst": "University of Toronto" - }, - { - "author_name": "Anne-Claude Gingras", - "author_inst": "Lunenfeld-Tanenbaum Research Institute" + "author_name": "Hongru Du", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Colin Kovacs", - "author_inst": "Maple Leaf Medical Clinic" + "author_name": "Samee Saiyed", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Mario Ostrowski", - "author_inst": "University of Toronto" + "author_name": "Lauren Marie Gardner", + "author_inst": "Johns Hopkins University" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.06.14.23291375", @@ -88713,41 +88320,37 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2023.06.07.23290927", - "rel_title": "SARS-CoV-2 infections among 12 000 pregnant women, 2020, Finland - cross-testing of neutralization assays", + "rel_doi": "10.1101/2023.06.08.23291050", + "rel_title": "Quantitatively assessing early detection strategies for mitigating COVID-19 and future pandemics", "rel_date": "2023-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.07.23290927", - "rel_abs": "We studied the development of SARS-CoV-2 pandemic in Finland in 2020 and evaluated the performance of two surrogate immunoassays for detection of neutralizing antibodies (NAbs). The dataset consisted of 12000 retrospectively collected samples from pregnant women in their 1st trimester throughout 2020. All the samples were initially screened for IgG with SARS-CoV-2 spike antibody assay (EIM-S1, Euroimmun, Lubeck, Germany) followed by confirmation with nucleocapsid antibody assay (Architect SARS-CoV-2, Abbott, Illinois, USA). Samples that were reactive (positive or borderline) with both assays were subjected to testing with commercial surrogate immunoassays of NeutraLISA (EIM) and cPassTM (GenScript Biotech Corporation, Rijswijk, Netherlands) by using pseudoneutralization assay (PNAbA) as a golden standard. No seropositive cases were detected between January and March. Between April and December, IgG (EIM-S1 and Abbott positive) and NAb (PNAbA positive) seroprevalences were between 0.4-1.4%. NeutraLISA showed 90% and cPass 55% concordant results with PNAbA among PNAbA negative samples and 49% and 92% among PNAbA positive samples giving NeutraLISA better specificity but lower sensitivity than cPass. To conclude, seroprevalence in pregnant women reflected that of the general population but the variability of the performance of serological protocols needs to be taken into account in inter-study comparison.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.06.08.23291050", + "rel_abs": "Researchers and policymakers have proposed systems to detect novel pathogens earlier than existing surveillance systems by monitoring samples from hospital patients, wastewater, and air travel, in order to mitigate future pandemics. How much benefit would such systems offer? We developed, empirically validated, and mathematically characterized a quantitative model that simulates disease spread and detection time for any given disease and detection system. We find that hospital monitoring could have detected COVID-19 in Wuhan 0.4 weeks earlier than it was actually discovered, at 2,300 cases (standard error: 76 cases) compared to 3,400 (standard error: 161 cases). Wastewater monitoring would not have accelerated COVID-19 detection in Wuhan, but provides benefit in smaller catchments and for asymptomatic or long-incubation diseases like polio or HIV/AIDS. Monitoring of air travel provides little benefit in most scenarios we evaluated. In sum, early detection systems can substantially mitigate some future pandemics, but would not have changed the course of COVID-19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jenni Virtanen", - "author_inst": "University of Helsinki" - }, - { - "author_name": "Essi M Korhonen", - "author_inst": "University of Helsinki" + "author_name": "Andrew Bo Liu", + "author_inst": "Harvard Medical School" }, { - "author_name": "Sami Salonen", - "author_inst": "University of Helsinki and Helsinki University Hospital" + "author_name": "Daniel Lee", + "author_inst": "Harvard Medical School" }, { - "author_name": "Olli Vapalahti", - "author_inst": "University of Helsinki" + "author_name": "Amogh Prabhav Jalihal", + "author_inst": "Harvard Medical School" }, { - "author_name": "Tarja Sironen", - "author_inst": "Haartman Institute, University of Helsinki" + "author_name": "William P. Hanage", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Anne J Jaaskelainen", - "author_inst": "University of Helsinki and Helsinki University Hospital" + "author_name": "Michael Springer", + "author_inst": "Harvard Medical School" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -90383,75 +89986,67 @@ "category": "animal behavior and cognition" }, { - "rel_doi": "10.1101/2023.06.03.543589", - "rel_title": "A deep learning-based drug repurposing screening and validation for anti-SARS-CoV-2 compounds by targeting the cell entry mechanism", + "rel_doi": "10.1101/2023.06.02.543458", + "rel_title": "Machine Learning-Guided Antibody Engineering That Leverages Domain Knowledge To Overcome The Small Data Problem", "rel_date": "2023-06-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.03.543589", - "rel_abs": "The recent outbreak of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been a severe threat to the global public health and economy, however, effective drugs to treat COVID-19 are still lacking. Here, we employ a deep learning-based drug repositioning strategy to systematically screen potential anti-SARS-CoV-2 drug candidates that target the cell entry mechanism of SARS-CoV-2 virus from 2,635 FDA-approved drugs and 1,062 active ingredients from Traditional Chinese Medicine herbs. In silico molecular docking analysis validates the interactions between the top compounds and host receptors or viral spike proteins. Using a SARS-CoV-2 pseudovirus system, we further identify several drug candidates including Fostamatinib, Linagliptin, Lysergol and Sophoridine that can effectively block the cell entry of SARS-CoV-2 variants into human lung cells even at a nanomolar scale. These efforts not only illuminate the feasibility of applying deep learning-based drug repositioning for antiviral agents by targeting a specified mechanism, but also provide a valuable resource of promising drug candidates or lead compounds to treat COVID-19.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.06.02.543458", + "rel_abs": "The application of Machine Learning (ML) tools to engineer novel antibodies having predictable functional properties is gaining prominence. Herein, we present a platform that employs an ML-guided optimization of the complementarity-determining region (CDR) together with a CDR framework (FR) shuffling method to engineer affinity-enhanced and clinically developable monoclonal antibodies (mAbs) from a limited experimental screen space (order of 10^2 designs) using only two experimental iterations. Although high-complexity deep learning models like graph neural networks (GNNs) and large language models (LLMs) have shown success on protein folding with large dataset sizes, the small and biased nature of the publicly available antibody-antigen interaction datasets is not sufficient to capture the diversity of mutations virtually screened using these models in an affinity enhancement campaign. To address this key gap, we introduced inductive biases learned from extensive domain knowledge on protein-protein interactions through feature engineering and selected model hyper parameters to reduce overfitting of the limited interaction datasets. Notably we show that this platform performs better than GNNs and LLMs on an in-house validation dataset that is enriched in diverse CDR mutations that go beyond alanine-scanning. To illustrate the broad applicability of this platform, we successfully solved a challenging problem of redesigning two different anti-SARS-COV-2 mAbs to enhance affinity (up to 2 orders of magnitude) and neutralizing potency against the dynamically evolving SARS-COV-2 Omicron variants.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Yingjia Yao", - "author_inst": "Northeastern University" + "author_name": "Thomas Clark", + "author_inst": "Altus Enterprises" }, { - "author_name": "Yunhan Zhang", - "author_inst": "Northeastern University" + "author_name": "Vidya Subramanian", + "author_inst": "Altus Enterprises" }, { - "author_name": "Zexu Li", - "author_inst": "Northeastern University" + "author_name": "AKila Jayaraman", + "author_inst": "Altus Enterprises" }, { - "author_name": "Zhisong Chen", - "author_inst": "Northeastern University" + "author_name": "Emmett Fitzpatrick", + "author_inst": "Altus Enterprises" }, { - "author_name": "Xiaofeng Wang", - "author_inst": "Northeastern University" + "author_name": "Ranjani Gopal", + "author_inst": "Altus Enterprises" }, { - "author_name": "Zihan Li", - "author_inst": "Northeastern University" + "author_name": "Niharika Pentakota", + "author_inst": "Altus Enterprises" }, { - "author_name": "Li Yu", - "author_inst": "Northeastern University" + "author_name": "Troy Rurak", + "author_inst": "Altus Enterprises" }, { - "author_name": "Xiaolong Cheng", - "author_inst": "Childrens National Hospital" + "author_name": "Shweta Anand", + "author_inst": "Altus Enterprises" }, { - "author_name": "Wei Li", - "author_inst": "Childrens National Hospital" + "author_name": "Alexander Viglione", + "author_inst": "Altus Enterprises" }, { - "author_name": "Wen-Jie Jiang", - "author_inst": "Peking University" + "author_name": "Kannan Tharakaraman", + "author_inst": "Altus Enterprises" }, { - "author_name": "Hua-Jun Wu", - "author_inst": "Peking University" - }, - { - "author_name": "Zezhong Feng", - "author_inst": "Northeastern University" - }, - { - "author_name": "Jinfu Sun", - "author_inst": "Institute of Biotechnology, College of Life and Health Sciences, Northeastern University" + "author_name": "Rahul Raman", + "author_inst": "Massachusetts Institute of Technology" }, { - "author_name": "Teng Fei", - "author_inst": "Northeastern University" + "author_name": "Ram Sasisekharan", + "author_inst": "Massachusetts Institute of Technology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "bioengineering" }, { "rel_doi": "10.1101/2023.06.02.543487", @@ -92657,73 +92252,49 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2023.05.31.543129", - "rel_title": "CD4+ T-cell immunity of SARS-CoV-2 patients determine pneumonia development", + "rel_doi": "10.1101/2023.05.30.542314", + "rel_title": "A semi-quantitative, rapid, point of care SARS-CoV-2 serologic assay predicts neutralizing antibody levels", "rel_date": "2023-06-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.31.543129", - "rel_abs": "Most humans infected with SARS-CoV-2 will recover without developing pneumonia. A few SARS-CoV-2 infected patients, however, develop pneumonia, and occasionally develop cytokine storms. In such cases, it is assumed that there is an inadequate immune response to eliminate viral infected cells and an excessive inappropriate immune response causing organ damage, but little is known about this mechanism. In this study, we used single cell RNA sequencing and mass cytometry to analyze peripheral blood T cells from patients hospitalized with proven COVID-19 infection in order to clarify the differences in host immune status among COVID-19 pneumonia cases, non-pneumonia cases, and healthy controls. The results showed that a specific CD4+ T cell cluster with chemokine receptor expression patterns, CXCR3+CCR4-CCR6+ (Th1/17), was less abundant in COVID-19 pneumonia patients. Interestingly, these CD4+ T-cell clusters were identical to those we have reported to correlate with antitumor immunity and predict programmed cell death (PD)-1 blockade treatment response in lung cancer. The Th1/17 cell percentages had biomarker performance in diagnosing pneumonia cases. In addition, CTLA-4 expression of type17 helper T cells (Th17) and regulatory T cells (Treg) was found to be significantly lower. This indicates that functional suppression of Th17 was less effective and Treg function was impaired in pneumonia cases. These results suggest that imbalance of CD4+ T-cell immunity generates excessive immunity that does not lead to viral eradication. This might be a potential therapeutic target mechanism to prevent severe viral infections.\n\nImportanceIn this observational study, 49 consecutive patients with SARS-CoV-2 infection confirmed by PCR testing and admitted to Saitama Medical University Hospital and Saitama Medical University International Medical Centre between December 4, 2020 and January 17, 2022 were included. Of these 49 patients, 29 were diagnosed with COVID-19 pneumonia by computed tomography (CT) scan (Table 1). The unique CD4+ T-cell immunity with less abundant Th1/17 CD4+ T-cell cluster and low expression of CTLA-4 in Th17 and Treg was consistently found in SARS-CoV-2 pneumonia patients on admission and 1-week of admission. The imbalance of CD4+ T-cell immunity may contribute to develop pneumonia in SARS-CoV-2 virus infected patients by delaying viral clearance and resulting in an excessive immune response.\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@1aac015org.highwire.dtl.DTLVardef@128c14dorg.highwire.dtl.DTLVardef@aacabaorg.highwire.dtl.DTLVardef@e39c8eorg.highwire.dtl.DTLVardef@13b439a_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1C_FLOATNO O_TABLECAPTIONPatient demographics\n\nC_TABLECAPTION C_TBL", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.30.542314", + "rel_abs": "The ongoing COVID-19 pandemic has caused millions of deaths and the continued emergence of new variants suggests continued circulation in the human population. In the current time of vaccine availability and new therapeutic development, including antibody-based therapies, many questions about long-term immunity and protection remain uncertain. Identification of protective antibodies in individuals is often done using highly specialized and challenging assays such as functional neutralizing assays, which are not available in the clinical setting. Therefore, there is a great need for the development of rapid, clinically available assays that correlate with neutralizing antibody assays to identify individuals who may benefit from additional vaccination or specific COVID-19 therapies. In this report, we apply a novel semi-quantitative method to an established lateral flow assay (sqLFA) and analyze its ability to detect the presence functional neutralizing antibodies from the serum of COVID-19 recovered individuals. We found that the sqLFA has a strong positive correlation with neutralizing antibody levels. At lower assay cutoffs, the sqLFA is a highly sensitive assay to identify the presence of a range of neutralizing antibody levels. At higher cutoffs, it can detect higher levels of neutralizing antibody with high specificity. This sqLFA can be used both as a screening tool to identify individuals with any level of neutralizing antibody to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), or as a more specific tool to identify those with high neutralizing antibody levels who may not benefit from antibody-based therapies or further vaccination.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Erika Naito", - "author_inst": "Saitama Ika Daigaku" - }, - { - "author_name": "Takahiro Uchida", - "author_inst": "Saitama Ika Daigaku" - }, - { - "author_name": "Satoshi Yamasaki", - "author_inst": "Saitama Ika Daigaku Kokusai Iryo Center" - }, - { - "author_name": "Kosuke Hashimoto", - "author_inst": "Saitama Ika Daigaku Kokusai Iryo Center" - }, - { - "author_name": "Yu Miura", - "author_inst": "Saitama Ika Daigaku Kokusai Iryo Center" - }, - { - "author_name": "Ayako Shiono", - "author_inst": "Saitama Medical University" - }, - { - "author_name": "Takayuki Kawamura", - "author_inst": "Saitama Ika Daigaku Kokusai Iryo Center" + "author_name": "Alena Janda Markmann", + "author_inst": "University of North Carolina Chapel Hill" }, { - "author_name": "Atsuto Mouri", - "author_inst": "Saitama Ika Daigaku Kokusai Iryo Center" + "author_name": "Debarshi Ryan Bhowmik", + "author_inst": "University of North Carolina Chapel Hill" }, { - "author_name": "Ou Yamaguchi", - "author_inst": "Saitama Ika Daigaku Kokusai Iryo Center" + "author_name": "Baowei Jiang", + "author_inst": "BioMedomics Inc." }, { - "author_name": "Hisao Imai", - "author_inst": "Saitama Ika Daigaku Kokusai Iryo Center" + "author_name": "Michael Van Hoy", + "author_inst": "BioMedomics Inc." }, { - "author_name": "Kyoichi Kaira", - "author_inst": "Saitama Ika Daigaku Kokusai Iryo Center" + "author_name": "Frank Wang", + "author_inst": "BioMedomics Inc." }, { - "author_name": "Manabu Nemoto", - "author_inst": "Saitama Medical University International Medical Center" + "author_name": "Yixuan Jacob Hou", + "author_inst": "Moderna" }, { - "author_name": "Kotaro Mitsutake", - "author_inst": "Tohoku Daigaku Daigakuin Igakukei Kenkyuka Igakubu" + "author_name": "Ralph S. Baric", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Makoto Nagata", - "author_inst": "Saitama Medical University" + "author_name": "Aravinda M de Silva", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Hiroshi Kagamu", - "author_inst": "Saitama Ika Daigaku Kokusai Iryo Center" + "author_name": "Luther A Bartelt", + "author_inst": "University of North Carolina Chapel Hill" } ], "version": "1", @@ -95151,99 +94722,43 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2023.05.25.542297", - "rel_title": "Multi-omic Profiling Reveals Early Immunological Indicators for Identifying COVID-19 Progressors", + "rel_doi": "10.1101/2023.05.25.542331", + "rel_title": "Evolution of transient RNA structure-RNA polymerase interactions in respiratory RNA virus genomes", "rel_date": "2023-05-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.25.542297", - "rel_abs": "The pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to a rapid response by the scientific community to further understand and combat its associated pathologic etiology. A focal point has been on the immune responses mounted during the acute and post-acute phases of infection, but the immediate post-diagnosis phase remains relatively understudied. We sought to better understand the immediate post-diagnosis phase by collecting blood from study participants soon after a positive test and identifying molecular associations with longitudinal disease outcomes. Multi-omic analyses identified differences in immune cell composition, cytokine levels, and cell subset-specific transcriptomic and epigenomic signatures between individuals on a more serious disease trajectory (Progressors) as compared to those on a milder course (Non-progressors). Higher levels of multiple cytokines were observed in Progressors, with IL-6 showing the largest difference. Blood monocyte cell subsets were also skewed, showing a comparative decrease in non-classical CD14-CD16+ and intermediate CD14+CD16+ monocytes. Additionally, in the lymphocyte compartment, CD8+ T effector memory cells displayed a gene expression signature consistent with stronger T cell activation in Progressors. Importantly, the identification of these cellular and molecular immune changes occurred at the early stages of COVID-19 disease. These observations could serve as the basis for the development of prognostic biomarkers of disease risk and interventional strategies to improve the management of severe COVID-19.\n\nOne Sentence SummaryImmunological changes associated with COVID-19 progression can be detected during the early stages of infection.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.25.542331", + "rel_abs": "RNA viruses are important human pathogens that cause seasonal epidemics and occasional pandemics. Examples are influenza A viruses (IAV) and coronaviruses (CoV). When emerging IAV and CoV spill over to humans, they adapt to evade immune responses and optimize their replication and spread in human cells. In IAV, adaptation occurs in all viral proteins, including the viral ribonucleoprotein (RNP) complex. RNPs consists of a copy of the viral RNA polymerase, a double-helical coil of nucleoprotein, and one of the eight segments of the IAV RNA genome. The RNA segments and their transcripts are partially structured to coordinate the packaging of the viral genome and modulate viral mRNA translation. In addition, RNA structures can affect the efficiency of viral RNA synthesis and the activation of host innate immune response. Here, we investigated if RNA structures that modulate IAV replication processivity, so called template loops (t-loops), vary during the adaptation of pandemic and emerging IAV to humans. Using cell culture-based replication assays and in silico sequence analyses, we find that the sensitivity of the IAV H3N2 RNA polymerase to t-loops increased between isolates from 1968 and 2017, whereas the total free energy of t-loops in the IAV H3N2 genome was reduced. This reduction is particularly prominent in the PB1 gene. In H1N1 IAV, we find two separate reductions in t-loop free energy, one following the 1918 pandemic and one following the 2009 pandemic. No destabilization of t-loops is observed in the IBV genome, whereas analysis of SARS-CoV-2 isolates reveals destabilization of viral RNA structures. Overall, we propose that a loss of free energy in the RNA genome of emerging respiratory RNA viruses may contribute to the adaption of these viruses to the human population.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Katherine A Drake", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Dimitri Talantov", - "author_inst": "Janssen Research & Development, LLC, San Diego, 92121, USA" - }, - { - "author_name": "Gary Tong", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Jack T Lin", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Simon Verheijden", - "author_inst": "Janssen Research & Development, Beerse, Belgium" - }, - { - "author_name": "Samuel Katz", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Jacqueline M Leung", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Benjamin Yuen", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Vinod Krishna", - "author_inst": "Janssen Research & Development, LLC, San Diego, 92121, USA" - }, - { - "author_name": "Michelle J Wu", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Alex Sutherland", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Sarah Short", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Pouya Kheradpour", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Maxwell R Mumbach", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" - }, - { - "author_name": "Kate M Franz", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" + "author_name": "Charlotte V Rigby", + "author_inst": "Princeton University" }, { - "author_name": "Vladimir Trifonov", - "author_inst": "Janssen Research & Development, LLC, San Diego, 92121, USA" + "author_name": "Kimberly R Sabsay", + "author_inst": "Princeton University" }, { - "author_name": "Molly V Lucas", - "author_inst": "Janssen Research & Development, LLC, New Jersey, 08933, USA" + "author_name": "Karishma Bisht", + "author_inst": "Princeton University" }, { - "author_name": "James Merson", - "author_inst": "Janssen Research & Development, LLC, San Diego, 92121, USA" + "author_name": "Dirk Eggink", + "author_inst": "National Institute for Public Health and The Environment (RIVM)" }, { - "author_name": "Charles C Kim", - "author_inst": "Verily Life Sciences, South San Francisco, 94080, USA" + "author_name": "Hamid Jalal", + "author_inst": "Public Health England" }, { - "author_name": "- The PRESCO Study Group", - "author_inst": "" + "author_name": "Aartjan J.W. te Velthuis", + "author_inst": "Princeton University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2023.05.25.542379", @@ -97093,47 +96608,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.05.19.23290234", - "rel_title": "Defining the Subtypes of Long COVID and Risk Factors for Prolonged Disease", + "rel_doi": "10.1101/2023.05.20.23290269", + "rel_title": "Evaluating the Association of Depressive Disorder Symptoms and Moral Injuries in Healthcare Workers during COVID-19 Pandemic", "rel_date": "2023-05-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.19.23290234", - "rel_abs": "ImportanceThere have been over 759 million confirmed cases of COVID-19 worldwide. A significant portion of these infections will lead to long COVID and its attendant morbidities and costs.\n\nObjectiveTo empirically derive a long COVID case definition consisting of significantly increased signs, symptoms, and diagnoses to support clinical, public health, research, and policy initiatives related to the pandemic.\n\nDesignCase-Crossover Population-based study.\n\nSettingVeterans Affairs (VA) medical centers across the United States between January 1, 2020 and August 18, 2022.\n\nParticipants367,148 individuals with positive COVID-19 tests and preexisting ICD-10-CM codes recorded in the VA electronic health record were enrolled.\n\nTriggerSARS-CoV-2 infection documented by positive laboratory test.\n\nCase WindowOne to seven months following positive COVID testing.\n\nMain Outcomes and MeasuresWe defined signs, symptoms, and diagnoses as being associated with long COVID if they had a novel case frequency of >= 1:1000 and they were significantly increased in our entire cohort after a positive COVID test when compared to case frequencies before COVID testing. We present odds ratios with confidence intervals for long COVID signs, symptoms, and diagnoses, organized by ICD-10-CM functional groups and medical specialty. We used our definition to assess long COVID risk based upon a patients demographics, Elixhauser score, vaccination status, and COVID disease severity.\n\nResultsWe developed a long COVID definition consisting of 323 ICD-10-CM diagnosis codes grouped into 143 ICD-10-CM functional groups that were significantly increased in our 367,148 patient post-COVID population. We define seventeen medical-specialty long COVID subtypes such as cardiology long COVID. COVID-19 positive patients developed signs, symptoms, or diagnoses included in our long COVID definition at a proportion of at least 59.7% (based on all COVID positive patients). Patients with more severe cases of COVID-19 and multiple comorbidities were more likely to develop long COVID.\n\nConclusions and RelevanceAn actionable, empirical definition for long COVID can help clinicians screen for and diagnose long COVID, allowing identified patients to be admitted into appropriate monitoring and treatment programs. An actionable long COVID definition can also support public health, research and policy initiatives. COVID patients with low oxygen saturation levels or multiple co-morbidities should be preferentially watched for the development of long COVID.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.20.23290269", + "rel_abs": "BackgroundMoral injury occurs when negative distressing emotions appear and are suppressed. This could lead to several mental health problems such as depression and post-traumatic stress disorder, and result in long-lasting emotional, behavioral, and social problems. Moral injury, a term more commonly used in war contexts, has come into the spotlight during COVID-19 pandemic. We aimed to evaluate the rate of moral injury and its association with psychological injuries during this healthcare crisis.\n\nMethodsWe assessed the rates of depression, anxiety, stress, and their association with moral injury among 333 nurses, medical interns, and residents between December 2020 and January 2021. This study was done using validated versions of Depression Anxiety Stress Scales (DASS- and Moral Injury Symptom Scale-Healthcare Professionals (MISS-HP) scores.\n\nResultsTotally 333 healthcare professionals participated in this study, mostly aged between 26 to 30 years old. Nearly half of the participants had a clinically significant moral injury. The average scores of anxiety and stress were significantly higher in women. The participants who were single showed higher rates of depression and moral injury than married ones. Moreover, anxiety, stress, depression, and moral injury were higher in nurses than other healthcare professionals. The scarcity of personal protective equipment at the workplace and giving care to patients with end-stage COVID-19 diagnosis were among the factors associated with a higher risk of developing mental health problems.\n\nConclusionThe results of this study showed that anxiety, stress, depression, and moral injury were prevalent among healthcare professionals during COVID-19 pandemic. Also, the rates of anxiety, stress, and depression were associated with moral injuries.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Skyler Resendez", - "author_inst": "University at Buffalo" + "author_name": "Amirhossein Behnampour", + "author_inst": "Department of Medical Ethics, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Steven H Brown", - "author_inst": "Department of Veterans Affairs" + "author_name": "Sedigheh Ebrahimi", + "author_inst": "Department of Medical Ethics, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Sebastian Ruiz", - "author_inst": "University at Bufalo" + "author_name": "Amir Bazrafshan", + "author_inst": "Department of Psychiatry, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Prahalad Rangan", - "author_inst": "University at Buffalo" - }, - { - "author_name": "Jonathan K Nebeker", - "author_inst": "Department of Veterans Affairs" + "author_name": "Amirhossein Kamyab", + "author_inst": "Faculty of Medicine, Fasa University of Medical Sciences, Fasa, Iran" }, { - "author_name": "Diane Montella", - "author_inst": "Department of Veterans Affairs" + "author_name": "Majid Pakdin", + "author_inst": "Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran" }, { - "author_name": "Peter L Elkin", - "author_inst": "University at Buffalo" + "author_name": "Alireza Ebrahimi", + "author_inst": "Student Research Committee, Shiraz University of Medical Sciences, Shiraz, Iran" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "medical ethics" }, { "rel_doi": "10.1101/2023.05.16.23290042", @@ -98915,55 +98426,27 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2023.05.10.23289325", - "rel_title": "Composite interventions on outcomes of severely and critically ill patients with COVID-19 in Shanghai, China", + "rel_doi": "10.1101/2023.05.09.23289706", + "rel_title": "Insight into risk associated phenotypes behind COVID-19 from phenotype genome-wide association studies", "rel_date": "2023-05-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.10.23289325", - "rel_abs": "BackgroundThe sixty-day effects of initial composite interventions for the treatment of severely and critically ill patients with COVID-19 are not fully assessed.\n\nMethodsUsing a bayesian piecewise exponential model, we analyzed the 60-day mortality, health-related quality of life (HRQoL) and disability in 1082 severely and critically patients with COVID-19 between December 8, 2022 and February 9, 2023 in Shanghai, China. The final 60-day follow-up was completed on April 10, 2023.\n\nResultsAmong 1082 patients (mean age, 78.0 years), 421 [38.9%] women), 139 patients (12.9%) died within 60 days. Azvudine had a 99.8% probability of improving 2-month survival (adjusted HR, 0.44 [95% credible interval, 0.24-0.79]) and Paxlovid had a 91.9% probability of improving 2-month survival (adjusted HR, 0.71 [95% credible interval, 0.44-1.14]) compared with the control. IL-6 receptor antagonist, Baricitinib, and a-thymosin each had a high probability of benefit (99.5%, 99.4%, and 97.5%, respectively) compared to their controls, while the probability of trail-defined statistical futility (HR >0.83) was high for therapeutic anticoagulation (99.8%; HR, 1.64 [95% CrI, 1.06-2.50]), and glucocorticoid (91.4%; HR, 1.20 [95% CrI, 0.71-2.16]). Paxlovid, Azvudine and therapeutic anticoagulation showed significant reduction in disability (p<0.05)\n\nConclusionsAmong severely and critically ill patients with COVID-19 who received 1 or more therapeutic interventions, treatment with Azvudine had a high probability of improved 60-day mortality compared with the control, indicating its potential in resource-limited scenario. Treatment with IL-6 receptor antagonist, Baricitinib, and a-thymosin also had high probabilities of benefit of improving 2-month survival, among which a-thymosin could improve HRQoL. Treatment with Paxlovid, Azvudine and therapeutic anticoagulation could significantly reduce disability at day 60.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.09.23289706", + "rel_abs": "Long COVID presents a complex and multi-systemic disease that poses a significant global public health challenge. Symptoms can vary widely, ranging from asymptomatic to severe, making the condition challenging to diagnose and manage effectively. Furthermore, identifying appropriate phenotypes in genome-wide association studies of COVID-19 remains unresolved. This study aimed to address these challenges by analyzing 220 deep-phenotype genome-wide association data sets (159 diseases, 38 biomarkers and 23 medication usage) from BioBank Japan (BBJ) (n=179,000), UK Biobank and FinnGen (n=628,000) to investigate pleiotropic effects of known COVID-19 risk associated single nucleotide variants. Our findings reveal 32 different phenotypes that share the common genetic risk factors with COVID-19 (p < 7.6x10-11), including two diseases (myocardial infarction and type 2 diabetes), 26 biomarkers with seven categories (blood cell, metabolic, liver-related, kidney-related, protein, inflammatory and anthropometric), and four medications (antithrombotic agents, HMG CoA reductase inhibitors, thyroid preparations and anilides). As long COVID continues to coexist with humans, our results highlight the need for targeted screening to support specific vulnerable populations to improve disease prevention and healthcare delivery.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Jiasheng Shao", - "author_inst": "Department of Immunology and Rheumatology, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences" - }, - { - "author_name": "Fan Rong", - "author_inst": "Center for Molecular and Cellular Bioengineering, Biotechnology Center, Technische Universitat Dresden" - }, - { - "author_name": "Chengnan Guo", - "author_inst": "Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai, China" - }, - { - "author_name": "Xuyuan Huang", - "author_inst": "Department of Urology, Renji Hospital, Shanghai JiaoTong University, Shanghai 200127, China" - }, - { - "author_name": "Runsheng Guo", - "author_inst": "Department of General Surgery, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences" + "author_name": "Zhongzhong Chen", + "author_inst": "Department of Urology, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University" }, { - "author_name": "Fengdi Zhang", - "author_inst": "Department of Infectious Disease, Shanghai East Hospital, Tongji University School of Medicine" - }, - { - "author_name": "Jianrong Hu", - "author_inst": "Department of Respiratory Medicine, Jiading District Central Hospital Affiliated Shanghai University of Medicine & Health Sciences" - }, - { - "author_name": "Gang Huang", - "author_inst": "Shanghai Key Laboratory of Molecular Imaging, Shanghai University of Medicine and Health Sciences" - }, - { - "author_name": "Liou Cao", - "author_inst": "Department of Nephrology, Molecular Cell Lab for Kidney Disease, Shanghai Peritoneal Dialysis Research Center, Ren Ji Hospital, Uremia Diagnosis and Treatment C" + "author_name": "Koichi Matsuda", + "author_inst": "Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, the University of Tokyo, Tokyo, Japan" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2023.05.12.23289913", @@ -100577,57 +100060,69 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2023.05.08.539929", - "rel_title": "Toll-like receptor 7 (TLR7)-mediated antiviral response protects mice from lethal SARS-CoV-2 infection", + "rel_doi": "10.1101/2023.05.09.539943", + "rel_title": "Dissecting the impact of somatic hypermutation on SARS-CoV-2 neutralization and viral escape", "rel_date": "2023-05-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.08.539929", - "rel_abs": "SARS-CoV-2-induced impaired antiviral and excessive inflammatory responses cause fatal pneumonia. However, the key pattern recognition receptors that elicit effective antiviral and lethal inflammatory responses in-vivo are not well defined. CoVs possess single-stranded RNA (ssRNA) genome that is abundantly produced during infection and stimulates both antiviral interferon (IFN) and inflammatory cytokine/ chemokine responses. Therefore, in this study, using wild-type control and TLR7 deficient BALB/c mice infected with a mouse-adapted SARS-COV-2 (MA-CoV-2), we evaluated the role of TLR7 signaling in MA-CoV-2-induced antiviral and inflammatory responses and disease outcome. We show that TLR7-deficient mice are more susceptible to MA-CoV-2 infection as compared to infected control mice. Further evaluation of MA-CoV-2 infected lungs showed significantly reduced mRNA levels of antiviral type I (IFN/{beta}) and type III (IFN{lambda}) IFNs, IFN stimulated genes (ISGs, ISG15 and CXCL10), and several pro-inflammatory cytokines/chemokines in TLR7 deficient compared to control mice. Reduced lung IFN/ISG levels and increased morbidity/mortality in TLR7 deficient mice correlated with high lung viral titer. Detailed examination of total cells from MA-CoV-2 infected lungs showed high neutrophil count in TLR7 deficient mice compared to control mice. Additionally, blocking TLR7 activity post-MA-CoV-2 infection using a specific inhibitor also enhanced disease severity. In summary, our results conclusively establish that TLR7 signaling is protective during SARS-CoV-2 infection, and despite robust inflammatory response, TLR7-mediated IFN/ISG responses likely protect the host from lethal disease. Given similar outcomes in control and TLR7 deficient humans and mice, these results show that MA-CoV-2 infected mice serve as excellent model to study COVID-19.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.05.09.539943", + "rel_abs": "Somatic hypermutation (SHM) drives affinity maturation and continues over months in SARS-CoV-2 neutralizing antibodies. Yet, several potent SARS-CoV-2 antibodies carry no or only few mutations, leaving the question of how ongoing SHM affects neutralization. Here, we reverted variable region mutations of 92 antibodies and tested their impact on SARS-CoV-2 binding and neutralization. Reverting higher numbers of mutations correlated with decreasing antibody functionality. However, some antibodies, including the public clonotype VH1-58, remained unaffected for Wu01 activity. Moreover, while mutations were dispensable for Wu01-induced VH1-58 antibodies to neutralize Alpha, Beta, and Delta variants, they were critical to neutralize Omicron BA.1/BA.2. Notably, we exploited this knowledge to convert the clinical antibody tixagevimab into a BA.1/BA.2-neutralizer. These findings substantially broaden our understanding of SHM as a mechanism that not only improves antibody responses during affinity maturation, but also counteracts antigenic imprinting through antibody diversification and thus increases the chances of neutralizing viral escape variants.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Roshan Ghimire", - "author_inst": "Oklahoma State University" + "author_name": "Michael Korenkov", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Rakshya Shrestha", - "author_inst": "Oklahoma State University" + "author_name": "Matthias Zehner", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Radhika Amaradhi", - "author_inst": "Emory University" + "author_name": "Hadas Cohen-Dvashi", + "author_inst": "Department of Chemical and Structural Biology, Weizmann Institute of Science, 76100 Rehovot, Israel" }, { - "author_name": "Titus Patton", - "author_inst": "Oklahoma State University" + "author_name": "Aliza Borenstein-Katz", + "author_inst": "Department of Chemical and Structural Biology, Weizmann Institute of Science, 76100 Rehovot, Israel" }, { - "author_name": "Cody Whitley", - "author_inst": "Oklahoma State University" + "author_name": "Lisa Kottege", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Debarati Chanda", - "author_inst": "Oklahoma State University" + "author_name": "Hanna Janicki", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Lin Liu", - "author_inst": "Oklahoma State University" + "author_name": "Kanika Vanshylla", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Sunil More", - "author_inst": "Oklahoma State University" + "author_name": "Timm Weber", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Thota Ganesh", - "author_inst": "Emory University" + "author_name": "Henning Gruell", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" }, { - "author_name": "Rudragouda Channappanavar", - "author_inst": "Oklahoma State University" + "author_name": "Manuel Koch", + "author_inst": "Institute for Dental Research and Oral Musculoskeletal Biology and Center for Biochemistry, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Ron Diskin", + "author_inst": "Department of Chemical and Structural Biology, Weizmann Institute of Science, 76100 Rehovot, Israel" + }, + { + "author_name": "Christoph Kreer", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" + }, + { + "author_name": "Florian Klein", + "author_inst": "Laboratory of Experimental Immunology, Institute of Virology, Faculty of Medicine and University Hospital Cologne, University of Cologne, 50931 Cologne, Germany" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -102127,107 +101622,79 @@ "category": "ophthalmology" }, { - "rel_doi": "10.1101/2023.05.02.23289345", - "rel_title": "Persistent immune abnormalities discriminate post-COVID syndrome from convalescence", + "rel_doi": "10.1101/2023.05.03.23289472", + "rel_title": "SARS-CoV-2 specific cellular and humoral immunity after bivalent BA.4/5 COVID-19 vaccination in previously infected and non-infected individuals", "rel_date": "2023-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.02.23289345", - "rel_abs": "Innate lymphoid cells (ILCs) are key organizers of tissue immune responses and regulate tissue development, repair, and pathology. Persistent clinical sequelae beyond 12 weeks following acute COVID-19 disease, named post-COVID syndrome (PCS), are increasingly recognized in convalescent individuals. ILCs have been associated with the severity of COVID-19 symptoms but their role in the development of PCS remains poorly defined. Here we used multiparametric immune phenotyping, finding expanded circulating ILC precursors (ILCPs) and concurrent decreased group 2 innate lymphoid cells (ILC2s) in PCS patients compared to well-matched convalescent control groups at > 3 months after infection. Patients with PCS showed elevated expression of chemokines and cytokines associated with trafficking of immune cells (CCL19/MIP-3b, FLT3-ligand), endothelial inflammation and repair (CXCL1, EGF, RANTES, IL1RA, PDGF-AA). These results define immunological parameters associated with PCS and might help find biomarkers and disease-relevant therapeutic strategies.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.05.03.23289472", + "rel_abs": "Knowledge is limited as to how prior SARS-CoV-2 infection influences cellular and humoral immunity after booster-vaccination with bivalent BA.4/5-adapted mRNA-vaccines, and whether vaccine-induced immunity correlates with subsequent infection. In this observational study, individuals with prior infection (n=64) showed higher vaccine-induced anti-spike IgG antibodies and neutralizing titers, but the relative increase was significantly higher in non-infected individuals (n=63). In general, both groups showed higher neutralizing activity towards the parental strain than towards Omicron subvariants BA.1, BA.2 and BA.5. In contrast, CD4 or CD8 T-cell levels towards spike from the parental strain and the Omicron subvariants, and cytokine expression profiles were similar irrespective of prior infection. Breakthrough infections occurred more frequently among previously non-infected individuals, who had significantly lower vaccine-induced spike-specific neutralizing activity and CD4 T-cell levels. Thus, the magnitude of vaccine-induced neutralizing activity and specific CD4 T-cells after bivalent vaccination may serve as a correlate for protection in previously non-infected individuals.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Julia Sbierski-Kind", - "author_inst": "Universitaetsklinikum Tuebingen" - }, - { - "author_name": "Stephan Schlickeiser", - "author_inst": "Charite- Universitaetsmedizin Berlin" - }, - { - "author_name": "Svenja Feldmann", - "author_inst": "LMU Munich" - }, - { - "author_name": "Veronica Ober", - "author_inst": "LMU Munich" - }, - { - "author_name": "Eva Gruener", - "author_inst": "LMU Munich" - }, - { - "author_name": "Claire Pleimelding", - "author_inst": "LMU Munich" - }, - { - "author_name": "Leonard Gilberg", - "author_inst": "LMU Munich" - }, - { - "author_name": "Isabel Brand", - "author_inst": "LMU Munich" + "author_name": "Rebecca Urschel", + "author_inst": "Saarland University" }, { - "author_name": "Nikolas Weigl", - "author_inst": "LMU Munich" + "author_name": "Saskia Bronder", + "author_inst": "Saarland University" }, { - "author_name": "Mohamed I.M. Ahmed", - "author_inst": "LMU Munich" + "author_name": "Verena Klemis", + "author_inst": "Saarland University" }, { - "author_name": "Gerardo Ibarra", - "author_inst": "LMU Munich" + "author_name": "Stefanie Marx", + "author_inst": "Saarland University" }, { - "author_name": "Michael Ruzicka", - "author_inst": "LMU Munich" + "author_name": "Franziska Hielscher", + "author_inst": "Saarland University" }, { - "author_name": "Christopher Benesch", - "author_inst": "LMU Munich" + "author_name": "Amina Abu-Omar", + "author_inst": "Saarland University" }, { - "author_name": "Anna Pernpruner", - "author_inst": "LMu Munich" + "author_name": "Candida Guckelmus", + "author_inst": "Saarland University" }, { - "author_name": "Elisabeth Valdinoci", - "author_inst": "LMU Munich" + "author_name": "Sophie Schneitler", + "author_inst": "Saarland University" }, { - "author_name": "Michael Hoelscher", - "author_inst": "LMU Medizinische Fakult\u00e4t: Ludwig-Maximilians-Universitat Munchen Medizinische Fakultat" + "author_name": "Christina Baum", + "author_inst": "Saarland University" }, { - "author_name": "Kristina Adorjan", - "author_inst": "LMU Munich" + "author_name": "Soeren L Becker", + "author_inst": "Saarland University" }, { - "author_name": "Hans Christian Stubbe", - "author_inst": "LMU Munich" + "author_name": "Barbara C Gaertner", + "author_inst": "University of the Saarland Medical School" }, { - "author_name": "Michael Pritsch", - "author_inst": "LMU Munich" + "author_name": "Urban Sester", + "author_inst": "SHG-Kliniken Voelklingen" }, { - "author_name": "Ulrich Seybold", - "author_inst": "LMU Munich" + "author_name": "Marek Widera", + "author_inst": "Universitaetsklinikum Frankfurt" }, { - "author_name": "Johannes Bogner", - "author_inst": "LMU Munich" + "author_name": "Tina Schmidt", + "author_inst": "Saarland University" }, { - "author_name": "Julia Roider", - "author_inst": "LMU Munich" + "author_name": "Martina Sester", + "author_inst": "Saarland University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.05.03.23289106", @@ -104661,67 +104128,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.04.28.23289257", - "rel_title": "The COV50 classifier predicts frailty and future death, independent from SARS-CoV-2 infection", + "rel_doi": "10.1101/2023.04.28.23289271", + "rel_title": "Effect of vaccination on time till Long COVID, a comparison of two ways to model effect of vaccination and two outcome definitions", "rel_date": "2023-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.28.23289257", - "rel_abs": "BackgroundThere is evidence of pre-established vulnerability in individuals that increases the risk of their progression to severe disease or death, though the mechanisms that cause this are still not fully understood. Previous research has demonstrated that a urinary peptide classifier (COV50) predicts disease progression and death from SARS-CoV-2 at an early stage, indicating that the outcome prediction may be partly due to already present vulnerabilities. The aim of this study is to examine the ability of COV50 to predict future non-COVID-19-related mortality, and evaluate whether the pre-established vulnerability can be generic and explained on a molecular level by urinary peptides.\n\nMethodsUrinary proteomic data from 9193 patients (1719 patients sampled at intensive care unit (ICU) admission and 7474 patients with other diseases (non-ICU)) were extracted from the Human Urinary Proteome Database. The previously developed COV50 classifier, a urinary proteomics biomarker panel consisting of 50 peptides, was applied to all datasets. The association of COV50 scoring with mortality was evaluated.\n\nResultsIn the ICU group, an increase in the COV50 score of one unit resulted in a 20% higher relative risk of death (adj. HR 1{middle dot}2 [95% CI 1{middle dot}17-1{middle dot}24]). The same increase in COV50 in non-ICU patients resulted in a higher relative risk of 61% (adj. HR 1{middle dot}61 [95% CI 1{middle dot}47-1{middle dot}76]), in line with adjusted meta-analytic HR estimate of 1{middle dot}55. The most notable and significant changes associated with future fatal events were reductions of specific collagen fragments, most of collagen alpha I(I).\n\nConclusionThe COV50 classifier is predictive of death in the absence of SARS-CoV-2 infection, suggesting that it detects pre-existing vulnerability. Prediction is based mainly on collagen fragments, possibly reflecting disturbances in the integrity of the extracellular matrix. These data may serve as basis for proteomics guided intervention aiming towards manipulating/improving collagen turnover, thereby reducing the risk of death.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.28.23289271", + "rel_abs": "Long COVID, or post-COVID syndrome, is a constellation of symptoms observed in patients at least four weeks after COVID-19 infection. We analyzed the effect of COVID-19 vaccination status on risk of either developing Long COVID symptoms or being diagnosed with Long COVID. In separate analyses we compared the effect of vaccination status at time of COVID-19 infection and the effect of vaccination status as a time-dependent covariate where vaccination could occur at any point with respect to COVID-19 infection.\n\nTo address this question, we identified a subset of adult patients from Truveta Data who experienced a COVID-19 infection as indicated by a positive laboratory test between 2021-10-01 and 2022-11-31. We considered two distinct ways of modeling the effect of vaccination status (time-independent and time-dependent) and two distinct outcomes of interest (Long COVID symptoms or diagnosis with Long COVID), representing four distinct analyses. The presence of Long COVID symptoms was defined as the presence of one or more new symptoms consistent with COVID-19/Long COVID at least four weeks post COVID-19 infection. Diagnosis of Long COVID was determined by the presence of one or more ICD-10-CM or SNOMED-CT codes explicitly identifying a patient as having been diagnosed with Long COVID.\n\nOur analysis focusing on the effect of COVID-19 vaccination status at time of COVID-19 infection found that patients who had completed a primary COVID-19 vaccination sequence or had completed a primary vaccination sequence and received a booster dose at time of COVID-19 infection were on average at lower risk of either developing Long COVID symptoms or being diagnosed with Long COVID than unvaccinated patients (vaccinated versus unvaccinated HR of symptoms 0.9 [0.87-0.94], HR of diagnosis 0.86 [0.74-0.99]; vaccinated and boosted versus unvaccinated HR of symptoms 0.87 [0.83-0.91], HR of diagnosis 0.81 [0.69-0.95]). We do not find evidence that having received a booster dose in addition to having completed a primary vaccination sequence offers additional protection over having completed the primary sequence alone (vaccinated and boosted versus vaccinated HR of symptoms 0.96 [0.91-1.01], HR of diagnosis 0.94-1.13).\n\nOur analysis of COVID-19 vaccination status modeled as a time-dependent covariate yielded similar results for patients who had completed a primary COVID-19 vaccination sequence or had completed a primary vaccination sequence and a booster dose. Both groups were on average at lower risk of developing Long COVID symptoms or being diagnosed with Long COVID than patients who where never vaccinated (vaccinated versus unvaccinated HR of symptoms 0.91 [0.88-0.95], HR of diagnosis 0.86 [0.75-0.99]; vaccinated and boosted versus unvaccinated HR of symptoms 0.88 [0.85-0.91], HR of diagnosis 0.77 [0.67-0.9]). As with the time-independent analysis, we also find that having completed a booster dose in addition to a primary COVID-19 vaccination sequence does not provide additional protection from developing Long COVID symptoms or being diagnosed with Long COVID over having completed the primary sequence alone (vaccinated and boosted versus vaccinated HR of symptoms 0.96 [0.92-1.01], HR of diagnosis 0.89 [0.76-1.06]).\n\nWe find that completing a primary vaccination sequence is associated with a decreased risk of developing Long COVID symptoms or being diagnosed with Long COVID compared with no vaccination regardless of whether vaccination status is modeled as a time-independent or time-dependent covariate. We find a similar protective effect in patients who have completed a primary vaccination sequence and a booster dose when compared to the those who are unvaccinated. However, we do not find evidence for a difference in protective effect between patients who have completed a primary vaccination sequence and a booster dose and those patients who have only completed a primary vaccination sequence.\n\nOur results support the growing evidence that having complete a primary vaccination sequence is protective against the development of Long COVID symptoms or the diagnosis of Long COVID.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Felix Keller", - "author_inst": "Department of Internal Medicine IV (Nephrology and Hypertension), Medical University of Innsbruck, 6020 Innsbruck, Austria" - }, - { - "author_name": "Joachim Beige", - "author_inst": "Hospital Sankt Georg" - }, - { - "author_name": "Justyna Siwy", - "author_inst": "Mosaiques Diagnostics" - }, - { - "author_name": "Alexandre Mebazaa", - "author_inst": "Department of Anaesthesiology and Intensive Care, Hospital Saint Louis-Lariboisiere, 75475 Paris Cedex 10, Paris, France" - }, - { - "author_name": "De-Wei An", - "author_inst": "Non-Profit Research Institute Alliance for the Promotion of Preventive Medicine, 2800 Mechelen, Belgium" + "author_name": "Peter D Smits", + "author_inst": "Truveta, Inc" }, { - "author_name": "Harald Mischak", - "author_inst": "Mosaiques Diagnostics" + "author_name": "Patricia J Rodriguez", + "author_inst": "Truveta, Inc" }, { - "author_name": "Joost P Schanstra", - "author_inst": "Institut National de la Sante et de la Recherche Medicale, Institute of Cardiovascular and Metabolic Disease, UMRS 1297, 31432 Toulouse, France; Universite Toul" + "author_name": "Samuel Gratzl", + "author_inst": "Truveta, Inc" }, { - "author_name": "Marika Mokou", - "author_inst": "Mosaiques Diagnostics" + "author_name": "Brianna M Goodwin Cartwright", + "author_inst": "Truveta, Inc" }, { - "author_name": "Paul Perco", - "author_inst": "Department of Internal Medicine IV (Nephrology and Hypertension), Medical University of Innsbruck, 6020 Innsbruck, Austria" + "author_name": "Sarah Gilson", + "author_inst": "Truveta, Inc" }, { - "author_name": "Jan A Staessen", - "author_inst": "Non-Profit Research Institute Alliance for the Promotion of Preventive Medicine, 2800 Mechelen, Belgium" + "author_name": "Ryan H Lee", + "author_inst": "Truveta, Inc" }, { - "author_name": "Antonia Vlahou", - "author_inst": "Biomedical Research Foundation Academy of Athens" + "author_name": "Charlotte Baker", + "author_inst": "Truveta, Inc" }, { - "author_name": "Agnieszka Latosinska", - "author_inst": "Mosiaques Diagnostics GmbH" + "author_name": "Nicholas Stucky", + "author_inst": "Truveta, Inc" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.04.28.23289248", @@ -106687,51 +106138,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.04.24.23288921", - "rel_title": "Immune signature of patients with cardiovascular disease - in-depth immunophenotyping predicts increased risk for a severe course of COVID-19", - "rel_date": "2023-04-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.24.23288921", - "rel_abs": "ObjectiveSARS-CoV-2 infection can lead to life-threatening clinical manifestations. Patients with cardiovascular disease (CVD) are at higher risk for severe courses of COVID-19. However, strategies to predict the course of SARS-CoV-2 infection in CVD patients at hospital admission are still missing. Here, we investigated whether the severity of SARS-CoV-2 infection can be predicted by analyzing the immunophenotype in the blood of CVD patients.\n\nApproach and ResultsWe prospectively analyzed the peripheral blood of 94 participants, including CVD patients with acute SARS-CoV-2 infection, uninfected CVD patients, and healthy donors using a 36-color spectral flow cytometry panel. Clinical assessment included blood sampling, echocardiography, and electrocardiography. Patients were classified by their ISARIC WHO 4C-Mortality-Score on the day of admission into three subgroups of an expected mild, moderate, or severe course of COVID-19. Unsupervised data analysis revealed 40 clusters corresponding to major circulating immune cell populations. This revealed little differences between healthy donors and CVD patients, whereas the distribution of the cell populations changed dramatically in SARS-CoV-2-infected CVD patients. The latter had more mature NK cells, activated monocyte subsets, central memory CD4+ T cells, and plasmablasts than uninfected CVD patients. In contrast, fewer dendritic cells, CD16+ monocytes, innate lymphoid cells, and CD8+ T cell subsets were detected in SARS-CoV-2-infected CVD patients. We identified an immune signature characterized by low frequencies of MAIT and intermediate effector CD8+ T cells in combination with a high frequency of NKT cells that is predictive for CVD patients with a severe course of SARS-CoV-2 infection on hospital admission.\n\nConclusionAcute SARS-CoV-2 infected CVD patients revealed marked changes in abundance and phenotype of several immune cell populations associated with COVID-19 severity. Our data indicate that intensified immunophenotype analyses can help identify patients at risk of severe COVID-19 at hospital admission, improving clinical outcomes through specific treatment.\n\nHighlightsO_LIPatients with cardiovascular disease are at higher risk of severe courses of COVID-19 and may exhibit an altered immune response\nC_LIO_LIUnsupervised data analysis revealed that patients with cardiovascular disease and SARS-CoV-2 infection showed significant changes in the abundance and the phenotype of various immune cell populations\nC_LIO_LIWe identified a disease-related immune signature in patients with cardiovascular disease and SARS-CoV-2 infection associated with the severity of COVID-19\nC_LIO_LIIntensified immunophenotyping helps to identify cardiovascular patients at risk of a severe course of COVID-19 already at the early stages of the disease and might thereby improve clinical outcomes and specific treatment of COVID-19\nC_LI", + "rel_doi": "10.1101/2023.04.24.538130", + "rel_title": "How Do Deer Respiratory Epithelial Cells Weather The Initial Storm of SARS-CoV-2?", + "rel_date": "2023-04-25", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.24.538130", + "rel_abs": "The potential infectivity of SARS-CoV-2 in animals raises a public health and economic concern, particularly the high susceptibility of white-tailed deer (WTD) to SARS-CoV-2. The disparity in the disease outcome between humans and WTD is very intriguing, as the latter are often asymptomatic, subclinical carriers of SARS-CoV-2. To date, no studies have evaluated the innate immune factors responsible for the contrasting SARS-CoV-2-associated disease outcomes in these mammalian species. A comparative transcriptomic analysis in primary respiratory epithelial cells of human (HRECs) and WTD (Deer-RECs) infected with SARS-CoV-2 was assessed throughout 48 hours post inoculation (hpi). Both HRECs and Deer-RECs were susceptible to SARS-COV-2, with significantly (P < 0.001) lower virus replication in Deer-RECs. The number of differentially expressed genes (DEG) gradually increased in Deer-RECs but decreased in HRECs throughout the infection. The ingenuity pathway analysis of DEGs further identified that genes commonly altered during SARS-CoV-2 infection mainly belong to cytokine and chemokine response pathways mediated via IL-17 and NF-{kappa}B signaling pathways. Inhibition of the NF-{kappa}B signaling in the Deer-RECs pathway was predicted as early as 6 hpi. The findings from this study could explain the lack of clinical signs reported in WTD in response to SARS-CoV-2 infection as opposed to the severe clinical outcomes reported in humans.\n\nHIGHLIGHTSO_LIWhite-tailed deer primary respiratory epithelial cells are susceptible to SARS- CoV-2 without causing hyper cytokine gene expression.\nC_LIO_LIDownregulation of IL-17 and NF-{kappa}B signaling pathways after SARS-CoV-2 infection could be key to the regulated cytokine response in deer cells.\nC_LIO_LIDeer innate immune system could play a critical role in early antiviral and tissue repair response following SARS-CoV-2 infection.\nC_LI", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Manina Guenter", - "author_inst": "Deutsches Krebsforschungszentrum Heidelberg" + "author_name": "Kaitlyn M. Sarlo Davila", + "author_inst": "USDA-ARS-NADC" }, { - "author_name": "Karin Anne Lydia Mueller", - "author_inst": "Universitaetsklinikum Tuebingen" + "author_name": "Rahul K. Nelli", + "author_inst": "Iowa State University" }, { - "author_name": "Mathew James Salazar", - "author_inst": "DKFZ" + "author_name": "Kruttika S. Phadke", + "author_inst": "Iowa State University" }, { - "author_name": "Sarah Gekeler", - "author_inst": "Universitaetsklinikum Tuebingen" + "author_name": "Rachel M. Ruden", + "author_inst": "Iowa State University" }, { - "author_name": "Carolin Prang", - "author_inst": "University Hospital Tuebingen" + "author_name": "Yongming Sang", + "author_inst": "Tennessee State University" }, { - "author_name": "Tobias Harm", - "author_inst": "Universitaetsklinikum Tuebingen" + "author_name": "Bryan H. Bellaire", + "author_inst": "Iowa State University" }, { - "author_name": "Meinrad Gawaz", - "author_inst": "Universit\u00e4t T\u00fcbingen" + "author_name": "Luis G. Gimenez-Lirola", + "author_inst": "Iowa State University" }, { - "author_name": "Stella E. Autenrieth", - "author_inst": "DKFZ" + "author_name": "Laura C Miller", + "author_inst": "Kansas State University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc0", + "type": "new results", + "category": "genomics" }, { "rel_doi": "10.1101/2023.04.24.538161", @@ -108793,27 +108244,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.04.18.23288715", - "rel_title": "Preliminary clinical characteristics of Pediatric Covid-19 cases during the ongoing Omicron XBB.1.16 driven surge in a north Indian city", + "rel_doi": "10.1101/2023.04.19.23288817", + "rel_title": "Mortality among persons with HIV in the United States during the COVID-19 pandemic: a population-level analysis", "rel_date": "2023-04-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.18.23288715", - "rel_abs": "India is experiencing a new surge in Covid-19 cases in most parts of the country. A new sub-variant of Omicron, XBB.1.16 which is far more aggressive and immune evasive than other sub-lineages of Omicron, is responsible for this outbreak. In this preliminary account, we describe key clinical characteristics of SARS-CoV-2 infected children, visiting an outdoor department of a pediatric hospital in a north Indian city. Our preliminary findings show a higher involvement of young infants than older children and mild respiratory illness predominates other presentations. One interesting finding was the presence of itchy, non-purulent conjunctivitis with mucoid discharge and stickiness of eyelids in 42.8% of positive infants. None of the children required hospitalization. All recovered with symptomatic treatment.\n\nKey findingsO_LIThe current ongoing XBB.1.16 driven surge of Covid-19 is causing mild febrile illness in children in India\nC_LIO_LIYoung infants are disproportionately more affected than older children.\nC_LIO_LIUnlike the previous BA.2 Omicron wave, respiratory symptoms are predominating the clinical presentation in young infants in the ongoing surge.\nC_LIO_LIConjunctival involvement is seen in 42.8% of affected infants.\nC_LI", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.19.23288817", + "rel_abs": "BackgroundWhether COVID-19 has had a disproportionate impact on mortality among persons with diagnosed HIV (PWDH) in United States is unclear. Through our macro-scale analysis, we seek to better understand how COVID-19 and subsequent behavioral changes affected mortality among PWDH.\n\nMethodsWe obtained mortality and population size data for the years 2018-2020 from the National HIV Surveillance System (NHSS) for the PWDH population aged [≥]13 years in the United States, and from publicly available data for the general population. We computed mortality rates and excess mortality for both the general and PWDH populations. Stratifications by age, race/ethnicity, and sex-at birth were considered. For each group, we determined whether the 2020 mortality rates and mortality risk ratio showed a statistically significant change from 2018-2019.\n\nResultsMortality rates increased in 2020 from 2018-2019 across the general population in all groups. Among PWDH, mortality rates either increased, or showed no statistically significant change. The mortality risk ratio between PWDH and the general population decreased 7.7% in 2020. Approximately 1550 excess deaths occurred among PWDH in 2020, with Black, Hispanic/Latino and PWDH above 55 and older representing the majority of excess deaths.\n\nConclusionsWhile mortality rates among PWDH increased in 2020 relative to 2018-2019, the increases were smaller than those observed in the general population. This suggests that COVID-19 and resulting behavioral changes among PWDH did not result in disproportionate mortality among PWDH. These findings suggest that COVID-19, and any associated indirect effects, do not represent a proportionally greater risk for PWDH compared to the general population.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Vipin M Vashishtha", - "author_inst": "Mangla Hospital & Research Center" + "author_name": "Alex Viguerie", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Ruiguang Song", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Karin Bosh", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Cynthia M. Lyles", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Puneet Kumar", - "author_inst": "Clinician, Kumar Child clinic, KM Chowk, Sector 12, Dwarka, New Delhi, India" + "author_name": "Paul G. Farnham", + "author_inst": "Centers for Disease Control and Prevention" } ], "version": "1", - "license": "cc_by", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "hiv aids" }, { "rel_doi": "10.1101/2023.04.18.23288763", @@ -110819,55 +110282,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.04.12.23288362", - "rel_title": "Bivalent COVID-19 booster vaccines induce cross-reactive but not BA.5-specific antibodies in polyclonal serum", + "rel_doi": "10.1101/2023.04.10.23288317", + "rel_title": "Social dialogue quality and workers' health as perceived by Belgian trade union representatives during the COVID-19 pandemic.", "rel_date": "2023-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.12.23288362", - "rel_abs": "The question if the bivalent mRNA COVID-19 booster vaccination, containing wild type and BA.5 spike, provides enhanced benefits against BA.5 and similar Omicron subvariants has been widely debated. One concern was an original antigenic sin-like effect which may redirect immune responses to the bivalent vaccine towards the wild type spike and may block de novo generation of BA.5 specific antibodies. Here, we characterized the response to the bivalent vaccine and we performed antibody depletion experiments. Interestingly, when we depleted serum of all antibodies to wild type RBD, we also removed all reactivity to BA.5 RBD. This suggests that all antibodies induced by the bivalent vaccine - at least with the limit of detection of our assay in polyclonal serum - are in fact cross-reactive. This further suggests that, on a serum antibody level, the bivalent vaccine did not induce a de novo response to BA.5.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.10.23288317", + "rel_abs": "BackgroundBesides major employment disruptions, the COVID-19 pandemic has generated policy responses with specific mechanisms to protect workers health. In Belgium, most of these policies were negotiated at national and cross-sectorial level but implemented at company level with company-based collective negotiation playing a key role. This study examines the relationship between trade union representatives perception of social dialogue quality and change in workers physical and mental health in such a context.\n\nMethodsUnion representatives were surveyed throughout Belgium between August and December 2021 through an online questionnaire (N=469). We asked about the way they perceived workers physical and mental health within their companies and explain variations with the self-perceived change in quality of social dialogue as an exposure. We use a modified Poisson regression for binary outcomes on four stratified models that additively account for no control, company characteristics, pre-pandemic self-reported health and COVID-19-related measures. Weights are generated to ensure sector representativeness.\n\nResults30.1% of the sample reported a worsening social dialogue quality during the pandemic. Relative Risks (RR) of poor physical and mental health when social dialogue has worsened are respectively 1.49 [95%CI:1.03; 2.15] and 1.38 [95%CI= 1.09;1.74] when controlling for company characteristics and pre-pandemic health. Adding pandemic-related measures reduces the risk of both poor mental [RR=1.25; 95%CI: 0.84; 1.87] and physical health [RR=1.18; 95%CI:0.94;1.49].\n\nConclusionsAlthough based on self-reported variables, the study shows an association between poor social dialogue quality and poor physical and mental health during the COVID-19 pandemic that must be explored further in post-pandemic context.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Juan Manuel Carreno Quiroz", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Gagandeep Singh", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Anass Abbad", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Temima Yellin", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Komal Srivastava", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Charles Gleason", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Harm van Bakel", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Jacques Wels", + "author_inst": "University College London" }, { - "author_name": "Viviana Simon", - "author_inst": "Icahn School of Medicine" + "author_name": "Natasia Hamarat", + "author_inst": "Universite libre de Bruxelles" }, { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Vanessa De Greef", + "author_inst": "Universite libre de Bruxelles" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2023.04.14.23288575", @@ -112812,35 +112251,83 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.04.07.23288300", - "rel_title": "Association between PM2.5 air pollution, temperature, and sunlight during different infectious stages with the case fatality of COVID-19 in the United Kingdom: a modeling study", - "rel_date": "2023-04-09", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.04.07.23288300", - "rel_abs": "Although the relationship between the environmental factors such as weather conditions and air pollution and COVID-19 case fatality rate (CFR) has been found, the impacts of these factors to which infected cases are exposed at different infectious stages (e.g., virus exposure time, incubation period, and at or after symptom onset) are still unknown. Understanding this link can help reduce mortality rates. During the first wave of COVID-19 in the United Kingdom (UK), the CFR varied widely between and among the four countries of the UK, allowing such differential impacts to be assessed.\n\nWe developed a generalized linear mixed-effect model combined with distributed lag nonlinear models to estimate the odds ratio of the weather factors (i.e., temperature, sunlight, relative humidity, and rainfall) and air pollution (i.e., ozone, NO2, SO2, CO, PM10 and PM2.5) using data between March 26, 2020 and May 12, 2020 in the UK. After retrospectively time adjusted CFR was estimated using back-projection technique, the stepwise model selection method was used to choose the best model based on Akaike information criteria (AIC) and the closeness between the predicted and observed values of CFR.\n\nWe found that the low temperature (8-11{degrees}C), prolonged sunlight duration (11-13hours) and increased PM2.5 (11-18 g/m3) after the incubation period posed a greater risk of death (measured by odds ratio (OR)) than the earlier infectious stages. The risk reached its maximum level when the low temperature occurred one day after (OR = 1.76; 95% CI: 1.10-2.81), prolonged sunlight duration 2-3 days after (OR = 1.50; 95% CI: 1.03-2.18) and increased P.M2.5 at the onset of symptom (OR =1.72; 95% CI: 1.30-2.26). In contrast, prolonged sunlight duration showed a protective effect during the incubation period or earlier.\n\nAfter reopening, many COVID-19 cases will be identified after their symptoms appear. The findings highlight the importance of designing different preventive measures against severe illness or death considering the time before and after symptom onset.", - "rel_num_authors": 4, + "rel_doi": "10.1101/2023.04.05.535806", + "rel_title": "A new tractable method for generating Human Alveolar Macrophage Like cells in vitro to study lung inflammatory processes and diseases", + "rel_date": "2023-04-08", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.04.05.535806", + "rel_abs": "Alveolar macrophages (AMs) are unique lung resident cells that contact airborne pathogens and environmental particulates. The contribution of human AMs (HAM) to pulmonary diseases remains poorly understood due to difficulty in accessing them from human donors and their rapid phenotypic change during in vitro culture. Thus, there remains an unmet need for cost-effective methods for generating and/or differentiating primary cells into a HAM phenotype, particularly important for translational and clinical studies. We developed cell culture conditions that mimic the lung alveolar environment in humans using lung lipids, i.e., Infasurf (calfactant, natural bovine surfactant) and lung-associated cytokines (GM-CSF, TGF-{beta}, and IL-10) that facilitate the conversion of blood-obtained monocytes to an AM-Like (AML) phenotype and function in tissue culture. Similar to HAM, AML cells are particularly susceptible to both Mycobacterium tuberculosis and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. This study reveals the importance of alveolar space components in the development and maintenance of HAM phenotype and function, and provides a readily accessible model to study HAM in infectious and inflammatory disease processes, as well as therapies and vaccines.\n\nIMPORTANCEMillions die annually from respiratory disorders. Lower respiratory track gas-exchanging alveoli maintain a precarious balance between fighting invaders and minimizing tissue damage. Key players herein are resident AMs. However, there are no easily accessible in vitro models of HAMs, presenting a huge scientific challenge. Here we present a novel model for generating AML cells based on differentiating blood monocytes in a defined lung component cocktail. This model is non-invasive, significantly less costly than performing a bronchoalveolar lavage, yields more AML cells than HAMs per donor and retains their phenotype in culture. We have applied this model to early studies of M. tuberculosis and SARS-CoV-2. This model will significantly advance respiratory biology research.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "M. Pear Hossain", - "author_inst": "City University of Hong Kong" + "author_name": "Susanta Pahari", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Wen Zhou", - "author_inst": "4. School of Energy and Environment, City University of Hong Kong, Hong Kong Special Administrative Region, China. 5. Department of Atmospheric and Oceanic Scie" + "author_name": "Eusondia Arnett", + "author_inst": "Ohio State University" }, { - "author_name": "Marco Y. T. Leung", - "author_inst": "6. School of Marine Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China" + "author_name": "Jan Simper", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Hsiang-Yu Yuan", - "author_inst": "1. Department of Biomedical Sciences, Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Hong Kong Special Administrati" + "author_name": "Abul Azad", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Israel Guerrero-Arguero", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Chengjin Ye", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Hao Zhang", + "author_inst": "University of Texas at San Antonio" + }, + { + "author_name": "Hong Cai", + "author_inst": "University of Texas at San Antonio" + }, + { + "author_name": "Yufeng Wang", + "author_inst": "University of Texas at San Antonio" + }, + { + "author_name": "Natalie Jarvis", + "author_inst": "University of Iowa Hospitals and Clinics" + }, + { + "author_name": "Miranda Lumbreras", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Diego Jose Maselli-Caceres", + "author_inst": "The University of Texas Health Science Center at San Antonio" + }, + { + "author_name": "Jay I Peters", + "author_inst": "The Universiy of Texas Health San Antonio" + }, + { + "author_name": "Jordi B Torrelles", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Luis Mart \u00ednez-Sobrido", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Larry S Schlesinger", + "author_inst": "Texas Biomedical Research Institute" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2023.04.03.535504", @@ -114774,43 +114261,35 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2023.03.30.23287969", - "rel_title": "A Graph Embedding Approach for Deciphering the Longitudinal Associations of Global Mobility and COVID-19 Cases", + "rel_doi": "10.1101/2023.03.31.23288023", + "rel_title": "Pharmaceutical and Non-Pharmaceutical Interventions for Controlling the COVID-19 Pandemic", "rel_date": "2023-04-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.30.23287969", - "rel_abs": "The COVID-19 pandemic has highlighted the importance of monitoring mobility patterns and their impact on disease spread. This paper presents a methodology for developing effective pandemic surveillance systems by extracting scalable graph features from mobility networks. We utilized Metas \"Travel Patterns\" dataset to capture the daily number of individuals traveling between countries from March 2020 to April 2022. We have used an optimized node2vec algorithm to extract scalable features from the mobility networks. Our analysis revealed that movement embeddings accurately represented the movement patterns of countries, with geographically proximate countries exhibiting similar movement patterns. The temporal association dynamics between Global mobility and COVID-19 cases highlighted the significance of high-page rank centrality countries in mobility networks as a key intervention target in controlling infection spread. Our proposed methodology provides a useful approach for tracking the trajectory of infectious diseases and developing evidence-based interventions.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.31.23288023", + "rel_abs": "Disease spread can be affected by pharmaceutical (such as vaccination) and non-pharmaceutical interventions (such as physical distancing, mask-wearing, and contact tracing). Understanding the relationship between disease dynamics and human behavior is a significant factor to controlling infections. In this work, we propose a compartmental epidemiological model for studying how the infection dynamics of COVID-19 evolves for people with different levels of social distancing, natural immunity, and vaccine-induced immunity. Our model recreates the transmission dynamics of COVID-19 in Ontario up to December 2021. Our results indicate that people change their behaviour based on the disease dynamics and mitigation measures. Specifically, they adapt more protective behaviour when the number of infections is high and social distancing measures are in effect, and they recommence their activities when vaccination coverage is high and relaxation measures are introduced. We demonstrate that waning of infection and vaccine-induced immunity are important for reproducing disease transmission in Fall 2021.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Raghav Awasthi", - "author_inst": "Indraprastha Institute of Information Technology, Delhi" - }, - { - "author_name": "Meet Modi", - "author_inst": "Indraprastha Institute of Information Technology, Delhi" - }, - { - "author_name": "Hardik Dudeja", - "author_inst": "Indraprastha Institute of Information Technology, Delhi" + "author_name": "Jeta Molla", + "author_inst": "York University" }, { - "author_name": "Tanav Bajaj", - "author_inst": "Indian Institute of Information Technology, Bhopal" + "author_name": "Suzan Farhang-Sardroodi", + "author_inst": "University of Manitoba" }, { - "author_name": "Shruti Rastogi", - "author_inst": "BITS Pilani, K.K.Birla Goa Campus" + "author_name": "Iain R Moyles", + "author_inst": "York University" }, { - "author_name": "Tavpritesh Sethi", - "author_inst": "Indraprastha Institute of Information Technology, Delhi" + "author_name": "Jane M Heffernan", + "author_inst": "York University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.03.31.23288026", @@ -116503,75 +115982,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.24.23287658", - "rel_title": "Safety and Immunogenicity of the NVX-CoV2373 Vaccine as a Booster in Adults Previously Vaccinated with the BBIBP-CorV Vaccine: An Interim Analysis", + "rel_doi": "10.1101/2023.03.26.23287758", + "rel_title": "Impact of opinion dynamics on the public health damage inflicted by COVID-19 in the presence of societal heterogeneities", "rel_date": "2023-03-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.24.23287658", - "rel_abs": "This phase 3 observer-blind, randomized, controlled study was conducted in adults [≥]18 years of age to assess the safety and immunogenicity of NVX-CoV2373 as a heterologous booster compared to BBIBP-CorV when utilized as a homologous booster. Approximately 1,000 participants were randomly assigned in a 1:1 ratio to receive a single dose of NVX-CoV2373 or BBIBP-CorV after prior vaccination with 2 or 3 doses of BBIBP-CorV. Solicited adverse events (AEs) were collected for 7 days after vaccination. Unsolicited AEs were collected for 28 days following the booster dose and serious adverse and adverse events of special interest (AESI) were collected throughout the study. For this interim analysis, anti-spike IgG and neutralizing antibodies against SARS-CoV-2 were measured at baseline, day 14, and day 28. The study achieved its primary non-inferiority endpoint and also demonstrated statistically higher neutralization responses of approximately 6-fold when NVX-CoV2373 was utilized as a heterologous booster compared with BBIBP-CorV as a homologous booster. Both vaccines had an acceptably low reactogenicity profile and no new safety concerns were found. Heterologous boosting with NVX-CoV2373 was a highly immunogenic and safe vaccine regimen in those previously vaccinated with BBIBP-CorV.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.26.23287758", + "rel_abs": "Certain behavioral practices such as wearing surgical masks, observing social distancing, and accepting vaccines impede the spread of COVID-19 and contain the severity of symptoms in the infected individuals. Opinions regarding whether to observe such behavioral practices evolve over time through interactions via networks that overlap with but are not identical to the physical interaction networks over which the disease progresses. This necessitates the joint study of COVID-19 evolution and opinion dynamics. We develop a mathematical model that can be easily adapted to a wide range of behavioral practices and captures in a computationally tractable manner the joint evolution of the disease and relevant opinions in populations of large sizes. Populations of large sizes are typically heterogeneous in that they comprise individuals of different age groups, genders, races, and underlying health conditions. Such groups have different propensities to imbibe severe forms of the disease, different physical contact, and social interaction patterns and rates. These lead to different disease and opinion dynamics in them. Our model is able to capture such diversities. Computations using our model reveal that opinion dynamics have a strong impact on fatality and hospitalization counts and the number of man-days lost due to symptoms both in the regular form of the disease and the extended forms, more commonly known as long COVID. We show that opinion dynamics in certain groups have a disproportionate impact on the overall public health attributes because they have high physical interaction rates, even when they have the lowest propensity to imbibe severe forms of the disease. This identifies a social vulnerability that mal-actors can utilize to inflict heavy public health damages through opinion campaigns targeting specific segments. Once such vulnerabilities are identified, which we accomplish, adequate precautions may be designed to enhance resilience to such targeted attacks and better protect public health.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Seth Toback", - "author_inst": "Novavax Inc." - }, - { - "author_name": "Anthony M. Marchese", - "author_inst": "Novavax Inc." - }, - { - "author_name": "Brandy Warren", - "author_inst": "Novavax Inc." - }, - { - "author_name": "Sondos Ayman", - "author_inst": "Insights Research Organization & Solutions" - }, - { - "author_name": "Senka Zarkovic", - "author_inst": "Insights Research Organization & Solutions" - }, - { - "author_name": "Islam ElTantawy", - "author_inst": "Insights Research Organization & Solutions" - }, - { - "author_name": "Raburn M. Mallory", - "author_inst": "Novavax Inc." - }, - { - "author_name": "Matthew Rousculp", - "author_inst": "Novavax Inc." - }, - { - "author_name": "Fahed Almarzooqi", - "author_inst": "G42 Healthcare" - }, - { - "author_name": "Bartlomiej Piechowski-Jozwiak", - "author_inst": "Cleveland Clinic Abu Dhabi" - }, - { - "author_name": "Maria-Fernanda Bonilla", - "author_inst": "Cleveland Clinic Abu Dhabi" - }, - { - "author_name": "Agyad Ebrahim Bakkour", - "author_inst": "Sheikh Khalifa Medical City" - }, - { - "author_name": "Salah Eldin Hussein", - "author_inst": "Sheikh Khalifa Medical City" + "author_name": "Rex N. Ali", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Nawal Al Kaabi", - "author_inst": "Sheikh Khalifa Medical City; College of Medicine and Health Sciences, Khalifa University" + "author_name": "Saswati Sarkar", + "author_inst": "University of Pennsylvania" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.03.27.23287835", @@ -118061,39 +117492,167 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2023.03.24.534062", - "rel_title": "Intra-Host Mutation Rate of Acute SARS-CoV-2 Infection During the Initial Pandemic Wave", + "rel_doi": "10.1101/2023.03.25.23287563", + "rel_title": "Longitudinal wastewater surveillance addressed public health priorities during the transition from \"dynamic COVID-zero\" to \"opening up\" in China: a population-based study", "rel_date": "2023-03-25", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.24.534062", - "rel_abs": "BackgroundOur understanding of SARS-CoV-2 evolution and mutation rate is limited. The rate of SARS-CoV-2 evolution is minimized through a proofreading function encoded by NSP-14 and may be affected by patient comorbidity. Current understanding of SARS-CoV-2 mutational rate is through population based analysis while intra-host mutation rate remains poorly studied.\n\nMethodsViral genome analysis was performed between paired samples and mutations quantified at allele frequencies (AF) [≥]0.25, [≥]0.5 and [≥]0.75. Mutation rate was determined employing F81 and JC69 evolution models and compared between isolates with ({Delta}NSP-14) and without (wtNSP-14) non-synonymous mutations in NSP-14 and by patient comorbidity.\n\nResultsForty paired samples with median interval of 13 days [IQR 8.5-20] were analyzed. The estimated mutation rate by F81 modeling was 93.6 (95%CI:90.8-96.4], 40.7 (95%CI:38.9-42.6) and 34.7 (95%CI:33.0-36.4) substitutions/genome/year at AF [≥]0.25, [≥]0.5, [≥]0.75 respectively. Mutation rate in {Delta}NSP-14 were significantly elevated at AF>0.25 vs wtNSP-14. Patients with immune comorbidities had higher mutation rate at all allele frequencies.\n\nDiscussionIntra-host SARS-CoV-2 mutation rates are substantially higher than those reported through population analysis. Virus strains with altered NSP-14 have accelerated mutation rate at low AF. Immunosuppressed patients have elevated mutation rate at all AF. Understanding intra-host virus evolution will aid in current and future pandemic modeling.", - "rel_num_authors": 5, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.25.23287563", + "rel_abs": "BackgroundWastewater surveillance provides real-time, cost-effective monitoring of SARS-CoV-2 transmission. We developed the first city-level wastewater warning system in mainland China, located in Shenzhen. Our study aimed to reveal cryptic transmissions under the \"dynamic COVID-zero\" policy and characterize the dynamics of the infected population and variant prevalence, and then guide the allocation of medical resources during the transition to \"opening up\" in China.\n\nMethodsIn this population-based study, a total of 1,204 COVID-19 cases were enrolled to evaluate the contribution of Omicron variant-specific faecal shedding rates in wastewater. After that, wastewater samples from up to 334 sites distributed in communities and port areas in two districts of Shenzhen covering 1{middle dot}74 million people were tested daily to evaluate the sensitivity and specificity of this approach, and were validated against daily SARS-CoV-2 screening. After the public health policy was switched to \"opening up\" in December 7, 2022, we conducted wastewater surveillance at wastewater treatment plants and pump stations covering 3{middle dot}55 million people to estimate infected populations using model prediction and detect the relative abundance of SARS-CoV-2 lineages using wastewater sequencing.\n\nFindingsIn total, 82{middle dot}4% of SARS-CoV-2 Omicron cases tested positive for faecal viral RNA within the first four days after the diagnosis, which was far more than the proportion of the ancestral variant. A total of 27,759 wastewater samples were detected from July 26 to November 30 in 2022, showing a sensitivity of 73{middle dot}8% and a specificity of 99{middle dot}8%. We further found that wastewater surveillance played roles in providing early warnings and revealing cryptic transmissions in two communities. Based on the above results, we employed a prediction model to monitor the daily number of infected individuals in Shenzhen during the transition to \"opening up\" in China, with over 80% of the population infected in both Futian District and Nanshan District. Notably, the prediction of the daily number of hospital admission was consistent with the actual number. Further sequencing revealed that the Omicron subvariant BA.5.2.48 accounted for the most abundant SARS-CoV-2 RNA in wastewater, and BF.7.14 and BA.5.2.49 ranked second and third, respectively, which was consistent with the clinical sequencing.\n\nInterpretationThis study provides a scalable solution for wastewater surveillance of SARS-CoV-2 to provide real-time monitoring of the new variants, infected populations and facilitate the precise prediction of hospital admission. This novel framework could be a One Health system for the surveillance of other infectious and emerging pathogens with faecal shedding and antibiotic resistance genes in the future.\n\nFundingSanming Project of Medicine in Shenzhen, Shenzhen Key Medical Discipline Construction Fund.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for articles published from December 1, 2019, to February 28, 2023, without any language restrictions, using the search terms \"wastewater surveillance\", \"SARS-CoV-2 shedding rate\", and \"China\". After checking abstracts and full texts of the search results, we found that the field of wastewater-based epidemiology (WBE) has been considered as a powerful, rapid, and inexpensive tool to monitor SARS-CoV-2 transmission in recent years. Researchers realized that SARS-CoV-2 RNA in wastewater is mainly from the faecal virus shedding of infected individuals, and the number of infected individuals can be estimated using a prediction model based on the viral RNA load in wastewater and the faecal viral shedding rate. However, there are no published clinical data regarding the faecal shedding rates of the pandemic variant Omicron. In particular, no previous studies have reported the size of Chinas SARS-CoV-2 infection after the public health policy was switched to \"opening up\" in December 7, 2022.\n\nAdded value of this studyThis study highlights pioneering work in the use of wastewater surveillance of SARS-CoV-2 conducted during the transition from \"dynamic COVID-zero\" to \"opening up\" in China. The study reported first about the high proportion of faecal viral shedding of SARS-CoV-2 Omicron cases, showcasing the generality of wastewater surveillance for tracking Omicron prevalence. On the one hand, wastewater surveillance can play roles in providing early warnings and revealing cryptic transmissions and has the potential to replace city-wide nucleic acid screening under stringent control measures. On the flip side, wastewater surveillance allows for robust predictions of the number of infected individuals, the relative abundance of SARS-CoV-2 lineages, and the rate of hospital admission after the public health policy was switched to relaxed COVID-19 restrictions.\n\nImplications of all the available evidenceGovernments are in urgent need of a paradigm to shorten the time lag observed between recognition of a new emerging pathogen with the potential to cause the next pandemic (e.g., SARS-CoV-2) and the development of public health response (e.g., early warning, management and control of the communities, allocation of medical resources). Our findings suggest that the system developed in this study is not only a valuable epidemiological tool to accurately monitor the infection trend but also transforms wastewater surveillance into a public health management framework, which could be a One Health system for the surveillance of other infectious and emerging pathogens with faecal shedding and antibiotic resistance genes.", + "rel_num_authors": 37, "rel_authors": [ { - "author_name": "Thamali Madhu Adhikari", - "author_inst": "Case Western Reserve University" + "author_name": "Yinghui Li", + "author_inst": "Shenzhen Center for Disease Control and Prevention" }, { - "author_name": "Xiaoyi Leng", - "author_inst": "Case Western Reserve University" + "author_name": "Chen Du", + "author_inst": "Shenzhen Center for Disease Control and Prevention" }, { - "author_name": "Xiangyi Zhang", - "author_inst": "Case Western Reserve University" + "author_name": "Ziquan Lv", + "author_inst": "Shenzhen Center for Disease Control and Prevention" }, { - "author_name": "Sarah Worley", - "author_inst": "Cleveland Clinic Foundation: Cleveland Clinic" + "author_name": "Fuxiang Wang", + "author_inst": "Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Afliated to Southern University of Science and Technology" }, { - "author_name": "Jing Li", - "author_inst": "Case Western Reserve University" + "author_name": "Liping Zhou", + "author_inst": "Health Commission of Shenzhen Municipality" + }, + { + "author_name": "Yuejing Peng", + "author_inst": "BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University" + }, + { + "author_name": "Wending Li", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Yulin Fu", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Jiangteng Song", + "author_inst": "Water Ecology and Environment Division, Shenzhen Ecology and Environment Bureau" + }, + { + "author_name": "Chunyan Jia", + "author_inst": "Water Ecology and Environment Division, Shenzhen Ecology and Environment Bureau" + }, + { + "author_name": "Xin Zhang", + "author_inst": "Water Ecology and Environment Division, Shenzhen Ecology and Environment Bureau" + }, + { + "author_name": "Mujun Liu", + "author_inst": "Futian District Water Authority" + }, + { + "author_name": "Zimiao Wang", + "author_inst": "Futian District Water Authority" + }, + { + "author_name": "Bin Liu", + "author_inst": "Futian District Water Authority" + }, + { + "author_name": "Shulan Yan", + "author_inst": "Nanshan District Water Authority" + }, + { + "author_name": "Yuxiang Yang", + "author_inst": "Nanshan District Water Authority" + }, + { + "author_name": "Xueyun Li", + "author_inst": "Futian District Center for Disease Control and Prevention" + }, + { + "author_name": "Yong Zhang", + "author_inst": "Futian District Center for Disease Control and Prevention" + }, + { + "author_name": "Jianhui Yuan", + "author_inst": "Nanshan District Center for Disease Control and Prevention" + }, + { + "author_name": "Shikuan Xu", + "author_inst": "Nanshan District Center for Disease Control and Prevention" + }, + { + "author_name": "Miaoling Chen", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Xiaolu Shi", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Bo Peng", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Qiongcheng Chen", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Yaqun Qiu", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Shuang Wu", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Min Jiang", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Miaomei Chen", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Jinzhen Tang", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Lei Wang", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Lulu Hu", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Chengsong Wan", + "author_inst": "BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University" + }, + { + "author_name": "Hongzhou Lu", + "author_inst": "Department of Infectious Diseases, Shenzhen Third People's Hospital, Second Hospital Afliated to Southern University of Science and Technology" + }, + { + "author_name": "Tong Zhang", + "author_inst": "Environmental Microbiome Engineering and Biotechnology Laboratory, Center for Environmental Engineering Research, Department of Civil Engineering, The Universit" + }, + { + "author_name": "Songzhe Fu", + "author_inst": "Key Laboratory of Environment Controlled Aquaculture Ministry of Education,Dalian Ocean University" + }, + { + "author_name": "Xuan Zou", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Qinghua Hu", + "author_inst": "Shenzhen Center for Disease Control and Prevention" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "evolutionary biology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2023.03.21.23287410", @@ -119583,31 +119142,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.03.20.23287490", - "rel_title": "The Change of Screen Time and Screen Addiction, and their Association with Psychological Well-being During the COVID-19 Pandemic: An Analysis of US Country-Wide School-Age Children and Adolescents Between 2018 and 2020", - "rel_date": "2023-03-21", + "rel_doi": "10.1101/2023.03.14.23287121", + "rel_title": "First-in-human immunoPET imaging of COVID-19 convalescent patients using dynamic total-body PET and a CD8-targeted minibody", + "rel_date": "2023-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.20.23287490", - "rel_abs": "Previous studies on screen use and childrens mental health during the Coronavirus Disease 2019 (COVID-19) pandemic either focused only on the timeframe during the pandemic, or only on children previously reporting COVID-related severe family economic hardship or worries. Instead, we used a large sample (n=63,211) of the National Survey of Childrens Health (NSCH) years 2018-20 to analyze changes in the trends of recreational screen device use before, versus during the COVID-19 pandemic, and associations with psychological well-being, widely among school-age children (6-17 year-olds) across the US. We assessed recreational screen use, instead of overall use including both instructional and recreational use, and developed psychological well-being issue scores to evaluate the associations among the pandemic, recreational screen use, and psychological well-being states. We found an increase in the prevalence of screen overuse/addiction and psychological well-being issues during the pandemic compared to the years prior, detected an association between the pandemic and psychological well-being issue scores (p <0.01 across all models), and observed increased magnitude of association between recreational screen overuse/addiction and mental health during the pandemic year (p <0.01 across all models). Further studies on elucidating and addressing the specific aspects of the pandemic that contribute to these associations are critical.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.14.23287121", + "rel_abs": "With the majority of CD8+ T cells residing and functioning in tissue, not blood, developing noninvasive methods for in vivo quantification of their biodistribution and kinetics in humans offers the means for studying their key role in adaptive immune response and memory. This study is the first report on using positron emission tomography (PET) dynamic imaging and compartmental kinetic modeling for in vivo measurement of whole-body biodistribution of CD8+ T cells in human subjects. For this, a 89Zr-labeled minibody with high affinity for human CD8 (89Zr-Df-Crefmirlimab) was used with total-body PET in healthy subjects (N=3) and in COVID-19 convalescent patients (N=5). The high detection sensitivity, total-body coverage, and the use of dynamic scans enabled the study of kinetics simultaneously in spleen, bone marrow, liver, lungs, thymus, lymph nodes, and tonsils, at reduced radiation doses compared to prior studies. Analysis and modeling of the kinetics was consistent with T cell trafficking effects expected from immunobiology of lymphoid organs, suggesting early uptake in spleen and bone marrow followed by redistribution and delayed increasing uptake in lymph nodes, tonsils, and thymus. Tissue-to-blood ratios from the first 7 h of CD8-targeted imaging showed significantly higher values in the bone marrow of COVID-19 patients compared to controls, with an increasing trend between 2 and 6 months post-infection, consistent with net influx rates obtained by kinetic modeling and flow cytometry analysis of peripheral blood samples. These results provide the platform for using dynamic PET scans and kinetic modelling to study total-body immunological response and memory.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Helena T Wu", - "author_inst": "Massachusetts General Hospital" + "author_name": "Negar Omidvari", + "author_inst": "University of California Davis, Department of Biomedical Engineering" }, { - "author_name": "Jiandong Li", - "author_inst": "Central University of Finance and Economics" + "author_name": "Terry Jones", + "author_inst": "University of California Davis, Department of Radiology" }, { - "author_name": "Amy Tsurumi", - "author_inst": "Massachusetts General Hospital" + "author_name": "Pat M Price", + "author_inst": "Imperial College London, Department of Surgery and Cancer" + }, + { + "author_name": "April L Ferre", + "author_inst": "University of California Davis, School of Medicine, Department of Medical Microbiology and Immunology" + }, + { + "author_name": "Jacqueline Lu", + "author_inst": "University of California Davis, School of Medicine, Department of Medical Microbiology and Immunology" + }, + { + "author_name": "Yasser G Abdelhafez", + "author_inst": "University of California Davis, Department of Radiology; Assiut University, South Egypt Cancer Institute, Radiotherapy and Nuclear Medicine Department;" + }, + { + "author_name": "Fatma Sen", + "author_inst": "University of California Davis, Department of Radiology" + }, + { + "author_name": "Stuart H Cohen", + "author_inst": "University of California Davis, Department of Internal Medicine" + }, + { + "author_name": "Kristin Schmiedehausen", + "author_inst": "ImaginAb, Inc." + }, + { + "author_name": "Ramsey D Badawi", + "author_inst": "University of California Davis, Department of Biomedical Engineering; University of California Davis, Department of Radiology;" + }, + { + "author_name": "Barbara L Shacklett", + "author_inst": "University of California Davis, School of Medicine, Department of Medical Microbiology and Immunology; University of California Davis, Department of Internal Me" + }, + { + "author_name": "Ian Wilson", + "author_inst": "ImaginAb, Inc." + }, + { + "author_name": "Simon R Cherry", + "author_inst": "University of California Davis, Department of Biomedical Engineering; University of California Davis, Department of Radiology;" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.03.19.23287456", @@ -121584,52 +121183,124 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2023.03.16.23287360", - "rel_title": "Relative vaccine effectiveness (rVE) of mRNA COVID-19 boosters in the UK vaccination programme, during the Spring-Summer (monovalent vaccine) and Autumn-Winter 2022 (bivalent vaccine) booster campaigns: a prospective test negative case-control study", + "rel_doi": "10.1101/2023.03.17.533092", + "rel_title": "Antibodies generated in vitro and in vivo elucidate design of a thermostable ADDomer COVID-19 nasal nanoparticle vaccine", "rel_date": "2023-03-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.16.23287360", - "rel_abs": "BackgroundUnderstanding the relative vaccine effectiveness (rVE) of new COVID-19 vaccine formulations against SARS-CoV-2 infection is an urgent public health priority. A precise analysis of the rVE of monovalent and bivalent boosters given during the 2022 Spring-Summer and Autumn-Winter campaigns, respectively, in a defined population has not been reported.\n\nAimWe therefore assessed rVE against hospitalisation for the Spring-Summer (fourth vs third monovalent mRNA vaccine doses) and Autumn-Winter (fifth BA.1/ancestral bivalent vs fourth monovalent mRNA vaccine dose) boosters.\n\nMethodsA prospective single-centre test-negative design case-control study of [≥]75 year-olds hospitalised with COVID-19 or other acute respiratory disease. We conducted regression analyses controlling for age, sex, socioeconomic status, patient comorbidities, community SARS-CoV-2 prevalence, vaccine brand and time between baseline dose and hospitalisation.\n\nResults682 controls and 182 cases were included in the Spring-Summer booster analysis; 572 controls and 152 cases for the Autumn-Winter booster analysis. A monovalent mRNA COVID-19 vaccine as fourth dose showed rVE 46{middle dot}6% (95% confidence interval [CI] 13{middle dot}9-67{middle dot}1) versus those not fully boosted. A bivalent mRNA COVID-19 vaccine as fifth dose had rVE 46{middle dot}7% (95%CI 18-65{middle dot}1), compared to a fourth monovalent mRNA COVID-19 vaccine dose.\n\nConclusionsBoth fourth monovalent and fifth BA.1/ancestral mRNA bivalent COVID-19 vaccine doses demonstrated benefit as a booster in older adults. Bivalent mRNA boosters offer similar protection against hospitalisation with Omicron infection to monovalent mRNA boosters given earlier in the year. These findings support immunisation programmes in several European countries that advised the use of BA.1/ancestral bivalent booster doses.", - "rel_num_authors": 13, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.17.533092", + "rel_abs": "COVID-19 continues to damage populations, communities and economies worldwide. Vaccines have reduced COVID-19-related hospitalisations and deaths, primarily in developed countries. Persisting infection rates, and highly transmissible SARS-CoV-2 Variants of Concern (VOCs) causing repeat and breakthrough infections, underscore the ongoing need for new treatments to achieve a global solution. Based on ADDomer, a self-assembling protein nanoparticle scaffold, we created ADDoCoV, a thermostable COVID-19 candidate vaccine displaying multiple copies of a SARS-CoV-2 receptor binding motif (RBM)-derived epitope. In vitro generated neutralising nanobodies combined with molecular dynamics (MD) simulations and electron cryo-microscopy (cryo-EM) established authenticity and accessibility of the epitopes displayed. A Gigabody comprising multimerized nanobodies prevented SARS-CoV-2 virion attachment with picomolar EC50. Antibodies generated by immunising mice cross-reacted with VOCs including Delta and Omicron. Our study elucidates nasal administration of ADDomer-based nanoparticles for active and passive immunisation against SARS-CoV-2 and provides a blueprint for designing nanoparticle reagents to combat respiratory viral infections.", + "rel_num_authors": 35, "rel_authors": [ { - "author_name": "Anastasia Chatzilena", + "author_name": "Dora Buzas", "author_inst": "University of Bristol" }, { - "author_name": "Catherine Hyams", + "author_name": "Hans Adrian Bunzel", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Oskar Staufer", + "author_inst": "Leibniz Institute for New Materials, Helmholtz Institute for Pharmaceutical Research and Center for Biophysics, Saarland University, Germany" + }, + { + "author_name": "Emily Milodowski", "author_inst": "University of Bristol" }, { - "author_name": "Robert Challen", + "author_name": "Grace Edmonds", "author_inst": "University of Bristol" }, { - "author_name": "Robin Marlow", + "author_name": "Joshua Bufton", "author_inst": "University of Bristol" }, { - "author_name": "Jade King", + "author_name": "Beatriz Vidana Matteo", "author_inst": "University of Bristol" }, { - "author_name": "David Adegbite", + "author_name": "Sathish Yadav", "author_inst": "University of Bristol" }, { - "author_name": "Jane Kinney", + "author_name": "Kapil Gupta", + "author_inst": "Imophoron Ltd" + }, + { + "author_name": "Charlotte Fletcher", "author_inst": "University of Bristol" }, { - "author_name": "Madeleine Clout", + "author_name": "Maia Kavanagh Williamson", "author_inst": "University of Bristol" }, { - "author_name": "Nick Maskell", + "author_name": "Alexandra Harrison", "author_inst": "University of Bristol" }, { - "author_name": "Jennifer Oliver", + "author_name": "Ufuk Borucu", + "author_inst": "University of Bristol" + }, + { + "author_name": "Julien Capin", + "author_inst": "University of Bristol" + }, + { + "author_name": "Ore Francis", + "author_inst": "University of Bristol" + }, + { + "author_name": "Georgia Balchin", + "author_inst": "University of Bristol" + }, + { + "author_name": "Sophie Hall", + "author_inst": "University of Bristol" + }, + { + "author_name": "Mirella Vivoli Vega", + "author_inst": "University of Bristol" + }, + { + "author_name": "Fabien Durbesson", + "author_inst": "AFMB Marseille France" + }, + { + "author_name": "Renaud Vincentelli", + "author_inst": "AFMB" + }, + { + "author_name": "Joe Roe", + "author_inst": "University of Bristol" + }, + { + "author_name": "Linda Wooldridge", + "author_inst": "University of Bristol" + }, + { + "author_name": "Rachel Burt", + "author_inst": "University of Bristol" + }, + { + "author_name": "Ross Anderson", + "author_inst": "University of Bristol" + }, + { + "author_name": "Adrian J Mulholland", + "author_inst": "University of Bristol" + }, + { + "author_name": "Jonathan Hare", + "author_inst": "Imophoron Ltd" + }, + { + "author_name": "Mick Bailey", + "author_inst": "University of Bristol" + }, + { + "author_name": "Andrew Davidson", "author_inst": "University of Bristol" }, { @@ -121637,18 +121308,34 @@ "author_inst": "University of Bristol" }, { - "author_name": "Leon Danon", - "author_inst": "Department of Engineering Mathematics, University of Bristol, UK." + "author_name": "David Morgan", + "author_inst": "University of Bristol" }, { - "author_name": "- The AvonCAP Research Group", - "author_inst": "-" + "author_name": "Jamie Mann", + "author_inst": "University of Bristol" + }, + { + "author_name": "Joachim Spatz", + "author_inst": "Max Planck Institute for Medical Research Heidelberg" + }, + { + "author_name": "Frederic Garzoni", + "author_inst": "Imophoron Ltd" + }, + { + "author_name": "Christiane Schaffitzel", + "author_inst": "University of Bristol UK" + }, + { + "author_name": "Imre Berger", + "author_inst": "University of Bristol" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2023.03.17.23287403", @@ -123438,47 +123125,59 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2023.03.11.23287138", - "rel_title": "How long is the long COVID? a retrospective analysis of football players in two major European Championships.", + "rel_doi": "10.1101/2023.03.13.532446", + "rel_title": "Murine Alveolar Macrophages Rapidly Accumulate Intranasally Administered SARS-CoV-2 Spike Protein leading to Neutrophil Recruitment and Damage", "rel_date": "2023-03-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.11.23287138", - "rel_abs": "Objectivesthe goal of this study was to investigate the correlation between SARS-CoV-2 infection and muscle injuries among a large sample of professional soccer players.\n\nMethodsA retrospective cohort study was conducted on professional soccer players from the Serie A and LaLiga leagues during the 2019-2020 and 2020-2021 football seasons. The players were divided into two groups based on whether they contracted the Sars-CoV-2 infection (C+) or not (C-) during the 2020/2021 season. Data collection was conducted using the Transfermarkt24 site.\n\nResultsIn the 2019-2020 both championships showed non-significant differences in the average number of muscular injuries between the C+ group and the C- group (Serie A: p=0.194; 95%CI: - 0.044 to 0.215, LaLiga p=0.915; 95%CI: -0.123 to 0.137). In the 2020-2021 the C+ group had a significantly higher number of muscular injuries compared to the C- group in both championships (Serie A: p<0.001; 95%CI 0.731 to 1.038; LaLiga: p<0.001; 95%CI: 0.773 to 1.054). Multiple linear regression analysis confirmed that belonging to C+ in the season 2020/2021 was the variable that most strongly influenced the probability of having a muscle injury in both championships. Survival analysis revealed a hazard ratio of 3.73 (95%CI 3.018 to 4.628) and of 5.14 (95% CI 3.200 to 8.254) for Serie A and LaLiga respectively.\n\nConclusionsThis retrospective cohort study revealed a significant association between SARS-CoV-2 infection and increased risk of muscle injury, emphasizing the importance of carefully considering the infection in the decision-making process for determining athletes readiness to return to sport.", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.13.532446", + "rel_abs": "The trimeric SARS-CoV-2 Spike protein mediates viral attachment facilitating cell entry. Most COVID-19 vaccines direct mammalian cells to express the Spike protein or deliver it directly via inoculation to engender a protective immune response. The trafficking and cellular tropism of the Spike protein in vivo and its impact on immune cells remains incompletely elucidated. In this study we inoculated mice intranasally, intravenously, and subcutaneously with fluorescently labeled recombinant SARS-CoV-2 Spike protein. Using flow cytometry and imaging techniques we analyzed its localization, immune cell tropism, and acute functional impact. Intranasal administration led to rapid lung alveolar macrophage uptake, pulmonary vascular leakage, and neutrophil recruitment and damage. When injected near the inguinal lymph node medullary, but not subcapsular macrophages, captured the protein, while scrotal injection recruited and fragmented neutrophils. Wide-spread endothelial and liver Kupffer cell uptake followed intravenous administration. Human peripheral blood cells B cells, neutrophils, monocytes, and myeloid dendritic cells all efficiently bound Spike protein. Exposure to the Spike protein enhanced neutrophil NETosis and augmented human macrophage TNF- and IL-6 production. Human and murine immune cells employed C-type lectin receptors and Siglecs to help capture the Spike protein. This study highlights the potential toxicity of the SARS-CoV-2 Spike protein for mammalian cells and illustrates the central role for alveolar macrophage in pathogenic protein uptake.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Sandra Miccinilli", - "author_inst": "Fondazione Policlinico Universitario Campus Bio-Medico" + "author_name": "Chung Park", + "author_inst": "National Institutes of Allergy and Infectious Diseases" }, { - "author_name": "Marco Bravi", - "author_inst": "Fondazione Policlinico Universitario Campus Bio-Medico" + "author_name": "Il-Young Hwang", + "author_inst": "National Institutes of Allergy and Infectious Diseases" }, { - "author_name": "Giorgio Conti", - "author_inst": "Fondazione Policlinico Universitario Campus Bio-Medico" + "author_name": "Serena Li-Sue Yan", + "author_inst": "National Institutes of Allergy and Infectious Diseases" }, { - "author_name": "Federica Bressi", - "author_inst": "Fondazione Policlinico Universitario Campus Bio-Medico" + "author_name": "Sinmanus Vimonpatranon", + "author_inst": "National Institutes of Allergy and Infectious Diseases" }, { - "author_name": "Silvia Sterzi", - "author_inst": "Fondazione Policlinico Universitario Campus Bio-Medico" + "author_name": "Danlan Wei", + "author_inst": "National Institutes of Allergy and Infectious Diseases" }, { - "author_name": "Fabio Santacaterina", - "author_inst": "Fondazione Policlinico Universitario Campus Bio-Medico" + "author_name": "Don Van Ryk", + "author_inst": "National Institutes of Allergy and Infectious Diseases" }, { - "author_name": "Massimo Ciccozzi", - "author_inst": "Campus Biomedical University of Rome" + "author_name": "Alexandre Girard", + "author_inst": "NIAID, NIH" + }, + { + "author_name": "Claudia Cicala", + "author_inst": "National Institutes of Allergy and Infectious Diseases" + }, + { + "author_name": "James Arthos", + "author_inst": "National Institute of Allergy and Infectious Diseases, National Institutes of Health" + }, + { + "author_name": "John H Kehrl", + "author_inst": "National Institutes of Allergy and Infectious Diseases" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "sports medicine" + "license": "cc0", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2023.03.14.532012", @@ -124948,47 +124647,83 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.09.23287034", - "rel_title": "Real-world effectiveness of sotrovimab for the treatment of SARS-CoV-2 infection during Omicron BA.2 subvariant predominance: a systematic literature review", + "rel_doi": "10.1101/2023.03.08.23286979", + "rel_title": "Prevalence of IgG and IgM to SARS-CoV-2 and other human coronaviruses in The Democratic Republic of Congo, Sierra Leone and Uganda: A Longitudinal Study", "rel_date": "2023-03-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.09.23287034", - "rel_abs": "PurposeEmerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have impacted the in vitro activity of sotrovimab 500 mg, with reduced fold change in EC50 for the Omicron BA.2 sublineage and onward. The correlation between this reduction and clinical efficacy outcomes is unknown. In the absence of clinical trials assessing the efficacy of sotrovimab against emerging variants, real-world evidence becomes a critical source of information. A systematic literature review (SLR) of published observational studies was undertaken to evaluate the effectiveness of sotrovimab on severe clinical outcomes during the Omicron BA.2 subvariant predominance period.\n\nMethodsSearches of indexed electronic databases for peer-reviewed journals, preprint articles, and conference abstracts published between January 1, 2022 and November 3, 2022 were undertaken using a combination of search terms for COVID-19, sotrovimab, and observational study design. Study quality was assessed using the Newcastle Ottawa Scale (NOS).\n\nResultsFrom the 343 unique titles and abstracts identified, five studies were eligible for inclusion in the SLR. Included studies displayed heterogeneity in study design and population. The OpenSAFELY study, which received a high NOS score and had a sufficient sample of patients treated with sotrovimab during BA.2 predominance, demonstrated clinical effectiveness during both BA.1 (adjusted hazard ratio (HR) 0.54, 95% confidence interval (CI) 0.33-0.88; p = 0.014) and BA.2 (adjusted HR 0.44, 95% CI 0.27-0.71; p = 0.001) periods vs molnupiravir. Furthermore, a US-based study that also received a high NOS score reported that sotrovimab was associated with a lower risk of 30-day all-cause hospitalization or mortality compared with no monoclonal antibody treatment during the BA.2 subvariant surge in March (adjusted relative risk (RR) 0.41, 95% CI 0.27-0.62) and April 2022 (adjusted RR 0.54, 95% CI 0.08-3.54). Although only a limited number of studies evaluated sotrovimab during both the BA.1 and BA.2 periods, these demonstrated that clinical outcomes in patients with COVID-19 treated with sotrovimab were consistently low across both periods. One large study directly compared data from the two periods and found no evidence of a difference in the clinical outcomes of sotrovimab-treated patients with sequencing-confirmed BA.1 and BA.2 (HR 1.17, 95% CI 0.74-1.86).\n\nConclusionThe observational data presented in this SLR provide evidence that the effectiveness of sotrovimab (IV 500 mg) is maintained against Omicron BA.2 in both ecological and sequencing-confirmed studies, either through the demonstration of low and comparable rates of severe clinical outcomes between the Omicron BA.1 and BA.2 periods, or by comparison against an active comparator or no treatment within the Omicron BA.2 period.\n\nKey pointsO_ST_ABSWhy carry out this study?C_ST_ABSO_LIEmerging SARS-CoV-2 variants have impacted the in vitro activity of sotrovimab 500 mg, with reduced fold change in EC50 relative to wild-type for the Omicron BA.2 sublineage and onward; the clinical relevance of this difference on outcomes for BA.2 (and other variants) is unknown.\nC_LIO_LIGiven the complexity of generating formal clinical trial data in the context of the constantly evolving SARS-CoV-2 landscape, real-world evidence is a key source of information with which to assess the effectiveness of treatments such as sotrovimab on newly predominant or emerging variants.\nC_LIO_LIWe conducted a systematic literature review to evaluate the effectiveness of sotrovimab for the early treatment of COVID-19 on clinical outcomes during the period predominated by the Omicron BA.2 subvariant.\nC_LI\n\nWhat was learned from the study?O_LISotrovimab treatment was associated with low proportions of severe clinical outcomes (such as all-cause or COVID-19-related hospitalization or mortality) in patients infected during periods of Omicron BA.2 predominance, despite reduction in the in vitro neutralization activity of sotrovimab.\nC_LIO_LIThese data support continued clinical effectiveness of sotrovimab during Omicron BA.2 predominance.\nC_LI", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.08.23286979", + "rel_abs": "ObjectivesWe assessed the prevalence of immunoglobulin G (IgG) and immunoglobulin M (IgM) against four endemic human coronaviruses (HCoVs) and two SARS-CoV-2 antigens, among vaccinated and unvaccinated staff at health care centres in Uganda, Sierra Leone, and the Democratic Republic of Congo (DRC).\n\nMethodsGovernment health facility staff who had patient contact in Goma (DRC), Kambia District (Sierra Leone), and Masaka District (Uganda) were enrolled. Questionnaires and blood samples were collected at three timepoints over four months. Blood samples were analysed with the Luminex MAGPIX(R).\n\nResultsAmong unvaccinated participants, the prevalence of IgG/IgM antibodies against SARS-CoV-2 RBD or N-protein at enrolment was 70% in Goma (138/196), 89% in Kambia (112/126) and 89% in Masaka (190/213). IgG responses against endemic HCoVs at baseline were not associated with SAR-CoV-2 sero-acquisition during follow-up. Among vaccinated participants, those who had evidence of SARS-CoV-2 IgG/IgM at baseline tended to have higher IgG responses to vaccination compared to those SARS-CoV-2 seronegative at baseline, controlling for the time of sample collection since vaccination.\n\nConclusionsThe high levels of natural immunity and hybrid immunity should be incorporated into both vaccination policy and prediction models of the impact of subsequent waves of infection in these settings.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Myriam Drysdale", - "author_inst": "Value Evidence and Outcomes, GSK, Middlesex, UK" + "author_name": "Katherine E. Gallagher", + "author_inst": "LSHTM" }, { - "author_name": "Daniel C. Gibbons", - "author_inst": "Value Evidence and Outcomes, GSK, Middlesex, UK" + "author_name": "Bolarinde J. Lawal", + "author_inst": "LSHTM-COMAHS Research Partnership, Kambia District, Sierra Leone" }, { - "author_name": "Moushmi Singh", - "author_inst": "Value Evidence and Outcomes, GSK, Middlesex, UK" + "author_name": "Jonathan Kitonsa", + "author_inst": "MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda" + }, + { + "author_name": "Daniel Tindanbil", + "author_inst": "LSHTM-COMAHS Research Partnership, Kambia District, Sierra Leone" }, { - "author_name": "Catherine Rolland", - "author_inst": "Evidence Synthesis, Modelling and Communications, PPD Evidera, London, UK" + "author_name": "Kambale Kasonia", + "author_inst": "LSHTM-INRB Research Partnership, Goma, Democratic Republic of the Congo" }, { - "author_name": "Louis Lavoie", - "author_inst": "Evidence Synthesis, Modelling and Communications, PPD Evidera, Montreal, Canada" + "author_name": "Abdoulie Drammeh", + "author_inst": "LSHTM-COMAHS Research Partnership, Kambia District, Sierra Leone" }, { - "author_name": "Andrew Skingsley", - "author_inst": "Clinical Research and Development, GSK, Middlesex, UK" + "author_name": "Brett Lowe", + "author_inst": "LSHTM" }, { - "author_name": "Emily J. Lloyd", - "author_inst": "Clinical Research and Development, GSK, Middlesex, UK" + "author_name": "Daniel Mukadi-Bamuleka", + "author_inst": "Laboratoire Rodolphe Merieux-Institute National Research biomedical (INRB), Goma, Democratic Republic of the Congo" + }, + { + "author_name": "Catriona Patterson", + "author_inst": "LSHTM" + }, + { + "author_name": "Brian Greenwood", + "author_inst": "LSHTM" + }, + { + "author_name": "Mohamed Samai", + "author_inst": "University of Sierra Leone College of Medicine and Allied Health Sciences (COMAHS), Freetown, Sierra Leone" + }, + { + "author_name": "Bailah Leigh", + "author_inst": "University of Sierra Leone College of Medicine and Allied Health Sciences (COMAHS), Freetown, Sierra Leone" + }, + { + "author_name": "Kevin A. Tetteh", + "author_inst": "LSHTM" + }, + { + "author_name": "Eugene Ruzagira", + "author_inst": "MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Uganda" + }, + { + "author_name": "Deborah Watson-Jones", + "author_inst": "LSHTM" + }, + { + "author_name": "Hugo Kavunga-Membo", + "author_inst": "Laboratoire Rodolphe Merieux-Institute National Research biomedical (INRB), Goma, Democratic Republic of the Congo" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.03.09.23285319", @@ -126722,39 +126457,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.06.531252", - "rel_title": "Unraveling the Interactions between Human DPP4 Receptor, SARS-CoV-2 Variants, and MERS-CoV, converged for Pulmonary Disorders Integrating through Immunoinformatics and Molecular Dynamics", + "rel_doi": "10.1101/2023.03.06.531431", + "rel_title": "Genome-scale CRISPR-Cas9 screen identifies novel host factors as potential therapeutic targets for SARS-CoV-2 infection.", "rel_date": "2023-03-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.06.531252", - "rel_abs": "Human coronaviruses like MERS CoV are known to utilize dipeptidyl peptidase 4 (DPP4), apart from angiotensin-converting enzyme 2(ACE2) as potential co-receptor for viral cell entry. DPP4, ubiquitous membrane-bound aminopeptidase is closely associated with elevation of disease severity in comorbidities. In SARS-CoV-2, there is inadequate evidence for combination of spike protein variants with DPP4, and underlying adversity in COVID19. To elucidate this mechanistic basis, we have investigated interaction of spike protein variants with DPP4 through molecular docking and simulation studies. The possible binding interactions between receptor binding domain (RBD) of different spike variants of SARS-CoV-2 and DPP4 have been compared with interactions observed in experimentally determined structure of complex of MERS-CoV with DPP4. Comparative binding affinity confers that Delta-CoV-2:DPP4 shows close proximity with MERS-CoV:DPP4, as depicted from accessible surface area, radius of gyration, number of hydrogen bonding and energy of interactions. Mutation in delta variant, L452R and T478K, directly participate in DPP4 interaction enhancing DPP4 binding. E484K in alpha and gamma variant of spike protein is also found to interact with DPP4. Hence, DPP4 interaction with spike protein gets more suitable due to mutation especially due to L452R, T478K and E484K. Furthermore, perturbation in the nearby residues Y495, Q474 and Y489 is evident due to L452R, T478K and E484K respectively. Virulent strains of spike protein are more susceptible to DPP4 interaction and are prone to be victimized in patients due to comorbidities. Our results will aid the rational optimization of DPP4 as a potential therapeutic target to manage COVID-19 disease severity.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.03.06.531431", + "rel_abs": "Although many host factors important for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have been reported, the mechanisms by which the virus interacts with host cells remain elusive. Here, we identified tripartite motif containing (TRIM) 28, TRIM33, euchromatic histone lysine methyltransferase (EHMT) 1, and EHMT2 as novel proviral factors involved in SARS-CoV-2 infection by CRISPR-Cas9 screening. We demonstrated that TRIM28 plays a role(s) in viral particle formation and that TRIM33, EHMT1, and EHMT2 are involved in viral transcription and replication using cells with suppressed gene expression. UNC0642, a compound that specifically inhibits the methyltransferase activity of EHMT1/2, strikingly suppressed SARS-CoV-2 growth in cultured cells and reduced disease severity in a hamster infection model. This study suggests that EHMT1/2 may be a novel therapeutic target for SARS-CoV-2 infection.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Aayatti Mallick Gupta", - "author_inst": "S N Bose National Centre for Basic Sciences" + "author_name": "Madoka Sakai", + "author_inst": "Kyoto University" }, { - "author_name": "Pongali B Raghavendra", - "author_inst": "National Institute of Biomedical Genomics" + "author_name": "Yoshie Masuda", + "author_inst": "Kyoto University" }, { - "author_name": "Arpan Narayan Roy", - "author_inst": "National Institute of Biomedical Genomics" + "author_name": "Yusuke Tarumoto", + "author_inst": "Kyoto University" }, { - "author_name": "Deboshmita Banerjee", - "author_inst": "National Institute of Biomedical Genomics" + "author_name": "Naoyuki Aihara", + "author_inst": "Azabu University" }, { - "author_name": "Jaydeb Chakrabarti", - "author_inst": "S N Bose National Centre for Basic Sciences" + "author_name": "Yugo Tsunoda", + "author_inst": "Kyoto University" + }, + { + "author_name": "Michiko Iwata", + "author_inst": "Kyoto University" + }, + { + "author_name": "Yumiko Kamiya", + "author_inst": "Azabu University" + }, + { + "author_name": "Ryo Komorizono", + "author_inst": "Kyoto University" + }, + { + "author_name": "Takeshi Noda", + "author_inst": "Kyoto University" + }, + { + "author_name": "Kosuke Yusa", + "author_inst": "Kyoto University" + }, + { + "author_name": "Keizo Tomonaga", + "author_inst": "Kyoto University" + }, + { + "author_name": "Akiko Makino", + "author_inst": "Kyoto University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "bioinformatics" + "category": "microbiology" }, { "rel_doi": "10.1101/2023.03.07.531527", @@ -128512,63 +128275,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.03.02.23286686", - "rel_title": "Impact of COVID-19 pandemic on the etiology and characteristics of community-acquired pneumonia among children requiring bronchoalveolar lavage in northern China", - "rel_date": "2023-03-05", + "rel_doi": "10.1101/2023.02.28.23286595", + "rel_title": "SARS-CoV-2 post-vaccine surveillance studies in Australian children and adults with cancer: SerOzNET Quality of Life, Toxicity and Vaccine Beliefs Substudy Statistical Analysis Plan", + "rel_date": "2023-03-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.03.02.23286686", - "rel_abs": "BackgroundTo investigate the etiology and clinical characteristics of community-acquired pneumonia (CAP) among children requiring bronchoalveolar lavage (BAL) and analyze the impact of the coronavirus disease 2019 (COVID-19) pandemic on the pathogen spectrum and clinical manifestations.\n\nMethodsChildren <14 years old hospitalized with CAP requiring BLA were enrolled between February 2019 to January 2020 and August 2021 to July 2022. Multiplex reverse transcription polymerase chain reaction (mRT-PCR) was used for pathogen detection. The demographic and clinical characteristics were compared between different pathogen-type infection groups, and before and during the COVID-19 pandemic.\n\nResultsPathogen was detected in 91.66% (1363/1487) children. Mycoplasma pneumoniae, adenovirus and human rhinovirus were the most frequently detected pathogens. The frequency of detection of virus infections and co-infections was decreased during the pandemic, but the detection of atypical bacterial infections was increased. The clinical manifestations and the results of CT scans and fiberoptic bronchoscopy showed a significant difference between different types of pathogen infection, and lung inflammation was reduced during the COVID-19 pandemic compared with before the pandemic.\n\nConclusionsM. pneumoniae infection might be the greatest pediatric disease burden leading to CAP in northern China. Wearing masks and social distancing in public places during the COVID-19 pandemic effectively reduced the transmission of respiratory viruses, but it did not reduce the infection rate of M. pneumoniae. In addition, these interventions significantly reduced lung inflammation in children compared with before the pandemic.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.28.23286595", + "rel_abs": "COVID-19 disease is associated with higher morbidity and mortality in cancer patients. SerOzNET is a prospective cohort study of adults and children with cancer undergoing routine SARS-CoV-2 vaccination in Australia. Peripheral blood was collected and processed at multiple points (one pre-vaccination and five or more post-vaccination) to address the primary aim of the study to assess the serological and immunological responses to vaccination.\n\nA secondary aim of the study was to \"document patient response to vaccination using qualitative measures, including patient-reported outcomes, vaccine hesitancy survey and post-hoc toxicity recording\" (body, et al.,2022). This statistical analysis plan describes the analysis of the data collected to address this aim. We will refer to this as the SerOzNET QoL Substudy.\n\nWe have no conflicts of interest to disclose.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ruihan Liu", - "author_inst": "Affiliated Hospital of Jining Medical University" - }, - { - "author_name": "Yuyan Zhang", - "author_inst": "Affiliated Hospital of Jining Medical University" + "author_name": "Mark W Donoghue", + "author_inst": "Stats Central @ The University of New South Wales" }, { - "author_name": "Zhouhua Lu", - "author_inst": "Affiliated Hospital of Jining Medical University" - }, - { - "author_name": "Changqing Shen", - "author_inst": "Affiliated Hospital of Jining Medical University" - }, - { - "author_name": "Jin Wang", - "author_inst": "Affiliated Hospital of Jining Medical University" - }, - { - "author_name": "Qing Zhao", - "author_inst": "Affiliated Hospital of Jining Medical University" - }, - { - "author_name": "Tongshu Hou", - "author_inst": "Binzhou Medical University - Yantai Campus" - }, - { - "author_name": "Fenghai Niu", - "author_inst": "Affiliated Hospital of Jining Medical University" + "author_name": "Amy Louise Body", + "author_inst": "Monash University, Victoria, Australia" }, { - "author_name": "Qingxia Kong", - "author_inst": "Affiliated Hospital of Jining Medical University" + "author_name": "Claire Wakefield", + "author_inst": "Kids Cancer Centre @ Sydney Children's Hospital, NSW, Australia" }, { - "author_name": "Jun Ning", - "author_inst": "Affiliated Hospital of Jining Medical University" + "author_name": "Elizabeth S Ahern", + "author_inst": "Monash Health/Monash University" }, { - "author_name": "Lei Yang", - "author_inst": "Affiliated Hospital of Jining Medical University" + "author_name": "Eva Segelov", + "author_inst": "University of Bern, Switzerland" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "oncology" }, { "rel_doi": "10.1101/2023.03.01.23286627", @@ -130278,47 +130017,67 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2023.02.26.23286261", - "rel_title": "SARS-CoV-2 post-vaccine surveillance studies in Australian children and adults with cancer: SerOzNET Statistical Analysis Plan", + "rel_doi": "10.1101/2023.02.28.23286466", + "rel_title": "COVID-19 or seasonal influenza? How to distinguish in people younger than 65 years old: A retrospective observational cohort study comparing the 2009 pandemic influenza A H1N1 with 2022 SARS-CoV-2 Omicron BA.2 outbreaks in China.", "rel_date": "2023-03-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.26.23286261", - "rel_abs": "COVID-19 disease is associated with higher morbidity and mortality in cancer patients. Our study aimed to characterize the optimal strategy to improve vaccine induced protection against COVID-19 in children and adolescents with cancer. Results from The SerOzNET study will contribute comprehensive data on serology, cellular immune correlates from functional T-cell assays, quality of life data, and associated toxicity in relation to COVID-19 vaccination in children and adults with cancer.\n\nIn this plan, we describe the statistics that will be used to report results of the SerOzNET study. SerOzNET examines COVID-19 vaccine response in children and adolescents with cancer.\n\nWe have no conflicts of interest to disclose.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.28.23286466", + "rel_abs": "ObjectiveThis study attempted to explore the difference of clinical characteristics in H1N1 influenza infection and SARS-CoV-2 Omicron infection in people younger than 65 years old, in order to better identify the two diseases.\n\nMethodsA total of 127 H1N1 influenza patients diagnosed from May 2009 to July 2009 and 3265 patients diagnosed and identified as SARS-CoV-2 Omicron BA.2 variant from March 2022 to May 2022 were admitted in this study. Through the 1 : 2 match based on age (The difference is less than 2 years), gender and underlying diseases, 115 patients with H1N1 infection and 230 patients with SARS-CoV-2 Omicron BA.2 infection(referred to as H1N1 group and Omicron group) were included in the statistics. The clinical manifestations of H1N1 group were compared with those of Omicron group. Logistic regression was performed to analyze the possible independent risk factors of H1N1 group and Omicron group. And multiple linear regression was used to analyze the factors for time for nucleic acid negativization (NAN).\n\nResultsThe median age of the two groups was 21 [11,26] years. Compared with the H1N1 group, the Omicron group had lower white blood cell count and CRP levels, less fever, nasal congestion, sore throat, cough, sputum and headache, while more olfactory loss, muscle soreness and LDH abnormalities. The Omicron group used less antibiotics and antiviral drugs, and the NAN time was longer (17 [14,20] VS 4 [3,5], P < 0.001). After logistic regression, it was found that fever, cough, headache, and increased white blood cell count were more correlated with the H1N1 group, while muscle soreness and LDH abnormalities were more correlated with the Omicron group. After analyzing the factors of NAN time, it was found that fever (B 1.529, 95 % CI [0.149,2.909], P = 0.030) significantly predicted longer NAN time in Omicron patients.\n\nConclusionThis study comprehensively evaluated the similarities and differences in clinical characteristics between SARS-CoV-2 Omicron infection and 2009 H1N1 influenza infection, which is of great significance for a better understanding for these diseases.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Amy Louise Body", - "author_inst": "Monash University, Victoria, Australia" + "author_name": "Wen Zhong", + "author_inst": "Department of Respiratory and Critical Care Medicine, Fujian Shengli Medical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China." }, { - "author_name": "Catherine Martin", - "author_inst": "Monash University, Victoria, Australia" + "author_name": "Yisong Wu", + "author_inst": "Department of Respiratory and Critical Care Medicine, Fujian Shengli Medical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China." }, { - "author_name": "Lucy Busija", - "author_inst": "Monash University, Victoria, Australia" + "author_name": "Wenxiang Yue", + "author_inst": "Department of Respiratory and Critical Care Medicine, Fujian Shengli Medical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China." }, { - "author_name": "Luxi Lal", - "author_inst": "Monash Health & Monash University, Victoria, Australia" + "author_name": "Jiabin Fang", + "author_inst": "Department of Respiratory and Critical Care Medicine, Fujian Shengli Medical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China." }, { - "author_name": "Elizabeth S Ahern", - "author_inst": "Monash Health/Monash University" + "author_name": "Baosong Xie", + "author_inst": "Department of Respiratory and Critical Care Medicine, Fujian Shengli Medical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China." }, { - "author_name": "Raina C MacIntyre", - "author_inst": "The Kirby Institute @ The University of New South Wales, Australia" + "author_name": "Nengluan Xu", + "author_inst": "Department of Respiratory and Critical Care Medicine, Fujian Shengli Medical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China." }, { - "author_name": "Eva Segelov", - "author_inst": "University of Bern, Switzerland and Monash University, Victoria, Australia" + "author_name": "Ming Lin", + "author_inst": "Department of Respiratory and Critical Care Medicine, Fujian Shengli Medical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China." + }, + { + "author_name": "Xiongpeng Zhu", + "author_inst": "Department of Hematology, Quanzhou First Hospital, Quanzhou, China." + }, + { + "author_name": "Zhijun Su", + "author_inst": "Department of Infectious Diseases, Quanzhou First Hospital, Fuzhou, China." + }, + { + "author_name": "Yusheng Chen", + "author_inst": "Department of Respiratory and Critical Care Medicine, Fujian Shengli Medical College, Fujian Medical University, Fujian Provincial Hospital, Fuzhou, China." + }, + { + "author_name": "Hong Li", + "author_inst": "School of Nursing, Fujian Medical University, Fujian Shengli Medical College, Fujian Medical University, Fuzhou, China." + }, + { + "author_name": "Hongru Li", + "author_inst": "Department of Respiratory and Critical Care Medicine, Fujian Shengli Medical College, Fujian Medical University, Fujian Provincial Key Laboratory of Medical Big" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "oncology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.02.27.530346", @@ -132036,105 +131795,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.02.16.23286009", - "rel_title": "Vaccine-induced correlate of protection against fatal COVID-19 in the old and frail during waves of neutralization resistant variants of concern.", + "rel_doi": "10.1101/2023.02.15.23285958", + "rel_title": "BRIEF COMMUNICATION High level of Anti SARS-Co-V2 RBD Antibody one year post booster vaccine hospital workers in Indonesia; Was second booster needed?", "rel_date": "2023-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.16.23286009", - "rel_abs": "BackgroundTo inform future preventive measures including repeated vaccinations, we have searched for a clinically useful immune correlate of protection against fatal Covid-19 among nursing homes residents.\n\nMethodsWe performed repeated capillary blood sampling with analysis of S-binding IgG in an open cohort study with inclusion of nursing home residents in Sweden. We analyzed immunological and registry data collected from September 2021 with end of follow-up 31 August 2022. The study period included implementation of the 3rd and 4th mRNA monovalent vaccine doses and Omicron virus waves.\n\nFindingsA total of 3012 nursing home residents with median age 86 were enrolled. The 3rd mRNA dose elicited a 99-fold relative increase of S-binding IgG among 2606 blood-sampled individuals and corresponding increase of neutralizing antibodies. The 4th mRNA vaccine dose boosted the levels 3.8-fold. Half-life of S-binding IgG was 72 days. A total 528 residents acquired their first SARS-CoV-2 infection after the 3rd or the 4th vaccine dose and the 30-day mortality was 9.1%. We found no indication that levels of vaccine-induced antibodies protected against infection with Omicron VOCs. In contrast, the risk of death was inversely correlated to levels of S-directed IgG below the 20th percentile. The risk plateaued at population average above lower 35th percentile of S-binding IgG.\n\nInterpretationIn the absence of neutralizing antibodies that protection from infection, quantification of S-binding IgG post vaccination may be useful to identify the most vulnerable for fatal Covid-19 among the oldest and frailest. This information is of importance for future strategies to protect vulnerable populations against neutralization resistant variants of concern.\n\nFundingSwedish Research Council, SciLife, Knut and Alice Wallenberg Foundation and Vinnova.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.15.23285958", + "rel_abs": "Healthcare workers in Indonesia acquired a complete 2 doses of Sinovac in early 2021 and first booster dose of Moderna in July 2021. In August 2022, the ministry of health prioritized healthcare workers to acquire the second booster dose of Moderna as antibody levels from the year before may have waned. We conducted a sequential serosurvey aimed to determine the level of SARS CoV2 S-RBD antibody reached by the first vaccine, after the first booster, and before the second booster to understand the dynamics of the antibody level. COVID-19 antibody test was conducted using the FastBioRBDtm test with a maximum limit detection level of 4000 BAU/mL. First serosurvey which was conducted in June 2021, one to six months after Sinovac vaccination, showed a median antibody level of 41.4 BAU/mL (IQR 10 - 629.4 BAU/mL). The second serosurvey was conducted one month (August 2021) after the first Moderna booster vaccine, and showed a median level of 4000 BAU/mL (IQR 3081 - 4000 BAU/mL). While the last serosurvey conducted a year (August 2022) after the booster, showed 4000 BAU/mL (IQR 4000 - 4000 BAU/mL). Only 39 (11.9%) healthcare workers have antibody levels below the maximum level of 4000 BAU./mL We did not see the waning of antibody levels among healthcare workers approximately 1 year after the booster. It increases perhaps due to the natural infection caused by the omicron variant outbreak in early 2022. Based on this fact, we suggest considering if the second booster dose is really necessary. The limited vaccine supply can better be given to the person or other high-risk groups of patients who has a low level of antibody based on serological testing.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Linnea Vikstrom", - "author_inst": "Umea University" - }, - { - "author_name": "Peter Fjallstrom", - "author_inst": "Umea University" - }, - { - "author_name": "Young-Dae Gwon", - "author_inst": "Umea University" - }, - { - "author_name": "Daniel J Sheward", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Julia Wigren-Bystrom", - "author_inst": "Umea University" + "author_name": "Amila Hanifan Muslimah", + "author_inst": "Rumah Sakit Dr Hasan Sadikin" }, { - "author_name": "Magnus Evander", - "author_inst": "Umea University" - }, - { - "author_name": "Oscar Bladh", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Micael Widerstroem", - "author_inst": "Umea University" - }, - { - "author_name": "Christian Molnar", - "author_inst": "Familjelakarna" - }, - { - "author_name": "Gunlog Rasmussen", - "author_inst": "Region Orebro lan" - }, - { - "author_name": "Louise Bennet", - "author_inst": "Lunds University" - }, - { - "author_name": "Mikael Aberg", - "author_inst": "Uppsala University" - }, - { - "author_name": "Jonas Bjork", - "author_inst": "Lund University" - }, - { - "author_name": "Staffan Tevell", - "author_inst": "Region Varmland" - }, - { - "author_name": "Charlotte Thalin", - "author_inst": "Karolinska Institutet" + "author_name": "Marita Restie Tiara", + "author_inst": "Universitas Padjadjaran" }, { - "author_name": "Kim Blom", - "author_inst": "Swedish Public Health Agency" + "author_name": "Hofiya Djauhari", + "author_inst": "Universitas Padjadjaran" }, { - "author_name": "Jonas Klingstrom", - "author_inst": "Linkopings University" + "author_name": "Hafizh Dewantara", + "author_inst": "Rumah Sakit Dr Hasan Sadikin" }, { - "author_name": "Benjamin Murrell", - "author_inst": "Karolinska Institutet" + "author_name": "Evan Susandi", + "author_inst": "Rumah Sakit Dr Hasan Sadikin" }, { - "author_name": "Clas Ahlm", - "author_inst": "Umea University" + "author_name": "Agnes Rengga Indrati", + "author_inst": "Rumah Sakit Dr Hasan Sadikin" }, { - "author_name": "Johan Normark", - "author_inst": "Umea University" + "author_name": "Arto Yuwono Soeroto", + "author_inst": "Rumah Sakit Dr Hasan Sadikin" }, { - "author_name": "Anders F Johansson", - "author_inst": "Umea University" + "author_name": "Bachti Alisjahbana", + "author_inst": "Rumah Sakit Dr Hasan Sadikin" }, { - "author_name": "Mattias Forsell", - "author_inst": "Umea University" + "author_name": "Rudi Wisaksana", + "author_inst": "Rumah Sakit Dr Hasan Sadikin" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -133898,71 +133605,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.02.14.23285860", - "rel_title": "REAL-WORLD EFFECTIVENESS OF NIRMATRELVIR/RITONAVIR ON COVID-19-ASSOCIATED HOSPITALIZATION PREVENTION: A POPULATION-BASED COHORT STUDY IN THE PROVINCE OF QUEBEC, CANADA", + "rel_doi": "10.1101/2023.02.19.23285730", + "rel_title": "Dynamics of Influenza A and SARS-CoV-2 coinfections during the COVID-19 pandemic in India", "rel_date": "2023-02-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.14.23285860", - "rel_abs": "IntroductionThe nirmatrelvir/ritonavir (PAXLOVID) is an antiviral blocking the replication of SARS-CoV-2. Early treatment with this antiviral has showed to reduce COVID-19 hospitalization and death in unvaccinated outpatients with mild-to-moderate COVID-19 and high risk of progression to severe disease with variants before Omicron. However, the current epidemiological context and the level of immunity in the population (vaccination and/or natural infection) have evolved considerably since the disclosure of these results. Thus, real-world evidence studies in vaccinated outpatients with lineage and sublineage of the variant are needed.\n\nObjectiveTo assess whether nirmatrelvir/ritonavir treatment reduces the risk of COVID-19-associated hospitalization among Quebec outpatients with mild-to-moderate COVID-19 at high risk of progression to severe disease in a real-world context, regardless of vaccination status and circulating variants, in the province of Quebec.\n\nMethodsThis was a retrospective cohort study of SARS-CoV-2-infected outpatients who received nirmatrelvir/ritonavir between March 15 and August 15, 2022, using data from the Quebec provincial clinico-administrative databases. Outpatients treated with nirmatrelvir/ritonavir were compared to unexposed ones. The treatment group was matched with controls using propensity-score matching in a ratio of 1:1. The outcome was COVID-19-associated hospitalization occurring within 30 days following the index date. Poisson regression with robust error variance was used to estimate the relative risk of hospitalization among the treatment group compared to the control group.\n\nResultsA total of 16,601 and 242,341 outpatients were eligible to be included in the treatment (nirmatrelvir/ritonavir) and control groups respectively. Among treated outpatients, 8,402 were matched to controls. Regardless of vaccination status, nirmatrelvir/ritonavir-treated outpatient status was associated with a 69% reduced relative risk of COVID-19-associated hospitalization (RR: 0.31 [95% CI: 0.28; 0.36]). The effect was more pronounced in outpatients without a complete primary vaccination course (RR: 0.04 [95% CI: 0.03; 0.06]), while treatment with nirmatrelvir/ritonavir was not associated with benefit when outpatients with a complete primary vaccination course were considered (RR: 0.93 [95% CI: 0.78; 1.08]) Subgroups analysis among outpatients with a primary vaccination course showed that nirmatrelvir/ritonavir treatment was associated with a significant decrease in relative risk of hospitalization in severely immunocompromised outpatients (RR: 0.66 [95% CI: 0.50; 0.89]) and in outpatients aged 70 years and older (RR: 0.50 [95% CI: 0.34; 0.74]) when the last dose of the vaccine was received more than six months before.\n\nConclusionsAmong SARS-CoV-2-infected outpatients at high risk for severe COVID-19 during Omicron BA.2 and BA.4/5 surges, treatment with nirmatrelvir/ritonavir was associated with a significant reduced relative risk of COVID-19-associated hospitalization. This effect was observed in outpatients with incomplete primary vaccination course and in outpatients who were severely immunocompromised. Except for severely immunocompromised outpatients, no evidence of benefit was found in any category of outpatient with a complete primary vaccination course whose last dose of COVID-19 vaccine was received within six months.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.19.23285730", + "rel_abs": "The SARS-CoV-2 exhibits similar aetiology, mode of transmission and clinical presentation as the H1N1pdm09 (a subtype of Influenza A) and Influenza A (other subtypes), and can exist as a coinfection in the same patient. It is essential to understand the coinfection dynamics of these viruses for effective management of the disease. This study examined 959 SARS-CoV-2 positive samples collected from the six states and three union territories in India from May to December 2022. The clinical data was accessed from the Integrated Health Information Platform (IHIP) and the Indian council of medical research (ICMR) COVID-19 data portal. The samples were tested for SARS-CoV-2, H1N1pdm09 and Influenza A using Reverse Transcriptase Real-Time Polymerase Chain Reaction q(RT-PCR). All 959 samples were subjected to SARS-CoV-2 whole genome sequencing (WGS) using Oxford Nanopore Next Generation Sequencing (NGS). From the 959 SARS-CoV-2 positive samples, 17.5% were co-infected with H1N1pdm09, 8.2% were co-infected with Influenza A, and 74.2% were only positive for SARS-CoV-2. The comparative analysis of viral load among the coinfected cases revealed that Influenza A and H1N1pdm09 had higher viral loads than SARS-CoV-2 in the studied samples. Out of 959 samples subjected to WGS, 815 and 144 were considered quality control (QC) passed, and QC failed, respectively, for SARS-CoV-2 variant calling. SARS-CoV-2 WGS identified 46 different variants belonging to the Omicron lineage. The SARS-CoV-2 and Influenza A coinfection group; and the SARS-CoV-2 and H1N1pdm09 coinfection group showed a higher proportion of symptomatic cases. This work demonstrates the need for coinfection analysis for the H1N1pdm09 virus, Influenza A virus and SARS-CoV-2 while studying the etiological agent in individuals with ILI/SARI symptoms. It is recommended that, in addition to determining the aetiology of ILI/SARI, an examination for H1N1pdm09 and Influenza A be conducted concurrently utilising molecular tools such as WGS and RT-PCR to understand the variant dynamics and the viral load for taking an informed decision during the patient management and treatment discourse.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Jean Luc Kabor\u00e9", - "author_inst": "Institut National d\u00b4Excellence en Sant\u00e9 et Services Sociaux (INESSS) du Qu\u00e9bec, Qu\u00e9bec, Canada" - }, - { - "author_name": "Beno\u00eet Laffont", - "author_inst": "Institut National d\u00b4Excellence en Sant\u00e9 et Services Sociaux (INESSS) du Qu\u00e9bec, Qu\u00e9bec, Canada" - }, - { - "author_name": "Mamadou Diop", - "author_inst": "Institut National d\u00b4Excellence en Sant\u00e9 et Services Sociaux (INESSS) du Qu\u00e9bec, Qu\u00e9bec, Canada" - }, - { - "author_name": "Melanie R. Tardif", - "author_inst": "Institut National d\u00b4Excellence en Sant\u00e9 et Services Sociaux (INESSS) du Qu\u00e9bec, Qu\u00e9bec, Canada" - }, - { - "author_name": "Alexis F. Turgeon", - "author_inst": "Department of Anesthesiology and Critical Care Medicine, Division of Critical Care Medicine, Universit\u00e9 Laval, Qu\u00e9bec City, Qu\u00e9bec, Canada" - }, - { - "author_name": "Jeannot Dumaresq", - "author_inst": "Department of microbiology-infectiology and immunology, Faculty of Medicine, Universit\u00e9 Laval, Qu\u00e9bec City, Qu\u00e9bec, Canada" - }, - { - "author_name": "Me-Linh Luong", - "author_inst": "Department of Medicine, Division of Infectious Diseases, CHUM, Montr\u00e9al, Qu\u00e9bec, Canada" - }, - { - "author_name": "Michel Cauchon", - "author_inst": "Department of Family Practice and Emergency, Universit\u00e9 Laval, Qu\u00e9bec City, Qu\u00e9bec, Canada" + "author_name": "Sandhra Ravikumar", + "author_inst": "Council of Scientific and Industrial Research-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India" }, { - "author_name": "Hugo Chapdelaine", - "author_inst": "Department of medicine, Research Centre of Centre Hospitalier de l\u00b4Universit\u00e9 de Montr\u00e9al (CRCHUM), Montr\u00e9al, Qu\u00e9bec, Canada" + "author_name": "Ekant Tamboli", + "author_inst": "Council of Scientific and Industrial Research-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India" }, { - "author_name": "David Claveau", - "author_inst": "Departments of Emergency Medicine and Critical Care Medicine, Centre hospitalier affili\u00e9 universitaire r\u00e9gional, Trois-Rivi\u00e8res, Qu\u00e9bec, Canada" + "author_name": "Shefali Rahangdale", + "author_inst": "Council of Scientific and Industrial Research-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India" }, { - "author_name": "Marc Brosseau", - "author_inst": "Department of Medicine, Faculty of Medicine, Universit\u00e9 de Montr\u00e9al, Montr\u00e9al, Qu\u00e9bec, Canada" + "author_name": "Lekha Salsekar", + "author_inst": "Council of Scientific and Industrial Research-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India" }, { - "author_name": "Elie Haddad", - "author_inst": "Department of Pediatrics, Universit\u00e9 de Montr\u00e9al, CHU Sainte-Justine, Montr\u00e9al, Qu\u00e9bec, Canada" + "author_name": "Siddharth Singh Tomar", + "author_inst": "Council of Scientific and Industrial Research-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India" }, { - "author_name": "Mike Benigeri", - "author_inst": "Institut National d\u00b4Excellence en Sant\u00e9 et Services Sociaux (INESSS) du Qu\u00e9bec, Qu\u00e9bec, Canada" + "author_name": "Krishna Khairnar", + "author_inst": "Council of Scientific and Industrial Research-National Environmental Engineering Research Institute (CSIR-NEERI), Nagpur, India" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.02.21.527754", @@ -135476,27 +135155,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.02.16.23286061", - "rel_title": "How well do we do social distancing?", + "rel_doi": "10.1101/2023.02.16.23286017", + "rel_title": "Long-term outdoor air pollution and COVID-19 mortality in London: an individual-level analysis", "rel_date": "2023-02-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.16.23286061", - "rel_abs": "During the pandemic of coronavirus disease 2019 (COVID-19), many jurisdictions around the world introduced a social distance rule under which people are instructed to keep a certain distance from others. Generally, this rule is implemented simply by telling people how many metres or feet of separation should be kept, without giving them precise instructions as to how the specified distance can be measured. Consequently, the rule is effective only to the extent that people are able to gauge this distance through their space perception. To examine the effectiveness of the rule from this point of view, the present study empirically investigated how much distance people would leave from another person when they relied on their perception of this distance. Participants (N = 153) were asked to stand exactly 1.5-m away from a researcher, and resultant interpersonal distances showed that while their mean was close to the correct 1.5-m distance, they exhibited large individual differences. These results suggest that a number of people would not stay sufficiently away from others even when they intend to do proper social distancing. Given this outcome, it is suggested that official health advice include measures that compensate for this tendency.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.16.23286017", + "rel_abs": "BackgroundThe risk of COVID-19 severity and mortality differs markedly by age, socio-demographic characteristics and pre-existing health status. Various studies have suggested that higher air pollution exposures also increase the likelihood of dying from COVID-19.\n\nObjectives: To assess the association between long-term outdoor air pollution (NO2, NOx, PM10 and PM2.5) concentrations and the risk of death involving COVID-19, using a large individual-level dataset.\n\nMethodsWe used comprehensive individual-level data from the Office for National Statistics Public Health Data Asset for September 2020 to January 2022 and London Air Quality Network modelled air pollution concentrations available for 2016. Using Cox proportional hazard regression models, we adjusted for potential confounders including age, sex, vaccination status, dominant virus variants, geographical factors (such as population density), ethnicity, area and household-level deprivation, and health comorbidities.\n\nResultsThere were 737,356 confirmed COVID-19 cases including 9,315 COVID-related deaths. When only adjusting for age, sex, and vaccination status, there was an increased risk of dying from COVID-19 with increased exposure to all air pollutants studied (NO2: HR 1.07 [95% confidence interval: 1.04-1.12] per 10 g/m3; NOx: 1.05[1.02-1.09] per 20 g/m3; PM10: 1.32[1.15-1.51] per 10 g/m3; PM2.5: 1.29[1.12-1.49] per 5 g/m3). However, after adjustment including ethnicity and socio-economic factors the HRs were close to unity (NO2: 0.98[0.90-1.06]; NOx: 0.99[0.94-1.04]; PM10: 0.95[0.74-1.22]; PM2.5: 0.90[0.67-1.20]). Additional adjustment for dominant variant or pre-existing health comorbidities did not alter the results.\n\nConclusionsObserved associations between long-term outdoor air pollution exposure and COVID-19 mortality in London are strongly confounded by geography, ethnicity and deprivation.\n\nSummaryUsing a large individual-level dataset, we found that a positive association between long-term outdoor air pollution and COVID-19 mortality in London did not persist after adjusting for confounders including population density, ethnicity and deprivation.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Naohide Yamamoto", - "author_inst": "Queensland University of Technology" + "author_name": "Loes Charlton", + "author_inst": "Office for National Statistics" }, { - "author_name": "Mia Nightingale", - "author_inst": "Queensland University of Technology" + "author_name": "Chris Gale", + "author_inst": "Office for National Statistics" + }, + { + "author_name": "Jasper Morgan", + "author_inst": "Office for National Statistics" + }, + { + "author_name": "Myer Glickman", + "author_inst": "Office for National Statistics" + }, + { + "author_name": "Sean Beevers", + "author_inst": "Imperial College London" + }, + { + "author_name": "Anna L Hansell", + "author_inst": "University of Leicester" + }, + { + "author_name": "Vah\u00e9 Nafilyan", + "author_inst": "Office for National Statistics" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2023.02.16.23286046", @@ -137526,99 +137225,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.02.13.528235", - "rel_title": "P-Selectin promotes SARS-CoV-2 interactions with platelets and the endothelium", + "rel_doi": "10.1101/2023.02.14.528496", + "rel_title": "Transcription regulation of SARS-CoV-2 receptor ACE2 by Sp1: a potential therapeutic target", "rel_date": "2023-02-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.13.528235", - "rel_abs": "COVID-19 causes a clinical spectrum of acute and chronic illness and host / virus interactions are not completely understood1,2. To identify host factors that can influence SARS-CoV-2 infection, we screened the human genome for genes that, when upregulated, alter the outcome of authentic SARS-CoV-2 infection. From this, we identify 34 new genes that can alter the course of infection, including the innate immune receptor P-selectin, which we show is a novel SARS-CoV-2 spike receptor. At the cellular level expression of P-selectin does not confer tropism for SARS-CoV-2, instead it acts to suppress infection. More broadly, P-selectin can also promote binding to SARS-CoV-2 variants, SARS-CoV-1 and MERS, acting as a general spike receptor for highly pathogenic coronaviruses. P-selectin is expressed on platelets and endothelium3, and we confirm SARS-CoV-2 spike interactions with these cells are P-selectin-dependent and can occur under shear flow conditions. In vivo, authentic SARS-CoV-2 uses P-selectin to home to airway capillary beds where the virus interacts with the endothelium and platelets, and blocking this interaction can clear vascular-associated SARS-CoV-2 from the lung. Together we show for the first time that coronaviruses can use the leukocyte recruitment system to control tissue localization, and this fundamental insight may help us understand and control highly pathogenic coronavirus disease progression.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.14.528496", + "rel_abs": "Angiotensin-converting enzyme 2 (ACE2) is a major cell entry receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Induction of ACE2 expression may represent an effective tactic employed by SARS-CoV-2 to facilitate its own propagation. However, the regulatory mechanisms of ACE2 expression after viral infection remain largely unknown. By employing an array of 45 different luciferase reporters, we identify that the transcription factor Sp1 positively and HNF4 negatively regulate the expression of ACE2 at the transcriptional levels in HPAEpiC cells, a human lung epithelial cell line. SARS-CoV-2 infection promotes and inhibits the transcription activity of Sp1 and HNF4, respectively. The PI3K/AKT signaling pathway, which is activated by SARS-CoV-2 infection, is a crucial node for induction of ACE2 expression by increasing Sp1 phosphorylation, an indicator of its activity, and reducing HNF4 nuclear location. Furthermore, we show that colchicine could inhibit the PI3K/AKT signaling pathway, thereby suppressing ACE2 expression. Inhibition of Sp1 by either its inhibitor mithramycin A or colchicine reduces viral replication and tissue injury in Syrian hamsters infected with SARS-CoV-2. In summary, our study uncovers a novel function of Sp1 in regulating ACE2 expression and suggests that Sp1 is a potential target to reduce SARS-CoV-2 infection.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Cesar L Moreno", - "author_inst": "The Dr. John and Anne Chong Lab for Functional Genomics, Charles Perkins Centre and School of Life & Environmental Sciences, The University of Sydney, Sydney, N" - }, - { - "author_name": "Fernanda V. S. Castanheira", - "author_inst": "Snyder Institute for Chronic Diseases, University of Calgary, Alberta T2N 4N1, Canada." - }, - { - "author_name": "Alberto Ospina Stella", - "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." - }, - { - "author_name": "Felicity Chung", - "author_inst": "The Dr. John and Anne Chong Lab for Functional Genomics, Charles Perkins Centre and School of Life & Environmental Sciences, The University of Sydney, Sydney, N" - }, - { - "author_name": "Anupriya Aggarwal", - "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." - }, - { - "author_name": "Alexander J Cole", - "author_inst": "Centenary Institute and Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia" - }, - { - "author_name": "Lipin Loo", - "author_inst": "The Dr. John and Anne Chong Lab for Functional Genomics, Charles Perkins Centre and School of Life & Environmental Sciences, The University of Sydney, Sydney, N" - }, - { - "author_name": "Alexander Dupuy", - "author_inst": "Haematology Research Lab, Heart Research Institute, University of Sydney, Sydney, NSW 2042, Australia." - }, - { - "author_name": "Yvonnne Kong", - "author_inst": "Haematology Research Lab, Heart Research Institute, University of Sydney, Sydney, NSW 2042, Australia." - }, - { - "author_name": "Lejla Hagimola", - "author_inst": "Haematology Research Lab, Heart Research Institute, University of Sydney, Sydney, NSW 2042, Australia." - }, - { - "author_name": "Jemma Fenwick", - "author_inst": "Haematology Research Lab, Heart Research Institute, University of Sydney, Sydney, NSW 2042, Australia." - }, - { - "author_name": "Paul Coleman", - "author_inst": "Haematology Research Lab, Heart Research Institute, University of Sydney, Sydney, NSW 2042, Australia." + "author_name": "Hui Han", + "author_inst": "Yunnan University" }, { - "author_name": "Michelle Wilson", - "author_inst": "Snyder Institute for Chronic Diseases, University of Calgary, Alberta T2N 4N1, Canada." + "author_name": "Rong-Hua Luo", + "author_inst": "Kunming Institute of Zoology" }, { - "author_name": "Maxwell Bui-Marinos", - "author_inst": "Snyder Institute for Chronic Diseases, University of Calgary, Alberta T2N 4N1, Canada." + "author_name": "Xin-Yan Long", + "author_inst": "Kunming Institute of Zoology" }, { - "author_name": "Daniel Hesselson", - "author_inst": "Centenary Institute and Faculty of Medicine and Health, The University of Sydney, Sydney, New South Wales, Australia" + "author_name": "Qian Zhu", + "author_inst": "Yunnan University" }, { - "author_name": "Jennifer Gamble", - "author_inst": "Vascular Biology Program Centenary Institute, The University of Sydney, Sydney, NSW, Australia." + "author_name": "Xin-Yue Tang", + "author_inst": "Yunnan University" }, { - "author_name": "Freda Passam", - "author_inst": "Haematology Research Lab, Heart Research Institute, University of Sydney, Sydney, NSW 2042, Australia." + "author_name": "Rui Zhu", + "author_inst": "Yunnan University" }, { - "author_name": "Stuart Turville", - "author_inst": "The Kirby Institute, University of New South Wales, New South Wales, Australia." + "author_name": "Yi-Cheng Ma", + "author_inst": "Yunnan University" }, { - "author_name": "Paul Kubes", - "author_inst": "Snyder Institute for Chronic Diseases, University of Calgary, Alberta T2N 4N1, Canada." + "author_name": "Yong-Tang Zheng", + "author_inst": "Kunming Institute of Zoology" }, { - "author_name": "G Gregory Neely", - "author_inst": "The University of Sydney" + "author_name": "Cheng-gang Zou", + "author_inst": "Yunnan University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2023.02.14.528476", @@ -139080,43 +138735,107 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.02.08.23285589", - "rel_title": "Clinical severity prediction of COVID-19 admitted patients in Spain: SEMI and REDISSEC cohorts", + "rel_doi": "10.1101/2023.02.08.23285673", + "rel_title": "Estimating serum cross-neutralizing responses to SARS-CoV-2 Omicron sub-lineages elicited by pre-Omicron or Omicron breakthrough infection with exposure interval compensation modeling", "rel_date": "2023-02-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.08.23285589", - "rel_abs": "This report addresses, from a machine learning perspective, a multi-class classification problem to predict the first deterioration level of a COVID-19 positive patient at the time of hospital admission. Socio-demographic features, laboratory tests and other measures are taken into account to learn the models. Our output is divided into 4 categories ranging from healthy patients, followed by patients requiring some form of ventilation (divided in 2 cate-gories) and finally patients expected to die. The study is conducted thanks to data provided by Sociedad Espanola de Medicina Interna (SEMI) and Red de Investigacion en Servicios de Salud de Enfermedades Cronicas (REDISSEC). Results show that logistic regression is the best method for identifying patients with clinical deterioration.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.08.23285673", + "rel_abs": "Understanding the differences in serum cross-neutralizing responses against SARS-CoV-2 variants, including Omicron sub-lineages BA.5, BA.2.75, and BQ.1.1, elicited by exposure to distinct antigens is essential for developing COVID-19 booster vaccines with enhanced cross-protection against antigenically distinct variants. However, fairly comparing the impact of breakthrough infection on serum neutralizing responses to several variants with distinct epidemic timing is challenging because responses after breakthrough infection are affected by the exposure interval between vaccination and infection. We assessed serum cross-neutralizing responses to SARS-CoV-2 variants, including Omicron sub-lineages, in individuals with breakthrough infections before or during the Omicron BA.1 epidemic. To understand the differences in serum cross-neutralizing responses after pre-Omicron or Omicron breakthrough infection, we used Bayesian hierarchical modeling to correct the cross-neutralizing responses for the exposure interval between vaccination and breakthrough infection. The exposure interval required to generate saturated cross-neutralizing potency against each variant differed by variant, with variants more antigenically distant from the ancestral strain requiring a longer interval. Additionally, Omicron breakthrough infection was estimated to have higher impact than booster vaccination and pre-Omicron breakthrough infection on inducing serum neutralizing responses to the ancestral strain and Omicron sub-lineages. However, the breadth of cross-neutralizing responses to Omicron sub-lineages, including BQ.1.1, after Omicron or pre-Omicron breakthrough infection with the ideal exposure interval were estimated to be comparable. Our results highlight the importance of optimizing the interval between vaccine doses for maximizing the breadth of cross-neutralizing activity elicited by booster vaccines with or without Omicron antigen.\n\nSignificance StatementSARS-CoV-2 infections after vaccination with COVID-19 mRNA vaccines with the ancestral spike antigen induce high serum neutralizing responses against Omicron sub-lineages, which are antigenically distant from the ancestral antigen. In individuals with breakthrough infections, the exposure interval from vaccination to infection is critical for the induction of serum cross-neutralizing activity. We used statistical modeling to estimate the serum neutralizing response to Omicron sub-lineages corrected for the influence of different exposure intervals between vaccination and breakthrough infection in individuals with pre-Omicron and Omicron breakthrough infections. This enabled us to assess fairly the effects of exposure to distinct antigens on inducing serum cross-neutralizing responses with the ideal exposure interval, and revealed the clinical significance of optimizing the dose interval in COVID-19 booster vaccination.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Mario Mart\u00ednez-Garc\u00eda", - "author_inst": "Basque Center for Applied Mathematics, BCAM, Bilbao, Spain" + "author_name": "Sho Miyamoto", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Yudai Kuroda", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Takayuki Kanno", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Akira Ueno", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Nozomi Shiwa-Sudo", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Naoko Iwata-Yoshikawa", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Yusuke Sakai", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Noriyo Nagata", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Takeshi Arashiro", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Akira Ainai", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Saya Moriyama", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Noriko Kishida", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Shinji Watanabe", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Kiyoko Nojima", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Yohei Seki", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Takuo Mizukami", + "author_inst": "National Institute of Infectious Diseases" + }, + { + "author_name": "Hideki Hasegawa", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Susana Garc\u00eda-Gutierrez", - "author_inst": "Galdakao Hospital, Osakidetza, Basque Country, Spain" + "author_name": "Hideki Ebihara", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Lasai Barre\u00f1ada Taleb", - "author_inst": "Basque Center for Applied Mathematics, BCAM, Bilbao, Spain" + "author_name": "Shuetsu Fukushi", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Rub\u00e9n Arma\u00f1anzas", - "author_inst": "Institute of Data Science and Artificial Intelligence, Universidad de Navarra, Pamplona, Spain" + "author_name": "Yoshimasa Takahashi", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Inaki Inza", - "author_inst": "University of the Basque Country UPV/EHU, Computer Science Faculty, San Sebasti\u00e1n, Spain" + "author_name": "Ken Maeda", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Jose A. Lozano", - "author_inst": "Basque Center for Applied Mathematics, BCAM, Bilbao, Spain" + "author_name": "Tadaki Suzuki", + "author_inst": "National Institute of Infectious Diseases" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.02.08.23285643", @@ -140766,85 +140485,109 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.02.02.23285352", - "rel_title": "Safety, Virology, Pharmacokinetics, and Clinical Experience of High-dose Intravenous Sotrovimab for the Treatment of Mild to Moderate COVID-19: An Open-label Clinical Trial", + "rel_doi": "10.1101/2023.02.02.23285391", + "rel_title": "Longitudinal and Quantitative Fecal Shedding Dynamics of SARS-CoV-2, Pepper Mild Mottle Virus and CrAssphage", "rel_date": "2023-02-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.02.23285352", - "rel_abs": "Background500 mg intravenous (IV) sotrovimab has been shown to be well tolerated and efficacious against pre-Omicron strains in treating patients with mild to moderate coronavirus disease 2019 (COVID-19) at high risk for disease progression.\n\nMethodsThis was an open-label, single-arm substudy of phase 3 COMET-TAIL (NCT04913675) assessing the safety and tolerability of a 2000 mg IV dose of sotrovimab. Symptomatic patients (aged [≥]18 years) with COVID-19 at high risk for progression were enrolled from June 30 through July 11, 2022, when Omicron BA.5, BA.2.12.1, and BA.4 were the predominant circulating variants in the United States. The primary endpoint was occurrence of adverse events (AEs), serious AEs (SAEs), AEs of special interest, and COVID-19 disease-related events (DREs) through Day 8. Safety, pharmacokinetics, viral load, and hospitalization >24 hours for acute management of illness or death through Day 29 were assessed.\n\nResultsAll participants (n=81) were Hispanic, 58% were female, and 51% were aged [≥]55 years. Through Day 8, no AEs, including infusion-related reactions or hypersensitivity, were reported; 2 participants reported DREs (mild cough, n=2). One SAE (acute myocardial infarction), which was considered unrelated to sotrovimab or COVID-19 by the investigator, occurred on Day 27 and was the only hospitalization reported. Maximum serum concentration (geometric mean) was 745.9 {micro}g/mL. Viral load decreased from baseline through Day 29; only 2 participants (3%) had persistently high viral load ([≥]4.1 log10 copies/mL) at Day 8.\n\nConclusions2000 mg IV sotrovimab was well tolerated, with no new unanticipated safety signals observed.\n\nKey points summaryIn participants with mild to moderate coronavirus disease 2019 at risk for progression to severe disease, a 2000 mg intravenous dose of sotrovimab had a low frequency of adverse events, with no hypersensitivity, infusion-related reactions, or deaths observed.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.02.02.23285391", + "rel_abs": "Wastewater-based epidemiology (WBE) emerged during the COVID-19 pandemic as a scalable and broadly applicable method for community-level monitoring of infectious disease burden, though the lack of high-quality, longitudinal fecal shedding data of SARS-CoV-2 and other viruses limits the interpretation and applicability of wastewater measurements. In this study, we present longitudinal, quantitative fecal shedding data for SARS-CoV-2 RNA, as well as the commonly used fecal indicators Pepper Mild Mottle Virus (PMMoV) RNA and crAss-like phage (crAssphage) DNA. The shedding trajectories from 48 SARS-CoV-2 infected individuals suggest a highly individualized, dynamic course of SARS-CoV-2 RNA fecal shedding, with individual measurements varying from below limit of detection to 2.79x106 gene copies/mg - dry mass of stool (gc/mg-dw). Of individuals that contributed at least 3 samples covering a range of at least 15 of the first 30 days after initial acute symptom onset, 77.4% had at least one positive SARS-CoV-2 RNA stool sample measurement. We detected PMMoV RNA in at least one sample from all individuals and in 96% (352/367) of samples overall; and measured crAssphage DNA above detection limits in 80% (38/48) of individuals and 48% (179/371) of samples. Median shedding values for PMMoV and crAssphage nucleic acids were 1x105 gc/mg-dw and 1.86x103 gc/mg-dw, respectively. These results can be used to inform and build mechanistic models to significantly broaden the potential of WBE modeling and to provide more accurate insight into SARS-CoV-2 prevalence estimates.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Jaynier Moya", - "author_inst": "Pines Care Research Center" + "author_name": "Peter J Arts", + "author_inst": "University of Michigan" }, { - "author_name": "Marisol Temech", - "author_inst": "Vir Biotechnology, Inc." + "author_name": "J Daniel Kelly", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Sergio Parra", - "author_inst": "Vir Biotechnology, Inc." + "author_name": "Claire M Midgley", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Erick Juarez", - "author_inst": "Florida International Medical Research" + "author_name": "Khamal Anglin", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Reinaldo Hernandez-Loy", - "author_inst": "Dynamic Medical Research, LLC" + "author_name": "Scott Lu", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Juan C. Moises Gutierrez", - "author_inst": "Continental Clinical Research, LLC" + "author_name": "Glen R Abedi", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Jorge Diaz", - "author_inst": "Doral Medical Research" + "author_name": "Raul N Andino", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Rubaba Hussain", - "author_inst": "RH Medical Urgent Care" + "author_name": "Kevin M Bakker", + "author_inst": "University of Michigan" }, { - "author_name": "Scott Segal", - "author_inst": "GSK" + "author_name": "Bryon Banman", + "author_inst": "University of Michigan" }, { - "author_name": "Claire Xu", - "author_inst": "GSK" + "author_name": "Alexandria Boehm", + "author_inst": "Stanford University" }, { - "author_name": "Andrew Skingsley", - "author_inst": "GSK" + "author_name": "Melissa Briggs-Hagen", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Gretja Schnell", - "author_inst": "Vir Biotechnology, Inc." + "author_name": "Andrew F Brouwer", + "author_inst": "University of Michigan" }, { - "author_name": "Asma El-Zailik", - "author_inst": "Vir Biotechnology, Inc." + "author_name": "Michelle C Davidson", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Jennnifer E. Sager", - "author_inst": "Vir Biotechnology, Inc." + "author_name": "Marisa C Eisenberg", + "author_inst": "University of Michigan" }, { - "author_name": "Melissa Aldinger", - "author_inst": "Vir Biotechnology, Inc." + "author_name": "Miguel A Garcia Knight", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Elizabeth L. Alexander", - "author_inst": "Vir Biotechnology, Inc." + "author_name": "Sterling Knight", + "author_inst": "University of Michigan" }, { - "author_name": "Gerard Acloque", - "author_inst": "Universal Medical and Research Center" + "author_name": "Michael J Peluso", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Jesus Pineda-Ramirez", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Michel Tassetto", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Ruth Diaz-Sanchez", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Sharon Saydeh", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Jeffrey N Martin", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Krista R Wigginton", + "author_inst": "University of Michigan" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -142432,75 +142175,59 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2023.02.02.526749", - "rel_title": "Investigations on SARS-CoV-2 and other coronaviruses in mink farms in France at the end of the first year of COVID-19 pandemic", + "rel_doi": "10.1101/2023.02.01.526623", + "rel_title": "Crystal Structures of Inhibitor-Bound Main Protease from Delta- and Gamma-Coronaviruses", "rel_date": "2023-02-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.02.526749", - "rel_abs": "Soon after the beginning of the COVID-19 pandemic in early 2020, the Betacoronavirus SARS-CoV-2 infection of several mink farms breeding American minks (Neovison vison) for fur was detected in several countries of Europe. The risk of a new reservoir formation and of a reverse zoonosis from minks was then a major concern. The aim of this study was to investigate the four French mink farms for the circulation of SARS-CoV-2 at the end of 2020. The investigations took place during the slaughtering period thus facilitating different types of sampling (swabs and blood). In one of the four mink farms, 96.6% of serum samples were positive in SARS-CoV-2 ELISA coated with purified N protein recombinant antigen and 54 out of 162 (33%) pharyngo-tracheal swabs were positive by RT-qPCR. The genetic variability among 12 SARS-CoV-2 genomes sequenced in this farm indicated the co-circulation of several lineages at the time of sampling. All SARS-CoV-2 genomes detected were nested within the 20A clade (Nextclade), together with SARS-CoV-2 genomes from humans sampled at the same period. The percentage of SARS-CoV-2 seropositivity by ELISA varied between 0.5 and 1.2% in the three other farms. Interestingly, among these three farms, 11 pharyngo-tracheal swabs and 3 fecal pools from two farms were positive by end-point RT-PCR for an Alphacoronavirus highly similar to a mink coronavirus sequence observed in Danish farms in 2015. In addition, a mink Caliciviridae was identified in one of the two positive farms for Alphacoronavirus. The clinical impact of these unapparent viral infections is not known. The co-infection of SARS-CoV-2 with other viruses in mink farms could contribute to explain the diversity of clinical symptoms noted in different infected farms in Europe. In addition, the co-circulation of an Alphacoronavirus and SARS-CoV-2 within a mink farm would increase potentially the risk of viral recombination between alpha and betacoronaviruses already suggested in wild and domestic animals, as well as in humans.\n\nAuthor summaryFrance is not a country of major mink fur production. Following the SARS-CoV-2 contamination of mink farms in Denmark and the Netherlands, the question arose for the four French farms.\n\nThe investigation conducted at the same time in the four farms revealed the contamination of one of them by a variant different from the one circulating at the same time in Denmark and the Netherlands mink farms.\n\nInvestigation of three other farms free of SARS-CoV-2 contamination revealed the circulation of other viruses including a mink Alphacoronavirus and Caliciviridae, which could modify the symptomatology of SARS-CoV-2 infection in minks.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.02.01.526623", + "rel_abs": "With the spread of SARS-CoV-2 throughout the globe to cause the COVID-19 pandemic, the threat of zoonotic transmissions of coronaviruses (CoV) has become even more evident. As human infections have been caused by alpha- and beta-CoVs, structural characterization and inhibitor design mostly focused on these two genera. However, viruses from the delta and gamma genera also infect mammals and pose potential zoonotic transmission threat. Here, we determined the inhibitor-bound crystal structures of the main protease (Mpro) from the delta-CoV porcine HKU15 and gamma-CoV SW1 from beluga whale. Comparison with the apo structure of SW1 Mpro, which we also present here, enabled identifying structural arrangements upon inhibitor binding at the active site. The binding modes and interactions of two covalent inhibitors, PF-00835231 (lufotrelvir) bound to HKU15 and GC376 bound to SW1 Mpro, reveal features that may be leveraged to target diverse coronaviruses and toward structure-based design of pan-CoV inhibitors.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Marine Wasniewski", - "author_inst": "Anses Laboratoire de la rage et de la faune sauvage de Nancy" - }, - { - "author_name": "Franck Bou\u00e9", - "author_inst": "Anses Laboratoire de la rage et de la faune sauvage de Nancy" - }, - { - "author_name": "C\u00e9line Richomme", - "author_inst": "Anses Laboratoire de la rage et de la faune sauvage de Nancy" - }, - { - "author_name": "Etienne Simon-Lori\u00e8re", - "author_inst": "Institut Pasteur" - }, - { - "author_name": "Sylvie Van der Werf", - "author_inst": "Institut Pasteur" + "author_name": "Sarah N Zvornicanin", + "author_inst": "Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, Massachusetts 01605, USA" }, { - "author_name": "Flora Donati", - "author_inst": "Institut Pasteur" + "author_name": "Ala M Shaqra", + "author_inst": "Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, Massachusetts 01605, USA" }, { - "author_name": "Vincent Enouf", - "author_inst": "Institut Pasteur" + "author_name": "Qiu Yu Huang", + "author_inst": "University of Massachusetts Medical School" }, { - "author_name": "Yannick Blanchard", - "author_inst": "Anses" + "author_name": "Elizabeth Ornelas", + "author_inst": "Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA" }, { - "author_name": "V\u00e9ronique Beven", - "author_inst": "Anses" + "author_name": "Mallika Moghe", + "author_inst": "Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA" }, { - "author_name": "Estelle Leperchois", - "author_inst": "Normandie Universite" + "author_name": "Mark Knapp", + "author_inst": "Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA" }, { - "author_name": "Bryce Leterrier", - "author_inst": "Normandie Universite" + "author_name": "Stephanie Moquin", + "author_inst": "Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA" }, { - "author_name": "Meriadeg Le Gouil", - "author_inst": "Normandie Universite" + "author_name": "Dustin Dovala", + "author_inst": "Novartis Institutes for Biomedical Research, Emeryville, CA 94608, USA" }, { - "author_name": "Elodie Monch\u00e2tre-Leroy", - "author_inst": "Anses Laboratoire de la rage et de la faune sauvage de Nancy" + "author_name": "Celia A Schiffer", + "author_inst": "Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, Massachusetts 01605, USA" }, { - "author_name": "Evelyne Picard-Meyer", - "author_inst": "Anses Laboratoire de la rage et de la faune sauvage de Nancy" + "author_name": "Nese Kurt Yilmaz", + "author_inst": "Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Chan Medical School, Worcester, Massachusetts 01605, USA" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2023.02.01.526694", @@ -144470,27 +144197,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2023.01.30.526314", - "rel_title": "Fitness effects of mutations to SARS-CoV-2 proteins", + "rel_doi": "10.1101/2023.01.30.526101", + "rel_title": "A comprehensive survey of coronaviral main protease active site diversity in 3D: Identifying and analyzing drug discovery targets in search of broad specificity inhibitors for the next coronavirus pandemic", "rel_date": "2023-01-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.30.526314", - "rel_abs": "Knowledge of the fitness effects of mutations to SARS-CoV-2 can inform assessment of new variants, design of therapeutics resistant to escape, and understanding of the functions of viral proteins. However, experimentally measuring effects of mutations is challenging: we lack tractable lab assays for many SARS-CoV-2 proteins, and comprehensive deep mutational scanning has been applied to only two SARS-CoV-2 proteins. Here we develop an approach that leverages millions of publicly available SARS-CoV-2 sequences to estimate effects of mutations. We first calculate how many independent occurrences of each mutation are expected to be observed along the SARS-CoV-2 phylogeny in the absence of selection. We then compare these expected observations to the actual observations to estimate the effect of each mutation. These estimates correlate well with deep mutational scanning measurements. For most genes, synonymous mutations are nearly neutral, stop-codon mutations are deleterious, and amino-acid mutations have a range of effects. However, some viral accessory proteins are under little to no selection. We provide interactive visualizations of effects of mutations to all SARS-CoV-2 proteins (https://jbloomlab.github.io/SARS2-mut-fitness/). The framework we describe is applicable to any virus for which the number of available sequences is sufficiently large that many independent occurrences of each neutral mutation are observed.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.30.526101", + "rel_abs": "Although the rapid development of therapeutic responses to combat SARS-CoV-2 represents a great human achievement, it also demonstrates untapped potential for advanced pandemic preparedness. Cross-species efficacy against multiple human coronaviruses by the main protease (MPro) inhibitor nirmatrelvir raises the question of its breadth of inhibition and our preparedness against future coronaviral threats. Herein, we describe sequence and structural analyses of 346 unique MPro enzymes from all coronaviruses represented in the NCBI Virus database. Cognate substrates of these representative proteases were inferred from their polyprotein sequences. We clustered MPro sequences based on sequence identity and AlphaFold2-predicted structures, showing approximate correspondence with known viral subspecies. Predicted structures of five representative MPros bound to their inferred cognate substrates showed high conservation in protease:substrate interaction modes, with some notable differences. Yeast-based proteolysis assays of the five representatives were able to confirm activity of three on inferred cognate substrates, and demonstrated that of the three, only one was effectively inhibited by nirmatrelvir. Our findings suggest that comprehensive preparedness against future potential coronaviral threats will require continued inhibitor development. Our methods may be applied to candidate coronaviral MPro inhibitors to evaluate in advance the breadth of their inhibition and identify target coronaviruses potentially meriting advanced development of alternative countermeasures.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Jesse D Bloom", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Joseph H Lubin", + "author_inst": "Rutgers University" }, { - "author_name": "Richard A Neher", - "author_inst": "University of Basel" + "author_name": "Samantha G Martinusen", + "author_inst": "University of Florida" + }, + { + "author_name": "Christine Zardecki", + "author_inst": "Rutgers University" + }, + { + "author_name": "Cassandra Olivas", + "author_inst": "California State University Stanislaus" + }, + { + "author_name": "Mickayla Bacorn", + "author_inst": "University of Maryland Baltimore County" + }, + { + "author_name": "MaryAgnes Balogun", + "author_inst": "Morgan State University" + }, + { + "author_name": "Ethan W Slaton", + "author_inst": "University of Florida" + }, + { + "author_name": "Amy Wu Wu", + "author_inst": "University of Puerto Rico Mayaguez" + }, + { + "author_name": "Sarah Sakeer", + "author_inst": "Rutgers University" + }, + { + "author_name": "Brian P Hudson", + "author_inst": "Rutgers University" + }, + { + "author_name": "Carl Denard", + "author_inst": "University of Florida" + }, + { + "author_name": "Stephen K Burley", + "author_inst": "Rutgers University" + }, + { + "author_name": "Sagar D Khare", + "author_inst": "Rutgers University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "evolutionary biology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2023.01.31.526312", @@ -146284,53 +146055,53 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2023.01.24.23284885", - "rel_title": "Impact of vaccination and risk factors on COVID-19 mortality amid delta surge in Libya: a single centre cohort study", + "rel_doi": "10.1101/2023.01.25.23284996", + "rel_title": "Bioinformatics and system biology approach to identify the influences of COVID-19 on metabolic unhealthy obese patients", "rel_date": "2023-01-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.24.23284885", - "rel_abs": "BackgroundThe Delta variant has led to a surge in COVID-19 cases in Libya, making it crucial to investigate the impact of vaccination on mortality rates among hospitalized patients and critically ill.\n\nAimsTo study risk factors and COVID-19 mortality rates among unvaccinated and vaccinated adults during delta wave at a single COVID-19 care centre in Tripoli, Libya.\n\nMethodsThe study involved two independent cohorts (n=341). One cohort was collected retrospectively from May 2021-August 2021 and the second cohort was prospectively collected from August 2021-October 2021 and most of them were during the Delta wave. The two cohorts were merged and analysed as one group.\n\nResultsMost patients were male (60.5%) and 53.3% were >60 years. The vast majority of admitted patients did not have previous COVID-19 infection (98.9%) and were unvaccinated (90.3%). Among vaccinated, 30 patients had one dose and only 3 had two doses. Among patients who received one dose, 58.1% (18/31) died and 41.9% (13/31) survived. Most patients (72.2%) had a pre-existing medical condition. Multivariable prediction model showed that age >60 years was significantly associated with death (odds ratio=2.328, CI 1.456-3.724, p-value=<0.0001).\n\nConclusionPrevious infection or full vaccination against COVID-19 significantly reduces hospitalization and death, as most admitted patients were unvaccinated and not previously infected. However, a single vaccine dose may not be adequate, especially for older individuals and those with underlying medical conditions. High-risk older patients with comorbidities should be fully vaccinated and offered up to date bivalent COVID-19 booster doses.", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.25.23284996", + "rel_abs": "ObjectiveThe severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) has posed a significant challenge to individuals health. Increasing evidence shows that patients with metabolic unhealthy obesity (MUO) and COVID-19 have severer complications and higher mortality rate. However, the molecular mechanisms underlying the association between MUO and COVID-19 are poorly understood. We sought to implement transcriptomic analysis using bioinformatics and systems biology analysis approaches.\n\nMethodsHere, two datasets (GSE196822 and GSE152991) were employed to extract differentially expressed genes (DEGs) to identify common hub genes, shared pathways and candidate drugs and construct a gene-disease network.\n\nResultsBased on the identified 65 common DEGs, the results revealed hub genes and essential modules. Moreover, common associations between MUO and COVID-19 were found. Transcription factors (TFs)-genes interaction, and DEGs-miRNAs coregulatory network were identified. Furthermore, the gene-disease association were obtained and constructed.\n\nConclusionsThe shared pathogenic pathways are noted worth paying attention to. Several genes are highlighted as critical targets for developing treatments for and investigating the complications of COVID-19 and MUO. Additionally, multiple genes are identified as promising biomarkers. We think this studys result may help in selecting and inventing future treatments that can combat COVID-19 and MUO.\n\nAnswer for the Study Importance QuestionsO_ST_ABSWhat is already known about this subject?C_ST_ABSSARS-COV-2 infection can cause additional severe complications, particularly in patients with obesity and associated metabolic disturbance, which can also increase the risk of SARS-COV-2 infection and hospitalization. SARS-COV-2 infection can cause additional severe complications, particularly in patients with obesity and associated metabolic disturbances, which can also increase the risk of SARS-COV-2 infection and hospitalization.\n\nWhat are the new findings in your manuscript?Based on the 65 identified common DEGs, the shared pathogenic pathways are noted worth paying attention to. Several genes are highlighted as critical targets for developing treatments for and investigating the complications of COVID-19 and MUO. Additionally, multiple genes are identified as promising biomarkers. We think this studys result may help in selecting candidate drugs and inventing future treatments that can combat COVID-19 and MUO.\n\nHow might your results change the direction of research or the focus of clinical practice?Potential pathways and genes that significantly affect the prognosis of COVID-19 patients with MUO were identified, which might be helpful for further research about the detailed mechanism of how obesity affects the coronavirus infection. Additionally, the extracted candidate drugs might be the potential drugs for treating these two diseases in clinical practice. The gene-disease network also revealed essential genes linking them with other diseases, providing information for complications studies.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Inas Mohamed Alhudiri", - "author_inst": "Biotechnology Research center" + "author_name": "Tengda Huang", + "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collabor" }, { - "author_name": "Zakarya Suleiman ABUSREWIL", - "author_inst": "University of Tripoli" + "author_name": "Nan Jiang", + "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collabor" }, { - "author_name": "Omran Dakhil", - "author_inst": "Souq Thullatha Isolation Centre, Tripoli, Libya" + "author_name": "Yujia Song", + "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collabor" }, { - "author_name": "Mosab Ali Zwaik", - "author_inst": "Souq Thullatha Isolation Centre, Tripoli, Libya" + "author_name": "Hongyuan Pan", + "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collabor" }, { - "author_name": "Mohammed Ammar Awn", - "author_inst": "Souq Thullatha Isolation Centre, Tripoli, Libya" + "author_name": "Jingcheng Bai", + "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collabor" }, { - "author_name": "Mwada Jallul", - "author_inst": "Libyan Biotechnology Research Centre, Tripoli, Libya" + "author_name": "Bingxuan Yu", + "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collabor" }, { - "author_name": "Aimen Ibrahim Ahmed", - "author_inst": "National Migration Health, International Organization for Migration, Tripoli, Libya" + "author_name": "Jingyi He", + "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collabor" }, { - "author_name": "Rasha Abugrara", - "author_inst": "National Migration Health, International Organization for Migration, Tripoli, Libya" + "author_name": "Kefei Yuan", + "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collabor" }, { - "author_name": "Adam Ibrahim Elzagheid", - "author_inst": "Libyan Biotechnology Research Center, Tripoli, Libya" + "author_name": "Zhen Wang", + "author_inst": "Department of Liver Surgery & Liver Transplantation, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, and Collabor" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -148194,59 +147965,159 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2023.01.24.525203", - "rel_title": "Multimodal characterization of antigen-specific CD8+ T cells across SARS-CoV-2 vaccination and infection.", + "rel_doi": "10.1101/2023.01.24.23284869", + "rel_title": "A Randomized Trial Comparing Omicron-Containing Boosters with the Original Covid-19 Vaccine mRNA-1273", "rel_date": "2023-01-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.24.525203", - "rel_abs": "The human immune response to SARS-CoV-2 antigen after infection or vaccination is defined by the durable production of antibodies and T cells. Population-based monitoring typically focuses on antibody titer, but there is a need for improved characterization and quantification of T cell responses. Here, we utilize multimodal sequencing technologies to perform a longitudinal analysis of circulating human leukocytes collected before and after BNT162b2 immunization. Our data reveal distinct subpopulations of CD8+ T cells which reliably appear 28 days after prime vaccination (7 days post boost). Using a suite of cross-modality integration tools, we define their transcriptome, accessible chromatin landscape, and immunophenotype, and identify unique biomarkers within each modality. By leveraging DNA-oligo-tagged peptide-MHC multimers and T cell receptor sequencing, we demonstrate that this vaccine-induced population is SARS-CoV-2 antigen-specific and capable of rapid clonal expansion. Moreover, we also identify these CD8+ populations in scRNA-seq datasets from COVID-19 patients and find that their relative frequency and differentiation outcomes are predictive of subsequent clinical outcomes. Our work contributes to our understanding of T cell immunity, and highlights the potential for integrative and multimodal analysis to characterize rare cell populations.", - "rel_num_authors": 10, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.24.23284869", + "rel_abs": "BackgroundOmicron-containing bivalent boosters are available worldwide. Results of a large, randomized, active-controlled study are presented.\n\nMethodsThis phase 3, randomized, observer-blind, active-controlled trial in the United Kingdom evaluated the immunogenicity and safety of 50-{micro}g doses of omicron-BA.1-monovalent mRNA-1273.529 and bivalent mRNA-1273.214 booster vaccines compared with 50-{micro}g mRNA-1273 administered as boosters in individuals [≥]16 years. Participants had previously received 2 doses of any authorized/approved Covid-19 vaccine with or without an mRNA vaccine booster. Safety and immunogenicity were primary objectives; immunogenicity was assessed in all participants, with analysis conducted based on prior infection status. Incidence of Covid-19 post-boost was a secondary (mRNA-1273.214) or exploratory (mRNA-1273.529) objective.\n\nResultsIn part 1 of the study, 719 participants received mRNA-1273.529 (n=362) or mRNA-1273 (n=357); in part 2, 2813 received mRNA-1273.214 (n=1418) or mRNA-1273 (n=1395). Median durations (months [interquartile range]) between the most recent Covid-19 vaccine and study boosters were similar in the mRNA-1273.529 (4.0 [3.6-4.7]) and mRNA-1273 (4.1 [3.5-4.7]) (part 1), and mRNA-1273.214 (5.5 [4.8-6.2] and mRNA-1273 (5.4 [4.8-6.2]) groups (part 2).\n\nBoth mRNA-1273.529 and mRNA-1273.214 elicited superior neutralizing antibody responses against omicron BA.1 with geometric mean ratios (99% CIs) of 1.68 (1.45-1.95) and 1.53 (1.41-1.67) compared to mRNA-1273 at day 29 post-boost. Although the study was not powered to assess relative vaccine efficacy, the incidence rates/1000 person years (95% CI) of Covid-19 trended lower with mRNA-1273.529 (670.5 [528.3-839.3]) than mRNA-1273 (769.3 [615.4-950.1]) and mRNA-1273.214 (633.0 [538.1-739.7]) than mRNA-1273 (711.6 [607.5-828.5]).\n\nSequence analysis in part 2 showed that this was driven by lower incidence of Covid-19 in the mRNA-1273.214 cohort with BA.2 and BA.4 sublineages but not BA.5 sublineages. All study boosters were well-tolerated.\n\nConclusionThe bivalent omicron BA.1-containing booster elicited superior neutralizing antibody responses against omicron BA.1 with acceptable safety results consistent with the BA.1 monovalent vaccine. Incidence rates for Covid-19 were numerically lower in participants who received mRNA-1273.214 compared to the original booster vaccine mRNA-1273, driven by the BA.2 and BA.4 sublineages.", + "rel_num_authors": 35, "rel_authors": [ { - "author_name": "Bingjie Zhang", - "author_inst": "1 New York Genome Center, New York, NY, USA. 2 Center for Genomics and Systems Biology, New York University, New York, NY, USA. 3 Department of Cell Biology and" + "author_name": "Ivan T. Lee", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" }, { - "author_name": "Rabi Upadhyay", - "author_inst": "3 Department of Cell Biology and Regenerative Medicine, New York University Grossman School of Medicine, New York, NY, USA. 4 Perlmutter Cancer Center, New York" + "author_name": "Catherine A. Cosgrove", + "author_inst": "Vaccine Institute, Centre for Neonatal and Paediatric Infection, St Georges University of London, London, UK" }, { - "author_name": "Yuhan Hao", - "author_inst": "1 New York Genome Center, New York, NY, USA. 2 Center for Genomics and Systems Biology, New York University, New York, NY, USA." + "author_name": "Patrick Moore", + "author_inst": "The Adam Practice, Poole, Dorset, UK, and University Hospital Southampton NHS Foundation Trust, Southampton, UK" }, { - "author_name": "Marie I. Samanovic", - "author_inst": "5 Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA. 6 New York University Langone Vaccine Center, New York, NY, USA." + "author_name": "Claire Bethune", + "author_inst": "University Hospitals Plymouth NHS Trust, Plymouth, UK" }, { - "author_name": "Ramin S. Herati", - "author_inst": "5 Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA. 6 New York University Langone Vaccine Center, New York, NY, USA." + "author_name": "Rhiannon Nally", + "author_inst": "Wansford and Kings Cliffe Practice, Wansford, UK" }, { - "author_name": "John Blair", - "author_inst": "1 New York Genome Center, New York, NY, USA. 2 Center for Genomics and Systems Biology, New York University, New York, NY, USA." + "author_name": "Marcin Bula", + "author_inst": "University of Liverpool, Liverpool, UK" }, { - "author_name": "Jordan Axelrad", - "author_inst": "5 Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA." + "author_name": "Philip A. Kalra", + "author_inst": "Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Salford, UK" }, { - "author_name": "Mark J Mulligan", - "author_inst": "5 Department of Medicine, New York University Grossman School of Medicine, New York, NY, USA. 6 New York University Langone Vaccine Center, New York, NY, USA." + "author_name": "Rebecca Clark", + "author_inst": "Layton Medical Centre, Blackpool, UK" }, { - "author_name": "Dan R Littman", - "author_inst": "3 Department of Cell Biology and Regenerative Medicine, New York University Grossman School of Medicine, New York, NY, USA. 4 Perlmutter Cancer Center, New York" + "author_name": "Paul Dargan", + "author_inst": "Guys and Saint Thomas NHS Foundation Trust, Kings College London, London, UK" }, { - "author_name": "Rahul Satija", - "author_inst": "1 New York Genome Center, New York, NY, USA. 2 Center for Genomics and Systems Biology, New York University, New York, NY, USA." + "author_name": "Marta Boffito", + "author_inst": "Chelsea and Westminster Hospital NHS Foundation Trust and Imperial College London, London, UK" + }, + { + "author_name": "Ray Sheridan", + "author_inst": "Royal Devon University Hospital, Exeter, UK" + }, + { + "author_name": "Ed Moran", + "author_inst": "Southmead Hospital, Bristol UK" + }, + { + "author_name": "Thomas C. Darton", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, UK" + }, + { + "author_name": "Fiona Burns", + "author_inst": "Royal Free London NHS Foundation Trust University and University College London" + }, + { + "author_name": "Dinesh Saralaya", + "author_inst": "National Institute for Health Research Patient Recruitment Centre and Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK" + }, + { + "author_name": "Christopher J. A. Duncan", + "author_inst": "Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK and NIHR Newcastle Clinical Research Facility, The Newcastle upon T" + }, + { + "author_name": "Patrick Lillie", + "author_inst": "Hull University Teaching Hospitals NHS Trust, Castle Hill Hospital, Cottingham, UK" + }, + { + "author_name": "Alberto San Francisco Ramos", + "author_inst": "Vaccine Institute, Centre for Neonatal and Paediatric Infection, St Georges University of London, London, UK" + }, + { + "author_name": "Eva Galiza", + "author_inst": "Vaccine Institute, Centre for Neonatal and Paediatric Infection, St Georges University of London, London, UK" + }, + { + "author_name": "Paul T. Heath", + "author_inst": "St Georges, University of London" + }, + { + "author_name": "Spyros Chalkias", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Bethany Girard", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Christy Parker", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Dondi Rust", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Shraddha Mehta", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Elizabeth de Windt", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Andrea Sutherland", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Joanne E. Tomassini", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Frank J. Dutko", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Weiping Deng", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Xing Chen", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "LaRee Tracy", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Honghong Zhou", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Jacqueline M. Millier", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" + }, + { + "author_name": "Rituparna Das", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts, USA" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "genomics" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/378257", @@ -149872,51 +149743,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2023.01.20.23284812", - "rel_title": "Immunogenicity, Safety and Effectiveness of COVID-19 Pfizer-BioNTech (BNT162b2) mRNA Vaccination in Immunocompromised Adolescents and Young Adults: A systematic Review and Meta-Analyses", + "rel_doi": "10.1101/2023.01.20.23284814", + "rel_title": "Frequency and Clinical Characteristics of Breakthrough Cases Post COVID-19 Vaccine and Predictive Risk Factors in College Students", "rel_date": "2023-01-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.20.23284812", - "rel_abs": "People with weak immune systems are more likely to develop severe COVID-19, less likely to be included in vaccine controlled studies but more likely to be under-vaccinated. We review post-marketing studies to examine the immunogenicity, safety and effectiveness of BNT162b2 vaccine in immunocompromised adolescents and young adults (AYA). We searched more than three international databases from 2020 to 30 May 2022 and used the ROBINS-I for bias assessment. Random effect model was used to estimate pooled proportion, log RR, and mean difference. Eggers regression and Beggs rank correlation were used to examine publication bias. 47 full texts were reviewed, and nine were included. Conditions studied were rheumatic diseases, diabetes mellitus, Down syndrome, solid tumours, neurodisability, and cystic fibrosis. Eight studies used cohort designs and one used cross-sectional designs. Europe led most of the investigations. Most studies had unclear risk of bias and none could rule out selection bias, ascertainment bias, or selective outcome reporting. The overall estimated proportion of combined local and systemic reactions after the first BNT162b2 vaccination was 30%[95% CI: 17-42%] and slightly rose to 32% [95% CI: 19-44%] after the second dose. Rheumatic illnesses had the highest rate of AEFI (40%[95% CI: 16-65%]), while cystic fibrosis had the lowest (27%[95% CI: 17%-38%]). Hospitalizations for AEFIs were rare. Healthy controls exhibited higher levels of neutralizing antibodies and measured IgG than immunocompromised AYA, although pooled estimations did not demonstrate a statistically significant difference after primary dose. BNT162b2 is safe and effective in immunocompromised AYA, with no significant difference to healthy controls. However, current evidence is low to moderate due to high RoB. Our research advocates for improving methodology in studies including specific AYA population.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.20.23284814", + "rel_abs": "BACKGROUNDCOVID-19 vaccines help protect against infection, severe illness, hospitalization and death. When someone who is vaccinated with either a primary series or a primary series plus a booster dose gets infected with the virus that causes COVID-19, it is referred to as a \"vaccine breakthrough infection.\"\n\nOBJECTIVESTo assess the frequency and clinical characteristics of breakthrough cases of COVID-19 infection and to study the predictive risk factors.\n\nSUBJECTS&METHODSA cross-sectional study was carried out including 604 undergraduate medical and non-medical students in Iraq from 10th of August to 29th of September 2022. Data was collected via an online specific questionnaire and analysed to estimate the frequency of COVID-19 breakthrough cases post vaccination, and number of doses of vaccine used. The association of different factors including age, gender, grade, body mass index, smoking, and comorbidities was also studied as predictive risk factors. We used the data to formulate tables, figures and perform statistical tests in IBM SPSS Statistics 25.\n\nRESULTSMean age of study sample was 21.78 year {+/-} 3.26 and 339 (56%) were females. In terms of COVID-19 vaccination data, 97 (16%) have received one dose, 459 (76%) two doses and 48 (8%) three doses. Regarding PCR test, 74 (12%) were positive after the first dose compared to 49 (8%) after the second dose. About the symptoms developed, the most frequent were fever in 372 (61.1%), unusual fatigue in 96 (15.79%), chills in 29 (4.77%) and persistent cough in 26 (4.28%). For most predictive factors, results were statistically insignificant.\n\nCONCLUSIONSIn current study; demographic factors showed no statistically significant impact on prevalence of COVID-19 breakthrough cases. Despite this; number of participants who develop symptoms after the second dose of vaccine was high; and having 3 or more symptoms. About half of participants showed symptoms even after being fully vaccinated.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Patrick DMC Katoto", - "author_inst": "South African Medical Research Council" - }, - { - "author_name": "Mireille AM Kakubu", - "author_inst": "Ministry of Health and Social Services of Namibia, Windhoek, Namibia" - }, - { - "author_name": "Jacques L Tamuzi", - "author_inst": "Stellenbosch University" - }, - { - "author_name": "Amanda S Brand", - "author_inst": "Centre for Evidence-based Health Care, Division of Epidemiology and Biostatistics, Department of Global Health, Faculty of Medicine and Health Sciences, Stellen" - }, - { - "author_name": "Adaeze Ayuk", - "author_inst": "Department of Paediatrics and Child Health, University of Nigeria Teaching Hospital, Enugu, Nigeria" + "author_name": "Manal Abdulrazaq", + "author_inst": "University of Baghdad" }, { - "author_name": "Liliane N. Byamungu", - "author_inst": "Department of Paediatric, Faculty of Medicine and Health Sciences, University of KwaZulu-Natal, Durban, South Africa" + "author_name": "Ahmed Jebur", + "author_inst": "University of Baghdad" }, { - "author_name": "Charles Shey Wiysonge", - "author_inst": "South African Medical Research Council" + "author_name": "Baqer Hamdan", + "author_inst": "University of Baghdad" }, { - "author_name": "Glenda Gray", - "author_inst": "Office of the President and CEO, South African Medical Research Council, Cape Town, South Africa" + "author_name": "Ahmed Ibrahim", + "author_inst": "University of Baghdad" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.01.19.23284764", @@ -151714,91 +151569,55 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2023.01.17.524469", - "rel_title": "A Systematic Survey of Reversibly Covalent Dipeptidyl Inhibitors of the SARS-CoV-2 Main Protease", + "rel_doi": "10.1101/2023.01.17.524492", + "rel_title": "Discovery of highly potent small molecule pan-coronavirus fusion inhibitors", "rel_date": "2023-01-18", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.17.524469", - "rel_abs": "SARS-CoV-2 is the coronavirus pathogen of the currently prevailing COVID-19 pandemic. It relies on its main protease (MPro) for replication and pathogenesis. MPro is a demonstrated target for the development of antivirals for SARS-CoV-2. Past studies have systematically explored tripeptidyl inhibitors such as nirmatrelvir as MPro inhibitors. However, dipeptidyl inhibitors especially those with a spiro residue at their P2 position have not been systematically investigated. In this work, we synthesized about 30 reversibly covalent dipeptidyl MPro inhibitors and characterized them on in vitro enzymatic inhibition potency, structures of their complexes with MPro, cellular MPro inhibition potency, antiviral potency, cytotoxicity, and in vitro metabolic stability. Our results indicated that MPro has a flexible S2 pocket that accommodates dipeptidyl inhibitors with a large P2 residue and revealed that dipeptidyl inhibitors with a large P2 spiro residue such as (S)-2-azaspiro[4,4]nonane-3-carboxylate and (S)-2-azaspiro[4,5]decane-3-carboxylate have optimal characteristics. One compound MPI60 containing a P2 (S)-2-azaspiro[4,4]nonane-3-carboxylate displayed high antiviral potency, low cellular cytotoxicity, and high in vitro metabolic stability and can be potentially advanced to further preclinical tests.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2023.01.17.524492", + "rel_abs": "The unprecedented pandemic of COVID-19, caused by a novel coronavirus, SARS-CoV-2, has led to massive human suffering, death, and economic devastation worldwide. The virus is mutating fast to more transmissible and infectious variants. The Delta variant (B.1.617.2), initially identified in India, and the omicron variant (BA.4 and BA.5) have spread worldwide. In addition, recently alarming antibody evasive SARS-CoV-2 subvariants, BQ and XBB, have been reported. These new variants may pose a substantial challenge to controlling the spread of this virus. Therefore, the continued development of novel drugs having pan-coronavirus inhibition to treat and prevent infection of COVID-19 is urgently needed. These drugs will be critically important in dealing with new pandemics that will emerge in the future. We report the discovery of several highly potent small molecule pan-coronavirus inhibitors. One of which, NBCoV63, showed low nM potency against SARS-CoV-2 (IC50: 55 nM), SARS-CoV (IC50: 59 nM), and MERS-CoV (IC50: 75 nM) in pseudovirus-based assays with excellent selectivity indices (SI: as high as > 900) demonstrating its pan-coronavirus inhibition. NBCoV63 showed equally effective antiviral potency against SARS-CoV-2 mutant (D614G) and several variants of concerns (VOCs) such as B.1.617.2 (Delta), B.1.1.529/BA.1 and BA.4/BA.5 (Omicron) and K417T/E484K/N501Y (Gamma). NBCoV63 also showed similar efficacy profiles to Remdesivir against authentic SARS-CoV-2 (Hong Kong strain) and two of its variants (Delta and Omicron) by plaque reduction in Calu3 cells. Additionally, we show that NBCoV63 inhibits virus-mediated cell-to-cell fusion in a dose-dependent manner. Furthermore, the Absorption, distribution, metabolism, and excretion (ADME) data of NBCoV63 demonstrated drug-like properties.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Zhi Zachary Geng", - "author_inst": "Texas A M University" - }, - { - "author_name": "Sandeep Atla", - "author_inst": "Texas AM University, Department of Chemistry" - }, - { - "author_name": "Namir Shaabani", - "author_inst": "Sorrento Therapeutics" - }, - { - "author_name": "Veerabhadra R Vulupara", - "author_inst": "Texas AM University, Department of Chemistry" - }, - { - "author_name": "Kai S Yang", - "author_inst": "Texas AM University, Department of Chemistry" - }, - { - "author_name": "Yugendar R Alugubelli", - "author_inst": "Texas AM University, Department of Chemistry" - }, - { - "author_name": "Kaustav Khatua", - "author_inst": "Texas AM University, Department of Chemistry" - }, - { - "author_name": "Peng-Hsun Chase Chen", - "author_inst": "Texas AM University, Department of Chemistry" - }, - { - "author_name": "Jing Xiao", - "author_inst": "Texas AM University, Department of Chemistry" - }, - { - "author_name": "Lauren R Blankenship", - "author_inst": "Texas AM University, Department of Chemistry" + "author_name": "Francesca Curreli", + "author_inst": "New York Blood Center" }, { - "author_name": "Xinyu R Ma", - "author_inst": "Texas AM University, Department of Chemistry" + "author_name": "Kent Chau", + "author_inst": "SRI Biosciences (A division of SRI International)" }, { - "author_name": "Erol Can Vatansever", - "author_inst": "Texas AM University, Department of Chemistry" + "author_name": "Thanh-Thuy Tran", + "author_inst": "SRI Biosciences (A division of SRI International)" }, { - "author_name": "Chia-Chuan Cho", - "author_inst": "Texas AM University, Department of Chemistry" + "author_name": "Isabella Nicolau", + "author_inst": "New York Blood Center" }, { - "author_name": "Yuying Ma", - "author_inst": "Texas AM University, Department of Chemistry" + "author_name": "Shahad Ahmed", + "author_inst": "New York Blood Center" }, { - "author_name": "Robert Allen", - "author_inst": "Sorrento Therapeutics" + "author_name": "Pujita Das", + "author_inst": "New York Blood Center" }, { - "author_name": "Henry Ji", - "author_inst": "Sorrento Therapeutics" + "author_name": "Christopher D Hillyer", + "author_inst": "New York Blood Center" }, { - "author_name": "Shiqing Xu", - "author_inst": "Texas AM University" + "author_name": "Mary Premenko-Lanier", + "author_inst": "SRI Biosciences (A division of SRI International)" }, { - "author_name": "Wenshe R Liu", - "author_inst": "Texas AM Drug Discovery Laboratory, Department of Chemistry, Texas AM University" + "author_name": "Asim K Debnath", + "author_inst": "New York Blood Center" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2023.01.17.524472", @@ -153620,23 +153439,23 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2023.01.12.23284481", - "rel_title": "Data-driven Targeting of COVID-19 Vaccination Programs: An Analysis of the Evidence on Impact, Implementation, Ethics and Equity", + "rel_doi": "10.1101/2023.01.13.23284524", + "rel_title": "The COVID-19 antibody responses, isotypes and glycosylation: Why SARS-CoV-2 Spike protein complex binding of IgG3 is potentiated in some and immuno-pathologies manifest.", "rel_date": "2023-01-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.12.23284481", - "rel_abs": "The data-driven targeting of COVID-19 vaccination programs is a major determinant of the ongoing toll of COVID-19. Targeting of access to, outreach about and incentives for vaccination can reduce total deaths by 20-50 percent relative to a first-come-first-served allocation. This piece performs a systematic review of the modeling literature on the relative benefits of targeting different groups for vaccination and evaluates the broader scholarly evidence - including analyses of real-world challenges around implementation, equity, and other ethical considerations - to guide vaccination targeting strategies. Three-quarters of the modeling studies reviewed concluded that the most effective way to save lives, reduce hospitalizations and mitigate the ongoing toll of COVID-19 is to target vaccination program resources to high-risk people directly rather than reducing transmission by targeting low-risk people. There is compelling evidence that defining vulnerability based on a combination of age, occupation, underlying medical conditions and geographic location is more effective than targeting based on age alone. Incorporating measures of economic vulnerability into the prioritization scheme not only reduces mortality but also improves equity. The data-driven targeting of COVID-19 vaccination program resources benefits everyone by efficiently mitigating the worst effects of the pandemic until the threat of COVID-19 has passed.", + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.13.23284524", + "rel_abs": "COVID-19 syndrome does not occur in all who are infected with SARS-CoV-2, and symptoms vary. The anti-SARS CoV-2 Spike immune responses is confounded by the Spike proteins ability to bind Ig{gamma}3 heavy chains. This appears to be via sialic acid glycans found on the O-Linked glycosylation moieties of this heavy chain extended neck domain. Furthermore glycosylation of light chains, particularly Kappa ({kappa}), is an associated feature of antibodies binding to SARS-CoV-2 antigens nucleocapsid and Spike protein. COVID-19 recovered patients had increased IgG1 and IgM levels and un-glycosylated {kappa} light chains; possibly In order to counter this immune system subjugation of IgG3. These molecular finding, together with our previous finding that Spike protein binds glycated human serum albumin (HSA), may explain the micro-vascular inflammatory clots that are a causative feature of COVID-19 acute respiratory syndrome (ARDS).\n\nThe postulated molecular sequelae are that SARS-CoV-2 virion, entering the blood circulation, being coated with IgG3 and glycated HSA forms a colloid and deposits into micro-focal clots which are also inflammatory. It is not that all IgG3 and albumin is being bound by the virus; this depends on the affinity the SARS-CoV2 virion has for binding an individuals IgG3 and albumin due to glycosylation and glycation status. The degree of glycosylation and terminal sialyation of an individuals antibodies is both a genetic and age-maturity dependant feature of the immune system. The degree of HSA glycation is also age related feature particularly related to type 2 diabetes. Thereby establishing the molecular basis of the association of severe COVID-19 disease syndrome and deaths with diabetes, metabolic disorders, and old age. Furthermore, already having cardiovascular disease, with hardened arteries, SARS-CoV2-glycated HSA-IgG3 deposition is going to exacerbate an already compromised circulatory physiology. The binding of IgG3 might also drives a shift in the immune repertoire response to SAR-CoV-2 anti-spike antibodies of increased IgG1 and prolonged IgM levels. This may be associated with Long Covid.\n\nIn summary, SARS-CoV-2 Spike protein binding of IgG3, via sialic acid glycan residues, along with increased glycosylated {kappa}-light chains and glycated-HSA may form a focal amyloid-like precipitate within blood vessels which in turn leads to the inflammatory micro-thrombosis characteristic of COVID-19 immuno-pathology.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Zoe M McLaren", - "author_inst": "University of Maryland Baltimore County" + "author_name": "Raymond Kruse Iles", + "author_inst": "MAP Sciences" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2023.01.13.23284515", @@ -155354,95 +155173,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.01.11.23284427", - "rel_title": "Genetic determinants of severe COVID-19 in young Asian and Middle Eastern patients", + "rel_doi": "10.1101/2023.01.03.22277971", + "rel_title": "Impact of COVID-19 pandemic on cancer screening in Denmark: A register-based study", "rel_date": "2023-01-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.11.23284427", - "rel_abs": "Studies of genetic factors associated with severe COVID-19 in young adults have been limited in non-Caucasian populations. Here, we use whole exome sequencing to characterize the genetic landscape of severe COVID-19 in a well phenotyped cohort of otherwise healthy, young adults (N=55; mean age 34.1 {+/-} SD 5.0 years) representing 16 countries in Asia, the Middle East, and North Africa. Our findings show enrichment of rare, likely deleterious missense and truncating variants in interferon-mediated and bacterial infection-susceptibility genes, when compared to control, mildly affected, or asymptomatic COVID-19 patients (N = 25), or to general populations representing Asia and the Middle East. Genetic variants tended to associate with mortality, intensive care admission, and ventilation support. Our findings confirm the association of interferon pathway genes with severe COVID-19 and highlight the importance of extending genetic studies to diverse populations given implications for pan-ethnic therapeutic and genetic screening options.\n\nAuthor SummaryBased on the hypothesis that rare monogenic variants contribute to the severity of SARS-CoV-2 infection outcomes, we performed whole exome sequencing in young, previously healthy patients with severe COVID-19 of Asian or Middle Eastern origins. We found an enrichment of rare missense and truncating variants in immune-related genes, mainly associated with interferon pathways and susceptibility to bacterial infections, which can be therapeutic targets. Genetic findings tended to correlate with mortality, intensive care unit (ICU) admission, high dependency unit (HDU) admission, and invasive ventilation.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.03.22277971", + "rel_abs": "BackgroundDenmark was one of the few countries where it was politically decided to continue cancer screening during the COVID-19 pandemic. We assessed the actual population uptake of mammography and cervical screening during this period.\n\nMethodsThe first COVID-19 lockdown in Denmark was announced on 11 March 2020. To investigate possible changes in cancer screening activity due to the COVID-19 pandemic, we analysed data from the beginning of 2017 until the end of 2021, searching for trends and outliers in the activity throughout this period, particularly after the first lockdown. Data on mammography screening and cervical screening were retrieved from governmental pandemic-specific monitoring of health care activities.\n\nResultsA brief drop was seen in screening activity right after the first COVID-19 lockdown, but the activity quickly returned to its previous level. A short-term deficit of 43% [-49 to -37] was found for mammography screening. A short-term deficit of 62% [-65 to -58] was found for cervical screening. Furthermore, a slight, statistically significant downward trend in cervical screening from 2018 to 2021 was probably unrelated to the pandemic. Other changes, e.g. a marked drop in mammography screening towards the end of 2021, also seem unrelated to the pandemic.\n\nConclusionsThe policy in Denmark of continuing cancer screening during the pandemic was implemented very effectively.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Beshr Badla", - "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences Hamdan Bin Mohammed College of Dental Medicine" - }, - { - "author_name": "Mohamed Hanifa", - "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences" - }, - { - "author_name": "Ruchi Jain", - "author_inst": "Al Jalila Children's Specialty Hospital" - }, - { - "author_name": "Maha El Naofal", - "author_inst": "Al Jalila Children's Specialty Hospital" - }, - { - "author_name": "Nour Halabi", - "author_inst": "Al Jalila Children's Specialty Hospital" - }, - { - "author_name": "Sawsan Yaslam", - "author_inst": "Al Jalila Children's Specialty Hospital" - }, - { - "author_name": "Sathishkumar Ramaswamy", - "author_inst": "Al Jalila Children's Specialty Hospital" - }, - { - "author_name": "Alan Taylor", - "author_inst": "Al Jalila Children's Specialty Hospital" - }, - { - "author_name": "Roudha Al Falasi", - "author_inst": "Al Jalila Children's Specialty Hospital" - }, - { - "author_name": "Shruti Shenbagam", - "author_inst": "Al Jalila Children's Specialty Hospital" - }, - { - "author_name": "Hamda Khansaheb", - "author_inst": "Dubai Health Authority" - }, - { - "author_name": "Hanan Al Suwaidi", - "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences" - }, - { - "author_name": "Norbert Nowotny", - "author_inst": "University of Veterinary Medicine Vienna: Veterinarmedizinische Universitat Wien" - }, - { - "author_name": "Rizwana Popatia", - "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences" + "author_name": "Mette Hartmann Nonboe", + "author_inst": "Nyk\u00f8bing F. Hospital" }, { - "author_name": "Alawi Alsheikh-Ali", - "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences Hamdan Bin Mohammed College of Dental Medicine" + "author_name": "George Napolitano", + "author_inst": "University of Copenhagen" }, { - "author_name": "Abdulla Al Khayat", - "author_inst": "Al Jalila Children's Specialty Hospital" + "author_name": "Jeppe Bennekou Schroll", + "author_inst": "Copenhagen University Hospital" }, { - "author_name": "Tom Loney", - "author_inst": "Mohammed Bin Rashid University of Medicine and Health Sciences" + "author_name": "Ilse Vejborg", + "author_inst": "Copenhagen University Hospital" }, { - "author_name": "Laila Al Dabal", - "author_inst": "Dubai Health Authority" + "author_name": "Marianne Waldstroem", + "author_inst": "Department of Pathology, Lillebaelt Hospital, Denmark and Department of Regional Health Research, University of Southern Denmark, Denmark" }, { - "author_name": "Ahamd N Abou Tayoun", - "author_inst": "Al Jalila Children's Specialty Hospital" + "author_name": "Elsebeth Lynge", + "author_inst": "Nyk\u00f8bing F. Hospital" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.01.10.523356", @@ -157128,75 +156895,31 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2023.01.05.23284247", - "rel_title": "Identification of differences in the magnitude and specificity of SARS-CoV-2 nucleocapsid antibody responses in naturally infected and vaccinated individuals", + "rel_doi": "10.1101/2023.01.06.23284283", + "rel_title": "Impact of the COVID-19 pandemic on food safety inspection outcomes in Toronto, Canada: a Bayesian interrupted time series analysis", "rel_date": "2023-01-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.05.23284247", - "rel_abs": "BackgroundAs there are limited data on B cell epitopes for the nucleocapsid protein in SARS-CoV-2, we sought to identify the immunodominant regions within the N protein, recognized by patients with varying severity of natural infection with the Wuhan strain (WT), delta, omicron and in those who received the Sinopharm vaccines, which is an inactivated, whole virus vaccine.\n\nMethodsUsing overlapping peptides representing the N protein, with an in-house ELISA, we mapped the immunodominant regions within the N protein, in seronegative (n=30), WT infected (n=30), delta infected (n=30), omicron infected+vaccinated (n=20) and Sinopharm (BBIBP-CorV) vaccinees (n=30). We then investigated the sensitivity and specificity of these immunodominant regions and analysed their conservation with other SARS-CoV-2 variants of concern, seasonal human coronaviruses and bat Sarbecoviruses. We then investigated the kinetics of responses to these regions in those with varying severity of acute COVID-19.\n\nResultsWe identified four immunodominant regions aa 29-52, aa 155-178, aa 274 to 297 and aa 365 to 388, were highly conserved within SARS-CoV-2 and the bat coronaviruses. The magnitude of responses to these regions varied based on the infecting SARS-CoV-2 variants, with WT infected individuals predominantly recognizing aa155 to 178 regions, delta infected individuals and vaccinated+omicron infected individuals predominantly recognizing regions aa 29 to 52 and aa 274 to 294 regions. Sinopharm vaccinees recognized all four regions, with the magnitude of responses significantly lower than other groups. >80% of individuals gave responses above the positive cut-off threshold to many of the four regions, with some differences with individuals who were infected with different VoCs. These regions were found to be 100% specific, as none of the seronegative individuals gave any responses.\n\nConclusionsN-protein specific responses appear to be detectable in over 90% of those who were naturally infected or vaccinated with a whole virus inactivated vaccine, with responses mainly directed against four regions of the protein, which were highly conserved. As these regions were highly specific with high sensitivity, they have a potential to be used to develop diagnostic assays and to be used in development of vaccines.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.06.23284283", + "rel_abs": "The coronavirus disease (COVID-19) pandemic resulted in major disruptions to the food service industry and regulatory food inspections. The objective of this study was to conduct an interrupted time series analysis to investigate the impact of the COVID-19 pandemic on food safety inspection trends in Toronto, Canada. Inspection data for restaurants and take-out establishments were obtained from 2017 to 2022 and ordered as a weekly time series. Bayesian segmented regression was conducted to evaluate the impact of the pandemic on weekly infraction and inspection pass rates. On average, a 0.31-point lower weekly infraction rate (95% credible interval [CI]: 0.23, 0.40) and a 2.0% higher probability of passing inspections (95% CI: 1.1%, 3.0%) were predicted in the pandemic period compared to pre-pandemic. Models predicted lower infraction rates and higher pass rates immediately following the pandemic that were regressing back toward pre-pandemic levels in 2022. Seasonal effects were also identified, with infraction rates highest in April and pass rates lowest in August. The COVID-19 pandemic resulted in an initial positive effect on food safety outcomes in restaurants and take-out food establishments in Toronto, but this effect appears to be temporary. Additional research is needed on seasonal and long-term inspection trends post-pandemic.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Pradeep D Pushpakumara", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Chandima Jeewandara", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Farha Bary", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Deshan Madushanka", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Lahiru Perera", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Inoka S Aberathna", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Thashmi Nimasha", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Jeewantha Jayamali", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Thushali Ranasinghe", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Heshan Kuruppu", - "author_inst": "University of Sri Jayewardenepura Faculty of Medical Sciences" - }, - { - "author_name": "Saubhagya Danasekara", - "author_inst": "University of Sri Jayewardenepura" - }, - { - "author_name": "Ananda Wijewickrama", - "author_inst": "National Institute of infectious diseases" + "author_name": "Ian Young", + "author_inst": "Toronto Metropolitan University" }, { - "author_name": "Graham Ogg", - "author_inst": "University of Oxford" + "author_name": "Binyam N Desta", + "author_inst": "Toronto Metropolitan University" }, { - "author_name": "Gathsaurie Neelika Malavige", - "author_inst": "University of Sri Jayewardenepura" + "author_name": "Fatih Sekercioglu", + "author_inst": "Toronto Metropolitan University" } ], "version": "1", "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2023.01.07.23284291", @@ -159394,53 +159117,125 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2023.01.02.23284120", - "rel_title": "The time between vaccination and infection impacts immunity against SARS-CoV-2 variants", + "rel_doi": "10.1101/2023.01.03.23284130", + "rel_title": "A Phase 2/3 observer-blind, randomized, controlled study to determine the safety and immunogenicity of SARS-CoV-2 recombinant spike protein vaccine in Indian children and adolescents aged 2 to 17 years", "rel_date": "2023-01-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.02.23284120", - "rel_abs": "As the COVID-19 pandemic continues, long-term immunity against SARS-CoV-2 will be globally important. Official weekly cases have not dropped below 2 million since September of 2020, and continued emergence of novel variants have created a moving target for our immune systems and public health alike. The temporal aspects of COVID-19 immunity, particularly from repeated vaccination and infection, are less well understood than short-term vaccine efficacy. In this study, we explore the impact of combined vaccination and infection, also known as hybrid immunity, and the timing thereof on the quality and quantity of antibodies produced by a cohort of 96 health care workers. We find robust neutralizing antibody responses among those with hybrid immunity against all variants, including Omicron BA.2, and we further found significantly improved neutralizing titers with longer vaccine-infection intervals up to 400 days. These results indicate that anti-SARS-CoV-2 antibody responses undergo continual maturation following primary exposure by either vaccination or infection for at least 400 days after last antigen exposure. We show that neutralizing antibody responses improved upon secondary boosting with greater impact seen after extended intervals. Our findings may also extend to booster vaccine doses, a critical consideration in future vaccine campaign strategies.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2023.01.03.23284130", + "rel_abs": "BackgroundA recombinant, adjuvanted COVID-19 vaccine, SII-NVX-CoV2373 was manufactured in India and evaluated in Indian children and adolescents to assess safety and immunogenicity.\n\nMethodsThis was a Phase 2/3 observer-blind, randomized, controlled immuno-bridging study in children and adolescents aged 2 to 17 years. Participants were randomly assigned in 3:1 ratio to receive two doses of SII-NVX-CoV2373 or placebo on day 1 and day 22. Solicited adverse events (AEs) were collected for 7 days after each vaccination. Unsolicited AEs were collected for 35 days following first dose and serious AEs (SAEs) and adverse events of special interest (AESI) were collected throughout the study. Anti S IgG and neutralizing antibodies against the SARS-CoV-2 were measured at baseline, day 22, day 36 and day 180. Variant immune responses were assessed in a subset of participants at baseline, day 36 and day 180. Primary objectives were to demonstrate non-inferiority of SII-NVX-CoV2373 in each pediatric age group (12 to 17 years and 2 to 11 years, separately) to that in adults in terms of ratio of titers of both anti-S IgG and neutralizing antibodies 14 days after the second dose (day 36). Non-inferiority was to be concluded if the lower bound of 95% CI of the ratio was >0.67.\n\nResultsA total of 920 children and adolescents (460 in each age cohort; 12 to 17 years and 2 to 11 years) were randomized and vaccinated. The demographic and baseline characteristics between the two groups were comparable in both age groups. After the second dose, there were more than 100-fold rise in anti-S IgG GMEUs and more than 84-fold rise in neutralizing antibodies GMTs from baseline in the participants who received SII-NVX-CoV2373. The lower bound of 95% CI of GMT ratios for anti-S IgG GMEUs and neutralizing antibodies in both age groups to those observed in Indian adults were >0.67, thus non-inferiority was met [Anti-S IgG GMT ratios 1.52 (1.38, 1.67), 1.20 (1.08, 1.34) and neutralizing antibodies GMT ratios 1.93 (1.70, 2.18), 1.33 (1.17, 1.50) for 2 to 11 years and 12 to 17 years groups, respectively]. The seroconversion rate was [≥] 98% (anti-S IgG) and [≥] 97.9 % (neutralizing antibodies) in both age groups, respectively. Similar findings were seen in the baseline seronegative participants. SII-NVX-CoV2373 also showed robust responses against various variants of concern. Injection site pain, tenderness, swelling, erythema and fever, headache, malaise, fatigue, were the common ([≥]5%) solicited adverse events which were transient and resolved without any sequelae. Throughout the study, only two causally unrelated SAEs and no AESI were reported.\n\nConclusionSII-NVX-CoV2373 has been found safe and well tolerated in children and adolescents of 2 to 17 years. The vaccine was highly immunogenic and the immune response was non-inferior to that in adults.\n\nRegistration - CTRI No. CTRI/2021/02/031554", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Timothy A. Bates", - "author_inst": "Oregon Health & Science University" + "author_name": "Bhagwat Gunale", + "author_inst": "Serum Institute of India Pvt Ltd" }, { - "author_name": "Hans C. Leier", - "author_inst": "Oregon Health & Science University" + "author_name": "Dhananjay Kapse", + "author_inst": "Serum Institute of India Pvt Ltd., Pune India" }, { - "author_name": "Savannah K. McBride", - "author_inst": "Oregon Health & Science University" + "author_name": "Sonali Kar", + "author_inst": "Kalinga Institute of Medical Sciences, Bhubaneswar, Odisha, India" }, { - "author_name": "Devin Schoen", - "author_inst": "Oregon Health & Science University" + "author_name": "Ashish Bavdekar", + "author_inst": "KEM Hospital Research Centre, Pune, Maharashtra, India" }, { - "author_name": "Zoe L. Lyski", - "author_inst": "Oregon Health & Science University" + "author_name": "Sunil Kohli", + "author_inst": "Hamdard Institute of Medical Sciences and Research with Centre for health Research and Development (CHRD), New Delhi, India" }, { - "author_name": "David X. Lee", - "author_inst": "Oregon Health & Science University" + "author_name": "Sanjay Lalwani", + "author_inst": "Bharati Vidyapeeth Deemed University Medical College and Hospital, Pune, Maharashtra, India" }, { - "author_name": "William B. Messer", - "author_inst": "Immunology, Oregon Health & Science University" + "author_name": "Sushant Meshram", + "author_inst": "Super Speciality Hospital, Government Medical College and Hospital, Nagpur, Maharashtra, India" }, { - "author_name": "Marcel E. Curlin", - "author_inst": "Oregon Health & Science University" + "author_name": "Abhishek Raut", + "author_inst": "Sushila Nayar School of Public Health, Mahatma Gandhi Institute of Medical Sciences, Wardha, Maharashtra, India" }, { - "author_name": "Fikadu G. Tafesse", - "author_inst": "Oregon Health & Science University" + "author_name": "Praveen Kulkarni", + "author_inst": "JSS Academy of Higher Education and Research, Mysore, Karnataka, India" + }, + { + "author_name": "Clarence Samuel", + "author_inst": "Christian Medical College & Hospital, Ludhiana, Punjab, India" + }, + { + "author_name": "Renuka Munshi", + "author_inst": "TN Medical College & BYL Nair Hospital, Mumbai, Maharashtra, India" + }, + { + "author_name": "Madhu Gupta", + "author_inst": "Post Graduate Institute of Medical Education and Research, Chandigarh, India" + }, + { + "author_name": "Joyce S Plested", + "author_inst": "Novavax, Inc. 21 Firstfield Road, Gaithersburg, MD 20878, USA" + }, + { + "author_name": "Shane Cloney-Clarke", + "author_inst": "Novavax, Inc. 21 Firstfield Road, Gaithersburg, MD 20878, USA" + }, + { + "author_name": "MingZhu Zhu", + "author_inst": "Novavax, Inc. 21 Firstfield Road, Gaithersburg, MD 20878, USA" + }, + { + "author_name": "Melinda Pryor", + "author_inst": "360biolabs Pty Ltd, Melbourne, 3004, Victoria, Australia," + }, + { + "author_name": "Stephanie Hamilton", + "author_inst": "360biolabs Pty Ltd, Melbourne, 3004, Victoria, Australia" + }, + { + "author_name": "Madhuri Thakar", + "author_inst": "Indian Council of Medical Research, National AIDS Research Institute, Pune, India" + }, + { + "author_name": "Ashwini Shete", + "author_inst": "Indian Council of Medical Research, National AIDS Research Institute, Pune, India" + }, + { + "author_name": "Abhijeet Dharmadhikari", + "author_inst": "Serum Institute of India Pvt Ltd., Pune India" + }, + { + "author_name": "Chetanraj Bhamare", + "author_inst": "Serum Institute of India Pvt Ltd., Pune India" + }, + { + "author_name": "Umesh Shaligram", + "author_inst": "Serum Institute of India Pvt Ltd., Pune India" + }, + { + "author_name": "Cyrus S Poonawalla", + "author_inst": "Serum Institute of India Pvt Ltd., Pune India" + }, + { + "author_name": "Raburn M. Mallory", + "author_inst": "Novavax, Inc. 21 Firstfield Road, Gaithersburg, MD 20878, USA" + }, + { + "author_name": "Gregory M. Glenn", + "author_inst": "Novavax, Inc. 21 Firstfield Road, Gaithersburg, MD 20878, USA" + }, + { + "author_name": "Prasad S. Kulkarni", + "author_inst": "Serum Institute of India Pvt Ltd., Pune India" + }, + { + "author_name": "- COVOVAX-Ped Study Group", + "author_inst": "-" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -161212,65 +161007,57 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.12.27.22283698", - "rel_title": "Safety and Effectiveness of SA58 Nasal Spray against COVID-19 Infection in Medical Personnel\uff1aAn Open-label, Blank-controlled Study", - "rel_date": "2022-12-31", + "rel_doi": "10.1101/2022.12.28.22283986", + "rel_title": "Cost-effectiveness of the second COVID-19 booster vaccination in the United States", + "rel_date": "2022-12-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.27.22283698", - "rel_abs": "Approved COVID-19 vaccines to date have limited effectiveness in protecting infection and blocking transmission. A nasal spray of broad-spectrum antibody against COVID-19 (SA58 Nasal Spray) has recently been developed by Sinovac Life Sciences Co., Ltd.. From October 31 to November 30, 2022, an open-label, blank controlled study on the SA58 Nasal Spray against COVID-19 infection was conducted with the medical personnel working in the designated COVID-19 hospitals and Fangcang shelter hospitals (alternate care sites) of COVID-19 cases in Hohhot city, the Inner Mongolia Autonomous Region. A total of 6662 medical personnel were involved in this study: 3368 used SA58 Nasal Spray from the drug group, and 3294 not used from blank control group. The medication was self-administered intranasally 1[~]2 times per day with an interval of 6 hours for 30 days.. The safety results indicated that the SA58 Nasal Spray was well tolerant. The incidence of adverse events (AEs) was 28.6% (497/1736), and the majority of the AEs were mild and from administrative site. 135 COVID-19 cases were identified for SARS-CoV-2 by RT-PCR during the 30-day observation. The cumulative incidence of COVID-19 in the drug group and the control group were 0.026% and 0.116%, respectively. The effectiveness of the SA58 Nasal Spray for preventing COVID-19 infection among medical personnel was evaluated as 77.7% (95% CI: 52.2% - 89.6%). In conclusion, the SA58 Nasal Spray is well-tolerant and highly effective against COVID-19 infection.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.28.22283986", + "rel_abs": "BackgroundThe United States (US) authorized the second COVID-19 booster for individuals aged 50+ years on March 29, 2022. To date, the cost-effectiveness of the second booster strategy remains unassessed.\n\nMethodsWe developed a decision-analytic SEIR-Markov model by five age groups (0-4yrs, 5-11yrs 12-17yrs, 18-49yrs, and 50+yrs) and calibrated the model by actual mortality in each age group in the US. We conducted fives scenarios to evaluate the cost-effectiveness of the second booster strategy and incremental benefits if the strategy would expand to 18-49yrs and 12-17yrs, from a healthcare system perspective.\n\nFindingsImplementing the second booster strategy for those aged 50+yrs would cost $807 million but reduce direct medical costs by $1,128 million, corresponding to a benefit-cost ratio of 1.40. Moreover, the strategy would also result in a gain of 1,048 quality-adjusted life-years (QALYs) during the 180 days, indicating it was cost-saving. Further, vaccinating individuals aged 18-49yrs with the second booster would result in an additional gain of $1,566 million and 2,276 QALYs. Similarly, expanding vaccination to individuals aged 12-17yrs would result in an additional gain of $15 million and 89 QALYs. However, if social interaction between all age groups was severed, vaccination expansion to 18-49yrs and 12-17yrs would no longer be cost-effective.\n\nInterpretationThe second booster strategy was likely to be cost-effective in reducing the disease burden of the COVID-19 pandemic. Expanding the second booster strategy to 18-49yrs and 12-17yrs would remain cost-effective due to their social contacts with the older age group.\n\nFundingWorld Health Organization", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Shujie Si", - "author_inst": "Inner Mongolia Fourth Hospital" - }, - { - "author_name": "Canrui Jin", - "author_inst": "Sinovac Biotech Co., Ltd." - }, - { - "author_name": "Yunlong Richard Cao", - "author_inst": "Peking University" + "author_name": "Rui Li", + "author_inst": "Xi'an Jiaotong University" }, { - "author_name": "Jianping Li", - "author_inst": "Sinovac Biotech Co., Ltd." + "author_name": "Pengyi Lu", + "author_inst": "Xi'an Jiaotong University" }, { - "author_name": "Biao Kan", - "author_inst": "Chinese Center for Disease Control and Prevention" + "author_name": "Christopher K Fairley", + "author_inst": "Xi'an Jiaotong University" }, { - "author_name": "Feng Xue", - "author_inst": "Sinovac Life Sciences Co., Ltd." + "author_name": "Jos\u00e9 A. Pag\u00e1n", + "author_inst": "New York University" }, { - "author_name": "Xiaoliang Sunny Xie", - "author_inst": "Peking University" + "author_name": "Wenyi Hu", + "author_inst": "The University of Melbourne" }, { - "author_name": "Liang Fang", - "author_inst": "Sinovac Biotech Co., Ltd." + "author_name": "Qianqian Yang", + "author_inst": "Xi'an Jiaotong University" }, { - "author_name": "Gang Zeng", - "author_inst": "Sinovac Biotech Co., Ltd." + "author_name": "Guihua Zhuang", + "author_inst": "Xi'an Jiaotong University" }, { - "author_name": "Shuo Zhang", - "author_inst": "Inner Mongolia Blood Center" + "author_name": "Mingwang Shen", + "author_inst": "Xi'an Jiaotong University" }, { - "author_name": "Yaling Hu", - "author_inst": "Sinovac Life Sciences Co., Ltd." + "author_name": "Yan Li", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Xiaoping Dong", - "author_inst": "Chinese Center for Disease Control and Prevention" + "author_name": "Lei Zhang", + "author_inst": "Xi'an Jiaotong University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -162942,21 +162729,57 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2022.12.24.22283835", - "rel_title": "Literature analysis of the efficacy of COVID-19 vaccinations", + "rel_doi": "10.1101/2022.12.25.22283940", + "rel_title": "Clinical Virology and Effect of Vaccination and Monoclonal Antibodies against SARS-CoV-2 Omicron Sub variant BF.7 (BA.5.2.1.7) : A systematic review", "rel_date": "2022-12-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.24.22283835", - "rel_abs": "The COVID-19 pandemic is the largest epidemic of the 21st century so far. Over 650 million people have already been infected with the SARS-CoV-2 virus. One of the ways to stop this pandemic, is to vaccinate the population and gain herd immunity. Many different vaccines are being used around the world, with differing efficacy. This review summarizes the 79 publications on the efficacy of the currently existing COVID-19 vaccines. It shows that there are eleven vaccines that have efficacy data published in a PubMed-indexed scientific journal. Most research has been done on the Pfizer/BioNTech BNT162B2 vaccine, and the eleven vaccines generally have a high efficacy in preventing illness. The Pfizer (86%-100%), Moderna (93.2%-94.1%), Sputnik-V (91.6%) and Novavax ([~]90%) vaccines show the highest efficacy, followed by the Sinovac (83.5%), QazCovid-in 82%) and Covaxin (77.8%) vaccines. The Oxford/AstraZeneca (69% - 81.5%) and Johnson & Johnson (66%) vaccines have lower efficacy in preventing illness. This overview also shows efficacies other than in preventing illness (e.g. asymptomatic, severe illness, hospitalization, death) in some cases. The results also show that the vaccines have specific effects on specific age groups (e.g. adolescents, adults, elderly) and people with diseases (e.g. leukemia, other cancers, HIV). Future research in this area will mostly focus on vaccine efficacy on specific strains of the SARS-CoV-2 virus (such as the Omicron variant) as well as the efficacy of booster vaccinations.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.25.22283940", + "rel_abs": "Since its identification, the novel coronavirus \"severe acute respiratory syndrome coronavirus 2 \"(SARS-CoV-2) In in late 2019 AT Wuhan, China, by the World Health Organization (WHO), which cause the coronavirus disease 2019, is rapidly spreading, resulting in the global pandemic. As of 19 December 2022, more than 64 million confirmed cases and 6,645,812 deaths have been reported across the world. Over time, the SARS-CoV-2 acquired genetic mutations resulting in multiple types of SARS-CoV-2 variants and subvariants that have been confirmed. The Omicron (B.1.1.529) variant was identified later in November 2021, with enhanced immune escape and was followed with various sublineages due to mutations in the spike protein of the SARS-CoV-2. However, rapid resurge in COVID-19 reports by Omicron subvariant BF.7(BA.2.75.2) in China and other countries, alarming global threat. The present systematic review was conducted using the MeSH terms and keywords \"Omicron\" AND \"BA.5.2.1.7\" OR \"BF.7\" in Pub Med, Google Scholar and MedRXiv database and grey literature from the authentic database and websites. We identified a total of 14 eligible studies. We have reviewed all the eligible available studies to understand the viral mutations, and factors associated with the increase in the reports of COVID-19 cases in China and across the world and to evaluate the effectiveness of vaccination and monoclonal antibodies against the BF.7 variant.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Tim Hulsen", - "author_inst": "Philips Research" + "author_name": "SANTENNA CHENCHULA", + "author_inst": "AIIMS,Bhopal" + }, + { + "author_name": "Krishna Chaitanya Amerneni Jr.", + "author_inst": "Western Michigan University, Kalamazoo" + }, + { + "author_name": "Mohan Krishna Ghanta Sr.", + "author_inst": "MVJ Medical College and Research Hospital, Bangalore, Karnataka" + }, + { + "author_name": "Padmavathi R Jr.", + "author_inst": "SVS Medical College Mahboobnagar,Telangana, India" + }, + { + "author_name": "Madhu Bhargavi Chandra Jr.", + "author_inst": "All India Institute of Medical sciences, Bhopal" + }, + { + "author_name": "Madhu Babu Adusumilli Jr.", + "author_inst": "All India Institute of Medical sciences, Bhopal" + }, + { + "author_name": "Sofia Mudda Sr.", + "author_inst": "All India Institute of Medical sciences, Bhopal" + }, + { + "author_name": "Madhavrao Chavan Sr.", + "author_inst": "All India Institute of Medical Sciences (AIIMS) Mangalagiri, Andhra Pradesh, India" + }, + { + "author_name": "Rupesh Gupta Sr.", + "author_inst": "Government Medical College, Shahdol, Madhyapradesh, India" + }, + { + "author_name": "Bhawna Lakhawat Jr.", + "author_inst": "All India Institute of Medical sciences, Bhopal" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -165120,23 +164943,27 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.12.22.22283830", - "rel_title": "To test or not to test? A new behavioral epidemiology framework for COVID-19", + "rel_doi": "10.1101/2022.12.21.22283809", + "rel_title": "Wastewater monitoring of SARS-CoV-2 RNA at K-12 schools: Comparison to pooled clinical testing data", "rel_date": "2022-12-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.22.22283830", - "rel_abs": "Recent clinical research finds that rapid transmission of SARS-CoV-2 is facilitated by substantial undocumented asymptomatic infections. Asymptomatic infections have implications for behavioral response to voluntary testing. The paper argues that a substantial proportion of SARS-CoV-2 infections are hidden due to rational test avoidance behavior, especially among those without perceptible disease symptoms. However, if perception of disease threat is prevalence dependent, testing compliance increases in response to reported infection prevalence rate in the population. This behavior, in turn, affects infection and mortality dynamics. This paper proposes an analytical framework that explicitly incorporates prevalence-dependent testing behavior in a standard epidemiological model, generating distinctive equilibrium epidemiological outcomes with significant policy implications. Numerical simulations show that failure to consider endogenous testing behavior among asymptomatic individuals leads to over- and underestimation of infection rates at the peaks and troughs, respectively, thereby distorting the disease containment policies. The results underscore the importance of augmenting testing capacity as an effective mitigation policy for COVID-19 and similar infectious diseases.\n\nJEL CodesI12, I18", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.21.22283809", + "rel_abs": "BackgroundWastewater measurements of SARS-CoV-2 RNA have been extensively used to supplement clinical data on COVID-19. Most examples in the literature that describe wastewater monitoring for SARS-CoV-2 RNA use samples from wastewater treatment plants and individual buildings that serve as the primary residence of community members. However, wastewater surveillance can be an attractive supplement to clinical testing in K-12 schools where individuals only spend a portion of their time but interact with others in close proximity, increasing risk of potential transmission of disease.\n\nMethodsWastewater samples were collected from two K-12 schools in California and divided into solid and liquid fractions to be processed for detection of SARS-CoV-2. The resulting detection rate in each wastewater fraction was compared to each other and the detection rate in pooled clinical specimens.\n\nResultsMost wastewater samples were positive for SARS-CoV-2 RNA when clinical testing was positive (75% for solid samples and 100% for liquid samples). Wastewater samples continued to test positive for SARS-CoV-2 RNA when clinical testing was negative or in absence of clinical testing (83% for both solid and liquid samples), indicating presence of infected individuals in the schools. Wastewater solids had a higher concentration of SARS-CoV-2 than wastewater liquids on an equivalent mass basis by three orders of magnitude.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Jayanta Sarkar", - "author_inst": "Queensland University of Technology" + "author_name": "Sooyeol Kim", + "author_inst": "Stanford University" + }, + { + "author_name": "Alexandria Boehm", + "author_inst": "Stanford University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.12.22.22283841", @@ -166578,177 +166405,45 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2022.12.20.22282909", - "rel_title": "The onset of late severe lung impairment in COVID-19 is associated with high inflammation markers at admission and metabolic syndrome markers", + "rel_doi": "10.1101/2022.12.18.22281291", + "rel_title": "A prospective evaluation of three saliva qualitative antigen testing kits for the detection of SARS-CoV-2 in Japan", "rel_date": "2022-12-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.20.22282909", - "rel_abs": "BackgroundCOVID-19 severity is mainly related to lung impairment. However, preexisting patient characteristics and biomarkers at admission associated with this event are not precisely known.\n\nMethodsWe report 205 patients admitted for a proven COVID-19 in our institution between March 7 and April 22, 2020, particularly their comorbidities, respiratory severity, immune profile, and metabolic profile.\n\nFindingsMedian age was 70 years [interquartile range (IQR) 25-75: 60;79]; 115 (56{middle dot}1%) patients were men. Oxygen supplementation of >2L/min was required in 107 patients (52{middle dot}2%) after a median time of 8 days [IQR: 6;10] after the first symptoms; 67 (32{middle dot}7%) patients were admitted to the intensive care unit (ICU), almost exclusively due to severe hypoxia. Patients requiring >2L/min oxygen therapy and/or ICU admission were older and more frequently males, with a significantly higher body mass index (BMI), a significantly higher total cholesterol (TC) / HDL cholesterol ratio, and higher triglycerides. They also had higher plasma levels of C-reactive protein (CRP) and interleukin 6 (IL-6); IL-6 >20 ng/L and CRP >70 mg/L were significantly associated with ICU admission and/or (for patients with a decision of limitation of life-support therapy) death. Higher BMI and TC/HDL-c ratio were associated with higher CRP and IL-6 levels. Steroid therapy was performed in 61 patients; while its clinical impact was inconclusive due to heterogeneous situations, IL-6 levels decreased significantly more in these patients.\n\nInterpretationSevere COVID-19 mostly relates to late-onset pneumonia associated with preexisting metabolic syndrome markers and a surge in inflammatory markers, allowing the early identification of at-risk patients.\n\nFundingThis work was supported by Foundation University of Grenoble Alpes.", - "rel_num_authors": 40, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.18.22281291", + "rel_abs": "IntroductionRapid qualitative antigen testing has been widely used for the laboratory diagnosis of COVID-19 with nasopharyngeal samples. Saliva samples have been used as alternative samples, but the analytical performance of those samples for qualitative antigen testing has not been sufficiently evaluated.\n\nMethodsA prospective observational study evaluated the analytical performance of three In Vitro Diagnostics (IVD) approved COVID-19 rapid antigen detection kits for saliva between June 2022 and July 2022 in Japan using real-time reverse transcription polymerase chain reaction (RT-PCR) as a reference. A nasopharyngeal sample and a saliva sample were simultaneously obtained, and RT-PCR was performed.\n\nResultsIn total, saliva samples and nasopharyngeal samples were collected from 471 participants (140 RT-PCR-positive saliva samples and 143 RT-PCR-positive nasopharyngeal samples) for the analysis. The median Ct values were 25.5 (interquartile range [IQR]: 21.9-28.8) for saliva samples and 17.1 (IQR: 15.5-18.7) for nasopharyngeal samples (p<0.001). Compared with saliva samples of RT-PCR, the sensitivity and specificity were 46.4% and 99.7% for ImunoAce SARS-CoV-2 Saliva, 59.3% and 99.1% for Espline SARS-CoV-2 N, and 61.4% and 98.8% for QuickChaser Auto SARS-CoV-2, respectively. The sensitivity is >90% for saliva samples with a moderate-to-high viral load (Ct<25), whereas the sensitivity is <70% for high-viral-load nasopharyngeal samples (Ct<20).\n\nConclusionCOVID-19 rapid antigen detection kits with saliva showed high specificities, but the sensitivities varied among kits, and the analytical performance of saliva qualitative antigen detection kits was much worse than that of kits using nasopharyngeal samples.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Olivier EPAULARD", - "author_inst": "Infectious Diseases Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Audrey LE GOUELLEC", - "author_inst": "Univ. Grenoble Alpes, CNRS, CHU Grenoble Alpes, Grenoble INP*, TIMC-IMAG, Grenoble, France" - }, - { - "author_name": "Marion LE MARECHAL", - "author_inst": "Infectious Diseases Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Benjamin NEMOZ", - "author_inst": "Institut de Biologie Structurale, UMR 5075 CEA-CNRS-UGA, Grenoble, France" - }, - { - "author_name": "Anne Laure BOREL", - "author_inst": "Nutrition Department, Grenoble-Alpes University Hospital, Grenoble, France; Hypoxia pathophysiology laboratory INSERM U1042, Grenoble Alpes University" - }, - { - "author_name": "Anais DARTEVEL", - "author_inst": "Medical Intensive Care Unit, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Hubert GHEERBRANT", - "author_inst": "Pneumology Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Marie Christine HERAULT", - "author_inst": "Department of Anaesthesia and Intensive Care Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Annick BOSSERAY", - "author_inst": "Internal Medicine Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Giovanna CLAVARINO", - "author_inst": "Univ. Grenoble Alpes, CNRS, CHU Grenoble Alpes, Grenoble INP*, TIMC-IMAG, Grenoble, France" - }, - { - "author_name": "Julien LUPO", - "author_inst": "Institut de Biologie Structurale, UMR 5075 CEA-CNRS-UGA, Grenoble, France" - }, - { - "author_name": "Damien VIGLINO", - "author_inst": "Emergency Department, Grenoble-Alpes University Hospital, Grenoble, France; Hypoxia pathophysiology laboratory INSERM U1042, Grenoble Alpes University" - }, - { - "author_name": "Fanny QUENARD", - "author_inst": "Infectious Diseases Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Clara CANDILLE", - "author_inst": "Medical Intensive Care Unit, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Boubou CAMARA", - "author_inst": "Pneumology Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Michel DURAND", - "author_inst": "Department of Anaesthesia and Intensive Care Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Patrice FAURE", - "author_inst": "Biochemistry Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Dorra GUERGOUR", - "author_inst": "Biochemistry Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Elena CHIDLOVSKI", - "author_inst": "Internal Medicine Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Marie Christine JACOB", - "author_inst": "Immunology Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Sylvie LARRAT", - "author_inst": "Institut de Biologie Structurale, UMR 5075 CEA-CNRS-UGA, Grenoble, France" - }, - { - "author_name": "Marie FROIDURE", - "author_inst": "Infectious Diseases Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Nicolas TERZI", - "author_inst": "Medical Intensive Care Unit, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Sebastien QUETANT", - "author_inst": "Pneumology Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Jean Francois PAYEN", - "author_inst": "Department of Anaesthesia and Intensive Care Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Barbara COLOMBE", - "author_inst": "Internal Medicine Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Tatiana RASKOVALOVA", - "author_inst": "Immunology Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Patrice MORAND", - "author_inst": "Institut de Biologie Structurale, UMR 5075 CEA-CNRS-UGA, Grenoble, France" - }, - { - "author_name": "Isabelle PIERRE", - "author_inst": "Infectious Diseases Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Carole SCHWEBEL", - "author_inst": "Medical Intensive Care Unit, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Rebecca HAMIDFAR", - "author_inst": "Pneumology Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Laurence BOUILLET", - "author_inst": "Internal Medicine Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Jean Paul BRION", - "author_inst": "Infectious Diseases Department, Grenoble-Alpes University Hospital, Grenoble, France" - }, - { - "author_name": "Candice TROCME", - "author_inst": "Univ. Grenoble Alpes, CNRS, CHU Grenoble Alpes, Grenoble INP*, TIMC-IMAG, Grenoble, France" + "author_name": "Norihiko Terada", + "author_inst": "University of Tsukuba" }, { - "author_name": "Sylvie BERTHIER", - "author_inst": "Univ. Grenoble Alpes, CNRS, CHU Grenoble Alpes, Grenoble INP*, TIMC-IMAG, Grenoble, France" + "author_name": "Yusaku Akashi", + "author_inst": "Tsukuba Medical Center Hospital" }, { - "author_name": "Carole CHIRICA", - "author_inst": "Biochemistry Department, Grenoble-Alpes University Hospital, Grenoble, France" + "author_name": "Yuto Takeuchi", + "author_inst": "University of Tsukuba Hospital" }, { - "author_name": "Anne Laure MOUNAYAR", - "author_inst": "Infectious Diseases Department, Grenoble-Alpes University Hospital, Grenoble, France" + "author_name": "Atsuo Ueda", + "author_inst": "Tsukuba Medical Center Hospital" }, { - "author_name": "Myriam BLANC", - "author_inst": "Infectious Diseases Department, Grenoble-Alpes University Hospital, Grenoble, France" + "author_name": "Shigeyuki Notake", + "author_inst": "Tsukuba Medical Center Hospital" }, { - "author_name": "Patricia PAVESE", - "author_inst": "Infectious Diseases Department, Grenoble-Alpes University Hospital, Grenoble, France" + "author_name": "Koji Nakamura", + "author_inst": "Tsukuba Medical Center Hospital" }, { - "author_name": "Bertrand TOUSSAINT", - "author_inst": "Univ. Grenoble Alpes, CNRS, CHU Grenoble Alpes, Grenoble INP*, TIMC-IMAG, Grenoble, France" + "author_name": "Hiromichi Suzuki", + "author_inst": "University of Tsukuba" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -168792,39 +168487,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.19.22283668", - "rel_title": "A retrospective analysis of COVID-19 non-pharmaceutical interventions for Mexico and Peru: a modeling study", + "rel_doi": "10.1101/2022.12.17.520843", + "rel_title": "Transgenic Mouse Models Establish a Protective Role of Type 1 IFN Response in SARS-CoV-2 infection-related Immunopathology", "rel_date": "2022-12-19", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.19.22283668", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWWe model the observed dynamics of COVID-19 in Mexico and Peru and explore the impact of hypothetical non-pharmaceutical interventions applied on key days of civic, religious, or political nature that increased contacts and transmission events. Using as a baseline the observed epidemic curve, we apply hypothetical reductions in the contact rates during the first year of the pandemic: i) near the beginning, ii) at the beginning of the second outbreak, and iii) end of the year. The effects of the interventions are different for Mexico and Peru but underlie the fact that strong early interventions do reduce the prevalence and, in general, allow for an epidemic evolution of relatively lower prevalence than interventions applied once the epidemic is underway. We provide evidence that key calendar days are good approximations of times when contact rates change and, therefore, are efficient periods for effective interventions particularly in places with low testing and lack of contact tracing. This has helped us to recreate different outbreaks of the COVID-19 disease dynamics in Mexico and Peru and explore the impact of hypothetical interventions that reduce the contact rate.", - "rel_num_authors": 5, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.17.520843", + "rel_abs": "Type 1 interferon (IFN-I) response is the first line of host defense against invading viruses. In the absence of definite mouse models, the role of IFN-I in SARS-CoV-2 infections remained to be perplexing. Here, we developed two mouse models, one with constitutively high IFN-I response (hACE2; Irgm1-/-) and the other with dampened IFN-I response (hACE2; Ifnar1-/-) to comprehend the role of IFN-I response during SARS-CoV-2 invasion. We found that hACE2; Irgm1-/- mice were resistant to lethal SARS-CoV-2 infection with substantially reduced cytokine storm and immunopathology. In striking contrast, a severe SARS-CoV-2 infection along with immune cells infiltration, inflammatory response, and enhanced pathology was observed in the lungs of hACE2; Ifnar1-/- mice. Additionally, hACE2; Ifnar1-/- mice were highly susceptible to SARS-CoV-2 neuroinvasion in the brain accompanied by immune cell infiltration, microglia/astrocytes activation, cytokine response, and demyelination of neurons. The hACE2; Irgm1-/- Ifnar1-/- double knockout mice or hACE2; Irgm1-/- mice treated with STING or RIPK2 pharmacological inhibitors displayed loss of the protective phenotypes observed in hACE2; Irgm1-/- mice suggesting that heightened IFN-I response accounts for the observed immunity. Taken together, we explicitly demonstrate that IFN-I protects from lethal SARS-CoV-2 infection, and Irgm1 (IRGM) could be an excellent therapeutic target.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC=\"FIGDIR/small/520843v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (51K):\norg.highwire.dtl.DTLVardef@a3aad4org.highwire.dtl.DTLVardef@12452fcorg.highwire.dtl.DTLVardef@1c43dc0org.highwire.dtl.DTLVardef@b2167d_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "M. Adrian Acuna-Zegarra", - "author_inst": "Universidad de Sonora" + "author_name": "Nishant Ranjan Chauhan", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" }, { - "author_name": "Mario Santana-Cibrian", - "author_inst": "UNAM ENES: Universidad Nacional Autonoma de Mexico - Escuela Nacional de Estudios Superiores Unidad Juriquilla" + "author_name": "Soumya Kundu", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" }, { - "author_name": "Carlos E. Rodriguez Hernandez-Vela", - "author_inst": "UNAM IIMAS: Universidad Nacional Autonoma de Mexico Instituto de Investigaciones en Matematicas Aplicadas y Sistemas" + "author_name": "Ramyasingh Bal", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" }, { - "author_name": "Ramses H. Mena", - "author_inst": "UNAM IIMAS: Universidad Nacional Autonoma de Mexico Instituto de Investigaciones en Matematicas Aplicadas y Sistemas" + "author_name": "Diya Chattopadhyay", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" }, { - "author_name": "Jorge X. Velasco-Hernandez", - "author_inst": "UNAM IMATE: Universidad Nacional Autonoma de Mexico, Campus Juriquilla - Instituto de Matematicas" + "author_name": "Subhash Mehto", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" + }, + { + "author_name": "Rinku Sahu", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" + }, + { + "author_name": "Rina Yadav", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" + }, + { + "author_name": "Sivaram Krishna", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" + }, + { + "author_name": "Kautilya Kumar Jena", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" + }, + { + "author_name": "Sameekshya Satapathy", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" + }, + { + "author_name": "Krushna C. Murmu", + "author_inst": "Epigenetic and Chromatin Biology Unit, Institute of Life Sciences, Bhubaneswar, 751023, India" + }, + { + "author_name": "Bharati Singh", + "author_inst": "Virus-Host Interactions Lab, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, Odisha, India" + }, + { + "author_name": "Sarita Jena", + "author_inst": "Experimental Animal Facility, Institute of Life Sciences, Bhubaneswar, 751023, India" + }, + { + "author_name": "Krishnan H. Harshan", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology, Hyderabad, Telangana, India" + }, + { + "author_name": "Gulam Hussain Syed", + "author_inst": "Virus-Host Interactions Lab, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, Odisha, India" + }, + { + "author_name": "Punit Prasad", + "author_inst": "Epigenetic and Chromatin Biology Unit, Institute of Life Sciences, Bhubaneswar, 751023, India" + }, + { + "author_name": "Santosh Chauhan", + "author_inst": "Cell Biology and Infectious Diseases Unit, Department of Infectious Disease Biology, Institute of Life Sciences, Bhubaneswar, 751023, India" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.12.19.22283660", @@ -170402,87 +170145,51 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2022.12.14.520265", - "rel_title": "COVID-19 Associated Pulmonary Aspergillosis isolates are genomically diverse but similar to each other in their responses to infection-relevant stresses", + "rel_doi": "10.1101/2022.12.15.22283503", + "rel_title": "Long-term neutralizing antibody dynamics against SARS-CoV-2 in symptomatic and asymptomatic infections: a systematic review and meta-analysis", "rel_date": "2022-12-15", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.14.520265", - "rel_abs": "Secondary infections caused by the pulmonary fungal pathogen Aspergillus fumigatus are a significant cause of mortality in patients with severe Coronavirus Disease 19 (COVID-19). Even though epithelial cell damage and aberrant cytokine responses have been linked with susceptibility to COVID-19 associated pulmonary aspergillosis (CAPA), little is known about the mechanisms underpinning co-pathogenicity. Here, we analysed the genomes of 11 A. fumigatus isolates from patients with CAPA in three centres from different European countries. CAPA isolates did not cluster based on geographic origin in a genome-scale phylogeny of representative A. fumigatus isolates. Phenotypically, CAPA isolates were more similar to the A. fumigatus A1160 reference strain than to the Af293 strain when grown in infection-relevant stresses; except for interactions with human immune cells wherein macrophage responses were similar to those induced by the Af293 reference strain. Collectively, our data indicates that CAPA isolates are genomically diverse but are more similar to each other in their responses to infection-relevant stresses. A larger number of isolates from CAPA patients should be studied to identify genetic drivers of co-pathogenicity in patients with COVID-19.\n\nImportanceCoronavirus disease 2019 (COVID-19)-associated pulmonary aspergillosis (CAPA) has been globally reported as a life-threatening complication in some patients with severe COVID-19. Most of these infections are caused by the environmental mould Aspergillus fumigatus which ranks third in the fungal pathogen priority list of the WHO. However, little is known about the molecular epidemiology of Aspergillus fumigatus CAPA strains. Here, we analysed the genomes of 11 A. fumigatus isolates from patients with CAPA in three centres from different European countries and, carried out phenotypic analyses with a view to understand the pathophysiology of the disease. Our data indicates that A. fumigatus CAPA isolates are genomically diverse but are more similar to each other in their responses to infection-relevant stresses.", - "rel_num_authors": 17, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.15.22283503", + "rel_abs": "BackgroundThe kinetics of the neutralizing antibody response against SARS-CoV-2 is crucial for responding to the pandemic as well as developing vaccination strategies. We aimed to fit the antibody curves in symptomatic and asymptomatic individuals.\n\nMethodsWe systematically searched PubMed, Embase, Web of Science, and Europe PMC for articles published in English between Jan 1, 2020, and Oct 2, 2022. Studies evaluating neutralizing antibody from people who had a natural SARS-CoV-2 infection history were included. Study quality was assessed using a modified standardized scoring system. We fitted dynamic patterns of neutralizing antibody using a generalized additive model and a generalized additive mixed model. We also used linear regression model to conduct both univariate and multivariable analyses to explore the potential affecting factors on antibody levels. This study is registered with PROSPERO, CRD42022348636.\n\nResults7,343 studies were identified in the initial search, 50 were assessed for eligibility after removal of duplicates as well as inappropriate titles, abstracts and full-text review, and 48 studies (2,726 individuals, 5,670 samples) were included in the meta-analysis after quality assessment. The neutralization titer of people who infected with SARS-CoV-2 prototype strain peaked around 27 days (217.4, 95%CI: 187.0-252.9) but remained below the Omicron BA.5 protection threshold all the time after illness onset or confirmation. Furthermore, neither symptomatic infections nor asymptomatic infections could provide over 50% protection against Omicron BA.5 sub-lineage. It also showed that the clinical severity and the type of laboratory assays may significantly correlated with the level of neutralizing antibody.\n\nConclusionsThis study provides a comprehensive mapping of the dynamic of neutralizing antibody against SARS-CoV-2 prototype strain induced by natural infection and compared the dynamic patterns between prototype and variant strains. It suggests that the protection probability provided by natural infection is limited. Therefore, timely vaccination is necessary for both previously infected symptomatic and asymptomatic individuals.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Matthew E Mead", - "author_inst": "Vanderbilt University, Nashville, Tennessee, USA" - }, - { - "author_name": "Patricia Alves de Castro", - "author_inst": "Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" - }, - { - "author_name": "Jacob B Steenwyk", - "author_inst": "Vanderbilt University, Nashville, Tennessee, USA" - }, - { - "author_name": "Jean-Pierre Gangneux", - "author_inst": "Univ Rennes, CHU Rennes," - }, - { - "author_name": "Martin Hoenigl", - "author_inst": "Medical University of Graz, Graz, Austria" - }, - { - "author_name": "Juergen Prattes", - "author_inst": "Medical University of Graz, Graz, Austria" - }, - { - "author_name": "Riina Rautemaa-Richardson", - "author_inst": "The University of Manchester, Manchester, UK" - }, - { - "author_name": "Helene Guegan", - "author_inst": "Univ Rennes, CHU Rennes," - }, - { - "author_name": "Caroline B Moore", - "author_inst": "The University of Manchester, Manchester, UK" - }, - { - "author_name": "Cornelia Lass-Floerl", - "author_inst": "Medical University of Innsbruck, Austria" + "author_name": "Wanying Lu", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Florian Reizine", - "author_inst": "Medical Intensive Care Unit , Rennes University Hospital, 35000 Rennes." + "author_name": "Nan Zheng", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Clara Valero", - "author_inst": "The University of Manchester, Manchester, UK" + "author_name": "Xinhua Chen", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Norman van Rhijn", - "author_inst": "The University of Manchester, Manchester, UK" + "author_name": "Ruijia Sun", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Mike J Bromley", - "author_inst": "The University of Manchester, Manchester, UK" + "author_name": "Jiayi Dong", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Antonis Rokas", - "author_inst": "Vanderbilt University, Nashville, Tennessee, USA" + "author_name": "Shijia Ge", + "author_inst": "Department of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Disea" }, { - "author_name": "Gustavo H Goldman", - "author_inst": "Universidade de Sao Paulo, Ribeirao Preto, Sao Paulo, Brazil" + "author_name": "Xiaowei Deng", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" }, { - "author_name": "Sara Gago", - "author_inst": "The University of Manchester, Manchester, UK" + "author_name": "Hongjie Yu", + "author_inst": "Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "cell biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.12.15.520197", @@ -172439,29 +172146,101 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.12.10.22283298", - "rel_title": "The Use and Safety Risk of Repurposed Drugs for COVID-19 patients: Lessons Learned Utilizing the Food and Drug Administrations Adverse Event Reporting System", + "rel_doi": "10.1101/2022.12.11.22283166", + "rel_title": "Safety and Immunogenicity of an Omicron BA.4/BA.5 Bivalent Vaccine against Covid-19", "rel_date": "2022-12-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.10.22283298", - "rel_abs": "ObjectivesThis study was designed to assess the disproportionality analyses of adverse drug reactions (ADRs) related to hydroxychloroquine and remdesivir and how ADR reporting fluctuated during the COVID-19 pandemic.\n\nMethodsA retrospective observational study was conducted utilizing the Food and Drug Administrations Adverse Event Reporting System (FAERS) data between 2019 and 2021. The study was conducted in two phases. In the first phase, all reports associated with the drugs of interest were evaluated to assess all related adverse drug reactions. In the second phase, specific outcomes of interest (i.e., QT prolongation and renal and hepatic events) were determined to study their association with the drugs of interest. A descriptive analysis was conducted for all adverse reactions related to the drugs being studied. In addition, disproportionality analyses were conducted to compute the reporting odds ratio, the proportional reporting ratio, the information component, and the empirical Bayes geometric mean. All analyses were conducted using RStudio.\n\nResultsA total of 9,443 ADR reports related to hydroxychloroquine; 6,160 (71.49) patients were female, and higher percentage of patients of both sexes were over the age of 65 years. QT prolongation (1.48%), pain (1.38%), and arthralgia (1.25%) were most frequently reported ADRs during the COVID-19 pandemic. The association of QT prolongation with use of hydroxychloroquine was statistically significant (ROR 47.28 [95% CI 35.95-62.18]; PRR 42.41 [95% CI 32.25-55.78]; EBGM 16.08; IC 4.95) compared with fluoroquinolone. The outcome was serious medical events in 48.01% of ADR reports; 27.42% required hospitalization and 8.61% resulted in death. Of 6,673 ADR reports related to remdesivir, 3,928 (61.13%) patients were male. During 2020, the top three ADR reports were elevated liver function tests (17.26%), acute kidney injury (5.95%) and death (2.84%). Additionally, 42.71% of ADR reports indicated serious medical events; 19.69% resulted in death and 11.71% indicated hospitalization. The ROR and PRR of hepatic and renal events associated with remdesivir were statistically significant, (4.81 [95% CI 4.46-5.19] and 2.96 [95% CI 2.66-3.29], respectively.\n\nConclusionOur study showed that several serious ADRs were reported with the use of hydroxychloroquine, which resulted in hospitalization and death. Trends with the use of remdesivir were similar, but to a lesser extent. Therefore, this study showed us that off-label use should be based on thorough evidence-based evaluation.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.11.22283166", + "rel_abs": "BackgroundInformation on the safety and immunogenicity of the omicron BA.4/BA.5-containing bivalent booster mRNA-1273.222 are needed.\n\nMethodsIn this ongoing, phase 2/3 trial, 50-g mRNA-1273.222 (25-g each ancestral Wuhan-Hu-1 and omicron BA.4/BA.5 spike mRNAs) is compared to 50-g mRNA-1273, administered as second boosters in adults who previously received a 2-injection (100-g) primary series and first booster (50-g) dose of mRNA-1273. The primary objectives were safety and immunogenicity 28 days post-boost.\n\nResultsParticipants received 50-g of mRNA-1273 (n=376) or mRNA-1273.222 (n=511) as second booster doses. Omicron BA.4/BA.5 and ancestral SARS-CoV-2 D614G neutralizing antibody geometric mean titers (GMTs [95% confidence interval]) after mRNA-1273.222 (2324.6 [1921.2-2812.7] and 7322.4 [6386.2-8395.7]) were significantly higher than mRNA-1273 (488.5 [427.4-558.4] and 5651.4 (5055.7-6317.3) respectively, at day 29 post-boost in participants with no prior SARS-CoV-2-infection. A randomly selected subgroup (N=60) of participants in the mRNA-1273.222 group also exhibited cross-neutralization against the emerging omicron variants BQ.1.1 and XBB.1. No new safety concerns were identified with mRNA-1273.222.\n\nVaccine effectiveness was not assessed in this study; in an exploratory analysis 1.6% (8/511) of mRNA-1273.222 recipients had Covid-19 post-boost.\n\nConclusionThe bivalent omicron BA.4/BA.5-containing vaccine mRNA-1273.222 elicited superior neutralizing antibody responses against BA.4/BA.5 compared to mRNA-1273, with no safety concerns identified.\n\n(Supported by Moderna; ClinicalTrials.gov Identifier: NCT04927065)", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Deemah S Alsuhaibani", - "author_inst": "Pharmaceutical Care Department, Medical Services for Armed Forces, Ministry of Defense, Riyadh, Saudi Arabia" + "author_name": "Spyros Chalkias", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" }, { - "author_name": "Heba H Edrees", - "author_inst": "Harvard T.H. Chan School of Public Health, Boston, MA" + "author_name": "Jordan Whatley", + "author_inst": "Meridian Clinical Research, Baton Rouge, Lousianna" }, { - "author_name": "Thamir M Alshammari", - "author_inst": "Medication Safety Research Chair, King Saud University, Riyadh, Saudi Arabia" + "author_name": "Frank Eder", + "author_inst": "Meridian Clinical Research, LLC, Binghamton, New York" + }, + { + "author_name": "Brandon Essink", + "author_inst": "Meridian Clinical Research, Omaha, Nebraska" + }, + { + "author_name": "Shishar Khetan", + "author_inst": "Meridian Clinical Research, Rockville, MD" + }, + { + "author_name": "Paul Bradley", + "author_inst": "Meridian Clinical Research, Savannah, Georgia" + }, + { + "author_name": "Adam Brosz", + "author_inst": "Meridian Clinical Research, Grand Island, Nebraska" + }, + { + "author_name": "Nichole McGhee", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" + }, + { + "author_name": "Joanne E Tomassini", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" + }, + { + "author_name": "Xing Chen", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" + }, + { + "author_name": "Andrea Sutherland", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" + }, + { + "author_name": "Xiaoying Shen", + "author_inst": "Duke University Medical Center, Durham, North Carolina" + }, + { + "author_name": "Bethany Girard", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" + }, + { + "author_name": "Darin K Edwards", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" + }, + { + "author_name": "Jing Feng", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" + }, + { + "author_name": "Honghong Zhou", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" + }, + { + "author_name": "Stephen R Walsh", + "author_inst": "Brigham and Womens Hospital, Boston, Massachusetts" + }, + { + "author_name": "David C Montefiori", + "author_inst": "Department of Surgery and Duke Human Vaccine Institute, Durham, North Carolina" + }, + { + "author_name": "Lindsey R Baden", + "author_inst": "Brigham and Womens Hospital, Boston, Massachusetts" + }, + { + "author_name": "Jacqueline M Miller", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" + }, + { + "author_name": "Rituparna Das", + "author_inst": "Moderna, Inc., Cambridge, Massachusetts" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -174073,41 +173852,65 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.12.08.22283272", - "rel_title": "Duration of viral shedding of the Omicron variant in asymptomatic and mild COVID-19 cases from Shanghai, China", + "rel_doi": "10.1101/2022.12.08.22283268", + "rel_title": "Respiratory Virus Circulation during the First Year of the COVID-19 Pandemic in the Household Influenza Vaccine Evaluation (HIVE) Cohort", "rel_date": "2022-12-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.08.22283272", - "rel_abs": "BackgroundThe Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), designated as a variant of concern by the World Health Organization, spreads globally and was confirmed as the cause of the Omicron wave of the coronavirus disease 2019 (COVID-19) pandemic in Shanghai, China. The viral shedding duration of Omicron variants needs to be determined.\n\nMethodsWe retrospectively analyzed 382 patients admitted to a shelter hospital for COVID-19. Of the patients, 8 patients were referred to a designated hospital, 100 were infected asymptomatic patients, and 274 patients had mild COVID-19.\n\nResultsThe vaccination rates (including fully and boosted) in the asymptomatic and mild COVID-19 patients were 92.00% and 94.16%, respectively. Majority of the studied population showed a first reverse transcription-polymerase chain reaction cycle threshold (Ct) value of 20. For 2565 nasopharyngeal swabs from close or sub-close contacts, the Ct value gradually increased to 35 for 8 days, and the median duration of viral shedding time was 10 days after the first positive detection of the SARS-CoV-2 nuclei acid.\n\nConclusionsQuantitative viral RNA load assays in COVID-19 (BA.2.2.1) close or sub-closed contacts could be used to prevent transmissions and control precautions.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.08.22283268", + "rel_abs": "BackgroundThe annual reappearance of respiratory viruses has been recognized for decades. The onset of the COVID-19 pandemic altered typical respiratory virus transmission patterns. COVID-19 mitigation measures taken during the pandemic were targeted at SARS-CoV-2 respiratory transmission and thus broadly impacted the burden of acute respiratory illnesses (ARIs), in general.\n\nMethodsWe used the longitudinal Household Influenza Vaccine Evaluation (HIVE) cohort of households in southeast Michigan to characterize mitigation strategy adherence, respiratory illness burden, and the circulation of 15 respiratory viruses during the COVID-19 pandemic determined by RT-PCR of respiratory specimens collected at illness onset. Study participants were surveyed twice during the study period (March 1, 2020, to June 30, 2021), and serologic specimens were collected for antibody measurement by electrochemiluminescence immunoassay. Incidence rates of ARI reports and virus detections were calculated and compared using incidence rate ratios for the study period and a pre-pandemic period of similar length.\n\nResultsOverall, 437 participants reported a total of 772 ARIs and 329 specimens (42.6%) had respiratory viruses detected. Rhinoviruses were the most frequently detected organism, but seasonal coronaviruses--excluding SARS-CoV-2--were also common. Illness reports and percent positivity were lowest from May to August 2020, when mitigation measures were most stringent. Study participants were more adherent to mitigation measures in the first survey compared with the second survey. Supplemental serology surveillance identified 5.3% seropositivity for SARS-CoV-2 in summer 2020; 3.0% between fall 2020 and winter 2021; and 11.3% in spring 2021. Compared to a pre-pandemic period of similar length, the incidence rate of total reported ARIs for the study period was 50% lower (95% CI: 0.5, 0.6; p<0.001) than the incidence rate from March 1, 2016, to June 30, 2017.\n\nConclusionsThe burden of ARI in the HIVE cohort during the COVID-19 pandemic fluctuated, with declines occurring concurrently with the widespread use of public health measures. It is notable, however, that rhinovirus and seasonal coronaviruses continued to circulate even as influenza and SARS-CoV-2 circulation was low.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Weijie Sun", - "author_inst": "Department of Clinical Laboratory, Ningbo First Hospital, University of Ningbo, Zhejiang Province, China" + "author_name": "Sydney R Fine", + "author_inst": "University of Michigan" }, { - "author_name": "Naibin Yang", - "author_inst": "Department of Infectious Diseases, Ningbo First Hospital, University of Ningbo, Zhejiang Province, China" + "author_name": "Latifa A Bazzi", + "author_inst": "University of Michigan" }, { - "author_name": "Yang Mao", - "author_inst": "Ningbo Municipal Center for Disease Control and Prevention, Ningbo, China" + "author_name": "Amy P Callear", + "author_inst": "University of Michigan" }, { - "author_name": "Danying Yan", - "author_inst": "Department of Infectious Diseases, Ningbo First Hospital, University of Ningbo, Zhejiang Province, China" + "author_name": "Joshua G Petrie", + "author_inst": "University of Michigan" }, { - "author_name": "Qifa Song", - "author_inst": "Medical Data Centre, Ningbo First Hospital, University of Ningbo, Zhejiang Province, China" + "author_name": "Ryan E Malosh", + "author_inst": "University of Michigan" + }, + { + "author_name": "Joshua E Tucker", + "author_inst": "University of Michigan" + }, + { + "author_name": "Matthew Smith", + "author_inst": "University of Michigan" + }, + { + "author_name": "Jessica Ibiebele", + "author_inst": "University of Michigan" + }, + { + "author_name": "Adrian McDermott", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases" + }, + { + "author_name": "Melissa A Rolfes", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Arnold S Monto", + "author_inst": "University of Michigan" }, { - "author_name": "Guoqing Qian Sr.", - "author_inst": "Department of Infectious Diseases, Ningbo First Hospital, University of Ningbo, Zhejiang Province, China" + "author_name": "Emily Toth Martin", + "author_inst": "University of Michigan-Ann Arbor" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -175883,83 +175686,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.12.04.22282996", - "rel_title": "COVID-19 vaccine coverage targets to inform reopening plans in a low incidence setting", + "rel_doi": "10.1101/2022.12.05.519191", + "rel_title": "A screen for modulation of nucleocapsid protein condensation identifies small molecules with anti-coronavirus activity", "rel_date": "2022-12-06", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.04.22282996", - "rel_abs": "Since the emergence of SARS-CoV-2 in 2019 through to mid-2021, much of the Australian population lived in a COVID-19 free environment. This followed the broadly successful implementation of a strong suppression strategy, including international border closures. With the availability of COVID-19 vaccines in early 2021, the national government sought to transition from a state of minimal incidence and strong suppression activities to one of high vaccine coverage and reduced restrictions but with still-manageable transmission. This transition is articulated in the national \"re-opening\" plan released in July 2021. Here we report on the dynamic modelling study that directly informed policies within the national re-opening plan including the identification of priority age groups for vaccination, target vaccine coverage thresholds and the anticipated requirements for continued public health measures -- assuming circulation of the Delta SARS-CoV-2 variant. Our findings demonstrated that adult vaccine coverage needed to be at least 70% to minimise public health and clinical impacts following the establishment of community transmission. They also supported the need for continued application of test-trace-isolate-quarantine and social measures during the vaccine roll-out phase and beyond.", - "rel_num_authors": 16, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.12.05.519191", + "rel_abs": "Biomolecular condensates formed by liquid-liquid phase separation have been implicated in multiple diseases. Modulation of condensate dynamics by small molecules has therapeutic potential, but so far, few condensate modulators have been disclosed. The SARS-CoV-2 nucleocapsid (N) protein forms phase separated condensates that are hypothesized to play critical roles in viral replication, transcription and packaging, suggesting that N condensation modulators might have anti-coronavirus activity across multiple strains and species. Here, we show that N proteins from all seven human coronaviruses (HCoVs) vary in their tendency to undergo phase separation when expressed in human lung epithelial cells. We developed a cell-based high-content screening platform and identified small molecules that both promote and inhibit condensation of SARS-CoV-2 N. Interestingly, these host-targeted small molecules exhibited condensate-modulatory effects across all HCoV Ns. Some have also been reported to exhibit antiviral activity against SARS-CoV-2, HCoV-OC43 and HCoV-229E viral infections in cell culture. Our work reveals that the assembly dynamics of N condensates can be regulated by small molecules with therapeutic potential. Our approach allows for screening based on viral genome sequences alone and might enable rapid paths to drug discovery with value for confronting future pandemics.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Eamon Conway", - "author_inst": "Walter and Eliza Hall Institute" - }, - { - "author_name": "Camelia Walker", - "author_inst": "The University of Melbourne" - }, - { - "author_name": "Chris Baker", - "author_inst": "The University of Melbourne" - }, - { - "author_name": "Michael Lydeamore", - "author_inst": "Monash University" - }, - { - "author_name": "Gerard E Ryan", - "author_inst": "Telethon Kids Institute; The University of Melbourne" - }, - { - "author_name": "Trish Campbell", - "author_inst": "The University of Melbourne; The Peter Doherty Institute for Infection and Immunity" - }, - { - "author_name": "Joel C Miller", - "author_inst": "La Trobe University" - }, - { - "author_name": "Max Yeung", - "author_inst": "Quantium" + "author_name": "Rui Tong Quek", + "author_inst": "Harvard Medical School" }, { - "author_name": "Greg Kabashima", - "author_inst": "Quantium" + "author_name": "Kierra S. Hardy", + "author_inst": "Harvard Medical School" }, { - "author_name": "James Wood", - "author_inst": "University of New South Wales" + "author_name": "Stephen G. Walker", + "author_inst": "AbbVie Inc." }, { - "author_name": "Nic Rebuli", - "author_inst": "University of New South Wales" + "author_name": "Dan T. Nguyen", + "author_inst": "Harvard Medical School" }, { - "author_name": "James M McCaw", - "author_inst": "The University of Melbourne" + "author_name": "Taciani de Almeida Magalh\u00e3es", + "author_inst": "Harvard Medical School" }, { - "author_name": "Jodie McVernon", - "author_inst": "The Peter Doherty Institute for Infection and Immunity" + "author_name": "Adrian Salic", + "author_inst": "Harvard Medical School" }, { - "author_name": "Nick Golding", - "author_inst": "Telethon Kids Institute and Curtin University" + "author_name": "Sujatha M. Gopalakrishnan", + "author_inst": "AbbVie Inc." }, { - "author_name": "David J Price", - "author_inst": "The University of Melbourne; The Peter Doherty Institute for Infection and Immunity" + "author_name": "Pamela A. Silver", + "author_inst": "Harvard Medical School" }, { - "author_name": "Freya M Shearer", - "author_inst": "The University of Melbourne" + "author_name": "Timothy J. Mitchison", + "author_inst": "Harvard Medical School" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "molecular biology" }, { "rel_doi": "10.1101/2022.12.04.22283077", @@ -177773,39 +177548,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.11.30.22282946", - "rel_title": "Discovering Social Determinants of Health from Case Reports using Natural Language Processing: Algorithmic Development and Validation", + "rel_doi": "10.1101/2022.12.01.22282963", + "rel_title": "Perceptions, readiness and recommendations of traditional herbalists to integrate traditional and modern medicine in controlling COVID-19 epidemics in Northeast Ethiopia: An interpretive qualitative study", "rel_date": "2022-12-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.30.22282946", - "rel_abs": "BackgroundSocial determinants of health are non-medical factors that influence health outcomes (SDOH). There is a wealth of SDOH information available in electronic health records, clinical reports, and social media data, usually in free text format. Extracting key information from free text poses a significant challenge and necessitates the use of natural language processing (NLP) techniques to extract key information.\n\nObjectiveThe objective of this research is to advance the automatic extraction of SDOH from clinical texts.\n\nSetting and DataThe case reports of COVID-19 patients from the published literature are curated to create a corpus. A portion of the data is annotated by experts to create ground truth labels, and semi-supervised learning method is used for corpus re-annotation.\n\nMethodsAn NLP framework is developed and tested to extract SDOH from the free texts. A two-way evaluation method is used to assess the quantity and quality of the methods.\n\nResultsThe proposed NER implementation achieves an accuracy (F1-score) of 92.98% on our test set and generalizes well on benchmark data. A careful analysis of case examples demonstrates the superiority of the proposed approach in correctly classifying the named entities.\n\nConclusionsNLP can be used to extract key information, such as SDOH factors from free texts. A more accurate understanding of SDOH is needed to further improve healthcare outcomes.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.12.01.22282963", + "rel_abs": "BackgroundTraditional medicine is an approach that has unique knowledge and beliefs which incorporates plant, animal or mineral based medicines that applied alone or in combination to treat, diagnose and prevent illnesses and maintain well-being. Suggestions from clinical practices and researches shown that integrated traditional Chinese and western medicine played an important role in Chinas successful control of COVID-19. Despite such evidence, the Ethiopian minister of health prohibited traditional herbalists from using traditional remedies for COVID-19. However many of the traditional herbalists and the community requested the government frequently to try traditional medicine for COVID-19. The aim of this study was to explore perceptions, readiness, and recommendations of traditional herbalists on the effect of traditional medicine on COVID-19 and to select the promising remedies for pre-clinical study.\n\nMethodsThe study design used was an interpretive qualitative study. An in-depth interview was employed to gain access to the traditional herbalists experiences, perceptions, readiness and their recommendations. Traditional herbalists who lived in the North Wollo Zone were interviewed about the probable medicinal plants that can treat COVID-19. An inductive qualitative content analysis was conducted.\n\nResultsFrom the in-depth interview with traditional herbalists, 4thematic frameworks were developed. Those major themes are;(1)perception of traditional medicine practitioners about COVID-19;(2) hypothesizing potential traditional remedies to treat COVID-19;(3)traditional practitioners recommendations for the community, and (4) integration of traditional and modern medicine. There was no pronounced difference in opinion among traditional herbalists about COVID-19 signs and symptoms, mode of transmission, and source of information about the epidemics.\n\nTraditional herbalists had not planned to treat COVID-19 because of the minister of healths prohibition of using traditional remedies. However, the traditional herbalists gave their remedies to minister of health, research institutes, and universities to get approval after the necessary procedures or laboratory investigations including toxicity studies. Despite the interest of traditional herbalists, currently, traditional medicine is not anymore economically and professionally useful for traditional herbalists because of many factors including the Ethiopian People Democracy Republic Fronts (EPDRF) government negative attitude, and its domination by the western medicine. Traditional herbalists were unsure which remedy might treat the COVID_19 but they believed that plants that were used to treat cough, acute respiratory distress syndrome (ARDS), and other respiratory infections might be used to control the signs and symptoms of COVID-19. If there is potential traditional remedy for COVID-19 from the traditional herbalists, integration of traditional medicine (TM) and modern medicine (MM) may be compulsory to manage COVID-19 effectively.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Shaina Raza", - "author_inst": "University of Toronto" - }, - { - "author_name": "Elham Dolatabadi", - "author_inst": "Vector Institute" + "author_name": "Mesfin Wudu Kassaw", + "author_inst": "Woldia University, Woldia, Ethiopia" }, { - "author_name": "Nancy Ondrusek", - "author_inst": "OAHPP" + "author_name": "Mohammed Hussen Mohammed", + "author_inst": "Woldia University" }, { - "author_name": "Laura Rosella", - "author_inst": "University of Toronto" - }, - { - "author_name": "Brian Schwartz", - "author_inst": "University of Toronto" + "author_name": "Ousman Ahmed Mohammed", + "author_inst": "Woldia University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "primary care research" }, { "rel_doi": "10.1101/2022.12.02.22282982", @@ -179727,71 +179494,27 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.11.30.22282922", - "rel_title": "Epidemiological impact of a large number of incorrect negative SARS-CoV-2 test results in South West England during September and October 2021", + "rel_doi": "10.1101/2022.11.26.518005", + "rel_title": "An Optimized Circular Polymerase Extension Reaction-based Method for Functional Analysis of SARS-CoV-2", "rel_date": "2022-11-30", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.30.22282922", - "rel_abs": "BackgroundIn England, free testing for COVID-19 was widely available from early in the pandemic until 1 April 2022. Based on apparent differences in the rate of positive PCR tests at a single laboratory compared to the rest of the laboratory network, we hypothesised that a substantial number of UK PCR tests processed during September and October 2021 may have been incorrectly reported as negative, compared with the rest of the laboratory network. We investigate the epidemiological impact of this incident.\n\nMethodsWe estimate the additional number of COVID-19 cases that would have been reported had the sensitivity of the laboratory test procedure not dropped for the period 2 September to 12 October. In addition, by making comparisons between the most affected local areas and comparator populations, we estimate the number of additional infections, cases, hospitalisations and deaths that could have occurred as a result of increased transmission due to the misclassification of tests.\n\nResultsWe estimate that around 39,000 tests may have been incorrectly classified during this period and, as a direct result of this incident, the most affected areas in the South West could have experienced between 6,000 and 34,000 additional reportable cases, with a central estimate of around 24,000 additional reportable cases. Using modelled relationships between key variables, we estimate that this central estimate could have translated to approximately 55,000 additional infections, which means that each incorrect negative test likely led to just over two additional infections. In those same geographical areas, our results also suggest an increased number of admissions and deaths.\n\nConclusionThe incident is likely to have had a measurable impact on cases and infections in the affected areas in the South West of England.", - "rel_num_authors": 13, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.26.518005", + "rel_abs": "SUMMARYReverse genetics systems have been crucial for studying specific viral genes and their relevance in the virus lifecycle, and become important tools for the rational attenuation of viruses and thereby for vaccine design. Recent rapid progress has been made in the establishment of reverse genetics systems for functional analysis of SARS-CoV-2, a coronavirus that causes the ongoing COVID-19 pandemic that has resulted in detrimental public health and economic burden. Among the different reverse genetics approaches, CPER (circular polymerase extension reaction) has become one of the leading methodologies to generate recombinant SARS-CoV-2 infectious clones due to its accuracy, efficiency, and flexibility. Here, we report an optimized CPER methodology which, through the use of a modified linker plasmid and by performing DNA nick ligation and direct transfection of permissive cells, overcomes certain intrinsic limitations of the traditional CPER approaches for SARS-CoV-2, allowing for efficient virus rescue. This optimized CPER system may facilitate research studies to assess the contribution of SARS-CoV-2 genes and individual motifs or residues to virus replication, pathogenesis and immune escape, and may also be adapted to other viruses.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Luke Hounsome", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Daniel Herr", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Ruby Bryant", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Robert Smith", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Leo Loman", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Joshua Harris", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Urslaan Youhan", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Evija Dzene", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Pantelis Hadjipantelis", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Harry Long", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Timothy Laurence", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Steven Riley", - "author_inst": "UK Health Security Agency" + "author_name": "GuanQun Liu", + "author_inst": "Cleveland Clinic Florida Research and Innovation Center" }, { - "author_name": "Fergus Cumming", - "author_inst": "UK Health Security Agency" + "author_name": "Michaela Gack", + "author_inst": "Cleveland Clinic Florida Research and Innovation Center" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.11.29.518257", @@ -181341,27 +181064,139 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.11.29.518406", - "rel_title": "Atomic-level characterization of the conformational transition pathways in SARS-CoV-1 and SARS-CoV-2 spike proteins", + "rel_doi": "10.1101/2022.11.28.22282858", + "rel_title": "Trajectories of host-response biomarkers and inflammatory subphenotypes in COVID-19 patients across the spectrum of respiratory support.", "rel_date": "2022-11-29", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.29.518406", - "rel_abs": "Severe acute respiratory syndrome (SARS) coronaviruses 1 and 2 (SARS-CoV-1 and SARS-CoV-2) derive transmissibility from spike protein activation in the receptor binding domain (RBD) and binding to the host cell angiotensin converting enzyme 2 (ACE2). However, the mechanistic details that describe the large-scale conformational changes associated with spike protein activation or deactivation are still somewhat unknown. Here, we have employed an extensive set of nonequilibrium all-atom molecular dynamics (MD) simulations, utilizing a novel protocol, for the SARS-CoV-1 (CoV-1) and SARS-CoV-2 (CoV-2) prefusion spike proteins in order to characterize the conformational pathways associated with the active-to-inactive transition. Our results indicate that both CoV-1 and CoV-2 spike proteins undergo conformational transitions along pathways unique to each protein. We have identified a number of key residues that form various inter-domain saltbridges, suggesting a multi-stage conformational change along the pathways. We have also constructed the free energy profiles along the transition pathways for both CoV-1 and CoV-2 spike proteins. The CoV-2 spike protein must overcome larger free energy barriers to undergo conformational changes towards protein activation or deactivation, when compared to CoV-1.", - "rel_num_authors": 2, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.28.22282858", + "rel_abs": "PurposeEnhanced understanding of the dynamic changes in the dysregulated inflammatory response in COVID-19 may help improve patient selection and timing for immunomodulatory therapies.\n\nMethodsWe enrolled 323 COVID-19 inpatients on different levels of baseline respiratory support: i) Low Flow Oxygen (37%), ii) Non-Invasive Ventilation or High Flow Oxygen (NIV_HFO, 29%), iii) Invasive Mechanical Ventilation (IMV, 27%), and iv) Extracorporeal Membrane Oxygenation (ECMO, 7%). We collected plasma samples upon enrollment and days 5 and 10 to measure host-response biomarkers. We classified subjects into inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker and subphenotype trajectories and outcomes during hospitalization.\n\nResultsIL-6, procalcitonin, and Angiopoietin-2 were persistently elevated in patients at higher levels of respiratory support, whereas sRAGE displayed the inverse pattern. Patients on NIV_HFO at baseline had the most dynamic clinical trajectory, with 26% eventually requiring intubation and exhibiting worse 60-day mortality than IMV patients at baseline (67% vs. 35%, p<0.0001). sRAGE levels predicted NIV failure and worse 60-day mortality for NIV_HFO patients, whereas IL-6 levels were predictive in IMV or ECMO patients. Hyper-inflammatory subjects at baseline (<10% by both models) had worse 60-day survival (p<0.0001) and 50% of them remained classified as hyper-inflammatory on follow-up sampling at 5 days post-enrollment. Receipt of combined immunomodulatory therapies (steroids and anti-IL6 agents) was associated with markedly increased IL-6 and lower Angiopoietin-2 levels (p<0.05).\n\nConclusionsLongitudinal study of systemic host responses in COVID-19 revealed substantial and predictive inter-individual variability, influenced by baseline levels of respiratory support and concurrent immunomodulatory therapies.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Dylan S Ogden", - "author_inst": "University of Arkansas" + "author_name": "Michael Lu", + "author_inst": "Internal Medicine Residency Program, University of Pittsburgh Medical Center, Pittsburgh, PA, USA" }, { - "author_name": "Mahmoud Moradi", - "author_inst": "University of Arkansas" + "author_name": "Callie Drohan", + "author_inst": "Internal Medicine Residency Program, University of Pittsburgh Medical Center, Pittsburgh, PA, USA" + }, + { + "author_name": "William Bain", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Faraaz A Shah", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Matthew Bittner", + "author_inst": "Internal Medicine Residency Program, University of Pittsburgh Medical Center, Pittsburgh, PA, USA" + }, + { + "author_name": "John Evankovich", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Niall Prendergast", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Matthew Hensley", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Tomeka Suber", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Meghan Fitzpatrick", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Raj Ramanan", + "author_inst": "Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Holt Murray", + "author_inst": "Department of Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Caitlin Schaefer", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Shulin Qin", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Xiaohong Wang", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Yingze Zhang", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Seyed M Nouraie", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Heather Gentry", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Cathy Kessinger", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Asha Patel", + "author_inst": "Center for Medicine and the Microbiome, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Bernard J Macatangay", + "author_inst": "Division of Infectious Diseases, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Jana Jacobs", + "author_inst": "Division of Infectious Diseases, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "John Mellors", + "author_inst": "Division of Infectious Diseases, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Janet S Lee", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Prabir Ray", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Anuradha Ray", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Barbara Methe", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Alison Morris", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Bryan J McVerry", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" + }, + { + "author_name": "Georgios D Kitsios", + "author_inst": "Division of Pulmonary, Allergy, and Critical Care Medicine, University of Pittsburgh, Pittsburgh, PA, USA" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "biophysics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2022.11.28.22282832", @@ -183359,99 +183194,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.11.23.22282648", - "rel_title": "An Early SARS-CoV-2 Omicron Outbreak in a Dormitory in Saint-Petersburg, Russia", + "rel_doi": "10.1101/2022.11.23.517678", + "rel_title": "An FcRn-targeted mucosal vaccine against SARS-CoV-2 infection and transmission", "rel_date": "2022-11-24", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.23.22282648", - "rel_abs": "The Omicron variant of SARS-CoV-2 has rapidly spread globally in late 2021 - early 2022, displacing the previously prevalent Delta variant. Before December 16, 2021, community transmission had already been observed in tens of countries globally. However, in Russia, the majority of reported cases at that time had been sporadic and associated with travel. Here, we report an Omicron outbreak at a student dormitory in Saint Petersburg between December 16 - 29, 2021, which was the earliest known instance of large-scale community transmission in Russia. Out of the 465 sampled residents of the dormitory, 180 (38.7%) tested PCR positive. Among the 118 residents for whom the variant has been tested by whole-genome sequencing, 111 (94.1%) carried the Omicron variant. Among these 111 residents, 60 (54.1%) were vaccinated or had reported previous COVID-19. Phylogenetic analysis confirmed that the outbreak was caused by a single introduction of the BA.1.1 sublineage of Omicron. The dormitory-derived clade constituted a significant proportion of BA.1.1 samples in Saint-Petersburg and has spread to other regions of Russia and other countries. The rapid spread of Omicron in a population with preexisting immunity to previous variants underlines its propensity for immune evasion.", - "rel_num_authors": 20, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.23.517678", + "rel_abs": "SARS-CoV-2 and its variants cause COVID-19, which is primarily transmitted through droplets and airborne aerosols. To prevent viral infection and reduce viral spread, vaccine strategies must elicit protective immunity in the airways. FcRn transfers IgG across epithelial barriers; we explore FcRn-mediated respiratory delivery of SARS-CoV-2 spike (S). A monomeric IgG Fc was fused to a stabilized S protein; the resulting S-Fc bound to S-specific antibodies (Ab) and FcRn. A significant increase in Ab responses was observed following the intranasal immunization of mice with S-Fc formulated in CpG as compared to the immunization with S alone or PBS. Furthermore, we intranasally immunize adult or aged mice and hamsters with S-Fc. A significant reduction of virus replication in nasal turbinate, lung, and brain was observed following nasal challenges with SARS-CoV-2, including Delta and Omicron variants. Intranasal immunization also significantly reduced viral transmission between immunized and naive hamsters. Protection was mediated by nasal IgA, serum-neutralizing Abs, tissue-resident memory T cells, and bone marrow S-specific plasma cells. Hence FcRn delivers an S-Fc antigen effectively into the airway and induces protection against SARS-CoV-2 infection and transmission. Based on these findings, FcRn-targeted non-invasive respiratory immunizations are superior strategies for preventing highly contagious respiratory viruses from spreading.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Galya V. Klink", - "author_inst": "IITP RAS" - }, - { - "author_name": "Daria M. Danilenko", - "author_inst": "Smorodintsev Research Institute of Influenza" - }, - { - "author_name": "Andrey B. Komissarov", - "author_inst": "Smorodintsev Research Institute for Influenza" - }, - { - "author_name": "Nikita Yolshin", - "author_inst": "Smorodintsev Research Institute of Influenza" - }, - { - "author_name": "Olga V. Shneider", - "author_inst": "Smorodintsev Research Institute of Influenza" - }, - { - "author_name": "Sergey Shcherbak", - "author_inst": "City Hospital 40" - }, - { - "author_name": "Elena Nabieva", - "author_inst": "IITP RAS" - }, - { - "author_name": "Nikita Shvyrev", - "author_inst": "HSE University" - }, - { - "author_name": "Nadezhda Konovalova", - "author_inst": "Smorodintsev Research Institute of Influenza" - }, - { - "author_name": "Alyona Zheltukhina", - "author_inst": "Smorodintsev Research Institute of Influenza" + "author_name": "Weizhong Li", + "author_inst": "Division of Immunology, VA-MD College of Veterinary Medicine" }, { - "author_name": "Artem Fadeev", - "author_inst": "Smorodintsev Research Institute of Influenza" + "author_name": "Tao Wang", + "author_inst": "Division of Immunology, VA-MD College of Veterinary Medicine" }, { - "author_name": "Kseniya Komissarova", - "author_inst": "Smorodintsev Research Institute of Influenza" + "author_name": "Arunraj Mekhemadhom Rajendrakumar", + "author_inst": "Division of Immunology, VA-MD College of Veterinary Medicine, Animal Parasitic Diseases Laboratory, ARS, United States Department of Agriculture, Beltsville, MD" }, { - "author_name": "Andrey Ksenafontov", - "author_inst": "Smorodintsev Research Institute of Influenza" + "author_name": "Gyanada Acharya", + "author_inst": "Division of Immunology, VA-MD College of Veterinary Medicine" }, { - "author_name": "Tamila Musaeva", - "author_inst": "Smorodintsev Research Institute of Influenza" + "author_name": "Zizhen Miao", + "author_inst": "Division of Immunology, VA-MD College of Veterinary Medicine" }, { - "author_name": "Veronica Eder", - "author_inst": "Smorodintsev Research Institute of Influenza" + "author_name": "Berin P Varghese", + "author_inst": "Division of Immunology, VA-MD College of Veterinary Medicine" }, { - "author_name": "Maria Pisareva", - "author_inst": "Smorodintsev Research Institute of Influenza" + "author_name": "Hailiang Yu", + "author_inst": "Division of Immunology, VA-MD College of Veterinary Medicine" }, { - "author_name": "Petr Nekrasov", - "author_inst": "Smorodintsev Research Institute of Influenza" + "author_name": "Bibek Dhakal", + "author_inst": "Division of Immunology, VA-MD College of Veterinary Medicine" }, { - "author_name": "Vladimir Shchur", - "author_inst": "HSE University" + "author_name": "Tanya LeRoith", + "author_inst": "Virginia Tech: Virginia Polytechnic Institute and State University" }, { - "author_name": "Georgii A Bazykin", - "author_inst": "Skoltech" + "author_name": "Wenbin Tuo", + "author_inst": "Animal Parasitic Diseases Laboratory, ARS, United States Department of Agriculture, Beltsville, MD 20705" }, { - "author_name": "Dmitry Lioznov", - "author_inst": "Smorodintsev Research Institute of Influenza" + "author_name": "Xiaoping Zhu", + "author_inst": "VA-MD College of Veterinary Medicine, University of Maryland" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.11.23.517706", @@ -185153,39 +184952,87 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2022.11.21.517338", - "rel_title": "Ultrasound treatment inhibits SARS-CoV-2 in vitro infectivity", - "rel_date": "2022-11-21", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.11.21.517338", - "rel_abs": "BackgroundCOVID-19 (coronavirus disease 2019) is a disease caused by infection with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), affecting millions of people worldwide, with a high rate of deaths. The present study aims to evaluate ultrasound (US) as a physical method for virus inactivation.\n\nMaterials and methodsThe US-transductor was exposed to the SARS-CoV-2 viral solution for 30 minutes. Vero-E6 cells were infected with medium exposure or not with the US, using 3-12, 5-10, or 6-18MHz as frequencies applied. We performed confocal microscopy to determine virus infection and replicative process. Moreover, we detected the virus particles with a titration assay.\n\nResultsWe observed an effective infection of SARS-CoV-2 Wuhan, Delta, and Gamma strains in comparison with mock, an uninfected experimental group. The US treatment was able to inhibit the Wuhan strain in all applied frequencies. Interestingly, 3-12 and 6-18MHz did not inhibit SARS-CoV-2 delta and gamma variants infection, on the other hand, 5-10MHz was able to abrogate infection and replication in all experimental conditions.\n\nConclusionsThese results show that SARS-CoV-2 is susceptible to US exposure at a specific frequency 5-10MHz and could be a novel tool for reducing the incidence of SARS-CoV-2 infection.", - "rel_num_authors": 5, + "rel_doi": "10.1101/2022.11.19.22282551", + "rel_title": "Serologic Responses to COVID-19 Vaccination in Children with History of Multisystem Inflammatory Syndrome (MIS-C)", + "rel_date": "2022-11-20", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.19.22282551", + "rel_abs": "Understanding the serological responses to COVID-19 vaccination in children with history of MIS-C could inform vaccination recommendations. We prospectively enrolled five children hospitalized with MIS-C and measured SARS-CoV-2 binding IgG antibodies to spike protein variants longitudinally pre- and post-Pfizer-BioNTech BNT162b2 primary series COVID-19 vaccination. We found that SARS-CoV-2 variant cross-reactive IgG antibodies waned following acute MIS-C, but were significantly boosted with vaccination and maintained for at least 3 months. We then compared post-vaccination binding, pseudovirus neutralizing, and functional antibody-dependent cell-mediated cytotoxicity (ADCC) titers to the reference strain (Wuhan-hu-1) and Omicron variant (B.1.1.529) among previously healthy children (n=6) and children with history of MIS-C (n=5) or COVID-19 (n=5). Despite the breadth of binding antibodies elicited by vaccination in all three groups, pseudovirus neutralizing and ADCC titers were reduced to the Omicron variant. Vaccination after MIS-C or COVID-19 (hybrid immunity) conferred advantage in generating pseudovirus neutralizing and functional ADCC antibodies to Omicron.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Flavio Protasio Veras", - "author_inst": "University of Sao Paulo" + "author_name": "Maria A. Perez", + "author_inst": "Emory University" }, { - "author_name": "Ronaldo Martins", - "author_inst": "University of Sao Paulo" + "author_name": "Hui-Mien Hsiao", + "author_inst": "Emory University" }, { - "author_name": "Eurico Arruda", - "author_inst": "University of Sao Paulo" + "author_name": "Xuemin Chen", + "author_inst": "Emory University" }, { - "author_name": "Fernando Q Cunha", - "author_inst": "University of Sao Paulo" + "author_name": "Amber Kunkel", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Odemir M Bruno", - "author_inst": "University of Sao Paulo" + "author_name": "Nadine Baida", + "author_inst": "Emory University" + }, + { + "author_name": "Laila Hussaini", + "author_inst": "Emory University" + }, + { + "author_name": "Austin T. Lu", + "author_inst": "Emory University" + }, + { + "author_name": "Carol M. Kao", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Federico R. Laham", + "author_inst": "Arnold Palmer Hospital for Children" + }, + { + "author_name": "David A. Hunstad", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Yajira Beltran", + "author_inst": "Arnold Palmer Hospital for Children" + }, + { + "author_name": "Teresa A. Hammett", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Shana Godfred-Cato", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Ann Chahroudi", + "author_inst": "Emory University" + }, + { + "author_name": "Evan J. Anderson", + "author_inst": "Emory University" + }, + { + "author_name": "Ermias Belay", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Christina A. Rostad", + "author_inst": "Emory University School of Medicine" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "biophysics" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.11.19.22282525", @@ -186911,43 +186758,63 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.11.16.22282406", - "rel_title": "Special Olympics global report on COVID-19 vaccination and reasons not to vaccinate among adults with intellectual disabilities", + "rel_doi": "10.1101/2022.11.18.22282501", + "rel_title": "Long-term temporal trends in incidence rate and case fatality of sepsis and COVID-19-related sepsis: nationwide registry study", "rel_date": "2022-11-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.16.22282406", - "rel_abs": "IntroductionThe COVID-19 pandemic has disproportionately affected people with intellectual disabilities worldwide. The objective of this study was to identify global rates of COVID-19 vaccination and reasons not to vaccinate among adults with intellectual disabilities (ID) associated with country economic income levels.\n\nMethodsThe Special Olympics COVID-19 online survey was administered in January-February 2022 to adults with ID from 138 countries. Descriptive analyses of survey responses include 95% margins of error. Logistic regression and Pearson Chi-squared tests were calculated to assess associations with predictive variables for vaccination using R 4.1.2 software.\n\nResultsParticipants (n=3560) represented 18 low (n=410), 35 lower-middle (n=1182), 41 upper-middle (n=837), and 44 high (n=1131) income countries. Globally, 76% (74.8-77.6%) received a COVID-19 vaccination while 49.5% (47.9-51.2%) received a COVID-19 booster. Upper-middle (93% (91.2-94.7%)) and high-income country (94% (92.1-95.0%)) participants had the highest rates of vaccination while low-income countries had the lowest rates (38% (33.3-42.7%)). In multivariate regression models, country economic income level (OR = 3.12, 95% CI [2.81, 3.48]), age (OR = 1.04, 95% CI [1.03, 1.05]), and living with family (OR = 0.70, 95% CI [0.53, 0.92]) were associated with vaccination. Among LLMICs, the major reason for not vaccinating was lack of access (41.2% (29.5-52.9%)). Globally, concerns about side effects (42%, (36.5-48.1%)) and parent/guardian not wanting the adult with ID to vaccinate (32% (26.1-37.0%)) were the most common reasons for not vaccinating.\n\nConclusionAdults with ID from low and low-middle income countries reported fewer COVID-19 vaccinations, suggesting reduced access and availability of resources in these countries. Globally, COVID-19 vaccination levels among adults with ID were higher than the general population. Interventions should address the increased risk of infection for those in congregate living situations and family caregiver apprehension to vaccinate this high-risk population.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.18.22282501", + "rel_abs": "ImportanceSepsis is one of the leading causes of morbidity and mortality. The majority of sepsis cases is attributed to bacterial infections, but virus infections can also induce sepsis. Conflicting results in incidence rates and case fatality trends of sepsis is reported, and how the COVID-19 pandemic influenced these trends are unknown.\n\nObjectiveTo estimate temporal trends in incidence rate and case fatality during a 14-year period from 2008 through 2021, and to assess possible shifts in these trends during the COVID-19 pandemic.\n\nDesignA nationwide longitudinal registry study using ICD-10 discharge codes to identify sepsis.\n\nSettingAll Norwegian hospitals from 2008 through 2021.\n\nParticipantsAll sepsis cases included 317.705 patients and of these, 222.832 had a first sepsis episode.\n\nMain outcomes and measuresAnnual age-standardized incidence rates with 95% confidence intervals (CI). Poisson regression was used to estimate changes in incidence rates across time, and logistic regression was used to estimate odds ratios for in-hospital death.\n\nResultsAmong 12.619.803 adult hospitalizations, 317.705 (2.5%) patients met the sepsis criteria and 222.832 (70.0%) had a first sepsis episode. In the period 2009-2019, the annual incidence rate for a first sepsis episode was stable (incidence rate ratio per year, 0.999; 95% CI, 0.994-1.004), whereas for all sepsis the incidence rate increased by 15.5% during the period (annual incidence rate ratio, 1.013; 95% CI 1.007-1.019). During the COVID-19 pandemic, the incidence rate ratio for a first sepsis was 0.877 (95% CI, 0.829-0.927) in 2020 and 0.929 (95% CI, 0.870-0.992) in 2021, and for all sepsis it was 0.870 (95% CI, 0.810-0.935) in 2020 and 0.908 (95% CI, 0.840-0.980) in 2021, compared to the previous 11-year period. In-hospital deaths declined in the period 2009-2019 (odds ratio per year, 0.954 [95% CI,0.950-0.958]), whereas deaths increased during the COVID-19 pandemic in 2020 (odds ratios, 1.061 [95% CI 1.001-1.124] and in 2021 odds ratio (1.164 [95% CI, 1.098-1.233]).\n\nConclusion and relevanceWe found a stable incidence rate of a first sepsis episode during the years 2009-2019. However, the increasing burden of all sepsis admissions indicates that sepsis awareness with updated guidelines and education must continue.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSHas there been a change in incidence rate and case fatality of sepsis over the past decade, and how did the COVID-19 pandemic influence sepsis incidence rates and in-hospital mortality?\n\nFindingsIn this nationwide longitudinal registry study the incidence rate of all sepsis episodes increased and the incidence rate of a first sepsis episode was stable during the period 2009-2019, whereas in 2020 and 2021, the incidence rate of a first and all sepsis episodes was lower than in the preceding 11-year period. Case fatality risk declined from 2009 to 2019, but increased somewhat in 2020 and 2021, when 9.7% of first sepsis cases were identified as COVID-19 related sepsis.\n\nMeaningDespite a stable incidence rate of first-time sepsis admissions over time, the burden of sepsis is rising due to an increased rate of patients admitted multiple times with sepsis. The COVID-19 pandemic have had an impact on sepsis incidence rate and hospital mortality and needs further evaluation.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Andrew Ethan Lincoln", - "author_inst": "Georgetown University Medical Center" + "author_name": "Nina V Skei", + "author_inst": "Norwegian University of Science and Technology" }, { - "author_name": "Alicia M Dixon-Ibarra", - "author_inst": "Special Olympics" + "author_name": "Tom Ivar Nilsen", + "author_inst": "Norwegian University of Science and Technology" }, { - "author_name": "John P Hanley", - "author_inst": "Special Olympics" + "author_name": "Siri Tandberg Knoop", + "author_inst": "University of Bergen" }, { - "author_name": "Ashlyn L Smith", - "author_inst": "Special Olympics" + "author_name": "Hallie Prescott", + "author_inst": "University of Michigan" }, { - "author_name": "Kiki Martin", - "author_inst": "Special Olympics" + "author_name": "Stian Lydersen", + "author_inst": "Norwegian University of Science and Technology" }, { - "author_name": "Alicia Bazzano", - "author_inst": "Special Olympics" + "author_name": "Randi Marie Mohus", + "author_inst": "Norwegian University of Science and Technology" + }, + { + "author_name": "Alen Brkic", + "author_inst": "Norwegian University of Science and Technology" + }, + { + "author_name": "Kristin Vardheim Liyanarachi", + "author_inst": "Norwegian University of Science and Technology" + }, + { + "author_name": "Erik Solligaard", + "author_inst": "Norwegian University of Science and Technology" + }, + { + "author_name": "Jan Kristian Damaas", + "author_inst": "Norwegian University of Science and Technology" + }, + { + "author_name": "Lise Tuset Gustad", + "author_inst": "Norwegian University of Science and Technology" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.11.18.22282459", @@ -188709,39 +188576,47 @@ "category": "rehabilitation medicine and physical therapy" }, { - "rel_doi": "10.1101/2022.11.11.22282032", - "rel_title": "COVID Seq as Laboratory Developed Test (LDT) for diagnosis of SARS-CoV-2 Variants of Concern (VOC)", + "rel_doi": "10.1101/2022.11.07.22281957", + "rel_title": "Clinical Evaluation of the GeneXpert(R) Xpert(R) Xpress SARS-CoV-2/Flu/RSV PLUS Combination Test", "rel_date": "2022-11-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.11.22282032", - "rel_abs": "Rapid classification and detection of SARS-CoV-2 variants have been critical in comprehending the viruss transmission dynamics. Clinical manifestation of the infection is influenced by comorbidities such as age, immune status, diabetes, and the infecting variant. Thus, clinical management may differ for new variants. For example, some monoclonal antibody treatments are variant-specific. Yet, an FDA-approved test for detecting the SARS-CoV-2 variant is unavailable. A laboratory-developed test (LDT) remains a viable option for reporting the infecting variant for clinical intervention or epidemiological purposes. Accordingly, we have validated the Illumina COVID-Seq assay as an LDT according to the guidelines prescribed by the College of American Pathologists (CAP) and Clinical Laboratory Improvement Amendments (CLIA). The limit of detection (LOD) of this test is Ct<30 ([~]15 viral copies) and >200X genomic coverage, and the test is 100% specific in the detection of existing variants. The test demonstrated 100% precision in inter-day, intra-day, and intra-laboratory reproducibility studies. It is also 100% accurate, defined by reference strain testing and split sample testing with other CLIA laboratories. Advanta Genetics LDT COVID Seq has been reviewed by CAP inspectors and is under review by FDA for Emergency Use Authorization.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.07.22281957", + "rel_abs": "The GeneXpert(R) Xpert(R) Xpress SARS-CoV-2/Flu/RSV PLUS combination test (PLUS Assay) received Health Canada approval in January 2022. The PLUS Assay is similar to the SARS-CoV-2/Flu/RSV combination test, with modifications to improve assay robustness against circulating and emerging variants. The performance characteristics of the PLUS Assay were assessed at the Lakeridge Health Oshawa Hospital Centre and the National Microbiology Laboratory of Canada. The PLUS Assay was directly compared to the SARS-CoV-2/Flu/RSV combination test using SARS-CoV-2 culture from five variants and remnant clinical specimens collected across the COVID-19 pandemic. This included 50 clinical specimens negative for all pathogens, 110 clinical specimens positive for SARS-CoV-2, Influenza A, Influenza B, RSVA, and/or RSVB and an additional 11 mixed samples to screen for target interactions. The PLUS Assay showed a high percent agreement with the widely used SARS-CoV-2/Flu/RSV combination test. Based on these findings, the PLUS Assay and the Xpert SARS-CoV-2/Flu/RSV combination test results are largely consistent with no observed difference in sensitivity, specificity, or time to result when challenged with various SARS-CoV-2 variants. The reported Ct values provided by the new PLUS Assay was also unchanged, with the exception of a possible 1-2 decrease reported Ct for RSVA across a limited sample size.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Rob E. Carpenter", - "author_inst": "University of Texas at Tyler, 3900 University Boulevard, Tyler, Texas 75799, USA" + "author_name": "Grant Johnson", + "author_inst": "Lakeridge Health, Laboratory Medicine and Infection Prevention and Control; Ontario Tech University" }, { - "author_name": "Vaibhav Kumar Tamrakar", - "author_inst": "ICMR-National Institute of Research in Tribal Health, Jabalpur M.P. India" + "author_name": "Branden S.J. Gregorchuk", + "author_inst": "Public Health Agency of Canada, National HIV and Retrovirology Laboratories, National Microbiology Laboratory Branch, JC Wilt Infectious Diseases Research Centr" }, { - "author_name": "Emily Brown", - "author_inst": "Advanta Genetics, 10935 CR 159 Tyler, Texas 75703, USA" + "author_name": "Arek Zubrzycki", + "author_inst": "Lakeridge Health, Laboratory Medicine and Infection Prevention and Control" }, { - "author_name": "Sadia Almas", - "author_inst": "Advanta Genetics, 10935 CR 159 Tyler, Texas 75703, USA" + "author_name": "Kurt Kolsun", + "author_inst": "Public Health Agency of Canada, National HIV and Retrovirology Laboratories, National Microbiology Laboratory Branch, JC Wilt Infectious Diseases Research Centr" }, { - "author_name": "Rahul Sharma", - "author_inst": "Advanta Genetics, 10935 CR 159 Tyler, Texas 75703, USA" + "author_name": "Adrienne F.A. Meyers", + "author_inst": "Public Health Agency of Canada, National HIV and Retrovirology Laboratories, National Microbiology Laboratory Branch, JC Wilt Infectious Diseases Research Centr" + }, + { + "author_name": "Paul A. Sandstorm", + "author_inst": "Public Health Agency of Canada, National HIV and Retrovirology Laboratories, National Microbiology Laboratory Branch, JC Wilt Infectious Diseases Research Centr" + }, + { + "author_name": "Michael G. Becker", + "author_inst": "Public Health Agency of Canada, National HIV and Retrovirology Laboratories, National Microbiology Laboratory Branch, JC Wilt Infectious Diseases Research Centr" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.11.12.22282242", @@ -190623,67 +190498,71 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.11.07.22282030", - "rel_title": "Neurologic sequalae of COVID-19 are determined by immunologic imprinting from previous Coronaviruses.", + "rel_doi": "10.1101/2022.11.08.22282097", + "rel_title": "The interface between SARS-CoV-2 and non-communicable diseases (NCDs) in a high HIV/TB burden district level hospital setting, Cape Town, South Africa", "rel_date": "2022-11-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.07.22282030", - "rel_abs": "Coronavirus disease 2019 (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), remains a global public health emergency. Although SARS-CoV-2 is primarily a respiratory pathogen, extra-respiratory organs, including the central nervous system (CNS), can also be affected. Neurologic symptoms have been observed not only during acute SARS-CoV-2 infection, but also at distance from respiratory disease, also known as long-COVID or neurological post-acute sequelae of COVID-19 (neuroPASC). The pathogenesis of neuroPASC is not well understood, but hypotheses include SARS-CoV-2-induced immune dysfunctions, hormonal dysregulations, and persistence of SARS-CoV-2 reservoirs. In this study, we used a high throughput systems serology approach to dissect the humoral response to SARS-CoV-2 (and other common Coronaviruses - 229E, HKU1, NL63, OC43) in the serum and cerebrospinal fluid (CSF) from 112 infected individuals who developed or did not develop neuroPASC. Unique SARS-CoV-2 humoral profiles were observed in the CSF of neuroPASC. All antibody isotypes (IgA, IgM, IgA) and subclasses (IgA1-2; IgG1-4) were detected in serum, whereas CSF was characterized by focused IgG1 (and absence of IgM). These data argue in favor of compartmentalized brain-specific responses against SARS-CoV-2 through selective transfer of antibodies from the serum to the CSF across the blood-brain-barrier, rather than intrathecal synthesis, where more diversity in antibody classes/subclasses would be expected. Moreover, compared to individuals who did not develop post-acute neurological complications following infection (n=94), those with neuroPASC (n=18) exhibited attenuated systemic antibody responses against SARS-CoV-2, characterized by decreased capacity to activate antibody-dependent complement deposition (ADCD), NK cell activation (ADNKA) and to bind Fc{gamma} receptors. However, surprisingly, neuroPASC showed significantly expanded antibody responses to other common Coronaviruses, including 229E, HKU1, NL63, and OC43. This biased humoral activation across coronaviruses was particularly enriched in neuroPASC individuals with poor outcome, suggesting an original antigenic sin (or immunologic imprinting), where pre-existing immune responses against related viruses shape the response to current infection, as a key prognostic marker of neuroPASC disease. Overall, these findings point to a pathogenic role for compromised anti-SARS-CoV-2 responses in the CSF, likely resulting in incomplete virus clearance from the brain and persistent neuroinflammation, in the development of post-acute neurologic complications of SARS-CoV-2 infection.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.08.22282097", + "rel_abs": "BackgroundCOVID-19 experiences on noncommunicable diseases (NCDs) from district-level hospital settings during waves I and II are scarcely documented. The aim of this study is to investigate the NCDs associated with COVID-19 severity and mortality in a district-level hospital with a high HIV/TB burden.\n\nMethodsThis was a retrospective observational study that compared COVID-19 waves I and II at Khayelitsha District Hospital in Cape Town, South Africa. COVID-19 adult patients with a confirmed SARS-CoV-2 polymerase chain reaction (PCR) or positive antigen test were included. In order to compare the inter wave period, clinical and laboratory parameters on hospital admission of noncommunicable diseases, the Student t-test or Mann-Whitney U for continuous data and the X2 test or Fishers Exact test for categorical data were used. The role of the NCD subpopulation on COVID-19 mortality was determined using latent class analysis (LCA).\n\nFindingsAmong 560 patients admitted with COVID-19, patients admitted during wave II were significantly older than those admitted during wave I. The most prevalent comorbidity patterns were hypertension (87%), diabetes mellitus (65%), HIV/AIDS (30%), obesity (19%), Chronic Kidney Disease (CKD) (13%), Congestive Cardiac Failure (CCF) (8.8%), Chronic Obstructive Pulmonary Disease (COPD) (3%), cerebrovascular accidents (CVA)/stroke (3%), with similar prevalence in both waves except HIV status [(23% vs 34% waves II and I, respectively), p = 0.022], obesity [(52% vs 2.5%, waves II and I, respectively), p <0.001], previous stroke [(1% vs 4.1%, waves II and I, respectively), p = 0.046]. In terms of clinical and laboratory findings, our study found that wave I patients had higher haemoglobin and HIV viral loads. Wave II, on the other hand, had statistically significant higher chest radiography abnormalities, fraction of inspired oxygen (FiO2), and uraemia. The adjusted odds ratio for death vs discharge between waves I and II was similar (0.94, 95%CI: 0.84-1.05). Wave I had a longer average survival time (8.0 vs 6.1 days) and a shorter average length of stay among patients discharged alive (9.2 vs 10.7 days). LCA revealed that the cardiovascular phenotype had the highest mortality, followed by diabetes and CKD phenotypes. Only Diabetes and hypertension phenotypes had the lowest mortality.\n\nConclusionEven though clinical and laboratory characteristics differed significantly between the two waves, mortality remained constant. According to LCA, the cardiovascular, diabetes, and CKD phenotypes had the highest death probability.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Marianna Spatola", - "author_inst": "Ragon Institute of MGH, MIT and Harvard, Cambridge, USA" + "author_name": "Ayanda Trevor Mnguni", + "author_inst": "Stellenbosch University - Tygerberg Campus: Stellenbosch University Faculty of Medicine and Health Sciences" }, { - "author_name": "Nadege Nziza", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" + "author_name": "Denzil Schietekat", + "author_inst": "Khayelitsha Hospital" }, { - "author_name": "Yixiang Deng", - "author_inst": "Ragon Institute of mGH, MIT and Harvard; Massachusetts Institute of Technology" + "author_name": "Nabilah Ebrahim", + "author_inst": "Khayelitsha Hospital" }, { - "author_name": "Wonyeong Jung", - "author_inst": "Ragon Institute of MGH, MIT and Harvard; Massachusetts Institute of Technology" + "author_name": "Nawhaal Sonday", + "author_inst": "Khayelitsha Hospital" }, { - "author_name": "Dansu Yuan", - "author_inst": "Ragon Institute of MGH, MIT and Harvard, Cambridge, USA" + "author_name": "Nicholas Boliter", + "author_inst": "Khayelitsha Hospital" + }, + { + "author_name": "Neshaad Schrueder", + "author_inst": "Khayelitsha Hospital" }, { - "author_name": "Alessandro Dinoto", - "author_inst": "Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona" + "author_name": "Shiraaz Gabriels", + "author_inst": "Khayelitsha Hospital" }, { - "author_name": "Silvia Bozzetti", - "author_inst": "Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona" + "author_name": "Annibale Cois", + "author_inst": "Stellenbosch University - Tygerberg Campus: Stellenbosch University Faculty of Medicine and Health Sciences" }, { - "author_name": "Vanessa Chiodega", - "author_inst": "Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona; Department of Neurology/Stroke Unit, San Maurizio hospital," + "author_name": "Jacques L. Tamuzi", + "author_inst": "Stellenbosch University - Tygerberg Campus: Stellenbosch University Faculty of Medicine and Health Sciences" }, { - "author_name": "Sergio Ferrari", - "author_inst": "Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona" + "author_name": "Yamanya Tembo", + "author_inst": "University of Cape Town Faculty of Health Sciences" }, { - "author_name": "Douglas A Lauffenburger", - "author_inst": "Massachusetts Institute of Technology, Cambridge, MA, USA" + "author_name": "Mary-Ann Davies", + "author_inst": "University of Cape Town Faculty of Health Sciences" }, { - "author_name": "Sara Mariotto", - "author_inst": "Neurology Unit, Department of Neuroscience, Biomedicine and Movement Sciences, University of Verona, Verona" + "author_name": "Rene English", + "author_inst": "Stellenbosch University - Tygerberg Campus: Stellenbosch University Faculty of Medicine and Health Sciences" }, { - "author_name": "Galit Alter", - "author_inst": "Ragon Institute of MGH, MIT and Harvard" + "author_name": "Peter S. Nyasulu", + "author_inst": "Stellenbosch University Faculty of Medicine and Health Sciences" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.11.06.22282006", @@ -192273,53 +192152,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.11.04.22281943", - "rel_title": "Fine scale human mobility changes in 26 US cities in 2020 in response to the COVID-19 pandemic were associated with distance and income", + "rel_doi": "10.1101/2022.11.06.22281984", + "rel_title": "The relationship between controllability, optimal testing resource allocation, and incubation-latent period mismatch as revealed by COVID-19", "rel_date": "2022-11-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.04.22281943", - "rel_abs": "Human mobility patterns changed greatly due to the COVID-19 pandemic. Despite many analyses investigating general mobility trends, there has been less work characterising changes in mobility on a fine spatial scale and developing frameworks to model these changes. We analyse zip code-level mobility data from 26 US cities between February 2 - August 31, 2020. We use Bayesian models to characterise the initial decrease in mobility and mobility patterns between June - August at this fine spatial scale. There were similar temporal trends across cities but large variations in the magnitude of mobility reductions. Long-distance routes and higher-income subscribers, but not age, were associated with greater mobility reductions. At the city level, mobility rates around early April, when mobility was lowest, and over summer showed little association with non-pharmaceutical interventions or case rates. Changes in mobility patterns lasted until the end of the study period, despite overall numbers of trips recovering to near baseline levels in many cities.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.06.22281984", + "rel_abs": "The severe shortfall in testing supplies during the initial COVID-19 outbreak and ensuing struggle to manage the pandemic have affirmed the critical importance of optimal supply-constrained resource allocation strategies for controlling novel disease epidemics. To address the challenge of constrained resource optimization for managing diseases with complications like pre- and asymptomatic transmission, we develop an integro partial differential equation compartmental disease model which incorporates realistic latent, incubation, and infectious period distributions along with limited testing supplies for identifying and quarantining infected individuals. Our model overcomes the limitations of typical ordinary differential equation compartmental models by decoupling symptom status from model compartments to allow a more realistic representation of symptom onset and presymptomatic transmission. To analyze the influence of these realistic features on disease controllability, we find optimal strategies for reducing total infection sizes that allocate limited testing resources between clinical testing, which targets symptomatic individuals, and non-clinical testing, which targets non-symptomatic individuals. We apply our model not only to the original, delta, and omicron COVID-19 variants, but also to generically parameterized disease systems with varying mismatches between latent and incubation period distributions, which permit varying degrees of presymptomatic transmission or symptom onset before infectiousness. We find that factors that decrease controllability generally call for reduced levels of non-clinical testing in optimal strategies, while the relationship between incubation-latent mismatch, controllability, and optimal strategies is complicated. In particular, though greater degrees of presymptomatic transmission reduce disease controllability, they may increase or decrease the role of non-clinical testing in optimal strategies depending on other disease factors like transmissibility and latent period length. Importantly, our model allows a spectrum of diseases to be compared within a consistent framework such that lessons learned from COVID-19 can be transferred to resource constrained scenarios in future emerging epidemics and analyzed for optimality.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Rohan Arambepola", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Kathryn L Schaber", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Catherine Schluth", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Angkana T Huang", - "author_inst": "Department of Genetics, Cambridge University" - }, - { - "author_name": "Alain B Labrique", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" - }, - { - "author_name": "Shruti H Mehta", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Jeffery Demers", + "author_inst": "Center for Advanced Systems Understanding (CASUS), Gorlitz, Germany and Dept. of Biology, University of Maryland, College Park, MD, USA" }, { - "author_name": "Sunil S Solomon", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "William F Fagan", + "author_inst": "Dept. of Biology, University of Maryland, College Park, MD, USA" }, { - "author_name": "Derek A T Cummings", - "author_inst": "Department of Biology and the Emerging Pathogens Institute, University of Florida" + "author_name": "Sryia Potluri", + "author_inst": "Dept. of Biology, University of Maryland, College Park, MD, USA" }, { - "author_name": "Amy Wesolowski", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Justin M Calabrese", + "author_inst": "Center for Advanced Systems Understanding (CASUS), Gorlitz, Germany / Dept. of Biology, University of Maryland, College Park, MD, USA /Dept. of Ecological Mode" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -193895,79 +193754,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.11.02.22281821", - "rel_title": "Screening COVID-19 by Swaasa AI Platform using cough sounds: A cross-sectional study", - "rel_date": "2022-11-04", + "rel_doi": "10.1101/2022.10.31.22281769", + "rel_title": "Time intervals between COVID-19 cases, and more severe outcomes", + "rel_date": "2022-11-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.11.02.22281821", - "rel_abs": "The Advent of Artificial Intelligence (AI) has led to the use of auditory data for detecting various diseases, including COVID-19. SARS-CoV-2 infection has claimed more than 6 million lives till date and hence, needs a robust screening technique to control the disease spread. In the present study we developed and validated the Swaasa AI platform for screening and prioritizing COVID-19 patients based on the signature cough sound and the symptoms presented by the subjects. The cough data records collected from 234 COVID-19 suspects were subjected to validate the convolutional neural network (CNN) architecture and tabular features-based algorithm. The likelihood of the disease was predicted by combining the final output obtained from both the models. In the clinical validation phase, Swaasa was found to be 75.54% accurate in detecting the likely presence of COVID-19 with 95.45% sensitivity and 73.46% specificity. The pilot testing of Swaasa was carried out on 183 presumptive COVID subjects, out of which 82 subjects were found to be positive for the disease by Swaasa. Among them, 58 subjects were truly COVID-19 positive, which corresponds to a Positive Predictive Value of 70.73%. The currently available rapid screening methods are very costly and require technical expertise, therefore a cost effective, remote monitoring tool would be very beneficial for preliminary screening of the potential COVID-19 subject.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.31.22281769", + "rel_abs": "A critical factor in infectious disease control is the risk of an outbreak overwhelming local healthcare capacity. The overall demand on healthcare services will depend on disease severity, but the precise timing and size of peak demand also depends on the time interval (or clinical time delay) between initial infection, and development of severe disease. A broader distribution of intervals may draw that demand out over a longer period, but have a lower peak demand. These interval distributions are therefore important in modelling trajectories of e.g. hospital admissions, given a trajectory of incidence. Conversely, as testing rates decline, an incidence trajectory may need to be inferred through the delayed, but relatively unbiased signal of hospital admissions.\n\nHealthcare demand has been extensively modelled during the COVID-19 pandemic, where localised waves of infection have imposed severe stresses on healthcare services. While the initial acute threat posed by this disease has since subsided from immunity buildup from vaccination and prior infection, prevalence remains high and waning immunity may lead to substantial pressures for years to come. In this work, then, we present a set of interval distributions, for COVID-19 cases and subsequent severe outcomes; hospital admission, ICU admission, and death. These may be used to model more realistic scenarios of hospital admissions and occupancy, given a trajectory of infections or cases.\n\nWe present a method for obtaining empirical distributions using COVID-19 outcomes data from Scotland between September 2020 and January 2022 (N = 31724 hospital admissions, N = 3514 ICU admissions, N = 8306 mortalities). We present separate distributions for individual age, sex, and deprivation of residing community. We show that, while the risk of severe disease following COVID-19 infection is substantially higher for the elderly or those residing in areas of high deprivation, the length of stay shows no strong dependence, suggesting that severe outcomes are equally severe across risk groups. As Scotland and other countries move into a phase where testing is no longer abundant, these intervals may be of use for retrospective modelling of patterns of infection, given data on severe outcomes.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Padmalatha P", - "author_inst": "Andhra Medical College" - }, - { - "author_name": "Gowrisree Rudraraju", - "author_inst": "Salcit Technologies" - }, - { - "author_name": "Narayana Rao Sripada", - "author_inst": "Salcit Technologies" - }, - { - "author_name": "Baswaraj Mamidgi", - "author_inst": "Salcit Technologies" - }, - { - "author_name": "Charishma Gottipulla", - "author_inst": "Salcit Technologies" - }, - { - "author_name": "Charan Jalukuru", - "author_inst": "Salcit Technologies" - }, - { - "author_name": "ShubhaDeepti Palreddy", - "author_inst": "Salcit Technologies" - }, - { - "author_name": "Nikhil kumar Reddy Bhoge", - "author_inst": "Salcit technologies" - }, - { - "author_name": "Priyanka Firmal", - "author_inst": "Salcit Technologies" - }, - { - "author_name": "Venkat Yechuri", - "author_inst": "Salcit Technologies" - }, - { - "author_name": "P V Sudhakar", - "author_inst": "Andhra Medical College" - }, - { - "author_name": "Devi Madhavi B", - "author_inst": "Andhra Medical College" - }, - { - "author_name": "Srinivas S", - "author_inst": "Andhra Medical College" - }, - { - "author_name": "K L Prasad K", - "author_inst": "Guntur Medical College" + "author_name": "Anthony J Wood", + "author_inst": "The University of Edinburgh" }, { - "author_name": "Niranjan Joshi", - "author_inst": "C-Camp" + "author_name": "Rowland Raymond Kao", + "author_inst": "University of Edinburgh" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.11.03.515010", @@ -195192,75 +194999,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.10.28.22281588", - "rel_title": "A novel hospital-at-home model for patients with COVID-19 built by a team of local primary care clinics and clinical outcomes: A multi-center retrospective cohort study", + "rel_doi": "10.1101/2022.10.30.22281600", + "rel_title": "The impact of the COVID-19 pandemic on the reporting of violence against children", "rel_date": "2022-10-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.28.22281588", - "rel_abs": "BackgroundHospital-at-home (HaH) care has been proposed as an alternative to inpatient care for patients with COVID-19. Previous reports were hospital-led and involved patients triaged at the hospitals. To reduce the burden on hospitals, we constructed a novel HaH care model organised by a team of local primary care clinics.\n\nMethodsWe conducted a multi-center retrospective cohort study of the COVID-19 patients who received our HaH care from Jan 1st to Mar 31st, 2022. Patients who were not able to be triaged for the need for hospitalization by the Health Center solely responsible for the management of COVID-19 patients in Osaka City were included. The primary outcome was receiving medical care beyond the HaH care defined as a composite outcome of any medical consultation, hospitalization, or death within 30 days from the initial treatment.\n\nResultsOf 382 eligible patients, 34 (9%) were triaged for hospitalization immediately after the initial visit. Of the remaining 348 patients followed up, 37 (11%) developed the primary outcome, while none died. Obesity, fever, and gastrointestinal symptoms at baseline were independently associated with an increased risk of needing medical care beyond the HaH care. A further 129 (37%) patients were managed online alone without home visit, and 170 (50%) required only one home visit in addition to online treatment.\n\nConclusionsThe HaH care model with a team of primary care clinics was able to triage patients with COVID-19 who needed immediate hospitalization without involving hospitals, and treated most of the remaining patients at home.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.30.22281600", + "rel_abs": "ObjectiveTo verify the impact (effect) of the COVID-19 pandemic on the rates of reporting of interpersonal violence against children aged 0-11 years old in Salvador, Bahia, from 2020 to 2021.\n\nMethodsThe study used two epidemiological approaches: a) temporal aggregation and b) an individual cross section, based on cases of interpersonal violence against children reported in SINAN from 2009 to 2021. Annual rates of reporting of interpersonal violence against children (per 10,000) and percentages were calculated according to different strata of each variable of interest. The temporal trend was analyzed using the simple linear regression method (R2=0.6955) applied to the rates from 2014 to 2019, the period in which they showed the most consistency.\n\nResultsThe rates of reporting of violence against children showed a large variation, with a mean of 4.7/10,000. In 2021, the rate was 7/10,000 (a 45.8% increase on the previous year). Regression analysis indicated a mean reduction of 0.337/10,000 a year, and expected rates of 4.62 and 4.28/10,000, respectively, for 2020 and 2021.\n\nConclusionThe occurrence of COVID-19 and, particularly, the increase in the number of reported cases of interpersonal violence against children in the second year of the pandemic in Bahia suggest that these events may be directly or indirectly related. More robust studies are needed to confirm this relationship.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Yasushi Tsujimoto", - "author_inst": "Oku Medical Clinic" - }, - { - "author_name": "Masanori Kobayashi", - "author_inst": "Kassai Medical Clinic" - }, - { - "author_name": "Tomohisa Oku", - "author_inst": "Oku Medical Clinic" - }, - { - "author_name": "Takahisa Ogawa", - "author_inst": "Oku Medical Clinic" - }, - { - "author_name": "Shinichi Yamadera", - "author_inst": "Nanohana Clinic" - }, - { - "author_name": "Masako Tsukamoto", - "author_inst": "Sagisu Naka Clinic" - }, - { - "author_name": "Noriya Matsuda", - "author_inst": "Matsuda Clinic" - }, - { - "author_name": "Morikazu Nishihira", - "author_inst": "Nishihira Clinic" - }, - { - "author_name": "Yu Terauchi", - "author_inst": "Terauchi Clinic" + "author_name": "Camila dos Santos Souza Andrade", + "author_inst": "Universidade Federal da Bahia" }, { - "author_name": "Takahiro Tanaka", - "author_inst": "Minato Clinic" + "author_name": "Maria da Concei\u00e7\u00e3o Nascimento COSTA", + "author_inst": "Universidade Federal da Bahia Instituto de Saude Coletiva" }, { - "author_name": "Yoshitaka Kawabata", - "author_inst": "Hinata Medical Clinic" + "author_name": "Leny Alves Bonfim TRAD", + "author_inst": "Universidade Federal da Bahia Instituto de Saude Coletiva" }, { - "author_name": "Yuki Miyamoto", - "author_inst": "Yoshiki Home Care Clinic" + "author_name": "Marcio Santos da NATIVIDADE", + "author_inst": "Universidade Federal da Bahia Instituto de Saude Coletiva" }, { - "author_name": "Yoshiki Morikami", - "author_inst": "Yoshiki Home Care Clinic" + "author_name": "Eliene dos Santos de JESUS", + "author_inst": "Universidade Federal da Bahia Instituto de Saude Coletiva" }, { - "author_name": "- The KISA2-Tai Osaka", - "author_inst": "" + "author_name": "Rita de C\u00e1ssia Oliveira de CARVALHO-SAUER", + "author_inst": "Universidade Federal da Bahia Instituto de Saude Coletiva" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "primary care research" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.10.27.22281609", @@ -197266,99 +197041,63 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2022.10.26.22278866", - "rel_title": "Experiences in the use of multiple doses of convalescent plasma in critically ill patients with COVID-19", + "rel_doi": "10.1101/2022.10.26.513886", + "rel_title": "Complex changes in serum protein levels upon recovery from SARS-CoV2 infection", "rel_date": "2022-10-27", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.26.22278866", - "rel_abs": "At the beginning of the SARS-CoV-2 pandemic, transfusion of COVID-19 convalescent plasma (CCP) was considered as one of the possibilities to help severe patients to overcome COVID-19 disease. The use of CCP has been controversial as its effectiveness depends on many variables from the plasma donor and the COVID-19 patient, for example, time of convalescence or symptoms onset. This was a feasibility study assessing the safety of multiple doses of CCP in mechanically ventilated intubated patients with respiratory failure due to COVID-19. Thirty (30) patients with severe respiratory failure, in ICU, with invasive mechanical ventilation received up to 5 doses of 300 to 600 ml of CP on alternate days (0,2,4,6 and 8) until extubation, futility, or death. Nineteen patients received five doses, seven received four, and four had 2 or 3 doses. On day 28 of follow-up, 57% of patients recovered and were at home and the long-term mortality observed was 27%. The ten severe adverse events reported in the study were unrelated to CCP transfusion. This study suggests that transfusion of multiple doses of convalescent plasma (CP) is safe. This strategy may represent an option to use in new studies, given the potential benefit of CCP transfusions in the early stage of infection in unvaccinated populations and in settings where monoclonal antibodies or antivirals are contraindicated or not available.\n\nSummary boxO_LITransfusion of multiple doses (up to 5 doses) of 300-600 ml of convalescent plasma from COVID-19 recovered patients is safe as it does not induce more severe effects than a single dose.\nC_LIO_LIIndependent of the number of transfused doses, most patients had detectable levels of total and neutralizing antibodies in plasma.\nC_LIO_LIFuture studies are needed to determine if multiple transfusion doses are more efficient in preventing severity than a single dose.\nC_LI", - "rel_num_authors": 20, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.26.513886", + "rel_abs": "The COVID-19 pandemic, triggered by severe acute respiratory syndrome coronavirus 2, has affected millions of people worldwide. Much research has been dedicated to our understanding of COVID-19 disease heterogeneity and severity, but less is known about recovery associated changes. To address this gap in knowledge, we quantified the proteome from serum samples from 29 COVID-19 convalescents and 29 age-, race-, and sex-matched healthy controls. Samples were acquired within the first months of the pandemic. Many proteins from pathways known to change during acute COVID-19 illness, such as from the complement cascade, coagulation system, inflammation and adaptive immune system, had returned to levels seen in healthy controls. In comparison, we identified 22 and 15 proteins with significantly elevated and lowered levels, respectively, amongst COVID-19 convalescents compared to healthy controls. Some of the changes were similar to those observed for the acute phase of the disease, i.e. elevated levels of proteins from hemolysis, the adaptive immune systems, and inflammation. In contrast, some alterations opposed those in the acute phase, e.g. elevated levels of CETP and APOA1 which function in lipid/cholesterol metabolism, and decreased levels of proteins from the complement cascade (e.g. C1R, C1S, and VWF), the coagulation system (e.g. THBS1 and VWF), and the regulation of the actin cytoskeleton (e.g. PFN1 and CFL1) amongst COVID-19 convalescents. We speculate that some of these shifts might originate from a transient decrease in platelet counts upon recovery from the disease. Finally, we observed race-specific changes, e.g. with respect to immunoglobulins and proteins related to cholesterol metabolism.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Ricardo Aguilar", - "author_inst": "Complejo Hospitalario Metropolitano Arnulfo Arias Madrid, Caja de Seguro Social, Panama, Panama" - }, - { - "author_name": "Sandra L Lopez-Verges", - "author_inst": "Gorgas Memorial Institute of Health Studies" - }, - { - "author_name": "Anarellys Quintana", - "author_inst": "Hospital Santo Tomas, Panama, Panama" - }, - { - "author_name": "Johanna Morris", - "author_inst": "Sociedad Panamena de Hematologia, Panama, Panama" - }, - { - "author_name": "Lineth Lopez", - "author_inst": "Complejo Hospitalario Metropolitano, Caja de Seguro Social, Panama, Panama" - }, - { - "author_name": "Ana Cooke", - "author_inst": "Complejo Hospitalario Metropolitano, Caja de Seguro Social, Panama, Panama" - }, - { - "author_name": "Dimas Quiel", - "author_inst": "Complejo Hospitalario Metropolitano, Caja de Seguro Social, Panama, Panama" - }, - { - "author_name": "Nathalie Buitron", - "author_inst": "Hospital Punta Pacifica" + "author_name": "Smruti Pushalkar", + "author_inst": "New York University" }, { - "author_name": "Yaseikiry Perez", - "author_inst": "Complejo Hospitalario Metropolitano, Caja de Seguro Social, Panama, Panama" + "author_name": "Shaohuan Wu", + "author_inst": "New York University" }, { - "author_name": "Lesbia Lobo", - "author_inst": "Complejo Hospitalario Metropolitano, Caja de Seguro Social" + "author_name": "Shuvadeep Maity", + "author_inst": "BITS Pilani" }, { - "author_name": "Yaneth Pitti", - "author_inst": "Gorgas Memorial Institute of Health Studies" + "author_name": "Matthew Pressler", + "author_inst": "NEW YORK UNIVERSITY" }, { - "author_name": "Yamilka Yamiselle Diaz", - "author_inst": "Gorgas Memorial Institute for Health Studies" + "author_name": "Justin Rendleman", + "author_inst": "NEW YORK UNIVERSITY" }, { - "author_name": "Lisseth Saenz", - "author_inst": "Gorgas Memorial Institute of Health Studies" + "author_name": "Lauren Y Jeffrey", + "author_inst": "NEW YORK UNIVERSITY" }, { - "author_name": "Danilo Franco", - "author_inst": "Gorgas Memorial Institute of Health Studies" + "author_name": "Burcu Vitrinel", + "author_inst": "NEW YORK UNIVERSITY" }, { - "author_name": "Daniel Castillo", - "author_inst": "Gorgas Memorial Institute of Health Studies" - }, - { - "author_name": "Elimelec Valdespino", - "author_inst": "Gorgas Memorial Institute of Health Studies" - }, - { - "author_name": "Isabel Blanco", - "author_inst": "Pacifica Salud, Centro de Investigacion Medica, Panama, PANAMA." + "author_name": "Michael A Carlock", + "author_inst": "University of Georgia, Athens, Georgia" }, { - "author_name": "Emilio Romero", - "author_inst": "Universidad de Panama" + "author_name": "Ted Ross", + "author_inst": "University System of Georgia" }, { - "author_name": "Alcibiades Villarreal", - "author_inst": "Instituto de Investigaciones Cientificas y Servicios de Alta Tecnologia INDICASAT-AIP, City of Knowledge, PANAMA." + "author_name": "Hyungwon Choi", + "author_inst": "National University of Singapore" }, { - "author_name": "Idalina Cubilla-Batista", - "author_inst": "Hospital Regional Dr. Rafael Estevez, Caja de Seguro Social, Panama, PANAMA" + "author_name": "Christine Vogel", + "author_inst": "New York University" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "hematology" + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.10.27.22281604", @@ -197366,7 +197105,7 @@ "rel_date": "2022-10-27", "rel_site": "medRxiv", "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.27.22281604", - "rel_abs": "Abstract Introduction In 2020, the UK government established a large-scale testing programme to rapidly identify individuals in England who were infected with SARS-CoV-2 and had COVID-19. This comprised part of the UK government's COVID-19 response strategy, to protect those at risk of severe COVID-19 disease and death and to reduce the burden on the health system. To assess the success of this approach, the UK Health Security Agency (UKHSA) commissioned an independent evaluation of the activities delivered by the National Health System (NHS) testing programme in England. The primary purpose of this evaluation will be to capture key learnings from the rollout of testing to different target populations via various testing services between October 2020 and March 2022 and to use these insights to formulate recommendations for future pandemic preparedness strategy. In this protocol, we detail the rationale, approach and study design. Methods and analysis The proposed study involves a stepwise mixed-methods approach, aligned with established methods for the evaluation of complex interventions in health, to retrospectively assess the combined impact of key asymptomatic and symptomatic testing services nationally. The research team will first develop a Theory of Change, formulated in collaboration with testing service stakeholders, to understand the causal pathways and intended and unintended outcomes of each testing service and explore contextual impacts on each testing service's intended outcomes. Insights gained will help identify indicators to evaluate how the combined aims of the testing programme were achieved, using a mixed methods approach.", + "rel_abs": "IntroductionIn 2020, the UK government established a large-scale testing programme to rapidly identify individuals in England who were infected with SARS-CoV-2 and had COVID-19. This comprised part of the UK governments COVID-19 response strategy, to protect those at risk of severe COVID-19 disease and death and to reduce the burden on the health system. To assess the success of this approach, the UK Health Security Agency (UKHSA) commissioned an independent evaluation of the activities delivered by the National Health System (NHS) testing programme in England. The primary purpose of this evaluation will be to capture key learnings from the rollout of testing to different target populations via various testing services between October 2020 and March 2022 and to use these insights to formulate recommendations for future pandemic preparedness strategy. In this protocol, we detail the rationale, approach and study design.\n\nMethods and analysisThe proposed study involves a stepwise mixed-methods approach, aligned with established methods for the evaluation of complex interventions in health, to retrospectively assess the combined impact of key asymptomatic and symptomatic testing services nationally. The research team will first develop a Theory of Change, formulated in collaboration with testing service stakeholders, to understand the causal pathways and intended and unintended outcomes of each testing service and explore contextual impacts on each testing services intended outcomes. Insights gained will help identify indicators to evaluate how the combined aims of the testing programme were achieved, using a mixed methods approach.\n\nEthics and disseminationThe study protocol was granted ethics approval by the UKHSA Research Ethics and Governance Group (reference NR0347). All relevant ethics guidelines will be followed throughout. Findings arising from this evaluation will be used to inform lessons learnt and recommendations for UKHSA on appropriate pandemic preparedness testing programme designs; findings will also be disseminated in peer-reviewed journals and at academic conferences. This will be the first evaluation to produce a portfolio of evidence in relation to the testing effectiveness and public health impact of the national testing programme in England, encompassing behavioural, economic, equity and public health impacts. These findings will strengthen the evidence base with regards to the effectiveness of COVID-19 testing and identify which aspects are necessary to prioritise in mitigating future pandemic threats when deploying a complex public health intervention such as testing.\n\nTransparency declarationThe lead author (the manuscripts guarantor) affirms that the manuscript is an honest, accurate and transparent account of the study being reported; no important aspects of the study have been omitted, and any discrepancies from the study as planned have been explained.\n\nStrengths and limitations of this protocolO_LIStrengths of this mixed methods evaluation protocol include the use of theory-based, complex evaluation approaches and an iterative and participatory approach with the stakeholder (UKHSA) to the evaluation process.\nC_LIO_LIGiven the scale and complexity of the COVID-19 testing response in England, there is a scarcity of previous relevant research, either in England or appropriate international comparators, warranting the mixed methods evaluation approach we will employ.\nC_LIO_LITo the best of the authors knowledge, this is the first national-scale evaluation of the COVID-19 testing programme in England to incorporate the broadest scope of testing services, a programme that formed an integral part of the UK pandemic response strategy. The approach proposed could be applied to the evaluation of pandemic responses in other contexts or to other types of interventions.\nC_LIO_LIWhereas most complex interventions are ideally accompanied by a prospective evaluation design initiated at the time of the intervention or earlier, this study will predominantly comprise a retrospective evaluation and is therefore limited by the quality of existing research and the data available to the research team at the time of conducting the evaluation, within the specified eight-month period allocated by UKHSA. As the UK government is in the process of consolidating data and policy related to the COVID-19 pandemic and subject to an independent inquiry, certain datasets may not be available to the researchers at the time of conducting the evaluation.\nC_LIO_LIThe scope of testing services to be evaluated and the selection of methods has been guided by the study sponsor team within UKHSA and must be achievable within the timeframe of the funding allocated to the study (eight months). Therefore, some trade-offs had to be made in terms of selecting research methods that would be feasible within this time constraint. For future evaluations, a mixed methods approach could be complemented by qualitative interviews with members of the public to gauge their experiences of testing and test-related behaviours, as well as an evaluation of other testing services that were out of scope for this research, including in prisons, the private sector and the events testing programme.\nC_LI", "rel_num_authors": 17, "rel_authors": [ { @@ -199724,35 +199463,107 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.10.24.513610", - "rel_title": "Fever temperatures modulate intraprotein dynamics and enhance the binding affinity between monoclonal antibodies and the Spike protein from SARS-CoV-2", + "rel_doi": "10.1101/2022.10.24.513619", + "rel_title": "Immunogenicity of the BA.5 Bivalent mRNA Vaccine Boosters", "rel_date": "2022-10-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.24.513610", - "rel_abs": "Fever is a typical symptom of most infectious diseases. While prolonged fever may be clinically undesirable, mild reversible fever (< 39{degrees}C, 312K) can potentiate the immune responses against pathogens. Here, using molecular dynamics, we investigated the effect of febrile temperatures (38{degrees}C to 40{degrees}C, 311K to 313K) on the immune complexes formed by the SARS-CoV-2 spike protein with two neutralizing antibodies. We found that, at mild fever temperatures (311-312K), the binding affinities of the two antibodies improve when compared to the physiological body temperature (37{degrees}C, 310K). Furthermore, only at 312K, antibodies exert distinct mechanical effects on the receptor binding domains of the spike protein that may hinder SARS-CoV-2 infectivity. Enhanced antibody binding affinity may thus be obtained using appropriate temperature conditions.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.24.513619", + "rel_abs": "Waning immunity following mRNA vaccination and the emergence of SARS-CoV-2 variants has led to reduced mRNA vaccine efficacy against both symptomatic infection and severe disease. Bivalent mRNA boosters expressing the Omicron BA.5 and ancestral WA1/2020 Spike proteins have been developed and approved, because BA.5 is currently the dominant SARS-CoV-2 variant and substantially evades neutralizing antibodies (NAbs). Our data show that BA.5 NAb titers were comparable following monovalent and bivalent mRNA boosters.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Dong Gun Kim", - "author_inst": "Korea Advanced Institute of Science and Technology" + "author_name": "Ai-ris Collier", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Hak Sung Kim", - "author_inst": "Korea Advanced Institute of Science and Technology" + "author_name": "Jessica Miller", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Nicole Hachmann", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Yoonjoo Choi", - "author_inst": "Chonnam National University Medical School" + "author_name": "Katherine McMahan", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Razvan Costin Stan", - "author_inst": "Chonnam National University" + "author_name": "Jinyan Liu", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Esther Bondzie", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Lydia Gallup", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Marjorie Rowe", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Eleanor Shonberg", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Siline Thai", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Julia Barrett", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Erica Borducchi", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Emily Bouffard", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Catherine Jacob-Dolan", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Camille Mazurek", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Audrey Mutoni", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Olivia Powers", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Michaela Sciacca", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Nehalee Surve", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Haley VanWyk", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Cindy Wu", + "author_inst": "Beth Israel Deaconess Medical Center" + }, + { + "author_name": "Dan Barouch", + "author_inst": "Beth Israel Deaconess Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "bioinformatics" + "category": "immunology" }, { "rel_doi": "10.1101/2022.10.21.22281319", @@ -201578,43 +201389,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.10.20.22281317", - "rel_title": "The COVID-19 burnout scale: Development and initial validation", + "rel_doi": "10.1101/2022.10.20.22281334", + "rel_title": "Prediction of COVID-19 Diagnosis from Healthy and Pneumonia CT scans using Convolutional Neural Networks", "rel_date": "2022-10-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.20.22281317", - "rel_abs": "We developed and validated a self-assessment instrument to measure COVID-19 pandemic-related burnout in the general population. We assessed the psychometric properties of the COVID-19 burnout scale (COVID-19-BS). Exploratory and confirmatory factor analysis identified three factors for the COVID-19-BS; emotional exhaustion, physical exhaustion, and exhaustion due to measures against the COVID-19. Cronbach s alpha coefficients for the three factors and the COVID-19-BS ranged from 0.860 to 0.921. Kaiser-Meyer-Olkin value was 0.945 and p-value for Bartlett test was <0.001 indicating highly acceptable values. Convergent validity results indicated a significant positive correlation between COVID-19-BS and anxiety and depression. Known-groups analysis identified the ability of COVID-19-BS to discriminate groups according to gender, chronic condition, and health status. Our findings indicate that the final 13-item model of COVID-19-BS is a brief, easy to administer, valid and reliable scale for assessing COVID-19-related burnout in the general public.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.20.22281334", + "rel_abs": "BackgroundCurrent methods of COVID-19 detection from other respiratory illnesses using computed tomography (CT) scans are highly inaccurate. However, understanding pathogen-specific immune responses can help reduce inconsistencies and improve the accuracy of COVID-19 and Pneumonia detection. A deep learning model using Relief-based feature selection (RBAs) was developed to detect COVID-19 and Pneumonia. Patient-specific Class Activation Maps (CAMs) were produced to highlight immunopathogenic differences and identify differences between COVID-19 and Pneumonia on CT scans.\n\nMethodsTo examine the effect on lung lesions, a COVIDx CT-2 dataset, containing CT scans from 3,745 patients, was examined. We developed an algorithm to convert the 3-D CT scan of each patient into multiple 2-D slices. Altogether, there were 194,344 2-D slices retrieved from 3,745 CT Scans. The distribution of slices was 67%-20%-17% consisting of COVID-19, Pneumonia, and normal CT scan, respectively. An AlexNet architecture was implemented with additional feature extraction layers (containing RBA) and classification layers to perform deep learning. The 2-D slices were divided into 3 groups: Training, Test, and Validation. The training set consisted of 70% of the data, the test set consisted of 20% of the data, and the validation consisted of 10% of the data. After training, unique CAMs were generated on patient CT scans using the immunopathogenic differences to highlight COVID-19 and Pneumonia related abnormalities.\n\nResultsThe model accurately distinguished hyperinflammation in COVID-19 patients from Pneumonia patients and achieved a validation accuracy of 95.60% and a false-positive rate of 4.65%. Additionally, the segmented lung, shown by the patient-specific CAMs, identified higher levels of inflammation in the lung of COVID scans compared to the other two groups.\n\nDiscussionThe use of deep learning in disease diagnosis and prevention has provided many avenues to advance current techniques. Likewise, in this analysis, deep learning was shown to successfully predict COVID-19 via CT scan. By providing patient-specific CAMs, the model can be used to not just aid in diagnosis but potentially also to evaluate serial chest CT scans for treatment.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Petros A Galanis", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" - }, - { - "author_name": "Aglaia Katsiroumpa", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" - }, - { - "author_name": "Panayota Sourtzi", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" - }, - { - "author_name": "Olga Siskou", - "author_inst": "University of Piraeus" - }, - { - "author_name": "Olympia Konstantakopoulou", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" + "author_name": "Rushil Srirambhatla", + "author_inst": "Westview High School" }, { - "author_name": "Daphne Kaitelidou", - "author_inst": "Faculty of Nursing, National and Kapodistrian University of Athens" + "author_name": "Helmet Talib Karim", + "author_inst": "University of Pittsburgh" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2022.10.20.22281265", @@ -203696,187 +203491,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.10.17.22281161", - "rel_title": "Clinical antiviral efficacy of remdesivir and casirivimab/imdevimab against the SARS-CoV-2 Delta and Omicron variants", + "rel_doi": "10.1101/2022.10.17.22280652", + "rel_title": "Effects of return-to-office, public schools reopening, and vaccination mandates on COVID-19 cases among municipal employee residents of New York City", "rel_date": "2022-10-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.17.22281161", - "rel_abs": "BackgroundUncertainty over the therapeutic benefit provided by parenteral remdesivir in COVID-19 has resulted in varying treatment guidelines. Early in the pandemic the monoclonal antibody cocktail, casirivimab/imdevimab, proved highly effective in clinical trials but because of weak or absent in vitro activity against the SARS-CoV-2 Omicron BA.1 subvariant, it is no longer recommended.\n\nMethodsIn a multicenter open label, randomized, controlled adaptive platform trial, low-risk adult patients with early symptomatic COVID-19 were randomized to one of eight treatment arms including intravenous remdesivir (200mg followed by 100mg daily for five days), casirivimab/imdevimab (600mg/600mg), and no study drug. The primary outcome was the viral clearance rate in the modified intention-to-treat population derived from daily log10 viral densities (days 0-7) in standardized duplicate oropharyngeal swab eluates. This ongoing adaptive trial is registered at ClinicalTrials.gov (NCT05041907).\n\nResultsAcceleration in mean estimated SARS-CoV-2 viral clearance, compared with the contemporaneous no study drug arm (n=64), was 42% (95%CI 18 to 73%) for remdesivir (n=67). Acceleration with casirivimab/imdevimab was 58% (95%CI: 10 to 120) in Delta (n=13), and 20% (95%CI: 3 to 43) in Omicron variant (n=61) infections compared with contemporaneous no study drug arm (n=84). In a post hoc subgroup analysis viral clearance was accelerated by 8% in BA.1 (95%CI: -21 to 59) and 23% (95%CI: 3 to 49) in BA.2 and BA.5 Omicron subvariants.\n\nConclusionsParenteral remdesivir accelerates viral clearance in early symptomatic COVID-19. Despite substantially reduced in vitro activities, casirivimab/imdevimab retains in vivo antiviral activity against COVID-19 infections caused by currently prevalent Omicron subvariants.\n\nBrief summaryIn early symptomatic COVID-19 remdesivir accelerated viral clearance by 42% while the monoclonal antibody cocktail casirivimab/imdevimab accelerated clearance by approximately 60% in SARS-CoV-2 Delta variant infections, and by approximately 25% in infections with Omicron subvariants BA.2 and BA.5.", - "rel_num_authors": 42, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.17.22280652", + "rel_abs": "ObjectiveOn September 13, 2021, teleworking ended for New York City municipal employees, and Department of Education (DOE) employees returned to reopened schools. On October 29, COVID-19 vaccination was mandated. We assessed these mandates short-term effects on disease transmission.\n\nMethodsUsing difference-in-difference analyses, we calculated COVID-19 incidence rate ratios (IRR) among residents 18-64 years-old by employment status pre- and post-policy implementation.\n\nResultsIRRs post-(September 23-October 28) vs. pre-(July 5-September 12) return-to-office were similar between office-based City employees and non-City employees. Among DOE employees, the IRR after schools reopened was elevated 28.4% (95% CI: 17.3%-40.3%). Among City employees, the IRR post-(October 29-November 30) vs. pre- (September 23- October 28) vaccination mandate was lowered 20.1% (95% CI: 13.7%-26.0%).\n\nConclusionsWorkforce mandates influenced disease transmission, among other societal effects.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Podjanee Jittamala", - "author_inst": "Department of Tropical Hygiene, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "William Henry Keith Schilling", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit (MORU)" - }, - { - "author_name": "James A Watson", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit" - }, - { - "author_name": "Viravarn Luvira", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Tanaya Siripoon", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Thundon Ngamprasertchai", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Pedro J Almeida", - "author_inst": "Clinical Research Unit, Center for Advanced and Innovative Therapies, Universidade Federal de Minas Gerais, Brazil" - }, - { - "author_name": "Maneerat Ekkapongpisit", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Cintia Cruz", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "James J Callery", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Simon Boyd", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Orawan Anunsittichai", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Maliwan Hongsuwan", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Yutaritat Singhaboot", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Watcharee Pagornrat", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Runch Tuntipaiboontana", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Varaporn Kruabkontho", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Thatsanun Ngernseng", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Jaruwan Tubprasert", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Mohammad Yazid Abdad", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Srisuda Keayarsa", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Wanassanan Madmanee", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Renato S Aguiar", - "author_inst": "Department of Genetics, Ecology and Evolution, Institute of Biological Sciences, Universidade Federal de Minas Gerais" - }, - { - "author_name": "Franciele M Santos", - "author_inst": "Department of Genetics, Ecology and Evolution, Institute of Biological Sciences, Universidade Federal de Minas Gerais" - }, - { - "author_name": "Elizabeth M Batty", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Pongtorn Hanboonkunupakarn", - "author_inst": "Bangplee Hospital, Ministry of Public Health, Thailand" - }, - { - "author_name": "Borimas Hanboonkunupakarn", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Sakol Sookprome", - "author_inst": "Bangplee Hospital, Ministry of Public Health, Thailand" - }, - { - "author_name": "Kittiyod Poovorawan", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Mallika Imwong", - "author_inst": "Department of Molecular Tropical Medicine and Genetics, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Walter RJ Taylor", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Vasin Chotivanich", - "author_inst": "Faculty of Medicine, Navamindradhiraj University, Thailand" - }, - { - "author_name": "Chunlanee Sangketchon", - "author_inst": "Faculty of Science and Health Technology, Navamindradhiraj University, Thailand" - }, - { - "author_name": "Wiroj Ruksakul", - "author_inst": "Faculty of Medicine, Navamindradhiraj University, Thailand" - }, - { - "author_name": "Kesinee Chotivanich", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Sasithon Pukrittayakamee", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" - }, - { - "author_name": "Arjen M Dondorp", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University, Thailand" + "author_name": "Sharon K. Greene", + "author_inst": "New York City Department of Health and Mental Hygiene" }, { - "author_name": "Nicholas PJ Day", - "author_inst": "Mahidol Oxford Tropical Medicine Research Unit" + "author_name": "Bahman P. Tabaei", + "author_inst": "New York City Department of Health and Mental Hygiene" }, { - "author_name": "Mauro M Teixeira", - "author_inst": "Clinical Research Unit, Center for Advanced and Innovative Therapies, Universidade Federal de Minas Gerais, Brazil" + "author_name": "Gretchen M. Culp", + "author_inst": "New York City Department of Health and Mental Hygiene" }, { - "author_name": "Watcharapong Piyaphanee", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" + "author_name": "Alison Levin-Rector", + "author_inst": "New York City Department of Health and Mental Hygiene" }, { - "author_name": "Weerapong Phumratanaprapin", - "author_inst": "Department of Clinical Tropical Medicine, Faculty of Tropical Medicine, Mahidol University, Thailand" + "author_name": "Nishant Kishore", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Nicholas J White", - "author_inst": "Faculty of Tropical Medicine, Mahidol University" + "author_name": "Jennifer Baumgartner", + "author_inst": "New York City Department of Health and Mental Hygiene" } ], "version": "1", - "license": "cc_by", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.10.14.22281081", @@ -205874,63 +205525,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.10.14.512325", - "rel_title": "The impact of the ABO/Rh blood group on susceptibility and severity among COVID-19 patients in Luanda, Angola", + "rel_doi": "10.1101/2022.10.15.512291", + "rel_title": "Diet Induced Obesity and Diabetes Enhance Mortality and Reduces Vaccine Efficacy for SARS-CoV-2", "rel_date": "2022-10-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.14.512325", - "rel_abs": "SARS-CoV-2 is a public health concern worldwide. Identification of biological factors that could influence transmission and worsen the disease has been the subject of extensive investigation. Herein, we investigate the impact of the ABO/Rh blood group on susceptibility and severity among COVID-19 patients in Luanda, Angola. This was a multicentric cohort study conducted with 101 COVID-19 patients. Chi-square and logistic regression were calculated to check factors related to the worsening of the disease and deemed significant when p<0.05. Blood type O (51.5%) and Rh-positive (93.1%) were the most frequent. Patients from blood type O had a high risk to severe disease [OR: 1.33 (95% CI: 0.42 - 4.18), p=0.630] and hospitalization [OR: 2.59 (95% CI: 0.84 - 8.00), p=0.099]. Also, Rh-positive blood type presented a high risk for severe disease (OR: 10.6, p=0.007) and hospitalization (OR: 6.04, p=0.026). We find a high susceptibility, severity, hospitalization, and mortality, respectively, among blood group O and Rh-positive patients, while blood group AB presented a low susceptibility, severity, hospitalization, and mortality, respectively. Our findings add to the body of evidence suggesting that ABO/Rh blood groups play an important role in the course of SARS-CoV-2 infection.", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.15.512291", + "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), the causative agent of Coronavirus disease 2019 (COVID-19), emerged in Wuhan, China, in December 2019. As of October 2022, there have been over 625 million confirmed cases of COVID-19, including over 6.5 million deaths. Epidemiological studies have indicated that comorbidities of obesity and diabetes mellitus are associated with increased morbidity and mortality following SARS-CoV-2 infection. We determined how the comorbidities of obesity and diabetes affect morbidity and mortality following SARS-CoV-2 infection in unvaccinated and adjuvanted spike nanoparticle (NVX-CoV2373) vaccinated mice. We find that obese/diabetic mice infected with SARS-CoV-2 have increased morbidity and mortality compared to age matched normal mice. Mice fed a high-fat diet (HFD) then vaccinated with NVX-CoV2373 produce equivalent neutralizing antibody titers to those fed a normal diet (ND). However, the HFD mice have reduced viral clearance early in infection. Analysis of the inflammatory immune response in HFD mice demonstrates a recruitment of neutrophils that was correlated with increased mortality and reduced clearance of the virus. Depletion of neutrophils in diabetic/obese vaccinated mice reduced disease severity and protected mice from lethality. This model recapitulates the increased disease severity associated with obesity and diabetes in humans with COVID-19 and is an important comorbidity to study with increasing obesity and diabetes across the world.\n\nImportanceSARS-CoV-2 has caused a wide spectrum of disease in the human population, from asymptomatic infections to death. It is important to study the host differences that may alter the pathogenesis of this virus. One clinical finding in COVID19 patients, is that people with obesity or diabetes are at increased risk of severe illness from SARS-CoV-2 infection. We used a high fat diet model in mice to study the effects of obesity and Type 2 diabetes on SARS-CoV-2 infection as well as how these comorbidities alter the response to vaccination. We find that diabetic/obese mice have increased disease after SARS-CoV-2 infection and they have slower clearance of virus. We find that the lungs of these mice have increased neutrophils and that removing these neutrophils protect diabetic/obese mice from disease. This demonstrates why these diseases have increased risk of severe disease and suggests specific interventions upon infection.", "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Cruz S. Sebasti\u00e3o", - "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Angola (CISA), Caxito, Angola" + "author_name": "Robert Johnson", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Alice Teixeira", - "author_inst": "Cl\u00ednica Girassol" + "author_name": "Jeremy Ardunay", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Ana Lu\u00edsa", - "author_inst": "Instituto Nacional de Investiga\u00e7\u00e3o em Sa\u00fade (INIS), Luanda, Angola" + "author_name": "Holly Hammond", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Margarete Arrais", - "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Angola (CISA), Caxito, Angola" + "author_name": "James Logue", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Chissengo Tchonhi", - "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Angola (CISA), Caxito, Angola" + "author_name": "Lian Jackson", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Adis Cogle", - "author_inst": "Cl\u00ednica Girassol" + "author_name": "Lauren Baracco", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Euclides Sacomboio", - "author_inst": "Instituto nacional de investiga\u00e7\u00e3o em sa\u00fade (INIS), Luanda, Angola" + "author_name": "Marisa McGrath", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Bruno Cardoso", - "author_inst": "Cl\u00ednica Girassol" + "author_name": "Carly Dillen", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Joana Morais", - "author_inst": "Inistituto Nacional de Investiga\u00e7\u00e3o em sa\u00fade (INIS), Luanda, Angola" + "author_name": "Nita Patel", + "author_inst": "Novavax" }, { - "author_name": "Jocelyne Vasconcelos", - "author_inst": "Centro de Investiga\u00e7\u00e3o em sa\u00fade de Angola (CISA), Caxito, Angola" + "author_name": "Gale Smith", + "author_inst": "Novavax" }, { - "author_name": "Miguel Brito", - "author_inst": "Centro de Investiga\u00e7\u00e3o em Sa\u00fade de Angola (CISA), Caxito, Angola" + "author_name": "Matthew Frieman", + "author_inst": "University of Maryland School of Medicine" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "genetics" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.10.16.512395", @@ -207832,47 +207483,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.10.12.512011", - "rel_title": "Laboratory evaluation of a quaternary ammonium compound (QAC)-based antimicrobial coating used in public transport during the COVID-19 pandemic", + "rel_doi": "10.1101/2022.10.12.22280904", + "rel_title": "Residential clustering of COVID-19 cases and efficiency of building-wide compulsory testing notices as a transmission control measure in Hong Kong", "rel_date": "2022-10-13", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.10.12.512011", - "rel_abs": "The virucidal activity of a quaternary ammonium compound (QAC)-based antimicrobial coating used by the UK rail industry during the COVID-19 pandemic was evaluated using the bacteriophage {phi}6 as a surrogate for SARS-CoV-2. Immediately after application and in the absence of interfering substance, the product showed efficacy (>3 log10 reduction) on some materials typically used in rail carriages (stainless steel, high pressure laminate and plastic), variable efficacy on glass and no efficacy (<3 log10 reduction) on a train armrest made of Terluran 22. If, after application of the product, the surfaces remained undisturbed, the antimicrobial coating retained its efficacy for at least 28 days on all materials where it was effective immediately after application. However, regardless of the material coated or time since application, the presence of organic debris (fetal bovine serum) significantly reduced the viricidal activity of the coating. Wiping the surface with a wetted cloth after organic debris deposition was not sufficient to restore efficacy. We conclude that the product is likely to be of limited effectiveness in a busy multi-user environment such as public transport.\n\nImportanceThis study evaluated the performance of a commercially available antimicrobial coating used by the transport industry in the UK during the COVID-19 pandemic. While the product initially showed efficacy against {phi}6 when applied to some materials, when organic debris was subsequently deposited, the efficacy was severely diminished and could not be recovered through wiping (cleaning) the surface. This highlights the importance of including relevant materials and conditions when evaluating antimicrobial coatings in the laboratory. Further efforts are required to identify suitable infection prevention and control practices for the transport industry.", - "rel_num_authors": 7, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.12.22280904", + "rel_abs": "BackgroundDespite relatively few reports of residential case clusters of COVID-19, building-wide compulsory testing notices on residential apartment blocks are frequently applied in Hong Kong with the aim of identifying cases and reducing transmission.\n\nMethodsWe aimed to describe the frequency of residential case clusters and the efficiency of compulsory testing notices in identifying cases. The residences of locally infected COVID-19 cases in Hong Kong were grouped to quantify the number of cases per residence.\n\nBuildings targeted in compulsory testing notices were matched with the residence of cases to estimate the number of cases identified.\n\nResultsWe found that most of the residential buildings (4246/7688, 55.2%) with a confirmed COVID-19 case had only one reported case. In the fourth and the fifth epidemic wave in Hong Kong, we estimated that compulsory testing notices detected 29 cases (95% confidence interval: 26, 32) and 46 cases (44, 48) from every 100 buildings tested (each with hundreds of residents), respectively. Approximately 13% of the daily reported cases were identified through compulsory testing notices.\n\nConclusionsCompulsory testing notices can be an essential method when attempting to maintain local elimination ( zero covid) and most impactful early in an epidemic when the benefit remains of stemming a new wave. Compulsory testing therefore appears to be a relatively inefficient control measure in response to sustained community transmission in the community.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Paz Aranega-Bou", - "author_inst": "UK Health Security Agency" + "author_name": "Ben Young", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Natalie Brown", - "author_inst": "University of Surrey" + "author_name": "Bingyi Yang", + "author_inst": "University of Hong Kong" }, { - "author_name": "Abigail Stigling", - "author_inst": "UK Health Security Agency" + "author_name": "Peng Wu", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Neville Q Verlander", - "author_inst": "UK Health Security Agency" + "author_name": "Dillon Adam", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Thomas Pottage", - "author_inst": "UK Health Security Agency" + "author_name": "Jessica Wong", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Allan Bennett", - "author_inst": "UK Health Security Agency" + "author_name": "Faith Ho", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Ginny Moore", - "author_inst": "UK Health Security Agency" + "author_name": "Huizhi Gao", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Gabriel Leung", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Benjamin J Cowling", + "author_inst": "The University of Hong Kong" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.10.13.22281010", @@ -209806,59 +209465,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.10.09.22280878", - "rel_title": "Associations Between Reported Post-COVID-19 Symptoms and Subjective Well-Being, Israel, July 2021 -April 2022", + "rel_doi": "10.1101/2022.10.07.22280827", + "rel_title": "Mitigating the Severity of COVID-19 Illness in the Primary Care Patient Population through Early Identification and Close Monitoring of Underlying Comorbidities", "rel_date": "2022-10-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.09.22280878", - "rel_abs": "The impact of individual symptoms reported post-COVID-19 on subjective well-being (SWB) is unknown. We described associations between SWB and selected reported symptoms following SARS-CoV-2 infection. We analysed reported symptoms and subjective well being from 2295 participants (of which 576 reporting previous infection) in an ongoing longitudinal cohort study taking place in Israel. We estimated changes in SWB associated with reported selected symptoms at three follow-up time points (3-6, 6-12, and 12-18 months post infection) among participants reporting previous SARS-CoV-2 infection, adjusted for key demographic variables, using linear regression. Our results suggest that the biggest and most sustained changes in SWB stems from non-specific symptoms (fatigue -7.7 percentage points (pp), confusion/ lack of concentration -10.7 pp, and sleep disorders -11.5pp, p<0.005), whereas the effect of system-specific symptoms, such as musculoskeletal symptoms (weakness in muscles and muscle pain) on SWB, are less profound and more transient. Taking a similar approach for other symptoms and following individuals over time to describe trends in SWB changes attributable to specific symptoms will help understand the post-acute phase of COVID-19 and how it should be defined and better managed.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.07.22280827", + "rel_abs": "PurposePrior studies have identified risk factors which prognosticate severity of SARS-CoV-2 illness among hospitalized patients. Since the majority of patients first present to ambulatory care sites, there is a need to identify early predictors of disease progression in this population.\n\nMethodsThis retrospective cohort study investigated the impact of underlying comorbid conditions on SARS-CoV-2 infection severity in the ambulatory setting. All patients who presented to a single federally qualified health center (FQHC) between March-May 2020 with a positive SARS-CoV-2 test were reviewed for inclusion. Patient demographics, symptomology, prior medical history, and outcomes were collected.\n\nResults301 patients were included, with nearly equal numbers of patients with (n=151) and without (n=150) underlying comorbidities. Overall, 269 patients (89%) had a mild outcome and 32 patients (11%) had a severe outcome. Advanced age (OR: 9.4 [95% CI: 3.4-27.4], p < 0.001) and male gender (OR: 3.2 [95% CI: 1.2-9.8], p = 0.02) were significant predictors of severe outcomes. Additionally, every obesity category (1: BMI = 30.0-34.9; 2: BMI = 35-39.9; 3: BMI = 40.0+) was associated with more severe outcomes compared to non-obese (OR: 3.5, p = 0.05; OR: 5.2, p = 0.03; OR: 13.9, p = 0.01). Compared to an HbA1C < 6, an HbA1C of 7.1-8.0 showed a clinically significant association.\n\nConclusionSARS-CoV-2 severity can be prognosticated in the ambulatory population by the presence and severity of pre-existing comorbidities. Early identification and risk stratification of these comorbidities will allow clinicians to develop plans for closer monitoring to prevent severe illness.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Yanay Gorelik", - "author_inst": "Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel" + "author_name": "Payal D Parikh", + "author_inst": "Rutgers, Robert Wood Johnson Medical School" }, { - "author_name": "Amiel A Dror", - "author_inst": "Galilee Medical Center, Azrieli Faculty of Medicine Bar-Ilan University" + "author_name": "Patricia Greenberg", + "author_inst": "Biostatistics and Epidemiology Services Center, Rutgers School of Public Health, Rutgers University, Piscataway, NJ, USA" }, { - "author_name": "Hiba Zayyad", - "author_inst": "Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel; Baruch Padeh Poriya Medical Center, Poriya, Israel" + "author_name": "Shmuel Halpert", + "author_inst": "Chemed Health Center, Lakewood, NJ, USA" }, { - "author_name": "Ofir Wertheim", - "author_inst": "Baruch Padeh Poriya Medical Center, Poriya, Israel" + "author_name": "Allison Abhrishami", + "author_inst": "Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA" }, { - "author_name": "Kamal Abu Jabal", - "author_inst": "Azrieli Faculty of Medicine, Safed, Israel; Ziv medical Centre, Safed, israel" + "author_name": "Liora Rabizadeh", + "author_inst": "Department of Psychology, University of California, Los Angeles, Los Angeles, CA, USA." }, { - "author_name": "Nazzal Saleh", - "author_inst": "Baruch Padeh Poriya Medical Center, Poriya, Israel" + "author_name": "Hannah Shayefar", + "author_inst": "Department of Cognitive Science, University of California, Los Angeles, Los Angeles, CA, USA" }, { - "author_name": "Paul Kuodi", - "author_inst": "The Azrieli Faculty of Medicine, Bar Ilan University, Tzfat, Israel" - }, - { - "author_name": "Jelte Elsinga", - "author_inst": "The Azrieli Faculty of Medicine, Bar Ilan University, Tzfat, Israel" + "author_name": "Lauren Tetelbaun", + "author_inst": "Bachelor of Medical Sciences, Western University, London, ON, Canada" }, { - "author_name": "Daniel Glikman", - "author_inst": "The Azrieli Faculty of Medicine, Bar Ilan University, Tzfat, Israel; Baruch Padeh Poriya Medical Center, Poriya, Israel" + "author_name": "Dovid Friedman", + "author_inst": "Chemed Health Center, Lakewood, NJ, USA" }, { - "author_name": "Michael Edelstein", - "author_inst": "Azrieli Faculty of Medicine, Bar Ilan University, Safed, Israel; Ziv Medical Centre, Safed, Israel" + "author_name": "Jeffrey Kaminetzky", + "author_inst": "Chemed Health Center, Lakewood, NJ, USA" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "primary care research" }, { "rel_doi": "10.1101/2022.10.10.22280907", @@ -211732,53 +211387,41 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2022.10.03.22280660", - "rel_title": "Effectiveness and duration of a second COVID-19 vaccine booster", + "rel_doi": "10.1101/2022.10.04.22280542", + "rel_title": "Key performance indicators of COVID-19 contact tracing in Belgium from September 2020 to December 2021", "rel_date": "2022-10-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.03.22280660", - "rel_abs": "Using a prospective national cohort of 3.75 million individuals aged 20 or older, we evaluated the effectiveness against COVID-19 related ICU admissions and death of mRNA-based second vaccine boosters for four different three-dose background regimes: BNT162b2 primary series plus a homologous booster, and CoronaVac primary series plus an mRNA booster, a homologous booster, and a ChAdOx-1 booster. We estimated the vaccine effectiveness weekly from February 14 to August 15, 2022, by estimating hazard ratios of immunization over non-vaccination, accounting for relevant confounders. The overall adjusted effectiveness of a second mRNA booster shot was 88.2% (95%CI, 86.2-89.9) and 90.5% (95%CI 89.4-91.4) against ICU admissions and death, respectively. Vaccine effectiveness showed a mild decrease for all regimens and outcomes, probably associated with the introduction of BA.4 and BA.5 Omicron sub-lineages and immunity waning. The duration of effectiveness suggests that no additional boosters are needed six months following a second booster shot.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.04.22280542", + "rel_abs": "BackgroundContact tracing aims to prevent onward transmission of infectious diseases and data obtained during tracing provide unique information on transmission characteristics. A key performance indicator that has been proposed to evaluate contact tracing is the proportion of cases arising from known contacts. However, few empirical studies have investigated the effectiveness of contact tracing.\n\nMethodsUsing data collected between September 2020 and December 2021 in Belgium, we investigated the impact of contact tracing on SARS-CoV-2 transmission. We compared confirmed cases that were previously identified as a close contact to those that were not yet known, in terms of their traced contacts and secondary cases as well as the serial interval. In addition, we established contact and transmission patterns by age.\n\nFindingsPreviously traced, hence known, cases comprised 20% of all cases and they were linked to relatively fewer close contacts as well as fewer secondary cases and a lower secondary attack rate compared to cases that were not already known. In addition we observed a shorter serial interval for known cases. There was a relative increase in transmission from children to adults during circulation of the Delta and Omicron variants, without an increase in the extent of contact between these age groups.\n\nInterpretationThese results suggest that contact tracing in Belgium has been effective in reducing onward transmission and that individuals aware of their exposure to SARS-CoV-2 seemed more reserved in their social contact behaviour. Data from a reference period or region are needed to measure the impact of contact tracing in terms of the number of cases and deaths averted.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Alejandro Jara", - "author_inst": "Pontificia Universidad Catolica de Chile" - }, - { - "author_name": "Cristobal Cuadrado", - "author_inst": "Ministerio de Salud Chile" - }, - { - "author_name": "Eduardo A Undurraga", - "author_inst": "Pontificia Universidad Catolica de Chile" - }, - { - "author_name": "Christian Garcia", - "author_inst": "Ministerio de Salud Chile" + "author_name": "C\u00e9cile Kremer", + "author_inst": "I-BioStat, Data Science Institute, Hasselt University, Belgium" }, { - "author_name": "Manuel Najera", - "author_inst": "Ministerio de Salud Chile" + "author_name": "Lander Willem", + "author_inst": "Centre for Health Economics Research and Modelling Infectious Diseases, VAXINFECTIO, University of Antwerp, Belgium" }, { - "author_name": "Maria Paz Bertoglia", - "author_inst": "Ministerio de Salud Chile" + "author_name": "Jorden Boone", + "author_inst": "KPMG Advisory, Public Sector practice, Belgium" }, { - "author_name": "Veronica Vergara", - "author_inst": "Ministerio de Salud Chile" + "author_name": "Wouter Arrazola de O\u00f1ate", + "author_inst": "Belgian Lung and Tuberculosis Association, Belgium & Flemish Association for Respiratory Health and Tuberculosis, Belgium" }, { - "author_name": "Jorge Fernandez", - "author_inst": "Ministerio de Salud Chile" + "author_name": "Na\u00efma Hammami", + "author_inst": "Department of Infectious Disease Prevention and Control, Agency for Care and Health, Belgium" }, { - "author_name": "Heriberto Garcia", - "author_inst": "Ministerio de Salud Chile" + "author_name": "Christel Faes", + "author_inst": "I-BioStat, Data Science Institute, Hasselt University, Belgium" }, { - "author_name": "Rafael Araos", - "author_inst": "Universidad del Desarrollo Clinica Alemana" + "author_name": "Niel Hens", + "author_inst": "I-BioStat, Data Science Institute, Hasselt University, Belgium & Centre for Health Economics Research and Modelling Infectious Diseases, VAXINFECTIO, University" } ], "version": "1", @@ -213782,51 +213425,75 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.10.02.22280627", - "rel_title": "Dynamics of Vaccine-Hesitant Parents' Considerations Regarding Covid-19 Vaccination", + "rel_doi": "10.1101/2022.10.03.22280639", + "rel_title": "Evaluation of primary allied healthcare in patients recovering from COVID-19: first results after six months follow-up in a Dutch nationwide prospective cohort study", "rel_date": "2022-10-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.02.22280627", - "rel_abs": "IntroductionMost studies present a snapshot of hesitant parents decisions and thinking concerning COVID-19 vaccination, but for many it is a dynamic rather than a stable process. We examined the considerations of a group of vaccine hesitant parents (VHPs) with respect to COVID-19 vaccinations for their children before, during and after the main vaccination campaign for the 12 to15-year-old age group in Israel, over a six-month period.\n\nMethodsDigital surveys were administered to 1118 Israeli parents. After VHPs were identified, three surveys were conducted to evaluate considerations that discourage or encourage vaccination. A logistic regression was carried out on sixteen models; of these, six were found to be statistically significant.\n\nResults456 parents data were analyzed. Parents intentions to vaccinate prior to the vaccination campaign were a good predictor of their actual behavior, (rp=.497, p<.001). We divided the parents into four groups: consistently pro-vaccine (39.4%), consistently anti-vaccine (15.2%), pro-vaccine parents who did not vaccinate (17.6%), and anti-vaccine parents who did vaccinate (27.9%). We identified eight considerations that were significant in VHPs vaccination behavior: trust in scientists, doctors and drug companies, childrens preferences, spread of COVID, social responsibility, childrens characteristics, the vaccines speed of development and its side effects.\n\nDiscussionGreater vaccine uptake for teenagers may depend on the attitudes and perceptions of their parents. We identified encouraging and discouraging considerations that may make potential targets for public health officials when communicating about vaccines.\n\nArticle SummaryEncouraging and discouraging considerations re COVID-19 vaccination are explored and identified in vaccine hesitant parents.\n\nWhats known on this subjectMost studies found that vaccine uptake is improved among well-to-do or highly educated parents. Severity of the disease and safety of the vaccination are the main factors influencing the decision.\n\nWhat this study addsThe dynamics of attitude change toward vaccination among VHPs may be affected by several different factors. Chief are childrens preferences and individual health characteristics, side effects and speed of vaccine development", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.10.03.22280639", + "rel_abs": "ObjectivesTo report the recovery of patients receiving primary allied healthcare after a COVID-19 infection at a six-month follow-up, and to explore which patient characteristics are associated with the changes in outcomes between the baseline and six-month follow-up.\n\nDesignProspective cohort study.\n\nSettingAllied healthcare in Dutch primary care.\n\nParticipants1,451 adult patients recovering from COVID-19 and receiving treatment from one or more primary care allied health professional(s) (i.e., dietitian, exercise therapist, occupational therapist, physical therapist and/or speech and language therapist).\n\nResultsFor participation (USER-P range 0 to 100), estimated mean differences of at least 2.3 points were observed after six months. For HRQoL (EQ-VAS range 0 to 100), the mean increase was 12.31 at six months. Furthermore, significant improvements were found for fatigue (FSS range 1 to 7): the mean decrease was -0.7 at six months. For physical functioning (PROMIS-PF range 13.8 to 61.3), the mean increase was 5.9 at six months. Mean differences of -0.8 for anxiety (HADS range 0 to 21), and -1.5 for depression (HADS range 0 to 21), were found after six months. Having a worse baseline score, hospital admission and male sex were associated with greater improvement between the baseline and six-month follow-up, whereas age, BMI, comorbidities and smoking status were not associated with mean changes in any outcome measure.\n\nConclusionsPatients recovering from COVID-19 who receive primary allied healthcare make progress in recovery, but still experience many limitations in their daily activities after six months. Our findings provide reference values to healthcare providers and healthcare policy-makers regarding what to expect from the recovery of patients who received health care from one or more primary care allied health professionals.\n\nTrial registrationClinicaltrials.gov registry (NCT04735744).", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Erga Atad", - "author_inst": "Reichman University" + "author_name": "Anne I. Slotegraaf", + "author_inst": "Division of Human Nutrition and Health, Wageningen University and Research, Wageningen, the Netherlands" }, { - "author_name": "Itamar Netzer", - "author_inst": "Clalit Healthcare" + "author_name": "Marissa H.G. Gerards", + "author_inst": "Department of Epidemiology, Care and Public Health Institute (CAPHRI), Faculty of Health, Medicine and Life sciences, Maastricht University, Maastricht, the Net" }, { - "author_name": "Orr Peleg", - "author_inst": "Technion, Israel Institute of Technology" + "author_name": "Arie Cornelis Verburg", + "author_inst": "Radboud Institute for Health Sciences, IQ healthcare, Radboud university medical centre, Nijmegen, the Netherlands" }, { - "author_name": "Keren Landsman", - "author_inst": "Mida'at, for Informed Health (RA)" + "author_name": "Marian A.E. de van der Schueren", + "author_inst": "Department of Nutrition, Dietetics and Lifestyle, HAN University of Applied Sciences, Nijmegen, the Netherlands" }, { - "author_name": "Keren Dalyot", - "author_inst": "Technion, Israel Institute of Technology" + "author_name": "Hinke M. Kruizenga", + "author_inst": "Amsterdam UMC location Vrije Universiteit Amsterdam, Department of Nutrition & Dietetics, Amsterdam Movement Sciences, Aging and Vitality, Amsterdam, the Nether" }, { - "author_name": "Shanny Edan-Reuvan", - "author_inst": "Technion, Israel Institute of Technology" + "author_name": "Maud J.L. Graff", + "author_inst": "Donders Institute for Brain, Cognition and Behaviour, Department of Rehabilitation, Radboud university medical centre, Nijmegen, the Netherlands" }, { - "author_name": "Eyal Nitzani", - "author_inst": "Amazon" + "author_name": "Edith H.C. Cup", + "author_inst": "Donders Institute for Brain, Cognition and Behaviour, Department of Rehabilitation, Radboud university medical centre, Nijmegen, the Netherlands" }, { - "author_name": "Ayelet Baram-Tsabari", - "author_inst": "Technion, Israel Institute of Technology" + "author_name": "Johanna G. Kalf", + "author_inst": "Donders Institute for Brain, Cognition and Behaviour, Department of Rehabilitation, Radboud university medical centre, Nijmegen, the Netherlands" + }, + { + "author_name": "Antoine F. Lenssen", + "author_inst": "Department of Physical Therapy, Maastricht university medical centre, Maastricht, the Netherlands" + }, + { + "author_name": "Willemijn M. Meijer", + "author_inst": "Netherlands Institute for Health Services Research, Nivel, Utrecht, the Netherlands" + }, + { + "author_name": "Renee A. Kool", + "author_inst": "Lung Foundation Netherlands, Amersfoort, the Netherlands" + }, + { + "author_name": "Rob A. de Bie", + "author_inst": "Department of Epidemiology, Care and Public Health Institute (CAPHRI), Faculty of Health, Medicine and Life sciences, Maastricht University, Maastricht, the Net" + }, + { + "author_name": "Philip J. van der Wees", + "author_inst": "Radboud Institute for Health Sciences, IQ healthcare, Radboud university medical centre, Nijmegen, the Netherlands" + }, + { + "author_name": "Thomas J. Hoogeboom", + "author_inst": "Radboud Institute for Health Sciences, IQ healthcare, Radboud university medical centre, Nijmegen, the Netherlands" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2022.10.02.22280609", @@ -215840,23 +215507,79 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2022.09.28.22280472", - "rel_title": "Covid-19: Qualitative Change in the Behavior of the \"Virus vs Human\" System - From Limit Cycle to Sustained Focus", + "rel_doi": "10.1101/2022.09.29.22280508", + "rel_title": "When Case Reporting Becomes Untenable: Can Sewer Networks Tell Us Where COVID-19 Transmission Occurs?", "rel_date": "2022-09-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.28.22280472", - "rel_abs": "AnnotationThe high contagiousness of the latest strains of Covid-19 qualitatively changes the behavior of the \"virus vs human\" system. Numerical experiments with a model of the Covid-19 epidemic in Moscow have shown that a reproduction number R0 of about 4 is critical, defining a qualitative change in the dynamics of the epidemic. Below this value (observed until 2022), the long-term forecast tends to undamped oscillations; above this value, it is described by damped oscillations: amplitudes of the epidemic waves get smaller and smaller, with a constant, very high background level of morbidity (or high-intensity vaccination) that maintains the state of natural immunity at a level close to 100% (reaching 93.7% for the current R0 value of about 16). At the limit, the system tends to a stable equilibrium point. Here we consider a reduced model of epidemic dynamics. Its study (search for equilibrium solutions, analysis of their stability, construction a bifurcation diagram and a phase portrait) confirms the presence of points of qualitative change in the behavior of the \"virus vs human\" system (bifurcation points). Some practical results for Moscow are given. A further increase in the contagiousness of the virus does not change the picture significantly, thus more infectious strains are not to be feared. The key parameter of the study is the function of the immunity level depending on the time after the disease. The damping of omicron waves (oscillations), observed recently in many countries, is a confirmation of the correctness of the accepted hypotheses.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.29.22280508", + "rel_abs": "Monitoring SARS-CoV-2 in wastewater is a valuable approach to track COVID-19 transmission. Designing wastewater surveillance (WWS) with representative sampling sites and quantifiable results requires knowledge of the sewerage system and virus fate and transport. We developed a multi-level WWS system to track COVID-19 in Atlanta using an adaptive nested sampling strategy. From March 2021 to April 2022, 868 wastewater samples were collected from influent lines to wastewater treatment facilities and upstream community manholes. Variations in SARS-CoV-2 concentrations in influent line samples preceded similar variations in numbers of reported COVID-19 cases in the corresponding catchment areas. Community sites under nested sampling represented mutually-exclusive catchment areas. Community sites with high SARS-CoV-2 detection rates in wastewater covered high COVID-19 incidence areas, and adaptive sampling enabled identification and tracing of COVID-19 hotspots. This study demonstrates how a well-designed WWS provides actionable information including early warning of surges in cases and identification of disease hotspots.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Alexander Sokolov", - "author_inst": "Institute for information transmission problem RAS" + "author_name": "Yuke Wang", + "author_inst": "Emory University" + }, + { + "author_name": "Pengbo Liu", + "author_inst": "Emory University" + }, + { + "author_name": "Jamie VanTassell", + "author_inst": "Emory University" + }, + { + "author_name": "Stephen P. Hilton", + "author_inst": "Emory University" + }, + { + "author_name": "Lizheng Guo", + "author_inst": "Emory University" + }, + { + "author_name": "Orlando Sablon", + "author_inst": "Emory University" + }, + { + "author_name": "Marlene K Wolfe", + "author_inst": "Emory University" + }, + { + "author_name": "Lorenzo Freeman", + "author_inst": "City of Atlanta Department of Watershed Management" + }, + { + "author_name": "Wayne Rose", + "author_inst": "City of Atlanta Department of Watershed Management" + }, + { + "author_name": "Carl Holt", + "author_inst": "City of Atlanta Department of Watershed Management" + }, + { + "author_name": "Mikita Browning", + "author_inst": "City of Atlanta Department of Watershed Management" + }, + { + "author_name": "Michael Bryan", + "author_inst": "Georgia Department of Public Health" + }, + { + "author_name": "Lance A. Waller", + "author_inst": "Emory University" + }, + { + "author_name": "Peter F.M. Teunis", + "author_inst": "Emory University" + }, + { + "author_name": "Christine L. Moe", + "author_inst": "Emory University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.09.28.22280475", @@ -217746,31 +217469,59 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2022.09.22.22280262", - "rel_title": "Development and validation of a methodology to measure exhaled carbon dioxide (CO2) and control indoor air renewal", + "rel_doi": "10.1101/2022.09.27.22280425", + "rel_title": "Association of IFNAR2 rs2236757 and OAS3 rs10735079 polymorphisms with susceptibility to COVID-19 infection and severity", "rel_date": "2022-09-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.22.22280262", - "rel_abs": "The measurement of CO2 has positioned itself as a low-cost and straightforward technique to indirectly control indoor air quality, allowing the reduction of the concentration of potentially pathogen-loaded aerosols to which we are exposed. However, on numerous occasions, bad practice limits the technique for CO2 level interpreting and does not apply methodologies that guarantee air renewal. This work proposes a new methodology for measuring and controlling CO2 levels for indoor air in shared spaces. The proposed methodology is based on three stages: diagnosis, correction protocols, and monitoring/control/surveillance (MCS). The procedure is explained using a cultural center as an actual base case study. Additionally, the procedure was validated by implementing 40 voluntary commercial spaces in Zaragoza (Spain). Standardization of methods is suggested so that the measurement of CO2 becomes an effective strategy to control the airborne transmission of pathogens and thus prevent future Covid-19 outbreaks and novel pandemics.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.27.22280425", + "rel_abs": "The clinical course and severity of COVID-19 vary among patients. This study aimed to investigate the association of the interferon receptor (IFNAR2) rs2236757 and oligoadenylate synthetase 3 (OAS3) rs10735079 gene polymorphisms with risk of COVID-19 infection and severity among Palestinian patients. The study was conducted between April and May 2021 on 154 participants that divided into three groups: the control group (RT-PCR-negative, n=52), the community cases group (RT-PCR-positive, n= 70) and the critically ill cases (ICU group; n=32). Genotyping of the studied polymorphisms was conducted by amplicon-based next-generation sequencing.\n\nThe genotype distribution of the IFNAR2 rs2236757 was significantly different among the study groups (P = 0.001), while no significant differences were observed in the distribution of OAS3 rs10735079 genotypes (P = 0.091). Logistic regression analysis adjusted for possible confounding factors revealed a significant association between the risk allele rs2236757A and critical COVID-19 illness (P < 0.025). Among all patients, the rs2236757GA carriers were more likely to have sore throat (OR, 2.52 (95% CI 1.02-6.24); P = 0.011); the risk allele rs2236757A was associated with dyspnea (OR, 4.70 (95% CI 1.80-12.27); P < 0.001), while the rs10735079A carriers were less prone to develop muscle aches (OR, 0.34 (95% CI 0.13-0.88); P = 0.0248) and sore throat (OR, 0.17 (95% CI 0.05-0.55); P < 0.001). In conclusion, our results revealed that the rs2236757A variant was associated with critical COVID-19 illness and dyspnea, whereas the rs10735079A variant was protective for muscle aches and sore throat.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Marta Baselga", - "author_inst": "Institute for Health Research Aragon (IIS Aragon)" + "author_name": "Mohammad Abdelhafez", + "author_inst": "Al-Quds University" }, { - "author_name": "Juan J Alba", - "author_inst": "University of Zaragoza" + "author_name": "Abedelmajeed Nasereddin", + "author_inst": "Al-Quds University" + }, + { + "author_name": "Omar Abu Shamma", + "author_inst": "Al-Quds university" + }, + { + "author_name": "Rajaa Abed", + "author_inst": "Al-Quds University" + }, + { + "author_name": "Raghida Sinnokrot", + "author_inst": "Al-Quds University" + }, + { + "author_name": "Omar Marof", + "author_inst": "Al Quds University: Al-Quds University" + }, + { + "author_name": "Tariq Heif", + "author_inst": "Al-Quds University" + }, + { + "author_name": "Zaid Erekat", + "author_inst": "Al-Quds University" + }, + { + "author_name": "Amer Al-Jawabreh", + "author_inst": "Arab American University, Jenin, Palestine" }, { - "author_name": "Alberto J Schuhmacher", - "author_inst": "Institute for Health Research Aragon (IIS Aragon)" + "author_name": "suheir Ereqat", + "author_inst": "AL-Quds University, Al-Quds Public Health Soceity" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.09.23.22280294", @@ -219784,43 +219535,567 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2022.09.23.22279458", - "rel_title": "Pan-Canadian survey on the impact of the COVID-19 pandemic on cervical cancer screening and management", + "rel_doi": "10.1101/2022.09.24.22280269", + "rel_title": "Emergence and spread of two SARS-CoV-2 variants of interest in Nigeria.", "rel_date": "2022-09-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.23.22279458", - "rel_abs": "BackgroundThe COVID-19 pandemic has caused disruptions to cancer care by delaying diagnoses and treatment, presenting challenges and uncertainties for both patients and physicians. We conducted a nationwide online survey to investigate the effects of the pandemic and capture modifications, prompted by pandemic-related control measures, on cervical cancer screening-related activities from mid-March to mid-August 2020, across Canada.\n\nMethodsThe survey consisted of 61 questions related to the continuum of care in cervical cancer screening and treatment: appointment scheduling, tests, colposcopy, follow-up, treatment of pre-cancerous lesions/cancer, and telemedicine. We piloted the survey with 21 Canadian experts in cervical cancer prevention and care. We partnered with the Society of Canadian Colposcopists, Society of Gynecologic Oncology of Canada, Canadian Association of Pathologists, and Society of Obstetricians and Gynecologists of Canada, which distributed the survey to their members via email. We reached out to family physicians and nurse practitioners via MDBriefCase. The survey was also posted on McGill Channels (Department of Family Medicine News and Events) and social media platforms. The data were analyzed descriptively.\n\nResultsUnique responses were collected from 510 participants (16 November 2020 - 28 February 2021), representing 418 fully- and 92 partially-completed surveys. Responses were from Ontario (41.0%), British Columbia (21.0%), and Alberta (12.8%), and mostly comprised family physicians/general practitioners (43.7%), and gynecologist/obstetrician professionals (21.6%). Cancelled screening appointments were mainly reported by family physicians/general practitioners (28.3%), followed by gynecologist/obstetrician professionals (19.8%), and primarily occurred in private clinics (30.5%). Decreases in the number of screening Pap tests and colposcopy procedures were consistently observed across Canadian provinces. About 90% reported that their practice/institution adopted telemedicine to communicate with patients.\n\nConclusionsThe area most severely impacted by the pandemic was appointment scheduling, with an important level of cancellations reported. Survey results may inform resumptions of various fronts in cervical cancer screening and management.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.24.22280269", + "rel_abs": "Identifying the dissemination patterns and impacts of a virus of economic or health importance during a pandemic is crucial, as it informs the public on policies for containment in order to reduce the spread of the virus. In this study, we integrated genomic and travel data to investigate the emergence and spread of the B.1.1.318 and B.1.525 variants of interest in Nigeria and the wider Africa region. By integrating travel data and phylogeographic reconstructions, we find that these two variants that arose during the second wave emerged from within Africa, with the B.1.525 from Nigeria, and then spread to other parts of the world. Our results show how regional connectivity in downsampled regions like Africa can often influence virus transmissions between neighbouring countries. Our findings demonstrate the power of genomic analysis when combined with mobility and epidemiological data to identify the drivers of transmission in the region, generating actionable information for public health decision makers in the region.", + "rel_num_authors": 137, "rel_authors": [ { - "author_name": "Mariam El-Zein", - "author_inst": "Division of Cancer Epidemiology, McGill University, Montreal, Quebec, Canada" + "author_name": "Idowu Bolade Olawoye", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" }, { - "author_name": "Rami Ali", - "author_inst": "Division of Cancer Epidemiology, McGill University, Montreal, Quebec, Canada" + "author_name": "Paul Eniola Oluniyi", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" }, { - "author_name": "Eliya Farah", - "author_inst": "Division of Cancer Epidemiology, McGill University, Montreal, Quebec, Canada" + "author_name": "Edyth Parker", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Sarah Botting-Provost", - "author_inst": "Division of Cancer Epidemiology, McGill University, Montreal, Quebec, Canada" + "author_name": "Judith Uche Oguzie", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" }, { - "author_name": "Eduardo L. Franco", - "author_inst": "Division of Cancer Epidemiology, McGill University, Montreal, Quebec, Canada" + "author_name": "Jessica Nnenna Uwanibe", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" }, { - "author_name": "- Survey Study Group", - "author_inst": "" + "author_name": "Tolulope Adeyemi Kayode", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Fehintola Victoria Ajogbasile", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Testimony Jesupamilerin Olumade", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Philomena Eromon", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Priscilla Abechi", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Tope Sobajo", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Chinedu Ugwu", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "George Uwem", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Femi Ayoade", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Kazeem Akano", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Oluwasemilogo Oluwasekunolami Akinlo", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Julie Oreoluwa Akin-John", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Nicholas Oyejide", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Olubukola Ayo-Ale", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Benjamin Adegboyega", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Grace Chizaramu Chukwu", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Ayomide Adeleke", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Grace Opemipo Ezekiel", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Farida Brimmo", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Olanrewaju Odunyemi Fayemi", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Iyanuoluwa Fred-Akintunwa", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Ibrahim F. Yusuf", + "author_inst": "Clinical Health manager,SPDC, Port Harcourt" + }, + { + "author_name": "Testimony Oluwatise Ipaye", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Oluwagboadurami John", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Ahmed Iluoreh Muhammad", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Deborah Chisom Nwodo", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Olusola Akinola Ogunsanya", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Johnson Okolie", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Abolade Esther Omoniyi", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Iyobosa Beatrice Omwanghe", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Oludayo Oluwaseyi Ope-ewe", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Shobi Otitoola", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Kemi Adedotun-Suleiman", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Courage Philip", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Mudasiru Femi Saibu", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Ayotunde Elijah Sijuwola", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Christabel Anamuma Terkuma", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Augustine Abu", + "author_inst": "Virology Laboratory, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Johnson Adekunle Adeniji", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Moses Olubusuyi Adewunmi", + "author_inst": "Department of Virology, College of Medicine, University of Ibadan, Ibadan, Nigeria" + }, + { + "author_name": "Olufemi Oluwapelumi Adeyemi", + "author_inst": "Department of Medical Microbiology and Parasitology. Faculty of Basic Clinical Sciences. College of Health Sciences. University of Ilorin. Ilorin Nigeria" + }, + { + "author_name": "Rahaman Ahmed", + "author_inst": "The Nigerian Institute of Medical Research, Yaba, Lagos, Nigeria" + }, + { + "author_name": "Anthony Ahumibe", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Anthony Nnennaya Ajayi", + "author_inst": "Internal Medicine Department, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Olusola Akanbi", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Olatunji Akande", + "author_inst": "Biorepository Clinical Virology Laboratory" + }, + { + "author_name": "Monilade Akinola", + "author_inst": "WHO Polio Laboratory, University of Maiduguri Teaching Hospital, P.M.B. 1414, Maiduguri" + }, + { + "author_name": "Afolabi Akinpelu", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "George Akpede", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Ekanem Anieno", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Antjony E. Atage", + "author_inst": "Molecular Laboratory, Regional Centre for Biotechnology and Bioresources Research, University of Port Harcourt" + }, + { + "author_name": "Oyeronke Ayansola", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Marycelin Baba", + "author_inst": "Dept. of Immunology, University of Maiduguri Teaching Hospital, P.M.B. 1414, Maiduguri" + }, + { + "author_name": "Olajumoke Babatunde", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Bamidele Soji Oderinde", + "author_inst": "Dept. of Microbiology, University of Maiduguri Teaching Hospital, P.M.B. 1414, Maiduguri" + }, + { + "author_name": "Ebo Benevolence", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Osiemi Blessing", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Mienye Bob-Manuel", + "author_inst": "Satellite Molecular Laboratory, Rivers State University Teaching Hospital, Port Harcourt" + }, + { + "author_name": "Andrew Bock-Oruma", + "author_inst": "Family Physician, SPDC, Port Harcourt" + }, + { + "author_name": "Aire Chris", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Chimaobi Chukwu", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Funmi Daramola", + "author_inst": "Clinical Health, SPDC, Port Harcourt" + }, + { + "author_name": "Adomeh Donatus", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Rosemay Duruihuoma", + "author_inst": "Virology Laboratory, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Yerumoh Edna", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Matthew Ekeh", + "author_inst": "Virology Laboratory, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Erim Ndoma", + "author_inst": "Virology Laboratory, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Richard Ewah", + "author_inst": "Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Akinwumi Fajola", + "author_inst": "Regional community health, SPDC, Port Harcourt" + }, + { + "author_name": "Enoch Olowatosin Fakayode", + "author_inst": "Department of Public Health. Ministry of Health. Ilorin. Kwara State. Nigeria" + }, + { + "author_name": "Adeola Fowotade", + "author_inst": "Medical Microbiology and Parasitology Department, College of Medicine, University of Ibadan, Ibadan, Nigeria" + }, + { + "author_name": "Galadima Gadzama", + "author_inst": "Dept. of Medical Microbiology, University of Maiduguri Teaching Hospital, P.M.B. 1414, Maiduguri" + }, + { + "author_name": "Daniel Igwe", + "author_inst": "Medical Microbiology Department, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Odia Ikponmwosa", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Rafiu Olasunkanmi Isamotu", + "author_inst": "Ministry of Health, Osun State, Nigeria" + }, + { + "author_name": "Agbukor Jacqueline", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Aiyepada John", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Julie Johnson Ekpo", + "author_inst": "Department of Medical Microbiology and Parasitology, University of Uyo, Akwa Ibom State" + }, + { + "author_name": "Ibrahim Kida", + "author_inst": "Dept. of Immunology, University of Maiduguri Teaching Hospital, P.M.B. 1414, Maiduguri" + }, + { + "author_name": "Nwando Mba", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Airende Micheal", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Mirabeau Youtchou Tatfeng", + "author_inst": "Department of Medical Laboratory Science, Niger Delta University, Bayelsa State, Nigeria" + }, + { + "author_name": "Worbianueri Beatrice Moore-Igwe", + "author_inst": "Rivers State University, Port Harcourt" + }, + { + "author_name": "Anietie Moses", + "author_inst": "Department of Medical Microbiology and Parasitology, University of Uyo, Akwa Ibom State" + }, + { + "author_name": "Okonofua Naregose", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Nsikak-Abasi Ntia", + "author_inst": "Occupational Health, SPDC, Port Harcourt" + }, + { + "author_name": "Ifeanyi Nwafor", + "author_inst": "Virology Laboratory, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Elizabeth Odeh", + "author_inst": "Virology Laboratory, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Ephraim Ogbaini", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Kingsley Chiedozie Ojide", + "author_inst": "Virology Laboratory, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Sylvanus Okogbenin", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Peter Okokhere", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Sylvanus Okoro", + "author_inst": "Medical Microbiology Department, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Azuka Okwuraiwe", + "author_inst": "The Nigerian Institute of Medical Research, Yaba, Lagos, Nigeria" + }, + { + "author_name": "Olisa Olasunkanmi", + "author_inst": "Biorepository Clinical Virology Laboratory" + }, + { + "author_name": "Oluseyi Olayinka", + "author_inst": "Department of Virology, College of Medicine, University of Ibadan, Ibadan, Nigeria" + }, + { + "author_name": "Adesuyi Omoare", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Ewean Chukwuma Omoruyi", + "author_inst": "Medical Microbiology and Parasitology Department, College of Medicine, University of Ibadan, Ibadan, Nigeria" + }, + { + "author_name": "Hannah E. Omunakwe", + "author_inst": "Satellite Molecular Laboratory, Rivers State University Teaching Hospital, Port Harcourt" + }, + { + "author_name": "Emeka Onwe Ogah", + "author_inst": "Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Chika Onwuamah", + "author_inst": "The Nigerian Institute of Medical Research, Yaba, Lagos, Nigeria" + }, + { + "author_name": "Venatious Onyia", + "author_inst": "Virology Laboratory, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Akhilomen Patience", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Ebhodaghe Paulson", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Omiunu Racheal", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Esumeh Rita", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Giwa Rosemary", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Joseph Shaibu", + "author_inst": "The Nigerian Institute of Medical Research, Yaba, Lagos, Nigeria" + }, + { + "author_name": "Joseph Shaibu", + "author_inst": "The Nigerian Institute of Medical Research, Yaba, Lagos, Nigeria" + }, + { + "author_name": "Ehikhametalor Solomon", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Ngozi Ugwu", + "author_inst": "Haematology Department, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Collins Nwachi Ugwu", + "author_inst": "Internal Medicine Department, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Kingsley Ukwuaja", + "author_inst": "Internal Medicine Department, Alex Ekwueme Federal University Teaching Hospital, Abakaliki, Nigeria" + }, + { + "author_name": "Zara Wudiri", + "author_inst": "Dept. of Community Medicine , University of Maiduguri Teaching Hospital, P.M.B. 1414, Maiduguri" + }, + { + "author_name": "Nnaemeka Ndodo", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Brittany Petros", + "author_inst": "Broad Institute of Harvard and MIT, Cambridge, MA, USA" + }, + { + "author_name": "Bronwyn Mcannis", + "author_inst": "Broad Institute of Harvard and MIT, Cambridge, MA, USA" + }, + { + "author_name": "Cyril Oshomah", + "author_inst": "Irrua Specialist Teaching Hospital" + }, + { + "author_name": "Femi Oladiji", + "author_inst": "Department of Epidemiology and Community Health, Faculty of Clinical Sciences. College of Health Sciences. University of Ilorin. Ilorin. Nigeria" + }, + { + "author_name": "Katherine J. Siddle", + "author_inst": "Broad Institute of Harvard and MIT, Cambridge, MA, USA" + }, + { + "author_name": "Rosemary Audu", + "author_inst": "The Nigerian Institute of Medical Research, Yaba, Lagos, Nigeria" + }, + { + "author_name": "Babatunde Lawal Salako", + "author_inst": "The Nigerian Institute of Medical Research, Yaba, Lagos, Nigeria" + }, + { + "author_name": "Stephen Schaffner", + "author_inst": "Broad Institute of Harvard and MIT, Cambridge, MA, USA" + }, + { + "author_name": "Danny Park", + "author_inst": "Broad Institute of Harvard and MIT, Cambridge, MA, USA" + }, + { + "author_name": "Ifedayo Adetifa", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Chikwe Ihekweazu", + "author_inst": "Nigeria Centre for Disease Control, Abuja, Nigeria" + }, + { + "author_name": "Oyewale Tomori", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Anise Nkenjop Happi", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Onikepe Folarin", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" + }, + { + "author_name": "Kristian G. Andersen", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Pardis C. Sabeti", + "author_inst": "Broad Institute of Harvard and MIT, Cambridge, MA, USA" + }, + { + "author_name": "Christian Tientcha Happi", + "author_inst": "African Centre of Excellence for Genomics of Infectious Diseases (ACEGID), Redeemer's University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "oncology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.09.23.22280118", @@ -221734,47 +222009,35 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.09.22.508999", - "rel_title": "Triple COVID-19 vaccination induces humoral and cellular immunity to SARS-CoV-2 with cross-recognition of the Omicron variant and IgA secretion", + "rel_doi": "10.1101/2022.09.20.22279832", + "rel_title": "Simplified Within Host and Dose-response Models of SARS-CoV-2", "rel_date": "2022-09-22", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.22.508999", - "rel_abs": "COVID-19 vaccination is the leading strategy to prevent severe courses after SARS-CoV-2 infection. In our study, we analyzed humoral and cellular immune responses in detail to three consecutive homologous or heterologous COVID-19 vaccinations. All individuals (n=20) responded to vaccination with increasing S1- /RBD-/S2-specific IgG levels, whereas specific plasma IgA displayed individual variability. The third dose increased antibody inhibitory capacity (AIC) against immune-escape variants Beta and Omicron independently from age. The mRNA-primed vaccination induced IgG and IgA immunity more efficiently, whereas vector-primed individuals displayed higher levels of memory T and B cells. Vaccinees showed a SARS-CoV-2-specific T cell responses, which were further improved and specified after Omicron breakthrough infections in parallel to appearance of new variant-specific antibodies. In conclusion, the third vaccination was essential to increase IgG levels, mandatory to boost AIC against immune-escape variants and induced SARS-CoV-2-specific T cells. Breakthrough infection with Omicron generates additional spike specificities covering all known variants.", - "rel_num_authors": 7, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.20.22279832", + "rel_abs": "Understanding the mechanistic dynamics of transmission is key to designing more targeted and effective interventions to limit the spread of infectious diseases. A well-described within-host model allows explicit simulation of how infectiousness changes over time at an individual level. This can then be coupled with dose-response models to investigate the impact of timing on transmission. We collected and compared a range of within-host models used in previous studies and identified a minimally-complex model that provides suitable within-host dynamics while keeping a reduced number of parameters to allow inference and limit unidentifiability issues. Furthermore, non-dimensionalised models were developed to further overcome the uncertainty in estimates of the size of the susceptible cell population, a common problem in many of these approaches. We will discuss these models, and their fit to data from the human challenge study (see Killingley et al. (2022)) for SARS-CoV-2 and the model selection results, which has been performed using ABC-SMC. The parameter posteriors have then used to simulate viral-load based infectiousness profiles via a range of dose-response models, which illustrate the large variability of the periods of infection window observed for COVID-19.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Louisa Ruhl", - "author_inst": "Hannover Medical School" - }, - { - "author_name": "Jenny F Kuehne", - "author_inst": "Hannover Medical School" - }, - { - "author_name": "Kerstin Beushausen", - "author_inst": "Hannover Medical School" - }, - { - "author_name": "Jana Keil", - "author_inst": "Hannover Medical School" + "author_name": "Jingsi Xu", + "author_inst": "University of Manchester" }, { - "author_name": "Stella Christoph", - "author_inst": "Hannover Medical School" + "author_name": "Jonathan Carruthers", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Jasper Sauer", - "author_inst": "Hannover Medical School" + "author_name": "Thomas James Ronald Finnie", + "author_inst": "United Kingdom Health Security Agency" }, { - "author_name": "Christine S Falk", - "author_inst": "Hannover Medical School" + "author_name": "Ian Hall", + "author_inst": "University of Manchester" } ], "version": "1", - "license": "cc_by_nd", - "type": "new results", - "category": "immunology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.09.21.22280191", @@ -223720,55 +223983,75 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.09.19.22280079", - "rel_title": "The impact of prior COVID-19 on vaccine response and the resultant hybrid immunity are age-dependent", - "rel_date": "2022-09-19", + "rel_doi": "10.1101/2022.09.13.22279673", + "rel_title": "Social Media Data for Omicron Detection from Unscripted Voice Samples", + "rel_date": "2022-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.19.22280079", - "rel_abs": "BackgroundMore people with a history of prior infection are receiving SARS-CoV-2 vaccines. Understanding the magnitude of protectivity granted by hybrid immunity, the combined response of infection- and vaccine-induced immunity, may impact vaccination strategies.\n\nMethodsA total of 36 synchronously infected ( prior infection) and, 33 SARS-CoV-2 naive ( naive) individuals participated. Participants provided sera six months after completing a round of BNT162b2 vaccination, to be processed for anti-spike antibody measurements and neutralization assays. The relationships between antibody titer, groups and age were explored.\n\nResultsAnti-spike antibody titers at 6 months post-vaccination were significantly higher, reaching 13- to 17-fold, in the prior infection group. Linear regression models showed that the enhancement in antibody titer attributable to positive infection history increased from 8.9- to 9.4- fold at age 30 to 19- to 32-fold at age 60. Sera from the prior infection group showed higher neutralizing capacity against all six analyzed strains, including the Omicron variant.\n\nConclusionsPrior COVID-19 led to establishing enhanced humoral immunity at 6 months after vaccination. Antibody fold-difference attributed to positive COVID-19 history increased with age, possibly because older individuals are prone to symptomatic infection accompanied by potentiated immune responses. Durable protection of hybrid immunity deserves reflection in vaccination campaigns.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.13.22279673", + "rel_abs": "The success of artificial intelligence in clinical environments relies upon the diversity and availability of training data. In some cases, social media data may be used to counterbalance the limited amount of accessible, well-curated clinical data, but this possibility remains largely unexplored. In this study, we mined YouTube to collect voice data from individuals with self-declared positive COVID-19 tests during time periods in which Omicron was the predominant variant1,2,3, while also sampling non-Omicron COVID-19 variants, other upper respiratory infections (URI), and healthy subjects. The resulting dataset was used to train a DenseNet model to detect the Omicron variant from voice changes. Our model achieved 0.85/0.80 specificity/sensitivity in separating Omicron samples from healthy samples and 0.76/0.70 specificity/sensitivity in separating Omicron samples from symptomatic non-COVID samples. In comparison with past studies, which used scripted voice samples, we showed that leveraging the intra-sample variance inherent to unscripted speech enhanced generalization. Our work introduced novel design paradigms for audio-based diagnostic tools and established the potential of social media data to train digital diagnostic models suitable for real-world deployment.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Sachie Nakagama", - "author_inst": "Osaka Metropolitan University" + "author_name": "James Anibal", + "author_inst": "University of Oxford" }, { - "author_name": "Yu Nakagama", - "author_inst": "Osaka Metropolitan University" + "author_name": "Adam Landa", + "author_inst": "Clinical Center, National Institutes of Health" }, { - "author_name": "Yuko Komase", - "author_inst": "St.Mariannna University, Yokohama Seibu Hospital" + "author_name": "Hang Nguyen", + "author_inst": "Oxford University Clinical Research Unit" }, { - "author_name": "Masaharu Kudo", - "author_inst": "Osaka Metropolitan University" + "author_name": "Alec Peltekian", + "author_inst": "Northwestern University" }, { - "author_name": "Takumi Imai", - "author_inst": "Osaka Metropolitan University" + "author_name": "Andrew Shin", + "author_inst": "National Library of Medicine, National Institutes of Health" }, { - "author_name": "Yuko Nitahara", - "author_inst": "Osaka Metropolitan University" + "author_name": "Miranda Song", + "author_inst": "Clinical Center, National Institutes of Health" }, { - "author_name": "Natsuko Kaku", - "author_inst": "Osaka Metropolitan University" + "author_name": "Anna Christou", + "author_inst": "Clinical Center, National Institutes of Health" }, { - "author_name": "Evariste Tshibangu-Kabamba", - "author_inst": "Osaka Metropolitan University" + "author_name": "Lindsey Hazen", + "author_inst": "Clinical Center, National Institutes of Health" }, { - "author_name": "Yasutoshi Kido", - "author_inst": "Osaka Metropolitan University" + "author_name": "Jocelyne Rivera", + "author_inst": "University of Oxford" + }, + { + "author_name": "Robert Morhard", + "author_inst": "Clinical Center, National Institutes of Health" + }, + { + "author_name": "Ulas Bagci", + "author_inst": "Northwestern University" + }, + { + "author_name": "Ming Li", + "author_inst": "Clinical Center, National Institutes of Health" + }, + { + "author_name": "David Clifton", + "author_inst": "University of Oxford" + }, + { + "author_name": "Bradford Wood", + "author_inst": "Clinical Center, National Institutes of Health" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "health informatics" }, { "rel_doi": "10.1101/2022.09.15.22279735", @@ -225618,47 +225901,55 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2022.09.09.22279763", - "rel_title": "COVID-19 induced birth sex ratio changes in England and Wales", + "rel_doi": "10.1101/2022.09.09.22279765", + "rel_title": "SDG5 Gender Equality and the COVID-19 pandemic: a rapid assessment of health system responses in selected upper-middle and high-income countries", "rel_date": "2022-09-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.09.22279763", - "rel_abs": "BackgroundThe sex ratio at birth (male live births divided by total live births) may be a sentinel health indicator. Stressful events reduce this ratio 3-5 months later by increasing male fetal loss. This ratio can also change 9 months after major population events that are linked to an increase or decrease in the frequency of sexual intercourse at the population level, with the ratio either rising or falling respectively after the event. We postulated that stress caused by the COVID-19 pandemic may have affected the ratio in England and Wales.\n\nMethodsPublicly available, monthly live birth data for England and Wales was obtained from the Office for National Statistics up to December 2020. The sex ratio at birth for 2020 (global COVID-19 onset) was predicted using data from 2012-2019. Observed and predicted values were compared.\n\nResultsThree months after COVID-19 was declared pandemic (March 2020), there was a significant fall in the sex ratio at birth to 0.5100 in June 2020 which was below the 95% prediction interval of 0.5102-0.5179. Nine months after the pandemic declaration, (December 2020), there was a significant rise to 0.5171 (95% prediction interval 0.5085-0.5162). However, December 2020 had the lowest number of live births of any month from 2012 to 2020.\n\nConclusionsGiven that June 2020 falls within the crucial window when population stressors are known to affect the sex ratio at birth, these findings imply that the start of the COVID-19 pandemic caused population stress with notable effects on those who were already pregnant by causing a disproportionate loss of male fetuses. The finding of a higher sex ratio at birth in December 2020, i.e., 9 months after COVID-19 was declared a pandemic, suggests that lockdown restrictions initially spurred more sexual activity in a subset of the population in March 2020.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.09.22279765", + "rel_abs": "The COVID-19 pandemic disrupted healthcare and societies, exacerbating existing inequalities for women and girls across every sphere. Our study explores health system responses to gender equality goals during the COVID-19 pandemic and inclusion in future policies. We apply a qualitative comparative approach, drawing on secondary sources and expert information; material was collected from March to July 2022. Australia, Brazil, Germany, the United Kingdom and USA were selected, reflecting upper-middle and high-income countries with established public health and gender policies but different types of healthcare systems and epidemiological and geo-political conditions. Three sub-goals of SDG 5 were analysed: maternity care and reproductive health, gender-based violence, and gender equality and womens leadership. We found similar trends across countries. Pandemic policies strongly cut into womens health, constrained prevention and support services and weakened reproductive rights, while essential maternity care services were kept open. Intersecting gender inequalities were reinforced, sexual violence increased and womens leadership was weak. All healthcare systems failed to protect womens health and essential public health targets. Yet there were relevant differences in the responses to increased violence and reproductive rights, ranging from some support measures in Australia to an abortion ban in the US. Our study highlights a need for revising pandemic policies through a feminist lens.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Gwinyai Masukume", - "author_inst": "Independent Researcher, Munster, Ireland" + "author_name": "Ellen Kuhlmann", + "author_inst": "Hannover Medical School" }, { - "author_name": "Margaret Ryan", - "author_inst": "Trinity College Dublin, Dublin, Ireland" + "author_name": "Gabriela Lotta", + "author_inst": "Department of Public Administration, Getulio Vargas Foundation" }, { - "author_name": "Rumbidzai Masukume", - "author_inst": "Department of Obstetrics and Gynaecology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa" + "author_name": "Michelle Fernandez", + "author_inst": "Universidade de Brasilia" }, { - "author_name": "Dorota Zammit", - "author_inst": "National Statistics Office, Valletta, Malta" + "author_name": "Asha Herten-Crabb", + "author_inst": "London School of Economics and Political Science" }, { - "author_name": "Victor Grech", - "author_inst": "Academic Department of Paediatrics, Medical School, Mater Dei Hospital, Msida, Malta" + "author_name": "Leonie Mac Fehr", + "author_inst": "Hannover Medical School" }, { - "author_name": "Witness Mapanga", - "author_inst": "Division of Medical Oncology, Department of Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, So" + "author_name": "Jaimie-Lee Maple", + "author_inst": "University of Victoria Melbourne Australia" }, { - "author_name": "Yosuke Inoue", - "author_inst": "Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Ligia Paina", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" + }, + { + "author_name": "Clare Wenham", + "author_inst": "London School of Economics and Political Science (LSE)" + }, + { + "author_name": "Karen Willis", + "author_inst": "University of Victoria, Melbourne, Australia" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "category": "health policy" }, { "rel_doi": "10.1101/2022.09.13.22279890", @@ -227512,39 +227803,71 @@ "category": "bioengineering" }, { - "rel_doi": "10.1101/2022.09.14.507985", - "rel_title": "Analysis and comprehensive lineage identification for SARS-CoV-2 genomes through scalable learning methods", + "rel_doi": "10.1101/2022.09.13.22279868", + "rel_title": "Excess mortality in the general population versus Veterans Healthcare System during the first year of the COVID-19 pandemic in the United States", "rel_date": "2022-09-14", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.14.507985", - "rel_abs": "Since its emergence in late 2019, SARS-CoV-2 has diversified into a large number of lineages and globally caused multiple waves of infection. Novel lineages have the potential to spread rapidly and internationally if they have higher intrinsic transmissibility and/or can evade host immune responses, as has been seen with the Alpha, Delta, and Omicron variants of concern (VoC). They can also cause increased mortality and morbidity if they have increased virulence, as was seen for Alpha and Delta, but not Omicron. Phylogenetic methods provide the gold standard for representing the global diversity of SARS-CoV-2 and to identify newly emerging lineages. However, these methods are computationally expensive, struggle when datasets get too large, and require manual curation to designate new lineages. These challenges together with the increasing volumes of genomic data available provide a motivation to develop complementary methods that can incorporate all of the genetic data available, without down-sampling, to extract meaningful information rapidly and with minimal curation. Here, we demonstrate the utility of using algorithmic approaches based on word-statistics to represent whole sequences, bringing speed, scalability, and interpretability to the construction of genetic topologies, and while not serving as a substitute for current phylogenetic analyses the proposed methods can be used as a complementary approach to identify and confirm new emerging variants.", - "rel_num_authors": 5, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.13.22279868", + "rel_abs": "ImportanceThe COVID-19 pandemic had a substantial impact on the overall rate of death in the United States during the first year. It is unclear whether access to comprehensive medical care, such as through the VA healthcare system, altered death rates compared to the US population.\n\nObjectiveQuantify the increase in death rates during the first year of the COVID-19 pandemic in the general US population and among individuals who receive comprehensive medical care through the Department of Veterans Affairs (VA).\n\nDesignAnalysis of changes in all-cause death rates by quarter, stratified by age, sex race/ethnicity, and region, based on individual-level data. Hierarchical regression models were fit in a Bayesian setting. Standardized rates were used for comparison between populations.\n\nSetting and participantsGeneral population of the United States, enrollees in the VA, and active users of VA healthcare.\n\nExposure and main outcomeChanges in rates of death from any cause during the COVID-19 pandemic in 2020 compared to previous years.\n\nResultsSharp increases were apparent across all of the adult age groups (25 years and older) in both the general US population and the VA populations. Across all of 2020, the relative increase in death rates was similar in the general US population (RR: 1.20 (95% CI: 1.17, 1.22)), VA enrollees (RR: 1.20 (95% CI: 1.14, 1.29)), and VA active users (RR: 1.19 (95% CI: 1.14, 1.26)). Because the pre-pandemic standardized mortality rates were higher in the VA populations prior to the pandemic, the absolute rates of excess mortality were higher in the VA populations.\n\nConclusions and RelevanceDespite access to comprehensive medical care, active users of the VA had similar relative mortality increases from all causes compared with the general US population. Factors that influenced baseline rates of death and that mitigated viral transmission in the community are more likely to have influenced the impact of the pandemic.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Roberto Cahuantzi", - "author_inst": "Univeristy of Manchester" + "author_name": "Daniel M Weinberger", + "author_inst": "Yale School of Public Health, New Haven, CT; Department of Veterans Affairs Connecticut Healthcare System, West Haven, CT" }, { - "author_name": "Katrina Lythgoe", - "author_inst": "University of Oxford" + "author_name": "Liam Rose", + "author_inst": "Department of Veterans Affairs Medical Center, Palo Alto, CA; Stanford School of Medicine, Palo Alto, CA" }, { - "author_name": "Ian Hall", - "author_inst": "University of Manchester" + "author_name": "Christopher T. Rentsch", + "author_inst": "Department of Veterans Affairs Connecticut Healthcare System, West Haven, CT; London School of Hygiene & Tropical Medicine, London, England; Yale School of Medi" }, { - "author_name": "Lorenzo Pellis", - "author_inst": "University of Manchester" + "author_name": "Steven M Asch", + "author_inst": "Department of Veterans Affairs Medical Center, Palo Alto, CA; Stanford School of Medicine, Palo Alto, CA" }, { - "author_name": "Thomas A House", - "author_inst": "University of Manchester" + "author_name": "Jesse A Columbo", + "author_inst": "Department of Veterans Affairs Medical Center, White River Junction, VT; Geisel School of Medicine at Dartmouth, Hanover, NH" + }, + { + "author_name": "Joseph T King Jr.", + "author_inst": "Yale School of Medicine; Department of Veterans Affairs Connecticut Healthcare System, West Haven, CT" + }, + { + "author_name": "Caroline Korves", + "author_inst": "Department of Veterans Affairs Medical Center, White River Junction, VT" + }, + { + "author_name": "Brian P Lucas", + "author_inst": "Department of Veterans Affairs Medical Center, White River Junction, VT; Geisel School of Medicine at Dartmouth, Hanover, NH" + }, + { + "author_name": "Cynthia C Taub", + "author_inst": "Dartmouth Hitchcock Medical Center, Lebanon, NH" + }, + { + "author_name": "Yinong Young-Xu", + "author_inst": "Department of Veterans Affairs Medical Center, White River Junction, VT" + }, + { + "author_name": "Anita Vashi", + "author_inst": "Department of Veterans Affairs Medical Center, Palo Alto, CA; Stanford School of Medicine, Palo Alto, CA; Department of Emergency Medicine, University of Califo" + }, + { + "author_name": "Louise Davies", + "author_inst": "Department of Veterans Affairs Medical Center, White River Junction, VT; Geisel School of Medicine at Dartmouth, Hanover, NH" + }, + { + "author_name": "Amy C Justice", + "author_inst": "Department of Veterans Affairs Connecticut Healthcare System, West Haven, CT; Yale School of Medicine, New Haven, CT; Yale School of Public Health, New Haven, C" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "bioinformatics" + "license": "cc0", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.09.09.22277383", @@ -229522,141 +229845,93 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2022.09.08.22279729", - "rel_title": "Image-based and machine learning-guided multiplexed serology test for SARS-CoV-2", + "rel_doi": "10.1101/2022.09.07.22279662", + "rel_title": "The aerobiology of SARS-CoV-2 in UK hospitals and the impact of aerosol generating procedures", "rel_date": "2022-09-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.08.22279729", - "rel_abs": "Here, we describe a scalable and automated, high-content microscopy -based mini-immunofluorescence assay (mini-IFA) for serological testing i.e., detection of antibodies. Unlike conventional IFA, which often relies on the use of cells infected with the target pathogen, our assay employs transfected cells expressing individual viral antigens. The assay builds on a custom neural network-based image analysis pipeline for the automated and multiplexed detection of immunoglobulins (IgG, IgA, and IgM) in patient samples. As a proof-of-concept, we employed high-throughput equipment to set up the assay for measuring antibody response against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection with spike (S), membrane (M), and nucleo (N) proteins, and the receptor-binding domain (R) as the antigens. We compared the automated mini-IFA results from hundreds of patient samples to the visual observations of human experts and to the results obtained with conventional ELISA. The comparisons demonstrated a high correlation to both, suggesting high sensitivity and specificity of the mini-IFA. By testing pre-pandemic samples and those collected from patients with RT-PCR confirmed SARS-CoV-2 infection, we found mini-IFA to be most suitable for IgG and IgA detection. The results demonstrated N and S proteins as the ideal antigens, and the use of these antigens can serve to distinguish between vaccinated and infected individuals. The assay principle described enables detection of antibodies against practically any pathogen, and none of the assay steps require high biosafety level environment. The simultaneous detection of multiple Ig classes allows for distinguishing between recent and past infection.\n\nPublic abstractThe manuscript describes a miniaturized immunofluorescence assay (mini-IFA) for measuring antibody response in patient blood samples. The automated method builds on machine-learning -guided image analysis with SARS-CoV-2 as the model pathogen. The method enables simultaneous measurement of IgM, IgA, and IgG responses against different virus antigens in a high throughput manner. The assay relies on antigens expressed through transfection and allows for differentiation between vaccine-induced and infection-induced antibody responses. The transfection-based antigen expression enables performing the assay at a low biosafety level laboratory and allows fast adaptation of the assay to emerging pathogens. Our results provide proof-of-concept for the approach, demonstrating fast and accurate measurement of antibody responses in a clinical and research set-up.", - "rel_num_authors": 32, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.07.22279662", + "rel_abs": "BackgroundSARS-CoV-2 nosocomial transmission to patients and healthcare workers (HCWs) has occurred throughout the COVID-19 pandemic. Aerosol generating procedures (AGPs) seemed particularly risky, and policies have restricted their use in all settings. We examined the prevalence of aerosolized SARS-CoV-2 in the rooms of COVID-19 patients requiring AGP or supplemental oxygen compared to those on room air.\n\nMethodsSamples were collected prospectively near to adults hospitalised with COVID-19 at two tertiary care hospitals in the UK from November 2020 - October 2021. The Sartorius MD8 AirPort air sampler was used to collect air samples at a minimum distance of 1.5 meters from patients. RT-qPCR was used following overnight incubation of membranes in culture media and extraction.\n\nResultsWe collected 219 samples from patients rooms: individuals on room air (n=67), receiving oxygen (n=65) or AGP (n=67). Of these, 54 (24.6%) samples were positive for SARS-CoV-2 viral RNA. The highest prevalence was identified in the air around patients receiving oxygen (32.3%, n=21, CI95% 22.2 to 44.3%) with AGP and room air recording prevalence of (20.7%, n=18, CI95% 14.1 - 33.7%) and (22.3%, n=15, CI95% 13.5 - 30.4%) respectively. We did not detect a significant difference in the observed frequency of viral RNA between interventions.\n\nInterpretationSARS-CoV-2 viral RNA was detected in the air of hospital rooms of COVID-19 patients, and AGPs did not appear to impact the likelihood of viral RNA. Enhanced respiratory protection and appropriate infection prevention and control measures are required to be fully and carefully implemented for all COVID-19 patients to reduce risk of aerosol transmission.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Vilja Pietiainen", - "author_inst": "Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Minttu Polso", - "author_inst": "Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Ede Migh", - "author_inst": "Laboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, Szeged, Hungary" - }, - { - "author_name": "Christian Guckelsberger", - "author_inst": "Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland; Department of Computer" - }, - { - "author_name": "Maria Harmati", - "author_inst": "Laboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, Szeged, Hungary" - }, - { - "author_name": "Akos Diosdi", - "author_inst": "Laboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, Szeged, Hungary" - }, - { - "author_name": "Laura Turunen", - "author_inst": "Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Antti Hassinen", - "author_inst": "Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Swapnil Potdar", - "author_inst": "Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Annika Koponen", - "author_inst": "Minerva Foundation Institute for Medical Research, Helsinki, Finland; Department of Anatomy, Faculty of Medicine, University of Helsinki, Helsinki, Finland" - }, - { - "author_name": "Edina Gyukity-Sebestyen", - "author_inst": "Laboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, Szeged, Hungary" - }, - { - "author_name": "Ferenc Kovacs", - "author_inst": "Laboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, Szeged, Hungary; Single-Cell Technologies " - }, - { - "author_name": "Andras Kriston", - "author_inst": "Laboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, Szeged, Hungary; Single-Cell Technologies " + "author_name": "Susan Gould", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Reka Hollandi", - "author_inst": "Laboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, Szeged, Hungary" + "author_name": "Rachel L Byrne", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Katalin Burian", - "author_inst": "Department of Medical Microbiology, Faculty of Medicine, University of Szeged, Szeged, Hungary" + "author_name": "Thomas Edwards", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Gabriella Terhes", - "author_inst": "Department of Medical Microbiology, Faculty of Medicine, University of Szeged, Szeged, Hungary" + "author_name": "Ghaith Aljayyoussi", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Adam Visnyovszki", - "author_inst": "1st Department of Internal Medicine, Faculty of Medicine, University of Szeged, Szeged, Hungary" + "author_name": "Dominic Wooding", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Eszter Fodor", - "author_inst": "Department of Sports Physiology, Inst. Sports and Health Sciences, University of Physical Education, Budapest, Hungary" + "author_name": "Kate Buist", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Zsombor Lacza", - "author_inst": "Department of Sports Physiology, Inst. Sports and Health Sciences, University of Physical Education, Budapest, Hungary" + "author_name": "Konstantina Kontogianni", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Anu Kantele", - "author_inst": "Meilahti Infectious Diseases and Vaccine Research Center, MeiVac, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Human Microbiome R" + "author_name": "Allan M Bennett", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Pekka Kolehmainen", - "author_inst": "Institute of Biomedicine, University of Turku, Turku, Finland" + "author_name": "Barry Atkinson", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Laura Kakkola", - "author_inst": "Institute of Biomedicine, University of Turku, Turku, Finland" + "author_name": "Ginny Moore", + "author_inst": "UK Health Security Agency" }, { - "author_name": "Tomas Strandin", - "author_inst": "Department of Virology, Medicum, University of Helsinki, Helsinki, Finland" + "author_name": "Jake Dunning", + "author_inst": "University of Oxford" }, { - "author_name": "Lev Levanov", - "author_inst": "Department of Virology, Medicum, University of Helsinki, Helsinki, Finland" + "author_name": "Stacy Todd", + "author_inst": "Liverpool University Hospital Trust" }, { - "author_name": "Olli Kallioniemi", - "author_inst": "Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland;Department of Oncology-" + "author_name": "Marie-Claire Hoyle", + "author_inst": "Liverpool University Hospital Trust" }, { - "author_name": "Lajos Kemeny", - "author_inst": "HCEMM-USZ Skin Research Group, Department of Dermatology and Allergology, University of Szeged, Szeged, Hungary" + "author_name": "Lance Turtle", + "author_inst": "University of Liverpool" }, { - "author_name": "Ilkka Julkunen", - "author_inst": "Institute of Biomedicine, University of Turku, Turku, Finland; Turku University Hospital, Turku, Finland" + "author_name": "Tom Solomon", + "author_inst": "University of Liverpool" }, { - "author_name": "Olli Vapalahti", - "author_inst": "Department of Virology, Medicum, University of Helsinki, Helsinki, Finland; Department of Veterinary Biosciences, University of Helsinki, Helsinki, Finland; HUS" + "author_name": "Richard Fitzgerald", + "author_inst": "University of Liverpool" }, { - "author_name": "Krisztina Buzas", - "author_inst": "Laboratory of Microscopic Image Analysis and Machine Learning, Institute of Biochemistry, Biological Research Centre, Szeged, Hungary; Department of Immunology," + "author_name": "Mike Beadsworth", + "author_inst": "Liverpool University Hospital Trust" }, { - "author_name": "Lassi Paavolainen", - "author_inst": "Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland" + "author_name": "Paul Garner", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Peter Horvath", - "author_inst": "Institute for Molecular Medicine Finland (FIMM), Helsinki Institute of Life Sciences (HiLIFE), University of Helsinki, Helsinki, Finland; Laboratory of Microsco" + "author_name": "Emily R Adams", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Jussi Hepojoki", - "author_inst": "Department of Virology, Medicum, University of Helsinki, Helsinki, Finland; University of Zurich, Vetsuisse Faculty, Institute of Veterinary Pathology, Zurich, " + "author_name": "Tom Fletcher", + "author_inst": "Liverpool School of Tropical Medicine" } ], "version": "1", @@ -231488,67 +231763,75 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.09.09.507257", - "rel_title": "Cellular stress modulates severity of the acute respiratory distress syndrome in COVID-19", + "rel_doi": "10.1101/2022.09.07.506979", + "rel_title": "A novel biopolymer for mucosal adjuvant against respiratory pathogens", "rel_date": "2022-09-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.09.507257", - "rel_abs": "Inflammation is a central pathogenic feature of the acute respiratory distress syndrome (ARDS) in COVID-19. Previous pathologies such as diabetes, autoimmune or cardiovascular diseases become risk factors for the severe hyperinflammatory syndrome. A common feature among these risk factors is the subclinical presence of cellular stress, a finding that has gained attention after the discovery that BiP (GRP78), a master regulator of stress, participates in the SARS-CoV-2 recognition. Here, we show that BiP serum levels are higher in COVID-19 patients who present certain risk factors. Moreover, early during the infection, BiP levels predict severe pneumonia, supporting the use of BiP as a prognosis biomarker. Using a mouse model of pulmonary inflammation, we demonstrate that cell surface BiP (cs-BiP) responds by increasing its levels in leukocytes. Neutrophiles show the highest levels of cs-BiP and respond by increasing their population, whereas alveolar macrophages increase their levels of cs-BiP. The modulation of cellular stress with the use of a clinically approved drug, 4-PBA, resulted in the amelioration of the lung hyperinflammatory response, supporting the anti-stress therapy as a valid therapeutic strategy for patients developing ARDS. Finally, we identified stress-modulated proteins that shed light into the mechanism underlying the cellular stress-inflammation network in lungs.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.09.07.506979", + "rel_abs": "Mucosal vaccinations for respiratory pathogens provide effective protection as they stimulate localized cellular and humoral immunities at the site of infection. Currently, the major limitation of intranasal vaccination is using effective adjuvants capable of withstanding the harsh environment imposed by the mucosa. Herein, we describe the efficacy of using a novel biopolymer, N-dihydrogalactochitosan (GC), as a nasal mucosal vaccine adjuvant against respiratory infections. Specifically, using COVID as an example, we mixed GC with recombinant SARS-CoV-2 trimeric spike (S) and nucleocapsid (NC) proteins to intranasally vaccinate K18-hACE2 transgenic mice, in comparison with Addavax (AV), an MF-59 equivalent. In contrast to AV, intranasal application of GC induces a robust, systemic antigen-specific antibody response and increases the number of T cells in the cervical lymph nodes. Moreover, GC+S+NC-vaccinated animals were largely resistant to the lethal SARS-CoV-2 challenge and experienced drastically reduced morbidity and mortality, with animal weights and behavior returning to normal 22 days post-infection. In contrast, animals intranasally vaccinated with AV+S+NC experienced severe weight loss, mortality, and respiratory distress, with none surviving beyond 6 days post-infection. Our findings demonstrate that GC can serve as a potent mucosal vaccine adjuvant against SARS-CoV-2 and potentially other respiratory viruses.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Gustavo Rico-Llanos", - "author_inst": "CIBER-BBN" + "author_name": "", + "author_inst": "" }, { - "author_name": "Oscar Porras", - "author_inst": "IBIMA" + "author_name": "", + "author_inst": "" }, { - "author_name": "Sandra Escalante", - "author_inst": "University of Malaga" + "author_name": "", + "author_inst": "" }, { - "author_name": "Daniel Vazquez", - "author_inst": "University of Malaga" + "author_name": "", + "author_inst": "" }, { - "author_name": "Lucia Valiente", - "author_inst": "IBIMA" + "author_name": "", + "author_inst": "" }, { - "author_name": "Maria Castillo", - "author_inst": "IBIMA" + "author_name": "", + "author_inst": "" }, { - "author_name": "Jose Miguel Perez-Tejeiro", - "author_inst": "University of Malaga" + "author_name": "", + "author_inst": "" }, { - "author_name": "David Baglietto", - "author_inst": "University of Malaga" + "author_name": "", + "author_inst": "" }, { - "author_name": "Jose Becerra", - "author_inst": "University of Malaga" + "author_name": "", + "author_inst": "" }, { - "author_name": "Jose Maria Reguera", - "author_inst": "IBIMA" + "author_name": "", + "author_inst": "" }, { - "author_name": "Ivan Duran", - "author_inst": "University of Malaga" + "author_name": "", + "author_inst": "" }, { - "author_name": "Fabiana Csukasi", - "author_inst": "University of Malaga" + "author_name": "", + "author_inst": "" + }, + { + "author_name": "", + "author_inst": "" + }, + { + "author_name": "", + "author_inst": "" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "cell biology" + "category": "bioengineering" }, { "rel_doi": "10.1101/2022.09.09.507133", @@ -233618,23 +233901,67 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2022.09.02.22279526", - "rel_title": "Spatial determination of COVID-19 mortality", + "rel_doi": "10.1101/2022.09.02.22279519", + "rel_title": "Metagenomic next-generation sequencing to characterize etiologies of non-malarial fever in a cohort living in a high malaria burden area of Uganda", "rel_date": "2022-09-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.02.22279526", - "rel_abs": "COVID-19 has affected at the global scale. However, its impacts are not evenly distributed. The article aims to explore the spatial determination of the COVID-19 related death. The data for the analysis has been accessed from the World Health Organization (WHO). Both descriptive and statistical analysis has been done to assess the COVID-19 related death and spatial explanation. The regression models suggested the explanatory power of spatial difference in the COVID-19 related death. However, further addition of various COVID-19 vaccine did not produce expected result.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.09.02.22279519", + "rel_abs": "BackgroundCauses of non-malarial fevers in sub-Saharan Africa remain understudied. We hypothesized that metagenomic next-generation sequencing (mNGS), which allows for broad genomic-level detection of infectious agents in a biological sample, can systematically identify potential causes of non-malarial fevers.\n\nMethods and FindingsThe 212 participants in this study were of all ages and were enrolled in a longitudinal malaria cohort in eastern Uganda. Between December 2020 and August 2021, respiratory swabs and plasma samples were collected at 313 study visits where participants presented with fever and were negative for malaria by microscopy. Samples were analyzed using CZ ID, a web-based platform for microbial detection in mNGS data. Overall, viral pathogens were detected at 123 of 313 visits (39%). SARS-CoV-2 was detected at 11 visits, from which full viral genomes were recovered from nine. Other prevalent viruses included Influenza A (14 visits), RSV (12 visits), and three of the four strains of seasonal coronaviruses (6 visits). Notably, 11 influenza cases occurred between May and July 2021, coinciding with when the Delta variant of SARS-CoV-2 was circulating in this population. The primary limitation of this study is that we were unable to estimate the contribution of bacterial microbes to non-malarial fevers, due to the difficulty of distinguishing bacterial microbes that were pathogenic from those that were commensal or contaminants.\n\nConclusionsThese results revealed the co-circulation of multiple viral pathogens likely associated with fever in the cohort during this time period. This study illustrates the utility of mNGS in elucidating the multiple causes of non-malarial febrile illness. A better understanding of the pathogen landscape in different settings and age groups could aid in informing diagnostics, case management, and public health surveillance systems.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Arun GC", - "author_inst": "Tribhuvan University Central Department of Economics" + "author_name": "Lusajo Mwakibete", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Saki Takahashi", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Vida Ahyong", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Allison Black", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "John Rek", + "author_inst": "Infectious Diseases Research Collaboration" + }, + { + "author_name": "Isaac Ssewanyana", + "author_inst": "Infectious Diseases Research Collaboration" + }, + { + "author_name": "Moses Kamya", + "author_inst": "Infectious Diseases Research Collaboration" + }, + { + "author_name": "Grant Dorsey", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Prasanna Jagannathan", + "author_inst": "Stanford University" + }, + { + "author_name": "Isabel Rodriguez-Barraquer", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Cristina M. Tato", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "Bryan Greenhouse", + "author_inst": "University of California San Francisco" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.09.03.22279558", @@ -235288,37 +235615,57 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.08.31.22279444", - "rel_title": "Effectiveness of the COVID-19 vaccines against severe disease with Omicron sub-lineages BA.4 and BA.5 in England", + "rel_doi": "10.1101/2022.08.31.22279428", + "rel_title": "Effects of inbound attendees of a mass gathering event on the COVID-19 epidemic using individual-based simulations", "rel_date": "2022-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.31.22279444", - "rel_abs": "The Omicron sub-lineages BA.4 and BA.5 were first detected in England in April 2022. A case surge followed despite England having recently experienced waves with BA.1 and BA.2. This study used a whole population test-negative case-control study design to estimate the effectiveness of the vaccines currently in use as part of the UK COVID-19 vaccination programme against hospitalisation following infection with BA.4 and BA.5 as compared to BA.2 during a period of co-circulation. Incremental VE was estimated in those vaccinated with either a third or fourth dose as compared to individuals with waned immunity who had received their second dose at least 25 weeks prior. Vaccination status was included as an independent variable and effectiveness was defined as 1-odds of vaccination in cases/odds of vaccination in controls. During the study period, there were 32,845 eligible tests from hospitalised individuals. Of these, 25,862 were negative (controls), 3,432 were BA.2, 273 were BA.4, 947 were BA.5 and 2,331 were either BA.4 or BA.5 cases. There was no evidence of reduced VE against hospitalisation for BA.4 or BA.5 as compared to BA.2. The incremental VE was 56.8% (95% C.I.; 24.0-75.4%), 59.9% (95% C.I.; 45.6-70.5%) and 52.4% (95% C.I.; 43.2-60.1%) for BA.4, BA.5 and BA.2, respectively, at 2 to 14 weeks after a third or fourth dose. VE against hospitalisation with BA.4/5 or BA.2 was slightly higher for the mRNA-1273 booster than the BNT162b2 booster at all time-points investigated, but confidence intervals overlapped. These data provide reassuring evidence of the protection conferred by the current vaccines against severe disease with BA.4 and BA.5.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.31.22279428", + "rel_abs": "Given that mass gathering events involve heterogeneous and time-varying contact between residents and visitors, we sought to identify possible measures to prevent the potential acceleration of the outbreak of an emerging infectious disease induced by such events. An individual-based simulator was built based on a description of the reproduction rate among people infected with the infectious disease in a hypothetical city. Three different scenarios were assessed using our simulator, in which controls aimed at reduced contact were assumed to be carried out only in the main event venue or at subsequent additional events, or in which behavior restrictions were carried out among the visitors to the main event. The simulation results indicated that the increase in the number of patients with COVID-19 could possibly be suppressed to a level equivalent to that if the event were not being held so long as the prevalence among visitors was only slightly higher than that among domestic residents and strict requirements were applied to the activities of visitors.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Freja Kirsebom", - "author_inst": "UK Health Security Agency" + "author_name": "MASAYA SAITO", + "author_inst": "University of Nagasaki, Siebold" }, { - "author_name": "Nick Andrews", - "author_inst": "UK Health Security Agency" + "author_name": "Kotoe Katayama", + "author_inst": "The University of Tokyo" }, { - "author_name": "Julia Stowe", - "author_inst": "UK Health Security Agency" + "author_name": "Akira Naruse", + "author_inst": "NVIDA" }, { - "author_name": "Mary Ramsay", - "author_inst": "UK Health Security Agency" + "author_name": "Peiying Ruan", + "author_inst": "NVIDIAAI Technology Center" }, { - "author_name": "Jamie Lopez Bernal", - "author_inst": "UK Health Security Agency" + "author_name": "Michio Murakami", + "author_inst": "Osaka University" + }, + { + "author_name": "Tomoaki Okuda", + "author_inst": "Keio University" + }, + { + "author_name": "Tetsuo Ysutaka", + "author_inst": "National Institute of Advanced Industrial Science and Technology (AIST)" + }, + { + "author_name": "Wataru Naito", + "author_inst": "National Institute of Advanced Industrial Science and Technology (AIST)" + }, + { + "author_name": "Masaharu Tsubokura", + "author_inst": "Fukushima Medical University School of Medicine" + }, + { + "author_name": "Seiya Imoto", + "author_inst": "The University of Tokyo" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -237078,51 +237425,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.08.29.22279161", - "rel_title": "Organizational impact of an ID NOW COVID-19 point-of-care testing for SARS-CoV2 detection in a maternity ward", + "rel_doi": "10.1101/2022.08.30.22279383", + "rel_title": "Polygenic Risk Scores for Asthma and Allergic Disease Predict COVID-19 Severity in 9/11 Responders", "rel_date": "2022-08-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.29.22279161", - "rel_abs": "BackgroundSARS-CoV-2 has been responsible for more than 550 million cases of COVID-19 worldwide. RT-PCR is considered the \"gold standard\" for the diagnosis of patients suspected of having COVID-19. During the heightened waves of the pandemic, more rapid tests have been required. Point-of-care tests (POCT) for COVID-19 include antigen tests, serological tests, and other molecular-based platforms. The ID NOW COVID-19 assay (Abbott) performs an isothermal gene amplification of a target encoding the RNA-dependent RNA polymerase of SARSCoV-2. The main objective of this study was to evaluate the organizational impact following the implementation of a POC testing platform ID NOW in a maternity ward.\n\nMaterials and MethodsThis retrospective study included pregnant women admitted for Groupe Hospitalier Paris Saint-Joseph Paris. The study was conducted over 2 periods lasting 6 months each. The first period (P1) corresponded to the 2nd wave in France (July to December 2020) whereas the second (P2) period focused on the 3rd wave (February to July 2021). During P1, viral detection was performed by RT-PCR at the hospitals laboratory. During P2, it was performed with the ID NOW COVID-19 test directly in the delivery room by nursing staff after training and certification. Our primary endpoint was the length of time in the birth room from admission to discharge in the postpartum period.\n\nResults2447 pregnant women were included, 1053 during P1 and 1394 during P2. The median age, percentage of singleton pregnancies, mean gestational age, percentage of nulliparous individuals, percentage of vaginal deliveries, and COVID19 positivity rate were comparable between the two periods. During P2, the length of stay in the delivery room was significantly shorter than during P1 (17.9 vs 14.7 hours, p<0.001).\n\nConclusionAnalysis of the data from this study following the implementation of the ID NOW POCT in the maternity ward indicates a significant decrease in the length of stay in the birth room. This outcome needs to be confirmed in a multicenter cohort, in particular to precise the specific impact of COVID-19 care on delays.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.30.22279383", + "rel_abs": "BackgroundGenetic factors contribute to individual differences in the severity of coronavirus disease 2019 (COVID-19). A portion of genetic predisposition can be captured using polygenic risk scores (PRS). Relatively little is known about the associations between PRS and COVID-19 severity or post-acute COVID-19 in community-dwelling individuals.\n\nMethodsParticipants in this study were 983 World Trade Center responders infected for the first time with SARS-CoV-2 (mean age at infection=56.06; 93.4% male; 82.7% European ancestry). Seventy-five (7.6%) responders were in the severe COVID-19 category; 306 (31.1%) reported at least one post-acute COVID-19 symptom at 4-week follow-up. Analyses were adjusted for population stratification and demographic covariates.\n\nFindingsThe asthma PRS was associated with severe COVID-19 category (odds ratio [OR]=1.61, 95% confidence interval: 1.17-2.21) and more severe COVID-19 symptomatology ({beta}=.09, p=.01), independently of respiratory disease diagnosis. Severe COVID-19 category was also associated with the allergic disease PRS (OR=1.97, [1.26-3.07]) and the PRS for COVID-19 hospitalization (OR=1.35, [1.01-1.82]). PRS for coronary artery disease and type II diabetes were not associated with COVID-19 severity.\n\nConclusionRecently developed polygenic biomarkers for asthma, allergic disease, and COVID-19 hospitalization capture some of the individual differences in severity and clinical course of COVID-19 illness in a community population.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Jean-Claude Nguyen Van", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Monika Waszczuk", + "author_inst": "Rosalind Franklin University of Medicine and Science" }, { - "author_name": "Benoit Pilmis", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Olga Morozova", + "author_inst": "SUNY Stony Brook" }, { - "author_name": "Amir Khaterchi", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Elizabeth Lhuillier", + "author_inst": "Stony Brook University" }, { - "author_name": "Olivier Billuart", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Anna Docherty", + "author_inst": "University of Utah School of Medicine" }, { - "author_name": "Gauthier Pean de Ponfilly", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Andrey Shabalin", + "author_inst": "University of Utah School of Medicine" }, { - "author_name": "Alban Le Monnier", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Xiaohua Yang", + "author_inst": "Stony Brook University" }, { - "author_name": "Elie Azria", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Melissa Carr", + "author_inst": "Stony Brook University" }, { - "author_name": "Assaf Mizrahi", - "author_inst": "Groupe Hospitalier Paris Saint-Joseph" + "author_name": "Sean Clouston", + "author_inst": "Renaissance School of Medicine at Stony Brook University" + }, + { + "author_name": "Roman Kotov", + "author_inst": "Stony Brook University" + }, + { + "author_name": "Benjamin Luft", + "author_inst": "Stony Brook University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2022.08.30.505841", @@ -238992,127 +239347,95 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.24.22279159", - "rel_title": "Dynamics of anti-S IgG antibodies titers after the second dose of COVID 19 mRNA and non-mRNA vaccines in the manual and craft worker population of Qatar", + "rel_doi": "10.1101/2022.08.24.22279197", + "rel_title": "TRENDS IN CASES, HOSPITALISATION AND MORTALITY RELATED TO THE OMICRON BA.4/BA.5 SUB-VARIANTS IN SOUTH AFRICA", "rel_date": "2022-08-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.24.22279159", - "rel_abs": "BackgroundThere is limited seroepidemiological evidence on the magnitude and long-term durability of antibody titers of mRNA and non-mRNA vaccines in the Qatari population. This study was conducted to generate evidence on long-term anti-S IgG antibodies titers and their dynamics in individuals who have completed a primary COVID-19 vaccination schedule.\n\nMethodsA total of 300 participants who received any of the following vaccines BNT162b2/Comirnaty or mRNA-1273 or ChAdOx1-S/Covishield or COVID-19 Vaccine Janssen/Johnson or BBIBP-CorV or Covaxin were enrolled in our study. All sera samples were tested by chemiluminescent microparticle immunoassay (CMIA) for the quantitative determination of IgG antibodies to SARS-CoV-2, receptor-binding domain (RBD) of the S1 subunit of the spike protein of SARS-CoV-2. Antibodies against SARS-CoV-2 nucleocapsid (SARS-CoV-2 N-protein IgG) were also determined. Kaplan-Meier survival curves were used to compare the time from the last dose of the primary vaccination schedule to the time by which anti-S IgG antibodies titers fell into the lowest quartile (range of values collected) for the mRNA and non-mRNA vaccines.\n\nResultsParticipants vaccinated with mRNA vaccines had higher median anti-S IgG antibody titers. Participants vaccinated with the mRNA-1273 vaccine had the highest median anti-S-antibody level of 13720.9 AU/mL (IQR 6426.5 to 30185.6 AU/mL) followed by BNT162b2 (median, 7570.9 AU/ml; IQR, 3757.9 to 16577.4 AU/mL); while the median anti-S antibody titer for non-mRNA vaccinated participants was 3759.7 AU/mL (IQR, 2059.7-5693.5 AU/mL). The median time to reach the lowest quartile was 3.53 months (IQR, 2.2-4.5 months) and 7.63 months (IQR, 6.3-8.4 months) for the non-mRNA vaccine recipients and Pfizer vaccine recipients, respectively. However, more than 50% of the Moderna vaccine recipients did not reach the lowest quartile by the end of the follow-up period.\n\nConclusionsThis evidence on anti-S IgG antibody titers, their durability and decay over time should be considered for the utility of these assays in transmission dynamics after the full course of primary vaccination.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.24.22279197", + "rel_abs": "IntroductionThe Omicron BA.1/BA.2 wave in South Africa had lower hospitalisation and mortality than previous SARS-CoV-2 variants and was followed by an Omicron BA.4/BA.5 wave. This study compared admission incidence risk across waves, and the risk of mortality in the Omicron BA.4/BA.5 wave, to the Omicron BA.1/BA.2 and Delta waves.\n\nMethodsData from South Africas national hospital surveillance system, SARS-CoV-2 case linelist and Electronic Vaccine Data System were linked and analysed. Wave periods were defined when the country passed a weekly incidence of 30 cases/100,000 people. Mortality rates in the Delta, Omicron BA.1/BA.2 and Omicron BA.4/BA.5 wave periods were compared by post-imputation random effect multivariable logistic regression models.\n\nResultsIn-hospital deaths declined 6-fold from 37,537 in the Delta wave to 6,074 in the Omicron BA.1/BA.2 wave and a further 7-fold to 837 in the Omicron BA.4/BA.5 wave. The case fatality ratio (CFR) was 25.9% (N=144,798), 10.9% (N=55,966) and 7.1% (N=11,860) in the Delta, Omicron BA.1/BA.2, and Omicron BA.4/BA.5 waves respectively. After adjusting for age, sex, race, comorbidities, health sector and province, compared to the Omicron BA.4/BA.5 wave, patients had higher risk of mortality in the Omicron BA.1/BA.2 wave (adjusted odds ratio [aOR] 1.43; 95% confidence interval [CI] 1.32-1.56) and Delta (aOR 3.22; 95% CI 2.98-3.49) wave. Being partially vaccinated (aOR 0.89, CI 0.86-0.93), fully vaccinated (aOR 0.63, CI 0.60-0.66) and boosted (aOR 0.31, CI 0.24-0.41); and prior laboratory-confirmed infection (aOR 0.38, CI 0.35-0.42) were associated with reduced risks of mortality.\n\nConclusionOverall, admission incidence risk and in-hospital mortality, which had increased progressively in South Africas first three waves, decreased in the fourth Omicron BA.1/BA.2 wave and declined even further in the fifth Omicron BA.4/BA.5 wave. Mortality risk was lower in those with natural infection and vaccination, declining further as the number of vaccine doses increased.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Devendra Bansal", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" - }, - { - "author_name": "Hassan Atia", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" - }, - { - "author_name": "Mashael Al Badr", - "author_inst": "National Reference Laboratory, Ministry of Public Health, Doha 42, Qatar" - }, - { - "author_name": "Mohamed Nour", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" - }, - { - "author_name": "Jazeel Abdulmajeed", - "author_inst": "Primary Health Care Corporation" - }, - { - "author_name": "Amal Hasan", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" - }, - { - "author_name": "Noora Al-Hajri", - "author_inst": "National Reference Laboratory, Ministry of Public Health, Doha 42, Qatar" - }, - { - "author_name": "Lina Ahmed", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" - }, - { - "author_name": "Rumissa Ibrahim", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "WAASILA JASSAT", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Reham Zamel", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Salim Abdool Karim", + "author_inst": "Centre for the AIDS Programme of Research in South Africa" }, { - "author_name": "Almuthana Mohamed", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Lovelyn Ozougwu", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Hamad Pattalaparambil", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Richard Welch", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Faisal Daraan", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Caroline Mudara", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Adil Chaudhry", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Maureen Masha", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Sahar Oraby", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Petro Rousseau", + "author_inst": "National Department of Health" }, { - "author_name": "Sahar El-Saleh", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Milani Wolmarans", + "author_inst": "National Department of Health" }, { - "author_name": "Sittana S El-Shafie", - "author_inst": "National Reference Laboratory, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Anthony Selikow", + "author_inst": "Council for Scientific and Industrial Research" }, { - "author_name": "Affra Faiz Al-Farsi", - "author_inst": "Laboratory Section, Medical Commission Department, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Nevashan Govender", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Jiji Paul", - "author_inst": "Laboratory Section, Medical Commission Department, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Sibongile Walaza", + "author_inst": "National Institute for Communicable Diseases of the National Health Laboratory Services. University of the Witwatersrand" }, { - "author_name": "Ahmed Ismail", - "author_inst": "Laboratory Section, Medical Commission Department, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Anne von Gottberg", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Hamad E. Al-Romaihi", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Nicole Wolter", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Mohammed H Al-Thani", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Pedro Terrence Pisa", + "author_inst": "Right to Care" }, { - "author_name": "Suhail A.R. Doi", - "author_inst": "Department of Population Medicine, College of Medicine, Q U Health, Qatar University, Doha, Qatar" + "author_name": "Ian Sanne", + "author_inst": "Right to Care" }, { - "author_name": "Susu M Zughaier", - "author_inst": "Department of Basic Medical Sciences, College of Medicine, Q U Health, Qatar University, Doha, Qatar" + "author_name": "Sharlene Govender", + "author_inst": "Right to Care" }, { - "author_name": "Farhan Cyprian", - "author_inst": "Department of Basic Medical Sciences, College of Medicine, Q U Health, Qatar University, Doha, Qatar" + "author_name": "Lucille Blumberg", + "author_inst": "National institute for communicable diseases of South Africa" }, { - "author_name": "Elmobashar Farag", - "author_inst": "Health Protection and Communicable Disease Control, Ministry of Public Health, Doha 42, Qatar" + "author_name": "Cheryl Cohen", + "author_inst": "National Institute for Communicable Diseases" }, { - "author_name": "Habib Hasan Farooqui", - "author_inst": "Department of Population Medicine, College of Medicine, Q U Health, Qatar University, Doha, Qatar" + "author_name": "Michelle Groome", + "author_inst": "National Institute for Communicable Diseases" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.08.24.22279143", @@ -240818,65 +241141,137 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.22.22279079", - "rel_title": "Assessing Vulnerability to COVID-19 in High-Risk Populations: The Role of SARS-CoV-2 Spike-Targeted Serology", + "rel_doi": "10.1101/2022.08.22.22279060", + "rel_title": "Omicron B.1.1.529 variant infections associated with severe disease are uncommon in a COVID-19 under-vaccinated, high SARS-CoV-2 seroprevalence population in Malawi", "rel_date": "2022-08-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.22.22279079", - "rel_abs": "ImportanceIndividuals at increased risk for severe outcomes from COVID-19, due to compromised immunity or other risk factors, would benefit from objective measures of vulnerability to infection based on prior infection and/or vaccination. We reviewed published data to identify a specific role and interpretation of SARS-CoV-2 spike-targeted serology testing for such individuals. We also provide real-world evidence of spike-targeted antibody test results, identifying the seronegativity rate across the United States from March 2021 through June 2022. Analysis of antibody test results were compared between post-transplant (ie, immunocompromised) and all other patients tested in the first half of 2022. Finally, specific recommendations are provided for an evidence-based and clinically useful interpretation of spike-targeted serology to identify vulnerability to infection and potential subsequent adverse outcomes.\n\nObservationsDecreased vaccine effectiveness among immunocompromised individuals is linked to correspondingly high rates of breakthrough infections. Evidence indicates that negative results on SARS-CoV-2 antibody tests are associated with increased risk for subsequent infection. Results from widely available, laboratory-based tests do not provide a direct measure of protection but appear to correlate well with the presence of surrogate pseudovirus-neutralizing antibodies. The results of SARS-CoV-2 semiquantitative tests have also been associated with vaccine effectiveness and the likelihood of breakthrough infection. The data suggest that \"low-positive\" results on semiquantitative SARS-CoV-2 spike-targeted antibody tests may help identify persons at increased relative risk for breakthrough infection leading to adverse outcomes. In an analysis of data from large national laboratories during the COVID-19 Omicron-related surge in 2022, results from SARS-CoV-2 spike-targeted antibody tests were negative in 16.6% (742/4459) of solid organ transplant recipients tested compared to only 11.0% (47,552/432,481) of the remaining tested population.\n\nConclusions and RelevanceStandardized semiquantitative and quantitative SARS-CoV-2 spike-targeted antibody tests may provide objective information on risk of SARS-CoV-2 infection and associated adverse outcomes. This holds especially for high-risk populations, including transplant recipients, who demonstrate a relatively higher rate of seronegativity. The widespread availability of such tests presents an opportunity to refine risk assessment for individuals with suboptimal SARS-CoV-2 antibody levels and to promote effective interventions. Interim federal guidance would support physicians and patients while additional investigations are pursued.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.22.22279060", + "rel_abs": "BackgroundThe B.1.1.529 (Omicron) variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has resulted in the fourth COVID-19 pandemic wave across the southern African region, including Malawi. The seroprevalence of SARS-CoV-2 antibodies and their association with epidemiological trends of hospitalisations and deaths are needed to aid locally relevant public health policy decisions.\n\nMethodsWe conducted a population-based serosurvey from December 27, 2021 to January 17, 2022, in 7 districts across Malawi to determine the seroprevalence of SARS-CoV-2 antibodies. Primary sampling units (PSU) were selected using probability proportionate to the number of households based on the 2018 national census, followed by second-stage sampling units that were selected from listed households. A random systematic sample of households was selected from each PSU within the 7 districts. Serum samples were tested for antibodies against SARS-CoV-2 receptor binding domain using WANTAI SARS-CoV-2 Receptor Binding Domain total antibody commercial enzyme-linked immunosorbent assay (ELISA). We also evaluated COVID-19 epidemiologic trends in Malawi, including cases, hospitalizations and deaths from April 1, 2021 through April 30, 2022, collected using the routine national COVID-19 reporting system.\n\nResultsSerum samples were analysed from 4619 participants (57% female; 65% aged 14 to 50 years), of whom 1018 (22%) had received a COVID-19 vaccine. The overall assay-adjusted seroprevalence was 86.3% (95% confidence interval (CI), 85.1% to 87.5%). Seroprevalence was lowest among children <13 years of age (66%) and highest among adults 18 to 50 years of age (82%). Seroprevalence was higher among vaccinated compared to unvaccinated participants (96% vs. 77%; risk ratio, 6.65; 95% CI, 4.16 to 11.40). Urban residents were more likely to test seropositive than those living in rural settings (91% vs. 78%; risk ratio, 2.81; 95% CI, 2.20 to 3.62). National COVID-19 data showed that at least a two-fold reduction in the proportion of hospitalisations and deaths among the reported cases in the fourth wave compared to the third wave (hospitalization, 10.7% (95% CI, 10.2 to 11.3) vs 4.86% (95% CI, 4.52 to 5.23), p<0.0001; deaths, 3.48% (95% CI, 3.18 to 3.81) vs 1.15% (95% CI, 1.00 to 1.34), p<0.0001).\n\nConclusionWe report reduction in proportion of hospitalisations and deaths from SARS-CoV-2 infections during the Omicron variant dominated wave in Malawi, in the context of high SARS-CoV-2 seroprevalence but low COVID-19 vaccination coverage. These findings suggest that COVID-19 vaccination policy in high seroprevalence settings may need to be amended from mass campaigns to targeted vaccination of at-risk populations.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Harvey W Kaufman", - "author_inst": "Quest Diagnostics" + "author_name": "Upendo L Mseka", + "author_inst": "Malawi-Liverpool-Wellcome Programme" }, { - "author_name": "William A Meyer", - "author_inst": "Quest Diagnostics" + "author_name": "Jonathan Mandolo", + "author_inst": "Malawi-Liverpool-Wellcome Programme" }, { - "author_name": "Nigel J Clarke", - "author_inst": "Quest Diagnostics" + "author_name": "Kenneth Nyoni", + "author_inst": "Public Health Institute of Malawi" }, { - "author_name": "William A Meyer", - "author_inst": "Quest Diagnostics" + "author_name": "Oscar Divala", + "author_inst": "Public Health Institute of Malawi" }, { - "author_name": "Christopher M Rank", - "author_inst": "Roche Diagnostics" + "author_name": "Dzinkambani Kambalame", + "author_inst": "Public Health Institute of Malawi" }, { - "author_name": "James Freeman", - "author_inst": "Siemens Healthineers" + "author_name": "Daniel Mapemba", + "author_inst": "Public Health Institute of Malawi" }, { - "author_name": "Marcia Eisenberg", - "author_inst": "LabCorp" + "author_name": "Moses Kamzati", + "author_inst": "Public Health Institute of Malawi" }, { - "author_name": "Laura Gillim", - "author_inst": "LabCorp" + "author_name": "Innocent Chibwe", + "author_inst": "Public Health Institute of Malawi" }, { - "author_name": "William G Morice", - "author_inst": "Mayo Medical Laboratories" + "author_name": "Marc Y.R Henrion", + "author_inst": "Malawi-Liverpool-Wellcome Programme" }, { - "author_name": "David M Briscoe", - "author_inst": "Boston Children's Hospital" + "author_name": "Kingsley Manda", + "author_inst": "National Statistical Office" }, { - "author_name": "David S Perlin", - "author_inst": "Center for Discovery and Innovation, Hackensack Meridian Health" + "author_name": "Deus Thindwa", + "author_inst": "Malawi-Liverpool-Wellcome Programme" }, { - "author_name": "Jay G Wohlgemuth", - "author_inst": "Quest Diagnostics" + "author_name": "Memory Mvula", + "author_inst": "Malawi-Liverpool-Wellcome Programme" + }, + { + "author_name": "Bright Odala", + "author_inst": "Public Health Institute of Malawi" + }, + { + "author_name": "Nelson Dzinza", + "author_inst": "National Statistical Office" + }, + { + "author_name": "Khuzwayo C Jere", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Nicholas Feasey", + "author_inst": "Malawi-Liverpool-Wellcome Programme" + }, + { + "author_name": "Antonia Ho", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Abena S Amoah", + "author_inst": "Malawi Epidemiology and Intervention Unit" + }, + { + "author_name": "Melita Gordon", + "author_inst": "Malawi-Liverpool-Wellcome Programme" + }, + { + "author_name": "Todd D Swarthout", + "author_inst": "NIHR Mucosal Pathogens Research Unit" + }, + { + "author_name": "Amelia Crampin", + "author_inst": "Malawi Epidemiology and Intervention Unit" + }, + { + "author_name": "Robert S Heyderman", + "author_inst": "NIHR Mucosal Pathogens Research Unit" + }, + { + "author_name": "Matthew Kagoli", + "author_inst": "Public Health Institute of Malawi" + }, + { + "author_name": "Evelyn Chitsa-Banda", + "author_inst": "Public Health Institute of Malawi" + }, + { + "author_name": "Collins Mitambo", + "author_inst": "Public Health Institute of Malawi" + }, + { + "author_name": "John Phuka", + "author_inst": "Public Health Institute of Malawi" + }, + { + "author_name": "Benson Chilima", + "author_inst": "Public Health Institute of Malawi" + }, + { + "author_name": "Watipaso Kasambara", + "author_inst": "Public Health Institute of Malawi" + }, + { + "author_name": "Kondwani C Jambo", + "author_inst": "Malawi-Liverpool-Wellcome Programme" + }, + { + "author_name": "Annie Chauma-Mwale", + "author_inst": "Public Health Institute of Malawi" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -242504,71 +242899,31 @@ "category": "transplantation" }, { - "rel_doi": "10.1101/2022.08.20.22279023", - "rel_title": "Brain microstructural changes and fatigue after COVID-19", + "rel_doi": "10.1101/2022.08.20.22279020", + "rel_title": "Clinical Study to Evaluate the Possible Efficacy and Safety of Antibodies Combination (casirivimab and imdevimab) versus standard antiviral therapy as antiviral agent against Corona virus 2 infection in hospitalized COVID-19 patients", "rel_date": "2022-08-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.20.22279023", - "rel_abs": "BackgroundFatigue and cognitive complaints are the most frequent persistent symptoms in patients after severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This study aimed to assess fatigue and neuropsychological performance and investigate changes in the thickness and volume of gray matter (GM) and microstructural abnormalities in the white matter (WM) in a group of patients with mild-to-moderate coronavirus disease 2019 (COVID-19).\n\nMethodsWe studied 56 COVID-19 patients and 37 matched controls using magnetic resonance imaging (MRI). Cognition was assessed using Montreal Cognitive Assessment and Cambridge Neuropsychological Test Automated Battery, and fatigue was assessed using Chalder Fatigue Scale (CFQ-11). T1-weighted MRI was used to assess GM thickness and volume. Fiber-specific apparent fiber density (FD), free water index, and diffusion tensor imaging data were extracted using diffusion-weighted MRI (d-MRI). d-MRI data were correlated with clinical and cognitive measures using partial correlations and general linear modeling.\n\nResultsCOVID-19 patients had mild-to-moderate acute illness (95% non-hospitalized). The average period between real-time quantitative reverse transcription polymerase chain reaction-based diagnosis and clinical/MRI assessments was 93.3 ({+/-}26.4) days. The COVID-19 group had higher CFQ-11 scores than the control group (p < 0.001). There were no differences in neuropsychological performance between groups. The COVID-19 group had lower FD in the association, projection, and commissural tracts, but no change in GM. The corona radiata, corticospinal tract, corpus callosum, arcuate fasciculus, cingulate, fornix, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, superior longitudinal fasciculus, and uncinate fasciculus were involved. CFQ-11 scores correlated with microstructural changes in patients with COVID-19.\n\nConclusionsQuantitative d-MRI detected changes in the WM microstructure of patients recovering from COVID-19. This study suggests a possible brain substrate underlying the symptoms caused by SARS-CoV-2 during medium- to long-term recovery.\n\nKey pointsO_LIPatients with COVID-19 had microstructural changes in the WM at a mean follow-up of 3 months.\nC_LIO_LIThere is a possible brain substrate underlying the symptoms caused by SARS-CoV-2 during medium- to long-term recovery.\nC_LIO_LIA serial d-MRI study following up on a non-hospitalized sample of patients with milder COVID-19 forms is warranted.\nC_LI", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.20.22279020", + "rel_abs": "IntroductionCorona Virus-induced disease - 2019 (COVID-19) pandemic stimulates research works to find a solution to this crisis from starting 2020 year up to now. With ending of the 2021 year, various advances in pharmacotherapy against COVID-19 have emerged.\n\nRegarding antiviral therapy, Casirivimab and imdevimab antibody combination is a type of new immunotherapy against COVID-19. Standard antiviral therapy against COVID-19 includes Remdesivir and Favipravir.\n\nAim of StudyTo compare the efficacy and safety of antibodies cocktail (casirivimab and imdevimab), Remdesivir, and Favipravir in the COVID-19 patients\n\nPatients and Population265 hospitalized COVID-19 patients were used to represent the COVID-19 population and were assigned into three groups in a ratio of (1:2:2) respectively, Group (A) received REGN3048-3051(Antibodies cocktail (casirivimab and imdevimab), group (B) received remdesivir, and group (C) received favipravir.\n\nMethodsThe study design is a single-blind non-Randomized Controlled Trial (non-RCT). The drugs of the study are owned by Mansoura University Hospital (MUH) and prescribed by chest diseases lectures of the faculty of medicine-Mansoura University. The duration of the study is about 6 months after ethical approval.\n\nResults and discussionCasirivimab and imdevimab achieve less 28-day mortality rate, less mortality at hospital discharge, more negative swab cases, less need for O2 therapy and IMV, less duration of this need, less hospital and ICU stay, less case progression as presented by lower World Health Organization (WHO) scale and better multi-organ functions as presented by lower Sequential Organ Function Assessment (SOFA) score than Remdesivir and Favipravir.\n\nConclusionFrom all of these results, it is concluded that Group A (Casirivimab & imdevimab) has more favorable clinical outcomes than B (remdesivir) & C (favipravir) intervention groups.\n\nClinical Trial Registration: NCT05502081, 16/08/2022, Clinicaltrials.gov, retrospectively registered", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Diogenes Diego de Carvalho Bispo", - "author_inst": "Brasilia University Hospital, University of Brasilia" - }, - { - "author_name": "Pedro Renato de Paula Brandao", - "author_inst": "Hospital Sirio Libanes (Brasilia)" - }, - { - "author_name": "Danilo Assis Pereira", - "author_inst": "Brazilian Institute of Neuropsychology and Cognitive Sciences" - }, - { - "author_name": "Fernando Bisinoto Maluf", - "author_inst": "Department of Radiology, Hospital Santa Marta" - }, - { - "author_name": "Bruna Arrais Dias", - "author_inst": "Department of Radiology, Hospital Santa Marta" - }, - { - "author_name": "Hugo Rafael Paranhos", - "author_inst": "Department of Radiology, Hospital Santa Marta" - }, - { - "author_name": "Felipe von Glehn", - "author_inst": "Faculty of Medicine, University of Brasilia" - }, - { - "author_name": "Augusto Cesar Penalva de Oliveira", - "author_inst": "Instituto de Infectologia Emilio Ribas" - }, - { - "author_name": "Neysa Aparecida Tinoco Regattieri", - "author_inst": "Faculty of Medicine, University of Brasilia" + "author_name": "Ahmed H Hassan Jr.", + "author_inst": "Mansoura Unversity Hospital" }, { - "author_name": "Lucas Scardua Silva", - "author_inst": "Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas" - }, - { - "author_name": "Clarissa Lin Yasuda", - "author_inst": "Brazilian Institute of Neuroscience and Neurotechnology (BRAINN), University of Campinas" - }, - { - "author_name": "Alexandre Anderson de Sousa Munhoz Soares", - "author_inst": "Faculty of Medicine, University of Brasilia" + "author_name": "Sahar K Hegazy Sr.", + "author_inst": "Tanta University, faculty of pharmacy" }, { - "author_name": "Maxime Descoteaux", - "author_inst": "Sherbrooke Connectivity Imaging Lab, University of Sherbrooke" + "author_name": "Samar T Radwan Sr.", + "author_inst": "Mansoura University, faculty of medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.08.20.22279010", @@ -244250,43 +244605,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.08.17.22278893", - "rel_title": "Uptake of Sotrovimab for prevention of severe COVID-19 and its safety in the community in England", + "rel_doi": "10.1101/2022.08.17.22278896", + "rel_title": "Impact of the COVID-19 Pandemic on Personal Networks and Neurological Outcomes of People with Multiple Sclerosis: A Case-Control Cross-sectional and Longitudinal Analysis", "rel_date": "2022-08-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.17.22278893", - "rel_abs": "Sotrovimab is a neutralising monoclonal antibody (nMAB), currently administrated in England to treat extremely clinically vulnerable COVID-19 patients. Trials have shown it to have mild or moderate side effects, however safety in real-world settings has not been yet evaluated. We used national databases to investigate its uptake and safety in community patients across England. We used a cohort study to describe uptake and a self-controlled case series design to evaluate the risks of 49 pre-specified suspected adverse events in the 2-28 days post-treatment. Between December 11, 2021 and May 24, 2022, there were 172,860 COVID-19 patients eligible for treatment. Of the 22,815 people who received Sotrovimab, 21,487 (94.2%) had a positive SARS-CoV-2 test and 5,999 (26.3%) were not on the eligible list. Between treated and untreated eligible individuals, the mean age (54.6, SD: 16.1 vs 54.1, SD: 18.3) and sex distribution (women: 60.9% vs 58.1%; men: 38.9% vs 41.1%) were similar. There were marked variations in uptake between ethnic groups, which was higher amongst Indian (15.0%; 95%CI 13.8, 16.3), Other Asian (13.7%; 95%CI 11.9, 15.8), White (13.4%; 95%CI 13.3, 13.6), and Bangladeshi (11.4%; 95%CI 8.8, 14.6); and lower amongst Black Caribbean individuals (6.4%; 95%CI 5.4, 7.5) and Black Africans (4.7%; 95%CI 4.1, 5.4). We found no increased risk of any of the suspected adverse events in the overall period of 2-28 days post-treatment, but an increased risk of rheumatoid arthritis (IRR 3.08, 95% CI 1.44, 6.58) and of systematic lupus erythematosus (IRR 5.15, 95% CI 1.60, 16.60) in the 2-3 days post-treatment, when we narrowed the risk period.\n\nFundingNational Institute of Health Research (Grant reference 135561)", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.17.22278896", + "rel_abs": "BackgroundThe COVID-19 pandemic has negatively impacted the social fabric of people with multiple sclerosis (pwMS).\n\nObjectiveTo evaluate the associations between personal social network environment and neurological function in pwMS and controls during the COVID-19 pandemic and compare with the pre-pandemic baseline.\n\nMethodsWe first analyzed data collected from 8 cohorts of pwMS and control participants during the COVID-19 pandemic (March-December 2020). We then leveraged data collected between 2017-2019 in 3 of the 8 cohorts for longitudinal comparison. Participants completed a questionnaire that quantified the structure and composition of their personal social network, including the health behaviors of network members. We assessed neurological disability using three interrelated patient-reported outcomes: Patient Determined Disease Steps (PDDS), Multiple Sclerosis Rating Scale - Revised (MSRS-R), and Patient Reported Outcomes Measurement Information System (PROMIS)-Physical Function. We identified the network features associated with neurologic disability using paired t-tests and covariate-adjusted regressions.\n\nResultsIn the cross-sectional analysis of the pandemic data from 1130 pwMS and 1250 control participants, higher percent of network members with a perceived negative health influence was associated with greater neurological symptom burden in pwMS (MSRS-R: Beta[95% CI]=2.181[1.082, 3.279], p<.001) and worse physical function in controls (PROMIS-Physical Function: Beta[95% CI]=-5.707[-7.405, -4.010], p<.001). In the longitudinal analysis of 230 pwMS and 136 control participants, the networks of both pwMS and controls experienced an increase in constraint (pwMS p=.006, control p=.001) as well as a decrease in network size (pwMS p=.003, control p<.001), effective size (pwMS p=.007, control p=.013), maximum degree (pwMS p=.01, control p<.001), and percent contacted weekly or less (pwMS p<.001, control p<.001), suggesting overall network contraction during the COVID-19 pandemic. There was also an increase in percentage of kin (p=.003) in the networks of pwMS but not controls during the COVID-19 pandemic when compared to the pre-pandemic baseline. These changes in personal social network due to the pandemic were not associated with worsening neurological disability during the pandemic.\n\nConclusionsOur findings suggest that perceived negative health influences in personal social networks are associated with worse disability in all participants during the COVID-19 pandemic. Despite the perturbation in social environment and connections during the pandemic, the stability in neurological function among pwMS suggests potential resilience.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Martina Patone", - "author_inst": "University of Oxford" + "author_name": "Claire S Riley", + "author_inst": "Columbia University Irving Medical Center" }, { - "author_name": "Holly Tibble", - "author_inst": "University of Edinburgh" + "author_name": "Shruthi Venkatesh", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Andrew JHL Snelling", - "author_inst": "University of Oxford" + "author_name": "Amar Dhand", + "author_inst": "Harvard Medical School" }, { - "author_name": "Carol Coupland", - "author_inst": "University of Oxford" + "author_name": "Nandini K Doshi", + "author_inst": "University of Pittsburgh" }, { - "author_name": "Aziz Sheikh", - "author_inst": "University of Edinburgh" + "author_name": "Katelyn Kavak", + "author_inst": "Jacobs School of Medicine and Biomedical Sciences" }, { - "author_name": "Julia Hippisley-Cox", - "author_inst": "University of Oxford" + "author_name": "Elle E Levit", + "author_inst": "Yale University" + }, + { + "author_name": "Christopher Perrone", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Bianca Weinstock-Guttman", + "author_inst": "Jacobs School of Medicine and Biomedical Sciences" + }, + { + "author_name": "Erin E Longbrake", + "author_inst": "Yale University" + }, + { + "author_name": "- MSReCOV Collaborative", + "author_inst": "" + }, + { + "author_name": "Philip L De Jager", + "author_inst": "Columbia University Irving Medical Center" + }, + { + "author_name": "Zongqi Xia", + "author_inst": "University of Pittsburgh" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "neurology" }, { "rel_doi": "10.1101/2022.08.16.22278800", @@ -245876,47 +246255,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.08.12.503822", - "rel_title": "The Spike protein of SARS-coV2 19B (S) clade mirrors critical features of viral adaptation and coevolution", + "rel_doi": "10.1101/2022.08.14.503921", + "rel_title": "Evasion of Neutralizing Antibody Response by the SARS-CoV-2 BA.2.75 Variant", "rel_date": "2022-08-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.12.503822", - "rel_abs": "Pathogens including viruses evolve in tandem with diversity in their animal and human hosts. For SARS-coV2, the focus is generally for understanding such coevolution on the virus spike protein since it demonstrates high mutation rates compared to other genome regions, particularly in the receptor-binding domain (RBD).\n\nViral sequences of the SARS-coV2 19B (S) clade and variants of concern from different continents, were investigated, with a focus on the A.29 lineage which presented with different mutational patterns within the 19B (S) lineages in order to learn more about how SARS-coV2 may have evolved and adapted to widely diverse populations globally.\n\nResults indicated that SARS-coV2 went through evolutionary constrains and intense selective pressure, particularly in Africa. This was manifested in a departure from neutrality with excess nonsynonymous mutations and a negative Tajima D consistent with rapid expansion and directional selection as well as deletion and deletion-frameshifts in the N-terminal domain (NTD region) of the spike protein.\n\nIn conclusion, viral transmission during epidemics through population of diverse genomic structure and marked complexity may be a significant factor for the virus to acquire distinct patterns of mutations within these populations in order to ensure its survival and fitness, hence in the emergence of novel variants and strains.\n\nImportanceIn this study, we justify the fact that the viruss evolution varies across continents, with each continent showing different amounts and patterns of mutations and deletions, which was manifested in the 19B (S) clade of SARS-coV2, particularly in areas with high population complexity, such as Africa, despite the low rate of sampling and data sharing. The findings show that SARS-coV2 was subject to evolutionary constraints and intense selective pressure. This study will contribute to the scanty amount of research on the SARS-coV2 coevolution and adaptation, in which the host variation is of great significance in understanding the intricacies of viral host coevolution.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.14.503921", + "rel_abs": "The newly emerged BA.2.75 SARS-CoV-2 variant exhibits an alarming 9 additional mutations in its spike (S) protein compared to the ancestral BA.2 variant. Here we examine the neutralizing antibody escape of BA.2.75 in mRNA-vaccinated and BA.1-infected individuals, as well as the molecular basis underlying functional changes in the S protein. Notably, BA.2.75 exhibits enhanced neutralization resistance over BA.2, but less than the BA.4/5 variant. The G446S and N460K mutations of BA.2.75 are primarily responsible for its enhanced resistance to neutralizing antibodies. The R493Q mutation, a reversion to the prototype sequence, reduces BA.2.75 neutralization resistance. The mutational impact is consistent with their locations in common neutralizing antibody epitopes. Further, the BA.2.75 variant shows enhanced cell-cell fusion over BA.2, driven largely by the N460K mutation, which enhances S processing. Structural modeling revealed a new receptor contact introduced by N460K, supporting a mechanism of potentiated receptor utilization and syncytia formation.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Bidour K. Hussein", - "author_inst": "Institute of Endemic Diseases, UofK" + "author_name": "Panke Qu", + "author_inst": "The Ohio State University" + }, + { + "author_name": "John P. Evans", + "author_inst": "The Ohio State University" }, { - "author_name": "Omnia M. Ibrahium", - "author_inst": "University of Khartoum, Faculty of science" + "author_name": "Yi-Min Zheng", + "author_inst": "The Ohio State University" }, { - "author_name": "Marwa F. Alamin", - "author_inst": "Institute of Endemic Diseases, UofK" + "author_name": "Claire Carlin", + "author_inst": "The Ohio State University" }, { - "author_name": "Lamees A.M Ahmed", - "author_inst": "Institute of Endemic Diseases, UofK" + "author_name": "Linda J. Saif", + "author_inst": "The Ohio State University" }, { - "author_name": "Safa A.E Abuswar", - "author_inst": "Institute of Endemic Diseases, UofK" + "author_name": "Eugene M. Oltz", + "author_inst": "The Ohio State University" }, { - "author_name": "Mohammed H. Abdelraheem", - "author_inst": "Institute of Endemic Diseases, UofK" + "author_name": "Kai Xu", + "author_inst": "The Ohio State University" }, { - "author_name": "Muntaser E. Ibrahim", - "author_inst": "Institute of Endemic Diseases, UofK" + "author_name": "Richard J. Gumina", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Shan-Lu Liu", + "author_inst": "The Ohio State University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "new results", - "category": "evolutionary biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.08.12.503821", @@ -248010,55 +248397,159 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.08.09.22274874", - "rel_title": "Procalcitonin and High APACHE Scores are Associated with the Development of Acute Kidney Injury in Patients with SARS-CoV-2", + "rel_doi": "10.1101/2022.08.09.22278592", + "rel_title": "Distinguishing features of Long COVID identified through immune profiling", "rel_date": "2022-08-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.09.22274874", - "rel_abs": "BackgroundAcute kidney injury (AKI) is associated with poor outcomes in patients infected with SARS-CoV-2. Sepsis, direct injury to kidney cells by the virus, and severe systemic inflammation are mechanisms implicated in its development. We investigated the association between inflammatory markers (C-reactive protein, procalcitonin, D-dimer, lactate dehydrogenase, and ferritin) in patients infected with SARS-CoV-2 and the development of AKI.\n\nMethodsA prospective cohort study performed at the Civil Hospital (Dr. Juan I. Menchaca) Guadalajara, Mexico, included patients aged >18 years with a diagnosis of SARS-CoV-2 pneumonia confirmed by RT-PCR and who did or did not present with AKI (KDIGO) while hospitalized. Biomarkers of inflammation were recorded, and kidney function was estimated using the CKD-EPI formula.\n\nResults291 patients were included (68% men; mean age, 57 years). The incidence of AKI was 40.5% (118 patients); 21% developed stage 1 AKI, 6% developed stage 2 AKI, and 14% developed stage 3 AKI. The development of AKI was associated with phosphate higher (p = 0.002) (RR 1.39, CI 95% 1.13 - 1.72), high procalcitonin levels at hospital admission (p = 0.005) (RR 2.09, CI 95% 1.26-3.50), and high APACHE scores (p = 0.011) (RR 2.0, CI 95% 1.17-3.40). The survival analysis free of AKI according to procalcitonin levels and APACHE scores demonstrated a lower survival in patients with procalcitonin >0.5 ng/ml (p= 0.001) and APACHE >15 points (p = 0.004).\n\nConclusionsphosphate, high procalcitonin levels, and APACHE scores >15 were predictors of AKI development in patients hospitalized with COVID-19.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.09.22278592", + "rel_abs": "SARS-CoV-2 infection can result in the development of a constellation of persistent sequelae following acute disease called post-acute sequelae of COVID-19 (PASC) or Long COVID1-3. Individuals diagnosed with Long COVID frequently report unremitting fatigue, post-exertional malaise, and a variety of cognitive and autonomic dysfunctions1-3; however, the basic biological mechanisms responsible for these debilitating symptoms are unclear. Here, 215 individuals were included in an exploratory, cross-sectional study to perform multi-dimensional immune phenotyping in conjunction with machine learning methods to identify key immunological features distinguishing Long COVID. Marked differences were noted in specific circulating myeloid and lymphocyte populations relative to matched control groups, as well as evidence of elevated humoral responses directed against SARS-CoV-2 among participants with Long COVID. Further, unexpected increases were observed in antibody responses directed against non-SARS-CoV-2 viral pathogens, particularly Epstein-Barr virus. Analysis of circulating immune mediators and various hormones also revealed pronounced differences, with levels of cortisol being uniformly lower among participants with Long COVID relative to matched control groups. Integration of immune phenotyping data into unbiased machine learning models identified significant distinguishing features critical in accurate classification of Long COVID, with decreased levels of cortisol being the most significant individual predictor. These findings will help guide additional studies into the pathobiology of Long COVID and may aid in the future development of objective biomarkers for Long COVID.", + "rel_num_authors": 35, "rel_authors": [ { - "author_name": "Jorge Andrade-Sierra", - "author_inst": "University of Guadalajara" + "author_name": "Jon Klein", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Jamie Wood", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Jillian Jaycox", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Peiwen Lu", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Claudia Delgado Astorga", - "author_inst": "Civil Hospital. Guadalajara, Mexico." + "author_name": "Rahul M. Dhodapkar", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Miriam Gabriela Nava Vargas", - "author_inst": "Civil Hospital, Guadalajara Mexico" + "author_name": "Jeffrey R. Gehlhausen", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Enrique Rojas Campos", - "author_inst": "Mexican Institute of Social Security. Jalisco, Mexico" + "author_name": "Alexandra Tabachnikova", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Karla Hernandez Morales", - "author_inst": "Civil Hospital, Guadalajara Mexico." + "author_name": "Laura Tabacof", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Carlos A Andrade Castellanos", - "author_inst": "Civil Hospital, Guadalajara Mexico" + "author_name": "Amyn A. Malik", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Kevin Javier Arellano Arteaga", - "author_inst": "Civil Hospital. Guadalajara Mexico." + "author_name": "Kathy Kamath", + "author_inst": "SerImmune Inc." }, { - "author_name": "Antonio de Jesus Andrade-Ortega Sr.", - "author_inst": "Universidad de Guadalajara" + "author_name": "Kerrie Greene", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Valter Silva Monteiro", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Mario Pena-Hernandez", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Tianyang Mao", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Bornali Bhattacharjee", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Takehiro Takahashi", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Carolina Lucas", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Luis Gerardo Gonzalez-Correa", - "author_inst": "Mexican Institute of Social Security. Guadalajara, Jalisco, Mexico" + "author_name": "Julio Silva", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Dayna Mccarthy", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Erica Breyman", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Jenna Tosto-Mancuso", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Yile Dai", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Emily Perotti", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Koray Akduman", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Tiffany Tzeng", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Lan Xu", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Inci Yildirim", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Harlan M. Krumholz", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "John Shon", + "author_inst": "SerImmune Inc." + }, + { + "author_name": "Ruslan Medzhitov", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Saad B. Omer", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "David van Dijk", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Aaron M. Ring", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "David Putrino", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Akiko Iwasaki", + "author_inst": "Yale School of Medicine" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "nephrology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.08.09.22278595", @@ -250084,105 +250575,97 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2022.08.07.22278510", - "rel_title": "Metabolomic and gut microbiome profiles across the spectrum of community-based COVID and non-COVID disease: A COVID-19 Biobank study.", + "rel_doi": "10.1101/2022.08.08.22278528", + "rel_title": "Quantifying the impact of delaying the second COVID-19 vaccine dose in England: a mathematical modelling study", "rel_date": "2022-08-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.07.22278510", - "rel_abs": "Whilst many with SARS-CoV-2 infection have mild disease, managed in the community, individuals with cardiovascular risk factors experienced often more severe acute disease, requiring hospitalisation. Increasing concern has also developed over long symptom duration in many individuals, including the majority who managed acutely in the community. Risk factors for long symptom duration, including biological variables, are still poorly defined.\n\nWe examine post-illness metabolomic and gut-microbiome profiles, in community-dwelling participants with SARS-CoV-2, ranging from asymptomatic illness to Post-COVID Syndrome, and participants with prolonged non-COVID-19 illnesses. We also assess a pre-established metabolomic biomarker score for its association with illness duration.\n\nWe found an atherogenic-dyslipidaemic metabolic profile, and greater biomarker scores, associated with longer illness, both in individuals with and without SARS-CoV-2 infection. We found no association between illness duration and gut microbiome in convalescence.\n\nFindings highlight the potential role of cardiometabolic dysfunction to the experience of long illness duration, including after COVID-19.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.08.22278528", + "rel_abs": "BackgroundThe UK was the first country to start national COVID-19 vaccination programmes, initially administering doses 3-weeks apart. However, early evidence of high vaccine effectiveness after the first dose and the emergence of the Alpha variant prompted the UK to extend the interval between doses to 12-weeks. In this study, we quantify the impact of delaying the second vaccine dose on the epidemic in England.\n\nMethodsWe used a previously described model of SARS-CoV-2 transmission and calibrated the model to English surveillance data including hospital admissions, hospital occupancy, seroprevalence data, and population-level PCR testing data using a Bayesian evidence synthesis framework. We modelled and compared the epidemic trajectory assuming that vaccine doses were administered 3-weeks apart against the real vaccine roll-out schedule. We estimated and compared the resulting number of daily infections, hospital admissions, and deaths. A range of scenarios spanning a range of vaccine effectiveness and waning assumptions were investigated.\n\nFindingsWe estimate that delaying the interval between the first and second COVID-19 vaccine doses from 3- to 12-weeks prevented an average 64,000 COVID-19 hospital admissions and 9,400 deaths between 8th December 2020 and 13th September 2021. Similarly, we estimate that the 3-week strategy would have resulted in more infections and deaths compared to the 12-week strategy. Across all sensitivity analyses the 3-week strategy resulted in a greater number of hospital admissions.\n\nInterpretationEnglands delayed second dose vaccination strategy was informed by early real-world vaccine effectiveness data and a careful assessment of the trade-offs in the context of limited vaccine supplies in a growing epidemic. Our study shows that rapidly providing partial vaccine-induced protection to a larger proportion of the population was successful in reducing the burden of COVID-19 hospitalisations and deaths. There is benefit in carefully considering and adapting guidelines in light of new emerging evidence and the population in question.\n\nFundingNational Institute for Health Research, UK Medical Research Council, Jameel Institute, Wellcome Trust, and UK Foreign, Commonwealth and Development Office, National Health and Medical Research Council.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed up to 10th June 2022, with no language restrictions using the following search terms: (COVID-19) AND (vaccin*) AND (dose OR dosing) AND (delay OR interval) AND (quant* OR assess* OR impact). We found 14 studies that explored the impact of different vaccine dosing intervals. However, the majority were prospective assessments of optimal vaccination strategies, exploring different trade-offs between vaccine mode of action, vaccine effectiveness, coverage, and availability. Only two studies retrospectively assessed the impact of different vaccination intervals. One assessed the optimal timing during the epidemic to switch to an extended dosing interval, and the other assessed the risk of all-cause mortality and hospitalisations between the two dosing groups.\n\nAdded value of this studyOur data synthesis approach combines real-world evidence from multiple data sources to retrospectively quantify the impact of extending the COVID-19 vaccine dosing interval from the manufacturer recommended 3-weeks to 12-weeks in England.\n\nImplications of all the available evidenceOur study demonstrates that rapidly providing partial vaccine-induced protection to a larger proportion of the population was successful in reducing the COVID-19 hospitalisations and mortality. This was enabled by rapid and careful monitoring of vaccine effectiveness as nationwide vaccine programmes were initiated, and adaptation of guidelines in light of emerging evidence.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Marc F \u00d6sterdahl", - "author_inst": "King's College London" - }, - { - "author_name": "Ronan Whiston", - "author_inst": "King's College London" - }, - { - "author_name": "Carole H Sudre", - "author_inst": "King's College London" + "author_name": "Natsuko Imai", + "author_inst": "Imperial College London" }, { - "author_name": "Francesco Asnicar", - "author_inst": "University of Trento" + "author_name": "Thomas Rawson", + "author_inst": "Imperial College London" }, { - "author_name": "Nathan J Cheetham", - "author_inst": "King's College London" + "author_name": "Edward S Knock", + "author_inst": "Imperial College London" }, { - "author_name": "Aitor Blanco Miguez", - "author_inst": "University of Trento" + "author_name": "Raphael Sonabend", + "author_inst": "Technische Universitat Kaiserslautern" }, { - "author_name": "Vicky Bowyer", - "author_inst": "King's College London" + "author_name": "Yasin Elmaci", + "author_inst": "Imperial College London" }, { - "author_name": "Michela Antonelli", - "author_inst": "King's College London" + "author_name": "Pablo N Perez-Guzman", + "author_inst": "Imperial College London" }, { - "author_name": "Olivia Snell", - "author_inst": "King's College London" + "author_name": "Lilith K Whittles", + "author_inst": "Imperial College London" }, { - "author_name": "Liane dos Santos Canas", - "author_inst": "King's College London" + "author_name": "Divya Thekke Kanapram", + "author_inst": "Imperial College London" }, { - "author_name": "Christina Hu", - "author_inst": "ZOE Global Ltd." + "author_name": "Katy AM Gaythorpe", + "author_inst": "Imperial College London" }, { - "author_name": "Jonathan Wolf", - "author_inst": "ZOE Global Ltd." + "author_name": "Wes Hinsley", + "author_inst": "Imperial College London" }, { - "author_name": "Cristina Menni", - "author_inst": "King's College London" + "author_name": "Bimandra AM Djaafara", + "author_inst": "Imperial College London" }, { - "author_name": "Michael Malim", - "author_inst": "King's College London" + "author_name": "Haowei Wang", + "author_inst": "Imperial College London" }, { - "author_name": "Deborah Hart", - "author_inst": "King's College London" + "author_name": "Keith Fraser", + "author_inst": "Imperial College London" }, { - "author_name": "Tim Spector", - "author_inst": "King's College London" + "author_name": "Richard G FitzJohn", + "author_inst": "Imperial College London" }, { - "author_name": "Sarah Berry", - "author_inst": "King's College London" + "author_name": "Alexandra B Hogan", + "author_inst": "University of New South Wales" }, { - "author_name": "Nicola Segata", - "author_inst": "University of Trento" + "author_name": "Patrick Doohan", + "author_inst": "Imperial College London" }, { - "author_name": "Katie Doores", - "author_inst": "King's College London" + "author_name": "Azra C Ghani", + "author_inst": "Imperial College London" }, { - "author_name": "Sebastien Ourselin", - "author_inst": "King's College London" + "author_name": "Neil M Ferguson", + "author_inst": "Imperial College London" }, { - "author_name": "Emma L Duncan", - "author_inst": "King's College London" + "author_name": "Marc Baguelin", + "author_inst": "Imperial College London" }, { - "author_name": "Claire J Steves", - "author_inst": "King's College London" + "author_name": "Anne Cori", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -252042,191 +252525,43 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2022.08.05.22278466", - "rel_title": "Performance of Screening for SARS-CoV-2 using Rapid Antigen Tests to Detect Incidence of Symptomatic and Asymptomatic SARS-CoV-2 Infection: findings from the Test Us at Home prospective cohort study", + "rel_doi": "10.1101/2022.08.04.22278446", + "rel_title": "Differential Impacts of Perceived Social Support on Alcohol and Cannabis Use in Young Adults: Lessons from the COVID-19 Pandemic", "rel_date": "2022-08-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.05.22278466", - "rel_abs": "BackgroundPerformance of rapid antigen tests for SARS-CoV-2 (Ag-RDT) varies over the course of an infection, and their performance in screening for SARS-CoV-2 is not well established. We aimed to evaluate performance of Ag-RDT for detection of SARS-CoV-2 for symptomatic and asymptomatic participants.\n\nMethodsParticipants >2 years old across the United States enrolled in the study between October 2021 and February 2022. Participants completed Ag-RDT and molecular testing (RT-PCR) for SARS-CoV-2 every 48 hours for 15 days. This analysis was limited to participants who were asymptomatic and tested negative on their first day of study participation. Onset of infection was defined as the day of first positive RT-PCR result. Sensitivity of Ag-RDT was measured based on testing once, twice (after 48-hours), and thrice (after 96 hours). Analysis was repeated for different Days Post Index PCR Positivity (DPIPP) and stratified based on symptom-status.\n\nResultsIn total, 5,609 of 7,361 participants were eligible for this analysis. Among 154 participants who tested positive for SARS-CoV-2, 97 were asymptomatic and 57 had symptoms at infection onset. Serial testing with Ag-RDT twice 48-hours apart resulted in an aggregated sensitivity of 93.4% (95% CI: 89.1-96.1%) among symptomatic participants on DPIPP 0-6. Excluding singleton positives, aggregated sensitivity on DPIPP 0-6 for two-time serial-testing among asymptomatic participants was lower at 62.7% (54.7-70.0%) but improved to 79.0% (71.0-85.3%) with testing three times at 48-hour intervals.\n\nDiscussionPerformance of Ag-RDT was optimized when asymptomatic participants tested three-times at 48-hour intervals and when symptomatic participants tested two-times separated by 48-hours.", - "rel_num_authors": 43, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.04.22278446", + "rel_abs": "Coronavirus (COVID-19) lockdowns provided a unique opportunity to examine how changes in the social environment impact mental health and wellbeing. We addressed this issue by assessing how perceived social support across COVID-19 restrictions alters alcohol and cannabis use in emerging adults, a population vulnerable to adverse outcomes of substance use. Four hundred sixty-three young adults in Canada and the United States completed online questionnaires for three retrospective time points: Pre-Covid, Lockdown and Eased Restrictions. Sociodemographic factors, perceived social support, and substance use were assessed. Overall, alcohol use decreased while cannabis use increased during Lockdown. Interestingly, social support negatively predicted alcohol use and positively predicted cannabis use during Lockdown. These findings suggest a difference in motives underlying alcohol and cannabis use in emerging adults. Importantly, these changes were not sustained when restrictions eased, suggesting that emerging adults exhibit resiliency to the impacts of COVID-19 restrictions on substance use.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Apurv Soni", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Carly Herbert", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Honghuang Lin", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Yi Yan", - "author_inst": "US Food and Drug Administration" - }, - { - "author_name": "Caitlin Pretz", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Pamela Stamegna", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Biqi Wang", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Taylor Orwig", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Colton Wright", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Seanan Tarrant", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Stephanie Behar", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Thejas Suvarna", - "author_inst": "CareEvolution, LLC" - }, - { - "author_name": "Summer Schrader", - "author_inst": "CareEvolution, LLC" - }, - { - "author_name": "Emma Harman", - "author_inst": "CareEvolution, LLC" - }, - { - "author_name": "Chris Nowak", - "author_inst": "CareEvolution, LLC" - }, - { - "author_name": "Vik Kheterpal", - "author_inst": "CareEvolution, LLC" - }, - { - "author_name": "Lokinendi V Rao", - "author_inst": "Quest Diagnostics" - }, - { - "author_name": "Lisa Cashman", - "author_inst": "Quest Diagnostics" - }, - { - "author_name": "Elizabeth Orvek", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Didem Ayturk", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Laura Gibson", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Adrian Zai", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Steven Wong", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Peter Lazar", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Ziyue Wang", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Andreas Filippaios", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Bruce Barton", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Chad Achenbach", - "author_inst": "Northwestern University" - }, - { - "author_name": "Robert Murphy", - "author_inst": "Northwestern University" - }, - { - "author_name": "Matthew Robinson", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Yuka Manabe", - "author_inst": "Johns Hopkins University School of Medicine" - }, - { - "author_name": "Shishir Pandey", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Andres Colubri", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Stephenie Lemon", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Nisha Fahey", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Katherine L Luzuriaga", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Nathaniel Hafer", - "author_inst": "University of Massachusetts Chan Medical School" - }, - { - "author_name": "Kristian Roth", - "author_inst": "Food and Drug administration" + "author_name": "Lindsay A. Lo", + "author_inst": "University of Toronto" }, { - "author_name": "Toby Lowe", - "author_inst": "Food and Drug administration" + "author_name": "Michelle J. Blumberg", + "author_inst": "York University" }, { - "author_name": "Timothy Stenzel", - "author_inst": "Food and Drug administration" + "author_name": "Geoffrey W. Harrison", + "author_inst": "Queen's University" }, { - "author_name": "Bill Heetderks", - "author_inst": "National Institute of Biomedical Imaging and Bioengineering" + "author_name": "Alison Dodwell", + "author_inst": "Queen's University" }, { - "author_name": "John Broach", - "author_inst": "University of Massachusetts Chan Medical School" + "author_name": "Samantha H. Irwin", + "author_inst": "Queen's University" }, { - "author_name": "David D McManus", - "author_inst": "University of Massachusetts Chan Medical School" + "author_name": "Mary C. Olmstead", + "author_inst": "Queen's University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.08.05.22278458", @@ -254408,49 +254743,61 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.08.03.22278359", - "rel_title": "COVID-19 convalescent plasma for the treatment of immunocompromised patients: a systematic review.", + "rel_doi": "10.1101/2022.08.02.22278342", + "rel_title": "Cellular and humoral immunity towards parental SARS-CoV-2 and variants of concern after two doses of the NVX-CoV2373-vaccine in comparison to homologous BNT162b and mRNA1273 regimens", "rel_date": "2022-08-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.03.22278359", - "rel_abs": "Immunosuppressed patients have increased risk for morbidity and mortality from COVID-19 because they less frequently mount antibody responses to vaccines and often cannot tolerate small-molecule antivirals. The Omicron variant of concern of SARS-CoV-2 has progressively defeated anti-Spike mAbs authorized so far, paving the way to a return to COVID-19 convalescent plasma (CCP) therapy. In this systematic review we performed a metanalysis of 9 controlled studies (totaling 535 treated patients and 1365 controls and including 4 randomized controlled trials), an individual patient data analysis of 125 case reports/series (totaling 265 patients), and a descriptive analysis of 13 uncontrolled large case series without individual patient data available (totaling 358 patients). The metanalysis of controlled studies showed a risk ratio for mortality of 0.65 (risk difference -0.11) in treatment with CCP versus standard of care for immunosuppressed COVID-19 patients. On the basis of this evidence, we encourage initiation of high-titer CCP from vaccinees( hybrid plasma) in immunocompromised patients.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.08.02.22278342", + "rel_abs": "The NVX-CoV2373-vaccine has recently been licensed, although data on vaccine-induced humoral and cellular immunity towards the parental strain and variants of concern (VOCs) in comparison to dual-dose mRNA-regimens are limited. In this observational study including 66 participants, we show that NVX-CoV2373-induced IgG-levels were lower than after vaccination with BNT162b2 or mRNA-1273 (n=22 each, p=0.006). Regardless of the vaccine and despite different IgG-levels, neutralizing activity towards VOCs was highest for Delta, followed by BA.2 and BA.1. Interestingly, spike-specific CD8 T-cell levels after NVX-CoV2373-vaccination were significantly lower and were detectable in 3/22 (14%) individuals only. In contrast, spike-specific CD4 T-cells were induced in 18/22 (82%) individuals. However, CD4 T-cell levels were lower (p<0.001), had lower CTLA-4 expression (p<0.0001) and comprised less multifunctional cells co-expressing IFN{gamma}, TNF and IL-2 (p=0.0007) as compared to mRNA-vaccinated individuals. Unlike neutralizing antibodies, NVX-CoV2373-induced CD4 T cells cross-reacted to all tested VOCs from Alpha to Omicron, which may hold promise to protect from severe disease.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Jonathon Senefeld", - "author_inst": "Mayo Clinic" + "author_name": "Franziska Hielscher", + "author_inst": "Saarland University, Department of Transplant and Infection Immunology" }, { - "author_name": "Massimo Franchini", - "author_inst": "Carlo Poma Hospital, Mantua, Italy" + "author_name": "Tina Schmidt", + "author_inst": "Saarland University, Department of Transpant and Infection Immunology" }, { - "author_name": "Carlo Mengoli", - "author_inst": "Carlo Poma Hospital, Mantua, Italy" + "author_name": "Verena Klemis", + "author_inst": "Saarland University, Department of Transpant and Infection Immunology" }, { - "author_name": "Mario Cruciani", - "author_inst": "Carlo Poma Hospital, Mantua, Italy" + "author_name": "Alexander Wilhelm", + "author_inst": "University Hospital Frankfurt, Goethe University Frankfurt" }, { - "author_name": "Matteo Zani", - "author_inst": "Carlo Poma Hospital, Mantua, Italy" + "author_name": "Stefanie Marx", + "author_inst": "Saarland University, Department of Transplant and Infection Immunology" }, { - "author_name": "Ellen K Gorman", - "author_inst": "Mayo Clinic, Rochester, USA" + "author_name": "Amina Abu-Omar", + "author_inst": "Saarland University, Department of Transplant and Infection Immunology" }, { - "author_name": "Daniele Focosi", - "author_inst": "Pisa University Hospital" + "author_name": "Laura Ziegler", + "author_inst": "Saarland University, Department of Transplant and Infection Immunology" }, { - "author_name": "Arturo Casadevall", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Candida Guckelmus", + "author_inst": "Saarland University, Department of Transplant and Infection Immunology" }, { - "author_name": "Michael J Joyner", - "author_inst": "Mayo Clinic, Rochester, USA" + "author_name": "Rebecca Urschel", + "author_inst": "Saarland University, Department of Transplant and Infection Immunology" + }, + { + "author_name": "Urban Sester", + "author_inst": "SHG Klinikum Voelklingen" + }, + { + "author_name": "Marek Widera", + "author_inst": "University Hospital Frankfurt, Goethe University Frankfurt, Germany" + }, + { + "author_name": "Martina Sester", + "author_inst": "Saarland University, Department of Transplant and Infection Immunology" } ], "version": "1", @@ -256166,63 +256513,87 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.07.29.502014", - "rel_title": "Coronaviruses using different strategies to antagonize antiviral responses and pyroptosis", + "rel_doi": "10.1101/2022.08.01.502275", + "rel_title": "SARS-CoV-2 ORF8 is a viral cytokine regulating immune responses", "rel_date": "2022-08-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.29.502014", - "rel_abs": "Viral infection triggers inflammasome-mediated caspase-1 activation. However, less is known about how viruses use the active caspase-1 to evade host immune response. Here, we use porcine epidemic diarrhea virus (PEDV) as a model of coronaviruses (CoVs) to illustrate the sophisticated regulation of CoVs to counteract IFN-I signaling and pyroptosis. We show that PEDV infection stabilizes caspase-1 expression via papain-like protease PLP2s deubiquitinase activity and the enhanced stabilization of caspase-1 disrupts IFN-I signaling by cleaving RIG-I at D189 residue. Meanwhile, PLP2 can degrade GSDMD-p30 by removing its K27-linked ubiquitin chain at K275 to restrain pyroptosis. Papain-like proteases from other genera of CoVs (PDCoV and SARS-CoV-2) have the similar activity to degrade GSDMD-p30. We further demonstrate that SARS-CoV-2 N protein induced NLRP3 inflammasome activation also uses the active caspase-1 to counter IFN-I signaling by cleaving RIG-I. Therefore, our work unravels a novel antagonistic mechanism employed by CoVs to evade host antiviral response.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.08.01.502275", + "rel_abs": "Many patients with severe COVID-19 suffer from pneumonia, and thus elucidation of the mechanisms underlying the development of such severe pneumonia is important. The ORF8 protein is a secreted protein of SARS-CoV-2, whose in vivo function is not well understood. Here, we analyzed the function of ORF8 protein by generating ORF8-knockout SARS-CoV-2. We found that the lung inflammation observed in wild-type SARS-CoV-2-infected hamsters was decreased in ORF8-knockout SARS-CoV-2-infected hamsters. Administration of recombinant ORF8 protein to hamsters also induced lymphocyte infiltration into the lungs. Similar pro-inflammatory cytokine production was observed in primary human monocytes treated with recombinant ORF8 protein. Furthermore, we demonstrate that the serum ORF8 protein levels are correlated well with clinical markers of inflammation. These results demonstrated that the ORF8 protein is a viral cytokine of SARS-CoV-2 involved in the in the immune dysregulation observed in COVID-19 patients, and that the ORF8 protein could be a novel therapeutic target in severe COVID-19 patients.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Xinyu Fu", - "author_inst": "Zhejiang University" + "author_name": "Masako Kohyama", + "author_inst": "Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Yang Yang", - "author_inst": "Zhejiang A&F University" + "author_name": "Tatsuya Suzuki", + "author_inst": "Institute for Advanced Co-Creation Studies, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Weilv Xu", - "author_inst": "Zhejiang University" + "author_name": "Wataru Nakai", + "author_inst": "Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University, Osaka" }, { - "author_name": "Danyue Li", - "author_inst": "Zhejiang University" + "author_name": "Chikako Ono", + "author_inst": "Department of Molecular Virology, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Xinyue Li", - "author_inst": "Zhejiang University" + "author_name": "Sumiko Matsuoka", + "author_inst": "Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Nan Chen", - "author_inst": "Zhejiang University" + "author_name": "Koichi Iwatani", + "author_inst": "Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Qian Lv", - "author_inst": "Zhejiang University" + "author_name": "Yafei Liu", + "author_inst": "Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Yuhua Shi", - "author_inst": "Zhejiang University" + "author_name": "Yusuke Sakai", + "author_inst": "Department of Veterinary Pathology, Yamaguchi University" }, { - "author_name": "Xiaoliang Li", - "author_inst": "Zhejiang University" + "author_name": "Atsushi Nakagawa", + "author_inst": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital" }, { - "author_name": "Jidong Xu", - "author_inst": "Zhejiang University" + "author_name": "Keisuke Tomii", + "author_inst": "Department of Respiratory Medicine, Kobe City Medical Center General Hospital" }, { - "author_name": "Fushan Shi", - "author_inst": "Zhejiang University" + "author_name": "Koichiro Ohmura", + "author_inst": "Department of Rheumatology, Kobe City Medical Center General Hospital" + }, + { + "author_name": "Masato Okada", + "author_inst": "Department of Oncogene Research, Research Institute for Microbial Diseases" + }, + { + "author_name": "Yoshiharu Matsuura", + "author_inst": "Department of Molecular Virology, Research Institute for Microbial Diseases" + }, + { + "author_name": "Shiro Oshima", + "author_inst": "Department of Clinical Research, Osaka Minami Medical Center, Osaka" + }, + { + "author_name": "Yusuke Maeda", + "author_inst": "Department of Molecular Virology, Research Institute for Microbial Diseases" + }, + { + "author_name": "Toru Okamoto", + "author_inst": "Institute for Advanced Co-Creation Studies, Research Institute for Microbial Diseases" + }, + { + "author_name": "Hisashi Arase", + "author_inst": "Department of Immunochemistry, Research Institute for Microbial Diseases, Osaka University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2022.08.01.502311", @@ -257916,67 +258287,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.24.22277784", - "rel_title": "Efficacy of a patient isolation hood in reducing exposure to airborne infectious virus in a simulated healthcare setting", + "rel_doi": "10.1101/2022.07.27.22278117", + "rel_title": "Projecting COVID-19 Cases and Subsequent Hospital Burden in Ohio", "rel_date": "2022-07-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.24.22277784", - "rel_abs": "BackgroundHealthcare workers treating patients with SARS-CoV-2 are at risk of infection from patient-emitted virus-laden aerosols. We quantified the reduction of airborne infectious virus in a simulated hospital room when a ventilated patient isolation (McMonty) hood was in use.\n\nMethodsWe nebulised 109 plaque forming units (PFU) of bacteriophage PhiX174 virus into a 35.1m3 room with a hood active or inactive. The airborne concentration of infectious virus was measured by BioSpot-VIVAS and settle plates using plaque assay quantification on the bacterial host Escherichia coli C. The particle number concentration (PNC) was monitored continuously using an optical particle sizer.\n\nResultsMedian airborne viral concentration in the room reached 1.41 x 105 PFU.m-3 with the hood inactive. Using the active hood as source containment reduced infectious virus concentration by 374-fold in air samples. This was associated with a 109-fold reduction in total airborne particle number escape rate. The deposition of infectious virus on the surface of settle plates was reduced by 87-fold.\n\nConclusionsThe isolation hood significantly reduced airborne infectious virus exposure in a simulated hospital room. Our findings support the use of the hood to limit exposure of healthcare workers to airborne virus in clinical environments.\n\nLay summaryCOVID-19 patients exhale aerosol particles which can potentially carry infectious viruses into the hospital environment, putting healthcare workers at risk of infection. This risk can be reduced by proper use of personal protective equipment (PPE) to protect workers from virus exposure. More effective strategies, however, aim to provide source control, reducing the amount of virus-contaminated air that is exhaled into the hospital room.\n\nThe McMonty isolation hood has been developed to trap and decontaminate the air around an infected patient. We tested the efficacy of the hood using a live virus model to mimic a COVID-19 patient in a hospital room. Using the McMonty hood reduced the amount of exhaled air particles in the room by over 109-times. In our tests, people working in the room were exposed to 374-times less infectious virus in the air, and room surfaces were 87-times less contaminated. Our study supports using devices like the McMonty hood in combination with PPE to keep healthcare workers safe from virus exposure at work.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.27.22278117", + "rel_abs": "As the Coronavirus 2019 (COVID-19) disease started to spread rapidly in the state of Ohio, the Ecology, Epidemiology and Population Health (EEPH) program within the Infectious Diseases Institute (IDI) at the Ohio State University (OSU) took the initiative to offer epidemic modeling and decision analytics support to the Ohio Department of Health (ODH). This paper describes the methodology used by the OSU/IDI response modeling team to predict statewide cases of new infections as well as potential hospital burden in the state.\n\nThe methodology has two components: 1) A Dynamic Survival Analysis (DSA)-based statistical method to perform parameter inference, statewide prediction and uncertainty quantification. 2) A geographic component that down-projects statewide predicted counts to potential hospital burden across the state. We demonstrate the overall methodology with publicly available data. A Python implementation of the methodology has been made available publicly.\n\nHighlightsO_LIWe present a novel statistical approach called Dynamic Survival Analysis (DSA) to model an epidemic curve with incomplete data. The DSA approach is advantageous over standard statistical methods primarily because it does not require prior knowledge of the size of the susceptible population, the overall prevalence of the disease, and also the shape of the epidemic curve.\nC_LIO_LIThe principal motivation behind the study was to obtain predictions of case counts of COVID-19 and the resulting hospital burden in the state of Ohio during the early phase of the pandemic.\nC_LIO_LIThe proposed methodology was applied to the COVID-19 incidence data in the state of Ohio to support the Ohio Department of Health (ODH) and the Ohio Hospital Association (OHA) with predictions of hospital burden in each of the Hospital Catchment Areas (HCAs) of the state.\nC_LI", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Leo Yi Yang Lee", - "author_inst": "The University of Melbourne" - }, - { - "author_name": "Shane A Landry", - "author_inst": "Monash University" - }, - { - "author_name": "Milan Jamriska", - "author_inst": "Defence Science and Technology Group" + "author_name": "Wasiur Rahman Khuda Bukhsh", + "author_inst": "School of Mathematical Sciences, University of Nottingham, University Park, Nottingham NG7 2RD, United Kingdom" }, { - "author_name": "Dinesh Subedi", - "author_inst": "Monash University" + "author_name": "Caleb D Bastian", + "author_inst": "Applied Mathematics, Princeton University and Massive Dynamics, Princeton NJ, USA" }, { - "author_name": "Simon A Joosten", - "author_inst": "Monash University" + "author_name": "Matthew Wascher", + "author_inst": "Department of Mathematics, University of Dayton, 300 College Park, Dayton, Ohio 45469, USA" }, { - "author_name": "Jeremy J Barr", - "author_inst": "Monash University" + "author_name": "Colin Klaus", + "author_inst": "College of Public Health, The Ohio State University, Cunz Hall, 1841 Neil Avenue, Columbus, OH 43210, USA" }, { - "author_name": "Reece Brown", - "author_inst": "Defence Science and Technology Group" + "author_name": "Saumya Yashmohini Sahai", + "author_inst": "Department of Computer Science and Engineering, The Ohio State University, 395 Dreese Laboratories, 2015 Neil Avenue, Columbus, OH 43210, USA" }, { - "author_name": "Kevin Kevin", - "author_inst": "The University of Melbourne" + "author_name": "Mark H Weir", + "author_inst": "The Ohio State University" }, { - "author_name": "Robyn Schofield", - "author_inst": "The University of Melbourne" + "author_name": "Eben Kenah", + "author_inst": "College of Public Health, The Ohio State University, Cunz Hall, 1841 Neil Avenue, Columbus, OH 43210, USA" }, { - "author_name": "Jason Monty", - "author_inst": "The University of Melbourne" + "author_name": "Elisabeth Root", + "author_inst": "Institute for Disease Modeling, The Bill \\& Melinda Gates Foundation, Seattle, Washington, USA" }, { - "author_name": "Kanta Subbarao", - "author_inst": "WHO Collaborating Centre for Reference and Research on Influenza" + "author_name": "Joseph H. Tien", + "author_inst": "The Ohio State University" }, { - "author_name": "Forbes McGain", - "author_inst": "Western Health" + "author_name": "Grzegorz A Rempala", + "author_inst": "The Ohio State University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.07.25.22277998", @@ -259798,119 +260161,139 @@ "category": "geriatric medicine" }, { - "rel_doi": "10.1101/2022.07.26.22278045", - "rel_title": "Effectiveness of the BNT162b2 vaccine against SARS-CoV-2 infection among children and adolescents in Qatar", + "rel_doi": "10.1101/2022.07.26.501570", + "rel_title": "Primary Omicron infection elicits weak antibody response but robust cellularimmunity in children", "rel_date": "2022-07-26", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.26.22278045", - "rel_abs": "BackgroundThe BNT162b2 COVID-19 vaccine is authorized for children 5-11 years of age and adolescents 12-17 years of age, but in different dose sizes. We assessed BNT162b2 real-world effectiveness against SARS-CoV-2 infection among children and adolescents in Qatar.\n\nMethodsThree matched, retrospective, target-trial, cohort studies were conducted to compare incidence of SARS-CoV-2 infection in the national cohort of vaccinated individuals to incidence in the national cohort of unvaccinated individuals. Associations were estimated using Cox proportional-hazards regression models.\n\nResultsEffectiveness of the 10 {micro}g dose for children against Omicron infection was 25.7% (95% CI: 10.0-38.6%). It was highest at 49.6% (95% CI: 28.5-64.5%) right after the second dose, but waned rapidly thereafter and was negligible after 3 months. Effectiveness was 46.3% (95% CI: 21.5-63.3%) among those aged 5-7 years and 16.6% (-4.2-33.2%) among those aged 8-11 years. Effectiveness of the 30 {micro}g dose for adolescents against Omicron infection was 30.6% (95% CI: 26.9-34.1%), but many adolescents were vaccinated months earlier. Effectiveness waned with time after the second dose. Effectiveness was 35.6% (95% CI: 31.2-39.6%) among those aged 12-14 years and 20.9% (13.8-27.4%) among those aged 15-17 years. Effectiveness of the 30 {micro}g dose for adolescents against pre-Omicron infection was 87.6% (95% CI: 84.0-90.4%) and waned relatively slowly after the second dose.\n\nConclusionsPediatric vaccination is associated with modest and rapidly waning protection against Omicron infection. Adolescent vaccination is associated with stronger and more durable protection, perhaps because of the larger dose size. Age at such young age appears to play a role in determining vaccine protection, with greater protection observed in younger than older children or adolescents.", - "rel_num_authors": 25, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.26.501570", + "rel_abs": "Omicron variants of SARS-CoV-2 are globally dominant and infection rates are very high in children. We determined immune responses following Omicron BA.1/2 infection in children aged 6-14 years and related this to prior and subsequent SARS-CoV-2 infection or vaccination. Primary Omicron infection elicited a weak antibody response with poor functional neutralizing antibodies. Subsequent Omicron reinfection or COVID-19 vaccination elicited increased antibody titres with broad neutralisation of Omicron subvariants. Prior pre-Omicron SARS-CoV-2 virus infection or vaccination primed for robust antibody responses following Omicron infection but these remained primarily focussed against ancestral variants. Primary Omicron infection thus elicits a weak antibody response in children which is boosted after reinfection or vaccination. Cellular responses were robust and broadly equivalent in all groups, providing protection against severe disease irrespective of SARS-CoV-2 variant. Immunological imprinting is likely to act as an important determinant of long-term humoral immunity, the future clinical importance of which is unknown.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Hiam Chemaitelly", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Alexander C Dowell", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "Sawsan AlMukdad", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Tara Lancaster", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "Houssein Ayoub", - "author_inst": "Qatar University" + "author_name": "Rachel Bruton", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "Heba N. Altarawneh", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Georgina Ireland", + "author_inst": "Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom" }, { - "author_name": "Peter Coyle", - "author_inst": "Hamad Medical Corporation" + "author_name": "Christopher Bentley", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "Patrick Tang", - "author_inst": "Sidra Medicine" + "author_name": "Panagiota Sylla", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "HADI M. YASSINE", - "author_inst": "Qatar University" + "author_name": "Jianmin Zuo", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "Hebah A. Al-Khatib", - "author_inst": "Qatar University" + "author_name": "Sam Scott", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK" }, { - "author_name": "Maria K. Smatti", - "author_inst": "Qatar University" + "author_name": "Azar Jardin", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "Mohammad R. Hasan", - "author_inst": "Sidra Medicine" + "author_name": "Jusnara Begum", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "Zaina Al-Kanaani", - "author_inst": "Hamad Medical Corporation" + "author_name": "Thomas Roberts", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "Einas Al-Kuwari", - "author_inst": "Hamad Medical Corporation" + "author_name": "Christine Stephens", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" }, { - "author_name": "Andrew Jeremijenko", - "author_inst": "Hamad Medical Corporation" + "author_name": "Shabana Ditta", + "author_inst": "Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK." }, { - "author_name": "Anvar Hassan Kaleeckal", - "author_inst": "Hamad Medical Corporation" + "author_name": "Rebecca Shepherdson", + "author_inst": "Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK." }, { - "author_name": "Ali Nizar Latif", - "author_inst": "Hamad Medical Corporation" + "author_name": "Annable Powell", + "author_inst": "Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom" }, { - "author_name": "Riyazuddin Mohammad Shaik", - "author_inst": "Hamad Medical Corporation" + "author_name": "Andrew Brent", + "author_inst": "Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE" }, { - "author_name": "Hanan F. Abdul-Rahim", - "author_inst": "Qatar University" + "author_name": "Bernadette Brent", + "author_inst": "Oxford University Hospitals NHS Foundation Trust, Old Road, Oxford OX3 7HE" }, { - "author_name": "Gheyath Nasrallah", - "author_inst": "Qatar University" + "author_name": "Frances Baawuah", + "author_inst": "Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom" }, { - "author_name": "Mohamed Ghaith Al-Kuwari", - "author_inst": "Primary Health Care Corporation" + "author_name": "Ifeanyichukwu Okike", + "author_inst": "Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom" }, { - "author_name": "Hamad E. Al-Romaihi", - "author_inst": "MoPH: Ministry of Public Health Qatar" + "author_name": "Joanna Beckmann", + "author_inst": "East London NHS Foundation Trust, 9 Allie Street, London E1 8DE, UK" }, { - "author_name": "Adeel A Butt", - "author_inst": "Hamad Medical Corporation" + "author_name": "Shazaad Ahmad", + "author_inst": "Manchester University NHS Foundation Trust, Oxford Road, Manchester M13 9WL, UK" }, { - "author_name": "Mohamed H. Al-Thani", - "author_inst": "MoPH: Ministry of Public Health Qatar" + "author_name": "Felicity Aiano", + "author_inst": "Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom" }, { - "author_name": "Abdullatif Al-Khal", - "author_inst": "Hamad Medical Corporation" + "author_name": "Joanna Garstang", + "author_inst": "Birmingham Community Healthcare NHS Trust, Holt Street, Aston B7 4BN, UK" }, { - "author_name": "Roberto Bertollini", - "author_inst": "Ministry of Public Health" + "author_name": "Mary Ramsay", + "author_inst": "Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom" }, { - "author_name": "Laith J Abu-Raddad", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Rafaq Azad", + "author_inst": "Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK." + }, + { + "author_name": "Dagmar Waiblinger", + "author_inst": "Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK." + }, + { + "author_name": "Brian Willet", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, 464 Bearsden Road, Glasgow G61-1QH, UK" + }, + { + "author_name": "John Wright", + "author_inst": "Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, BD9 6RJ, UK." + }, + { + "author_name": "Shamez Ladhani", + "author_inst": "Immunisation Department, UK Health Security Agency, 61 Colindale Avenue, London, United Kingdom" + }, + { + "author_name": "Paul Moss", + "author_inst": "Institute of Immunology & Immunotherapy, Collage of Medical and Dental Sciences, University of Birmingham, Birmingham, B15 2TT, UK" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.07.25.501479", @@ -261528,127 +261911,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.07.22.22277947", - "rel_title": "High titre neutralizing antibodies in response to SARS-CoV-2 infection require RBD-specific CD4 T cells that include proliferative memory cells.", - "rel_date": "2022-07-24", + "rel_doi": "10.1101/2022.07.19.22277806", + "rel_title": "Cervical cancer screening improvements with self- sampling during the COVID-19 pandemic", + "rel_date": "2022-07-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.22.22277947", - "rel_abs": "Long-term immunity to SARS-CoV-2 infection, including neutralizing antibodies and T cell-mediated immunity, is required in a very large majority of the population in order to reduce ongoing disease burden. We have investigated the association between memory CD4 and CD8 T cells and levels of neutralizing antibodies in convalescent COVID-19 subjects. Higher titres of convalescent neutralizing antibodies were associated with significantly higher levels of RBD-specific CD4 T cells, including specific memory cells that proliferated vigorously in vitro. Conversely, up to half of convalescent individuals had low neutralizing antibody titres together with a lack of receptor binding domain (RBD)- specific memory CD4 T cells. These low antibody subjects had other, non-RBD, spike-specific CD4 T cells, but with more of an inhibitory Foxp3+ and CTLA-4+ cell phenotype, rather than the effector T- bet+, cytotoxic granzymes+ and perforin+ cells seen in high antibody subjects. Single cell transcriptomics of antigen-specific CD4+ T cells from high antibody subjects revealed heterogenous RBD-specific CD4+ T cells that comprised central memory, transitional memory and Tregs, as well as cytotoxic clusters containing diverse TCR repertoires, that were absent in individuals with low antibody levels. However, vaccination in low antibody convalescent individuals led to a slight but significant improvement in RBD-specific memory CD4 T cells and increased neutralizing antibody titres. Our results suggest that targeting CD4 T cell epitopes proximal to and within the RBD- region should be prioritized in booster vaccines.\n\nOne Sentence SummaryIndividuals with low neutralising antibody titres may be at risk of SARS-CoV-2 re-infection due to a failure to generate a high quality CD4 T cell response specific for receptor binding domain (RBD), including memory CD4 T cells that proliferate in vitro in response to RBD, and which are also therefore an important target for vaccine design.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.19.22277806", + "rel_abs": "BackgroundAt the onset of the COVID-19 pandemic cervical screening in the capital region of Sweden was cancelled for several months. A series of measures to preserve and improve the cervical screening under the circumstances were instituted, including a switch to screening with HPV self-sampling to enable screening in compliance with social distancing recommendations.\n\nMethodsWe describe the major changes implemented, which were i) nationwide implementation of HPV screening ii) switch to primary self-sampling instead of clinician sampling iii) implementation of HPV screening in all screening ages and iv) combined HPV vaccination and HPV screening in the cervical screening program.\n\nResultsA temporary government regulation allowed primary self-sampling with HPV screening in all ages. In the Stockholm region, 330,000 self-sampling kits were sent to the home address of screening-eligible women, instead of an invitation to clinician sampling. An increase in population test coverage was seen (from 66% to 70% in just one year). In addition, a national campaign for faster elimination of cervical cancer with concomitant screening and vaccination for women in ages 23-28 was launched.\n\nConclusionsThe COVID-19 pandemic necessitated major changes in the cervical cancer preventive strategies, where it can already be concluded that the strategy with organised primary self-sampling for HPV has resulted in a major improvement of population test-coverage.\n\nFundingFunded by the Swedish Association of Local Authorities and Regions, the Swedish Cancer Society, the European Unions Horizon 2020 Research and Innovation Program, the Swedish government and the Stockholm county.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Chansavath Phetsouphanh", - "author_inst": "The Kirby Institute, University of New South Wales" - }, - { - "author_name": "Weng Hua Khoo", - "author_inst": "Garvan Institute of Medical Research" - }, - { - "author_name": "Katherine Jackson", - "author_inst": "Garvan Institute of Medical Research" - }, - { - "author_name": "Vera Klemm", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Annett Howe", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Anupriya Aggarwal", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Anouschka Akerman", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Vanessa Milogiannakis", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Alberto Ospina Stella", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Romain Rouet", - "author_inst": "Garvan Institute of Medical Research" - }, - { - "author_name": "Peter Schofield", - "author_inst": "Garvan Institute of Medical Research" - }, - { - "author_name": "Megan L. Faulks", - "author_inst": "Garvan Institute of Medical Research" - }, - { - "author_name": "Hannah Law", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Thidarat Danwilai", - "author_inst": "NSW State Reference Laboratory for HIV St Vincents Centre for Applied Medical Research" - }, - { - "author_name": "Mitchell Starr", - "author_inst": "NSW State Reference Laboratory for HIV St Vincents Centre for Applied Medical Research" - }, - { - "author_name": "C.Mee Ling Munier", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Daniel Christ", - "author_inst": "Garvan Institute of Medical Research" - }, - { - "author_name": "Mandeep Singh", - "author_inst": "Garvan Institute of Medical Research" - }, - { - "author_name": "Peter I Croucher", - "author_inst": "Garvan Institute of Medical Research" - }, - { - "author_name": "Fabienne Brilot-Turville", - "author_inst": "Sydney Institute for Infectious Diseases The University of Sydney" - }, - { - "author_name": "Stuart Turville", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Tri Giang Phan", - "author_inst": "Garvan Institute of Medical Research" - }, - { - "author_name": "Gregory J Dore", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Philip Cunningham", - "author_inst": "NSW State Reference Laboratory for HIV, St Vincents Centre for Applied Medical Research" - }, - { - "author_name": "Gail V Matthews", - "author_inst": "Kirby Institute, UNSW" - }, - { - "author_name": "Anthony D Kelleher", - "author_inst": "Kirby Institute, UNSW" + "author_name": "Miriam Elfstr\u00f6m", + "author_inst": "Karolinska University Hospital" }, { - "author_name": "John J Zaunders", - "author_inst": "St Vincent's Hospital" + "author_name": "Joakim Dillner", + "author_inst": "Karolinska Institutet" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.07.22.22277931", @@ -263238,83 +263521,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.20.22277838", - "rel_title": "National and regional prevalence of SARS-CoV-2 antibodies in primary and secondary school children in England: the School Infection Survey, a national open cohort study, November 2021", + "rel_doi": "10.1101/2022.07.20.22277872", + "rel_title": "Geographic and Temporal Patterns in Covid-19 Mortality by Race and Ethnicity in the United States from March 2020 to February 2022", "rel_date": "2022-07-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.20.22277838", - "rel_abs": "BackgroundRisk factors for infection and, therefore, antibody positivity rates will be different in children compared to adults. We aim to estimate national and regional prevalence of SARS-CoV-2 antibodies in primary (4-11-year-olds) and secondary (11-15-year-olds) school children between 10 November and 10 December 2021.\n\nMethodsCross-sectional surveillance in England using two stage sampling, firstly stratifying into regions and selecting local authorities, then selecting schools according to a stratified sample within selected local authorities. Participants were sampled using a novel oral fluid validated assay for SARS-CoV-2 spike and nucleocapsid IgG antibodies.\n\nResults4,980 students from 117 state-funded schools (2,706 from 83 primary schools, 2,274 from 34 secondary schools) provided a valid sample. After weighting for age, sex and ethnicity, and adjusting for assay accuracy, the national prevalence of SARS-CoV-2 antibodies in primary school students, who were all unvaccinated, was 40.1% (95%CI; 37.3-43.0). Antibody prevalence increased with age (p<0.001) and were higher in urban than rural schools (p=0.01). In secondary school students, the adjusted, weighted national prevalence of SARS-CoV-2 antibodies was 82.4% (95%CI; 79.5-85.1); including 57.5% (95%CI; 53.9-61.1) in unvaccinated and 97.5% (95%CI; 96.1-98.5) in vaccinated students. Antibody prevalence increased with age (p<0.001), and was not significantly different in urban versus rural students (p=0.1).\n\nConclusionsUsing a validated oral fluid assay, we estimated national and regional seroprevalence of SARS-CoV-2 antibodies in primary and secondary school students. In November 2021, 40% of primary school students and nearly all secondary school students in England had SARS-CoV2 antibodies through a combination of natural infection and vaccination.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.20.22277872", + "rel_abs": "Prior research has established that American Indian, Alaska Native, Black, Hispanic, and Pacific Islander populations in the United States have experienced substantially higher mortality rates from Covid-19 compared to non-Hispanic white residents during the first year of the pandemic. What remains less clear is how mortality rates have changed for each of these racial/ethnic groups during 2021, given the increasing prevalence of vaccination. In particular, it is unknown how these changes in mortality have varied geographically. In this study, we used provisional data from the National Center for Health Statistics (NCHS) to produce age-standardized estimates of Covid-19 mortality by race/ethnicity in the United States from March 2020 to February 2022 in each metro-nonmetro category, Census region, and Census division. We calculated changes in mortality rates between the first and second years of the pandemic and examined mortality changes by month. We found that when Covid-19 first affected a geographic area, non-Hispanic Black and Hispanic populations experienced extremely high levels of Covid-19 mortality and racial/ethnic inequity that were not repeated at any other time during the pandemic. Between the first and second year of the pandemic, racial/ethnic inequities in Covid-19 mortality decreased--but were not eliminated--for Hispanic, non-Hispanic Black, and non-Hispanic AIAN residents. These inequities decreased due to reductions in mortality for these populations alongside increases in non-Hispanic white mortality. Though racial/ethnic inequities in Covid-19 mortality decreased, substantial inequities still existed in most geographic areas during the pandemics second year: Non-Hispanic Black, non-Hispanic AIAN, and Hispanic residents reported higher Covid-19 death rates in rural areas than in urban areas, indicating that these communities are facing serious public health challenges. At the same time, the non-Hispanic white mortality rate worsened in rural areas during the second year of the pandemic, suggesting there may be unique factors driving mortality in this population. Finally, vaccination rates were associated with reductions in Covid-19 mortality for Hispanic, non-Hispanic Black, and non-Hispanic white residents, and increased vaccination may have contributed to the decreases in racial/ethnic inequities in Covid-19 mortality observed during the second year of the pandemic. Despite reductions in mortality, Covid-19 mortality remained elevated in nonmetro areas and increased for some racial/ethnic groups, highlighting the need for increased vaccination delivery and equitable public health measures especially in rural communities. Taken together, these findings highlight the continued need to prioritize health equity in the pandemic response and to modify the structures and policies through which systemic racism operates and has generated racial health inequities.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Annabel A Powell", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Georgina Ireland", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Rebecca Leeson", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "Andrea Lacey", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "Ben Ford", - "author_inst": "Office for National Statistics" - }, - { - "author_name": "John Poh", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Samreen Ijaz", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Justin Shute", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Peter Cherepanov", - "author_inst": "Imperial College London" - }, - { - "author_name": "Richard Tedder", - "author_inst": "Francis Crick Institute" - }, - { - "author_name": "Christian Bottomley", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Dielle J Lundberg", + "author_inst": "Boston University School of Public Health" }, { - "author_name": "Fiona Dawe", - "author_inst": "Office for National Statistics" + "author_name": "Ahyoung Cho", + "author_inst": "Boston University" }, { - "author_name": "Punam Mangtani", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Rafeya V Raquib", + "author_inst": "Boston University School of Public Health" }, { - "author_name": "Peter Jones", - "author_inst": "Office for National Statistics" + "author_name": "Elaine O Nsoesie", + "author_inst": "Boston University School of Public Health" }, { - "author_name": "Patrick Nguipdop-Djomo", - "author_inst": "London School of Hygiene & Tropical Medicine" + "author_name": "Elizabeth Wrigley-Field", + "author_inst": "University of Minnesota, Twin Cities" }, { - "author_name": "Shamez Ladhani", - "author_inst": "UK Health Security Agency" + "author_name": "Andrew C Stokes", + "author_inst": "Boston University School of Public Health" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.07.21.22277893", @@ -265008,71 +265251,51 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.07.16.22277716", - "rel_title": "The association of typical and atypical symptoms on in-hospital mortality of older adults with COVID-19: a multicentre cohort study", + "rel_doi": "10.1101/2022.07.18.22277744", + "rel_title": "A pilot surveillance report of SARS-CoV-2 rapid antigen test results among volunteers in Germany, 1st week of July 2022", "rel_date": "2022-07-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.16.22277716", - "rel_abs": "Atypical disease presentations are common in older adults with COVID-19. The objective of this study was to determine the prevalence of atypical and typical symptoms in older adults with COVID-19 through progressive pandemic waves and the association of these symptoms with in-hospital mortality. This retrospective cohort study included consecutive adults aged over 65 years with confirmed COVID-19 infection who were admitted to seven hospitals in Toronto, Canada from March 1, 2020 to June 30, 2021. The median age for the 1786 patients was 78.0 years and 847 (47.5%) were female. Atypical symptoms (as defined by geriatric syndromes) occurred in 1187 patients (66.5%), but rarely occurred in the absence of other symptoms (n=106, 6.2%). The most common atypical symptoms were anorexia (n=598, 33.5%), weakness (n=519, 23.9%), and delirium (n=449, 25.1%). Dyspnea (adjusted odds ratio [aOR] 2.05, 95% confidence interval [CI] 1.62-2.62), tachycardia (aOR 1.87, 95% CI 1.14-3.04), and delirium (aOR 1.52, 95% CI 1.18-1.96) were independently associated with in-hospital mortality. In a cohort of older adults hospitalized with COVID-19 infection, atypical presentations frequently overlapped with typical symptoms. Further research should be directed at understanding the cause and clinical significance of atypical presentations in older adults.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.18.22277744", + "rel_abs": "We hypothesized that reported SARS-CoV-2 infection numbers are underestimated and piloted a point prevalence by rapid antigen testing in the VACCELERATE volunteer registry.\n\nBetween July-1 and July-7, 2022, 7/419 (1.67%) tests were positive. Compared to reports of the German Federal Government, our results suggest a 2.39-fold higher prevalence.\n\nOur findings imply that the actual prevalence of SARS-CoV-2 may be higher than detected by current surveillance systems, so that current pandemic surveillance and testing strategies need to be adapted.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Eric Kai-Chung Wong", - "author_inst": "University of Toronto" - }, - { - "author_name": "Jennifer Watt", - "author_inst": "University of Toronto" - }, - { - "author_name": "Hanyan Zou", - "author_inst": "Sinai Health and University Health Network" - }, - { - "author_name": "Arthana Chandraraj", - "author_inst": "Li Ka Shing Knowledge Institute" - }, - { - "author_name": "Alissa Wenyue Zhang", - "author_inst": "Sunnybrook Health Sciences Centre" - }, - { - "author_name": "Jahnel Brookes", - "author_inst": "Baycrest Health Sciences Centre" + "author_name": "Jannik Stemler", + "author_inst": "University Hospital Cologne: Uniklinik Koln" }, { - "author_name": "Ashley Verduyn", - "author_inst": "Providence Healthcare and Houses of Providence" + "author_name": "Jon Salmanton-Garcia", + "author_inst": "University Hospital Cologne: Uniklinik Koln" }, { - "author_name": "Anna Berall", - "author_inst": "Baycrest Health Sciences Centre" + "author_name": "Ben Weise", + "author_inst": "University Hospital Cologne: Uniklinik Koln" }, { - "author_name": "Richard Norman", - "author_inst": "Sinai Health and University Health Network" + "author_name": "Christina Toebben", + "author_inst": "University Hospital Cologne: Uniklinik Koln" }, { - "author_name": "Katrina Lynn Piggott", - "author_inst": "Sunnybrook Health Sciences Centre" + "author_name": "Carolin Joisten", + "author_inst": "University Hospital Cologne: Uniklinik Koln" }, { - "author_name": "Terumi Izukawa", - "author_inst": "Baycrest Health Sciences Centre" + "author_name": "Julian Fleig", + "author_inst": "University Hospital Cologne: Uniklinik Koln" }, { - "author_name": "Sharon E Straus", - "author_inst": "Unity Health Toronto" + "author_name": "Oliver Andreas Cornely", + "author_inst": "University Hospital Cologne: Uniklinik Koln" }, { - "author_name": "Barbara Liu", - "author_inst": "Sunnybrook Health Sciences Centre" + "author_name": "- VACCELERATE Consortium", + "author_inst": "" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "geriatric medicine" + "category": "health policy" }, { "rel_doi": "10.1101/2022.07.18.22277741", @@ -266986,59 +267209,71 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.12.22277518", - "rel_title": "Tracing the international arrivals of SARS-CoV-2 Omicron variants after Aotearoa New Zealand reopened its border", + "rel_doi": "10.1101/2022.07.14.22277617", + "rel_title": "An Evaluation of the Safety and Immunogenicity of MVC-COV1901: Results of an interim analysis of a phase III, parallel group, randomized, double-blind, active-controlled study", "rel_date": "2022-07-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.12.22277518", - "rel_abs": "Recently there has been a surge in emergent SARS-CoV-2 lineages that are able to evade both vaccine induced immunity as well as prior infection from the founding Omicron BA.1 and BA.2 lineages. These highly transmissible and evasive lineages are on the rise and include Omicron variants BA.2.12.1, BA.4, and BA.5. Aotearoa New Zealand recently reopened its borders to many travellers, without their need to enter quarantine. By generating 10,403 complete SARS-CoV-2 genomes classified as Omicron, we show that New Zealand is observing an influx of these immune-evasive variants through the border. Specifically, there has been a recent surge of BA.5 and BA.2.12.1 introductions into the community and these can be explained by the gradual return to pre-pandemic levels of international traveller arrival rates. We estimate there is one Omicron transmission event from the border to the community for every [~]5,000 passenger arrivals into the country, or around one introduction event per day at the current levels of travel. Given the waning levels of population immunity, this rate of importation presents the risk of a large wave in New Zealand during the second half of 2022. Genomic surveillance, coupled with modelling the rate at which new variants cross the border into the community, provides a lens on the rate at which new variants might gain a foothold and trigger new waves of infection.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.14.22277617", + "rel_abs": "BackgroundData from previous studies of the MVC-COV1901 vaccine, a subunit vaccine against SARS-CoV-2 based on the stable prefusion spike protein (S-2P) adjuvanted with CpG 1018 adjuvant and aluminum hydroxide, suggest that the vaccine is generally safe and elicits a good immune response in healthy adults and adolescents. By comparing with AZD1222, this study adds to the findings from previous trials and further evaluates the breadth of protection offered by MVC-COV1901.\n\nMethodsIn this phase 3, parallel group, randomized, double-blind, active-controlled trial conducted in 2 sites in Paraguay, we assigned adults aged 18 to 91 years in a 1:1 ratio to receive intramuscular doses of MVC-COV1901 or AZD1222 administered as scheduled in the clinical trial. Serum samples were collected on the day of vaccination and 14 days after the second dose. Primary and secondary safety and immunogenicity endpoints were assessed. In addition, other outcomes investigated were cross-reactive immunity against the Omicron strain and the induction of IgG subclasses.\n\nResultsA total of 1,030 participants underwent randomization. Safety data was derived from this set while primary immunogenicity data involved a per-protocol immunogenicity (PPI) subset including 225 participants. Among the participants, 58% are seropositive at baseline. When compared against AZD1222, MVC-COV1901 exhibited superiority in terms of neutralizing antibody titers and non-inferiority in terms of seroconversion rates. Reactogenicity was generally mild and no serious adverse event was attributable to MVC-COV1901. Both vaccines have a Th1-biased response predominated by the production of IgG1 and IgG3 subclasses. Omicron-neutralizing titers were 44.5 times lower compared to wildtype-neutralizing titers among seronegative individuals at baseline. This fold-reduction was 3.0 times among the seropositive.\n\nConclusionResults presented here demonstrate the safe and robust immunogenicity from MVC-COV1901. Previous infection coupled with vaccination of this vaccine may offer protection against the Omicron strain though its durability is still unknown.\n\nClinicalTrials.gov registrationNCT05011526", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Jordan Douglas", - "author_inst": "University of Auckland" + "author_name": "Julio Torales", + "author_inst": "School of Medical Sciences, National University of Asuncion, San Lorenzo, Paraguay" }, { - "author_name": "David Winter", - "author_inst": "Institute of Environmental Science and Research" + "author_name": "Osmar Cuenca-Torres", + "author_inst": "School of Medical Sciences, National University of Asuncion, San Lorenzo, Paraguay" }, { - "author_name": "Xiaoyun Ren", - "author_inst": "Institute of Environmental Science and Research" + "author_name": "Laurentino Barrios", + "author_inst": "School of Medical Sciences, National University of Asuncion, San Lorenzo, Paraguay" }, { - "author_name": "Andrea McNeill", - "author_inst": "Institute of Environmental Science and Research" + "author_name": "Luis Armoa-Garcia", + "author_inst": "School of Medical Sciences, National University of Asuncion, San Lorenzo, Paraguay" }, { - "author_name": "Michael Bunce", - "author_inst": "Institute of Environmental Science and Research" + "author_name": "Gladys Estigarribia", + "author_inst": "School of Medical Sciences, National University of Asuncion, San Lorenzo, Paraguay" }, { - "author_name": "Nigel French", - "author_inst": "Massey University" + "author_name": "Gabriela Sanabria", + "author_inst": "School of Medical Sciences, National University of Asuncion, San Lorenzo, Paraguay" }, { - "author_name": "James Hadfield", - "author_inst": "Fred Hutchinson Cancer Research Centre" + "author_name": "Meei-Yun Lin", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan" }, { - "author_name": "Joep de Ligt", - "author_inst": "Institute of Environmental Science and Research" + "author_name": "Josue Antonio Garcia Estrada", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan" }, { - "author_name": "David Welch", - "author_inst": "University of Auckland" + "author_name": "Lila Estephan", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan" }, { - "author_name": "Jemma L Geoghegan", - "author_inst": "University of Otago" + "author_name": "Hao-Yuan Cheng", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan" + }, + { + "author_name": "Charles Chen", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan" + }, + { + "author_name": "Robert Janssen", + "author_inst": "Dynavax Technologies Corporation, Emeryville, CA, USA" + }, + { + "author_name": "Chia En Lien", + "author_inst": "Medigen Vaccine Biologics Corporation, Taipei, Taiwan; Institute of Public Health, National Yang-Ming Chiao Tung University, Taipei, Taiwan" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.07.12.22277336", @@ -268944,73 +269179,41 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.07.14.500068", - "rel_title": "Ending transmission of SARS-CoV-2: sterilizing immunity using an intranasal subunit vaccine", + "rel_doi": "10.1101/2022.07.14.500031", + "rel_title": "A zebrafish model of COVID-19-associated cytokine storm syndrome reveals that the Spike protein signals via TLR2", "rel_date": "2022-07-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.14.500068", - "rel_abs": "Immunization programs against SARS-CoV-2 with commercial intramuscular (IM) vaccines prevent disease but not infections. The continued evolution of variants of concern (VOC) like Delta and Omicron has increased infections even in countries with high vaccination coverage. This is due to commercial vaccines being unable to prevent viral infection in the upper airways and exclusively targeting the spike (S) protein that is subject to continuous evolution facilitating immune escape. Here we report a multi-antigen, intranasal vaccine, NanoSTING-NS that yields sterilizing immunity and leads to the rapid and complete elimination of viral loads in both the lungs and the nostrils upon viral challenge with SARS-CoV-2 VOC. We formulated vaccines with the S and nucleocapsid (N) proteins individually to demonstrate that immune responses against S are sufficient to prevent disease whereas combination immune responses against both proteins prevents viral replication in the nasal compartment. Studies with the highly infectious Omicron VOC showed that even in vaccine-naive animals, a single dose of NanoSTING-NS significantly reduced transmission. These observations have two implications: (1) mucosal multi-antigen vaccines present a pathway to preventing transmission and ending the pandemic, and (2) an explanation for why hybrid immunity in humans is superior to vaccine-mediated immunity by current IM vaccines.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.14.500031", + "rel_abs": "Understanding the mechanism of virulence of SARS-CoV-2 and host innate immune responses are essential to develop novel therapies. One of the most studied defense mechanisms against invading pathogens, including viruses, are Toll-like receptors (TLRs). Among them, TLR3, TLR7, TLR8 and TLR9 detect different forms of viral nucleic acids in endosomal compartments, whereas TLR2 and TLR4 recognize viral structural and nonstructural proteins outside the cell. Although many different TLRs have been shown to be involved in SARS-CoV-2 infection and detection of different structural proteins, most studies have been performed in vitro and the results obtained are rather contradictory. In this study, we report using the unique advantages of the zebrafish model for in vivo imaging and gene editing that the S1 domain of the Spike protein from the Wuhan strain (S1WT) induced hyperinflammation in zebrafish larvae via a Tlr2/Myd88 signaling pathway and independently of interleukin-1{beta} production. In addition, S1WT also triggered emergency myelopoiesis, but in this case through a Tlr2/Myd88-independent signaling pathway. These results shed light on the mechanisms involved in the COVID-19-associated cytokine storm syndrome.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Ankita Leekha", - "author_inst": "Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA" - }, - { - "author_name": "Arash Saeedi", - "author_inst": "Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA" - }, - { - "author_name": "Samiur Rahman Sefat", - "author_inst": "Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA" - }, - { - "author_name": "Monish Kumar", - "author_inst": "Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA" - }, - { - "author_name": "Melisa Martinez Paniagua", - "author_inst": "Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA" - }, - { - "author_name": "Adrian Damian", - "author_inst": "Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA" - }, - { - "author_name": "Rohan Kulkarni", - "author_inst": "Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA" - }, - { - "author_name": "Ali Rezvan", - "author_inst": "Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA" - }, - { - "author_name": "Shalaleh Mosoumi", - "author_inst": "Department of Pharmacological and Pharmaceutical Sciences, College of Pharmacy, University of Houston, Houston, TX, USA" + "author_name": "Sylwia D Tyrkalska", + "author_inst": "Universidad de Murcia" }, { - "author_name": "Xinli Liu", - "author_inst": "Department of Pharmacological and Pharmaceutical Sciences, College of Pharmacy, University of Houston, Houston, TX, USA" + "author_name": "Alicia Martinez-Lopez", + "author_inst": "Instituto Murciano de Investigacion Biosanitaria Arrixaca" }, { - "author_name": "Laurence J.N. Cooper", - "author_inst": "AuraVax Therapeutics, Houston, TX, USA" + "author_name": "Annamaria Pedoto", + "author_inst": "Universidad de Murcia" }, { - "author_name": "Manu Sebastian", - "author_inst": "AuraVax Therapeutics, Houston, TX, USA" + "author_name": "Sergio Candel", + "author_inst": "Universidad de Murcia" }, { - "author_name": "Brett L. Hurst", - "author_inst": "Institute for Antiviral Research, Utah State University, Logan, UT, USA" + "author_name": "Maria L. Cayuela", + "author_inst": "University Hospital \"Virgen de la Arrixaca\"" }, { - "author_name": "Navin Varadarajan", - "author_inst": "Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA" + "author_name": "Victoriano Mulero", + "author_inst": "Universidad de Murcia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -270710,57 +270913,129 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.12.22277538", - "rel_title": "Dengue seroprevalence study during COVID-19 pandemic in Bali", + "rel_doi": "10.1101/2022.07.12.22277549", + "rel_title": "Delayed generation of functional virus-specific circulating T follicular helper cells correlates with severe COVID-19", "rel_date": "2022-07-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.12.22277538", - "rel_abs": "IntroductionDengue infection poses significant public health problems in tropical and subtropical regions all over the world. The clinical manifestation of dengue varies from asymptomatic cases to severe dengue manifestation. The detection of clinical cases enables us to measure the incidence of dengue infection, whereas serological surveys give insights into the prevalence of infection. This study aimed to determine the dengue prevalence among healthy adult patients in Bali.\n\nMethodCross-sectional seroprevalence surveys were performed from July 2020 to June 2021 among healthy and adult patients in Denpasar Bali. Blood samples were collected from 539 randomly selected samples from urban sites in Denpasar. IgG antibodies against DENV were detected in serum using a commercial enzyme-linked immunosorbent assay (ELISA) kit.\n\nResultsOverall, the positive dengue seroprevalence rate among 539 clinically healthy adult patients was high (85.5%). The subjects median age was 34.1 (range between 18-86.1) years old. Most participants in the study were younger than 40 years old (61.2%). The gender is dominated by males (54.5%). The study found a significant association of dengue seropositivity among people age more than 40 years old with healthy status (p=0.005 and p<0.001, respectively). Another seroprevalence study reported a lower rate of dengue infection in children in Indonesia (69.4%). The difference may be associated with less probability of Aedes bites among the children. The study reflected the proportion of asymptomatic dengue that needs better assessment with a serological test.\n\nConclusionThe current study highlighted a high prevalence of dengue seropositive with a relatively dominant proportion of asymptomatic cases. The study guides the physicians o to beware of every dengue infection in tropical countries and prevents the spread of the disease.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.12.22277549", + "rel_abs": "Effective humoral immune responses require well-orchestrated cellular interactions between B and T follicular helper (Tfh) cells. Whether this interaction is impaired and associated with COVID-19 disease severity is unknown. Here, longitudinal acute and convalescent blood samples from 49 COVID-19 patients across mild to severe disease were analysed. We found that during acute infection activated and SARS-CoV-2-specific circulating Tfh (cTfh) cell frequencies expanded with increasing disease severity. The frequency of activated and SARS-CoV-2-specific cTfh cells correlated with plasmablast frequencies and SARS-CoV-2 antibody titers, avidity and neutralization. Furthermore, cTfh cells but not other memory CD4 T cells, isolated from severe patients induced more pronounced differentiation of autologous plasmablast and antibody production in vitro compared to cTfh cells isolated from mild patients. However, the development of virus-specific cTfh cells was delayed in patients that displayed or later developed severe disease compared to those that maintained a mild or moderate disease. This correlated with a delayed induction of high-avidity and neutralizing virus-specific antibodies. Our study therefore suggests that impaired generation of functional virus-specific cTfh cells delays the production of high-quality antibodies to combat the infection at an early stage and thereby enabling progression to more severe COVID-19 disease.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "Sri Masyeni", - "author_inst": "University of Warmadewa: Universitas Warmadewa" + "author_name": "Meng Yu", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Afandi Charles", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Alberto Cagigi", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Wanda Christ", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Bjorn Osterberg", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Sara Falck-Jones", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Lida Azizmohammadi", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Eric Ahlberg", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Ryan Falck-Jones", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Julia Svensson", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Mu Nie", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Anna Warnqvist", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Fredrika Hellgren", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Klara Lenart", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Rodrigo Arcoverde Cerveira", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Sebastian Ols", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Gustaf Lindgren", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Ang Lin", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Holden Maecker", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Rois Muqsith Fatawy", - "author_inst": "Universitas Indonesia Fakultas Kedokteran" + "author_name": "Max Bell", + "author_inst": "Karolinska Institutet" }, { - "author_name": "AAAL Paramasatiari", - "author_inst": "University of Warmadewa Faculty of Health and Medicine: Universitas Warmadewa Fakultas Kedokteran dan Ilmu Kesehatan" + "author_name": "Niclas Johansson", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Ananda Maheraditya", - "author_inst": "University of Warmadewa Faculty of Health and Medicine: Universitas Warmadewa Fakultas Kedokteran dan Ilmu Kesehatan" + "author_name": "Jan Albert", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Ratna Kartika Dewi", - "author_inst": "University of Warmadewa Faculty of Health and Medicine: Universitas Warmadewa Fakultas Kedokteran dan Ilmu Kesehatan" + "author_name": "Christopher Sundling", + "author_inst": "Karolinska Institutet" }, { - "author_name": "NW Winianti", - "author_inst": "University of Warmadewa Faculty of Health and Medicine: Universitas Warmadewa Fakultas Kedokteran dan Ilmu Kesehatan" + "author_name": "Paulo Czarnewski", + "author_inst": "Stockholm University" }, { - "author_name": "Agus Santosa", - "author_inst": "University of Warmadewa Faculty of Health and Medicine: Universitas Warmadewa Fakultas Kedokteran dan Ilmu Kesehatan" + "author_name": "Jonas Klingstrom", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Marta Setiabudy", - "author_inst": "University of Warmadewa Faculty of Health and Medicine: Universitas Warmadewa Fakultas Kedokteran dan Ilmu Kesehatan" + "author_name": "Anna Farnert", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Nyoman Trisna Sumadewi", - "author_inst": "Udayana University Faculty of Medicine: Universitas Udayana Fakultas Kedokteran" + "author_name": "Karin Lore", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Sianny Herawati", - "author_inst": "Udayana University Faculty of Medicine: Universitas Udayana Fakultas Kedokteran" + "author_name": "Anna Smed-Sorensen", + "author_inst": "Karolinska Institutet" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -272912,87 +273187,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.07.08.22276768", - "rel_title": "Healthcare utilization following SARS-CoV-2 infection in children and adolescents with chronic conditions: An EHR-based Cohort Study from the RECOVER Program", + "rel_doi": "10.1101/2022.07.07.22277395", + "rel_title": "Analysing COVID treatment outcomes in dedicated wards at a large university hospital in northern Poland. A result-based observational study.", "rel_date": "2022-07-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.08.22276768", - "rel_abs": "BackgroundChronic medical conditions are a risk factor for moderate or severe COVID-19 in children, but little is known about post-acute sequelae of SARS-CoV-2 infection (PASC) in children with chronic medical conditions (CMCs). To understand whether SARS-CoV-2 infection led to potential exacerbation of underlying chronic disease in children, we explored whether children with CMCs had increased healthcare utilization in the post-acute (28 days after infection) period compared to children with CMCs without SARS-CoV-2 infection.\n\nMethodsWe conducted a retrospective, matched-cohort study using electronic health record data collected from 8 pediatric health care systems participating in the PEDSnet network. We included children <21 years of age with a wide array of chronic conditions, defined by the presence of diagnostic codes, who were diagnosed with COVID-19 between March 1, 2020 and February 28, 2022. Cohort entry was defined by presence of a positive SARS-CoV-2 PCR test (polymerase chain reaction or antigen) or diagnostic codes for COVID-19, PASC or MIS-C. A comparison cohort of patients testing negative or without these conditions was matched using a stratified propensity score model and exact matching on age group, race/ethnicity, institution, test location, and month of cohort entry. A negative binomial model was used to examine our primary outcome: composite and setting-specific (inpatient, outpatient, ED) utilization rate ratios between the positive and comparison cohorts. Secondary outcomes included time to first utilization in the post-acute period, and utilization stratified by severity at cohort entry.\n\nResultsWe identified 748,692 patients with at least one chronic condition, 78,744 of whom met inclusion criteria for the COVID-19 cohort. 96% of patients from the positive cohort were matched. Cohorts were well-balanced for chronic condition clusters, total number of conditions, time since first diagnosis, baseline utilization, cohort entry period, age, sex, race/ethnicity and test location. We found that among children with chronic medical conditions, those with COVID-19 had higher healthcare utilization than those with no recorded COVID-19 diagnosis or positive test, with utilization rate ratio of 1.21 (95% CI: 1.18-1.24). The utilization was highest for inpatient care with utilization rate ratio of 2.03 (95% CI: 1.85-2.23) but the utilization was increased across all settings. Hazard ratios estimated in time-to-first-utilization analysis mirrored these results. Patients with severe or moderate acute COVID-19 illness had greater increases in utilization in all settings than those with mild or asymptomatic disease.\n\nConclusionsWe found that care utilization in all settings was increased following COVID-19 in children with chronic medical conditions in the post-acute period, particularly in the inpatient setting. Increased utilization was correlated with more severe COVID-19. Additional research is needed to better understand the reasons for higher care utilization by studying condition-specific outcomes in children with chronic disease.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.07.22277395", + "rel_abs": "IntroductionPresenting outcomes of patients hospitalised for coronavirus disease (COVID-19) should be put in context and comparison with other facilities. Number of statistical parameters can be used to compare effectiveness of treatment, however varied methodology applied in studies can impede or hinder a reliable comparison. The aim of this study is to present outcomes of COVID-19 treatment in our facility using simplest parameters allowing for intercenter comparison - case fatality ratio (CFR), length of stay (LOS) and transparent patients characteristics, and to discuss factors affecting mortality in COVID-19.\n\nMethodsThe data were collected from patients hospitalized in COVID-19 general and ICU isolation wards in the University Clinical Centre (UCC) in Gdansk, Poland, from November 2020 to June 2021, using a computer-based patient record system. The group consisted of 642 patients - 144 (39,1 %) were women and 391 (60,9 %) were men, with a median age of 69 (IQR 59-78) years. Values of LOS and CFR were calculated and analysed.\n\nResultsOverall CFR for the analysed period was 24,8 %, varying from 19,9 % in January to May 2021 to 33,8 % in November to December 2020. CFR was 18,9 % in general ward and 70,7 % in ICU. All ICU patients required intubation and mechanical ventilation, and forty-four (75,9 %) of them developed acute respiratory distress syndrome (ARDS). Average length of stay was 13,1 ({+/-} 7,1) days.\n\nConclusionCFR in the general ward in UCC was analogous to published outcomes, but higher in our ICU ward. It resulted from more rigorous ICU admittance criteria in UCC compared to other facilities, which corresponds with patients severe clinical condition and unfavourable prognosis. Heterogeneity of methods assessing initial clinical condition in different facilities makes a meaningful intercenter comparison challenging. In this study, we propose simple and transparent statistical and clinical parameters applicable in an intercenter analysis.\n\nO_LIWhat is already known on this topic - the outbreak of global pandemic caused by novel coronavirus SARS-CoV-2 has strained healthcare systems all over the world. Healthcare workers faced new challenges, as organisational, structural, and personal flaws were unearthed in the process. In subsequent waves the number of hospitalisations increased together with the death number in the ICUs. As we come to terms with a new disease, numerous studies reports, analyse and assess COVID-19 treatment outcomes\nC_LIO_LIWhat this study adds - COVID-19 treatment outcomes in ICU in our facility contrast with most of the published reports. We analyse the influence of some commonly omitted under-examined factors and propose simple and applicable parameters to compare results, such as CFR and LOS, enabling a meaningful intercenter comparison.\nC_LIO_LIHow this study might affect research, practice, or policy - inclusion of CFR and LOS in studies on COVID-19 would remove significant bias and enable more robust evaluation of therapeutic interventions and outcomes. In this study we also discuss heterogeneity of admission criteria and show how their influence on treatment outcomes.\nC_LI", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Nathan M Pajor", - "author_inst": "Division of Pulmonary Medicine, Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine" - }, - { - "author_name": "Vitaly Lorman", - "author_inst": "Applied Clinical Research Center, Children's Hospital of Philadelphia" - }, - { - "author_name": "Hanieh Razzaghi", - "author_inst": "Applied Clinical Research Center, Children's Hospital of Philadelphia" - }, - { - "author_name": "Abigail Case", - "author_inst": "Division of Physical Medicine & Rehabilitation, The Children's Hospital of Philadelphia" - }, - { - "author_name": "Priya Prahalad", - "author_inst": "Department of Pediatrics, Division of Endocrinology, Stanford University" - }, - { - "author_name": "Seuli Bose-Brill", - "author_inst": "Internal Medicine and Pediatrics Section, Division of General Internal Medicine, Department of Internal Medicine, Ohio State University College of Medicine and " - }, - { - "author_name": "Qiong Wu", - "author_inst": "Department of Biostatistics, Epidemiology and Informatics, the University of Pennsylvania" - }, - { - "author_name": "Yong Chen", - "author_inst": "Department of Biostatistics, Epidemiology and Informatics, the University of Pennsylvania" - }, - { - "author_name": "Jason P Block", - "author_inst": "Harvard Pilgrim Health Care Institute/Harvard Medical School" - }, - { - "author_name": "Payal B Patel", - "author_inst": "Department of Neurology, University of Washington" + "author_name": "Damian Krystian Palus", + "author_inst": "Medical University of Gdansk" }, { - "author_name": "Suchitra Rao", - "author_inst": "Department of Pediatrics, University of Colorado School of Medicine and Children's Hospital of Colorado" + "author_name": "Martyna Ewa Go\u0142\u0119biewska", + "author_inst": "Medical University of Gdansk" }, { - "author_name": "Asuncion Mejias", - "author_inst": "Division of Infectious Diseases, Department of Pediatrics, Nationwide Children's Hospital and The Ohio State University" + "author_name": "Olga Pi\u0105tek", + "author_inst": "Medical University of Gdansk" }, { - "author_name": "Deepika Thacker", - "author_inst": "Nemours Cardiac Center, Nemours Childrens Health" + "author_name": "Alan Majeranowski", + "author_inst": "Medical University of Gdansk, Department of Hematology and Transplantology" }, { - "author_name": "Ravi Jhaveri", - "author_inst": "Division of Infectious Diseases, Ann & Robert H. Lurie Children's Hospital of Chicago" + "author_name": "Rados\u0142aw Owczuk", + "author_inst": "Medical University of Gdansk, Department of Anesthesiology and Intensive Therapy" }, { - "author_name": "L Charles Bailey", - "author_inst": "Applied Clinical Research Center, Children's Hospital of Philadelphia" - }, - { - "author_name": "Christopher B Forrest", - "author_inst": "Applied Clinical Research Center, Children's Hospital of Philadelphia" + "author_name": "Krzysztof Kuziemski", + "author_inst": "Medical University of Gdansk, Department of Pulmonology and Allergology" }, { - "author_name": "Grace M Lee", - "author_inst": "Division of Infectious Diseases, Department of Pediatrics, Stanford University School of Medicine" + "author_name": "Tomasz Stefaniak", + "author_inst": "Medical University of Gdansk, Department of General, Endocrine and Transplant Surgery" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.07.07.22276915", @@ -274930,67 +275165,111 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2022.07.04.22277193", - "rel_title": "Reductions in stillbirths and preterm birth in COVID-19 vaccinated women: a multi-center cohort study of vaccination uptake and perinatal outcomes", + "rel_doi": "10.1101/2022.07.05.22277281", + "rel_title": "Efficacy and longevity of immune response to 3rd COVID-19 vaccine and effectiveness of a 4th dose in severely immunocompromised patients with cancer", "rel_date": "2022-07-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.04.22277193", - "rel_abs": "BackgroundCOVID-19 infection in pregnancy is associated with a higher risk of progression to severe disease, but vaccine uptake by pregnant women is hindered by persistent safety concerns. COVID-19 vaccination in pregnancy has been shown to reduce stillbirth, but its relationship with preterm birth is uncertain.\n\nObjectiveThe aim of this study was to investigate the sociodemographic characteristics associated with vaccine uptake in Melbourne, Australia, and to compare perinatal outcomes by vaccination status.\n\nStudy designRetrospective multicenter cohort study in Melbourne following the national recommendations for mRNA COVID-19 vaccination during pregnancy in June 2021. Routinely collected data from all 12 public maternity hospitals in Melbourne were extracted on births [≥] 20 weeks gestation from 1st July 2021 to 31 March 2022. Maternal sociodemographic characteristics were analyzed from the total birth cohort. Perinatal outcomes were compared between vaccinated and unvaccinated women for whom weeks 20-43 of gestation fell entirely within the 9-month data collection period. The primary outcome was the rate of congenital anomaly in singleton infants [≥] 20 weeks gestation among women vaccinated during pregnancy. Secondary perinatal outcomes including stillbirth, preterm birth (spontaneous and iatrogenic), birthweight [≤] 3rd centile, and newborn intensive care unit admissions were examined for singleton infants [≥] 24 weeks gestation without congenital anomalies. We calculated the adjusted odds ratio of congenital anomalies and perinatal outcomes among vaccinated versus unvaccinated women using inverse propensity score weighting regression adjustment with multiple covariates; p< 0.05 was considered statistically significant.\n\nResultsBirths from 32,536 women were analyzed: 17,365 (53.4%) were vaccinated and 15,171 (47.6%) were unvaccinated. Vaccinated women were significantly more likely to be older, nulliparous, non-smoking, not requiring an interpreter, of higher socioeconomic status, and vaccinated against pertussis and influenza. Vaccination status also varied by region of birth: compared with women born in Australia, women born in South and Eastern Europe, the Middle East, Africa and Oceania had lower adjusted odds of vaccination. There was no significant increase in the rate of congenital anomalies or birth weight [≤] 3rd centile in vaccinated women. Vaccinated women were significantly less like to have an infant with a major congenital anomaly compared with the unvaccinated group (2.4% vs 3.0%, aOR 0.72, 95%CI 0.56-0.94, p=0.02). This finding remained significant even when the analysis was restricted to women vaccinated before 20 weeks gestation. Vaccinated women had a significantly lower rate of stillbirth (0.2% vs 0.8%, aOR 0.18, 95%CI 0.09-0.37, P < 0.001. Vaccination was associated with a significant reduction in total preterm births < 37 weeks (5.1% vs 9.2%, aOR 0.60, 95% CI 0.51-0.71, p< 0.001), spontaneous preterm birth (2.4% vs 4.0%, aOR 0.73 95% CI 0.56-0.96, p=0.02) and iatrogenic preterm birth (2.7% vs 5.2%, aOR 0.52, 95%CI 0.41-0.65, p< 0.001).\n\nConclusionsCOVID-19 Vaccine coverage was significantly influenced by known social determinants of health, which is likely to influence the strong association between COVID-19 vaccination and lower risks of stillbirth and preterm birth. We did not observe any adverse impacts of vaccination on fetal growth or development.\n\nAT A GLANCEO_ST_ABSWhy was this study conducted?C_ST_ABS COVID-19 infection in pregnancy is associated with a higher risk of progression to severe disease, but vaccine uptake by pregnant women is hindered by persistent safety concerns. COVID-19 vaccination in pregnancy has been shown to reduce stillbirth, but its relationship with preterm birth is uncertain.\n Most of the published literature on COVID-19 vaccination in pregnancy have methodological limitations including fixed cohort bias and time-varying exposure.\n We conducted this multicenter study to provide robust evidence on mRNA COVID-19 vaccination and perinatal outcomes including congenital anomalies, stillbirth, and preterm birth.\n\n\nWhat are the key findings? The adjusted odds of stillbirth, preterm birth, and neonatal intensive care admission were significantly reduced among infants born to COVID-19 vaccinated women compared with unvaccinated women. COVID-19 vaccination during pregnancy was not associated with an increase in congenital anomalies.\n Our results conclusively demonstrate a significant reduction in both spontaneous and iatrogenic preterm birth for vaccinated women\n Vaccinated women were significantly more likely to be older, nulliparous, non-smoking, not requiring an interpreter, residing in a higher socioeconomic postcode, and vaccinated against pertussis and influenza. There were also significant differences in vaccination rates by region of birth.\n\n\nWhat does this study add to what is already known? Our analysis confirmed a strong relationship between the COVID-19 mRNA vaccine and lower preterm births and stillbirths\n In addition to its impact on reducing severe COVID-19 illness, vaccination may be a proxy for other biological and social determinants of health among our pregnant population.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.07.05.22277281", + "rel_abs": "Cancer patients show increased morbidity with COVID-19 and need effective immunization strategies. We demonstrate that a 3rd dose of COVID-19 vaccine leads to seroconversion in 57% of patients that were seronegative after primary vaccination. The immune response is durable as assessed by anti-S antibody titers, T-cell activity and neutralization activity against wild-type SARS-CoV2 and BA1.1.529 at 6 months of follow up. A subset of severely immunocompromised hematologic malignancy patients were unable to mount adequate immune response after the 3rd dose and were treated with a 4th dose in a prospective clinical trial which led to adequate immune-boost in 67% of patients. Low baseline IgM levels and CD19 counts were associated with inadequate seroconversion. Booster doses induced limited neutralization activity against the Omicron variant. These results indicate that vaccine booster-induced immunity is durable in cancer patients and additional doses can further stimulate immunity in a subset of hematologic malignancy patients.\n\nStatement of significanceWe demonstrate that a 3rd dose of vaccine leads to seroconversion in 57% of negative patients with durable immune responses at 6 months. A 4th dose of vaccine can seroconvert hematologic malignancy patients with higher baseline IgM and CD19 levels.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Lisa Hui", - "author_inst": "University of Melbourne" + "author_name": "Astha Thakkar", + "author_inst": "Montefiore Einstein Cancer Center" }, { - "author_name": "Melvin B Marzan", - "author_inst": "University of Melbourne" + "author_name": "Kith Pradhan", + "author_inst": "Albert Einstein College of Medicine" }, { - "author_name": "Daniel L Rolnik", - "author_inst": "Monash University" + "author_name": "Benjamin Duva", + "author_inst": "Montefiore Einstein Cancer Center" }, { - "author_name": "Stephanie Potenza", - "author_inst": "Mercy Hospital for Women" + "author_name": "Juan Manuel Carreno", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Natasha Pritchard", - "author_inst": "University of Melbourne" + "author_name": "Srabani Sahu", + "author_inst": "Albert Einstein College of Medicine" }, { - "author_name": "Joanne M Said", - "author_inst": "University of Melbourne" + "author_name": "Victor Thiruthuvanathan", + "author_inst": "Albert Einstein College of Medicine" }, { - "author_name": "Kirsten R Palmer", - "author_inst": "Monash University" + "author_name": "Sean T Campbell", + "author_inst": "Albert Einstein College of Medicine" }, { - "author_name": "Clare L Whitehead", - "author_inst": "University of Melbourne" + "author_name": "Sonia Gallego", + "author_inst": "Albert Einstein College of Medicine" }, { - "author_name": "Penelope M Sheehan", - "author_inst": "Monash University" + "author_name": "Tushar D Bhagat", + "author_inst": "Albert Einstein College of Medicine" }, { - "author_name": "Jolyon Ford", - "author_inst": "Peninsula Health" + "author_name": "Johanna Rivera", + "author_inst": "Albert Einstein College of Medicine" }, { - "author_name": "Ben W. Mol", - "author_inst": "Monash University" + "author_name": "Gaurav C Choudhary", + "author_inst": "Albert Einstein College of Medicine" }, { - "author_name": "Susan P Walker", - "author_inst": "University of Melbourne" + "author_name": "Raul Olea", + "author_inst": "Albert Einstein College of Medicine" + }, + { + "author_name": "Maite Sabalza", + "author_inst": "Euroimmun US" + }, + { + "author_name": "Lauren C Shapiro", + "author_inst": "Montefiore Einstein Cancer Center" + }, + { + "author_name": "Matthew Lee", + "author_inst": "Montefiore Einstein Cancer Center" + }, + { + "author_name": "Ryann Quinn", + "author_inst": "Montefiore Einstein Cancer Center" + }, + { + "author_name": "Ioannis Mantzaris", + "author_inst": "Montefiore Einstein Cancer Center" + }, + { + "author_name": "Edward Chu", + "author_inst": "Montefiore Einstein Cancer Center" + }, + { + "author_name": "Britta Will", + "author_inst": "Albert Einstein College of Medicine" + }, + { + "author_name": "Liise-anne Pirofski", + "author_inst": "Albert Einstein College of Medicine" + }, + { + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Amit Verma", + "author_inst": "Montefiore Einstein Cancer Center" + }, + { + "author_name": "Balazs Halmos", + "author_inst": "Montefiore Einstein Cancer Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "category": "oncology" }, { "rel_doi": "10.1101/2022.07.05.22277283", @@ -278196,35 +278475,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.07.02.495455", - "rel_title": "SARS-CoV-2 3CLpro mutations confer resistance to Paxlovid (nirmatrelvir/ritonavir) in a VSV-based, non-gain-of-function system", + "rel_doi": "10.1101/2022.06.28.22276997", + "rel_title": "Role of Error Catastrophe in Transmission Ability of Virus", "rel_date": "2022-07-04", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.07.02.495455", - "rel_abs": "Protease inhibitors are among the most powerful antiviral drugs. A first protease inhibitor against the SARS-CoV-2 protease 3CLpro, Paxlovid (nirmatrelvir / ritonavir), has recently been authorized by the U.S. FDA for emergency use (EUA 105 Pfizer Paxlovid). To find resistant mutants against the protease-inhibitor-component of Paxlovid, nirmatrelvir, we engineered a chimeric Vesicular Stomatitis Virus (VSV). By replacing an intergenic region, which is essential for separate gene transcription, with 3CLpro, this chimeric VSV became dependent on the protease to process two of its genes. We then applied selective pressure with nirmatrelvir to induce mutations. The effect of those mutants was confirmed by re-introduction in the 3CLpro and testing with a recently developed cellular assay. Furthermore, we found that mutations predicted by our method already exist in SARS-CoV-2 sequence depositions in NCBI and GISAID data bases. These may represent emerging resistant virus variants or a natural heterogeneity in the susceptibility to nirmatrelvir.\n\nOne-Sentence SummaryMutations of the main protease of SARS-CoV-2 result in resistance against licensed drugs such as Paxlovid (nirmatrelvir / ritonavir).\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=144 SRC=\"FIGDIR/small/495455v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (32K):\norg.highwire.dtl.DTLVardef@1d539d3org.highwire.dtl.DTLVardef@1c76534org.highwire.dtl.DTLVardef@1c54c4corg.highwire.dtl.DTLVardef@14355d_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 4, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.28.22276997", + "rel_abs": "The role played by \"error catastrophe\" is explicitly taken into account in the mathematical formulation to analyze the COVID-19 data. The idea is to combine the mathematical genetics formalism of the error catastrophe of mutations in the virus gene loci with the standard model of epidemics which lacks the explicit incorporation of the mutation effect on the spreading of the viruses. We apply the formalism to the case of SARS-CoV-2 virus. We assume the \"universality\" of the error catastrophe in the process of analyzing the data. This means that some basic parameter to describe the error catastrophe is independent of which group (country or city) we deal with. Concretely, we analyze the omicron data of South Africa and then analyze the cases of Japan using the same value of the basic parameter derived in the South Africa analysis. The result of the excellent fittings of the two data, one from South Africa and the other from Japan with the common values of genetic parameters, justifies our universality assumption of these parameters.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Emmanuel Heilmann", - "author_inst": "Medical University of Innsbruck" + "author_name": "Naoyuki Takahata", + "author_inst": "Sokendai" }, { - "author_name": "Francesco Costacurta", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Andre Volland", - "author_inst": "Medical University of Innsbruck" - }, - { - "author_name": "Dorothee von Laer", - "author_inst": "Medical University of Innsbruck" + "author_name": "Hirotaka Sugawara", + "author_inst": "KEK" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.07.01.22277143", @@ -279870,55 +280141,87 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.06.29.498191", - "rel_title": "Inhibitory effects of GT0918 on acute lung injury and the molecular mechanisms of anti-inflammatory response", + "rel_doi": "10.1101/2022.06.29.22277044", + "rel_title": "Severity of Omicron (B.1.1.529) and Delta (B.1.1.617.2) SARS-CoV-2 infection among hospitalised adults: a prospective cohort study", "rel_date": "2022-06-30", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.29.498191", - "rel_abs": "Coronavirus disease 2019 (COVID-19) has caused the public health crisis in the whole world. Anti-androgens block severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entry and protect against severe clinical COVID-19 outcomes. GT0918, a novel androgen receptor antagonist, accelerated viral clearance and increased recovery rate in outpatients by blocking SARS-CoV-2 infection though down-regulating ACE2 and TMPRSS2 expression. Further clinical study showed that GT0918 reduced mortality rate and shortened hospital stay in hospitalized COVID-19 patients. GT0918 also exhibits protective efficacy in severe COVID-19 patient in critical care. However, the mechanism of GT0918 treatment for severe COVID-19 disease is unknown. Here, we found GT0918 decreased the expression and secretion of proinflammatory cytokines through NF-{kappa}B signaling pathway. The acute lung injury induced by LPS or Poly(I:C) was also attenuated in GT0918-treated mice, compared with vehicle control group. Moreover, GT0918 elevated the NRF2 protein level but not mRNA transcription activity. GT0918 induced proinflammatory cytokines downregulation was partially dependent on NRF2. In conclusion, our data demonstrate that GT0918 reduced cytokine release and suppressed inflammatory responses through inhibiting NF-{kappa}B signaling and activating NRF2. GT0918 is not only effective for treatment of mild to moderate COVID-19 patients, but also a potential therapeutic drug for severe COVID-19 patients by reducing the risk of cytokine storm and acute respiratory distress syndrome.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.29.22277044", + "rel_abs": "BackgroundThere is an urgent public health need to evaluate disease severity in adults hospitalised with Delta and Omicron SARS-CoV-2 variant infections. However, limited data exist assessing severity of disease in adults hospitalised with Omicron SARS-CoV-2 infections, and to what extent patient-factors, including vaccination, age, frailty and pre-existing disease, affect variant-dependent disease severity.\n\nMethodsA prospective cohort study of adults ([≥]18 years of age) hospitalised with acute lower respiratory tract disease at acute care hospitals in Bristol, UK conducted over 10-months. Delta or Omicron SARS-CoV-2 infection was defined by positive SARS-CoV-2 PCR and variant identification or inferred by dominant circulating variant. We constructed adjusted regression analyses to assess disease severity using three different measures: FiO2 >28% (fraction inspired oxygen), World Health Organization (WHO) outcome score >5 (assessing need for ventilatory support), and hospital length of stay (LOS) >3 days following admission for Omicron or Delta infection.\n\nFindingsIndependent of other variables, including vaccination, Omicron variant infection in hospitalised adults was associated with lower severity than Delta. Risk reductions were 58%, 67%, and 16% for supplementary oxygen with >28% FiO2 [Relative Risk (RR)=0{middle dot}42 (95%CI: 0{middle dot}34-0{middle dot}52), P<0.001], WHO outcome score >5 [RR=0{middle dot}33 (95%CI: 0{middle dot}21-0{middle dot}50), P<0.001], and to have had a LOS>3 days [RR=0{middle dot}84 (95%CI: 0{middle dot}76-0{middle dot}92), P<0.001]. Younger age and vaccination with two or three doses were also independently associated with lower COVID-19 severity.\n\nInterpretationWe provide reassuring evidence that Omicron infection results in less serious adverse outcomes than Delta in hospitalised patients. Despite lower severity relative to Delta, Omicron infection still resulted in substantial patient and public health burden and an increased admission rate of older patients with Omicron which counteracts some of the benefit arising from less severe disease.\n\nFundingAvonCAP is an investigator-led project funded under a collaborative agreement by Pfizer.\n\nRESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSThe burden of COVID-19 on hospital services is determined by the prevalence and severity of SARS-CoV-2 variants, and modified by individual factors such as age, frailty and vaccination status. Real world data suggest that vaccine effectiveness is lower and may wane faster over time against symptomatic disease with Omicron (B.1.1.529) than with Delta (B.1.617.2) SARS-CoV-2 variant. However, numbers of hospitalisations as a case proportion during the Omicron wave have been considerably lower than previous waves. Several reports have compared the risk of hospitalisation or severe disease based on SARS-CoV-2 variant, some suggesting that Omicron is probably less severe than Delta in vaccinated and unvaccinated individuals.\n\nAdded value of this studyThis study provides robust data assessing the relative severity of Delta and Omicron SARS-CoV-2 variants in patients admitted to hospital, including the first analysis assessing risk for any positive pressure ventilatory support, as well as risk of supplementary oxygen requirement and extended hospital admission, that may guide resource planning in hospitals. We found evidence that infection with Omicron was associated with a milder clinical course following hospital admission than that caused by Delta and that vaccination was independently associated with lower in-hospital disease severity using these three separate severity measures. Specifically, compared to Delta, Omicron-related hospitalizations were 58%, 67%, and 16% less likely to require high flow oxygen >28% FiO2, positive pressure ventilatory support or more critical care, and to have a hospital stay lasting more than three days, respectively.\n\nThis study reports the considerable morbidity resulting from Omicron infection, with 18% of Omicron admissions requiring oxygen supplementation FiO2 >28%, 6% requiring positive pressure ventilation, 62% needing hospitalization [≥]four days, and 4% in-hospital mortality. In determining the reduced requirement of increased oxygen requirement and total positive pressure requirement, including non-invasive ventilation, this analysis should contribute to future hospital care and service planning assessments.\n\nImplications of all the available evidenceThe risk of severe outcomes following SARS-CoV-2 infection is substantially lower for Omicron than for Delta, with greater reductions for more severe disease outcomes. Significant variation in risk occurs with age and vaccination status, with older and unvaccinated individuals remaining at particular risk of adverse outcome. These results highlight the importance of maintaining high levels of vaccine coverage in patient groups at risk of severe disease.\n\nThe impact of lower severity Omicron-related hospitalization must be balanced against increased transmissibility and overall higher numbers of infections with this variant and there remains a substantial patient and public health burden. The increased admission rate of older patients with Omicron counteracts some of the benefit arising from less severe disease. Despite the risk reduction in high level oxygen supplementation requirement and high dependency care with Omicron compared to earlier variants at the individual level, healthcare systems could still be overwhelmed.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Xiaodan Hou", - "author_inst": "Kintor Pharmaceutical Limited" + "author_name": "Catherine Hyams", + "author_inst": "University of Bristol" }, { - "author_name": "Honghua Yan", - "author_inst": "Kintor Pharmaceutical Limited" + "author_name": "Robert Challen", + "author_inst": "University of Bristol" }, { - "author_name": "Ao Wang", - "author_inst": "Kintor Pharmaceutical Limited" + "author_name": "Jennifer Nguyen", + "author_inst": "Pfizer Inc" }, { - "author_name": "Cong Liu", - "author_inst": "Kintor Pharmaceutical Limited" + "author_name": "Elizabeth Begier", + "author_inst": "Pfizer Inc" }, { - "author_name": "Qianxiang Zhou", - "author_inst": "Kintor Pharmaceutical Limited" + "author_name": "Jo Southern", + "author_inst": "Pfizer Inc" }, { - "author_name": "Liandong Ma", - "author_inst": "Kintor Pharmaceutical Limited" + "author_name": "Jade King", + "author_inst": "Bristol Vaccine Centre" }, { - "author_name": "Jie Chen", - "author_inst": "Kintor Pharmaceutical Limited" + "author_name": "Anna Morley", + "author_inst": "Academic Respiratory Unit" }, { - "author_name": "Zhihua Ren", - "author_inst": "Kintor Pharmaceutical Limited" + "author_name": "Jane Kinney", + "author_inst": "Bristol Vaccine Centre" + }, + { + "author_name": "Madeleine Clout", + "author_inst": "Bristol Vaccine Centre" + }, + { + "author_name": "Jennifer Oliver", + "author_inst": "Bristol Vaccine Centre" }, { - "author_name": "Youzhi Tong", - "author_inst": "Kintor Pharmaceutical Limited" + "author_name": "Gillian Ellsbury", + "author_inst": "Pfizer Inc" + }, + { + "author_name": "Nick Maskell", + "author_inst": "Academic Respiratory Unit" + }, + { + "author_name": "Luis Jodar", + "author_inst": "Pfizer Inc" + }, + { + "author_name": "Bradford Gessner", + "author_inst": "Pfizer Inc" + }, + { + "author_name": "John McLaughlin", + "author_inst": "Pfizer Inc" + }, + { + "author_name": "Leon Danon", + "author_inst": "University of Bristol" + }, + { + "author_name": "Adam Finn", + "author_inst": "University of Bristol" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "cell biology" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.06.29.22277060", @@ -281588,55 +281891,223 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.28.22276851", - "rel_title": "The COVID-19 pandemic sparked off a large-scale outbreak of carbapenem-resistant Acinetobacter baumannii from the endemic strains of an Italian hospital", + "rel_doi": "10.1101/2022.06.28.22276983", + "rel_title": "Outcomes of laboratory-confirmed SARS-CoV-2 infection during resurgence driven by Omicron lineages BA.4 and BA.5 compared with previous waves in the Western Cape Province, South Africa", "rel_date": "2022-06-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.28.22276851", - "rel_abs": "Acinetobacter baumannii is a nosocomial pathogen that poses a serious threat due to the rise of incidence of multidrug resistant (MDR) strains. During the COVID-19 pandemic, MDR A.baumannii clones have caused several outbreaks worldwide. Here we describe a detailed investigation of an MDR A. baumannii outbreak that occurred at Fondazione IRCCS Policlinico San Matteo (Pavia, Italy). A total of 96 A. baumannii strains, isolated between January and July 2020 from 41 inpatients (both SARS-CoV-2 positive and negative) in different wards, were characterized by phenotypic and genomic analyses combining Illumina and Nanopore sequencing. Antibiotic susceptibility testing revealed that all isolates were resistant to carbapenems and the sequence analysis attributed this to the carbapenemase gene blaOXA-23. Screening of virulence factors unveiled that all strains carried determinants for biofilm formation, while plasmid analysis revealed the presence of two plasmids, one of which was a 100kbp long and encoded a phage sequence.\n\nA core genome-based phylogeny was inferred to integrate outbreak strain genomes with background genomes from public databases and from the local surveillance program. All strains belonged to the globally disseminated ST2 clone and were mainly divided into two clades. Isolates from the outbreak clustered with surveillance isolates from 2019, suggesting that the outbreak was caused by two strains that were already circulating in the hospital before the start of the pandemic. The intensive spread of A. baumannii in the hospital was enhanced by the extreme emergency situation of the first COVID-19 pandemic wave that resulted in minor attention to infection prevention and control practices.\n\nImportanceThe COVID-19 pandemic, especially during the first wave, posed a great challenge to the hospital management and generally promoted nosocomial pathogen dissemination. Multidrug resistant (MDR) A. baumannii can easily spread and persist for a long time on surfaces, causing outbreaks in healthcare settings. Infection prevention and control practices, epidemiological surveillance and microbiological screening are fundamental in order to control such outbreaks.\n\nHere, we sequenced the genomes of 96 isolates from an outbreak of MDR A. baumannii strains using both short- and long-read technology in order to reconstruct the outbreak events in fine detail. The sequence data demonstrated that two endemic clones of MDR A. baumannii were the source of this large hospital outbreak during the first COVID-19 pandemic wave, confirming the effect of COVID-19 emergency disrupting the protection provided by the use of the standard prevention procedures.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.28.22276983", + "rel_abs": "ObjectiveWe aimed to compare clinical severity of Omicron BA.4/BA.5 infection with BA.1 and earlier variant infections among laboratory-confirmed SARS-CoV-2 cases in the Western Cape, South Africa, using timing of infection to infer the lineage/variant causing infection.\n\nMethodsWe included public sector patients aged [≥]20 years with laboratory-confirmed COVID-19 between 1-21 May 2022 (BA.4/BA.5 wave) and equivalent prior wave periods. We compared the risk between waves of (i) death and (ii) severe hospitalization/death (all within 21 days of diagnosis) using Cox regression adjusted for demographics, comorbidities, admission pressure, vaccination and prior infection.\n\nResultsAmong 3,793 patients from the BA.4/BA.5 wave and 190,836 patients from previous waves the risk of severe hospitalization/death was similar in the BA.4/BA.5 and BA.1 waves (adjusted hazard ratio [aHR] 1.12; 95% confidence interval [CI] 0.93; 1.34). Both Omicron waves had lower risk of severe outcomes than previous waves. Prior infection (aHR 0.29, 95% CI 0.24; 0.36) and vaccination (aHR 0.17; 95% CI 0.07; 0.40 for boosted vs. no vaccine) were protective.\n\nConclusionDisease severity was similar amongst diagnosed COVID-19 cases in the BA.4/BA.5 and BA.1 periods in the context of growing immunity against SARS-CoV-2 due to prior infection and vaccination, both of which were strongly protective.", + "rel_num_authors": 51, "rel_authors": [ { - "author_name": "Greta Petazzoni", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" + "author_name": "Mary-Ann Davies", + "author_inst": "Health Intelligence, Western Cape Government: Health & Wellness, South Africa; Centre for Infectious Disease Epidemiology and Research and Division of Public He" }, { - "author_name": "Greta Bellinzona", - "author_inst": "Universit\u00e0 degli Studi di Pavia" + "author_name": "Erna Morden", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa; Division of Public Health Medicine, School of Public Health and Family Medicine" }, { - "author_name": "Cristina Merla", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" + "author_name": "Petro Rosseau", + "author_inst": "National Department of Health" }, { - "author_name": "Marta Corbella", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" + "author_name": "Juanita Arendse", + "author_inst": "Western Cape Department of Health and Wellness" }, { - "author_name": "\u00d8rjan Samuelsen", - "author_inst": "University Hospital of North Norway" + "author_name": "Jamy-Lee Bam", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa" }, { - "author_name": "Jukka Corander", - "author_inst": "University of Oslo" + "author_name": "Linda Boloko", + "author_inst": "Groote Schuur Hospital, Western Cape Government: Health and Wellness, South Africa; Division of Infectious Diseases and HIV Medicine, Department of Medicine, U" }, { - "author_name": "Davide Sassera", - "author_inst": "Universit\u00e0 degli Studi di Pavia" + "author_name": "Keith Cloete", + "author_inst": "Western Cape Department of Health and Wellness" }, { - "author_name": "Stefano Gaiarsa", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" + "author_name": "Cheryl Cohen", + "author_inst": "National Institute for Communicable Diseases, National Health Laboratory Service, South Africa School of Public Health, Faculty of Health Sciences, University o" }, { - "author_name": "Patrizia Cambieri", - "author_inst": "Fondazione IRCCS Policlinico San Matteo" + "author_name": "Nicole Chetty", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa Centre for Infectious Disease Epidemiology and Research, School of Public Health" + }, + { + "author_name": "Pierre Dane", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa Centre for Infectious Disease Epidemiology and Research, School of Public Health" + }, + { + "author_name": "Alexa Heekes", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa Centre for Infectious Disease Epidemiology and Research, School of Public Health" + }, + { + "author_name": "Nei-Yuan Hsiao", + "author_inst": "Division of Medical Virology, University of Cape Town, Cape Town, Western Cape, South Africa National Health Laboratory Service, South Africa" + }, + { + "author_name": "Mehreen Hunter", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa; Division of Public Health Medicine, School of Public Health and Family Medicine" + }, + { + "author_name": "Hannah Hussey", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa; Division of Public Health Medicine, School of Public Health and Family Medicine" + }, + { + "author_name": "Theuns Jacobs", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa" + }, + { + "author_name": "Waasila Jassat", + "author_inst": "National Institute for Communicable Diseases, National Health Laboratory Service, South Africa" + }, + { + "author_name": "Saadiq Kariem", + "author_inst": "Western Cape Department of Health and Wellness" + }, + { + "author_name": "Reshma Kassanjee", + "author_inst": "Centre for Infectious Disease Epidemiology and Research, School of Public Health and Family Medicine, University of Cape Town, South Africa" + }, + { + "author_name": "Inneke Laenen", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa; Division of Health Systems and Public Health, Department of Global Health, Facu" + }, + { + "author_name": "Sue Le Roux", + "author_inst": "Western Cape Government: Health and Wellness, South Africa; Karl Bremer Hospital, Western Cape Government: Health" + }, + { + "author_name": "Richard Lessells", + "author_inst": "KwaZulu-Natal Research, Innovation & Sequencing Platform, University of KwaZulu-Natal, Durban, South Africa" + }, + { + "author_name": "Hassan Mahomed", + "author_inst": "Metro Health Services, Western Cape Government: Health Division of Health Systems and Public Health, Department of Global Health, Faculty of Medicine and Health" + }, + { + "author_name": "Deborah Maughan", + "author_inst": "Groote Schuur Hospital, Western Cape Government: Health and Wellness, South Africa; Department of Medicine, University of Cape Town" + }, + { + "author_name": "Graeme Meintjes", + "author_inst": "Groote Schuur Hospital, Western Cape Government: Health and Wellness, South Africa; Department of Medicine, University of Cape Town" + }, + { + "author_name": "Marc Mendelson", + "author_inst": "Groote Schuur Hospital, Western Cape Government: Health and Wellness, South Africa; Division of Infectious Diseases and HIV Medicine, Department of Medicine, U" + }, + { + "author_name": "Ayanda Mnguni", + "author_inst": "Khayelitsha District Hospital, Western Cape Government: Health" + }, + { + "author_name": "Melvin Moodley", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa" + }, + { + "author_name": "Katy Murie", + "author_inst": "Western Cape Government: Health and Wellness, South Africa; Metro Health Services, Western Cape Government: Health" + }, + { + "author_name": "Jonathan Naude", + "author_inst": "Mitchells Plain Hospital, Western Cape Government: Health" + }, + { + "author_name": "Ntobeko A.B. Ntusi", + "author_inst": "Groote Schuur Hospital, Western Cape Government: Health and Wellness, South Africa; Department of Medicine, University of Cape Town" + }, + { + "author_name": "Masudah Paleker", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa; Western Cape Government: Health and Wellness, South Africa" + }, + { + "author_name": "Arifa Parker", + "author_inst": "Tygerberg Hospital, Western Cape Government: Health Division of Infectious Diseases, Department of Medicine, Stellenbosch University, South Africa" + }, + { + "author_name": "David Pienaar", + "author_inst": "Rural Health Services, Western Cape Government: Health and Wellness, South Africa" + }, + { + "author_name": "Wolfgang Preiser", + "author_inst": "National Health Laboratory Service, South Africa; Division of Medical Virology, University of Stellenbosch, South Africa" + }, + { + "author_name": "Hans Prozesky", + "author_inst": "Tygerberg Hospital, Western Cape Government: Health Division of Infectious Diseases, Department of Medicine, Stellenbosch University, South Africa" + }, + { + "author_name": "Peter Raubenheimer", + "author_inst": "Groote Schuur Hospital, Western Cape Government: Health and Wellness, South Africa; Department of Medicine, University of Cape Town" + }, + { + "author_name": "Liezel Rossouw", + "author_inst": "Western Cape Government: Health and Wellness, South Africa" + }, + { + "author_name": "Neshaad Schreuder", + "author_inst": "Tygerberg Hospital, Western Cape Government: Health and Wellness; Division of General Medicine, Department of Medicine, Stellenbosch University, South Africa" + }, + { + "author_name": "Barry Smith", + "author_inst": "Karl Bremer Hospital, Western Cape Government: Health; Western Cape Government: Health and Wellness, South Africa" + }, + { + "author_name": "Mariette Smith", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness, South Africa Centre for Infectious Disease Epidemiology and Research, School of Public Health" + }, + { + "author_name": "Wesley Solomon", + "author_inst": "National Department of Health, South Africa" + }, + { + "author_name": "Greg Symons", + "author_inst": "Groote Schuur Hospital, Western Cape Government: Health and Wellness, South Africa; Department of Medicine, University of Cape Town" + }, + { + "author_name": "Jantjie Taljaard", + "author_inst": "Tygerberg Hospital, Western Cape Government: Health Division of Infectious Diseases, Department of Medicine, Stellenbosch University, South Africa" + }, + { + "author_name": "Sean Wasserman", + "author_inst": "Groote Schuur Hospital, Western Cape Government: Health and Wellness, South Africa Division of Infectious Diseases and HIV Medicine, Department of Medicine, Un" + }, + { + "author_name": "Robert J. Wilkinson", + "author_inst": "The Francis Crick Institute, UK; Department of Infectious Diseases, Imperial College, UK; Wellcome Centre for Infectious Disease Research in Africa, Institute o" + }, + { + "author_name": "Milani Wolmarans", + "author_inst": "National Department of Health, South Africa" + }, + { + "author_name": "Nicole Wolter", + "author_inst": "National Institute for Communicable Diseases, National Health Laboratory Service, South Africa; School of Pathology, Faculty of Health Sciences, University of W" + }, + { + "author_name": "Andrew Boulle", + "author_inst": "Health Intelligence, Western Cape Government: Health and Wellness; Centre for Infectious Disease Epidemiology and Research & Division of Public Health Medicine," + }, + { + "author_name": "- Western Cape Department of Health and Wellness", + "author_inst": "" + }, + { + "author_name": "- National Departments of Health", + "author_inst": "" + }, + { + "author_name": "- National Institute for Communicable Diseases in South Africa", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.06.27.497816", @@ -283114,39 +283585,55 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2022.06.27.22276736", - "rel_title": "An Economic Evaluation of a virtual Covid Ward in Leicester, Leicestershire, and Rutland", + "rel_doi": "10.1101/2022.06.27.22276960", + "rel_title": "Telemedicine Use Among People with HIV in 2021: The Hybrid-Care Environment", "rel_date": "2022-06-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.27.22276736", - "rel_abs": "ObjectiveThe objective of this study was to demonstrate the impact of a virtual Covid--19 ward on NHS resource use.\n\nMethodsDifferent methods were used to derive comparators for the observational data on acute length of stay versus the actual lengths of stay of 310 patients on acute wards and differences estimated. The resource use associated with delivering care in the virtual ward were collected on an ongoing basis.\n\nResultsThe virtual ward delivered estimated health care system savings of 1,103 bed days, {pound}529,719 in net financial savings across two key groups of patients; those who had been on oxygen and required weaning off it while within the virtual ward and those not requiring oxygen therapy with less severe acute Covid disease. The costs of the intervention were 9.7% of the estimated gross savings and the mean net saving per patient was {pound}1,709 in the base case without including the savings associated with a likely reduction in re-admissions. The 30-day re-admission rate was 2.9%, which was substantially beneath alternative comparative data. The mean cost of the intervention was {pound}184.38 per patient.\n\nConclusionThe virtual ward delivered significant financial savings in both groups of patients, did so with a high degree of confidence, whilst doing so at a very low absolute and relative cost.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.27.22276960", + "rel_abs": "BackgroundTelemedicine use for the care of people with HIV (PWH) was widely expanded during the COVID-19 pandemic. During 2021, as on-site care was re-introduced, care was delivered through a mixture of in-person and telemedicine. We studied how different patient populations used telemedicine in this hybrid-care environment.\n\nMethodsUsing observational data from patients enrolled in the Johns Hopkins HIV Clinical Cohort, we analyzed all in-person and telemedicine HIV primary care visits completed in an HIV clinic from January 1st, 2021 to December 30th, 2021. We used log-binomial regression models to investigate the association between patient characteristics and the probability of completing a telemedicine versus in-person visit. A secondary analysis of telemedicine visits investigated the probably of completing a video versus telephone visit.\n\nResultsA total of 5,518 visits were completed by 1,884 patients; 4,282 (77.6%) visits were in-person, 800 (14.5%) by phone, and 436 (7.9%) by video. The relative risk (RR) of completing telemedicine vs. in-person visits was 0.65 (95% Confidence Interval (CI): 0.47, 0.91) for patients age 65+ vs. age 20-39; 0.84 (95% CI: 0.72, 0.98) for males vs. females; 0.81 (95% CI: 0.66, 0.99) for Black vs. white patients; 0.62 (95% CI: 0.49, 0.79) for patients in the highest vs. lowest quartile of Area Deprivation Index; and 1.52 (95% CI: 1.26, 1.84) for patients >15 miles vs. <5 miles from clinic.\n\nConclusionsIn the second year of the pandemic, overall in-person care was utilized more than telemedicine, and significant differences persist across subgroups in telemedicine uptake.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jim Swift", - "author_inst": "Spirit Health Group" + "author_name": "Walid El-Nahal", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Noel O'Kelly", - "author_inst": "Spirit Health" + "author_name": "Geetanjali Chander", + "author_inst": "University of Washington School of Medicine" }, { - "author_name": "Chris Barker", - "author_inst": "Spirit Health" + "author_name": "Joyce L. Jones", + "author_inst": "Johns Hopkins School of Medicine" }, { - "author_name": "Alex Woodward", - "author_inst": "Leicestershire Partnership Trust" + "author_name": "Anthony T. Fojo", + "author_inst": "Johns Hopkins School of Medicine" }, { - "author_name": "Sudip Ghosh", - "author_inst": "De Montford University & Leicestershire Partnership Trust" + "author_name": "Jeanne C. Keruly", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Yukari C. Manabe", + "author_inst": "Johns Hopkins School of Medicine" + }, + { + "author_name": "Richard D. Moore", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Kelly A. Gebo", + "author_inst": "Johns Hopkins University School of Medicine" + }, + { + "author_name": "Catherine R. Lesko", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "hiv aids" }, { "rel_doi": "10.1101/2022.06.27.22276959", @@ -284848,179 +285335,79 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.22.22276362", - "rel_title": "Immune Correlates Analysis of the PREVENT-19 COVID-19 Vaccine Efficacy Clinical Trial", + "rel_doi": "10.1101/2022.06.22.22276755", + "rel_title": "New, fast, and precise method of COVID-19 detection in nasopharyngeal and tracheal aspirate samples combining optical spectroscopy and machine learning", "rel_date": "2022-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.22.22276362", - "rel_abs": "In the randomized, placebo-controlled PREVENT-19 phase 3 trial conducted in the U.S. and Mexico of the NVX-CoV2373 adjuvanted, recombinant spike protein nanoparticle vaccine, anti-spike binding IgG concentration (spike IgG) and pseudovirus 50% neutralizing antibody titer (nAb ID50) measured two weeks after two doses were assessed as correlates of risk and as correlates of protection against PCR-confirmed symptomatic SARS-CoV-2 infection (COVID- 19). These immune correlates analyses were conducted in the U.S. cohort of baseline SARS- CoV-2 negative per-protocol participants using a case-cohort design that measured the antibody markers from all 12 vaccine recipient breakthrough COVID-19 cases starting 7 days post antibody measurement and from 639 vaccine recipient non-cases (Mexico was excluded due to zero breakthrough cases with the efficacy data cut-off date April 19, 2021). In vaccine recipients, the baseline risk factor-adjusted hazard ratio of COVID-19 was 0.36 (95% CI: 0.20, 0.63), p<0.001 (adjusted p-0.005) per 10-fold increase in IgG spike concentration and 0.39 (0.19, 0.82), p=0.013 (adjusted p=0.030) per 10-fold increase in nAb ID50 titer. At spike IgG concentration 100, 1000, and 6934 binding antibody units/ml (100 is the 3rd percentile, 6934 is the 97.5th percentile), vaccine efficacy to reduce the probability of acquiring COVID-19 at 59 days post marker measurement was 65.5% (95% CI: 23.0%, 90.8%), 87.7% (77.7%, 94.4%), and 94.8% (88.0%, 97.9%), respectively. At nAb ID50 titers of 50, 100, 1000, and 7230 IU50/ml (50 is the 5th percentile, 7230 the 97.5th percentile), these estimates were 75.7% (49.8%, 93.2%), 81.7% (66.3%, 93.2%), 92.8% (85.1%, 97.4%) and 96.8% (88.3%, 99.3%). The same two antibody markers were assessed as immune correlates via the same study design and statistical analysis in the mRNA-1273 phase 3 COVE trial (except in COVE the markers were measured four weeks post dose two). Spike IgG levels were slightly lower and nAb ID50 titers slightly higher after NVX-CoV2373 than after mRNA-1273 vaccination. The strength of the nAb ID50 correlate was similar between the trials, whereas the spike IgG antibodies appeared to correlate more strongly with NVX-CoV2373 in PREVENT-19, as quantified by the hazard ratio and the degree of change in vaccine efficacy across antibody levels. However, the relatively few breakthrough cases in PREVENT-19 limited the ability to infer a stronger correlate. The conclusion is that both markers were consistent correlates of protection for the two vaccines, supporting potential cross-vaccine platform applications of these markers for guiding decisions about vaccine approval and use.", - "rel_num_authors": 40, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.22.22276755", + "rel_abs": "Fast, precise, and low-cost diagnostic testing to identify persons infected with SARS- CoV-2 virus is pivotal to control the global pandemic of COVID-19 that began in late 2019. The gold standard method of diagnostic recommended is the RT-qPCR test. However, this method is not universally available, and is time-consuming and requires specialized personnel, as well as sophisticated laboratories. Currently, machine learning is a useful predictive tool for biomedical applications, being able to classify data from diverse nature. Relying on the artificial intelligence learning process, spectroscopic data from nasopharyngeal swab and tracheal aspirate samples can be used to leverage characteristic patterns and nuances in healthy and infected body fluids, which allows to identify infection regardless of symptoms or any other clinical or laboratorial tests. Hence, when new measurements are performed on samples of unknown status and the corresponding data is submitted to such an algorithm, it will be possible to predict whether the source individual is infected or not. This work presents a new methodology for rapid and precise label-free diagnosing of SARS-CoV-2 infection in clinical samples, which combines spectroscopic data acquisition and analysis via artificial intelligence algorithms. Our results show an accuracy of 85% for detection of SARS-CoV-2 in nasopharyngeal swab samples collected from asymptomatic patients or with mild symptoms, as well as an accuracy of 97% in tracheal aspirate samples collected from critically ill COVID-19 patients under mechanical ventilation. Moreover, the acquisition and processing of the information is fast, simple, and cheaper than traditional approaches, suggesting this methodology as a promising tool for biomedical diagnosis vis-a-vis the emerging and re-emerging viral SARS-CoV-2 variant threats in the future.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Youyi Fong", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Yunda Huang", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "David Benkeser", - "author_inst": "Emory" - }, - { - "author_name": "Lindsay N. Carpp", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Germ\u00e1n \u00c1\u00f1ez", - "author_inst": "Novavax, Inc." - }, - { - "author_name": "Wayne Woo", - "author_inst": "Novavax, Inc." - }, - { - "author_name": "Alice McGarry", - "author_inst": "Novavax, Inc." - }, - { - "author_name": "Lisa M. Dunkle", - "author_inst": "Novavax, Inc." - }, - { - "author_name": "Iksung Cho", - "author_inst": "Novavax, Inc." - }, - { - "author_name": "Christopher R. Houchens", - "author_inst": "Biomedical Advanced Research and Development Authority" - }, - { - "author_name": "Karen Martins", - "author_inst": "Biomedical Advanced Research and Development Authority" - }, - { - "author_name": "Lakshmi Jayashankar", - "author_inst": "Biomedical Advanced Research and Development Authority" - }, - { - "author_name": "Flora Castellino", - "author_inst": "Biomedical Advanced Research and Development Authority" - }, - { - "author_name": "Christos Petropoulos", - "author_inst": "Monogram Biosciences" - }, - { - "author_name": "Andrew Leith", - "author_inst": "Nexelis" - }, - { - "author_name": "Deanne Haugaard", - "author_inst": "Nexelis" - }, - { - "author_name": "Bill Webb", - "author_inst": "Nexelis" - }, - { - "author_name": "Yiwen Lu", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Chenchen Yu", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Bhavesh Borate", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Lars W. P. van der Laan", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Nima S. Hejazi", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "April Kaur Randhawa", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Michele P. Andrasik", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "James G. Kublin", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Julia Hutter", - "author_inst": "Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases" + "author_name": "Denny M. Ceccon", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Maryam Keshtkar-Jahromi", - "author_inst": "Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases" + "author_name": "Paulo Henrique R. Amaral", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Tatiana H. Beresnev", - "author_inst": "Division of Microbiology and Infectious Diseases, National Institute of Allergy and Infectious Diseases" + "author_name": "Lidia M. Andrade", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Lawrence Corey", - "author_inst": "Fred Hutchinson Cancer Center" + "author_name": "Maria I. N. da Silva", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Kathleen M. Neuzil", - "author_inst": "Center for Vaccine Development and Global Health, University of Maryland School of Medicine" + "author_name": "Luis A. F. Andrade", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Dean Follmann", - "author_inst": "Biostatistics Research Branch, National Institute of Allergy and Infectious Diseases, National Institutes of Health" + "author_name": "Thais F.S. Moraes", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Julie A. Ake", - "author_inst": "U.S. Military HIV Research Program, Walter Reed Army Institute of Research" + "author_name": "Flavia F. Bagno", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Cynthia L. Gay", - "author_inst": "University of North Carolina School of Medicine" + "author_name": "Raissa P. Rocha", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Karen L. Kotloff", - "author_inst": "Center for Vaccine Development and Global Health, University of Maryland School of Medicine" + "author_name": "Daisymara Priscila de Almeida Marques", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Richard A. Koup", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" + "author_name": "Geovane M. Ferreira", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Ruben O. Donis", - "author_inst": "Biomedical Advanced Research and Development Authority" + "author_name": "Alice Aparecido Lourenco", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "Peter B. Gilbert", - "author_inst": "Fred Hutchinson Cancer Center" + "author_name": "Agata Lopes Ribeiro", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "- Immune Assays Team", - "author_inst": "Immune Assays Team" + "author_name": "Jordana G. A. Coelho-dos-Reis", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "- Coronavirus Vaccine Prevention Network (CoVPN)/2019nCoV-301 Principal Investigators and Study Team", - "author_inst": "" + "author_name": "Flavio G da Fonseca", + "author_inst": "Universidade Federal de Minas Gerais" }, { - "author_name": "- United States Government (USG)/CoVPN Biostatistics Team", - "author_inst": "" + "author_name": "Juan C. Gonzalez", + "author_inst": "Universidade Federal de Minas Gerais" } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.06.23.22276797", @@ -286806,83 +287193,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.06.21.497047", - "rel_title": "Within-host evolutionary dynamics and tissue compartmentalization during acute SARS-CoV-2 infection", + "rel_doi": "10.1101/2022.06.21.22276712", + "rel_title": "U.S. state-level COVID-19 transmission insights from a mechanistic mobility-incidence model", "rel_date": "2022-06-22", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.21.497047", - "rel_abs": "The global evolution of SARS-CoV-2 depends in part upon the evolutionary dynamics within individual hosts with varying immune histories. To characterize the within-host evolution of acute SARS-CoV-2 infection, we deep sequenced saliva and nasal samples collected daily from immune and unvaccinated individuals early during infection. We show that longitudinal sampling facilitates high-confidence genetic variant detection and reveals evolutionary dynamics missed by less-frequent sampling strategies. Within-host dynamics in both naive and immune individuals appeared largely stochastic; however, we identified clear mutational hotspots within the viral genome, consistent with selection and differing between naive and immune individuals. In rare cases, minor genetic variants emerged to frequencies sufficient for forward transmission. Finally, we detected significant genetic compartmentalization of virus between saliva and nasal swab sample sites in many individuals. Altogether, these data provide a high-resolution profile of within-host SARS-CoV-2 evolutionary dynamics.", - "rel_num_authors": 16, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.21.22276712", + "rel_abs": "SO_SCPLOWUMMARYC_SCPLOWO_ST_ABSBackgroundC_ST_ABSThroughout the COVID-19 pandemic, human mobility has played a central role in shaping disease transmission. In this study, we develop a mechanistic model to calculate disease incidence from commercially-available US mobility data over the course of 2020. We use it to study, at the US state level, the lag between infection and case report. We examine the evolution of per-contact transmission probability, and its dependence on mean air temperature. Finally, we evaluate the potential of the model to produce short-term incidence forecasts from mobility data.\n\nMethodsWe develop a mechanistic model that relates COVID-19 incidence to time series contact index (CCI) data collected by mobility data vendor Cuebiq. From this, we perform maximum-likelihood estimates of the transmission probability per CCI event. Finally, we retrospectively conduct forecasts from multiple dates in 2020 forward.\n\nFindingsAcross US states, we find a median lag of 19 days between transmission and case report. We find that the median transmission probability from May onward was about 20% lower than it was during March and April. We find a moderate, statistically significant negative correlation between mean state temperature and transmission probability, r = - .57, N = 49, p = 2 x 10-5. We conclude that for short-range forecasting, CCI data would likely have performed best overall during the first few months of the pandemic.\n\nInterpretationOur results are consistent with associations between colder temperatures and stronger COVID-19 burden reported in previous studies, and suggest that changes in the per-contact transmission probability play an important role. Our model displays good potential as a short-range (2 to 3 week) forecasting tool during the early stages of a future pandemic, before non-pharmaceutical interventions (NPIs) that modify per-contact transmission probability, principally face masks, come into widespread use. Hence, future development should also incorporate time series data of NPI use.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Mireille Farjo", - "author_inst": "University of Illinois at Urbana-Champaign" - }, - { - "author_name": "Katia Koelle", - "author_inst": "Emory University" - }, - { - "author_name": "Michael A. Martin", - "author_inst": "Emory University" - }, - { - "author_name": "Laura L Gibson", - "author_inst": "University of Massachusetts Medical School" - }, - { - "author_name": "Kimberly KO Walden", - "author_inst": "University of Illinois at Urbana-Champaign" - }, - { - "author_name": "Gloria Rendon", - "author_inst": "University of Illinois at Urbana Champaign" - }, - { - "author_name": "Christopher J. Fields", - "author_inst": "University of Illinois at Urbana Champaign" + "author_name": "Edward Wolfgang Thommes", + "author_inst": "University of Guelph" }, { - "author_name": "Fadi Alnaji", - "author_inst": "University of Illinois at Urbana Champaign" + "author_name": "Zahra Mohammadi", + "author_inst": "University of Guelph" }, { - "author_name": "Nicholas Gallagher", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Darren Flynn-Primrose", + "author_inst": "University of Guelph" }, { - "author_name": "Chun Huai Luo", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Sarah Smook", + "author_inst": "University of Guelph" }, { - "author_name": "Heba H. Mostafa", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Gabriela Gomez", + "author_inst": "Sanofi" }, { - "author_name": "Yukari C Manabe", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Sandra S. Chaves", + "author_inst": "Sanofi" }, { - "author_name": "Andrew Pekosz", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Laurent Coudeville", + "author_inst": "Sanofi" }, { - "author_name": "Rebecca Lee Smith", - "author_inst": "University of Illinois at Urbana-Champaign" + "author_name": "Robertus van Aalst", + "author_inst": "Sanofi" }, { - "author_name": "David D McManus", - "author_inst": "University of Massachusetts Medical School" + "author_name": "Cedric Mahe", + "author_inst": "Sanofi" }, { - "author_name": "Christopher B Brooke", - "author_inst": "University of Illinois at Urbana-Champaign" + "author_name": "Monica Gabriela Cojocaru", + "author_inst": "University of Guelph" } ], "version": "1", "license": "cc_no", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.06.22.22276746", @@ -288712,39 +289075,99 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.06.17.22276229", - "rel_title": "Low level of knowledge about COVID-19 among a sample of Deaf persons in Ghana.", - "rel_date": "2022-06-20", + "rel_doi": "10.1101/2022.06.18.22276437", + "rel_title": "A patient-centric characterization of systemic recovery from SARS-CoV-2 infection", + "rel_date": "2022-06-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.17.22276229", - "rel_abs": "Global observations have shown that the success or failure in preventing and controlling the spread of COVID-19 largely relies on human behaviours. Human behaviours in preventing and controlling the spread of the disease principally, is dependent on the level of knowledge of the disease, the attitudes adopted by persons due to the level of knowledge of the disease and the decision to adhere to the preventive practices (KAP) of the disease. Since the beginning of this pandemic, numerous studies have been conducted to investigate the KAP on the novel COVID-19 among diverse demographic groups. However, no reported studies have been found on the KAP of the COVID-19 pandemic among the deaf in various populations around the world. This study sought to assess the KAP of COVID-19 among deaf persons in the Greater Accra region of Ghana.\n\nThe design of this study utilized the knowledge, attitude and practice (KAP) survey. Good attitude and adherence to the preventive practices of COVID-19 was observed among the deaf persons. However, knowledge about the science of the disease was lacking. Educational campaigns about COVID-19 should also emphasize the teaching and understanding of the science of the virus and the disease to its audience.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.18.22276437", + "rel_abs": "The biology driving individual patient responses to SARS-CoV-2 infection remains ill understood. Here, we developed a patient-centric framework leveraging detailed longitudinal phenotyping data, covering a year post disease onset, from 215 SARS-CoV-2 infected subjects with differing disease severities. Our analyses revealed distinct \"systemic recovery\" profiles with specific progression and resolution of the inflammatory, immune, metabolic and clinical responses, over weeks to several months after infection. In particular, we found a strong intra-patient temporal covariation of innate immune cell numbers, kynurenine- and host lipid-metabolites, which suggested candidate immunometabolic pathways putatively influencing restoration of homeostasis, the risk of death and of long COVID. Based on these data, we identified a composite signature predictive of systemic recovery on the patient level, using a joint model on cellular and molecular parameters measured soon after disease onset. New predictions can be generated using the online tool http://shiny.mrc-bsu.cam.ac.uk/apps/covid-systemic-recovery-prediction-app, designed to test our findings prospectively.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/22276437v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (38K):\norg.highwire.dtl.DTLVardef@12b0afborg.highwire.dtl.DTLVardef@ddf3b2org.highwire.dtl.DTLVardef@1aa670forg.highwire.dtl.DTLVardef@5415ec_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Reginald Arthur-Mensah Jr.", - "author_inst": "Pentecost University College" + "author_name": "H\u00e9l\u00e8ne Ruffieux", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Aimee Hanson", + "author_inst": "University of Cambridge" }, { - "author_name": "Jacob Nartey Quao", - "author_inst": "Ghana Health Service" + "author_name": "Samantha Lodge", + "author_inst": "Murdoch University" }, { - "author_name": "Louisa Yeboah", - "author_inst": "Ga North Municipal Hospital" + "author_name": "Nathan Lawler", + "author_inst": "Murdoch University" }, { - "author_name": "Zanu Dassah", - "author_inst": "Ghana Health Service" + "author_name": "Luke Whiley", + "author_inst": "Murdoch University" + }, + { + "author_name": "Nicola Gray", + "author_inst": "Murdoch University" + }, + { + "author_name": "Tui Nolan", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Laura Bergamaschi", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Federica Mescia", + "author_inst": "University of Cambridge" + }, + { + "author_name": "- CITIID-NIHR COVID BioResource Collaboration", + "author_inst": "" + }, + { + "author_name": "Nathalie Kingston", + "author_inst": "University of Cambridge" + }, + { + "author_name": "John Bradley", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Elaine Holmes", + "author_inst": "Murdoch University" + }, + { + "author_name": "Julien Wist", + "author_inst": "Murdoch University" + }, + { + "author_name": "Jeremy Nicholson", + "author_inst": "Murdoch University" }, { - "author_name": "Abigail Agartha Kyei", - "author_inst": "Pentecost University College" + "author_name": "Paul Lyons", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Kenneth Smith", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Sylvia Richardson", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Glenn Bantug", + "author_inst": "University and University Hospital Basel" + }, + { + "author_name": "Christoph Hess", + "author_inst": "University of Cambridge" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.06.16.22276533", @@ -290574,65 +290997,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.06.15.22276466", - "rel_title": "Effectiveness of mRNA COVID-19 vaccine boosters against infection, hospitalization and death: a target trial emulation in the omicron (B.1.1.529) variant era", + "rel_doi": "10.1101/2022.06.12.22276048", + "rel_title": "Prevalence of COVID-19 and Long COVID in Collegiate Student Athletes from Spring 2020 to Fall 2021: A Retrospective Survey", "rel_date": "2022-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.15.22276466", - "rel_abs": "AbstractO_ST_ABSBackgroundC_ST_ABSThe effectiveness of a 3rd mRNA COVID-19 vaccine (\"booster\") dose against the omicron (B.1.1.529) variant is uncertain especially in older, high-risk populations.\n\nObjectiveTo determine mRNA booster vaccine effectiveness (VE) against SARS-CoV-2 infection, hospitalization and death in the omicron era by type of booster, type of primary vaccine, time since primary vaccine, age and comorbidity burden.\n\nDesignTarget trial emulation study comparing booster vaccination versus no booster.\n\nSettingU.S. Department of Veterans Affairs (VA) healthcare system\n\nParticipants and InterventionAmong persons who had received two mRNA COVID-19 vaccine doses at least 5 months earlier, we designed this retrospective matched cohort study to emulate a target trial of booster mRNA vaccination (BNT162b2 or mRNA-1273) versus no booster, conducted from 12/01/2021 to 03/31/2022.\n\nMeasurementsBooster VE.\n\nResultsEach group included 490,838 well-matched persons, predominantly male (88%), mean age 63.0{+/-}14.0 years, followed for up to 121 days (mean 79.8 days). Booster VE >10 days after booster was 42.3% (95% CI 40.6-43.9) against SARS-CoV-2 infection, 53.3% (48.1-58.0) against SARS-CoV-2-related hospitalization and 79.1% (71.2-84.9) against SARS-CoV-2-related death. Booster VE was similar for different booster types (BNT162b2 or mRNA-1273), age groups or primary vaccination regimens, but was significantly higher with longer time since primary vaccination and with higher comorbidity burden.\n\nLimitationsPredominantly male population.\n\nConclusionsBooster mRNA vaccination was highly effective in preventing death and moderately effective in preventing infection and hospitalization for up to 4 months after administration in the omicron era. Increased uptake of booster vaccination, which is currently suboptimal, should be pursued to limit the morbidity and mortality of SARS-CoV-2 infection, especially in persons with high comorbidity burden.\n\nPrimary Funding Source: Department of Veterans Affairs", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.12.22276048", + "rel_abs": "Symptomatic COVID-19 and post-COVID conditions, also referred to as post-acute sequelae of SARS-CoV-2 (PASC) or Long COVID, have been widely reported in young, healthy people, but their prevalence has not yet been determined in student athletes. We surveyed a convenience sample of 18 collegiate school administrators, representing about 7,000 student athletes. According to their survey responses, 9.8% of student athletes tested positive for COVID-19 in spring 2020 and 25.4% tested positive in the academic year of fall 2020 to spring 2021. About 4% of student athletes who tested positive from spring 2020 to spring 2021 developed Long COVID, defined as new, recurring, or ongoing physical or mental health consequences occurring 4 or more weeks after SARS-CoV-2 infection. This study highlights that Long COVID occurs in healthy collegiate athletes and merits a larger study to determine population-wide prevalence.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "George N. Ioannou", - "author_inst": "University of Washington" - }, - { - "author_name": "Amy S.B. Bohnert", - "author_inst": "University of Michigan" - }, - { - "author_name": "Ann M. O'Hare", - "author_inst": "University of Washington" - }, - { - "author_name": "Edward J. Boyko", - "author_inst": "University of Washington" - }, - { - "author_name": "Valerie A. Smith", - "author_inst": "Duke University" + "author_name": "Daisy Massey", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Matthew L. Maciejewski", - "author_inst": "Duke University" + "author_name": "Sharon Saydah", + "author_inst": "Division of Viral Diseases, Centers for Disease Control and Prevention, Respiratory Viruses Branch" }, { - "author_name": "C. Barrett Bowling", - "author_inst": "Duke University" + "author_name": "Blythe Adamson", + "author_inst": "Infectious Economics, LLC" }, { - "author_name": "Elizabeth Viglianti", - "author_inst": "University of Michigan" + "author_name": "Andrew Lincoln", + "author_inst": "Special Olympics" }, { - "author_name": "Theodore J. Iwashyna", - "author_inst": "University of Michigan" + "author_name": "Douglas Aukerman", + "author_inst": "Samaritan Athletic Medicine at Oregon State University, Samaritan Health Services" }, { - "author_name": "Denise M. Hynes", - "author_inst": "Veterans Affairs Portland Healthcare System" + "author_name": "Ethan Berke", + "author_inst": "UnitedHealth Group" }, { - "author_name": "Kristin Berry", - "author_inst": "Veterans Affairs Puget Sound Healthcare System" + "author_name": "Robby Sikka", + "author_inst": "COVID-19 Sports and Society Working Group" }, { - "author_name": "- COVID-19 Observational Research Collaboratory (CORC)", - "author_inst": "" + "author_name": "Harlan Krumholz", + "author_inst": "Yale University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -292896,67 +293303,59 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.06.14.22276393", - "rel_title": "Nirmatrelvir plus ritonavir for early COVID-19 and hospitalization in a large US health system", - "rel_date": "2022-06-16", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.14.22276393", - "rel_abs": "BackgroundIn the EPIC-HR trial, nirmatrelvir plus ritonavir led to an 88% reduction in hospitalization or death among unvaccinated outpatients with early COVID-19. Clinical impact of nirmatrelvir plus ritonavir among vaccinated populations is uncertain.\n\nObjectiveTo assess whether nirmatrelvir plus ritonavir reduces risk of hospitalization among outpatients with early COVID-19 in the setting of prevalent SARS-CoV-2 immunity and immune evasive SARS-CoV-2 lineages.\n\nDesignPopulation-based cohort study analyzed to emulate a clinical trial utilizing two-stage, inverse-probability weighted models to account for anticipated bias in testing and treatment.\n\nSettingA large healthcare system providing care for 1.5 million patients in Massachusetts and New Hampshire during Omicron wave (January 1 to May 15, 2022) with staged access and capacity to prescribe nirmatrelvir plus ritonavir.\n\nPatients30,322 non-hospitalized adults (87.2% vaccinated) aged 50 and older with COVID-19 and without contraindications to nirmatrelvir plus ritonavir.\n\nMeasurementPrimary outcome was hospitalization within 14 days of COVID-19 diagnosis.\n\nResultsDuring the study period, 6036 (19.9%) patients were prescribed nirmatrelvir plus ritonavir and 24,286 (80.1%) patients were not. Patients prescribed nirmatrelvir were more likely to be older, have more comorbidities, and be unvaccinated. Hospitalization occurred in 40 (0.66%) and 232 (0.96%) patients prescribed and not prescribed nirmatrelvir plus ritonavir, respectively. The adjusted risk ratio was 0.55 (95% confidence interval 0.38 to 0.80, p = 0.002). Observed risk reduction was greater among unvaccinated patients and obese patients.\n\nLimitationsPotential for residual confounding due to differential access and uptake of COVID-19 vaccines, diagnostics, and treatment.\n\nConclusionsThe overall risk of hospitalization was already low (<1%) following an outpatient diagnosis of COVID-19, but this risk was 45% lower among patients prescribed nirmatrelvir plus ritonavir.\n\nFundingNational Institutes of Health (P30 AI060354 and R01 CA236546).", - "rel_num_authors": 12, + "rel_doi": "10.1101/2022.06.15.496220", + "rel_title": "The Omicron variant BA.1.1 presents a lower pathogenicity than B.1 D614G and Delta variants in a feline model of SARS-CoV-2 infection", + "rel_date": "2022-06-15", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.15.496220", + "rel_abs": "Omicron (B.1.1.529) is the most recent SARS-CoV-2 variant of concern (VOC), which emerged in late 2021 and rapidly achieved global predominance in early 2022. In this study, we compared the infection dynamics, tissue tropism and pathogenesis and pathogenicity of SARS-CoV-2 D614G (B.1), Delta (B.1.617.2) and Omicron BA.1.1 sublineage (B.1.1.529) variants in a highly susceptible feline model of infection. While D614G- and Delta-inoculated cats became lethargic, and showed increased body temperatures between days 1 and 3 post-infection (pi), Omicron-inoculated cats remained subclinical and, similar to control animals, gained weight throughout the 14-day experimental period. Intranasal inoculation of cats with D614G- and the Delta variants resulted in high infectious virus shedding in nasal secretions (up to 6.3 log10 TCID50.ml-1), whereas strikingly lower level of viruses shedding (<3.1 log10 TCID50.ml-1) was observed in Omicron-inoculated animals. In addition, tissue distribution of the Omicron variant was markedly reduced in comparison to the D614G and Delta variants, as evidenced by in situ viral RNA detection, in situ immunofluorescence, and quantification of viral loads in tissues on days 3, 5, and 14 pi. Nasal turbinate, trachea, and lung were the main - but not the only - sites of replication for all three viral variants. However, only scarce virus staining and lower viral titers suggest lower levels of viral replication in tissues from Omicron-infected animals. Notably, while D614G- and Delta-inoculated cats had severe pneumonia, histologic examination of the lungs from Omicron-infected cats revealed mild to modest inflammation. Together, these results demonstrate that the Omicron variant BA.1.1 is less pathogenic than D614G and Delta variants in a highly susceptible feline model.\n\nAuthor SummaryThe SARS-CoV-2 Omicron (B.1.1.529) variant of concern (VOC) emerged in South Africa late in 2021 and rapidly spread across the world causing a significant increase in the number of infections. Importantly, this variant was also associated with an increased risk of reinfections. However, the number of hospitalizations and deaths due to COVID-19 did not follow the same trends. These early observations, suggested effective protection conferred by immunizations and/or overall lower virulence of the highly mutated variant virus. In this study we present novel evidence demonstrating that the Omicron BA.1.1 variant of concern (VOC) presents a lower pathogenicity when compared to D614G- or Delta variants in cats. Clinical, virological and pathological evaluations revealed lower disease severity, viral replication and lung pathology in Omicron-infected cats when compared to D614G and Delta variant inoculated animals, confirming that Omicron BA.1.1 is less pathogenic in a highly susceptible feline model of infection.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Scott Dryden-Peterson", - "author_inst": "Brigham and Women's Hospital, Boston, Massachusetts" - }, - { - "author_name": "Andy Kim", - "author_inst": "Brigham and Women's Hospital, Boston, Massachusetts" - }, - { - "author_name": "Arthur Y Kim", - "author_inst": "Massachusetts General Hospital, Boston, Massachusetts" + "author_name": "Mathias Martins", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Ellen C Caniglia", - "author_inst": "Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania" + "author_name": "Gabriela M. do Nascimento", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Inga Lennes", - "author_inst": "Massachusetts General Hospital, Boston, Massachusetts" + "author_name": "Mohammed Nooruzzaman", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Rajesh Patel", - "author_inst": "Beth Israel Lahey Health, Cambridge, Massachusetts" + "author_name": "Fangfeng Yuan", + "author_inst": "University of Illinois Urbana-Champaign" }, { - "author_name": "Lindsay Gainer", - "author_inst": "Mass General Brigham Integrated Care" + "author_name": "Chi Chen", + "author_inst": "UIUC: University of Illinois at Urbana-Champaign" }, { - "author_name": "Lisa Dutton", - "author_inst": "Brigham and Women's Hospital, Boston, Massachusetts" + "author_name": "Leonardo C. Caserta", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Elizabeth Donahue", - "author_inst": "Brigham and Women's Hospital, Boston, Massachusetts" + "author_name": "Andrew D. Miller", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Rajesh T Gandhi", - "author_inst": "Massachusetts General Hospital, Boston, Massachusetts" + "author_name": "Gary R. Whittaker", + "author_inst": "Cornell University College of Veterinary Medicine" }, { - "author_name": "Lindsey R Baden", - "author_inst": "Brigham and Women's Hospital, Boston, Massachusetts" + "author_name": "Ying Fang", + "author_inst": "University of Illinois Urbana-Champaign" }, { - "author_name": "Ann E Woolley", - "author_inst": "Brigham and Women's Hospital, Boston, Massachusetts" + "author_name": "Diego G. Diel", + "author_inst": "Cornell University College of Veterinary Medicine" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2022.06.14.496062", @@ -294734,37 +295133,49 @@ "category": "obstetrics and gynecology" }, { - "rel_doi": "10.1101/2022.06.08.22276134", - "rel_title": "Implementation of a digital early warning score (NEWS2) in a cardiac specialist and general hospital settings in the COVID-19 pandemic: A qualitative study.", + "rel_doi": "10.1101/2022.06.10.22276247", + "rel_title": "Using routinely collected hospital data to investigate healthcare worker mobility and patient contacts within a UK hospital during the COVID-19 pandemic", "rel_date": "2022-06-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.08.22276134", - "rel_abs": "ObjectivesTo evaluate implementation of EHR-integrated NEWS2 in a cardiac care setting and a general hospital setting in the COVID-19 pandemic.\n\nDesignThematic analysis of qualitative semi-structured interviews with purposefully sampled nurses and managers, as well as online surveys.\n\nSettingsSpecialist cardiac hospital (St Bartholomews Hospital) and General teaching hospital (University College London Hospital).\n\nParticipantsEleven nurses and managers from cardiology, cardiac surgery, oncology, and intensive care wards (St Bartholomews) and medical, haematology and intensive care wards (UCLH) were interviewed and sixty-seven were surveyed online.\n\nResultsThree main themes emerged: (i) Implementing NEWS2 challenges and supports; (ii) Value of NEWS2 to alarm, escalate, particularly during the pandemic; and (iii) Digitalisation: EHR integration and automation. The value of NEWS2 was partly positive in escalation, yet there were concerns by nurses who undervalued NEWS2 particularly in cardiac care. Challenges, like clinicians behaviours, lack of resources and training and the perception of NEWS2 value, limit the success of this implementation. Changes in guidelines in the pandemic have led to overlooking NEWS2. EHR integration and automated monitoring are improvement solutions that are not fully employed yet.\n\nConclusionWhether in specialist or general medical settings, the health professionals implementing EWS in healthcare face cultural and systems related challenges to adopting NEWS2 and digital solutions. The validity of NEWS2 in specialised settings and complex conditions is not yet apparent and requires comprehensive validation. EHRs integration and automation are powerful tools to facilitate NEWS2 if its principles are reviewed and rectified, and resources and training are accessible. Further examination of implementation from the cultural and automation domains are needed.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.10.22276247", + "rel_abs": "Movement and contacts are central to the transmission of infectious diseases and, within the hospital setting, healthcare worker (HCW) mobility and their contact with patients play an important role in the spread of nosocomial disease. Yet data relating to HCW behaviours associated with mobility and contacts in the healthcare environment are often limited. This paper proposes a framework for integrating several electronic data sources routinely-collected by modern hospitals, to enable the measurement of HCW behaviours relevant to the transmission of infections. Using data from a London teaching hospital during the COVID-19 pandemic, we demonstrate how, at an aggregate level, electronic medical records (EMRs) and door access logs can be used to establish changes in HCW mobility and patient contacts. In addition, to show the utility of these data sources in supporting infection prevention and control (IPC), we investigate changes in the indirect connectivity of patients (resulting from shared contacts with HCWs) and spatial connectivity of floors (owing to the movements of HCWs). Average daily rates of patient contacts are computed and found to be higher throughout the pandemic compared to that pre-pandemic, while the average daily rates of HCW mobility remained stable until the second wave, where they surpassed pre-pandemic levels. The response of HCW behaviour to the pandemic was not equal between floors, whereby the highest increases in patient contacts and mobility were on floors handling the majority of COVID-19 patients. The first wave of COVID-19 patients resulted in changes to the flow of HCWs between floors, but the interconnectivity between COVID-19 and non COVID-19 wards was evident throughout the pandemic. Daily rates of indirect contact between patients provided evidence for reactive staff cohorting, whereby indirect contact rates between COVID-19 positive and negative patients were lowest during peaks in COVID-19 hospital admissions. We propose that IPC practitioners use these routinely collected data on HCW behaviour to support infection control activities and to help better protect hospital staff and patients from nosocomial outbreaks of communicable diseases.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Baneen Alhmoud", - "author_inst": "University College London, University College London Hospital, Barts Health Trust." + "author_name": "Jared K Wilson-Aggarwal", + "author_inst": "University of Leeds" }, { - "author_name": "Timothy Bonicci", - "author_inst": "University College London, University College London Hospital" + "author_name": "Nick Gotts", + "author_inst": "University of Leeds" }, { - "author_name": "Riyaz Patel", - "author_inst": "University College London, University College London Hospital." + "author_name": "Wai Keong Wong", + "author_inst": "University College London Hospitals NHS Foundation Trust" }, { - "author_name": "Daniel Melley", - "author_inst": "Barts Health Trust" + "author_name": "Christopher Liddington", + "author_inst": "University College London Hospitals NHS Foundation Trust" }, { - "author_name": "Louise Hicks", - "author_inst": "Barts Health Trust" + "author_name": "Simon Knight", + "author_inst": "University College London Hospitals NHS Foundation Trust" }, { - "author_name": "Amitava Banerjee", - "author_inst": "University College London, University College London Hospital, Barts Health Trust." + "author_name": "Moira J Spyer", + "author_inst": "University College London Hospitals NHS Foundation Trust" + }, + { + "author_name": "Catherine F Houlihan", + "author_inst": "University College London Hospitals NHS Foundation Trust" + }, + { + "author_name": "Eleni Nastouli", + "author_inst": "University College London Hospitals NHS Foundation Trust" + }, + { + "author_name": "Ed Manley", + "author_inst": "University of Leeds" } ], "version": "1", @@ -296504,23 +296915,59 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.06.10.22276252", - "rel_title": "Ivermectin for Treatment of Mild-to-Moderate COVID-19 in the Outpatient Setting: A Decentralized, Placebo-controlled, Randomized, Platform Clinical Trial", - "rel_date": "2022-06-12", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.10.22276252", - "rel_abs": "BackgroundThe effectiveness of ivermectin to shorten symptom duration or prevent hospitalization among outpatients in the United States with mild-to-moderate symptomatic coronavirus disease 2019 (COVID-19) is unknown.\n\nObjectiveWe evaluated the efficacy of ivermectin 400 {micro}g/kg daily for 3 days compared with placebo for the treatment of early mild-to-moderate COVID-19.\n\nMethodsACTIV-6 is an ongoing, decentralized, double-blind, randomized, placebo-controlled platform trial to evaluate repurposed therapies in outpatients with mild-to-moderate COVID-19. Non-hospitalized adults age [≥]30 years with confirmed COVID-19, experiencing [≥]2 symptoms of acute infection for [≤]7 days were randomized to receive ivermectin 400 {micro}g/kg daily for 3 days or placebo. The main outcome measure was time to sustained recovery, defined as achieving at least 3 consecutive days without symptoms. Secondary outcomes included a composite of hospitalization or death by day 28.\n\nResultsOf the 3457 participants who consented to be evaluated for inclusion in the ivermectin arm, 1591 were eligible for this study arm, randomized to receive ivermectin 400 {micro}g/kg (n=817) or placebo (n=774), and received study drug. Of those enrolled, 47% reported receiving at least 2 doses of SARS-CoV-2 vaccination. The posterior probability for any improvement in time to recovery was 0.91 (hazard ratio 1.07, 95% credible interval 0.96-1.17). The posterior probability of this benefit exceeding 24 hours was less than 0.01, as measured by the difference in mean time unwell. Hospitalizations or deaths were uncommon (ivermectin [n=10]; placebo [n=9]). Ivermectin at 400 {micro}g/kg was safe and without serious adverse events as compared with placebo (ivermectin [n=10]; placebo [n=9]).\n\nConclusionsIvermectin dosed at 400 {micro}g/kg daily for 3 days resulted in less than one day of shortening of symptoms and did not lower incidence of hospitalization or death among outpatients with COVID-19 in the United States during the delta and omicron variant time periods.\n\nTrial registrationClinicalTrials.gov Identifier: NCT04885530.", - "rel_num_authors": 1, + "rel_doi": "10.1101/2022.06.11.495733", + "rel_title": "Evolutionary trajectory of the physicochemical mechanism of interaction of SARS-CoV-2 spike protein with ACE2", + "rel_date": "2022-06-11", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.11.495733", + "rel_abs": "SARS-CoV-2 infects cells by attachment to its receptor - the angiotensin converting enzyme 2 (ACE2). Regardless of the wealth of structural data, little is known about the physicochemical mechanism of interactions of the viral spike (S) protein with ACE2 and how this mechanism has evolved during the pandemic. Here, we applied experimental and computational approaches to characterize the molecular interaction of S proteins from SARS-CoV-2 variants of concern (VOC). Data on kinetics, activation- and equilibrium thermodynamics of binding of the receptor binding domain (RBD) from VOC with ACE2 as well as data from computational protein electrostatics revealed a profound remodeling of the physicochemical characteristics of the interaction during the evolution. Thus, as compared to RBDs from Wuhan strain and other VOC, Omicron RBD presented as a unique protein in terms of conformational dynamics and types of non-covalent forces driving the complex formation with ACE2. Viral evolution resulted in a restriction of the RBD structural dynamics, and a shift to a major role of polar forces for ACE2 binding. Further, we investigated how the reshaping of the physicochemical characteristics of interaction affect the binding specificity of S proteins. Data from various binding assays revealed that SARS-CoV-2 Wuhan and Omicron RBDs manifest capacity for promiscuous recognition of unrelated human proteins, but they harbor distinct reactivity patterns. These findings might contribute for mechanistic understanding of the viral tropism, and capacity to evade immune responses during evolution.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Susanna Naggie", - "author_inst": "Duke Clinical Research Institute, Duke University School of Medicine" + "author_name": "Cyril Planchais", + "author_inst": "Laboratory of Humoral Immunology, Institut Pasteur, Universite Paris Cite, INSERM U1222" + }, + { + "author_name": "Alejandra Reyes-Ruiz", + "author_inst": "Centre de Recherche des Cordeliers, INSERM, CNRS, Sorbonne Universite, Universite de Paris" + }, + { + "author_name": "Robin Lacombe", + "author_inst": "Centre de Recherche des Cordeliers, INSERM, CNRS, Sorbonne Universite, Universite de Paris" + }, + { + "author_name": "Alessandra Zarantonello", + "author_inst": "Centre de Recherche des Cordeliers, INSERM, CNRS, Sorbonne Universite, Universite de Paris" + }, + { + "author_name": "Maxime Lecerf", + "author_inst": "Centre de Recherche des Cordeliers, INSERM, CNRS, Sorbonne Universite, Universite de Paris" + }, + { + "author_name": "Margot Revel", + "author_inst": "Centre de Recherche des Cordeliers, INSERM, CNRS, Sorbonne Universite, Universite de Paris" + }, + { + "author_name": "Lubka T. Roumenina", + "author_inst": "Centre de Recherche des Cordeliers, INSERM, CNRS, Sorbonne Universite, Universite de Paris" + }, + { + "author_name": "Boris P. Atanasov", + "author_inst": "Institute of Organic Chemistry, Bulgarian Academy of Sciences" + }, + { + "author_name": "Hugo Mouquet", + "author_inst": "Laboratory of Humoral Immunology, Institut Pasteur, Universite Paris Cite" + }, + { + "author_name": "Jordan D. Dimitrov", + "author_inst": "Centre de Recherche des Cordeliers, INSERM, CNRS, Sorbonne Universite, Universite de Paris" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2022.06.09.495578", @@ -298106,43 +298553,103 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.06.07.22275493", - "rel_title": "Precarious employment and associations with health during COVID-19: a nationally representative survey in Wales, UK", + "rel_doi": "10.1101/2022.06.07.22276080", + "rel_title": "Non-pharmacological therapies for post-viral syndromes, including Long COVID: A systematic review", "rel_date": "2022-06-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.07.22275493", - "rel_abs": "BackgroundThe COVID-19 pandemic had an early impact on employment, with the United States (US) and the United Kingdom (UK) experiencing more severe immediate labour market impacts than other Western countries. Emerging evidence from the initial phase of the pandemic highlighted that job losses were experienced more by those holding atypical contracts. Furthermore, it is predicted that this associated unemployment will increase precarious employment arrangements during the COVID-19 pandemic.\n\nIn this paper we seek to answer the following research questions:\n\nO_LIWhat is the prevalence of precarious employment in Wales and are there differences in employment precariousness by socio-demographic characteristics and self-reported health status?\nC_LIO_LIWhich domains are the main contributing factors of precarious employment in Wales?\nC_LIO_LIWhich domains of precarious employment are associated with poorer health?\nC_LIO_LIHaves there been changes in job quality (as reflected by precarious employment domains) during the COVID pandemic (between February 2020 and Winter 2020/2021)?\nC_LI\n\nMethodsData was collected from a national household survey carried out in May/June 2020, with a sample of 1,032 residents in Wales and follow-up responses from 429 individuals collected between November 2020 and January 2021. To examine the associations between experiencing precarious employment or the separate domains of employment precariousness and socio-demographics and health, chi-squared analyses and logistic regression models (multinomial and binary) were used. To determine longitudinal changes in precarious employment experienced by socio-demographic groups and furlough status, McNemars test was used. The data is presented as proportion of respondents or adjusted odds ratios (aOR) and 95% confidence intervals following logistic regression.\n\nResultsOverall, pre-pandemic, one in four respondents were determined to be in precarious employment (26.5%). A higher proportion of females (28.3%) and those aged 18-29 years (41.0%) were in precarious employment in February 2020. In addition, a greater percentage of individuals who reported poorer health across all self-reported measures were in precarious employment compared to those reporting better health. Worse perceived treatment at work was twice as likely in those who reported a pre-existing condition (aOR 2.45 95% CI [1.33-4.49]), poorer general health (aOR 2.33 95% CI [1.22-4.47]) or low mental wellbeing (aOR 2.81 95% CI [1.34-5.88]) when compared to their healthier counterparts. Those calculated to have high wage precariousness were three times more likely to report low mental wellbeing (aOR 3.12 95% CI [1.54-6.32]). In the subsample, there was an observed increase in the prevalence of precarious employment, with this being attributable to lower affordability of wages and a perceived increase in vulnerability at work. The subgroups that were most impacted by this decrease in job quality were females and the 30-39 years age group.\n\nImplicationsImproving the vulnerability and wages domains, through the creation and provision of secure, adequately paid job opportunities has the potential to reduce the prevalence of precarious employment in Wales. In turn, these changes would improve the health and wellbeing of the working age population, some of which are already adversely impacted by the COVID-19 pandemic.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.07.22276080", + "rel_abs": "BackgroundPost-viral syndromes (PVS), including Long COVID, are symptoms sustained from weeks to years following an acute viral infection. Non-pharmacological treatments for these symptoms are poorly understood. This review summarises evidence for the effectiveness of non-pharmacological treatments for symptoms of PVS. It also summarises the symptoms and health impacts of PVS in individuals recruited to studies evaluating treatments.\n\nMethods and findingsWe conducted a systematic review to evaluate the effectiveness of non-pharmacological interventions for PVS, as compared to either standard care, alternative non-pharmacological therapy, or placebo. The outcomes of interest were changes in symptoms, exercise capacity, quality of life (including mental health and wellbeing), and work capability. We searched five databases (Embase, MEDLINE, PsycINFO, CINAHL, MedRxiv) for randomised controlled trials (RCTs) published between 1st January 2001 to 29th October 2021. We anticipated that there would be few RCTs specifically pertaining to Long COVID, so we also included observational studies only if they assessed interventions in individuals where the viral pathogen was SARS-COV-2. Relevant outcome data were extracted, study quality appraised using the Cochrane Risk of Bias tool, and the findings were synthesised narratively. Quantitative synthesis was not planned due to substantial heterogeneity between the studies. Overall, five studies of five different interventions (Pilates, music therapy, telerehabilitation, resistance exercise, neuromodulation) met the inclusion criteria. Aside from music-based intervention, all other selected interventions demonstrated some support in the management of PVS in some patients.\n\nConclusionsIn this study, we observed a lack of robust evidence evaluating non-pharmacological treatments for PVS, including Long COVID. Considering the prevalence of prolonged symptoms following acute viral infections, there is an urgent need for clinical trials evaluating the effectiveness and cost-effectiveness of non-pharmacological treatments for patients with PVS as well as what may work for certain sub-groups of patients with differential symptom presentation.\n\nRegistrationThe study protocol was registered with PROSPERO [CRD42021282074] in October 2021 and published in BMJ Open in 2022.\n\nAuthor summaryWhy was this study done?\n\nO_LIThe prevalence of Long COVID following exposure to SARS CoV-2 is substantial, and the current guidance provides few evidence-based treatment options for clinicians to suggest to their patients.\nC_LIO_LIDue to the similarities in presentation of other post-viral syndromes (PVS), and the lack of consensus in management approaches, there is a need to synthesise the available data on PVS to both support patients with PVS predating the pandemic, and those with Long COVID.\nC_LI\n\nWhat did the researchers do and find?\n\nO_LIThis is the first comprehensive systematic review of the effectiveness of non-pharmacological treatments for patients with PVS, including Long COVID.\nC_LIO_LIWe identified four non-pharmacological treatments (Pilates, telerehabilitation, resistance exercises and neuromodulation) which have shown promise in those who have experienced signs and symptoms related to PVS.\nC_LI\n\nWhat do these findings mean?\n\nO_LIIn this study, we identified few trials assessing the effectiveness of non-pharmacological therapies to support the management of symptoms of PVS. Considering the prevalence of PVS, including Long COVID, there is an urgent need for clinical trials evaluating the effectiveness and cost-effectiveness of non-pharmacological therapies to support these patients.\nC_LI", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Benjamin J Gray", - "author_inst": "Research and Evaluation Division, Public Health Wales" + "author_name": "Joht Singh Chandan", + "author_inst": "University of Birmingham" }, { - "author_name": "Richard G Kyle", - "author_inst": "Academy of Nursing, University of Exeter" + "author_name": "Kirsty R Brown", + "author_inst": "University of Birmingham" }, { - "author_name": "Kate R Isherwood", - "author_inst": "School of Sport and Health Sciences, Cardiff Metropolitan University" + "author_name": "Nikita Simms-Williams", + "author_inst": "University of Birmingham" }, { - "author_name": "Ciar\u00e1n Humphreys", - "author_inst": "Wider Determinants of Health Unit, Public Health Wales" + "author_name": "Nasir Z Bashir", + "author_inst": "University of Bristol" }, { - "author_name": "Melda Lois Griffiths", - "author_inst": "Research and Evaluation Division, Public Health Wales; National Centre for Population Health and Wellbeing Research, Swansea University" + "author_name": "Jenny Camaradou", + "author_inst": "COVID END Evidence Network" }, { - "author_name": "Alisha R Davies", - "author_inst": "Research and Evaluation Division, Public Health Wales; National Centre for Population Health and Wellbeing Research, Swansea University" + "author_name": "Dominic Heining", + "author_inst": "Department of Microbiology, Royal Wolverhampton NHS Trust, UK" + }, + { + "author_name": "Grace M Turner", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Samantha Cruz Rivera", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Richard Hotham", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Sonica Minhas", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Krishnarajah Niratharakumar", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Manoj Sivan", + "author_inst": "University of Leeds" + }, + { + "author_name": "Kamlesh Khunti", + "author_inst": "University of Leicester" + }, + { + "author_name": "Devan Raindi", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Steven Marwaha", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Sarah E Hughes", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Christel McMullan", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Tom Marshall", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Melanie J Calvert", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Shamil Haroon", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Olalekan Lee Aiyegbusi", + "author_inst": "University of Birmingham" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.06.07.22276020", @@ -300188,31 +300695,31 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2022.06.06.22276040", - "rel_title": "Transcriptomics Meta-Analysis Predicts Two Robust Human Biomarkers for Severe Infection with SARS-CoV-2", + "rel_doi": "10.1101/2022.06.06.22276025", + "rel_title": "The impact of surgical mask-wearing, contact tracing program, and vaccination on COVID-19 transmission in Taiwan 2020-2022: a modelling study", "rel_date": "2022-06-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.06.22276040", - "rel_abs": "Defining the human factors associated with severe vs mild SARS-CoV-2 infection has become of increasing interest. Mining large numbers of public gene expression datasets is an effective way to identify genes that contribute to a given phenotype. Combining RNA-sequencing data with the associated clinical metadata describing disease severity can enable earlier identification of patients who are at higher risk of developing severe COVID-19 disease. We consequently identified 358 public RNA-seq human transcriptome samples from the Gene Expression Omnibus database that had disease severity metadata. We then subjected these samples to a robust RNA-seq data processing workflow to quantify gene expression in each patient. This process involved using Salmon to map the reads to the reference transcriptomes, edgeR to calculate significant differential expression levels, and gene ontology enrichment using Camera. We then applied a machine learning algorithm to the read counts data to identify features that best differentiated samples based on COVID-19 severity phenotype. Ultimately, we produced a ranked list of genes based on their Gini importance values that includes GIMAP7 and S1PR2, which are associated with immunity and inflammation (respectively). Our results show that these two genes can potentially predict people with severe COVID-19 at up to [~]90% accuracy. We expect that our findings can help contribute to the development of improved prognostics for severe COVID-19.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.06.06.22276025", + "rel_abs": "The effectiveness of interventions such as public mask-wearing, contact tracing, and vaccination presents an important lesson for control of the further COVID-19 outbreaks without of whole country lockdowns and the restriction of individual movement. We simulated different scenarios of COVID-19 waves in Taiwan from 2020 to the beginning of March 2022 and considered the following interventions: travel restrictions, quarantine of infected individuals, contact tracing, mask-wearing, vaccination, and mass gathering restrictions. We propose an epidemiological compartmental model modified from the susceptible-exposed-infectious-removed (SEIR) model and derive a formula for the basic reproduction number (R0) describing its dependence on all investigated parameters. The simulation results are fitted with the official Taiwanese COVID-19 data. Thus, the results demonstrate that the fast introduction of the interventions and maintaining them at a high level are able the outbreak control without strict lockdowns. By estimation of the R0, it was shown that it is necessary to maintain on high implementation level of both non- and pharmaceutical intervention types to control the COVID-19 transmission. Our results can be useful as advice or recommendation for public health policies, and our model can be applied for other epidemiological simulation studies.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jeffrey Clancy", - "author_inst": "Brigham Young University-Provo: Brigham Young University" + "author_name": "Tatiana Filonets", + "author_inst": "National Taiwan University" }, { - "author_name": "Curtis S Hoffmann", - "author_inst": "Brigham Young University-Provo: Brigham Young University" + "author_name": "Maxim Solovchuk", + "author_inst": "National Health Research Institutes" }, { - "author_name": "Brett E Pickett", - "author_inst": "Brigham Young University" + "author_name": "Wayne Gao", + "author_inst": "Taipei Medical University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.06.06.494965", @@ -302002,39 +302509,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.05.31.22275835", - "rel_title": "One Million and Counting: Estimates of Deaths in the United States from Ancestral SARS-CoV-2 and Variants", + "rel_doi": "10.1101/2022.06.01.494393", + "rel_title": "OxoScan-MS: Oxonium ion scanning mass spectrometry facilitates plasma glycoproteomics in large scale", "rel_date": "2022-06-02", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.31.22275835", - "rel_abs": "BackgroundOver one million COVID-19 deaths have been recorded in the United States. Sustained global SARS-CoV-2 transmission has led to the emergence of new variants with increased transmissibility, virulence, and/or immune evasion. The specific burden of mortality from each variant over the course of the U.S. COVID-19 epidemic remains unclear.\n\nMethodsWe constructed an epidemiologic model using data reported by the CDC on COVID-19 mortality and circulating variant proportions to estimate the number of recorded COVID-19 deaths attributable to each SARS-CoV-2 variant in the U.S. We conducted sensitivity analysis to account for parameter uncertainty.\n\nFindingsOf the 1,003,419 COVID-19 deaths recorded as of May 12, 2022, we estimate that 460,124 (46%) were attributable to WHO-designated variants. By U.S. Census Region, the South recorded the most variant deaths per capita (median estimate 158 per 100,000), while the Northeast recorded the fewest (111 per 100,000). Over 40 percent of national COVID-19 deaths were estimated to be caused by the combination of Alpha (median estimate 39,548 deaths), Delta (273,801), and Omicron (117,560).\n\nInterpretationSARS-CoV-2 variants that have emerged around the world have imposed a significant mortality burden in the U.S. In addition to national public health strategies, greater efforts are needed to lower the risk of new variants emerging, including through global COVID-19 vaccination, treatment, and outbreak mitigation.", - "rel_num_authors": 5, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.06.01.494393", + "rel_abs": "Protein glycosylation is a complex and heterogeneous post-translational modification. Specifically, the human plasma proteome is rich in glycoproteins, and as protein glycosylation is frequently dysregulated in disease, glycoproteomics is considered an underexplored resource for biomarker discovery. Here, we present OxoScan-MS, a data-independent mass spectrometric acquisition technology and data analysis software that facilitates sensitive, fast, and cost-effective glycoproteome profiling of plasma and serum samples in large cohort studies. OxoScan-MS quantifies glycosylated peptide features by exploiting a scanning quadrupole to assign precursors to oxonium ions, glycopeptide-specific fragments. OxoScan-MS reaches a high level of sensitivity and selectivity in untargeted glycopeptide profiling, such that it can be efficiently used with fast microflow chromatography without a need for experimental enrichment of glycopeptides from neat plasma. We apply OxoScan-MS to profile the plasma glycoproteomic in an inpatient cohort hospitalised due to severe COVID-19, and obtain precise quantities for 1,002 glycopeptide features. We reveal that severe COVID-19 induces differential glycosylation in disease-relevant plasma glycoproteins, including IgA, fibrinogen and alpha-1-antitrypsin. Thus, with OxoScan-MS we present a strategy for quantitatively mapping glycoproteomes that scales to hundreds and thousands of samples, and report glycoproteomic changes in severe COVID-19.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Jo Walker", - "author_inst": "Yale School of Public Health" + "author_name": "Matthew E H White", + "author_inst": "Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, United Kingdom" }, { - "author_name": "Nathan D. Grubaugh", - "author_inst": "Yale School of Public Health" + "author_name": "D. Marc Jones", + "author_inst": "Bioinformatics and Computational Biology Laboratory, The Francis Crick Institute, London, United Kingdom; Department of Basic & Clinical Neuroscience, Maurice W" }, { - "author_name": "Gregg Gonsalves", - "author_inst": "Yale School of Public Health" + "author_name": "Joost de Folter", + "author_inst": "Software Engineering and Artificial Intelligence Technology Platform, The Francis Crick Institute, London, United Kingdom" }, { - "author_name": "Virginia E. Pitzer", - "author_inst": "Yale School of Public Health" + "author_name": "Simran K Aulakh", + "author_inst": "Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, United Kingdom" }, { - "author_name": "Zain Rizvi", - "author_inst": "Public Citizen" + "author_name": "Helen R Flynn", + "author_inst": "Mass Spectrometry Proteomics Science Technology Platform, The Francis Crick Institute, London, United Kingdom" + }, + { + "author_name": "Lynn Kr\u00fcger", + "author_inst": "Department of Human Medicine, Medical School Berlin, Berlin, Germany; Institute of Diagnostic Laboratory Medicine, Charit\u00e9 Universit\u00e4tsmedizin, Berlin, Germany" + }, + { + "author_name": "Vadim Demichev", + "author_inst": "Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, United Kingdom; Department of Biochemistry, Charit\u00e9 Universit\u00e4tsmedizin Berlin," + }, + { + "author_name": "Pinkus Tober-Lau", + "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charit\u00e9 Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Florian Kurth", + "author_inst": "Department of Infectious Diseases and Respiratory Medicine, Charit\u00e9 Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Michael M\u00fclleder", + "author_inst": "Core Facility High-throughput Mass spectrometry, Charit\u00e9 Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "V\u00e9ronique Blanchard", + "author_inst": "Department of Human Medicine, Medical School Berlin, Berlin, Germany; Institute of Diagnostic Laboratory Medicine, Charit\u00e9 Universit\u00e4tsmedizin, Berlin, Germany" + }, + { + "author_name": "Christoph B Messner", + "author_inst": "Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, United Kingdom; Department of Biochemistry, Charit\u00e9 Universit\u00e4tsmedizin Berlin," + }, + { + "author_name": "Markus Ralser", + "author_inst": "Molecular Biology of Metabolism Laboratory, The Francis Crick Institute, London, United Kingdom; Department of Biochemistry, Charit\u00e9 Universit\u00e4tsmedizin Berlin," } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "type": "new results", + "category": "systems biology" }, { "rel_doi": "10.1101/2022.06.01.22275674", @@ -303764,47 +304303,39 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2022.05.31.22275814", - "rel_title": "Heterogeneous evolution of SARS-CoV-2 seroprevalence in school-age children: Results from the Ciao Corona study in November-December 2021 in the canton of Zurich", + "rel_doi": "10.1101/2022.05.31.494170", + "rel_title": "Accurate Prediction of Virus-Host Protein-Protein Interactions via a Siamese Neural Network Using Deep Protein Sequence Embeddings", "rel_date": "2022-05-31", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.31.22275814", - "rel_abs": "BackgroundMuch remains unknown regarding the evolution of SARS-CoV-2 seroprevalence and variability in seropositive children in districts, schools, and classes as only a few school-based co-hort studies exist. Vaccination of children, initiated at different times for different age groups, adds additional complexity to understand how seroprevalence developed in the school aged population.\n\nAimWe investigated the evolution of SARS-CoV-2 seroprevalence in children and its variability in districts, schools, and classes in Switzerland from June/July 2020 to November/December 2021.\n\nMethodsIn this school-based cohort study, SARS-CoV-2 antibodies were measured in primary and secondary school children from randomly selected schools in the canton of Zurich in October/November 2020, March/April 2021, and November/December 2021. Seroprevalence was estimated using Bayesian logistic regression to adjust for test sensitivity and specificity. Variability of seroprevalence between school classes was expressed as maximum minus minimum sero-prevalence in a class and summarized as median (interquartile range).\n\nResults1875 children from 287 classes in 43 schools were tested, with median age 12 (range 6-17), 51% 12+ vaccinated. Seroprevalence increased from 5.6% (95% CrI: 3.5-7.6%) to 31.1% (27.0-36.1%) in unvaccinated children, and 46.4% (42.6-50.9%) in all children (including vaccinated). Earlier in the pandemic, seropositivity rates in primary schools were similar to or slightly higher (<5%) than those in secondary schools, but by late 2021, primary schools had 12.3% (44.3%) lower seroprevalence for unvaccinated (all) subjects. Variability in seroprevalence among districts and schools increased more than twofold over time, and in classes from 11% (7-17%) to 40% (22-49%).\n\nConclusionSeroprevalence in children increased greatly, especially in 2021 following introduction of vaccines. Variability in seroprevalence was high and increased substantially over time, suggesting complex transmission chains.\n\nTrial Registration: ClinicalTrials.gov NCT04448717", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.31.494170", + "rel_abs": "Prediction and understanding of tissue-specific virus-host interactions have relevance for the development of novel therapeutic interventions strategies. In addition, virus-like particles (VLPs) open novel opportunities to deliver therapeutic compounds to targeted cell types and tissues. Given our incomplete knowledge of virus-host interactions on one hand and the cost and time associated with experimental procedures on the other, we here propose a novel deep learning approach to predict virus-host protein-protein interactions (PPIs). Our method (Siamese Tailored deep sequence Embedding of Proteins - STEP) is based on recent deep protein sequence embedding techniques, which we integrate into a Siamese neural network architecture. After evaluating the high prediction performance of STEP in comparison to an existing method, we apply it to two use cases, SARS-CoV-2 and John Cunningham polyomavirus (JCV), to predict virus protein to human host interactions. For the SARS-CoV-2 spike protein our method predicts an interaction with the sigma 2 receptor, which has been suggested as a drug target. As a second use case, we apply STEP to predict interactions of the JCV VP1 protein showing an enrichment of PPIs with neurotransmitters, which are known to function as an entry point of the virus into glial brain cells. In both cases we demonstrate how recent techniques from the field of Explainable AI (XAI) can be employed to identify those parts of a pair of sequences, which most likely contribute to the protein-protein interaction. Altogether our work highlights the potential of deep sequence embedding techniques originating from the field of natural language processing as well as XAI methods for the analysis of biological sequences. We have made our method publicly available via GitHub.\n\nThe bigger pictureDevelopment of novel cell and tissue specific therapies requires a profound knowledge about protein-protein interactions (PPIs). Identifying these PPIs with experimental approaches such as biochemical assays or yeast two-hybrid screens is cumbersome, costly, and at the same time difficult to scale. Computational approaches can help to prioritize huge amounts of possible PPIs by learning from biological sequences plus already-known PPIs. In this work, we developed a novel approach (Siamese Tailored deep sequence Embedding of Proteins - STEP) that is based on recent deep protein sequence embedding techniques, which we integrate into a Siamese neural network architecture. We use this approach to train models by utilizing protein sequence information and known PPIs. After evaluating the high prediction performance of STEP in comparison to an existing method, we apply it to two use cases, SARS-CoV-2 and John Cunningham polyomavirus (JCV), to predict virus protein to human host interactions. Altogether our work highlights the potential of deep sequence embedding techniques originating from the field of natural language processing as well as Explainable AI methods for the analysis of biological sequence data.\n\nHighlightsO_LIA novel deep learning approach (STEP) predicts virus protein to human host protein interactions based on recent deep protein sequence embedding and a Siamese neural network architecture\nC_LIO_LIPrediction of protein-protein interactions of the JCV VP1 protein and of the SARS-CoV-2 spike protein\nC_LIO_LIIdentification of parts of sequences that most likely contribute to the protein-protein interaction using Explainable AI (XAI) techniques\nC_LI\n\nData Science MaturityDSML 3: Development/Pre-production: Data science output has been rolled out/validated across multiple domains/problems", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Sarah R Haile", - "author_inst": "University of Zurich, Epidemiology, Biostatistics and Prevention Institute (EBPI)" - }, - { - "author_name": "Alessia Raineri", - "author_inst": "University of Zurich, Epidemiology, Biostatistics and Prevention Institute (EBPI)" - }, - { - "author_name": "Sonja Rueegg", - "author_inst": "University of Zurich, Epidemiology, Biostatistics and Prevention Institute (EBPI)" + "author_name": "Sumit Madan", + "author_inst": "Fraunhofer SCAI" }, { - "author_name": "Thomas Radtke", - "author_inst": "University of Zurich, Epidemiology, Biostatistics and Prevention Institute (EBPI)" + "author_name": "Victoria Demina", + "author_inst": "NEUWAY Pharma GmbH" }, { - "author_name": "Agne Ulyte", - "author_inst": "Epidemiology, Biostatistics and Prevention Institute (EBPI)" + "author_name": "Marcus Stapf", + "author_inst": "NEUWAY Pharma GmbH" }, { - "author_name": "Milo A. Puhan", - "author_inst": "Epidemiology, Biostatistics and Prevention Institute (EBPI)" + "author_name": "Oliver Ernst", + "author_inst": "NEUWAY Pharma GmbH" }, { - "author_name": "Susi Kriemler", - "author_inst": "Epidemiology, Biostatistics and Prevention Institute (EBPI)" + "author_name": "Holger Froehlich", + "author_inst": "Fraunhofer SCAI" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2022.05.28.22275432", @@ -305342,51 +305873,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.05.27.22275708", - "rel_title": "Identifying COVID-19 phenotypes using cluster analysis and assessing their clinical outcomes", + "rel_doi": "10.1101/2022.05.28.22275707", + "rel_title": "Comparison of the burnout among medical residents before and during the pandemic: not more exhausted but less accomplished", "rel_date": "2022-05-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.27.22275708", - "rel_abs": "Multiple clinical phenotypes have been proposed for COVID-19, but few have stemmed from data-driven methods. We aimed to identify distinct phenotypes in patients admitted with COVID-19 using cluster analysis, and compare their respective characteristics and clinical outcomes.\n\nWe analyzed the data from 547 patients hospitalized with COVID-19 in a Canadian academic hospital from January 1, 2020, to January 30, 2021. We compared four clustering algorithms: K-means, PAM (partition around medoids), divisive and agglomerative hierarchical clustering. We used imaging data and 34 clinical variables collected within the first 24 hours of admission to train our algorithm. We then conducted survival analysis to compare clinical outcomes across phenotypes and trained a classification and regression tree (CART) to facilitate phenotype interpretation and phenotype assignment.\n\nWe identified three clinical phenotypes, with 61 patients (17%) in Cluster 1, 221 patients (40%) in Cluster 2 and 235 (43%) in Cluster 3. Cluster 2 and Cluster 3 were both characterized by a low-risk respiratory and inflammatory profile, but differed in terms of demographics. Compared with Cluster 3, Cluster 2 comprised older patients with more comorbidities. Cluster 1 represented the group with the most severe clinical presentation, as inferred by the highest rate of hypoxemia and the highest radiological burden. Mortality, mechanical ventilation and ICU admission risk were all significantly different across phenotypes.\n\nWe conducted a phenotypic analysis of adult inpatients with COVID-19 and identified three distinct phenotypes associated with different clinical outcomes. Further research is needed to determine how to properly incorporate those phenotypes in the management of patients with COVID-19.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.28.22275707", + "rel_abs": "ObjectiveThis study aims to compare the level of burnout syndrome in medical residents before and during the COVID-19 pandemic and identify potential risk factors.\n\nMethodsThis cross-sectional study was conducted on medical residents from three different university hospitals in Turkey in March 2021, one year after the pandemic hit Turkey. Burnout is measured by the Maslach Burnout Inventory which assesses three dimensions of it: emotional exhaustion, depersonalization, and personal accomplishment. Collected data were combined and compared with data from a previous study held in the same hospitals in December 2019, three months before the pandemic.\n\nResults412 medical residents from three universities participated. The mean age was 27.8{+/-}2.4 and half of them were female. Compared to pre-pandemic levels, no significant differences in emotional exhaustion (pre:19.0{+/-}7.6 post:18.8{+/-}7.8), depersonalization (pre:7.3{+/-}4.3 post:7.2{+/-}4.4), and personal accomplishment (pre:20.8{+/-}5.1 post:21.1{+/-}5) scores were observed one year after the pandemic. Adjusting for confounders, multiple linear regression models indicated that those who are female, are in a surgical speciality, have vulnerable cohabitants, and have more night shifts face higher emotional exhaustion. Depersonalisation is higher among those who spent more years in residency, have more night shifts, or have COVID-19 outpatient duty. Females and those who have vulnerable cohabitants have lower levels of Personal Achievement.\n\nConclusionThis study does not support the hypothesis that pandemic increases the burnout levels. Yet it identifies a couple of pandemic-related factors that are associated with burnout and confirms the association of several previously known factors.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Eric Yamga", - "author_inst": "CHUM: Centre Hospitalier de L'Universite de Montreal" - }, - { - "author_name": "Louis Mullie", - "author_inst": "CHUM: Centre Hospitalier de L'Universite de Montreal" - }, - { - "author_name": "Madeleine Durand", - "author_inst": "CHUM: Centre Hospitalier de L'Universite de Montreal" + "author_name": "H\u00fcseyin K\u00fc\u00e7\u00fckali", + "author_inst": "Queen's University Belfast" }, { - "author_name": "Alexandre Cadrin-Chenevert", - "author_inst": "Centre hospitalier de Lanaudi\u00e8re: Centre hospitalier de Lanaudiere" + "author_name": "Sezanur Nazl\u0131 T\u00fcrko\u011flu", + "author_inst": "Bezmialem Vakif University" }, { - "author_name": "An Tang", - "author_inst": "CHUM: Centre Hospitalier de L'Universite de Montreal" + "author_name": "Shams Hasanli", + "author_inst": "University of Health Sciences" }, { - "author_name": "Emmanuel Montagnon", - "author_inst": "CHUM Research Centre: Centre Hospitalier de l'Universite de Montreal Centre de Recherche" + "author_name": "Fatma Nur Dayan\u0131r \u00c7ok", + "author_inst": "Dicle University" }, { - "author_name": "Carl Chartrand-Lefebvre", - "author_inst": "CHUM: Centre Hospitalier de L'Universite de Montreal" + "author_name": "Hazal Cansu Culpan", + "author_inst": "Karaman Central Community Health Center" }, { - "author_name": "Micha\u00ebl Chass\u00e9", - "author_inst": "Centre Hospitalier de l'Universite de Montreal Centre de Recherche" + "author_name": "Osman Hayran", + "author_inst": "Istanbul Medipol University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2022.05.28.22275691", @@ -307324,49 +307847,125 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.05.24.22275478", - "rel_title": "Effective antiviral regimens to reduce COVID-19 hospitalizations: a systematic comparison of randomized controlled trials", + "rel_doi": "10.1101/2022.05.25.22275533", + "rel_title": "Intrahost evolution and forward transmission of a novel SARS-CoV-2 Omicron BA.1 subvariant", "rel_date": "2022-05-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.24.22275478", - "rel_abs": "BackgroundDuring pandemics, early outpatient treatments reduce the health system burden. Randomized controlled trials (RCTs) in COVID-19 outpatients have tested therapeutic agents, but no RCT or systematic review has been conducted comparing the efficacy of the main outpatient treatment classes to each other. We aimed in this systematic review of outpatient RCTs in COVID-19 to compare hospitalisation rate reductions with four classes of treatment: convalescent plasma, monoclonal antibodies, small molecule antivirals and repurposed drugs.\n\nMethodsWe conducted a systematic review and meta-analysis of all COVID-19 outpatient RCTs that included the endpoint of progression to hospitalisation. We assembled, from multiple published and preprint databases, participant characteristics, hospitalisations, resolution of symptoms and mortality from January 2020 to May 21, 2023. The risk of bias from COVID-NMA was incorporated into the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. We measured heterogeneity with I2. Meta-analysis by a random or fixed effect model dependent on significant heterogeneity (I2 >50%) was performed. The protocol was registered in PROSPERO, CRD42022369181.\n\nFindingsThe search identified 281 studies of which 54 RCTs for 30 diverse interventions were included in the final analysis. These trials, performed largely in unvaccinated cohorts during pre-Omicron waves, focused on populations with at least one COVID-19 hospitalisation risk factor. Grouping by class, monoclonal antibodies (OR=0.31 [95% CI=0.24-0.40]) had highest efficacy, followed by COVID-19 convalescent plasma (CCP) (OR=0.69 [95% CI=0.53 to 0.90]) and small molecule antivirals (OR=0.78 [95% CI=0.48-1.33]) for hospital reduction. Repurposed drugs (OR=0.82 [95% CI-0.72-0.93]) had lower efficacy.\n\nInterpretationInasmuch as omicron sublineages (XBB and BQ.1.1) are now resistant to monoclonal antibodies, oral antivirals are the preferred treatment in outpatients where available, but intravenous interventions from convalescent plasma to remdesivir are also effective and necessary in constrained medical resource settings or for acute and chronic COVID-19 in the immunocompromised.\n\nFundingUS Department of Defense and National Institute of Health\n\nResearch in context Evidence before this studyWe systematically searched the published and preprint data bases for outpatient randomized clinical trials of treatment of COVID-19 disease with hospitalisation as an endpoint. Previous systematic reviews and meta-analyses have confined the reviews to specific classes such as convalescent plasma, monoclonal antibodies, small molecule antivirals or repurposed drugs. Few comparisons have been made between these therapeutic classes. The trials took place both in the pre-vaccination and the vaccination era, spanning periods with dominance of different COVID variants. We sought to compare efficacy between the four classes of treatments listed above when used in outpatient COVID-19 patients as shown in randomized, placebo-controlled trials.\n\nAdded value of this studyThis systematic review and meta-analysis brings together trials that assessed hospitalisation rates in diverse COVID-19 outpatient populations varying in age and comorbidities, permitting us to assess the efficacy of interventions both within and across therapeutic classes. While heterogeneity exists within and between these intervention classes, the meta-analysis can be placed in context of trial diverse populations over variant time periods of the pandemic. At present most of the world population has either had COVID-19 or been vaccinated with a high seropositivity rate, indicating that future placebo-controlled trials will be limited because of the sample sizes required to document hospitalisation outcomes.\n\nImplications of all the available evidenceNumerous diverse therapeutic tools need to be ready for a resilient response to changing SARS-CoV-2 variants in both immunocompetent and immunocompromised COVID-19 outpatient populations. To date few head-to-head randomized controlled trials (RCTs) has compared treatment options for COVID-19 outpatients, making comparisons and treatment choices difficult. This systematic review compares outcomes among RCTs of outpatient therapy for COVID-19, taking into account time between onset of symptoms and treatment administration. We found that small-chemical antivirals, convalescent plasma and monoclonal antibodies had comparable efficacy between classes and amongst interventions within the four classes. Monoclonals have lost efficacy with viral mutation, and chemical antivirals have contraindications and adverse events, while intravenous interventions like convalescent plasma or remdesivir remain resilient options for the immunocompromised, and, in the case of CCP, in resource constrained settings with limited availability of oral drugs.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.25.22275533", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWPersistent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections have been reported in immune-compromised individuals and people undergoing immune-modulatory treatments. Although intrahost evolution has been documented, to our knowledge, no direct evidence of subsequent transmission and stepwise adaptation is available.\n\nHere we describe sequential persistent SARS-CoV-2 infections in three individuals that led to the emergence, forward transmission, and continued evolution of a new Omicron sublineage, BA.1.23, over an eight-month period. The initially transmitted BA.1.23 variant encoded seven additional amino acid substitutions within the spike protein (E96D, R346T, L455W, K458M, A484V, H681R, A688V), and displayed substantial resistance to neutralization by sera from boosted and/or Omicron BA.1-infected study participants. Subsequent continued BA.1.23 replication resulted in additional substitutions in the spike protein (S254F, N448S, F456L, M458K, F981L, S982L) as well as in five other virus proteins.\n\nOur findings demonstrate that the Omicron BA.1 lineage can diverge further from its already exceptionally mutated genome during persistent infection in more than one host, and also document ongoing transmission of these novel variants. There is an urgent need to implement strategies to prevent prolonged SARS-CoV-2 replication and to limit the spread of newly emerging, neutralization-resistant variants in vulnerable patients.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "David J Sullivan", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Ana S. Gonzalez-Reiche", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" }, { - "author_name": "Daniele Focosi", - "author_inst": "Pisa University Hospital" + "author_name": "Hala Alshammary", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" }, { - "author_name": "Daniel F Hanley", - "author_inst": "Johns Hopkins University" + "author_name": "Sarah Schaefer", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" }, { - "author_name": "Mario Cruciani", - "author_inst": "Division of Hematology, Carlo Poma Hospital" + "author_name": "Gopi Patel", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" }, { - "author_name": "Massimo Franchini", - "author_inst": "Pisa University Hospital" + "author_name": "Jose Polanco", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" }, { - "author_name": "Jiangda Ou", - "author_inst": "Johns Hopkins University" + "author_name": "Juan Manuel Carreno Quiroz", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Arturo Casadevall", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Angela Amoako", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" }, { - "author_name": "Nigel Paneth", - "author_inst": "Michigan State University" + "author_name": "Aria Rooker", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Christian Cognigni", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Daniel Floda", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Adriana van de Guchte", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Zain Khalil", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Keith Farrugia", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Nima Assad", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Jian Zhang", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Bremy Alburquerque", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Levy Sominsky", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Komal Srivastava", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Robert Sebra", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Juan David Ramirez", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Radhika Banu", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Paras Shrestha", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Alberto Paniz-Mondolfi", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Emilia Mia Sordillo", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Viviana Simon", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" + }, + { + "author_name": "Harm van Bakel", + "author_inst": "Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -309594,31 +310193,147 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2022.05.24.22275529", - "rel_title": "Depressive and anxiety symptoms during the COVID-19 pandemic: A two-year follow-up", + "rel_doi": "10.1101/2022.05.23.22275444", + "rel_title": "Evaluation of triage checklist for mild COVID-19 outpatients in predicting subsequent emergency department visits and hospitalization during isolation period", "rel_date": "2022-05-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.24.22275529", - "rel_abs": "BackgroundThere has been much research into the mental health impact of the COVID-19 pandemic and how it is related to time-invariant individual characteristics (e.g. age and gender). However, there is still a lack of research showing long-term trajectories of mental health across different stages of the pandemic. And little is known regarding the longitudinal association of time-varying contextual and individual factors (e.g. COVID-19 policy response and pandemic intensity) with mental health outcomes. This study aimed to provide a longitudinal profile of how depressive and anxiety symptoms changed by month between March 2020 and April 2022, and to examine their longitudinal associations with time-varying contextual and individual level factors.\n\nMethods and findingsDrawing data from a large panel study of over 58,000 adults living in England, we showed that mental health changes were largely in line with changes in COVID-19 policy response and pandemic intensity. Further, data were analysed using fixed-effects, with models fitted separately across three stages of the COVID-19 pandemic. We found that more stringent policy response was associated with increased mental health symptoms, in particular during lockdown periods. Higher COVID-19 deaths were also associated with poorer mental health, but this association weakened over time. Finally, there was also evidence for the longitudinal association of mental health with individual level factors, including confidence in government/healthcare/essentials, COVID-19 knowledge, COVID-19 stress, COVID-19 infection and social support.\n\nConclusionsOur results provided empirical evidence on how changes in contextual and individual level factors were related to depressive and anxiety symptoms. While some factors clearly acted as consistent predictors of mental health during a pandemic, other factors were dependent on the specific situations occurring within society. This could provide important implications for policy making and for a better understanding of mental health of the general public during a national or global health crisis.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.23.22275444", + "rel_abs": "Background and objectiveLimited evidence exists regarding the outcomes of patients with coronavirus disease 2019 (COVID-19) who are not hospitalized. This study aimed to assess the outcomes for mild COVID-19 patients in terms of emergency department (ED) visits and hospital admission given initial outpatient triage evaluation and to identify the triage factors affecting these outcomes.\n\nMethodsThis retrospective cohort study investigated adult COVID-19 Japanese patients who were triaged at Nagasaki University Hospital between April 1, 2021, and May 31, 2021. A triage checklist with 30 factors was used to identify patients requiring hospitalization. Patients recommended for isolation were followed up for later ED visit or hospital admission.\n\nResultsOverall, 338 COVID-19 patients (mean age, 44.7; 45% women) visited the clinic at an average of 5.4 days after symptom onset. Thirty-six patients (10.6%) were hospitalized from triage, and the rest were recommended for isolation. Seventy-two non-hospitalized patients (23.8%) visited ED during their isolation period, and 30 (9.9%) were hospitalized after ED evaluation. The mean duration to ED visit and hospitalization after symptom onset were 8.8 and 9.7 days, respectively. Checklist factors associated with hospitalization during the isolation period were age > 50 years, obesity with BMI > 25, underlying hypertension, tachycardia with HR > 100/min or blood pressure >135 mmHg at triage, and >{square}3-day delay in hospital visit after symptom onset.\n\nConclusionClinicians should be wary of COVID-19 patients with above risk factors and prompt them to seek follow-up assessment by a medical professional.\n\nSUMMARY AT A GLANCEOverall, 338 patients with mild COVID-19 were retrospectively followed up. Factors such as age >{square}50 years, BMI{square}> {square}25, underlying hypertension, high blood pressure and tachycardia at triage, and delayed visit after symptom onset were associated with emergency department visit and hospitalization during the isolation period.", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Feifei Bu", - "author_inst": "UCL" + "author_name": "Yasuhiro Tanaka", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Graduate School of Biomedical Sciences/Department of Respiratory Medicine, Nagasaki University Hospital" }, { - "author_name": "Andrew Steptoe", - "author_inst": "UCL" + "author_name": "Kazuko Yamamoto", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" }, { - "author_name": "Daisy Fancourt", - "author_inst": "University College London" + "author_name": "Shimpei Morimoto", + "author_inst": "Clinical Research Center, Nagasaki University Hospital" + }, + { + "author_name": "Takeshi Nabeshima", + "author_inst": "Department of Virology, Institute of Tropical Medicine, Nagasaki University" + }, + { + "author_name": "Kayoko Matsushima", + "author_inst": "Medical Education Development Center, Nagasaki University Hospital" + }, + { + "author_name": "Hiroshi Ishimoto", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Nobuyuki Ashizawa", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital/Infection Control and Education Center, Nagasaki University Hospital" + }, + { + "author_name": "Tatsuro Hirayama", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Kazuaki Takeda", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Hiroshi Gyotoku", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Naoki Iwanaga", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Shinnosuke Takemoto", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Susumu Fukahori", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Takahiro Takazono", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital/Department of Infectious Diseases, Nagasaki University Graduate School of Biomedical Sciences" + }, + { + "author_name": "Hiroyuki Yamaguchi", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital/Clinical Oncology Center, Nagasaki University Hospital" + }, + { + "author_name": "Takashi Kido", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Noriho Sakamoto", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Naoki Hosogaya", + "author_inst": "Clinical Research Center, Nagasaki University Hospital" + }, + { + "author_name": "Shogo Akabame", + "author_inst": "Department of General Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Takashi Sugimoto", + "author_inst": "Department of General Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Hirotomo Yamanashi", + "author_inst": "Department of General Medicine, Nagasaki University Hospital/Department of Infectious Diseases, Nagasaki University Hospital" + }, + { + "author_name": "Kosuke Matsui", + "author_inst": "Department of Infectious Diseases, Nagasaki University Hospital" + }, + { + "author_name": "Mai Izumida", + "author_inst": "Department of Infectious Diseases, Nagasaki University Hospital" + }, + { + "author_name": "Ayumi Fujita", + "author_inst": "Infection Control and Education Center, Nagasaki University Hospital" + }, + { + "author_name": "Masato Tashiro", + "author_inst": "Infection Control and Education Center, Nagasaki University Hospital/Department of Infectious Diseases, Nagasaki University Graduate School of Biomedical Scienc" + }, + { + "author_name": "Takeshi Tanaka", + "author_inst": "Infection Control and Education Center, Nagasaki University Hospital" + }, + { + "author_name": "Koya Ariyoshi", + "author_inst": "Department of Infectious Diseases, Nagasaki University Hospital" + }, + { + "author_name": "Akitsugu Furumoto", + "author_inst": "Infectious Diseases Experts Training Center, Nagasaki University Hospital" + }, + { + "author_name": "Koichi Morita", + "author_inst": "Department of Virology, Institute of Tropical Medicine, Nagasaki University" + }, + { + "author_name": "Koichi Izumikawa", + "author_inst": "Infection Control and Education Center, Nagasaki University Hospital/Department of Infectious Diseases, Nagasaki University Graduate School of Biomedical Scienc" + }, + { + "author_name": "Katsunori Yanagihara", + "author_inst": "Department of Laboratory Medicine, Nagasaki University Hospital" + }, + { + "author_name": "Hiroshi Mukae", + "author_inst": "Department of Respiratory Medicine, Nagasaki University Graduate School of Biomedical Sciences/Department of Respiratory Medicine, Nagasaki University Hospital" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2022.05.24.493348", @@ -311392,37 +312107,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.05.21.492928", - "rel_title": "Modeling suggests that multiple immunizations or infections will reveal the benefits of updating SARS-CoV-2 vaccines", + "rel_doi": "10.1101/2022.05.21.492903", + "rel_title": "Reduced Neutralization of SARS-CoV-2 Omicron Variant in Sera from SARS-CoV-1 Survivors after 3-dose of Vaccination", "rel_date": "2022-05-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.21.492928", - "rel_abs": "When should vaccines to evolving pathogens such as SARS-CoV-2 be updated? Our computational models address this focusing on updating SARS-CoV-2 vaccines to the currently circulating Omicron variant. Current studies typically compare the antibody titers to the new variant following a single dose of the original-vaccine versus the updated-vaccine in previously immunized individuals. These studies find that the updated-vaccine does not induce higher titers to the vaccine-variant compared with the original-vaccine, suggesting that updating may not be needed. Our models recapitulate this observation but suggest that vaccination with the updated-vaccine generates qualitatively different humoral immunity, a small fraction of which is specific for unique epitopes to the new variant. Our simulations suggest that these new variant-specific responses could dominate following subsequent vaccination or infection with either the currently circulating or future variants. We suggest a two-dose strategy for determining if the vaccine needs updating and for vaccinating high-risk individuals.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.21.492903", + "rel_abs": "Recent studies found that Omicron variant escapes vaccine-elicited immunity. Interestingly, potent cross-clade pan-sarbecovirus neutralizing antibodies were found in survivors of the infection by SARS-CoV-1 after BNT162b2 mRNA vaccination (N Engl J Med. 2021 Oct 7;385(15):1401-1406). These pan-sarbecovirus neutralizing antibodies were observed to efficiently neutralize the infection driven by the S protein from both SARS-CoV and multiple SARS-CoV-2 variants of concern (VOC) including B.1.1.7 (Alpha), B.1.351 (Beta), and B.1.617.2 (Delta). However, whether these cross-reactive antibodies could neutralize the Omicron variant is still unknown. Based on the data collected from a cohort of SARS-CoV-1 survivors received 3-dose of immunization, our studies reported herein showed that a high level of neutralizing antibodies against both SARS-CoV-1 and SARS-CoV-2 were elicited by a 3rd-dose of booster vaccination of protein subunit vaccine ZF2001. However, a dramatically reduced neutralization of SARS-CoV-2 Omicron Variant (B.1.1.529) is observed in sera from these SARS-CoV-1 survivors received 3-dose of Vaccination. Our results indicates that the rapid development of pan-variant adapted vaccines is warranted.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Rajat Desikan", - "author_inst": "GSK" + "author_name": "Xuesen Zhao", + "author_inst": "Institute of Infectious disease, Beijing Ditan Hospital, Capital Medical University" }, { - "author_name": "Susanne L Linderman", - "author_inst": "Emory University" + "author_name": "Danying Chen", + "author_inst": "Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, Ch" }, { - "author_name": "Carl W. Davis", - "author_inst": "Emory University School of Medicine" + "author_name": "Xiaohua Hao", + "author_inst": "National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, P.R. China." }, { - "author_name": "Veronika I Zarnitsyna", - "author_inst": "Emory University School of Medicine" + "author_name": "Yaruo Qiu", + "author_inst": "Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, Ch" }, { - "author_name": "Hasan R Ahmed", - "author_inst": "Emory University" + "author_name": "Juan Du", + "author_inst": "Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, Ch" }, { - "author_name": "Rustom Antia", - "author_inst": "Emory University" + "author_name": "Yuanyuan Zhang", + "author_inst": "Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, Ch" + }, + { + "author_name": "Fan Xiao", + "author_inst": "Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, Ch" + }, + { + "author_name": "Xinglin Li", + "author_inst": "Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, Ch" + }, + { + "author_name": "Yanjun Song", + "author_inst": "Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, Ch" + }, + { + "author_name": "Rui Song", + "author_inst": "National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, P.R. China" + }, + { + "author_name": "Xi Wang", + "author_inst": "Beijing Key Laboratory of Emerging Infectious Diseases, Institute of Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, Ch" + }, + { + "author_name": "Ronghua Jin", + "author_inst": "National Center for Infectious Diseases, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, P.R. China" } ], "version": "1", @@ -313434,55 +314173,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.05.20.492819", - "rel_title": "Revealing druggable cryptic pockets in the Nsp-1 of SARS-CoV-2 and other \u03b2-coronaviruses by simulations and crystallography", + "rel_doi": "10.1101/2022.05.20.492834", + "rel_title": "SARS-CoV-2 Infects Peripheral and Central Neurons of Mice Before Viremia, Facilitated by Neuropilin-1", "rel_date": "2022-05-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.20.492819", - "rel_abs": "Non-structural protein 1 (Nsp1) is a main pathogenicity factor of - and {beta}-coronaviruses. Nsp1 of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) suppresses the host gene expression by sterically blocking 40S host ribosomal subunits and promoting host mRNA degradation. This mechanism leads to the downregulation of the translation-mediated innate immune response in host cells, ultimately mediating the observed immune evasion capabilities of SARS-CoV-2. Here, by combining extensive Molecular Dynamics simulations, fragment screening and crystallography, we reveal druggable pockets in Nsp1. Structural and computational solvent mapping analyses indicate the partial crypticity of these newly discovered and druggable binding sites. The results of fragment-based screening via X-ray crystallography confirm the druggability of the major pocket of Nsp1. Finally, we show how the targeting of this pocket could disrupt the Nsp1-mRNA complex and open a novel avenue to design new inhibitors for other Nsp1s present in homologous {beta}-coronaviruses.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.20.492834", + "rel_abs": "Neurological symptoms associated with COVID-19, acute and long-term, suggest SARS-CoV-2 affects both central and peripheral nervous systems. Although studies have shown olfactory and hematogenous entry into the brain and neuroinflammation, little attention has been paid to the susceptibility of the peripheral nervous system to infection or to alternative routes of CNS invasion. We show that neurons in the central and peripheral nervous system are susceptible to productive infection with SARS-CoV-2. Infection of K18-hACE2 mice, wild-type mice, golden Syrian hamsters, and primary neuronal cultures demonstrate viral RNA, protein, and infectious virus in peripheral nervous system neurons and satellite glial cells, spinal cord, and specific brain regions. Moreover, neuropilin-1 facilitates SARS-CoV-2 neuronal infection. Our data show that SARS-CoV-2 rapidly invades and establishes a productive infection in the peripheral and central nervous system via direct invasion of neurons prior to viremia, which may underlie some cognitive and sensory symptoms associated with COVID-19.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Alberto Borsatto", - "author_inst": "University of Geneva" + "author_name": "Jonathan D. Joyce", + "author_inst": "Translational Biology, Medicine, and Health, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA; Center for Emerging Zoonotic and Arthropod-" }, { - "author_name": "Obaeda Akkad", - "author_inst": "University of Geneva" + "author_name": "Greyson A. Moore", + "author_inst": "Biomedical and Veterinary Science, Virginia Maryland College of Veterinary Medicine, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" }, { - "author_name": "Ioannis Galdadas", - "author_inst": "University of Geneva" + "author_name": "Poorna Goswami", + "author_inst": "Translational Biology, Medicine, and Health, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" }, { - "author_name": "Shumeng Ma", - "author_inst": "University College London" + "author_name": "Telvin L. Harrell", + "author_inst": "Biomedical and Veterinary Science, Virginia Maryland College of Veterinary Medicine, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" }, { - "author_name": "Shymaa Damfo", - "author_inst": "University College London" + "author_name": "Tina M Taylor", + "author_inst": "Population Health Sciences, Virginia Maryland College of Veterinary Medicine, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" }, { - "author_name": "Shozeb Haider", - "author_inst": "University College London School of Pharmacy" + "author_name": "Seth A Hawks", + "author_inst": "Biomedical Sciences and Pathobiology, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" }, { - "author_name": "Frank Kozielski", - "author_inst": "University College London" + "author_name": "Jillian C Green", + "author_inst": "Biomedical and Veterinary Science, Virginia Maryland College of Veterinary Medicine, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" }, { - "author_name": "Carolina Estarellas", - "author_inst": "University of Barcelona" + "author_name": "Mo Jia", + "author_inst": "Population Health Sciences, Virginia Maryland College of Veterinary Medicine, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" }, { - "author_name": "Francesco Luigi Gervasio", - "author_inst": "University of Geneva" + "author_name": "Neeharika Yallayi", + "author_inst": "College of Science, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" + }, + { + "author_name": "Emma H. Leslie", + "author_inst": "Translational Biology, Medicine, and Health, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" + }, + { + "author_name": "Nisha K Duggal", + "author_inst": "Biomedical Sciences and Pathobiology, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA; Center for Emerging Zoonotic and Arthropod-borne P" + }, + { + "author_name": "Christopher K. Thompson", + "author_inst": "School of Neuroscience, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA" + }, + { + "author_name": "Andrea S Bertke", + "author_inst": "Population Health Sciences, Virginia Maryland College of Veterinary Medicine, Virginia Polytechnic Institute & State University, Blacksburg, VA, USA; Center for" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "neuroscience" }, { "rel_doi": "10.1101/2022.05.20.492764", @@ -315368,35 +316123,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.05.19.22275055", - "rel_title": "How Should COVID-19 Vaccines be Distributed between the Global North and South? A Discrete Choice Experiment in Six European Countries", + "rel_doi": "10.1101/2022.05.18.492441", + "rel_title": "Comprehensive analysis of pathways in Coronavirus 2019 (COVID-19) using an unsupervised machine learning method", "rel_date": "2022-05-19", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.19.22275055", - "rel_abs": "BackgroundThe global distribution of COVID-19 vaccinations remains highly unequal. We examine public preferences in six European countries regarding the allocation of COVID-19 vaccines between the Global South and Global North.\n\nMethodsWe conducted online discrete choice experiments with adult participants in France (n=766), Germany (n=1964), Italy (n=767), Poland (n=670), Spain (n=925), and Sweden (n=938). Respondents were asked to decide which one of two candidates, who varied along four attributes: age, mortality risk, employment, and living in a low- or high-income country, should receive the vaccine first. We analysed the relevance of each attribute in allocation decisions using a conditional logit regression.\n\nResultsAcross countries, respondents selected candidates with a high mortality and infection risk, irrespective of whether the candidate lived in their own country. All else equal, respondents in Italy, France, Spain, and Sweden gave priority to a candidate from a low-income country, whereas German respondents were significantly more likely to choose the candidate from their own country. Female, younger, and more educated respondents were more favourable of an equitable vaccine distribution.\n\nConclusionsGiven these preferences for global solidarity, European governments should promote vaccine transfers to poorer world regions.\n\nFundingFunding was provided by the European Unions Horizon H2020 research and innovation programme under grant agreement 101016233 (PERISCOPE).", - "rel_num_authors": 4, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.18.492441", + "rel_abs": "The World Health Organization (WHO) introduced \"Coronavirus disease 19\" or \"COVID-19\" as a novel coronavirus in March 2020. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires the fast discovery of effective treatments to fight this worldwide crisis. Artificial intelligence and bioinformatics analysis pipelines can assist with finding biomarkers, explanations, and cures. Artificial intelligence and machine learning methods provide powerful infrastructures for interpreting and understanding the available data. On the other hand, pathway enrichment analysis, as a dominant tool, could help researchers discover potential key targets present in biological pathways of host cells that are targeted by SARS-CoV-2. In this work, we propose a two-stage machine learning approach for pathway analysis. During the first stage, four informative gene sets that can represent important COVID-19 related pathways are selected. These \"representative genes\" are associated with the COVID-19 pathology. Then, two distinctive networks were constructed for COVID-19 related signaling and disease pathways. In the second stage, the pathways of each network are ranked with respect to some unsupervised scorning method based on our defined informative features. Finally, we present a comprehensive analysis of the top important pathways in both networks. Materials and implementations are available at: https://github.com/MahnazHabibi/Pathway.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Janina Isabel Steinert", - "author_inst": "Technical University of Munich" - }, - { - "author_name": "Henrike Sternberg", - "author_inst": "Technical University of Munich" - }, - { - "author_name": "Giuseppe Alessandro Veltri", - "author_inst": "University of Trento" + "author_name": "Golnaz Taheri", + "author_inst": "KTH Royal Institute of Technology" }, { - "author_name": "Tim Buethe", - "author_inst": "Technical University of Munich" + "author_name": "Mahnaz Habibi", + "author_inst": "Department of Mathematics, Qazvin Branch, Islamic Azad University, Qazvin, Iran" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "systems biology" }, { "rel_doi": "10.1101/2022.05.17.22275187", @@ -316898,87 +317645,47 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.05.15.22275086", - "rel_title": "Clinical Performance of Direct RT-PCR Testing of Raw Saliva for Detection of SARS-CoV-2 in Symptomatic and Asymptomatic Individuals", + "rel_doi": "10.1101/2022.05.12.22274993", + "rel_title": "Applying machine-learning to rapidly analyse large qualitative text datasets to inform the COVID-19 pandemic response: Comparing human and machine-assisted topic analysis techniques", "rel_date": "2022-05-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.15.22275086", - "rel_abs": "RT-qPCR tests based on RNA extraction from nasopharyngeal swab samples are promoted as the \"gold standard\" for SARS-CoV-2 detection. However, self-collected saliva samples offer a non-invasive alternative more suited to high-throughput testing. This study evaluated the performance of TaqPath COVID-19 Fast PCR Combo Kit 2.0 assay for detection of SARS-CoV-2 in raw saliva relative to a lab-developed direct RT-qPCR test (SalivaDirect-based PCR) and a RT-qPCR test based on RNA extraction from NPS samples. Both samples were collected from symptomatic and asymptomatic individuals (N=615). Saliva samples were tested for SARS-CoV-2 using the TaqPath COVID-19 Fast PCR Combo Kit 2.0 and the SalivaDirect-based PCR, while RNA extracts from NPS samples were tested by RT-qPCR according to the Irish national testing system. The TaqPath COVID-19 Fast PCR detected SARS-CoV-2 in 52 saliva samples, of which 51 were also positive with the SalivaDirect-based PCR. 49 samples displayed concordant results with the NPS extraction-based method, while three samples were positive on raw saliva. Among the negative samples, 10 discordant cases were found with the TaqPath COVID-19 Fast PCR (PPA-85.7%; NPA-99.5%), when compared to the RNA extraction-based NPS method, performing similarly to the SalivaDirect-based PCR (PPA-87.5%; NPA-99.5%). The direct RT-qPCR testing of saliva samples shows high concordance with NPS extraction-based method for SARS-CoV-2 detection, providing a cost-effective and highly-scalable system for high-throughput COVID-19 rapid-testing.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.12.22274993", + "rel_abs": "BackgroundMachine-assisted topic analysis (MATA) uses artificial intelligence methods to assist qualitative researchers to analyse large amounts of textual data. This could allow qualitative researchers to inform and update public health interventions in real-time, to ensure they remain acceptable and effective during rapidly changing contexts (such as a pandemic). In this novel study we aimed to understand the potential for such approaches to support intervention implementation, by directly comparing MATA and human-only thematic analysis techniques when applied to the same dataset (1472 free-text responses from users of the COVID-19 infection control intervention Germ Defence).\n\nMethodsIn MATA, the analysis process included an unsupervised topic modelling approach to identify latent topics in the text. The human research team then described the topics and identified broad themes. In human-only codebook analysis, an initial codebook was developed by an experienced qualitative researcher and applied to the dataset by a well-trained research team, who met regularly to critique and refine the codes. To understand similarities and difference, formal triangulation using a convergence coding matrix compared the findings from both methods, categorising them as agreement, complementary, dissonant, or silent.\n\nResultsHuman analysis took much longer (147.5 hours) than MATA (40 hours). Both human-only and MATA identified key themes about what users found helpful and unhelpful (e.g. Boosting confidence in how to perform the behaviours vs Lack of personally relevant content). Formal triangulation of the codes created showed high similarity between the findings. All codes developed from the MATA were classified as in agreement or complementary to the human themes. Where the findings were classified as complementary, this was typically due to slightly differing interpretations or nuance present in the human-only analysis.\n\nConclusionsOverall, the quality of MATA was as high as the human-only thematic analysis, with substantial time savings. For simple analyses that do not require an in-depth or subtle understanding of the data, MATA is a useful tool that can support qualitative researchers to interpret and analyse large datasets quickly. These findings have practical implications for intervention development and implementation, such as enabling rapid optimisation during public health emergencies.\n\nContributions to the literatureO_LINatural language processing (NLP) techniques have been applied within health research due to the need to rapidly analyse large samples of qualitative data. However, the extent to which these techniques lead to results comparable to human coding requires further assessment.\nC_LIO_LIWe demonstrate that combining NLP with human analysis to analyse free-text data can be a trustworthy and efficient method to use on large quantities of qualitative data.\nC_LIO_LIThis method has the potential to play an important role in contexts where rapid descriptive or exploratory analysis of very large datasets is required, such as during a public health emergency.\nC_LI", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Rosa Castillo-Bravo", - "author_inst": "National University of Ireland Galway" - }, - { - "author_name": "Noel Lucca", - "author_inst": "National University of Ireland Galway" - }, - { - "author_name": "Linyi Lai", - "author_inst": "National University of Ireland Galway" - }, - { - "author_name": "Killian Marlborough", - "author_inst": "National University of Ireland Galway" - }, - { - "author_name": "Galina Brychkova", - "author_inst": "National University of Ireland Galway" - }, - { - "author_name": "Charlie Lonergan", - "author_inst": "National University of Ireland Galway" - }, - { - "author_name": "Justin O'Grady", - "author_inst": "Quadram Institute Bioscience" - }, - { - "author_name": "Nabil-Fareed Alikhan", - "author_inst": "Quadram Institute Bioscience" - }, - { - "author_name": "Alexander Trotter", - "author_inst": "Quadram Institute Bioscience" - }, - { - "author_name": "Andrew Page", - "author_inst": "Quadram Institute Bioscience" - }, - { - "author_name": "Breda Smyth", - "author_inst": "National University of Ireland Galway" + "author_name": "Lauren Towler", + "author_inst": "University of Southampton" }, { - "author_name": "Peter C. McKeown", - "author_inst": "National University of Ireland Galway" + "author_name": "Paulina Bondaronek", + "author_inst": "Office for Health Improvement & Disparities, Department of Health and Social Care" }, { - "author_name": "Jelena Feenstra", - "author_inst": "Thermo Fisher Scientific" + "author_name": "Trisevgeni Papakonstantinou", + "author_inst": "Office for Health Improvement & Disparities, Department of Health and Social Care" }, { - "author_name": "Camilla Ulekleiv", - "author_inst": "Thermo Fisher Scientific" + "author_name": "Richard Aml\u00f4t", + "author_inst": "Behavioural Science and Insights Unit, UK Health Security Agency" }, { - "author_name": "Oceane Sorel", - "author_inst": "Thermo Fisher Scientific" + "author_name": "Tim Chadborn", + "author_inst": "Office for Health Improvement & Disparities, Department of Health and Social Care" }, { - "author_name": "Manoj Gandhi", - "author_inst": "Thermo Fisher Scientific" + "author_name": "Ben Ainsworth", + "author_inst": "University of Bath" }, { - "author_name": "Charles Spillane", - "author_inst": "National University of Ireland Galway" + "author_name": "Lucy Yardley", + "author_inst": "University of Bristol" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.05.14.22275079", @@ -318548,23 +319255,147 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.05.15.22273842", - "rel_title": "Summaries, Analysis and Simulations of Recent COVID-19 Epidemic in Shanghai", + "rel_doi": "10.1101/2022.05.16.492138", + "rel_title": "A live attenuated vaccine confers superior mucosal and systemic immunity to SARS-CoV-2 variants", "rel_date": "2022-05-16", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.15.22273842", - "rel_abs": "BackgroundAfter successfully preventing the spread of five wave COVID-19 epidemics in Shanghai, Omicron and Delta variants have been causing a surge COVID-19 infection in this city recently. Summaries, analysis and simulations for this wave epidemic are important issues.\n\nMethodsUsing differential equations and real word data, this study modelings and simulates the recent COVID-19 epidemic in Shanghai, estimates transmission rates, recovery rates, and blocking rates to symptomatic and asymptomatic infections, and symptomatic (infected) individuals death rates. Visual simulations predict the outcomes of this wave Shanghai epidemic. It compares parallely with the recent mainland China COVID-19 epidemics (RMCE).\n\nResultsThe simulation results were in good agreement with the real word data at the end points of 11 investigated time-intervals. Visual simulation results showed that on the day 90, the number of the current symptomatic (infected) individuals may be between 852 and 7314, the number of the current asymptomatic (infected) individuals charged in the observations may be between 10066 and 50292, the number of the current cumulative recovered symptomatic infected individuals may be between 52070 and 74687, the number of the current cumulative asymptomatic individuals discharged from the medical observations may be between 63509 and 5164535. The number of the died symptomatic individuals may be between 801 and 1226.\n\nO_LIThe transmission rate of the symptomatic infections caused by the symptomatic individuals was much lower than the corresponding average transmission rate of the RMCE.\nC_LIO_LIThe transmission rate of the asymptomatic infections caused by the symptomatic individuals was much higher than the first 90 days average transmission rate of RMCE.\nC_LIO_LIThe transmission rate of the symptomatic infections caused by the asymptomatic individuals was much lower than the first 60 days average transmission rate of RMCE, and was much higher than the last 60 days average transmission rate of RMCE.\nC_LIO_LIThe transmission rate to the asymptomatic infections caused by the asymptomatic individuals was much higher than the corresponding average transmission rate of RMCE.\nC_LIO_LIThe last 30 days average blocking rate to the symptomatic infections were lower than the last 30 days average blocking rates of RMCE\nC_LIO_LIThe last 30 days average blocking rate to the asymptomatic infections were much higher than the last 30 days average blocking rate of RMCE. However the first 30 days average blocking rate to the asymptomatic infections were much lower than the first 30 days average blocking rate of RMCE.\nC_LIO_LIThe first 37 days recovery rates of the symptomatic individuals were much lower than the corresponding first 70 days recovery rates of the symptomatic individuals of RMCE. The recovery rates between 38- and 52-days of the symptomatic individuals were much lower than the corresponding the recovery rates between 91- and 115-days of the symptomatic individuals of RMCE. The last weeks recovery rate was similar to the last weeks recovery rate of RMCE.\nC_LIO_LIThe first 30 days average recovery rate recovery rate to the symptomatic individuals were much lower than the first 30 days average recovery rate recovery rate of RMCE. The last 30 days average recovery rate recovery rate of the symptomatic individuals were still much lower than the last 30 days average recovery rate of RMCE.\nC_LI\n\nConclusionsThe last 30 days low blocking rates to the symptomatic infections, the first 30 days low blocking rates to the symptomatic infections to asymptomatic infections, the low recovery rates of the symptomatic and asymptomatic individuals, and the high transmission rate of the asymptomatic infections may be the reasons to cause the rapid spread of the recent Shanghai epidemic. It needs to implement more strict prevention and control strategies, rise the recovery rates of symptomatic and asymptomatic infections, and reduce the death rates for preventing the spread of this wave COVID-19 epidemic in Shanghai.", - "rel_num_authors": 1, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.16.492138", + "rel_abs": "Vaccines are a cornerstone in COVID-19 pandemic management. Here, we compare immune responses to and preclinical efficacy of the mRNA vaccine BNT162b2, an adenovirus-vectored spike vaccine, and the live-attenuated-virus vaccine candidate sCPD9 after single and double vaccination in Syrian hamsters. All regimens containing sCPD9 showed superior efficacy. The robust immunity elicited by sCPD9 was evident in a wide range of immune parameters after challenge with heterologous SARS-CoV-2 including rapid viral clearance, reduced tissue damage, fast differentiation of pre-plasmablasts, strong systemic and mucosal humoral responses, and rapid recall of memory T cells from lung tissue. Our results demonstrate that use of live-attenuated vaccines may offer advantages over available COVID-19 vaccines, specifically when applied as booster, and may provide a solution for containment of the COVID-19 pandemic.", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Lequan Min", - "author_inst": "University of Science and Technology Beijing" + "author_name": "Geraldine Nouailles", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Julia M Adler", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin and Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Peter Pennitz", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Stefan Peidli", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin and Humboldt-Universit\u00e4t zu Berlin" + }, + { + "author_name": "Gustavo Teixeira Alves", + "author_inst": "Max Delbruck Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany" + }, + { + "author_name": "Morris Baumgart", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Judith Bushe", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Anne Voss", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Alina Langenhagen", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Fabian Pott", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany and Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Julia Kazmierski", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany and Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Cengiz Goekeri", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany and Cyprus International University, Nicosia, Cyprus" + }, + { + "author_name": "Szandor Simmons", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Na Xing", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Christine Langner", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Ricardo Martin Vidal", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Azza Abdelgawad", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Susanne Herwig", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "G\u00fcnter Cichon", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Daniela Niemeyer", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany and German Center for Infection Research (DZIF), partner site Charit\u00e9, Berlin, Germany" + }, + { + "author_name": "Christian Drosten", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany and German Center for Infection Research (DZIF), partner site Charit\u00e9, Berlin, Germany" + }, + { + "author_name": "Christine Goffinet", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany and Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Markus Landthaler", + "author_inst": "Max Delbruck Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany and IRI Life Sciences, In" + }, + { + "author_name": "Nils Bl\u00fcthgen", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin and Humboldt-Universit\u00e4t zu Berlin" + }, + { + "author_name": "Haibo Wu", + "author_inst": "School of Life Sciences, Chongqing University, Chongqing 401331, China" + }, + { + "author_name": "Martin Witzenrath", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Achim D Gruber", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Samantha D Praktiknjo", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin and Humboldt-Universit\u00e4t zu Berlin" + }, + { + "author_name": "Nikolaus Osterrieder", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany and City University of Hong Kong, Kowloon, Hong Kong" + }, + { + "author_name": "Emanuel Wyler", + "author_inst": "Max Delbruck Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany" + }, + { + "author_name": "Dusan Kunec", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Jakob Trimpert", + "author_inst": "Freie Universit\u00e4t Berlin, Berlin, Germany" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.05.13.22274812", @@ -320190,43 +321021,99 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.05.09.22274776", - "rel_title": "Early detection of fraudulent COVID-19 products from Twitter chatter", - "rel_date": "2022-05-11", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.09.22274776", - "rel_abs": "Social media have served as lucrative platforms for misinformation and for promoting fraudulent products for the treatment, testing and prevention of COVID-19. This has resulted in the issuance of many warning letters by the United States Food and Drug Administration (FDA). While social media continue to serve as the primary platform for the promotion of such fraudulent products, they also present the opportunity to identify these products early by employing effective social media mining methods. In this study, we employ natural language processing and time series anomaly detection methods for automatically detecting fraudulent COVID-19 products early from Twitter. Our approach is based on the intuition that increases in the popularity of fraudulent products lead to corresponding anomalous increases in the volume of chatter regarding them. We utilized an anomaly detection method on streaming COVID-19-related Twitter data to detect potentially anomalous increases in mentions of fraudulent products. Our unsupervised approach detected 34/44 (77.3%) signals about fraudulent products earlier than the FDA letter issuance dates, and an additional 6/44 (13.6%) within a week following the corresponding FDA letters. Our proposed method is simple, effective and easy to deploy, and do not require high performance computing machinery unlike deep neural network-based methods.", - "rel_num_authors": 6, + "rel_doi": "10.1101/2022.05.09.491196", + "rel_title": "Persistent serum protein signatures define an inflammatory subset of long COVID", + "rel_date": "2022-05-10", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.09.491196", + "rel_abs": "Long COVID or post-acute sequelae of SARS-CoV-2 (PASC) is a clinical syndrome featuring diverse symptoms that can persist for months after acute SARS-CoV-2 infection. The etiologies are unknown but may include persistent inflammation, unresolved tissue damage, or delayed clearance of viral protein or RNA. Attempts to classify subsets of PASC by symptoms alone have been unsuccessful. To molecularly define PASC, we evaluated the serum proteome in longitudinal samples from 55 PASC individuals with symptoms lasting [≥]60 days after onset of acute infection and compared this to symptomatically recovered SARS-CoV-2 infected and uninfected individuals. We identified subsets of PASC with distinct signatures of persistent inflammation. Type II interferon signaling and canonical NF-{kappa}B signaling (particularly associated with TNF), were the most differentially enriched pathways. These findings help to resolve the heterogeneity of PASC, identify patients with molecular evidence of persistent inflammation, and highlight dominant pathways that may have diagnostic or therapeutic relevance.\n\nOne Sentence SummarySerum proteome profiling identifies subsets of long COVID patients with evidence of persistent inflammation including key immune signaling pathways that may be amenable to therapeutic intervention.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Abeed Sarker", - "author_inst": "Emory University" + "author_name": "Aarthi Talla", + "author_inst": "Allen Institute for Immunology; Seattle, USA" }, { - "author_name": "Sahithi Lakamana", - "author_inst": "Emory University" + "author_name": "Suhas V Vasaikar", + "author_inst": "Allen Institute for Immunology; Seattle, USA" }, { - "author_name": "Ruqi Liao", - "author_inst": "Emory University" + "author_name": "Gregory Szeto", + "author_inst": "Allen Institute for Immunology; Seattle, USA" }, { - "author_name": "Aamir Abbas", - "author_inst": "Carnegie Mellon University" + "author_name": "Maria P Lemos", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA" }, { - "author_name": "Yuan-Chi Yang", - "author_inst": "Emory University" + "author_name": "Julie L Czartoski", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA" }, { - "author_name": "Mohammed Al-Garadi", - "author_inst": "Emory University" + "author_name": "Hugh MacMillan", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA" + }, + { + "author_name": "Zoe Moodie", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA" + }, + { + "author_name": "Kristen W Cohen", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA" + }, + { + "author_name": "Lamar B Fleming", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA" + }, + { + "author_name": "Zachary Thomson", + "author_inst": "Allen Institute for Immunology; Seattle, USA" + }, + { + "author_name": "Lauren Okada", + "author_inst": "Allen Institute for Immunology; Seattle, USA" + }, + { + "author_name": "Lynne A Becker", + "author_inst": "Allen Institute for Immunology; Seattle, USA" + }, + { + "author_name": "Ernest M Coffey", + "author_inst": "Allen Institute for Immunology; Seattle, USA" + }, + { + "author_name": "Stephen C DeRosa", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA" + }, + { + "author_name": "Evan W Newell", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA" + }, + { + "author_name": "Peter J Skene", + "author_inst": "Allen Institute for Immunology; Seattle, USA" + }, + { + "author_name": "Xiaojun Li", + "author_inst": "Allen Institute for Immunology; Seattle, USA" + }, + { + "author_name": "Thomas F Bumol", + "author_inst": "Allen Institute for Immunology; Seattle, USA" + }, + { + "author_name": "M. Juliana McElrath", + "author_inst": "Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, USA" + }, + { + "author_name": "Troy R Torgerson", + "author_inst": "Allen Institute for Immunology; Seattle, USA" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.05.07.491004", @@ -322196,119 +323083,119 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.05.09.491201", - "rel_title": "COVID-19 mRNA third dose induces a unique hybrid immunity-like antibody response", + "rel_doi": "10.1101/2022.05.10.491266", + "rel_title": "Activated interstitial macrophages are a predominant target of viral takeover and focus of inflammation in COVID-19 initiation in human lung", "rel_date": "2022-05-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.09.491201", - "rel_abs": "The continuous evolution of SARS-CoV-2 generated highly mutated variants, like omicron BA.1 and BA.2, able to escape natural and vaccine-induced primary immunity1,2. The administration of a third dose of mRNA vaccines induces a secondary response with increased protection. We investigated, at single-cell level, the longitudinal evolution of the neutralizing antibody response in four donors after three mRNA doses3. A total of 4,100 spike protein specific memory B cells were single cell sorted and 350 neutralizing antibodies were identified. The third dose increased the antibody neutralization potency and breadth against all SARS-CoV-2 variants of concern as previously observed with hybrid immunity3. However, the B cell repertoire that stands behind the response is dramatically different. The increased neutralizing response was largely due to the expansion of B cell germlines poorly represented after two doses, and the reduction of germlines predominant after primary immunization such as IGHV3-53;IGHJ6-1 and IGHV3-66;IGHJ4-1. Divergently to hybrid immunity, cross-protection after a third dose was mainly guided by Class 1/2 antibodies encoded by IGHV1-58;IGHJ3-1 and IGHV1-69;IGHJ4-1 germlines. The IGHV2-5;IGHJ3-1 germline, which induced broadly cross-reactive Class 3 antibodies after infection or viral vector vaccination, was not induced by a third mRNA dose. Our data show that while neutralizing breadth and potency can be improved by different immunization regimens, each of them has a unique molecular signature which should be considered while designing novel vaccines and immunization strategies.", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.10.491266", + "rel_abs": "Early stages of deadly respiratory diseases such as COVID-19 have been challenging to elucidate due to lack of an experimental system that recapitulates the cellular and structural complexity of the human lung while allowing precise control over disease initiation and systematic interrogation of molecular events at cellular resolution. Here we show healthy human lung slices cultured ex vivo can be productively infected with SARS-CoV-2, and the cellular tropism of the virus and its distinct and dynamic effects on host cell gene expression can be determined by single cell RNA sequencing and reconstruction of \"infection pseudotime\" for individual lung cell types. This revealed that the prominent SARS-CoV-2 target is a population of activated interstitial macrophages (IMs), which as infection proceeds accumulate thousands of viral RNA molecules per cell, comprising up to 60% of the cellular transcriptome and including canonical and novel subgenomic RNAs. During viral takeover of IMs, there is cell-autonomous induction of a pro-fibrotic program (TGFB1, SPP1), and an inflammatory program characterized by the early interferon response, chemokines (CCL2, 7, 8, 13, CXCL10) and cytokines (IL6, IL10), along with destruction of cellular architecture and formation of dense viral genomic RNA bodies revealed by super-resolution microscopy. In contrast, alveolar macrophages (AMs) showed neither viral takeover nor induction of a substantial inflammatory response, although both purified AMs and IMs supported production of infectious virions. Spike-dependent viral entry into AMs was neutralized by blockade of ACE2 or Sialoadhesin/CD169, whereas IM entry was neutralized only by DC-SIGN/CD209 blockade. These results provide a molecular characterization of the initiation of COVID-19 in human lung tissue, identify activated IMs as a prominent site of viral takeover and focus of inflammation and fibrosis, and suggest therapeutic targeting of the DC-SIGN/CD209 entry mechanism to prevent IM infection, destruction and early pathology in COVID-19 pneumonia. Our approach can be generalized to define the initiation program and evaluate therapeutics for any human lung infection at cellular resolution.", "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Emanuele Andreano", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Timothy Ting-Hsuan Wu", + "author_inst": "Department of Biochemistry, Stanford University School of Medicine and Howard Hughes Medical Institute" }, { - "author_name": "Ida Paciello", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Kyle J. Travaglini", + "author_inst": "Department of Biochemistry, Stanford University School of Medicine and Howard Hughes Medical Institute" }, { - "author_name": "Giulio Pierleoni", - "author_inst": "VisMederi Research S.r.l., Siena, Italy" + "author_name": "Arjun Rustagi", + "author_inst": "Department of Medicine, Division of Infectious Diseases and Program of Immunology, Stanford University School of Medicine" }, { - "author_name": "Giulia Piccini", - "author_inst": "VisMederi S.r.l, Siena, Italy" + "author_name": "Duo Xu", + "author_inst": "Department of Biochemistry, Stanford University School of Medicine and Stanford ChEM-H, Stanford University, Stanford, CA, USA" }, { - "author_name": "Valentina Abbiento", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Yue Zhang", + "author_inst": "Department of Biochemistry, Stanford University School of Medicine and Howard Hughes Medical Institute" }, { - "author_name": "Giada Antonelli", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Leonid Andronov", + "author_inst": "Stanford University" }, { - "author_name": "Piero Pileri", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Sori K. Jang", + "author_inst": "Department of Biochemistry, Stanford University School of Medicine and Howard Hughes Medical Institute" }, { - "author_name": "Noemi Manganaro", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Astrid Gillich", + "author_inst": "Department of Biochemistry, Stanford University School of Medicine and Howard Hughes Medical Institute" }, { - "author_name": "Elisa Pantano", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Roozbeh Dehghannasiri", + "author_inst": "Department of Biochemistry and Department of Biomedical Data Science, Stanford University School of Medicine" }, { - "author_name": "Giuseppe Maccari", - "author_inst": "Data Science for Health (DaScH) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Giovanny Martinez-Colon", + "author_inst": "Department of Medicine, Division of Infectious Diseases and Program of Immunology, Stanford University School of Medicine" }, { - "author_name": "Silvia Marchese", - "author_inst": "Department of Pharmacological and Biomolecular Sciences DiSFeB, University of Milan, Milan, Italy" + "author_name": "Aimee Beck", + "author_inst": "Department of Medicine, Division of Infectious Diseases, Stanford University School of Medicine" }, { - "author_name": "Lorena Donnici", - "author_inst": "INGM, Istituto Nazionale Genetica Molecolare \"Romeo ed Enrica Invernizzi\", Milan, Italy" + "author_name": "Daniel Dan Liu", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Linda Benincasa", - "author_inst": "VisMederi Research S.r.l., Siena, Italy" + "author_name": "Aaron J. Wilk", + "author_inst": "Department of Medicine, Division of Infectious Diseases and Program of Immunology, Stanford University School of Medicine" }, { - "author_name": "Ginevra Giglioli", - "author_inst": "VisMederi Research S.r.l., Siena, Italy" + "author_name": "Maurizio Morri", + "author_inst": "Chan Zuckerberg Biohub, San Francisco, CA, USA" }, { - "author_name": "Margherita Leonardi", - "author_inst": "VisMederi Research S.r.l., Siena, Italy; VisMederi S.r.l, Siena, Italy" + "author_name": "Winston L. Trope", + "author_inst": "Department of Cardiothoracic Surgery, Stanford University School of Medicine" }, { - "author_name": "Concetta De Santi", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Rob Bierman", + "author_inst": "Stanford University Scool of Medicine" }, { - "author_name": "Massimiliano Fabbiani", - "author_inst": "Department of Medical Sciences, Infectious and Tropical Diseases Unit, Siena University Hospital, Siena, Italy" + "author_name": "Irving L Weissman", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Ilaria Rancan", - "author_inst": "Department of Medical Sciences, Infectious and Tropical Diseases Unit, Siena University Hospital, Siena, Italy" + "author_name": "Joseph B. Shrager", + "author_inst": "Department of Cardiothoracic Surgery, Stanford University School of Medicine and Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA" }, { - "author_name": "Mario Tumbarello", - "author_inst": "Department of Medical Sciences, Infectious and Tropical Diseases Unit, Siena University Hospital, Siena, Italy; Department of Medical Biotechnologies, Universit" + "author_name": "Steve R. Quake", + "author_inst": "Chan Zuckerberg Biohub, San Francisco, CA, USA and Department of Bioengineering, Stanford University" }, { - "author_name": "Francesca Montagnani", - "author_inst": "Department of Medical Sciences, Infectious and Tropical Diseases Unit, Siena University Hospital, Siena, Italy; Department of Medical Biotechnologies, Universit" + "author_name": "Christin S. Kuo", + "author_inst": "Department of Pediatrics, Division of Pulmonary Medicine, Stanford University School of Medicine" }, { - "author_name": "Claudia Sala", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Julia Salzman", + "author_inst": "Department of Biochemistry and Department of Biomedical Data Science, Stanford University School of Medicine" }, { - "author_name": "Duccio Medini", - "author_inst": "Data Science for Health (DaScH) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "W.E. Moerner", + "author_inst": "Stanford University" }, { - "author_name": "Raffaele De Francesco", - "author_inst": "Department of Pharmacological and Biomolecular Sciences DiSFeB, University of Milan, Milan, Italy; INGM, Istituto Nazionale Genetica Molecolare \"Romeo ed Enrica" + "author_name": "Peter S. Kim", + "author_inst": "Department of Biochemistry, Stanford University School of Medicine and Stanford ChEM-H, Stanford University, Stanford, CA, USA, and Chan Zuckerberg Biohub, San " }, { - "author_name": "Emanuele Montomoli", - "author_inst": "VisMederi Research S.r.l., Siena, Italy; VisMederi S.r.l, Siena, Italy; Department of Molecular and Developmental Medicine, University of Siena, Siena, Italy" + "author_name": "Catherine A. Blish", + "author_inst": "Department of Medicine, Division of Infectious Diseases and Program of Immunology, Stanford University School of Medicine and Chan Zuckerberg Biohub, San Franci" }, { - "author_name": "Rino Rappuoli", - "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences, Siena, Italy" + "author_name": "Mark A. Krasnow", + "author_inst": "Department of Biochemistry, Stanford University School of Medicine and Howard Hughes Medical Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "genomics" }, { "rel_doi": "10.1101/2022.05.09.22274860", @@ -323918,117 +324805,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.05.06.22274701", - "rel_title": "COVID-19 vaccine effectiveness during a prison outbreak when the Omicron was the dominant circulating variant, Zambia, December 2021", + "rel_doi": "10.1101/2022.05.04.22274665", + "rel_title": "School immunization coverage during the COVID-19 pandemic: A retrospective cohort study", "rel_date": "2022-05-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.06.22274701", - "rel_abs": "During a COVID-19 outbreak in a prison in Zambia from 14th to 19th December 2021, a case control study was done to measure vaccine effectiveness (VE) against infection and symptomatic infection, when the Omicron variant was the dominant circulating variant. Among 382 participants, 74.1% were fully vaccinated and the median time since full vaccination was 54 days. There were no hospitalizations or deaths. COVID-19 VE against any SARS-CoV-2 infection was 64.8% and VE against symptomatic SARS-CoV-2 infection was 72.9%. COVID-19 vaccination helped protect incarcerated persons against SARS-CoV-2 infection during an outbreak while Omicron was the dominant variant in Zambia.", - "rel_num_authors": 25, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.05.04.22274665", + "rel_abs": "Few studies have assessed the impact of the COVID-19 pandemic on immunization coverage for adolescents, and little is known about how coverage has changed throughout the pandemic. We aimed to: (1) assess the change in coverage for school-based vaccines in Alberta, Canada resulting from the pandemic; (2) determine whether coverage differed by geographic health zone and school type; and (3) ascertain whether coverage has returned to pre-pandemic levels. Using a retrospective cohort design, we used administrative health data to compare coverage for human papillomavirus (HPV) and meningococcal conjugate A, C, Y, W-135 (MenC-ACYW) vaccines in Alberta, Canada between pre-pandemic (2017-2018 school year) and pandemic (2019-2020 and 2020-2021 school years) cohorts (N=289,420). Coverage was also compared by health zone and authority type. The 2019-2020 cohort was followed over one year to assess catch-up. Compared to 2017-2018, immunization coverage for HPV was significantly lower in the 2019-2020 (absolute difference: 60.8%; 95% CI: 60.4-61.3%) and 2020-2021 cohorts (absolute difference: 59.9%; 95% CI: 59.4-60.3%). There was a smaller, significant decline in MenC-ACYW coverage comparing 2017-2018 to 2019-2020 (absolute difference: 6.1%; 95% CI: 5.6-6.5%) and 2020-2021 (absolute difference: 32.2%; 95% CI: 31.6-32.7%). Private schools had low coverage overall, while coverage fluctuated by zone. During follow-up of the 2019-2020 cohort, coverage for HPV and MenC-ACYW increased from 5.6% to 50.2%, and 80.7% to 83.0%, respectively. There was a substantial decrease in school-based immunization coverage during the COVID-19 pandemic, and coverage has not returned to pre-pandemic levels, suggesting further catch-up is needed.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "John Simwanza", - "author_inst": "Zambia Field Epidemiology Training Program" - }, - { - "author_name": "Jonas Z. Hines", - "author_inst": "U.S. Centers for Disease Control and Prevention" - }, - { - "author_name": "Danny Sinyange", - "author_inst": "Zambia Field Epidemiology Training Program" - }, - { - "author_name": "Nyambe Sinyange", - "author_inst": "Zambia National Public Health Institute" - }, - { - "author_name": "Chilufya Mulenga", - "author_inst": "Zambia Field Epidemiology Training Program" - }, - { - "author_name": "Sarah Hanyinza", - "author_inst": "Zambia National Public Health Institute" - }, - { - "author_name": "Patrick Sakubita", - "author_inst": "Zambia National Public Health Institute" - }, - { - "author_name": "Nelia Langa", - "author_inst": "Zambia National Public Health Institute" - }, - { - "author_name": "Haggai Nowa", - "author_inst": "Zambia Prison Services" - }, - { - "author_name": "Priscilla Gardner", - "author_inst": "Lusaka District Health Office" - }, - { - "author_name": "Ngonda Saasa", - "author_inst": "University of Zambia Veterinary Medicine Laboratory School" - }, - { - "author_name": "Gabriel Chipeta", - "author_inst": "Lusaka District Health Office" - }, - { - "author_name": "James Simpungwe", - "author_inst": "U.S. Centers for Disease Control and Prevention" - }, - { - "author_name": "Warren Malambo", - "author_inst": "U.S. Centers for Disease Control and Prevention" - }, - { - "author_name": "Busiku Hamainza", - "author_inst": "National Malaria Elimination Centre" - }, - { - "author_name": "Nathan Kapata", - "author_inst": "Zambia National Public Health Institute" - }, - { - "author_name": "Muzala Kapina", - "author_inst": "Zambia National Public Health Institute" - }, - { - "author_name": "Kunda Musonda", - "author_inst": "Zambia National Public Health Institute" - }, - { - "author_name": "Mazyanga Liwewe", - "author_inst": "Zambia National Public Health Institute" - }, - { - "author_name": "Consity Mwale", - "author_inst": "Lusaka Province Health Office" - }, - { - "author_name": "Sombo Fwoloshi", - "author_inst": "Zambia Ministry of Health" - }, - { - "author_name": "Lloyd B. Mulenga", - "author_inst": "Zambia Ministry of Health" + "author_name": "Hannah Sell", + "author_inst": "University of Alberta" }, { - "author_name": "Simon Agolory", - "author_inst": "U.S. Centers for Disease Control and Prevention" + "author_name": "Yuba Raj Paudel", + "author_inst": "University of Alberta" }, { - "author_name": "Victor Mukonka", - "author_inst": "Zambia National Public Health Institute" + "author_name": "Donald Voaklander", + "author_inst": "University of Alberta" }, { - "author_name": "Roma Chilengi", - "author_inst": "Zambia National Public Health Institute" + "author_name": "Shannon E MacDonald", + "author_inst": "University of Alberta" } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -325872,39 +326675,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.05.04.490614", - "rel_title": "SARS-CoV-2 variants do not evolve to promote further escape from MHC-I recognition", + "rel_doi": "10.1101/2022.05.04.490631", + "rel_title": "Adsorption of Pulmonary and Exogeneous Surfactants on SARS-CoV-2 Spike Protein", "rel_date": "2022-05-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.04.490614", - "rel_abs": "SARS-CoV-2 variants of concern (VOCs) possess mutations that confer resistance to neutralizing antibodies within the Spike protein and are associated with breakthrough infection and reinfection. By contrast, less is known about the escape from CD8+ T cell-mediated immunity by VOC. Here, we demonstrated that all SARS-CoV-2 VOCs possess the ability to suppress MHC I expression. We identified several viral genes that contribute to the suppression of MHC I expression. Notably, MHC-I upregulation was strongly inhibited after SARS-CoV-2 infection in vivo. While earlier VOCs possess similar capacity as the ancestral strain to suppress MHC I, Omicron subvariants exhibit a greater ability to suppress surface MHC-I expressions. Collectively, our data suggest that, in addition to escape from neutralizing antibodies, the success of Omicron subvariants to cause breakthrough infection and reinfection may in part be due to its optimized evasion from T cell recognition.\n\nSignificanceNumerous pathogenic viruses have developed strategies to evade host CD8+ T cell-mediated clearance. Here, we demonstrated that SARS-CoV-2 encodes multiple viral factors that can modulate MHC-I expression in the host cells. We found that MHC-I upregulation was strongly suppressed during SARS-CoV-2 infection in vivo. Notably, the Omicron subvariants showed an enhanced ability to suppress MHC-I compared to the original strain and the earlier SARS-CoV-2 variants of concern (VOCs). Our results point to the inherently strong ability of SARS-CoV-2 to hinder MHC-I expression and demonstrated that Omicron subvariants have evolved an even more optimized capacity to evade CD8 T cell recognition.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.05.04.490631", + "rel_abs": "COVID-19 is transmitted by inhaling SARS-CoV-2 virions, which are enveloped by a lipid bilayer decorated by a \"crown\" of Spike protein protrusions. In the respiratory tract, virions interact with surfactant films composed of phospholipids and cholesterol that coat lung airways. Here, we explore by using coarse-grained molecular dynamics simulations the physico-chemical mechanisms of surfactant adsorption on Spike proteins. With examples of zwitterionic dipalmitoyl phosphatidyl choline, cholesterol, and anionic sodium dodecyl sulphate, we show that surfactants form micellar aggregates that selectively adhere to the specific regions of S1 domain of the Spike protein that are responsible for binding with ACE2 receptors and virus transmission into the cells. We find high cholesterol adsorption and preferential affinity of anionic surfactants to Arginine and Lysine residues within S1 receptor binding motif. These findings have important implications for informing the search for extraneous therapeutic surfactants for curing and preventing COVID-19 by SARS-CoV-2 and its variants.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Miyu Moriyama", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Carolina Lucas", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "Valter Silva Monteiro", - "author_inst": "Yale University School of Medicine" - }, - { - "author_name": "- Yale SARS-CoV-2 Genomic Surveillance Initiative", - "author_inst": "-" + "author_name": "Kolattukudy P Santo", + "author_inst": "Rutgers, The State University of New Jersey" }, { - "author_name": "Akiko Iwasaki", - "author_inst": "Yale University School of Medicine" + "author_name": "Alexander V Neimark", + "author_inst": "Rutgers, The State University of New Jersey, Piscataway, NJ, 08854" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "biophysics" }, { "rel_doi": "10.1101/2022.05.02.22274586", @@ -328102,25 +328893,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.04.29.22274485", - "rel_title": "Human behaviour, NPI and mobility reduction effects on COVID-19 transmission in different countries of the world", + "rel_doi": "10.1101/2022.04.28.22274446", + "rel_title": "Vaccine Stockpile Sharing For Selfish Objectives", "rel_date": "2022-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.29.22274485", - "rel_abs": "BackgroundThe outbreak of Coronavirus disease, which originated in Wuhan, China in 2019, has affected the lives of billions of people globally. Throughout 2020, the reproduction number of COVID-19 was widely used by decision-makers to explain their strategies to control the pandemic.\n\nMethodsIn this work, we deduce and analyze both initial and effective reproduction numbers for 12 diverse world regions between February and December of 2020. We consider mobility reductions, mask wearing and compliance with masks, mask efficacy values alongside other non-pharmaceutical interventions (NPIs) in each region to get further insights in how each of the above factored into each regions SARS-COV-2 transmission dynamic.\n\nResultsWe quantify in each region the following reductions in the observed effective reproduction numbers of the pandemic: i) reduction due to decrease in mobility (as captured in Google mobility reports); ii) reduction due to mask wearing and mask compliance; iii) reduction due to other NPIs, over and above the ones identified in i) and ii).\n\nConclusionIn most cases mobility reduction coming from nationwide lockdown measures has helped stave off the initial wave in countries who took these types of measures. Beyond the first waves, mask mandates and compliance, together with social-distancing measures (which we refer to as other NPIs) have allowed some control of subsequent disease spread. The methodology we propose here is novel and can be applied to other respiratory diseases such as influenza or RSV.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.28.22274446", + "rel_abs": "The COVAX program aims to provide global equitable access to life-saving vaccines. However, vaccine protectionism by wealthy nations has limited progress towards vaccine sharing goals. For example, as of April 2022 only[~] 20% of the population in Africa has received at least one COVID-19 vaccine dose. Here we use a two-nation coupled epidemic model to evaluate optimal vaccine-sharing policies given a selfish objective: in which countries with vaccine stockpiles aim to minimize fatalities in their own populations. Despite the selfish objective, we find it is often optimal for a donor nation to share a significant fraction of its vaccine stockpile. Mechanistically, sharing a vaccine stockpile reduces the intensity of outbreaks in the recipient nation, in turn reducing travel-associated incidence in the donor nation. This effect is intensified as vaccination rates decrease and epidemic coupling increases. Despite acting selfishly, vaccine sharing by a donor nation significantly reduces transmission and fatalities in the recipient nation. Moreover, we find that there are hybrid sharing policies that have a negligible effect on fatalities in the donor nation compared to the optimal policy while significantly reducing fatalities in the recipient nation. Altogether, these findings provide a rationale for nations with extensive vaccine stockpiles to share with other nations.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Zahra Mohammadi", - "author_inst": "University of Guelph" + "author_name": "Shashwat Shivam", + "author_inst": "Georgia Institute of Technology" }, { - "author_name": "Monica Gabriela Cojocaru", - "author_inst": "University of Guelph" + "author_name": "Joshua Weitz", + "author_inst": "Georgia Tech" }, { - "author_name": "Edward Wolfgang Thommes", - "author_inst": "Sanofi Pasteur Global, Toronto, Canada" + "author_name": "Yorai Wardi", + "author_inst": "Georgia Institute of Technology" } ], "version": "1", @@ -329872,35 +330663,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.04.26.22274301", - "rel_title": "Trends in non-COVID-19 hospitalizations prior to and during the COVID-19 pandemic period, United States, 2017-2021", + "rel_doi": "10.1101/2022.04.25.22274300", + "rel_title": "Characterization of Autonomic Symptom Burden in Long COVID: A Global Survey of 2,314 Adults", "rel_date": "2022-04-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.26.22274301", - "rel_abs": "COVID-19 pandemic-related shifts in healthcare utilization, in combination with trends in non-COVID-19 disease transmission and NPI use, had clear impacts on infectious and chronic disease hospitalization rates. Using a national healthcare billing database (C19RDB), we estimated the monthly incidence rate ratio of hospitalizations between March 2020 and June 2021 according to 19 ICD-10 diagnostic chapters and 189 subchapters. The majority of hospitalization causes showed an immediate decline in incidence during March 2020. Hospitalizations for diagnoses such as reproductive neoplasms, hypertension, and diabetes returned to pre-pandemic norms in incidence during late 2020 and early 2021, while others, like those for infectious respiratory disease, never returned to pre-pandemic norms. These results are crucial for contextualizing future research, particularly time series analyses, utilizing surveillance and hospitalization data for non-COVID-19 disease. Our assessment of subchapter level primary hospitalization codes offers new insight into trends among less frequent causes of hospitalization during the COVID-19 pandemic.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.25.22274300", + "rel_abs": "BackgroundAutonomic dysfunction is a common complication of post-acute sequalae of SARS-CoV-2 (PASC)/long COVID, however prevalence and severity rates are unknown.\n\nObjectiveThe primary goal of this study was to assess the frequency and severity of autonomic symptoms in PASC. We also aimed to assess symptom burden in PASC though well-validated questionnaires, evaluate which pre-existing conditions are associated with an increased risk of developing autonomic dysfunction, and determine whether the severity of acute COVID-19 illness is associated with the severity of autonomic dysfunction in this population.\n\nMethodsWe conducted an online survey of 2,314 adults with PASC using several validated questionnaires including the COMPASS-31 to evaluate for autonomic dysfunction. We included both participants who had tested positive for COVID-19 (test-confirmed) and participants who were diagnosed with COVID-19 based on clinical symptoms alone (test-unconfirmed). Additional analyses were performed on test-confirmed participants, comparing hospitalized to non-hospitalized participants.\n\nResults67% of PASC patients had a COMPASS-31 score >20, suggestive of moderate to severe autonomic dysfunction. COMPASS-31 scores did not differ between test-confirmed hospitalized and non-hospitalized participants (28.95{+/-}30.98 vs 26.4{+/-}28.35, p=0.06). Both hospitalized and non-hospitalized participants reported significant functional disability across all quality-of-life domains.\n\nConclusionsModerate to severe autonomic dysfunction was seen in all PASC groups in our study, independent of hospitalization status, suggesting that autonomic dysfunction is highly prevalent in the PASC population and not necessarily dependent on the severity of acute COVID illness.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Kelsie Cassell", - "author_inst": "Yale School of Public Health" + "author_name": "Nicholas W. Larsen", + "author_inst": "Stanford University" }, { - "author_name": "Casey M Zipfel", - "author_inst": "Georgetown University" + "author_name": "Lauren E. Stiles", + "author_inst": "Stony Brook University Renaissance School of Medicine" }, { - "author_name": "Shweta Bansal", - "author_inst": "Georgetown University" + "author_name": "Ruba Shaik", + "author_inst": "Stanford University" }, { - "author_name": "Daniel Weinberger", - "author_inst": "Yale School of Public Health" + "author_name": "Logan Schneider", + "author_inst": "Stanford University" + }, + { + "author_name": "Srikanth Muppidi", + "author_inst": "Stanford University" + }, + { + "author_name": "Cheuk To Tsui", + "author_inst": "University of Chicago" + }, + { + "author_name": "Mitchell G. Miglis", + "author_inst": "Stanford University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "neurology" }, { "rel_doi": "10.1101/2022.04.25.22274283", @@ -331954,85 +332757,49 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.04.25.22273197", - "rel_title": "Clinical characteristics and outcome of immunocompromised patients with COVID-19 caused by the Omicron variant: a prospective observational study", + "rel_doi": "10.1101/2022.04.26.22271727", + "rel_title": "Risk of COVID-19 breakthrough infection and hospitalization in individuals with comorbidities", "rel_date": "2022-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.25.22273197", - "rel_abs": "BackgroundIn the general population, illness after infection with the SARS-CoV-2 Omicron variant is less severe compared with previous variants. Data on the disease burden of Omicron in immunocompromised patients are lacking. We investigated the clinical characteristics and outcome of a cohort of immunocompromised patients with COVID-19 caused by Omicron.\n\nMethodsSolid organ transplant recipients, patients on anti-CD20 therapy, and allogenic hematopoietic stem cell transplantation recipients on immunosuppressive therapy infected with the Omicron variant, were included. Patients were contacted regularly until symptom resolution. Clinical characteristics of consenting patients were collected through their electronic patient files. To identify possible risk factors for hospitalization, a univariate logistic analysis was performed.\n\nResultsA total of 114 consecutive immunocompromised patients were enrolled. Eighty-nine percent had previously received three mRNA vaccinations. While only one patient died, 23 (20%) required hospital admission for a median of 11 days. A low SARS-CoV-2 IgG antibody response (<300 BAU/mL) at diagnosis, higher age, being a lung transplant recipient, more comorbidities and a higher frailty were associated with hospital admission (all p<0.01). At the end of follow-up, 25% had still not fully recovered. Of the 23 hospitalized patients, 70% had a negative and 92% a low IgG (<300 BAU/mL) antibody response at admission. Sotrovimab was administered to 17 of them, of which one died.\n\nConclusionsWhile the mortality in immunocompromised patients infected with Omicron was low, hospital admission was frequent and the duration of symptoms often prolonged. Besides vaccination, other interventions are needed to limit the morbidity from COVID-19 in immunocompromised patients.\n\nSummaryCOVID-19-associated morbidity and mortality in immunocompromised patients is unknown for the SARS-CoV-2 Omicron variant. This prospective registry, demonstrated low COVID-19-associated mortality in these vulnerable patients. However, morbidity remained substantial. Other interventions to abate COVID-19 severity are needed.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.26.22271727", + "rel_abs": "BackgroundThe successful development of multiple COVID-19 vaccines has led to a global vaccination effort to reduce severe COVID-19 infection and mortality. However, the effectiveness of the COVID-19 vaccines wane over time leading to breakthrough infections where vaccinated individuals experience a COVID-19 infection. Here we estimate the risks of break-through infection and subsequent hospitalization in individuals with common comorbidities who had completed an initial vaccination series.\n\nMethodsOur study population included vaccinated patients between January 1, 2021 to March 31, 2022 who are present in the Truveta patient population. Models were developed to describe 1) time from completing primary vaccination series till breakthrough infection; and 2) if a patient was hospitalized within 14 days of breakthrough infection. We adjusted for age, race, ethnicity, sex, and year-month of vaccination.\n\nResultsOf 1,192,135 patients in the Truveta Platform who had completed an initial vaccination sequence between January 1, 2021 and March 31, 2022, 2.84, 3.42, 2.76, and 2.89 percent of patients with CKD, chronic lung disease, diabetes, or are in an immunocompromised state experienced breakthrough infection, respectively, compared to 1.35 percent of the population without any of these four comorbidities. We found an increased risk of breakthrough infection and subsequent hospitalization in individuals with any of the four comorbidities when compared to individuals without these four comorbidities.\n\nConclusionsVaccinated individuals with comorbidities experienced an increased risk of breakthrough COVID-19 infection and subsequent hospitalizations compared to the general population. Individuals with immunocompromising conditions and chronic lung disease were most at risk of breakthrough infection, while people with CKD were most at risk of hospitalization following breakthrough infection. Individuals with comorbidities should remain vigilant against infection even if vaccinated.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "S. Reshwan K. Malahe", - "author_inst": "Department of Internal Medicine, Erasmus, University Medical Center, Rotterdam," - }, - { - "author_name": "Rogier A.S. Hoek", - "author_inst": "Department of Pulmonary Medicine, Erasmus, University Medical Center, Rotterdam, The Netherlands" - }, - { - "author_name": "Virgil A.S.H. Dalm", - "author_inst": "Department of Internal Medicine, division of Allergy and Clinical Immunology; Department of Immunology, Erasmus, University Medical Center, Rotterdam, The Neth" - }, - { - "author_name": "Annoek E.C. Broers", - "author_inst": "Department of Hematology, Erasmus, Cancer Institute, Rotterdam, The Netherlands" - }, - { - "author_name": "Caroline M. den Hoed", - "author_inst": "Department of Gastroenterology and Hepatology, Erasmus, University Medical Center, Rotterdam, The Netherlands" - }, - { - "author_name": "Olivier C. Manintveld", - "author_inst": "Department of Cardiology, Erasmus, University Medical Center, Rotterdam, The Netherlands" - }, - { - "author_name": "Carla C. Baan", - "author_inst": "Erasmus MC Transplant Institute, Erasmus, University Medical Center, Rotterdam, The Netherlands" - }, - { - "author_name": "Charlotte M. van Deuzen", - "author_inst": "Department of Internal Medicine, Section of Infectious Diseases and Department of Medical Microbiology and Infectious Diseases, Erasmus, University Medical Cent" - }, - { - "author_name": "Grigorios Papageorgiou", - "author_inst": "Department of Biostatistics and department of Epidemiology, Erasmus, University Medical Center, Rotterdam, the Netherlands" - }, - { - "author_name": "Hannelore I. Bax", - "author_inst": "Department of Internal Medicine, Section of Infectious Diseases and Department of Medical Microbiology and Infectious Diseases, Erasmus, University Medical Cent" + "author_name": "Peter D Smits", + "author_inst": "Truveta Incorporated" }, { - "author_name": "Jeroen J. van Kampen", - "author_inst": "Department of Viroscience, Erasmus, University Medical Center, Rotterdam, The Netherlands" + "author_name": "Samuel Gratzl", + "author_inst": "Truveta Incorporated" }, { - "author_name": "Merel E. Hellemons", - "author_inst": "Department of Pulmonary Medicine, Erasmus, University Medical Center, Rotterdam, The Netherlands" + "author_name": "Michael Simonov", + "author_inst": "Truveta Incorporated" }, { - "author_name": "Marcia M.L. Kho", - "author_inst": "Department of Internal Medicine, Erasmus, University Medical Center, Rotterdam, The Netherlands" + "author_name": "Senthil K Nachimuthu", + "author_inst": "Truveta Incorporated" }, { - "author_name": "Rory D. de Vries", - "author_inst": "Department of Viroscience, Erasmus, University Medical Center, Rotterdam, The Netherlands" + "author_name": "Brianna M Goodwin", + "author_inst": "Truveta Incorporated" }, { - "author_name": "Richard Molenkamp", - "author_inst": "Department of Viroscience, Erasmus, University Medical Center, Rotterdam, The Netherlands" + "author_name": "Michael D Wang", + "author_inst": "Truveta Incorporated" }, { - "author_name": "Marlies E.J. Reinders", - "author_inst": "Department of Internal Medicine, Erasmus, University Medical Center, Rotterdam, The Netherlands" + "author_name": "Benjamin Muir Althouse", + "author_inst": "Truveta Incorporated" }, { - "author_name": "Bart J.A. Rijnders", - "author_inst": "Department of Internal Medicine, Section of Infectious Diseases and Department of Medical Microbiology and Infectious Diseases, Erasmus, University Medical Cent" + "author_name": "Nicholas Stucky", + "author_inst": "Truveta Incorporated" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -333540,55 +334307,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.04.19.22274030", - "rel_title": "Estimating the distribution of COVID-19-susceptible, -recovered, and -vaccinated individuals in Germany up to April 2022", + "rel_doi": "10.1101/2022.04.19.22273864", + "rel_title": "Immune and pathophysiologic profiling of antenatal COVID-19 in the GIFT cohort: A Singaporean case-control study.", "rel_date": "2022-04-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.19.22274030", - "rel_abs": "After having affected the population for two years, the COVID-19 pandemic has reached a phase where a considerable number of people in Germany have been either infected with a SARS-CoV-2 variant, vaccinated, or both. Yet the full extent to which the population has been in contact with either virus or vaccine remains elusive, particularly on a regional level, because (a) infection counts suffer from under-reporting, and (b) the overlap between the vaccinated and recovered subpopulations is unknown. Since previous infection, vaccination, or especially a combination of both reduce the risk of severe disease, a high share of individuals with SARS-CoV-2 immunity lowers the probability of severe outbreaks that could potentially overburden the public health system once again, given that emerging variants do not escape this reduction in susceptibility. Here, we estimate the share of immunologically naive individuals by age group for each of the 16 German federal states by integrating an infectious disease model based on weekly incidences of SARS-CoV-2 infections in the national surveillance system and vaccine uptake, as well as assumptions regarding under-ascertainment. We estimate a median share of 7.0% of individuals in the German population have neither been in contact with vaccine nor any variant as of March 31, 2022 (quartile range [3.6%- 9.8%]). For the adult population at higher risk of severe disease, this figure is reduced to 3.5% [1.3%-5.5%] for ages 18-59 and 4.3% [2.7%-5.8%] for ages 60 and above. However, estimates vary between German states mostly due to heterogeneous vaccine uptake. Excluding Omicron infections from the analysis, 16.1% [14.0%-17.8%] of the population in Germany, across all ages, are estimated to be immunologically naive, highlighting the large impact the Omicron wave had until the beginning of spring in 2022.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.19.22273864", + "rel_abs": "BackgroundCOVID-19 has been a major public health threat for the past two years, with disproportionate effects on the elderly, immunocompromised, and pregnant women. While much has been done in delineating immune dysfunctions and pathogenesis in the former two groups, less is known about the diseases progression in expectant women and children born to them. To address this knowledge gap, we profiled the immune responses in maternal and child sera as well as breast milk in terms of antibody and cytokine expression and performed histopathological studies on placentae obtained from mothers convalescent from antenatal COVID-19.\n\nMethods and findingsA total of 17 mother-child dyads (8 cases of antenatal COVID-19 and 9 healthy unrelated controls; 34 individuals in total) were recruited to the Gestational Immunity For Transfer (GIFT) study. Maternal and infant sera, and breast milk samples were collected over the first year of life. All samples were analyzed for IgG and IgA against whole SARS-CoV-2 spike protein, the spike receptor-binding domain (RBD), and previously reported immunodominant epitopes, with conventional ELISA approaches. Cytokine levels were quantified in maternal sera using multiplex microbead-based Luminex arrays. The placentae were examined microscopically. We found high levels of virus-specific IgG in convalescent mothers and similarly elevated titers in newborn children. Virus-specific IgG in infant circulation waned within 3-6 months of life. Virus-specific IgA levels were variable among convalescent individuals sera and breast milk. Convalescent mothers also showed a blood cytokine signature indicative of a persistent pro-inflammatory state. Four placentae presented signs of acute inflammation marked by neutrophil infiltration even though >50 days had elapsed between virus clearance and delivery. Administration of a single dose of BNT162b2 mRNA vaccine to mothers convalescent from antenatal COVID-19 increased virus-specific IgG and IgA titers in breast milk.\n\nConclusionsAntenatal SARS-CoV-2 infection led to high plasma titres of virus-specific antibodies in infants postnatally. However, this was not reflected in milk; milk-borne antibody levels varied widely. Additionally, placentae from COVID-19 positive mothers exhibited signs of acute inflammation with neutrophilic involvement, particularly in the subchorionic region. Virus neutralisation by plasma was not uniformly achieved, and the presence of antibodies targeting known immunodominant epitopes did not assure neutralisation. Antibody transfer ratios and the decay of transplacentally transferred virus-specific antibodies in neonatal circulation resembled that for other pathogens. Convalescent mothers showed signs of chronic inflammation marked by persistently elevated IL17RA levels in their blood. A single dose of the Pfizer BNT162b2 mRNA vaccine provided significant boosts to milk-borne virus-specific antibodies, highlighting the importance of receiving the vaccine even after natural infection with the added benefit of enhanced passive immunity. The study is registered at clinicaltrials.gov under the identifier NCT04802278.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Benjamin F Maier", - "author_inst": "Robert Koch Institute" + "author_name": "Yue Gu", + "author_inst": "National University of Singapore" }, { - "author_name": "Annika H Rose", - "author_inst": "Robert Koch Institute" + "author_name": "Jia Ming Low", + "author_inst": "National University of Singapore" }, { - "author_name": "Angelique Burdinski", - "author_inst": "Robert Koch Institute" + "author_name": "Jolene Su Yi Tan", + "author_inst": "Duke-NUS Medical School, Singapore" }, { - "author_name": "Pascal Klamser", - "author_inst": "Robert Koch Institute" + "author_name": "Melissa Shu Feng Ng", + "author_inst": "Agency for Science, Technology and Research" }, { - "author_name": "Hannelore Neuhauser", - "author_inst": "Robert Koch Institute" + "author_name": "Lisa F.P. Ng", + "author_inst": "Agency for Science, Technology and Research" }, { - "author_name": "Ole Wichmann", - "author_inst": "Robert Koch Institute" + "author_name": "Bhuvaneshwari D/O Shunmuganathan", + "author_inst": "National University of Singapore" }, { - "author_name": "Lars Schaade", - "author_inst": "Robert Koch Institute" + "author_name": "Rashi Gupta", + "author_inst": "National University of Singapore" }, { - "author_name": "Lothar H Wieler", - "author_inst": "Robert Koch Institute" + "author_name": "Paul A. MacAry", + "author_inst": "National University of Singapore" }, { - "author_name": "Dirk Brockmann", - "author_inst": "Robert Koch Institute" + "author_name": "Zubair Amin", + "author_inst": "National University of Singapore" + }, + { + "author_name": "Le Ye Lee", + "author_inst": "National University of Singapore" + }, + { + "author_name": "Derrick W.Q. Lian", + "author_inst": "National University of Singapore" + }, + { + "author_name": "Lynette Pei-Chi Shek", + "author_inst": "National University of Singapore" + }, + { + "author_name": "Youjia Zhong", + "author_inst": "National University of Singapore" + }, + { + "author_name": "Liang Wei Wang", + "author_inst": "Agency for Science, Technology and Research" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "pediatrics" }, { "rel_doi": "10.1101/2022.04.19.22274029", @@ -335378,65 +336165,21 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2022.04.19.22274026", - "rel_title": "A Platform for Data-centric, Continuous Epidemiological Analyses", + "rel_doi": "10.1101/2022.04.19.22274036", + "rel_title": "A Statistical Argument Against Vaccine Injury", "rel_date": "2022-04-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.19.22274026", - "rel_abs": "Guaranteeing durability, provenance, accessibility, and trust in open datasets can be challenging for researchers and organizations that rely on public repositories of data critical to epidemiology and other health analytics. Not only are the required repositories sometimes difficult to locate, and nearly always require conversion into a compatible format, they may move or change unpredictably. Any single change of the rules in one repository can hinder updating of a public dashboard reliant on pulling data from external sources. These concerns are particularly challenging at the international level, because systems aimed at harmonizing health and related data are typically dictated by national governments to serve their individual needs. In this paper, we introduce a comprehensive public health data platform, the EpiGraphHub, that aims to provide a single interoperable repository for open health and related data, curated by the international research community, which allows secure local integration of sensitive databases whilst facilitating the development of data-driven applications and reports for decision-makers. The platform development is co-funded by the World Health Organization and is fully open-source to maximize its value for large-scale public health studies.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.19.22274036", + "rel_abs": "Vaccine hesitancy is a major threat to public health. While the root causes of vaccine hesitancy are numerous, they largely revolve around some form of perceived risk to the self. In particular, the unknown long-term risks are amongst the most frequently cited concerns. In this work, we show that regardless of their peak onset following vaccination, the incidence of adverse outcomes will follow some distribution f (x| {micro}, {sigma}2) of mean onset {micro}, and standard deviation{sigma} , and variance{sigma} 2. Despite the small proportion of events at the tails of these distributions, the large-scale public deployment of vaccines would imply that any signal for a given adverse outcome would be observed soon after distribution begins, even in cases where tx < t{micro}-3{sigma}. The absence of such an early signal, however low, would suggest that long term effects are unlikely and that vaccine safety is therefore likely. Indeed, when enough individuals have been exposed to a new therapy - even if the majority of adverse outcomes only manifest at a future time t{micro}, the number of adverse outcomes given by the cumulative density function (CDF) near t0 + dt > 0. Otherwise stated:\n\nO_FD O_INLINEFIG[Formula 1]C_INLINEFIGM_FD(1)C_FD\n\nWe evoke the theory behind normal (Gaussian) and skew-normal distributions and use Chebyshevs Theorem to evaluate the COVID-19 vaccine data as an example. The findings of this study are not vaccine-specific and can be applied to assess the health effects of the mass distribution of any good, treatment or policy at large.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Fl\u00e1vio Code\u00e7o Coelho", - "author_inst": "Funda\u00e7\u00e3o Getulio Vargas" - }, - { - "author_name": "Daniel C P C\u00e2mara", - "author_inst": "Fundacao Oswaldo Cruz" - }, - { - "author_name": "Eduardo Correa Araujo", - "author_inst": "Universidade Tecnologica Federal do Parana" - }, - { - "author_name": "Lucas Bianchi", - "author_inst": "Fundacao Oswaldo Cruz" - }, - { - "author_name": "Ivan Ogasawara", - "author_inst": "The Graph Network" - }, - { - "author_name": "Jyoti Dalal", - "author_inst": "The Graph Network" - }, - { - "author_name": "Ananthu James", - "author_inst": "Indian Institute of Science, Bangalore" - }, - { - "author_name": "Jessica Lee Abbate", - "author_inst": "Geomatys" - }, - { - "author_name": "Aziza Merzouki", - "author_inst": "University of Geneva" - }, - { - "author_name": "Izabel Reis", - "author_inst": "World Health Organization" - }, - { - "author_name": "Kenechukwu David Nwosu", - "author_inst": "Institute of Global Health - University of Geneva" - }, - { - "author_name": "Olivia Keiser", - "author_inst": "Institute of Global Health - University of Geneva" + "author_name": "Jacques Balayla", + "author_inst": "McGill University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -338796,69 +339539,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.18.22271936", - "rel_title": "Anti-nucleocapsid antibodies following SARS-CoV-2 infection in the blinded phase of the mRNA-1273 Covid-19 vaccine efficacy clinical trial", + "rel_doi": "10.1101/2022.04.18.22273989", + "rel_title": "Validation of Reduced S-gene Target Performance and Failure for Rapid Surveillance of SARS-CoV-2 Variants", "rel_date": "2022-04-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.18.22271936", - "rel_abs": "ImportanceThe performance of immunoassays for determining past SARS-CoV-2 infection, which were developed in unvaccinated individuals, has not been assessed in vaccinated individuals.\n\nObjectiveTo evaluate anti-nucleocapsid antibody (anti-N Ab) seropositivity in mRNA-1273 vaccine efficacy trial participants after SARS-CoV-2 infection during the trials blinded phase.\n\nDesignNested analysis in a Phase 3 randomized, placebo-controlled vaccine efficacy trial. Nasopharyngeal swabs for SARS-CoV-2 PCR testing were taken from all participants on Day 1 and Day 29 (vaccination days), and during symptom-prompted illness visits. Serum samples from Days 1, 29, 57, and the Participant Decision Visit (PDV, when participants were informed of treatment assignment, median day 149) were tested for anti-N Abs.\n\nSettingMulticenter, randomized, double-blind, placebo-controlled trial at 99 sites in the US.\n\nParticipantsTrial participants were [≥] 18 years old with no known history of SARS-CoV-2 infection and at appreciable risk of SARS-CoV-2 infection and/or high risk of severe Covid-19. Nested sub-study consists of participants with SARS-CoV-2 infection during the blinded phase of the trial.\n\nInterventionTwo mRNA-1273 (Moderna) or Placebo injections, 28 days apart.\n\nMain Outcome and MeasureDetection of serum anti-N Abs by the Elecsys (Roche) immunoassay in samples taken at the PDV from participants with SARS-CoV-2 infection during the blinded phase. The hypothesis tested was that mRNA-1273 recipients have different anti-N Ab seroconversion and/or seroreversion profiles after SARS-CoV-2 infection, compared to placebo recipients. The hypothesis was formed during data collection; all main analyses were pre-specified before being conducted.\n\nResultsWe analyzed data from 1,789 participants (1,298 placebo recipients and 491 vaccine recipients) with SARS-CoV-2 infection during the blinded phase (through March 2021). Among participants with PCR-confirmed Covid-19 illness, seroconversion to anti-N Abs at a median follow up of 53 days post diagnosis occurred in 21/52 (40%) of the mRNA-1273 vaccine recipients vs. 605/648 (93%) of the placebo recipients (p < 0.001). Higher SARS-CoV-2 viral copies at diagnosis was associated with a higher likelihood of anti-N Ab seropositivity (odds ratio 1.90 per 1-log increase; 95% confidence interval 1.59, 2.28).\n\nConclusions and RelevanceAs a marker of recent infection, anti-N Abs may have lower sensitivity in mRNA-1273-vaccinated persons who become infected. Vaccination status should be considered when interpreting seroprevalence and seropositivity data based solely on anti-N Ab testing\n\nTrial RegistrationClinicalTrials.gov NCT04470427\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDoes prior mRNA-1273 vaccination influence anti-nucleocapsid antibody seroconversion and/or seroreversion after SARS-CoV-2 infection?\n\nFindingsAmong participants in the mRNA-1273 vaccine efficacy trial with PCR-confirmed Covid-19, anti-nucleocapsid antibody seroconversion at the time of study unblinding (median 53 days post diagnosis and 149 days post enrollment) occurred in 40% of the mRNA-1273 vaccine recipients vs. 93% of the placebo recipients, a significant difference. Higher SARS-CoV-2 viral copy number upon diagnosis was associated with a greater chance of anti-nucleocapsid antibody seropositivity (odds ratio 1.90 per 1-log increase; 95% confidence interval 1.59, 2.28). All infections analyzed occurred prior to the circulation of delta and omicron viral variants.\n\nMeaningConclusions about the prevalence and incidence of SARS-CoV-2 infection in vaccinated persons based on anti-nucleocapsid antibody assays need to be weighed in the context of these results.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.18.22273989", + "rel_abs": "SARS-CoV-2, the virus that causes COVID-19, has many variants capable of rapid transmission causing serious illness. Timely surveillance of new variants is essential for an effective public health response. Ensuring availability and access to diagnostic and molecular testing is key to this type of surveillance. This study utilized reverse transcription polymerase chain reaction (RT-PCR) and whole genome sequencing results from COVID-19-positive patient samples obtained through a collaboration between Aegis Sciences Corporation and Walgreens Pharmacy that has conducted more than 8.5 million COVID-19 tests at [~]5,200 locations across the United States and Puerto Rico.\n\nViral evolution of SARS-CoV-2 can lead to mutations in the S-gene that cause reduced or failed S-gene amplification in diagnostic PCR tests. These anomalies, labeled reduced S-gene target performance (rSGTP) and S-gene target failure (SGTF), are characteristic of Alpha and Omicron (B.1.1.529, BA.1, and BA.1.1) lineages. This observation has been validated by whole genome sequencing and can provide presumptive lineage data following completion of diagnostic PCR testing in 24-48 hours from collection. Active surveillance of trends in PCR and sequencing results is key to the identification of changes in viral transmission and emerging variants. This study shows that rSGTP and SGTF can be utilized for near real-time tracking and surveillance of SARS-CoV-2 variants.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Dean Follmann", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Holly E. Janes", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Olive D. Buhule", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Honghong Zhou", - "author_inst": "Moderna, Inc." + "author_name": "Cyndi Clark", + "author_inst": "Aegis Sciences Corporation" }, { - "author_name": "Bethany Girard", - "author_inst": "Moderna, Inc." + "author_name": "Joshua Schrecker", + "author_inst": "Aegis Sciences Corporation" }, { - "author_name": "Kristen Marks", - "author_inst": "Weill Cornell Medicine" - }, - { - "author_name": "Karen Kotloff", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Matthew Hardison", + "author_inst": "Aegis Sciences Corporation" }, { - "author_name": "Micha\u00ebl Desjardins", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Lawrence Corey", - "author_inst": "Fred Hutchinson Cancer Center" - }, - { - "author_name": "Kathleen M. Neuzil", - "author_inst": "University of Maryland School of Medicine" - }, - { - "author_name": "Jacqueline M. Miller", - "author_inst": "Moderna, Inc." - }, - { - "author_name": "Hana M. El Sahly", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Lindsey R. Baden", - "author_inst": "Harvard Medical School" + "author_name": "Michael S Taitel", + "author_inst": "Walgreens" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -340406,51 +341113,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.04.18.22273961", - "rel_title": "Clonal diversity determines persistence of SARS-CoV-2 epitope-specific T cell response", + "rel_doi": "10.1101/2022.04.13.22273830", + "rel_title": "Why were Twitter Users Obsessed with Vitamin D during the first year of the pandemic?", "rel_date": "2022-04-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.18.22273961", - "rel_abs": "T cells play a pivotal role in reducing disease severity during SARS-CoV-2 infection and formation of long-term immune memory. We studied 50 COVID-19 convalescent patients and found that T cell response was induced more frequently and persisted longer than circulating antibodies. To identify epitopes that give rise to long-lived T cell memory, we performed ex vivo T cell expansion, MHC-tetramer cell-sorting, and high-throughput sequencing. We identified 756 clonotypes specific to nine known CD8+ T cell receptor (TCR) epitopes. Some epitopes were recognized by highly similar public clonotypes with restricted variable and joining segment usage. Receptors for other epitopes were extremely diverse, suggesting alternative modes of recognition. We also tracked persistence of epitope-specific response and individual clonotypes for a median of eight months after infection. The number of recognized epitopes per patient and quantity of epitope-specific clonotypes decreased over time, but the studied epitopes were characterized by uneven decline in the number of specific T cells. Epitopes with more clonally diverse TCR repertoires induced more pronounced and durable responses. In contrast, the abundance of specific clonotypes in peripheral circulation had no influence on their persistence. Our study demonstrates the durability of SARS-CoV-2-specific CD8+ memory, and offers important implications for vaccine design.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.13.22273830", + "rel_abs": "The aim of this study was to explore how the relationship between vitamin D and COVID-19 has been represented on the social media site Twitter. NCapture was used to collect textual Tweets on a weekly basis for three months during the pandemic. In total, 21,140 Tweets containing the keywords \"vitamin D\" and \"COVID\" were collected and imported to NVivo12. An inductive thematic analysis was carried out on the Tweets collected on the first (12/2/2021) and last week (21/5/2021) of the recording period to identify themes and subthemes. Quality control of the coding was conducted on a sample of the dataset (20%). Data were also compared to the \"ground truth\" to explore the accuracy of media outputs. The four main themes identified were \"association of vitamin D with COVID-19\", \"politically informed views\", \"vitamin D deficiency\" and \"vitamin D sources\". When compared to the ground truth, the majority of information relating to the key findings was incorrect for all of the findings. This study contributes to the area of research by highlighting the extent of the issue social media sites face with health-related misinformation. In the context of COVID-19, it is important that sites such as Twitter improve their existing misinformation policies, as misinformation can be detrimental in disease prevention.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ksenia V Zornikova", - "author_inst": "National Medical Research Center for Hematology, Moscow, Russia" - }, - { - "author_name": "Alexandra Khmelevskaya", - "author_inst": "National Medical Research Center for Hematology, Moscow, Russia" - }, - { - "author_name": "Savely A Sheetikov", - "author_inst": "National Medical Research Center for Hematology, Moscow, Russia" - }, - { - "author_name": "Dmitry O Kiryukhin", - "author_inst": "National Medical Research Center for Hematology, Moscow, Russia" - }, - { - "author_name": "Olga V Shcherbakova", - "author_inst": "National Medical Research Center for Hematology, Moscow, Russia" + "author_name": "Alexandra Mavroeidi", + "author_inst": "University of Strathclyde" }, { - "author_name": "Aleksei Titov", - "author_inst": "National Medical Research Center for Hematology, Moscow, Russia" + "author_name": "Ryan Innes", + "author_inst": "University of Strathclyde" }, { - "author_name": "Ivan V Zvyagin", - "author_inst": "Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia" + "author_name": "Esperanza Miyake", + "author_inst": "University of Strathclyde" }, { - "author_name": "Grigory Efimov", - "author_inst": "National Medical Research Center for Hematology, Moscow, Russia" + "author_name": "Diane Pennington", + "author_inst": "University of Strathclyde" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "nutrition" }, { "rel_doi": "10.1101/2022.04.13.22273832", @@ -342304,65 +342995,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.08.22273532", - "rel_title": "Heterologous Gam-COVID-Vac (Sputnik V) / mRNA-1273 (Moderna) vaccination induces a stronger humoral response than homologous Sputnik V in a real-world data analysis", + "rel_doi": "10.1101/2022.04.07.22273591", + "rel_title": "Monitoring real-time transmission heterogeneity from Incidence data", "rel_date": "2022-04-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.08.22273532", - "rel_abs": "IntroductionGrowing data are demonstrating safety and immunogenicity of heterologous vaccination schemes against severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection. This strategy opens up the possibility of a shorter path towards the end of the pandemic.\n\nObjectiveTo compare the homologous prime-boost vaccination scheme of Gam-COVID-Vac (Sputnik V, SpV) to its heterologous combination with mRNA-1273 (Moderna, Mod) vaccine.\n\nMethodsSARS-CoV-2 anti-spike (S)-receptor binding domain (RBD) IgG concentration was assessed three to seven weeks after complete vaccination. Reactogenicity was evaluated by declared side events and medical assistance required until day 7 post-boost.\n\nResultsOf 190 participants enrolled, 105 received homologous SpV/SpV and the remaining heterologous SpV/Mod vaccination scheme, respectively. Median (interquartile range, IQR) age was 54 (37-63) years, 132 (69.5%) were female and 46 (24.2%) individuals had a prior confirmed COVID-19. Anti-S-RBD IgG median (IQR) titers were significantly higher for SpV/Mod [2511 (1476-3992) BAU/mL] than for SpV/SpV [582 (209-1609) BAU/mL, p<0.001] vaccination scheme. In a linear model adjusted for age, gender, time to the serological assay and time between doses, SpV/Mod [4.154 (6.585-615.554), p<0.001] and prior COVID [3.732 (8.641-202.010), p<0.001] were independently associated with higher anti-S-RBD IgG values. A higher frequency of mild-moderate adverse effects was associated with the heterologous scheme, although it was well tolerated by all individuals and no medical assistance was required.\n\nConclusionThe heterologous SpV/Mod combination against SARS-CoV-2 is well tolerated and significantly increases humoral immune response as compared to the homologous SpV/SpV immunization.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.07.22273591", + "rel_abs": "The transmission heterogeneity of an epidemic is associated with a complex mixture of host, pathogen and environmental factors. And it may indicate superspreading events to reduce the efficiency of population-level control measures and to sustain the epidemic over a larger scale and a longer duration. Methods have been proposed to identify significant transmission heterogeneity in historic epidemics based on several data sources, such as contact history, viral genomes and spatial information, which is sophisticated and may not be available, and more importantly ignore the temporal trend of transmission heterogeneity. Here we attempted to establish a convenient method to estimate real-time heterogeneity over an epidemic. Within the branching process framework, we introduced an instant-individualheterogenous infectiousness model to jointly characterized the variation in infectiousness both between individuals and among different times. With this model, we could simultaneously estimate the transmission heterogeneity and the reproduction number from incidence time series. We validated the model with both simulated data and five historic epidemics. Our estimates of the overall and real-time heterogeneities of the five epidemics were consistent with those presented in the literature. Additionally, our model is robust to the ubiquitous bias of under-reporting and misspecification of serial interval. By analyzing the recent data from South Africa, we found evidences that the Omicron might be of more significant transmission heterogeneity than the Delta. Our model based on incidence data was proved to be reliable in estimating the real-time transmission heterogeneity.\n\nAuthor summaryThe transmission of many infectious diseases is usually heterogeneous in time and space. Such transmission heterogeneity may indicate superspreading events (where some infected individuals transmit to disproportionately more susceptible than others), reduce the efficiency of the population-level control measures, and sustain the epidemic over a larger scale and a longer duration. Classical methods of monitoring epidemic spread centered on the reproduction number which represent the average transmission potential of the epidemic at the population level, but failed to reflect the systematic variation in transmission. Several recent methods have been proposed to identify significant transmission heterogeneity in the epidemics such as Ebola, MERS, COVID-19. However, these methods are developed based on some sophisticated information such as contact history, viral genome and spatial information, of the confirmed cases, which are typically field-specific and not easy to generalize. In this study, we proposed a simple and generic method of estimating transmission heterogeneity from incidence time series, which provided consistent estimation of heterogeneity with those records with sophisticated data. It also helps in exploring the transmission heterogeneity of the newly emerging variant of Omicron. Our model enhances current understanding of epidemic dynamics, and highlight the potential importance of targeted control measures.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Matias Javier Pereson", - "author_inst": "Universidad de Buenos Aires. Facultad de Farmacia y Bioquimica. Instituto de Investigaciones en Bacteriologia y Virologia Molecular (IBaViM). Buenos Aires, Arge" - }, - { - "author_name": "Lucas Amaya", - "author_inst": "Virology Section, Centro de Educacion Medica e Investigaciones Clinicas Norberto Quirno \"CEMIC\". Buenos Aires, Argentina." - }, - { - "author_name": "Karin Neukam", - "author_inst": "Servicio de Enfermedades Infecciosas, UCEIMP. Hospital Universitario Virgen del Rocio. Seville, Spain." - }, - { - "author_name": "Patricia Bare", - "author_inst": "Academia Nacional de Medicina" - }, - { - "author_name": "Natalia Echegoyen", - "author_inst": "Virology Section, Centro de Educacion Medica e Investigaciones Clinicas Norberto Quirno \"CEMIC\". Buenos Aires, Argentina." - }, - { - "author_name": "Maria Noel Badano", - "author_inst": "Instituto de Medicina Experimental (IMEX), Academia Nacional de Medicina, Ciudad Autonoma de Buenos Aires, Argentina." - }, - { - "author_name": "Alicia Lucero", - "author_inst": "Virology Section, Centro de Educacion Medica e Investigaciones Clinicas Norberto Quirno \"CEMIC\". Buenos Aires, Argentina." - }, - { - "author_name": "Antonella Martelli", - "author_inst": "Virology Section, Centro de Educacion Medica e Investigaciones Clinicas Norberto Quirno \"CEMIC\". Buenos Aires, Argentina." - }, - { - "author_name": "Gabriel Garcia", - "author_inst": "Universidad de Buenos Aires. Facultad de Farmacia y Bioquimica. Instituto de Investigaciones en Bacteriologia y Virologia Molecular (IBaViM). Buenos Aires, Arge" - }, - { - "author_name": "Cristina Videla", - "author_inst": "Virology Section, Centro de Educacion Medica e Investigaciones Clinicas Norberto Quirno \"CEMIC\". Buenos Aires, Argentina." + "author_name": "Yunjun Zhang", + "author_inst": "Peking University" }, { - "author_name": "Alfredo Martinez", - "author_inst": "Virology Section, Centro de Educacion Medica e Investigaciones Clinicas Norberto Quirno \"CEMIC\". Buenos Aires, Argentina." + "author_name": "Tom Britton", + "author_inst": "Stockholm University: Stockholms Universitet" }, { - "author_name": "Federico Alejandro Di Lello Sr.", - "author_inst": "Universidad de Buenos Aires. Facultad de Farmacia y Bioquimica. Instituto de Investigaciones en Bacteriologia y Virologia Molecular (IBaViM). Buenos Aires, Arge" + "author_name": "Xiaohua Zhou", + "author_inst": "Peking University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -343874,49 +344529,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.13.22273835", - "rel_title": "Evaluation of machine learning for predicting COVID-19 outcomes from a national electronic medical records database", + "rel_doi": "10.1101/2022.04.12.22273466", + "rel_title": "Level and duration of IgG and neutralizing antibodies to SARS-CoV-2 in children with symptomatic or asymptomatic SARS-CoV-2 infection", "rel_date": "2022-04-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.13.22273835", - "rel_abs": "ObjectiveWhen novel diseases such as COVID-19 emerge, predictors of clinical outcomes might be unknown. Using data from electronic medical records (EMR) allows evaluation of potential predictors without selecting specific features a priori for a model. We evaluated different machine learning models for predicting outcomes among COVID-19 inpatients using raw EMR data.\n\nMaterials and MethodsIn Premier Healthcare Data Special Release: COVID-19 Edition (PHD-SR COVID-19, release date March, 24 2021), we included patients admitted with COVID-19 during February 2020 through April 2021 and built time-ordered medical histories. Setting the prediction horizon at 24 hours into the first COVID-19 inpatient visit, we aimed to predict intensive care unit (ICU) admission, hyperinflammatory syndrome (HS), and death. We evaluated the following models: L2-penalized logistic regression, random forest, gradient boosting classifier, deep averaging network, and recurrent neural network with a long short-term memory cell.\n\nResultsThere were 57,355 COVID-19 patients identified in PHD-SR COVID-19. ICU admission was the easiest outcome to predict (best AUC=79%), and HS was the hardest to predict (best AUC=70%). Models performed similarly within each outcome.\n\nDiscussionAlthough the models learned to attend to meaningful clinical information, they performed similarly, suggesting performance limitations are inherent to the data.\n\nConclusionPredictive models using raw EMR data are promising because they can use many observations and encompass a large feature space; however, traditional and deep learning models may perform similarly when few features are available at the individual patient level.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.12.22273466", + "rel_abs": "BackgroundThere are presently conflicting data about level and duration of antibodies to SARS-CoV-2 in children after symptomatic or asymptomatic infection.\n\nMethodsWe enrolled adults and children in a prospective 6-month study in the following categories: 1) symptomatic, SARS-CoV-2 PCR+ (SP+; children, n=8; adults, n=16), 2) symptomatic, PCR- or untested (children, n=27), 3) asymptomatic exposed (children, n=13) and 4) asymptomatic, no known exposure (children, n=19). Neutralizing and IgG antibodies to SARS-CoV-2 antigens and Spike protein variants were measured by multiplex serological assays.\n\nResultsAll SP+ children developed nAb, whereas 81% of SP+ adults developed nAb. Decline in the presence of nAb over 6 months was not significant in symptomatic children (100% to 87.5%, p=0.32) in contrast to adults (81.3 to 50.0%, p=0.03). Among all children with nAb (n=22), nAb titers and change in titers over 6 months were similar in symptomatic and asymptomatic children. Levels of IgG antibodies in children to the SARS-CoV-2 Spike, RBD-1 and -2, nucleocapsid and N-terminal domain antigens and to Spike protein variants were similar to those in adults. IgG levels to primary antigens decreased over time in both children and adults, but levels to three of six Spike variants decreased only in children.\n\nConclusionsChildren with asymptomatic or symptomatic SARS-CoV-2 infection develop robust neutralizing antibodies that remain present longer than in adults but wane in titer over time, and broad IgG antibodies that also wane in level over time.\n\nKey PointsChildren have robust neutralizing and IgG antibody responses to SARS-CoV-2 infection after symptomatic or asymptomatic disease that are at least as strong as in adults. Neutralizing antibodies in children last longer than in adults but wane over time.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Scott Lee", - "author_inst": "CDC: Centers for Disease Control and Prevention" + "author_name": "Alka Khaitan", + "author_inst": "Indiana University" }, { - "author_name": "Sean Browning", - "author_inst": "US Centers for Disease Control and Prevention" + "author_name": "Dibyadyuti Datta", + "author_inst": "Indiana University" }, { - "author_name": "Ermias Belay", - "author_inst": "US Centers for Disease Control and Prevention" + "author_name": "Caitlin Bond", + "author_inst": "Indiana University" }, { - "author_name": "Jennifer DeCuir", - "author_inst": "US Centers for Disease Control and Prevention" + "author_name": "Micael Goings", + "author_inst": "Indiana University" }, { - "author_name": "Shana Godfred Cato", - "author_inst": "US Centers for Disease Control and Prevention" + "author_name": "Katrina Co", + "author_inst": "Indiana University" }, { - "author_name": "Pragna Patel", - "author_inst": "US Centers for Disease Control and Prevention" + "author_name": "Eliud O Odhiambo", + "author_inst": "Indiana University" }, { - "author_name": "Noah Schwartz", - "author_inst": "US Centers for Disease Control and Prevention" + "author_name": "Lin Zhang", + "author_inst": "Eli Lilly and Company, Indianapolis, IN, United States" }, { - "author_name": "Karen Wong", - "author_inst": "US Centers for Disease Control and Prevention" + "author_name": "Stephanie Beasley", + "author_inst": "Eli Lilly and Company, Indianapolis, IN, United States" + }, + { + "author_name": "Josh Poorbaugh", + "author_inst": "Eli Lilly and Company, Indianapolis, IN, United States" + }, + { + "author_name": "Chandy C John", + "author_inst": "Indiana University" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -345491,83 +346154,83 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2022.04.12.487988", - "rel_title": "An ACAT inhibitor regulates SARS-CoV-2 replication and antiviral T cell activity", + "rel_doi": "10.1101/2022.04.11.487660", + "rel_title": "A high potent synthetic nanobody with broad-spectrum activity neutralizes SARS-Cov-2 virus and Omicron variant through a unique binding mode", "rel_date": "2022-04-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.12.487988", - "rel_abs": "The severity of disease following infection with SARS-CoV-2 is determined by viral replication kinetics and host immunity, with early T cell responses and/or suppression of viraemia driving a favourable outcome. Recent studies have uncovered a role for cholesterol metabolism in the SARS-CoV-2 life cycle and in T cell function. Here we show that blockade of the enzyme Acyl-CoA:cholesterol acyltransferase (ACAT) with Avasimibe inhibits SARS-CoV-2 entry and fusion independent of transmembrane protease serine 2 expression in multiple cell types. We also demonstrate a role for ACAT in regulating SARS-CoV-2 RNA replication in primary bronchial epithelial cells. Furthermore, Avasimibe boosts the expansion of functional SARS-CoV-2-specific T cells from the blood of patients sampled in the acute phase of infection. Thus, re-purposing of available ACAT inhibitors provides a compelling therapeutic strategy for the treatment of COVID-19 to achieve both antiviral and immunomodulatory effects.", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.11.487660", + "rel_abs": "The major challenge to control COVID pandemic is the rapid mutation rate of the SARS-Cov-2 virus, leading to the escape of the protection of vaccines and most of the neutralizing antibodies to date. Thus, it is essential to develop neutralizing antibodies with broad-spectrum activity targeting multiple SARS-Cov-2 variants. Here, we reported a synthetic nanobody (named C5G2) obtianed by phage display and subsequent antibody engineering. C5G2 has a single digit nanomolar binding affinity to RBD domain and inhibits its binding to ACE2 with an IC50 of 3.7 nM. Pseudovirus assay indicated that the monovalent C5G2 could protect the cells from the infection of SARS-Cov-2 wild type virus and most of the virus of concern, i.e. Alpha, Beta, Gamma and Omicron variants. Strikingly, C5G2 has the highest potency against Omicron among all the variants with the IC50 of 4.9ng/mL. The Cryo-EM structure of C5G2 in complex with the Spike trimer showed that C5G2 bind to RBD mainly through its CDR3 at a conserved region that not overlapping with the ACE2 binding surface. Additionally, C5G2 bind simultaneously to the neighboring NTD domain of spike trimer through the same CDR3 loop, which may further increase its potency against the virus infection. Third, the steric hindrance caused by FR2 of C5G2 could inhibit the binding of ACE2 to RBD as well. Thus, this triple-function nanobody may be served as an effective drug for the prophylaxis and therapy against Omicron as well as future variants.", "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Nathalie M Schmidt", - "author_inst": "University College London" + "author_name": "Dongping Zhao", + "author_inst": "Qingdao University" }, { - "author_name": "Peter AC Wing", - "author_inst": "University of Oxford" + "author_name": "Liqin Liu", + "author_inst": "Xiamen university" }, { - "author_name": "Rory Peters", - "author_inst": "University of Oxford" + "author_name": "Xinlin Liu", + "author_inst": "The Cancer Institute, Qingdao University" }, { - "author_name": "Rachel Brown", - "author_inst": "University College London" + "author_name": "Jinlei Zhang", + "author_inst": "Xiamen University" }, { - "author_name": "Hao Wang", - "author_inst": "Scripps Research Institute" + "author_name": "Yuqing Yin", + "author_inst": "Noventi Biopharmaceuticals Co., Ltd" }, { - "author_name": "Leo Swadling", - "author_inst": "University College London" + "author_name": "Linli Luan", + "author_inst": "Noventi Biopharmaceuticals Co., Ltd" }, { - "author_name": "Joseph Newman", - "author_inst": "The Pirbright Institute" + "author_name": "Dingwen Jiang", + "author_inst": "Noventi Biopharmaceuticals Co., Ltd" }, { - "author_name": "Nazia Thakur", - "author_inst": "The Pirbright Institute" + "author_name": "Xiong Yang", + "author_inst": "Noventi Biopharmaceuticals Co., Ltd" }, { - "author_name": "Kaho Shionoya", - "author_inst": "National Institute of Infectious Diseases, Tokyo" + "author_name": "Lei Li", + "author_inst": "Qingdao University" }, { - "author_name": "Sophie B Morgan", - "author_inst": "University of Oxford" + "author_name": "Hualong Xiong", + "author_inst": "Xiamen University" }, { - "author_name": "Timothy SC Hinks", - "author_inst": "University of Oxford" + "author_name": "Dongming Xing", + "author_inst": "Qingdao University" }, { - "author_name": "Koichi Watashi", - "author_inst": "National Institute of Infectious Diseases" + "author_name": "Qingbing Zheng", + "author_inst": "Xiamen University" }, { - "author_name": "Dalan Bailey", - "author_inst": "The Pirbright Institute" + "author_name": "Ningshao Xia", + "author_inst": "Xiamen University" }, { - "author_name": "Scott B Hansen", - "author_inst": "The Scripps Research Institute" + "author_name": "Yuyong Tao", + "author_inst": "University of Science and Technology of China" }, { - "author_name": "Mala K Maini", - "author_inst": "UCL" + "author_name": "Shaowei Li", + "author_inst": "Xiamen University" }, { - "author_name": "Jane A. McKeating", - "author_inst": "University of Oxford" + "author_name": "Haiming Huang", + "author_inst": "Shanghai Asia United Antibody Medical Ltd" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2022.04.11.487920", @@ -346982,31 +347645,63 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2022.04.11.487882", - "rel_title": "Receptor binding domain of SARS-CoV-2 is a functional \u03b1v-integrin agonist", - "rel_date": "2022-04-11", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.11.487882", - "rel_abs": "Among the novel mutations distinguishing SARS-CoV-2 from similar respiratory coronaviruses is a K403R substitution in the receptor-binding domain (RBD) of the viral spike (S) protein within its S1 region. This amino acid substitution occurs near the angiotensin-converting enzyme 2 (ACE2)-binding interface and gives rise to a canonical RGD adhesion motif that is often found in native extracellular matrix proteins, including fibronectin. In the present study, the ability of recombinant S1-RBD to bind to cell surface integrins and trigger downstream signaling pathways was assessed and compared to RGD-containing, integrin-binding fragments of fibronectin. S1-RBD supported adhesion of both fibronectin-null mouse embryonic fibroblasts as well as primary human small airway epithelial cells. Cell adhesion to S1-RBD was cation- and RGD-dependent, and was inhibited by blocking antibodies against v and {beta}3, but not 5 or {beta}1, integrins. Similarly, direct binding of S1-RBD to recombinant human v{beta}3 and v{beta}6 integrins, but not 5{beta}1 integrins, was observed by surface plasmon resonance. Adhesion to S1-RBD initiated cell spreading, focal adhesion formation, and actin stress fiber organization to a similar extent as fibronectin. Moreover, S1-RBD stimulated tyrosine phosphorylation of the adhesion mediators FAK, Src, and paxillin, Akt activation, and supported cell proliferation. Together, these data demonstrate that the RGD sequence within S1-RBD can function as an v-selective integrin agonist. This study provides evidence that cell surface v-containing integrins can respond functionally to spike protein and raise the possibility that S1-mediated dysregulation of ECM dynamics may contribute to the pathogenesis and/or post-acute sequelae of SARS-CoV-2 infection.", - "rel_num_authors": 3, + "rel_doi": "10.1101/2022.04.09.22273420", + "rel_title": "Characteristics and outcomes of COVID-19 patients during B.1.1.529 (Omicron) dominance compared to B.1.617.2 (Delta) in 89 German hospitals", + "rel_date": "2022-04-10", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.09.22273420", + "rel_abs": "BackgroundThe SARS-CoV-2 variant of concern B.1.1.529 (Omicron) was first described in November 2021 and soon became the dominant variant worldwide. Existing data suggests a reduced disease severity in comparison to B.1.617.2 (Delta). Differences in characteristics and in-hospital outcomes of patients with COVID-19 in Germany during the Omicron period compared to Delta are not thoroughly studied. Surveillance for severe acute respiratory infections (SARI) represents an integral part of infectious disease control in Germany.\n\nMethodsAdministrative data from 89 German Helios hospitals was retrospectively analysed. Laboratory-confirmed SARS-CoV-2 infections were identified by ICD-10-code U07.1 and SARI cases by ICD-10-codes J09-J22. COVID-19 cases were stratified by concomitant SARI. A nine-week observational period between December 6, 2021 and February 6, 2022 was defined and divided into three phases with respect to the dominating virus variant (Delta, Delta to Omicron transition, Omicron). Regression analyses adjusted for age, gender and Elixhauser comorbidities were applied to assess in-hospital patient outcomes.\n\nResultsA total cohort of 4,494 inpatients was analysed. Patients in the Omicron dominance period were younger (mean age 61.6 vs. 47.8; p<0.01), more likely to be female (54.7% vs. 47.5%; p<0.01) and characterized by a lower comorbidity burden (mean Elixhauser comorbidity index 8.2 vs. 5.4; p<0.01). Comparing Delta and Omicron periods, patients were at significantly lower risk for intensive care treatment (adjusted odds ratio 0.64 [0.51-0.8]; p<0.001), mechanical ventilation (adjusted odds ratio 0.38 [0.28-0.51]; p<0.001), and in-hospital mortality (adjusted odds ratio 0.42 [0.32-0.56]; p<0.001). This also applied to the separate COVID-SARI group. During the Delta to Omicron transition, case numbers of COVID-19 without SARI exceeded COVID-SARI.\n\nConclusionPatient characteristics and outcomes differ during the Omicron dominance period as compared to Delta suggesting a reduced disease severity with Omicron infections. SARI surveillance might play a crucial role in assessing disease severity of future SARS-CoV-2 variants.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Emma G Norris", - "author_inst": "University of Rochester Medical Center" + "author_name": "Johannes Leiner", + "author_inst": "Heart Center Leipzig" }, { - "author_name": "Xuan Sabrina Pan", - "author_inst": "University of Rochester" + "author_name": "Vincent Pellissier", + "author_inst": "Leipzig Heart Institute" }, { - "author_name": "Denise C Hocking", - "author_inst": "University of Rochester Medical Center" + "author_name": "Sven Hohenstein", + "author_inst": "Leipzig Heart Institute" + }, + { + "author_name": "Sebastian Koenig", + "author_inst": "Heart Center Leipzig" + }, + { + "author_name": "Ekkehard Schuler", + "author_inst": "Helios Kliniken GmbH" + }, + { + "author_name": "Robert Moeller", + "author_inst": "Helios Kliniken GmbH" + }, + { + "author_name": "Irit Nachtigall", + "author_inst": "Helios Kliniken GmbH" + }, + { + "author_name": "Marzia Bonsignore", + "author_inst": "Helios University Hospital Wuppertal and Helios St. Anna Hospital Duisburg" + }, + { + "author_name": "Gerhard Hindricks", + "author_inst": "Heart Center Leipzig" + }, + { + "author_name": "Ralf Kuhlen", + "author_inst": "Helios Health GmbH" + }, + { + "author_name": "ANDREAS BOLLMANN", + "author_inst": "Heart Center Leipzig" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "cell biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.04.07.22273557", @@ -348816,83 +349511,55 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.04.07.487489", - "rel_title": "Antibody Resistance of SARS-CoV-2 Omicron BA.1, BA.1.1, BA.2 and BA.3 Sub-lineages", + "rel_doi": "10.1101/2022.04.07.487460", + "rel_title": "Distinct evolutionary trajectories of SARS-CoV-2 interacting proteins in bats and primates identify important host determinants of COVID-19", "rel_date": "2022-04-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.07.487489", - "rel_abs": "The SARS-CoV-2 Omicron variant has been partitioned into four sub-lineages designated BA.1, BA.1.1, BA.2 and BA.3, with BA.2 becoming dominant worldwide recently by outcompeting BA.1 and BA.1.1. We and others have reported the striking antibody evasion of BA.1 and BA.2, but side-by-side comparison of susceptibility of all the major Omicron sub-lineages to vaccine-elicited or monoclonal antibody (mAb)-mediated neutralization are urgently needed. Using VSV-based pseudovirus, we found that sera from individuals vaccinated by two doses of inactivated whole-virion vaccines (BBIBP-CorV) showed very weak to no neutralization activity, while a homologous inactivated vaccine booster or a heterologous booster with protein subunit vaccine (ZF2001) markedly improved the neutralization titers against all Omicron variants. The comparison between sub-lineages indicated that BA.1.1, BA.2 and BA.3 had comparable or even greater antibody resistance than BA.1. We further evaluated the neutralization profile of a panel of 20 mAbs, including 10 already authorized or approved, against these Omicron sub-lineages as well as viruses with different Omicron spike single or combined mutations. Most mAbs lost their neutralizing activity completely or substantially, while some demonstrated distinct neutralization patterns among Omicron sub-lineages, reflecting their antigenic difference. Taken together, our results suggest all four Omicron sub-lineages threaten the efficacies of current vaccines and antibody therapeutics, highlighting the importance of vaccine boosters to combat the emerging SARS-CoV-2 variants.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.07.487460", + "rel_abs": "The COVID-19 pandemic is caused by SARS-CoV-2, a novel coronavirus that spilled from the bat reservoir. Despite numerous clinical trials and vaccines, the burden remains immense, and the host determinants of SARS-CoV-2 susceptibility and COVID-19 severity remain largely unknown. Signatures of positive selection detected by comparative functional-genetic analyses in primate and bat genomes can uncover important and specific adaptations that occurred at virus-host interfaces. Here, we performed high-throughput evolutionary analyses of 334 SARS- CoV-2 interacting proteins to identify SARS-CoV adaptive loci and uncover functional differences between modern humans, primates and bats. Using DGINN (Detection of Genetic INNovation), we identified 38 bat and 81 primate proteins with marks of positive selection. Seventeen genes, including the ACE2 receptor, present adaptive marks in both mammalian orders, suggesting common virus-host interfaces and past epidemics of coronaviruses shaping their genomes. Yet, 84 genes presented distinct adaptations in bats and primates. Notably, residues involved in ubiquitination and phosphorylation of the inflammatory RIPK1 have rapidly evolved in bats but not primates, suggesting different inflammation regulation versus humans. Furthermore, we discovered residues with typical virus-host arms-race marks in primates, such as in the entry factor TMPRSS2 or the autophagy adaptor FYCO1, pointing to host-specific in vivo important interfaces that may be drug targets. Finally, we found that FYCO1 sites under adaptation in primates are those associated with severe COVID-19, supporting their importance in pathogenesis and replication. Overall, we identified functional adaptations involved in SARS- CoV-2 infection in bats and primates, critically enlightening modern genetic determinants of virus susceptibility and severity.\n\nKey findingsO_LIEvolutionary history of 334 SARS-CoV-2 interacting proteins (VIPs) in bats and primates identifying how the past has shaped modern viral reservoirs and humans - results publicly-available in an online resource.\nC_LIO_LIIdentification of 81 primate and 38 bat VIPs with signatures of adaptive evolution. The common ones among species delineate a core adaptive interactome, while the ones displaying distinct evolutionary trajectories enlighten host lineage-specific determinants.\nC_LIO_LIEvidence of primate specific adaptation of the entry factor TMPRSS2 pointing to its host- specific in vivo importance and predicting molecular interfaces.\nC_LIO_LIFYCO1 sites associated with severe COVID-19 in human (GWAS) display hallmarks of ancient adaptive evolution in primates, highlighting its importance in SARS-CoV-2 replication or pathogenesis and differences with the bat reservoir.\nC_LIO_LIIdentification of adaptive evolution in the bats multifunctional RIPK1 at residues that may differentially regulate inflammation.\nC_LI", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jingwen Ai", - "author_inst": "Fudan University" - }, - { - "author_name": "Xun Wang", - "author_inst": "Fudan University" - }, - { - "author_name": "Xinyi He", - "author_inst": "Fudan University" - }, - { - "author_name": "Xiaoyu Zhao", - "author_inst": "Fudan University" - }, - { - "author_name": "Yi Zhang", - "author_inst": "Fudan University" - }, - { - "author_name": "Yuchao Jiang", - "author_inst": "Pigentech Lab Limited" - }, - { - "author_name": "Minghui Li", - "author_inst": "Fudan University" + "author_name": "Marie Cariou", + "author_inst": "CIRI, Centre International de Recherche en Infectiologie" }, { - "author_name": "Yuchen Cui", - "author_inst": "Fudan University" + "author_name": "Lea Picard", + "author_inst": "CIRI, Centre International de Recherche en Infectiologie" }, { - "author_name": "Yanjia Chen", - "author_inst": "Fudan University" + "author_name": "Laurent Gueguen", + "author_inst": "Universite Lyon 1" }, { - "author_name": "Rui Qiao", - "author_inst": "Fudan University" + "author_name": "Stephanie Jacquet", + "author_inst": "CIRI, Centre International de Recherche en Infectiologie, and LBBE, Laboratoire de Biometrie et Biologie Evolutive" }, { - "author_name": "Lin Li", - "author_inst": "Fudan University" - }, - { - "author_name": "Lulu Yang", - "author_inst": "Fudan University" + "author_name": "Andrea Cimarelli", + "author_inst": "CIRI, ENSL" }, { - "author_name": "Yi Li", - "author_inst": "Fudan University" + "author_name": "Oliver I Fregoso", + "author_inst": "UCLA" }, { - "author_name": "Zixin Hu", - "author_inst": "Fudan University" + "author_name": "Antoine Molaro", + "author_inst": "Genetics, Reproduction & Development Institute" }, { - "author_name": "Wenhong Zhang", - "author_inst": "Huashan Hospital, Fudan University" + "author_name": "Vincent Navratil", + "author_inst": "PRABI: Pole Rhone-Alpes de Bio-Informatique" }, { - "author_name": "Pengfei Wang", - "author_inst": "Fudan University" + "author_name": "Lucie Etienne", + "author_inst": "CIRI, Centre International de Recherche en Infectiologie" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2022.04.06.22273514", @@ -350622,43 +351289,75 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.04.06.487306", - "rel_title": "An Ultralong Bovine CDRH3 that Targets a Conserved, Cryptic Epitope on SARS-CoV and SARS-CoV-2", - "rel_date": "2022-04-06", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.04.06.487306", - "rel_abs": "The ability of broadly neutralising antibodies to target conserved epitopes gives them huge potential as antibody-based therapeutics, particularly in the face of constant viral antigen evolution. Certain bovine antibodies are highly adept at binding conserved, glycosylated epitopes, courtesy of their ultralong complementarity determining region (CDR)H3. Here, we used a SARS-naive, bovine ultralong CDRH3 library and mammalian cell display, to isolate a bovine paratope that engages the SARS-CoV and SARS-CoV-2 receptor-binding domain (RBD). This neutralises viruses pseudo-typed with SARS-CoV Spike protein but not by competition with RBD binding to ACE2. Instead, using differential hydrogen-deuterium exchange mass spectrometry and site-directed mutagenesis, we demonstrate that this ultralong CDRH3 recognises a rarely identified, conserved, cryptic epitope that overlaps the target of pan-sarbecovirus antibodies (7D6/6D6). The epitope is glycan-shielded and becomes accessible only transiently via inter-domain movements. This represents the first bovine anti-sarbecovirus paratope and highlights the power of this approach in identifying novel tools to combat emerging pathogens.", - "rel_num_authors": 6, + "rel_doi": "10.1101/2022.04.03.22273360", + "rel_title": "Real-World Evidence of the Neutralizing Monoclonal Antibody Sotrovimab for Preventing Hospitalization and Mortality in COVID-19 Outpatients", + "rel_date": "2022-04-05", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.03.22273360", + "rel_abs": "BackgroundIt is not known whether sotrovimab, a neutralizing monoclonal antibody (mAb) treatment authorized for early symptomatic COVID-19 patients, is effective against the SARS-CoV-2 Delta variant to prevent progression to severe disease and mortality.\n\nMethodsObservational cohort study of non-hospitalized adult patients with SARS-CoV-2 infection from October 1st 2021 - December 11th 2021, using electronic health records from a statewide health system plus state-level vaccine and mortality data. We used propensity matching to select 3 patients not receiving mAbs for each patient who received outpatient sotrovimab treatment. The primary outcome was 28-day hospitalization; secondary outcomes included mortality and severity of hospitalization.\n\nResultsOf 10,036 patients with SARS-CoV-2 infection, 522 receiving sotrovimab were matched to 1,563 not receiving mAbs. Compared to mAb-untreated patients, sotrovimab treatment was associated with a 63% decrease in the odds of all-cause hospitalization (raw rate 2.1% versus 5.7%; adjusted OR 0.37, 95% CI 0.19-0.66) and an 89% decrease in the odds of all-cause 28-day mortality (raw rate 0% versus 1.0%; adjusted OR 0.11, 95% CI 0.0-0.79), and may reduce respiratory disease severity among those hospitalized.\n\nConclusionReal-world evidence demonstrated sotrovimab effectiveness in reducing hospitalization and all-cause 28-day mortality among COVID-19 outpatients during the Delta variant phase.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Matthew J Burke", - "author_inst": "University of Leeds" + "author_name": "Neil Aggarwal", + "author_inst": "University of Colorado School of Medicine" }, { - "author_name": "James NF Scott", - "author_inst": "University of Leeds" + "author_name": "Laurel Beatty", + "author_inst": "University of Colorado Anschutz Medical Campus" }, { - "author_name": "Thomas Minshull", - "author_inst": "University of Leeds" + "author_name": "Tellen D Bennett", + "author_inst": "University of Colorado School of Medicine" }, { - "author_name": "Peter G Stockley", - "author_inst": "University of Leeds" + "author_name": "Nichole Carlson", + "author_inst": "Colorado School of Public Health" }, { - "author_name": "Antonio N Calabrese", - "author_inst": "University of Leeds" + "author_name": "Christopher Davis", + "author_inst": "University of Colorado School of Medicine" }, { - "author_name": "Joan Boyes", - "author_inst": "University of Leeds" + "author_name": "Bethany Kwan", + "author_inst": "University of Colorado School of Medicine" + }, + { + "author_name": "David Mayer", + "author_inst": "University of Colorado School of Medicine" + }, + { + "author_name": "Toan Ong", + "author_inst": "University of Colorado School of Medicine" + }, + { + "author_name": "Seth Russell", + "author_inst": "University of Colorado Anschutz Medical Campus" + }, + { + "author_name": "Jeffrey Steele", + "author_inst": "Children's Hospital Colorado" + }, + { + "author_name": "Adane Wogu", + "author_inst": "Colorado School of Public Health" + }, + { + "author_name": "Matthew Wynia", + "author_inst": "University of Colorado School of Medicine" + }, + { + "author_name": "Richard Zane", + "author_inst": "University of Colorado School of Medicine" + }, + { + "author_name": "Adit A Ginde", + "author_inst": "University of Colorado School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "molecular biology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.04.04.22273314", @@ -352356,87 +353055,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.04.03.22272610", - "rel_title": "Cardiac impairment in Long Covid 1-year post-SARS-CoV-2 infection", + "rel_doi": "10.1101/2022.04.04.22272731", + "rel_title": "Estimating the number of breakthrough COVID-19 deaths in the United States", "rel_date": "2022-04-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.03.22272610", - "rel_abs": "BackgroundLong Covid is associated with multiple symptoms and impairment in multiple organs. Cardiac impairment has been reported to varying degrees by varying methodologies in cross-sectional studies. Using cardiac magnetic resonance (CMR), we investigated the 12-month trajectory of cardiac impairment in individuals with Long Covid.\n\nMethods534 individuals with Long Covid underwent baseline CMR (T1 and T2 mapping, cardiac mass, volumes, function, and strain) and multi-organ MRI at 6 months (IQR 4.3,7.3) since first post-COVID-19 symptoms and 330 were rescanned at 12.6 (IQR 11.4, 14.2) months if abnormal findings were reported at baseline. Symptoms, standardised questionnaires, and blood samples were collected at both timepoints. Cardiac impairment was defined as one or more of: low left or right ventricular ejection fraction (LVEF and RVEF), high left or right ventricular end diastolic volume (LVEDV and RVEDV), low 3D left ventricular global longitudinal strain (GLS), or elevated native T1 in [≥]3 cardiac segments. A significant change over time was reported by comparison with 92 healthy controls.\n\nResultsThe technical success of this multiorgan assessment in non-acute settings was 99.1% at baseline, and 98.3% at follow up, with 99.6% and 98.8% for CMR respectively. Of individuals with Long Covid, 102/534 [19%] had cardiac impairment at baseline; 71/102 had complete paired data at 12 months. Of those, 58% presented with ongoing cardiac impairment at 12 months. High sensitivity cardiac troponin I and B-type natriuretic peptide were not predictive of CMR findings, symptoms, or clinical outcomes. At baseline, low LVEF, high RVEDV and low GLS were associated with cardiac impairment. Low LVEF at baseline was associated with persistent cardiac impairment at 12 months.\n\nConclusionCardiac impairment, other than myocarditis, is present in 1 in 5 individuals with Long Covid at 6 months, persisting in over half of those at 12 months. Cardiac-related blood biomarkers are unable to identify cardiac impairment in Long COVID. Subtypes of disease (based on symptoms, examination, and investigations) and predictive biomarkers are yet to be established. Interventional trials with pre-specified subgroup analyses are required to inform therapeutic options.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.04.04.22272731", + "rel_abs": "While there is compelling evidence of the effectiveness of COVID-19 vaccines, increasing attention has also been paid to the fact that, like all vaccines, they are not 100% effective. Therefore, some fully vaccinated people have developed \"breakthrough\" cases of COVID-19, and some of these individuals have died as a result. The purpose of this study was to estimate the number of fully vaccinated or \"breakthrough\" deaths from COVID-19 in the United States. Data was compiled from state COVID-19 dashboards and various other sources for as many states as possible. As of March 27, 2022 based on data from 46 U.S. states and the District of Columbia, an estimated minimum of 57,617 breakthrough COVID-19 deaths had occurred in the United States. Furthermore, based on this incomplete data, a total of 12.8% of all COVID-19 deaths in the included regions and time periods were among fully vaccinated individuals (whether boosted or not). Extrapolating this data to the entire United States implies that the minimum total number of such deaths as of March 27, 2022 was 79,917. Data from a MMWR article, if similarly extrapolated to the entire country, implies a significantly larger number of breakthrough deaths throughout the United States: 99,152.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Adriana Roca-Fernandez", - "author_inst": "Perspectum Diagnostics" - }, - { - "author_name": "Malgorzata Wamil", - "author_inst": "Great Western Hospital Foundation NHS Trust, Swindon, UK" - }, - { - "author_name": "Alison Telford", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "Valentina Carapella", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "Alessandra Borlotti", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "David Monteiro", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "Helena Thomaides-Brears", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "Matthew D Kelly", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "Andrea Dennis", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "Rajarshi Banerjee", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "Matthew Robson", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "Michael Brady", - "author_inst": "Perspectum Ltd" - }, - { - "author_name": "Gregory Lip", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Sacha Bull", - "author_inst": "Royal Berkshire Hospital, Reading" - }, - { - "author_name": "Melissa J Heightman", - "author_inst": "UCLH" - }, - { - "author_name": "Ntobeko Ntusi", - "author_inst": "University of Cape Town, Cape Town, South Africa" - }, - { - "author_name": "Amitava Banerjee", - "author_inst": "University College London" + "author_name": "Jinkinson Payne Smith", + "author_inst": "n/a" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.04.03.22273355", @@ -354374,39 +355009,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.27.22271628", - "rel_title": "Spatial prediction of COVID-19 pandemic dynamics in the United States", + "rel_doi": "10.1101/2022.03.28.22273020", + "rel_title": "Detection of a BA.1/BA.2 recombinant in travelers arriving in Hong Kong, February 2022", "rel_date": "2022-04-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.27.22271628", - "rel_abs": "BackgroundThe impact of COVID-19 across the United States has been heterogeneous, with some areas demonstrating more rapid spread and greater mortality than others. We used geographically-linked data to test the hypothesis that the risk for COVID-19 is spatially defined and sought to define which features are most closely associated with elevated COVID-19 spread and mortality.\n\nMethodsLeveraging geographically-restricted social, economic, political, and demographic information from U.S. counties, we developed a computational framework using structured Gaussian processing to predict county-level case and death counts during both the initial and the nationwide phases of the pandemic. After identifying the most predictive spatial features, we applied an unsupervised clustering algorithm, topic modelling, to identify groups of features that are most closely associated with COVID-19 spread.\n\nFindingsWe found that the inclusion of spatial features modeled case counts very well, with overall Pearsons correlation coefficient (PCC) and R2of 0.96 and 0.84 during the initial phase and 0.95 and 0.87, respectively, during the nationwide phase. The most frequently selected features were associated with urbanicity and 2020 presidential vote margins. When trained using death counts, models revealed similar performance metrics, with the addition of aging metrics to those most frequently selected. Topic modeling showed that counties with similar socioeconomic and demographic features tended to group together, and some feature sets were associated with COVID-19 dynamics. Unsupervised clustering of counties based on these topics revealed groups of counties that experienced markedly different COVID-19 spread.\n\nInterpretationSpatial features explained most of the variability in COVID-19 dynamics between counties. Topic modeling can be used to group collinear features and identify counties with similar features in epidemiologic research.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.28.22273020", + "rel_abs": "We studied SARS-CoV-2 genomes from travelers arriving in Hong Kong from November-2021 to February-2022. Apart from detecting Omicron (BA.1, BA1.1. and BA.2) and Delta variants, we detected a BA.1/BA.2 recombinant in two epidemiologically linked cases. This recombinant has a breakpoint near the 5 end of Spike gene (nucleotide position 20055-21618).", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Cigdem Ak", - "author_inst": "Oregon Health & Science University" + "author_name": "Haogao Gu", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Alex D Chitsazan", - "author_inst": "Oregon Health & Science University" + "author_name": "Daisy Ng", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Mehmet Gonen", - "author_inst": "Koc University" + "author_name": "Gigi Liu", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Ruth Etzioni", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Samuel Cheng", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Aaron Grossberg", - "author_inst": "Oregon Health and Science University" + "author_name": "Pavithra Krishnan", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Lydia Chang", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Sammi Cheuk", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Mani Hui", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Tommy Tsan-Yuk Lam", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Joseph Sriyal Malik Peiris", + "author_inst": "University of Hong Kong" + }, + { + "author_name": "Leo Poon", + "author_inst": "The University of Hong Kong" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.04.01.486788", @@ -356212,51 +356871,39 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.03.30.486345", - "rel_title": "Ancestral origins are associated with SARS-CoV-2 susceptibility and protection in a Florida patient population", + "rel_doi": "10.1101/2022.03.30.486418", + "rel_title": "Contributions of the N-terminal intrinsically disordered region of the SARS-CoV-2 nucleocapsid protein to RNA-induced phase separation", "rel_date": "2022-03-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.30.486345", - "rel_abs": "COVID-19 is caused by severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2). The severity of COVID-19 is highly variable and related to known (e.g., age, obesity, immune deficiency) and unknown risk factors. The widespread clinical symptoms encompass a large group of asymptomatic COVID-19 patients, raising a crucial question regarding genetic susceptibility, e.g., whether individual differences in immunity play a role in patient symptomatology and how much human leukocyte antigen (HLA) contributes to this. To reveal genetic determinants of susceptibility to COVID-19 severity in the population and further explore potential immune-related factors, we performed a genome-wide association study on 284 confirmed COVID-19 patients (cases) and 95 healthy individuals (controls). We compared cases and controls of European (EUR) ancestry and African American (AFR) ancestry separately. We identified two loci on chromosomes 5q32 and 11p12, which reach the significance threshold of suggestive association (p<1x10-5 threshold adjusted for multiple trait testing) and are associated with the COVID-19 susceptibility in the European ancestry (index rs17448496: odds ratio [OR] = 0.173; 95% confidence interval [CI], 0.08-0.36 for G allele; p=5.15x 10-5 and index rs768632395: OR = 0.166; 95% CI, 0.07-0.35 for A allele; p= 4.25x10-6, respectively), which were associated with two genes, PPP2R2B at 5q32, and LRRC4C at 11p12, respectively. To explore the linkage between HLA and COVID-19 severity, we applied fine-mapping analysis to dissect the HLA association with mild and severe cases. Using In-silico binding predictions to map the binding of risk/protective HLA to the viral structural proteins, we found the differential presentation of viral peptides in both ancestries. Lastly, extrapolation of the identified HLA from the cohort to the worldwide population revealed notable correlations. The study uncovers possible differences in susceptibility to COVID-19 in different ancestral origins in the genetic background, which may provide new insights into the pathogenesis and clinical treatment of the disease.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.30.486418", + "rel_abs": "SARS-CoV-2 nucleocapsid protein is an essential structural component of mature virions, encapsulating the genomic RNA and modulating RNA transcription and replication. Several of its activities might be associated with the proteins ability to undergo liquid-liquid phase separation. NSARS-CoV-2 contains an intrinsically disordered region at its N-terminus (NTE) that can be phosphorylated and is affected by disease-relevant mutations. Here we show that NTE deletion decreases the range of RNA concentrations that can induce phase separation of NSARS-CoV-2. In addition, deletion of the prion-like NTE allows NSARS-CoV-2 droplets to retain their liquid-like nature during incubation. We further demonstrate that RNA-binding engages multiple parts of the NTE and changes NTEs structural properties. The results form the foundation to characterize the impact of N-terminal mutations and post-translational modifications on the molecular properties of the SARS-CoV-2 nucleocapsid protein.\n\nStatementThe nucleocapsid protein of SARS-CoV-2 plays an important role in both genome packaging and viral replication upon host infection. Replication has been associated with RNA-induced liquid-liquid phase separation of the nucleocapsid protein. We present insights into the role of the N-terminal part of the nucleocapsid protein in the proteins RNA-mediated liquid-liquid phase separation.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Yiran Shen", - "author_inst": "University of Florida College of Veterinary Medicine" - }, - { - "author_name": "Bhuwan Khatri", - "author_inst": "Oklahoma Medical Research Foundation" - }, - { - "author_name": "Santosh Rananaware", - "author_inst": "University of Florida College of Engineering: University of Florida Herbert Wertheim College of Engineering" - }, - { - "author_name": "Danmeng Li", - "author_inst": "University of Florida College of Veterinary Medicine" + "author_name": "Milan Zachrdla", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE)" }, { - "author_name": "David Ostrov", - "author_inst": "University of Florida College of Medicine" + "author_name": "Adriana Savastano", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE)" }, { - "author_name": "Piyush Jain", - "author_inst": "University of Florida College of Medicine" + "author_name": "Alain Ibanez de Opakua", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE)" }, { - "author_name": "Christopher Lessard", - "author_inst": "Oklahoma Medical Research Foundation" + "author_name": "Maria-Sol Cima-Omori", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE)" }, { - "author_name": "Cuong Nguyen", - "author_inst": "University of Florida" + "author_name": "Markus Zweckstetter", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE)" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "new results", - "category": "genetics" + "category": "biophysics" }, { "rel_doi": "10.1101/2022.03.30.486409", @@ -358266,55 +358913,43 @@ "category": "sexual and reproductive health" }, { - "rel_doi": "10.1101/2022.03.29.486331", - "rel_title": "Genetic surveillance of SARS-CoV-2 Mpro reveals high sequence and structural conservation prior to the introduction of protease inhibitor Paxlovid", + "rel_doi": "10.1101/2022.03.28.22273033", + "rel_title": "Key topics in pandemic health risk communication: A qualitative study of expert opinions and knowledge", "rel_date": "2022-03-30", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.29.486331", - "rel_abs": "SARS-CoV-2 continues to represent a global health emergency as a highly transmissible, airborne virus. An important coronaviral drug target for treatment of COVID-19 is the conserved main protease (Mpro). Nirmatrelvir is a potent Mpro inhibitor and the antiviral component of Paxlovid. The significant viral sequencing effort during the ongoing COVID-19 pandemic represented a unique opportunity to assess potential nirmatrelvir escape mutations from emerging variants of SARS-CoV-2. To establish the baseline mutational landscape of Mpro prior to the introduction of Mpro inhibitors, Mpro sequences and its cleavage junction regions were retrieved from [~]4,892,000 high-quality SARS-CoV-2 genomes in GISAID. Any mutations identified from comparison to the reference sequence (Wuhan-hu-1) were cataloged and analyzed. Mutations at sites key to nirmatrelvir binding and protease functionality (e.g., dimerization sites) were still rare. Structural comparison of Mpro also showed conservation of key nirmatrelvir contact residues across the extended Coronaviridae family (alpha-, beta-, and gamma-coronaviruses). Additionally, we showed that over time the SARS-CoV-2 Mpro enzyme remained under purifying selection and was highly conserved relative to the spike protein. Now, with the EUA approval of Paxlovid and its expected widespread use across the globe, it is essential to continue large-scale genomic surveillance of SARS-CoV-2 Mpro evolution. This study establishes a robust analysis framework for monitoring emergent mutations in millions of virus isolates, with the goal of identifying potential resistance to present and future SARS-CoV-2 antivirals.\n\nImportanceThe recent authorization of oral SARS-CoV-2 antivirals, such as Paxlovid, has ushered in a new era of the COVID-19 pandemic. Emergence of new variants, as well as selective pressure imposed by antiviral drugs themselves, raise concern for potential escape mutations in key drug binding motifs. To determine the potential emergence of antiviral resistance in globally circulating isolates and its implications for the clinical response to the COVID-19 pandemic, sequencing of SARS-CoV-2 viral isolates before, during, and after the introduction of new antiviral treatments is critical. The infrastructure built herein for active genetic surveillance of Mpro evolution and emergent mutations will play an important role in assessing potential antiviral resistance as the pandemic progresses and Mpro inhibitors are introduced. We anticipate our framework to be the starting point in a larger effort for global monitoring of the SARS-CoV-2 Mpro mutational landscape.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.28.22273033", + "rel_abs": "BackgroundScience communication can provide people with more accurate information on pandemic health risks by translating complex scientific topics into language that helps people make more informed choices on how to protect themselves and others. During pandemics, experts in medicine, science, public health, and communication are important sources of knowledge for science communication. This study uses the COVID-19 pandemic to explore these experts opinions and knowledge of what to communicate to the public during a pandemic. The research question is: What are the key topics to communicate to the public about health risks during a pandemic?\n\nMethodWe purposively sampled 13 experts in medicine, science, public health, and communication for individual interviews, with a range of different types of knowledge of COVID-19 risk and communication at the national, regional and hospital levels in Norway. The interview transcripts were coded and analysed inductively in a qualitative thematic analysis.\n\nResultsThe studys findings emphasise three central topics pertaining to communication about pandemic health risk during the first year of the COVID-19 pandemic in Norway: 1) how the virus enters the human body and generates disease; 2) how to protect oneself and others from being infected; and 3) pandemic health risk for the individual and the society.\n\nConclusionThe key topics emerging from the expert interviews relate to concepts originating from multiple disciplinary fields, and can inform frameworks for interprofessional communication about health risks during a pandemic. The study highlights the complexity of communicating pandemic messages, due to scientific uncertainty, fear of risk amplification, and heterogeneity in public health and scientific literacy. The study contributes with insight into the complex communication processes of pandemic health risk communication.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Jonathan T Lee", - "author_inst": "Pfizer, Inc" - }, - { - "author_name": "Qingyi Yang", - "author_inst": "Pfizer Inc." - }, - { - "author_name": "Alexey Gribenko", - "author_inst": "Pfizer" - }, - { - "author_name": "B Scott Perrin Jr.", - "author_inst": "Pfizer Inc." + "author_name": "Siv Hilde Berg", + "author_inst": "University of Stavanger" }, { - "author_name": "Yuao Zhu", - "author_inst": "Pfizer Inc." + "author_name": "Marie Therese Shortt", + "author_inst": "University of Stavanger" }, { - "author_name": "Rhonda Cardin", - "author_inst": "Pfizer Inc." + "author_name": "Jo Roislien", + "author_inst": "University of Stavanger" }, { - "author_name": "Paul A Liberator", - "author_inst": "Pfizer, Inc." + "author_name": "Daniel Adrian Lungu", + "author_inst": "University of Stavanger" }, { - "author_name": "Annaliesa S Anderson", - "author_inst": "Pfizer (United States)" + "author_name": "Henriette Thune", + "author_inst": "University of Stavanger" }, { - "author_name": "Li Hao", - "author_inst": "Pfizer, Inc" + "author_name": "Siri Wiig", + "author_inst": "University of Stavanger" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "genomics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2022.03.24.22272837", @@ -361084,189 +361719,57 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.03.25.485832", - "rel_title": "A SARS-CoV-2 Spike Ferritin Nanoparticle Vaccine is Protective and Promotes a Strong Immunological Response in the Cynomolgus Macaque Coronavirus Disease 2019 (COVID-19) Model", + "rel_doi": "10.1101/2022.03.28.486075", + "rel_title": "An engineered ACE2 decoy receptor can be administered by inhalation and potently targets the BA.1 and BA.2 omicron variants of SARS-CoV-2", "rel_date": "2022-03-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.25.485832", - "rel_abs": "The COVID-19 pandemic has had a staggering impact on social, economic, and public health systems worldwide. Vaccine development and mobilization against SARS-CoV-2 (the etiologic agent of COVID-19) has been rapid. However, novel strategies are still necessary to slow the pandemic, and this includes new approaches to vaccine development and/or delivery, which improve vaccination compliance and demonstrate efficacy against emerging variants. Here we report on the immunogenicity and efficacy of a SARS-CoV-2 vaccine comprised of stabilized, pre-fusion Spike protein trimers displayed on a ferritin nanoparticle (SpFN) adjuvanted with either conventional aluminum hydroxide or the Army Liposomal Formulation QS-21 (ALFQ) in a cynomolgus macaque COVID-19 model. Vaccination resulted in robust cell-mediated and humoral responses and a significant reduction of lung lesions following SARS-CoV-2 infection. The strength of the immune response suggests that dose sparing through reduced or single dosing in primates may be possible with this vaccine. Overall, the data support further evaluation of SpFN as a SARS-CoV-2 protein-based vaccine candidate with attention to fractional dosing and schedule optimization.", - "rel_num_authors": 44, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.28.486075", + "rel_abs": "Monoclonal antibodies targeting the SARS-CoV-2 spike (S) glycoprotein neutralize infection and are efficacious for the treatment of mild-to-moderate COVID-19. However, SARS-CoV-2 variants have emerged that partially or fully escape monoclonal antibodies in clinical use. Notably, the BA.2 sublineage of B.1.1.529/omicron escapes nearly all monoclonal antibodies currently authorized for therapeutic treatment of COVID-19. Decoy receptors, which are based on soluble forms of the host entry receptor ACE2, are an alternative strategy that broadly bind and block S from SARS-CoV-2 variants and related betacoronaviruses. The high-affinity and catalytically active decoy sACE22.v2.4-IgG1 was previously shown to be effective in vivo against SARS-CoV-2 variants when administered intravenously. Here, the inhalation of sACE22.v2.4-IgG1 is found to increase survival and ameliorate lung injury in K18-hACE2 transgenic mice inoculated with a lethal dose of the virulent P.1/gamma virus. Loss of catalytic activity reduced the decoys therapeutic efficacy supporting dual mechanisms of action: direct blocking of viral S and turnover of ACE2 substrates associated with lung injury and inflammation. Binding of sACE22.v2.4-IgG1 remained tight to S of BA.1 omicron, despite BA.1 omicron having extensive mutations, and binding exceeded that of four monoclonal antibodies approved for clinical use. BA.1 pseudovirus and authentic virus were neutralized at picomolar concentrations. Finally, tight binding was maintained against S from the BA.2 omicron sublineage, which differs from S of BA.1 by 26 mutations. Overall, the therapeutic potential of sACE22.v2.4-IgG1 is further confirmed by inhalation route and broad neutralization potency persists against increasingly divergent SARS-CoV-2 variants.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Sara C Johnston", - "author_inst": "USAMRIID" - }, - { - "author_name": "Keersten M Ricks", - "author_inst": "USAMRIID" - }, - { - "author_name": "Ines Lakhal-Naouar", - "author_inst": "Walter Reed Army Institute of Research" - }, - { - "author_name": "Alexandra Jay", - "author_inst": "USAMRIID" - }, - { - "author_name": "Caroline Subra", - "author_inst": "Walter Reed Army Institute for Research" - }, - { - "author_name": "Jo Lynne Raymond", - "author_inst": "USAMRIID" - }, - { - "author_name": "Hannah A D King", - "author_inst": "NIH" - }, - { - "author_name": "Franco Rossi", - "author_inst": "USAMRIID" - }, - { - "author_name": "Tamara L Clements", - "author_inst": "USAMRIID" - }, - { - "author_name": "David Fetterer", - "author_inst": "USAMRIID" - }, - { - "author_name": "Samantha Tostenson", - "author_inst": "USAMRIID" - }, - { - "author_name": "Camila Macedo Cincotta", - "author_inst": "WRAIR" - }, - { - "author_name": "Holly R Hack", - "author_inst": "WRAIR" - }, - { - "author_name": "Caitlin Kuklis", - "author_inst": "WRAIR" - }, - { - "author_name": "Sandrine Soman", - "author_inst": "WRAIR" - }, - { - "author_name": "Jocelyn King", - "author_inst": "WRAIR" - }, - { - "author_name": "Kristina K Peachman", - "author_inst": "WRAIR" - }, - { - "author_name": "Dohoon Kim", - "author_inst": "WRAIR" - }, - { - "author_name": "Wei-Hung Chen", - "author_inst": "WRAIR" - }, - { - "author_name": "Rajeshwer S Sankhala", - "author_inst": "WRAIR" - }, - { - "author_name": "Elizabeth J Martinez", - "author_inst": "WRAIR" - }, - { - "author_name": "Agnes Hajduczki", - "author_inst": "WRAIR" - }, - { - "author_name": "William C Chang", - "author_inst": "WRAIR" - }, - { - "author_name": "Misook Choe", - "author_inst": "WRAIR" - }, - { - "author_name": "Paul V Thomas", - "author_inst": "WRAIR" - }, - { - "author_name": "Caroline E Peterson", - "author_inst": "WRAIR" - }, - { - "author_name": "Alexander Anderson", - "author_inst": "WRAIR" - }, - { - "author_name": "Isabella Swafford", - "author_inst": "WRAIR" - }, - { - "author_name": "Jeffrey R Currier", - "author_inst": "WRAIR" - }, - { - "author_name": "Dominic Paquin-Proulx", - "author_inst": "WRAIR" - }, - { - "author_name": "Linda L Jagodzinski", - "author_inst": "WRAIR" - }, - { - "author_name": "Gary R Matyas", - "author_inst": "WRAIR" - }, - { - "author_name": "Mangala Rao", - "author_inst": "WRAIR" - }, - { - "author_name": "Gregory D Gromowski", - "author_inst": "WRAIR" + "author_name": "Lianghui Zhang", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Sheila A Peel", - "author_inst": "WRAIR" + "author_name": "Krishna Kumar Narayanan", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Lauren White", - "author_inst": "USAMRIID" + "author_name": "Laura Cooper", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Jeffrey M Smith", - "author_inst": "USAMRIID" + "author_name": "Kui K Chan", + "author_inst": "Cyrus Biotechnology, Inc." }, { - "author_name": "Jay W Hooper", - "author_inst": "USAMRIID" + "author_name": "Christine Anne Devlin", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Nelson L L Michael", - "author_inst": "WRAIR" + "author_name": "Aaron Aguhob", + "author_inst": "Cyrus Biotechnology, Inc." }, { - "author_name": "Kayvon Modjarrad", - "author_inst": "WRAIR" + "author_name": "Kristie Shirley", + "author_inst": "Cyrus Biotechnology, Inc." }, { - "author_name": "M. Gordon Joyce", - "author_inst": "WRAIR" + "author_name": "Lijun Rong", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Aysegul Nalca", - "author_inst": "USAMRIID" + "author_name": "Jalees Rehman", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Diane L Bolton", - "author_inst": "WRAIR" + "author_name": "Asrar B Malik", + "author_inst": "University of Illinois at Chicago" }, { - "author_name": "Margaret LM Pitt", - "author_inst": "USAMRIID" + "author_name": "Erik Procko", + "author_inst": "University of Illinois at Urbana-Champaign" } ], "version": "1", @@ -363226,59 +363729,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.03.24.22272854", - "rel_title": "Vaccine effectiveness with BNT162b2 (Comirnaty, Pfizer-BioNTech) vaccine against reported SARS-CoV-2 Delta and Omicron infection among adolescents, Norway, August 2021 to January 2022", + "rel_doi": "10.1101/2022.03.25.22272950", + "rel_title": "THE IMPACT OF ROUTINES ON EMOTIONAL AND BEHAVIOURAL DIFFICULTIES IN CHILDREN AND ON PARENTAL ANXIETY DURING COVID-19", "rel_date": "2022-03-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.24.22272854", - "rel_abs": "BackgroundCOVID-19 vaccination was recommended for adolescents in Norway since August 2021. In this population-based cohort study, we estimated the BNT162b2 vaccine effectiveness against any PCR-confirmed (symptomatic or not) SARS-CoV-2 infections caused by the Delta and Omicron variant among adolescents (12-17-years-old) in Norway from August 2021 to January 2022.\n\nMethodsUsing Cox proportional hazard models, we estimated the BNT162b2 vaccine effectiveness against any Delta and Omicron infections. Vaccine status was included as a time-varying covariate and models were adjusted for age, sex, comorbidities, county of residence, country of birth, and living conditions. Data were obtained from the National Preparedness registry for COVID-19, which contains individual-level data from national health and administrative registries.\n\nFindingsVaccine effectiveness against Delta infection peaked at 68% (95%CI: 64-71%) and 62% (95%CI: 57- 66%) in days 21-48 after the first dose among 12-15-year-olds and 16-17-year-olds respectively. Among 16-17-year-olds that received two doses, vaccine effectiveness peaked at 93% (95%CI: 90-95%) in days 35-62 and declined to 84% (95%CI: 76-89%) in 63 days or more after the second dose. For both age-groups, we found no protection against Omicron infection after receiving one dose. Among 16-17-year-olds, vaccine effectiveness against Omicron infection peaked at 53% (95%CI: 43-62%) in 7-34 days after the second dose and decreased to 23% (95%CI: 3-40%) in 63 days or more after vaccination. Vaccine effectiveness decreased with time since vaccination for both variants, but waning was observed to occur faster for Omicron.\n\nInterpretationOur results suggest reduced protection from BNT162b2 vaccination against any SARS-CoV-2 infection caused by the Omicron variant compared to the Delta. In addition, waning immunity was observed to occur faster for Omicron. The impact of vaccination among adolescents on reducing infection and thus transmission is limited during omicron dominance.\n\nFundingNo funding was received.\n\nResearch in context\n\nEvidence before this studyBNT162b2 (Comirnaty, Pfizer-BioNTech) and mRNA-1273 (Spikevax, Moderna) vaccines have been approved for use in adolescents, based on results from randomized placebo-controlled trials demonstrating comparable immunogenicity and safety profile as in young adults. In addition, observational studies from Israel, the USA and England have reported high protection of BNT162b2 vaccines against SARS-CoV-2 Delta infection among adolescents. These studies also reported decrease in effectiveness with time since last vaccine dose. Evidence on the effect of an extended interval between doses, longer time since vaccination and the effect against different variants is limited. When we first planned this study in early February 2022, no data were available regarding vaccine effectiveness against SARS-CoV-2 Omicron infection among adolescents. To our knowledge when we completed this study and before submitting this article, only one study from England reported results in a preprint on vaccine effectiveness against symptomatic SARS-CoV-2 Omicron infection among adolescents. We searched for studies that evaluated vaccine efficacy or effectiveness after vaccination of adolescents during 2021-2022 in PubMed, medRxiv, bioRxiv, SSRN. We searched for studies with several variations of the primary key search terms \"COVID-19\", \"SARS-CoV-2\", and \"vaccine\" (including names of specific vaccines, as BNT162b2), \"vaccine effectiveness\", \"adolescents\", \"children\".\n\nAdded value of this studyThe rapid increase in the incidence of SARS-CoV-2 infection caused by the Omicron variant in highly vaccinated populations has raised concerns about the effectiveness of current vaccines in adults but also adolescents. In this population-based cohort study, we showed that the vaccine effectiveness against Omicron is lower than against Delta infections among adolescents, including symptomatic and asymptomatic infections. We should note that evidence suggests higher rates of asymptomatic carriage for Omicron than other variants of concern. Vaccine effectiveness that includes asymptomatic cases, as in the study from England, is expected to be lower than when including symptomatic cases only. We found that one and two doses of BNT162b2 among adolescents protected well against Delta. Vaccination provided high protection against Delta infections (>91%) among Norwegian 16-17-year-olds 7-62 days after the second dose. We found no protection against Omicron SARS-CoV-2 infection after one vaccine dose, and moderate effectiveness after two doses (peaked at 53%) among the 16-17-year-olds. Moreover, waning immunity was observed to occur faster for Omicron.\n\nImplications of all the available evidenceBased on the available evidence, the vaccine effectiveness among adolescents is similar to that reported among adults, also with an extended period of 8-12 weeks between doses which was used in Norway. Protection is significantly lower against Omicron than Delta infections and immunity wanes faster against Omicron. The impact of vaccination among adolescents on reducing infection and thus transmission is limited during omicron dominance. Policies should take into account the impact of vaccination campaigns among adolescents and their primary objective. Vaccine effectiveness should be re-evaluated when other variants appear as they might have different outcomes as shown between Delta and Omicron infections.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.25.22272950", + "rel_abs": "Aims and hypothesisWe hypothesised that there would be an association between maintaining a routine during lockdown and both lower emotional and behavioural difficulties in children and lower parental anxiety. We also hypothesised that children of keyworker parents would have fewer emotional and behavioural symptoms due to having maintained more normal routines.\n\nBackgroundThe Covid-19 pandemic and related public health measures have impacted on mental health of children.\n\nMethodsWe used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) to explore associations between maintaining a routine, and emotional and behavioural difficulties in children, using linear regression models. We included measures of parental anxiety. We separately explored associations with having a keyworker parent. We used the Carey Infant Temperament Questionnaire and the Revised Rutter Parent Scale for Preschool Children to establish levels of emotional and behavioural difficulties.\n\nResults289 parents completed questionnaires about their 411 children. Keeping a routine was associated with emotional and behavioural difficulty scores 5.0 points lower (95% CI -10.0 to - 0.1), p=0.045 than not keeping a routine. Parents who reported keeping a routine had anxiety scores 4.3 points lower (95% CI -7.5 to -1.1), p=0.009 than those who did not. Children of keyworkers tended to have lower emotional and behavioural difficulty scores (-3.1 (95%CI -6.26 to 0.08), p=0.056) than children of non-keyworkers. All models were adjusted for relevant potential confounders.\n\nConclusionMaintaining a routine may be beneficial for both child emotional wellbeing and parental anxiety, although it is also possible that lower parental anxiety levels made maintaining a routine easier. Being the child of a keyworker parent during lockdown may have been protective for child emotional wellbeing.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Lamprini Veneti", - "author_inst": "Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway" + "author_name": "Vera Lees", + "author_inst": "Gloucestershire Health and Care NHS Foundation Trust" }, { - "author_name": "Jacob Dag Berild", - "author_inst": "Department of Infection Control and Vaccines, Norwegian Institute of Public Health, Oslo, Norway" + "author_name": "Rosie Hay", + "author_inst": "Gloucestershire Health and Care NHS Foundation Trust" }, { - "author_name": "Sara Viksmoen Watle", - "author_inst": "Department of Infection Control and Vaccines, Norwegian Institute of Public Health, Oslo, Norway" - }, - { - "author_name": "Jostein Starrfelt", - "author_inst": "Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway" - }, - { - "author_name": "Margrethe Greve-Isdahl", - "author_inst": "Department of Infection Control and Vaccines, Norwegian Institute of Public Health, Oslo, Norway" - }, - { - "author_name": "Petter Langlete", - "author_inst": "Department of Infection Control and Preparedness, Norwegian Institute of Public Health, Oslo, Norway" + "author_name": "Helen Bould", + "author_inst": "Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol," }, { - "author_name": "Hakon Boas", - "author_inst": "Department of Infection Control and Vaccines, Norwegian Institute of Public Health, Oslo, Norway" + "author_name": "Alex Siu Fung Kwong", + "author_inst": "University of Bristol" }, { - "author_name": "Karoline Bragstad", - "author_inst": "Department of Virology, Norwegian Institute of Public Health, Oslo, Norway" + "author_name": "Daniel Smith", + "author_inst": "University of Bristol" }, { - "author_name": "Olav Hungnes", - "author_inst": "Department of Virology, Norwegian Institute of Public Health, Oslo, Norway" + "author_name": "Daphne Kounali", + "author_inst": "University of Bristol" }, { - "author_name": "Hinta Meijerink", - "author_inst": "Department of Infection Control and Vaccines, Norwegian Institute of Public Health, Oslo, Norway" + "author_name": "Rebecca Pearson", + "author_inst": "Manchester Metropolitan University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2022.03.24.22272864", @@ -364772,55 +365263,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.03.21.22272673", - "rel_title": "Sequential appearance and isolation of a SARS-CoV-2 recombinant between two major SARS-CoV-2 variants in a chronically infected immunocompromised patient", + "rel_doi": "10.1101/2022.03.22.484725", + "rel_title": "Jupytope: Computational extraction of structural properties of viral epitopes", "rel_date": "2022-03-23", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.21.22272673", - "rel_abs": "Genetic recombination is a major evolutionary mechanism among RNA viruses, and it is common in coronaviruses, including those infecting humans. A few SARS-CoV-2 recombinants have been reported to date whose genome harbored combinations of mutations from different mutants or variants, but a single patients sample was analyzed, and the virus was not isolated. Here, we re-port the gradual creation of a hybrid genome of B.1.160 and Alpha variants in a lymphoma patient chronically infected for 14 months, and we isolated the recombinant virus. The hybrid genome was obtained by next-generation sequencing, and recombination sites were confirmed by PCR. This consisted of a parental B.1.160 backbone interspersed with two fragments, including the spike gene, from an Alpha variant. Analysis of seven sequential samples from the patient decoded the recombination steps, including the initial infection with a B.1.160 variant, then a concurrent infec-tion with this variant and an Alpha variant, the generation of hybrid genomes, and eventually the emergence of a predominant recombinant virus isolated at the end of the patients follow-up. This case exemplifies the recombination process of SARS-CoV-2 in real life, and it calls for intensifying genomic surveillance in patients coinfected with different SARS-CoV-2 variants, and more gener-ally with several RNA viruses, as this may lead to the creation of new viruses.", - "rel_num_authors": 9, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.22.484725", + "rel_abs": "Epitope residues located on viral surface proteins are of immense interest in immunology and related applications such as vaccine development, disease diagnosis and drug design. Most tools rely on sequence based statistical comparisons, such as information entropy of residue positions in aligned columns to infer location and properties of epitope sites. To facilitate cross-structural comparisons of epitopes on viral surface proteins, a python-based extraction tool implemented with Jupyter notebook is presented (Jupytope). Given a viral antigen structure of interest, a list of known epitope sites and a reference structure, the corresponding epitope structural properties can quickly be obtained. The tool integrates biopython modules for commonly used software such as NACCESS, DSSP as well as residue depth and outputs a list of structure derived properties such as dihedral angles, solvent accessibility, residue depth and secondary structure that can be saved in several convenient data formats. To ensure correct spatial alignment, Jupytope takes a list of given epitope sites and their corresponding reference structure and aligns them before extracting the desired properties. Examples are demonstrated for epitopes of Influenza and SARS-CoV2 viral strains. The extracted properties assist detection of two Influenza subtypes and show potential in distinguishing between four major clades of SARS-CoV2, as compared with randomized labels. The tool will facilitate analytical and predictive works on viral epitopes through the extracted structural information.\n\nKey MessagesO_LIJupytope combines existing 3D-structural software to extract the properties of viral epitopes into a convenient text or csv file format\nC_LIO_LIThe structural properties serve as parameters or features that quantitatively capture viral epitopes\nC_LIO_LIAssociation of structural properties to viral subtypes (for Influenza) or clades (SARS-CoV2) is demonstrated with a simple XGBoost model\nC_LIO_LIStructure datasets mapped to SARS-CoV2 WHO clades and Pango lineages, as well as chain annotations are available for download\nC_LI", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Emilie Burel", - "author_inst": "IHU Mediterranee Infection" + "author_name": "Shamima Rashid", + "author_inst": "Nanyang Technological University, Singapore" }, { - "author_name": "Philippe Colson", - "author_inst": "Aix-Marseille university" + "author_name": "Teng Ann Ng", + "author_inst": "Nanyang Technological University, Singapore" }, { - "author_name": "Jean-Christophe Lagier", - "author_inst": "IHU Mediterranee Infection" - }, - { - "author_name": "Anthony LEVASSEUR", - "author_inst": "Aix-Marseille University" - }, - { - "author_name": "Marielle Bedotto", - "author_inst": "IHU Mediterranee Infection" - }, - { - "author_name": "Philippe Lavrard", - "author_inst": "IHU Mediterranee Infection" - }, - { - "author_name": "Pierre-Edouard Fournier", - "author_inst": "IHU Mediterranee Infection" - }, - { - "author_name": "Bernard LA SCOLA", - "author_inst": "Aix Marseille University" - }, - { - "author_name": "Didier Raoult", - "author_inst": "Aix-Marseille Universite IHU Mediterranee Infection" + "author_name": "Chee Keong Kwoh", + "author_inst": "Nanyang Technological University, Singapore" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nd", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2022.03.22.485418", @@ -366874,23 +367341,107 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.03.21.22272722", - "rel_title": "The dramatic surge of excess mortality in the United States between 2017 and 2021", + "rel_doi": "10.1101/2022.03.20.22271891", + "rel_title": "Immunogenic superiority and safety of Biological E CORBEVAX vaccine compared to COVISHIELD (ChAdOx1 nCoV-19) vaccine studied in a phase III, single blind, multicenter, randomized clinical trial", "rel_date": "2022-03-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.21.22272722", - "rel_abs": "A mortality gap between the United States and other high-income nations emerged before the pandemic. International comparisons of Covid-19 mortality suggest this gap might have increased during the pandemic.\n\nApplying average mortality rates of the five largest West European countries to the US population shows that the number of \"excess deaths\" attributable to this mortality gap continues to increase year after year in the United States. The annual number of such excess deaths has doubled between 2017 and 2021, with most of the increase occurring during the pandemic (+89.1% between 2019 and 2021). In 2021, excess mortality in the United States relative to its European peers contributed 892,491 excess deaths, amounting to 25.8% of all US deaths that year, up from 15.7% in 2017.\n\nOf the 450,224 excess deaths added between 2017 and 2021, 42,317 are attributable to population change (9.4%), 230,672 to differential rates of Covid-19 mortality (51.2%), and the remaining 177,235 to differential rates of mortality from other causes (39.4%, possibly including misclassified deaths due to Covid-19). The contribution of Covid-19 mortality to excess mortality in the United States (relative to its European peers) grew between 2020 and 2021 due to diverging trends in Covid-19 mortality, especially towards the end of 2021 as US vaccination rates plateaued at lower levels than in European countries. While this contribution might be transient, divergent trends in mortality from other causes persistently separates the United States from West European countries. Excess mortality is particularly high between ages 15 and 64. In 2021, nearly half of all US deaths in this age range are excess deaths (48.0%).", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.20.22271891", + "rel_abs": "BackgroundOptimum formulation of Biological Es CORBEVAX vaccine that contains protein sub unit of Receptor Binding Domain (RBD) from the spike protein of SARS-COV-2 formulated with aluminum hydroxide (Al3+) and CpG1018 as adjuvants was selected in phase-1 and 2 studies and proven to be safe, well tolerated and immunogenic in healthy adult population. In the current study, additional data was generated to determine immunogenic superiority of CORBEVAX vaccine over COVISHIELD vaccine and safety in larger and older population.\n\nMethodsThis is a phase III prospective, single blinded, randomized, active controlled study (CTRI/2021/08/036074) conducted at 20 sites across India in healthy adults aged between 18-80 years. This study has two arms; immunogenicity arm and safety arm. Participants in immunogenicity arm were randomized equally to either CORBEVAX or COVISHIELD vaccination groups to determine the immunogenic superiority. Healthy adults without a history of Covid-19 vaccination or SARS-CoV-2 infection, were enrolled.\n\nFindingsThe safety profile of CORBEVAX vaccine was comparable to the comparator vaccine COVISHIELD in terms of overall AE rates, related AE rates and medically attended AEs. Majority of reported AEs were mild in nature, and overall CORBEVAX appeared to cause fewer local and systemic adverse reactions/events. Overall, two grade-3 serious AEs (Dengue fever and femur fracture) were reported and they are unrelated to study vaccine. Neutralizing Antibody titers, against both Ancestral and Delta strain, induced post two-dose vaccination regimen were higher in the CORBEVAX arm as compared to COVISHIELD and the analysis of GMT ratios demonstrated immunogenic superiority of CORBEVAX in comparison with COVISHIELD. Both CORBEVAX and COVISHIELD vaccines showed comparable seroconversion post vaccination when assessed against anti-RBD IgG response. The subjects in CORBEVAX cohort also exhibited higher Interferon-gamma secreting PBMCs post stimulation with SARS-COV-2 RBD peptides than the subjects in COVISHIELD cohort.\n\nInterpretationsNeutralizing antibody titers induced by CORBEVAX vaccine against Delta and Ancestral strains were protective, indicative of vaccine effectiveness of >90% for prevention of symptomatic infections based on the Correlates of Protection assessment performed during Moderna and Astra-Zeneca vaccine Phase III studies. Safety findings revealed that CORBEVAX vaccine has excellent safety profile when tested in larger and older population.\n\nFundingBIRAC-division of Department of Biotechnology, Government of India, and the Coalition for Epidemic Preparedness Innovations funded the study.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Patrick Heuveline", - "author_inst": "UCLA" + "author_name": "Subhash Thuluva", + "author_inst": "Biological E. Limited" + }, + { + "author_name": "Vikram Paradkar", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Kishore Turaga", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Subbareddy Gunneri", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Vijay Yerroju", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Rammohan Reddy Mogulla", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Venkata Suneetha Pothakamuri", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Mahesh Kyasani", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Senthilkumar Manoharan", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Srikanth Adabala", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Aditya Sri Javvadi", + "author_inst": "Biological E Limited" + }, + { + "author_name": "Guruprasad R Medigeshi", + "author_inst": "Translational Health Science and Technology Institute" + }, + { + "author_name": "Janmejay Singh", + "author_inst": "Translational Health Science and Technology Institute" + }, + { + "author_name": "Heena Shaman", + "author_inst": "Translational Health Science and Technology Institute" + }, + { + "author_name": "Akshay Binayke", + "author_inst": "Translational Health Science and Technology Institute" + }, + { + "author_name": "Aymaan Zaheer", + "author_inst": "Translational Health Science and Technology Institute" + }, + { + "author_name": "Amit Awasrhi", + "author_inst": "Translational Health Science and Technology Institute" + }, + { + "author_name": "Chandramani Singh", + "author_inst": "All India Institute of Medical Sciences" + }, + { + "author_name": "Venkateshwar Rao A", + "author_inst": "Department of General Medicine, St. Theresa Hospital" + }, + { + "author_name": "Indranil Basu", + "author_inst": "Shubham Sudbhawana Hospital, Varanasi" + }, + { + "author_name": "Akash Ashok Kumar Khobragade", + "author_inst": "Grant Medical College & Sir J.J Hospital, Mumbai" + }, + { + "author_name": "Anil Kumar Pandey", + "author_inst": "ESIC Medical College & Hospital, Faridabad" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.03.21.22272672", @@ -368760,31 +369311,99 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2022.03.19.22272644", - "rel_title": "More severe pneumonitis in children predicts the need for admission and elevation of some but not all markers of severe Covid-19.", + "rel_doi": "10.1101/2022.03.19.484981", + "rel_title": "Identification of a Novel SARS-CoV-2 Delta-Omicron Recombinant Virus in the United States", "rel_date": "2022-03-21", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.19.22272644", - "rel_abs": "Unlike most other viral pneumonitis, SARS-CoV-2 often causes hyperferritinemia, elevations in D-dimer, lactate dehydrogenase (LDH), transaminases, troponin, CRP, and other inflammatory markers. We questioned (1) if the severity of pneumonitis observed on lung ultrasound was associated with hospitalization and (2) could lung ultrasound be used to stratify which children needed blood tests?\n\nMethodsWe did a retrospective cross-sectional review of children aged between 14 days and 21 years of age being evaluated for Covid-19 in our pediatric emergency department from 30/November/2019 to 14/August/2021 who had had a point-of-care lung ultrasound. Lung ultrasounds were categorized using a 6-point ordinal scale. We used logistic regression to estimate the adjusted effect of lung ultrasound on hospital admission. We performed ordinary least square regression for the association between lung ultrasound severity and laboratory abnormalities. We adjusted these using propensity score derived inverse probability weighting to account for the non-random decision to obtain laboratory investigations.\n\nResultsWe identified 500 point-of-care lung ultrasounds of which 427 could be assigned a severity category. Increasing lung ultrasound severity was associated with increased hospital admission OR 1.36(95% CI 1.08, 1.72.) Ferritin, LDH, transaminases, and D-dimer, but not CRP or troponin were significantly associated with more than moderately severe lung ultrasounds. D-Dimer, CRP, and troponin were sometimes elevated even when lung ultrasound was normal.\n\nConclusionSeverity of pneumonitis was associated with hospital admission. Ferritin, LDH, transaminases, and D-dimer were increased in more than moderately severe pneumonitis but lung ultrasound did not predict elevation of other markers.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.19.484981", + "rel_abs": "Recombination between SARS-CoV-2 virus variants can result in different viral properties (e.g., infectiousness or pathogenicity). In this report, we describe viruses with recombinant genomes containing signature mutations from Delta and Omicron variants. These genomes are the first evidence for a Delta-Omicron hybrid Spike protein in the United States.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Paul Walsh", - "author_inst": "Sutter Medical Center Sacramento" + "author_name": "Kristine A Lacek", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Andrea Hankins", - "author_inst": "Sutter Institute for Medical Research" + "author_name": "Benjamin Rambo-Martin", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Heejung Bang", - "author_inst": "University of California Davis" + "author_name": "Dhwani Batra", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Xiao-yu Zheng", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Matthew W Keller", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Malania Wilson", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Mili Sheth", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Morgan Davis", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Mark Burroughs", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Jonathan Gerhart", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Norman Hassell", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Justin Lee", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Samuel S Shepard", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Peter W Cook", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "David E Wentworth", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "John R Barnes", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Rebecca Kondor", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Clinton R Paden", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Thomas P R Peacock", + "author_inst": "University College London (UCL)" + }, + { + "author_name": "Hitoshi Sakaguchi", + "author_inst": "None" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "license": "cc0", + "type": "new results", + "category": "genomics" }, { "rel_doi": "10.1101/2022.03.18.484953", @@ -370794,77 +371413,65 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.03.16.22271100", - "rel_title": "Effectiveness of whole virus COVID-19 vaccine at protecting health care personnel against SARS-CoV-2 infections in Lima, Peru", + "rel_doi": "10.1101/2022.03.17.22272479", + "rel_title": "Characteristics of mental health stability during COVID-19: An online survey with people residing in the Liverpool City Region", "rel_date": "2022-03-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.16.22271100", - "rel_abs": "In February 2021, Peru launched a vaccination campaign among healthcare personnel using BBIBP-CorV inactivated whole virus (BBIBP-CorV) COVID-19 vaccine. Two doses of BBIBP-CorV vaccine are recommended, 21 days apart. Data on BBIBP-CorV vaccine effectiveness will inform the use and acceptance of vaccination with BBIBP-CorV vaccine.\n\nWe evaluated BBIBP-CorV vaccine effectiveness among an existing multi-year influenza cohort at two hospitals in Lima. We analyzed data on 290 participants followed between February and May 2021. Participants completed a baseline questionnaire and provided weekly self-collected anterior nasal swabs tested for SARS-CoV-2 by rRT-PCR for sixteen weeks. We performed multivariable logistic regression models adjusting for pre-selected characteristics (age, sex, exposure to COVID-19 patients, work in intensive care unit or emergency department, BMI, and exposure time in days). BBIBP-CorV vaccine effectiveness was calculated after the two-week post-vaccination period as (1-Odds Ratio for testing SARS-CoV-2 positive)x100%.\n\nSARS-CoV-2 was detected by rRT-PCR among 25 (9%) participants during follow-up (February-May 2021). Follow-up period ranged 1-11 weeks (median: 2 weeks). Among cohort participants who were fully vaccinated the adjusted vaccine effectiveness against SARS-CoV-2 infection was estimated as 95% (95% CI: 70%, 99%) and 100% (95% CI: 88%, 100%) for those partially vaccinated.\n\nDuring the study period, vaccination of healthcare personnel with BBIBP-CorV vaccine was effective at reducing SARS-CoV-2 infections in the weeks immediately following vaccination. This information can be used to support vaccination efforts in the region, especially among those who could be concerned about their effectiveness.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.17.22272479", + "rel_abs": "Background and aimDespite the significant mental health challenges the COVID-19 pandemic and its associated government measures have presented, research have shown that the majority of people have adapted and coped well. The aim of this study was i) to determine the proportion of people with mental stability and volatility during the pandemic in a North West urban environment sample and ii) to establish group differences in psychosocial variables. Mental stability and volatility refer to the extent to which individuals reported change in levels of common mental health symptoms over the course of 12 weeks.\n\nMethoda two-wave-online survey (N = 163) was used to explore the psychological and social impact of the pandemic on relatively disadvantaged neighbourhoods within the Liverpool City Region over 12 weeks. Kruskal-Wallis with post-hoc tests were used to determine how people with mental stability and volatility differed on factors categorised within an ecological framework of resilience (individual, community, societal, and COVID-19 specific).\n\nResultsIndividuals categorised as stable in terms of mental health symptoms (63.6%) had better mental and physical health; were more tolerant of uncertainty; reported higher levels of resilience and wellbeing compared to very volatile people (19.8%). These individuals also reported feeling less socially isolated, experienced a greater sense of belonging to their community which was more likely to fulfil their needs, and were more likely to have access to green space nearby for their recommended daily exercise. Stable individuals did not report worrying any more during the pandemic than usual and tolerated uncertainty better compared to those in the volatile group.\n\nImplicationsThe majority of participants in this sample were mentally stable and coping well with the challenges presented by the pandemic. The resilience of these individuals was related to key place-based factors such as a strong sense of community and useable local assets. The data showcase the role of place-based social determinants in supporting resilience and thereby highlight key preventative measures for public mental health during times of international crisis.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Carmen Arriola", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Giselle Soto", - "author_inst": "Naval Medical Research Unit No 6 (NAMRU-6)" - }, - { - "author_name": "Matthew Westercamp", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Susan Bollinger", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Katalin Ujhelyi Gomez", + "author_inst": "University of Liverpool" }, { - "author_name": "Angelica Espinoza", - "author_inst": "Naval Medical Research Unit No 6 (NAMRU-6)" + "author_name": "Rhiannon Corcoran", + "author_inst": "University of Liverpool" }, { - "author_name": "Max Grogl", - "author_inst": "Naval Medical Research Unit No 6 (NAMRU-6)" + "author_name": "Adele Ring", + "author_inst": "University of Liverpool" }, { - "author_name": "Alejandro Llanos-Cuentas", - "author_inst": "Cayetano Heredia Hospital" + "author_name": "Shaima Hassan", + "author_inst": "University of Liverpool" }, { - "author_name": "Eduardo Matos", - "author_inst": "Arzobispo Loayza National Hospital" + "author_name": "Katherine Abba", + "author_inst": "University of Liverpool" }, { - "author_name": "Candice Romero", - "author_inst": "Naval Medical Research Unit No 6 (NAMRU-6)" + "author_name": "Jennifer Downing", + "author_inst": "University of Liverpool" }, { - "author_name": "Maria Silva", - "author_inst": "Naval Medical Research Unit No 6 (NAMRU-6)" + "author_name": "Mark Goodall", + "author_inst": "University of Liverpool" }, { - "author_name": "Rachel Smith", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Mark Gabbay", + "author_inst": "University of Liverpool" }, { - "author_name": "Natalie Olson", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Pam Clarke", + "author_inst": "University of Liverpool" }, { - "author_name": "Michael Prouty", - "author_inst": "Naval Medical Research Unit No 6 (NAMRU-6)" + "author_name": "Paul Moran", + "author_inst": "University of Liverpool" }, { - "author_name": "Eduardo Azziz-Baumgartner", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Dorcas Akeju Obe", + "author_inst": "University of Liverpool" }, { - "author_name": "Fernanda Lessa", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Kate M Bennett", + "author_inst": "University of Liverpool" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -372600,83 +373207,59 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.03.15.484467", - "rel_title": "A conserved immune trajectory of recovery in hospitalized COVID-19 patients", + "rel_doi": "10.1101/2022.03.16.22271983", + "rel_title": "Minimal SARS-CoV-2 classroom transmission at a large urban university experiencing repeated into campus introduction", "rel_date": "2022-03-16", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.15.484467", - "rel_abs": "Many studies have provided insights into the immune response to COVID-19; however, little is known about the immunological changes and immune signaling occurring during COVID-19 resolution. Individual heterogeneity and variable disease resolution timelines obscure unifying immune characteristics. Here, we collected and profiled >200 longitudinal peripheral blood samples from patients hospitalized with COVID-19, with other respiratory infections, and healthy individuals, using mass cytometry to measure immune cells and signaling states at single cell resolution. COVID-19 patients showed a unique immune composition and an early, coordinated and elevated immune cell signaling profile, which correlated with early hospital discharge. Intra-patient time course analysis tied to clinically relevant events of recovery revealed a conserved set of immunological processes that accompany, and are unique to, disease resolution and discharge. This immunological process, together with additional changes in CD4 regulatory T cells and basophils, accompanies recovery from respiratory failure and is associated with better clinical outcomes at the time of admission. Our work elucidates the biological timeline of immune recovery from COVID-19 and provides insights into the fundamental processes of COVID-19 resolution in hospitalized patients.", - "rel_num_authors": 16, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.16.22271983", + "rel_abs": "SARS-CoV-2, the causative agent of COVID-19, has displayed person to person transmission in a variety of indoor situations. This potential for robust transmission has posed significant challenges to day-to-day activities of colleges and universities where indoor learning is a focus. Concerns about transmission in the classroom setting have been of concern for students, faculty and staff. With the simultaneous implementation of both non-pharmaceutical and pharmaceutical control measures meant to curb the spread of the disease, defining whether in-class instruction without any physical distancing is a risk for driving transmission is important. We examined the evidence for SARS-CoV-2 transmission on a large urban university campus that mandated vaccination and masking but was otherwise fully open without physical distancing during a time of ongoing transmission of SARS-CoV-2 both at the university and in the surrounding counties. Using weekly surveillance testing of all on-campus individuals and rapid contact tracing of individuals testing positive for the virus we found little evidence of in-class transmission. Of more than 140,000 in-person class events, only nine instances of potential in-class transmission were identified. When each of these events were further interrogated by whole-genome sequencing of all positive cases significant genetic distance was identified between all potential in-class transmission pairings, providing evidence that all individuals were infected outside of the classroom. These data suggest that under robust transmission abatement strategies, in-class instruction is not an appreciable source of disease transmission.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Trine Line Hauge Okholm", - "author_inst": "University of California San Francisco" - }, - { - "author_name": "Cassandra E Burnett", - "author_inst": "University of California San Francisco" - }, - { - "author_name": "Iliana Tenvooren", - "author_inst": "University of California San Francisco" - }, - { - "author_name": "Diana M Marquez", - "author_inst": "University of California San Francisco" - }, - { - "author_name": "Stanley Tamaki", - "author_inst": "University of California San Francisco" - }, - { - "author_name": "Priscila Munoz Sandoval", - "author_inst": "University of California San Francisco" - }, - { - "author_name": "- The UCSF COMET Consortium", - "author_inst": "-" + "author_name": "Kayla J Kuhfeldt", + "author_inst": "Boston University" }, { - "author_name": "Carolyn S Calfee", - "author_inst": "University of California San Francisco" + "author_name": "Jacquelun Turcinovic", + "author_inst": "Boston University/NEIDL" }, { - "author_name": "Carolyn M Hendrickson", - "author_inst": "University of California San Francisco" + "author_name": "Madison L Sullivan", + "author_inst": "Boston University" }, { - "author_name": "Kirsten N Kangelaris", - "author_inst": "University of California San Francisco" + "author_name": "Lena Landaverde", + "author_inst": "Boston University" }, { - "author_name": "Charles R Langelier", - "author_inst": "University of California San Francisco" + "author_name": "Lynn Doucette-Stamm", + "author_inst": "Boston University" }, { - "author_name": "Matthew F Krummel", - "author_inst": "University of California San Francisco" + "author_name": "Davidson H Hamer", + "author_inst": "Boston University School of Public Health" }, { - "author_name": "Prescott G Woodruff", - "author_inst": "University of California San Francisco" + "author_name": "Judy Platt", + "author_inst": "Boston University" }, { - "author_name": "David J Erle", - "author_inst": "UCSF" + "author_name": "Catherine M. Klapperich", + "author_inst": "Boston University College of Engineering" }, { - "author_name": "Karl Mark Ansel", - "author_inst": "UCSF" + "author_name": "Hannah E Landsberg", + "author_inst": "Boston University" }, { - "author_name": "Matthew H. Spitzer", - "author_inst": "University of California, San Francisco" + "author_name": "John Connor", + "author_inst": "Boston University/NEIDL" } ], "version": "1", - "license": "cc_by_nd", - "type": "new results", - "category": "immunology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.03.16.484554", @@ -374402,31 +374985,51 @@ "category": "dentistry and oral medicine" }, { - "rel_doi": "10.1101/2022.03.10.22272193", - "rel_title": "Presence of Mediastinal Lymphadenopathy in Hospitalized Covid-19 Patients in a Tertiary Care Hospital in Pakistan - A cross-sectional study", + "rel_doi": "10.1101/2022.03.11.483867", + "rel_title": "Accelerating PERx Reaction Enables Covalent Nanobodies for Potent Neutralization of SARS-Cov-2 and Variants", "rel_date": "2022-03-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.10.22272193", - "rel_abs": "BackgroundThe aim of this study was to investigate the presence of mediastinal lymphadenopathy in hospitalized Covid-19 patients in a tertiary care hospital in the metropolitan city of Lahore, Pakistan from September 2020 till July 2021.\n\nMethodsWe retrospectively collected data of Covid-19 patients hospitalized from September 2020 till July 2021. Only those patients who tested PCR positive through a nasopharyngeal swab, were enrolled in the study. Patients whose data were missing were excluded from this study. Our exclusion criteria included patients who tested negative on Covid-19 PCR, patients with comorbidities that may cause enlarged mediastinal lymphadenopathies such as haemophagocytic lymphohistiocytosis, neoplasia, tuberculosis, sarcoidosis or a systemic disease. The extent of lung involvement in Covid-19 patients was quantified by using a 25-point visual quantitative assessment called the Chest Computed Tomography Score. This score was then correlated with the presence of mediastinal lymphadenopathy.\n\nFindingsOf the 210 hospitalized patients included in the study, 131 (62.4%) had mediastinal lymphadenopathy. The mean and median Severity Score of Covid-19 patients with mediastinal lymphadenopathy (mean: 17.1, SD:5.7; median: 17, IQR: 13-23) were higher as compared to those without mediastinal lymphadenopathy (mean: 12.3, SD:5.4; median: 12, IQR:9-16)\n\nInterpretationOur study documents a high prevalence of mediastinal lymphadenopathy in hospitalized patients with Covid-19 with the severity score being higher in its presence representing a more severe course of disease.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.11.483867", + "rel_abs": "The long-lasting COVID-19 pandemic and increasing SARS-CoV-2 variants demand effective drugs for prophylactics and treatment. Protein-based biologics offer high specificity yet their noncovalent interactions often lead to drug dissociation and incomplete inhibition. Here we developed covalent nanobodies capable of binding with SARS-CoV-2 spike protein irreversibly via proximity-enabled reactive therapeutic (PERx) mechanism. A novel latent bioreactive amino acid FFY was designed and genetically encoded into nanobodies to accelerate PERx reaction rate. After covalent engineering, nanobodies binding with the Spike in the down state, but not in the up state, were discovered to possess striking enhancement in inhibiting viral infection. In comparison with the noncovalent wildtype nanobody, the FFY-incorporated covalent nanobody neutralized both authentic SARS-CoV-2 and its Alpha and Delta variants with potency drastically increased over tens of folds. This PERx-enabled covalent nanobody strategy and uncovered insights on potency increase can be valuable to developing effective therapeutics for various viral infections.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Amyn Abdul Malik", - "author_inst": "Yale University School of Medicine" + "author_name": "Bingchen Yu", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Shanshan Li", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Takako Tabata", + "author_inst": "Gladstone Institutes" + }, + { + "author_name": "Nanxi Wang", + "author_inst": "University of California San Francisco" }, { - "author_name": "Faryal S. Bhatti", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" + "author_name": "G. Renuka Kumar", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Adeel A. Malik", - "author_inst": "Doctors Hospital & Medical Centre" + "author_name": "Jun Liu", + "author_inst": "University of California San Francisco" + }, + { + "author_name": "Melanie M. Ott", + "author_inst": "Gladstone Institutes" + }, + { + "author_name": "Lei Wang", + "author_inst": "University of California San Francisco" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "synthetic biology" }, { "rel_doi": "10.1101/2022.03.13.484123", @@ -376132,95 +376735,43 @@ "category": "dentistry and oral medicine" }, { - "rel_doi": "10.1101/2022.03.11.22271912", - "rel_title": "External validation of risk scores to predict in-hospital mortality in patients hospitalized due to coronavirus disease 2019.", + "rel_doi": "10.1101/2022.03.11.22272264", + "rel_title": "Daily Rapid Antigen Testing in a University Setting to Inform COVID-19 Isolation Duration Policy", "rel_date": "2022-03-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.11.22271912", - "rel_abs": "BackgroundThe coronavirus disease 2019 (COVID-19) presents an urgent threat to global health. Prediction models that accurately estimate mortality risk in hospitalized patients could assist medical staff in treatment and allocating limited resources.\n\nAimsTo externally validate two promising previously published risk scores that predict in-hospital mortality among hospitalized COVID-19 patients.\n\nMethodsTwo cohorts were available; a cohort of 1028 patients admitted to one of nine hospitals in Lombardy, Italy (the Lombardy cohort) and a cohort of 432 patients admitted to a hospital in Leiden, the Netherlands (the Leiden cohort). The primary endpoint was in-hospital mortality. All patients were adult and tested COVID-19 PCR-positive. Model discrimination and calibration were assessed.\n\nResultsThe C-statistic of the 4C mortality score was good in the Lombardy cohort (0.85, 95CI: 0.82-0.89) and in the Leiden cohort (0.87, 95CI: 0.80-0.94). Model calibration was acceptable in the Lombardy cohort but poor in the Leiden cohort due to the model systematically overpredicting the mortality risk for all patients. The C-statistic of the CURB-65 score was good in the Lombardy cohort (0.80, 95CI: 0.75-0.85) and in the Leiden cohort (0.82, 95CI: 0.76-0.88). The mortality rate in the CURB-65 development cohort was much lower than the mortality rate in the Lombardy cohort. A similar but less pronounced trend was found for patients in the Leiden cohort.\n\nConclusionAlthough performances did not differ greatly, the 4C mortality score showed the best performance. However, because of quickly changing circumstances, model recalibration may be necessary before using the 4C mortality score.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.11.22272264", + "rel_abs": "ImportanceThe suitability of the currently recommended 5-day COVID-19 isolation period remains unclear in an Omicron-dominant landscape. Early data suggest high positivity via rapid antigen test beyond day 5, but evidence gaps remain regarding optimal isolation duration and the best use of limited RATs to exit isolation.\n\nObjectiveTo determine the percentage of SARS-CoV-2 infected persons who remain positive via RAT on isolation day 5+ and assess possible factors associated with isolation duration.\n\nDesignWe evaluated daily rapid antigen test case series data from 324 persons in a managed isolation program who initially tested positive between January 1 and February 11, 2022, an Omicron-dominant period. Arrival tests and twice-weekly screening were mandated. Positive persons isolated and began mandatory daily self-testing on day 5 until testing negative. Trained staff proctored exit testing.\n\nSettingA mid-sized university in the United States.\n\nParticipantsUniversity students in isolation.\n\nMain Outcomes and MeasuresThe percentage of persons remaining positive on isolation day 5 and each subsequent day. The association between possible prognostic factors and isolation duration as measured by event-time-ratios (ETR).\n\nResultsWe found 47% twice-weekly screeners and 26-28% less frequent screeners remained positive on day 5, with the percentage approximately halving each additional day. Having a negative test [≥] 10 days before diagnosis (ETR 0.85 (95% CI 0.75-0.96)) and prior infection > 90 days (ETR 0.50 (95% CI 0.33-0.76)) were significantly associated with shorter isolation. Symptoms before or at diagnosis (ETR 1.13 (95% CI 1.02-1.25)) and receipt of 3 vaccine doses (ETR 1.20 (95% CI 1.04-1.39)) were significantly associated with prolonged isolation. However, these factors were associated with duration of isolation, not infection, and could reflect how early infections were detected.\n\nConclusions and RelevanceA high percentage of university students during an Omicron-dominant period remained positive after the currently recommended 5-day isolation, highlighting possible onward transmission risk. Persons diagnosed early in their infections or using symptom onset as their isolation start may particularly require longer isolations. Significant factors associated with isolation duration should be further explored to determine relationships with infection duration.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat percentage of SARS-CoV-2 infected persons remain positive via rapid antigen test on days 5+ of isolation?\n\nFindingsIn this case series of 324 university students, 47% of twice-weekly screeners and 26-28% of less frequent screeners remained positive via rapid antigen on isolation day 5, with the percent still positive approximately halving with each subsequent day.\n\nMeaningWhile isolation duration decisions are complex, our study adds to growing evidence that a 5-day isolation may be 1-2 days too short to sufficiently reduce the onward transmission risk, particularly for those in dense settings or among vulnerable populations.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Shermarke Hassan", - "author_inst": "University of Milan, Department of Pathophysiology and Transplantation. Leiden University Medical Center, Department of Clinical Epidemiology." - }, - { - "author_name": "Chava L. Ramspek", - "author_inst": "Leiden University Medical Center, Department of Clinical Epidemiology." - }, - { - "author_name": "Barbara Ferrari", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, U.O.C. Medicina Generale Emostasi e Trombosi." - }, - { - "author_name": "Merel van Diepen", - "author_inst": "Leiden University Medical Center, Department of Clinical Epidemiology." - }, - { - "author_name": "Raffaella Rossio", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, U.O.C. Medicina Generale Emostasi e Trombosi." - }, - { - "author_name": "Rachel Knevel", - "author_inst": "Leiden University Medical Center, Department of Rheumatology." - }, - { - "author_name": "Vincenzo la Mura", - "author_inst": "University of Milan, Department of Pathophysiology and Transplantation. Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, U.O.C. Medicina Generale Emos" - }, - { - "author_name": "Andrea Artoni", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Angelo Bianchi Bonomi Hemophilia and Thrombosis Centre." - }, - { - "author_name": "Ida Martinelli", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Angelo Bianchi Bonomi Hemophilia and Thrombosis Centre." - }, - { - "author_name": "Alessandra Bandera", - "author_inst": "University of Milan, Department of Pathophysiology and Transplantation. Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Infectious Disease Unit." - }, - { - "author_name": "Alessandro Nobili", - "author_inst": "Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Department of Health Policy." - }, - { - "author_name": "Andrea Gori", - "author_inst": "University of Milan, Department of Pathophysiology and Transplantation. Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Infectious Disease Unit." - }, - { - "author_name": "Francesco Blasi", - "author_inst": "University of Milan, Department of Pathophysiology and Transplantation. Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Respiratory Unit and Cystic F" - }, - { - "author_name": "Ciro Canetta", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Department of Medicine, High Care Internal Medicine Unit." + "author_name": "Rebecca Earnest", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Nicola Montano", - "author_inst": "Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Medicina Generale Immunologia e Allergologia." + "author_name": "Christine Chen", + "author_inst": "Yale Health Center" }, { - "author_name": "Frits R. Rosendaal", - "author_inst": "Leiden University Medical Center, Department of Clinical Epidemiology." + "author_name": "Chrispin Chaguza", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Flora Peyvandi", - "author_inst": "University of Milan, Department of Pathophysiology and Transplantation. Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, U.O.C. Medicina Generale Emos" + "author_name": "Nathan D Grubaugh", + "author_inst": "Yale School of Public Health" }, { - "author_name": "- LUMC COVID-19 Research Group", - "author_inst": "" + "author_name": "Madeline S Wilson", + "author_inst": "Yale Health Center" }, { - "author_name": "- COVID-19 Network working group", + "author_name": "- Yale COVID-19 Resulting and Isolation Team", "author_inst": "" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.03.11.22271527", @@ -378154,335 +378705,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.03.10.22272081", - "rel_title": "Interstitial lung damage following COVID-19 hospitalisation: an interim analysis of the UKILD Post-COVID study.", + "rel_doi": "10.1101/2022.03.09.22272170", + "rel_title": "SARS-CoV-2 Omicron disease burden in Australia following border reopening: a modelling analysis", "rel_date": "2022-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.10.22272081", - "rel_abs": "IntroductionShared characteristics between COVID-19 and pulmonary fibrosis, including symptoms, genetic architecture, and circulating biomarkers, suggests interstitial lung disease (ILD) development may be associated with SARS-CoV-2 infection.\n\nMethodsThe UKILD Post-COVID study planned interim analysis was designed to stratify risk groups and estimate the prevalence of Post-COVID Interstitial Lung Damage (ILDam) using the Post-HOSPitalisation COVID-19 (PHOSP-COVID) Study. Demographics, radiological patterns and missing data were assessed descriptively. Bayes binomial regression was used to estimate the risk ratio of persistent lung damage >10% involvement in linked, clinically indicated CT scans. Indexing thresholds of percent predicted DLco, chest X-ray findings and severity of admission were used to generate risk strata. Number of cases within strata were used to estimate the amount of suspected Post-COVID ILDam.\n\nResultsA total 3702 people were included in the UKILD interim cohort, 2406 completed an early follow-up research visit within 240 days of discharge and 1296 had follow-up through routine clinical review. We linked the cohort to 87 clinically indicated CTs with visually scored radiological patterns (median 119 days from discharge; interquartile range 83 to 155, max 240), of which 74 people had ILDam. ILDam was associated with abnormal chest X-ray (RR 1.21 95%CrI 1.05; 1.40), percent predicted DLco<80% (RR 1.25 95%CrI 1.00; 1.56) and severe admission (RR 1.27 95%CrI 1.07; 1.55). A risk index based on these features suggested 6.9% of the interim cohort had moderate to very-high risk of Post-COVID ILDam. Comparable radiological patterns were observed in repeat scans >90 days in a subset of participants.\n\nConclusionThese interim data highlight that ILDam was not uncommon in clinically indicated thoracic CT up to 8 months following SARS-CoV-2 hospitalisation. Whether the ILDam will progress to ILD is currently unknown, however health services should radiologically and physiologically monitor individuals who have Post-COVID ILDam risk factors.", - "rel_num_authors": 79, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.09.22272170", + "rel_abs": "BackgroundCountries with high COVID-19 vaccination rates have seen the SARS-CoV-2 Omicron variant result in rapidly increasing case numbers. This study evaluated the impact on the health system which may occur following introduction of the Omicron variant into Western Australia following state border reopening. We aimed to understand the effect of high vaccine coverage levels on the population health burden in the context of lower vaccine effectiveness against the Omicron variant, the impact of a third dose booster regime, and ongoing waning of vaccine-induced immunity. Originally scheduled for 5th February 2022, the Western Australian border was opened on 3rd March 2022, we also aimed to determine the impact of delaying border reopening on the COVID-19 health burden and whether the West Australian health system would be able to manage the resulting peak demand.\n\nMethodsAn agent-based model was used to evaluate changes in the COVID-19 health burden resulting from different border openings, at monthly intervals. We assumed immunity was derived from vaccination with the BNT162b2 Pfizer BioNTech vaccine and waned at observed rates from the UK. The model was calibrated against outbreaks in two other Australian states, Queensland and South Australia, both of which were in a similar situation to Western Australia with negligible COVID-19 transmission prior to Omicrons introduction. Age-specific infections generated by the model, together with recent UK data, permitted resulting outbreak health burden to be quantified, in particular peak ICU demand.\n\nResultsOverall population immunity in Western Australia is shown to peak and then plateau for a period of 5 months, between February and June 2022, resulting in a similar health burden if the border is reopened prior to June 2022. For an opening date of 5th March 2022, hospitalisations are predicated to peak at 510 beds, 51 of which will be in ICU, with a total of 383 deaths. If the border reopened on 5th June 2022, hospitalisations are expected to peak with 750 beds required, 75 of which would be in ICU, and a total of 478 deaths. With a total surge capacity of 52 fully staffed ICU beds, West Australian hospitals are predicted to have adequate ICU capacity for future COVID-19 demands if border reopening occurs prior to May 2022.\n\nConclusionsOur results show that with extremely high SARS-CoV-2 vaccination rates in Western Australian, and documented vaccine-induced vaccine waning rates, the overall population immunity in Western Australia will be at its highest in the period of February 2022 to June 2022. Opening the Western Australian border prior to the end this period will result in the lowest health burden in comparison to opening in June 2022 or later. With a border reopening of 3rd March 2022 announced by the Western Australian government, our data for a 5th March 2022 opening date may be used to predict the progression of this resulting outbreak. These data show expected peak demand of 510 hospital beds, 51 of which will be in ICU, with a total of 383 deaths. With a surge capacity of 52 ICU beds, it is expected that the Western Australian hospital system will be able to handle the additional load during the peak of the wave.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "I Stewart", - "author_inst": "National Heart & Lung Institute, Imperial College London" - }, - { - "author_name": "J Jacob", - "author_inst": "Respiratory Medicine, University College London" - }, - { - "author_name": "PM George", - "author_inst": "Royal Brompton and Harefield NHS Foundation Trust" - }, - { - "author_name": "PL Molyneaux", - "author_inst": "National Heart & Lung Institute, Imperial College London" - }, - { - "author_name": "JC Porter", - "author_inst": "University College London" - }, - { - "author_name": "RJ Allen", - "author_inst": "University of Leicester" - }, - { - "author_name": "JK Baillie", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "SL Barratt", - "author_inst": "North Bristol NHS Trust" - }, - { - "author_name": "P Beirne", - "author_inst": "Leeds Teaching Hospitals & University of Leeds" - }, - { - "author_name": "SM Bianchi", - "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust" - }, - { - "author_name": "JF Blaikley", - "author_inst": "University of Manchester" - }, - { - "author_name": "J Chalmers", - "author_inst": "University of Dundee" - }, - { - "author_name": "RC Chambers", - "author_inst": "Respiratory Medicine, University College London" - }, - { - "author_name": "N Chadhuri", - "author_inst": "University of Manchester" - }, - { - "author_name": "C Coleman", - "author_inst": "University of Nottingham" - }, - { - "author_name": "G Collier", - "author_inst": "University of Sheffield" - }, - { - "author_name": "EK Denneny", - "author_inst": "University College London" - }, - { - "author_name": "A Docherty", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "O Elneima", - "author_inst": "University Hospitals of Leicester NHS Trust" - }, - { - "author_name": "RA Evans", - "author_inst": "University Hospitals of Leicester NHS Trust" - }, - { - "author_name": "L Fabbri", - "author_inst": "National Heart & Lung Institute, Imperial College London" - }, - { - "author_name": "MA Gibbons", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" - }, - { - "author_name": "FV Gleeson", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "B Gooptu", - "author_inst": "University of Leicester" - }, - { - "author_name": "NJ Greening", - "author_inst": "University of Leicester" - }, - { - "author_name": "B Guillen Guio", - "author_inst": "University of Leicester" - }, - { - "author_name": "IP Hall", - "author_inst": "University of Nottingham" - }, - { - "author_name": "NA Hanley", - "author_inst": "University of Manchester" - }, - { - "author_name": "V Harris", - "author_inst": "University Hospitals of Leicester NHS Trust" - }, - { - "author_name": "E Harrison", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "M Heightman", - "author_inst": "University College London Hospital" - }, - { - "author_name": "TE Hillman", - "author_inst": "University College London Hospital" - }, - { - "author_name": "A Horsley", - "author_inst": "University of Manchester" - }, - { - "author_name": "L Houchen-Wolloff", - "author_inst": "University Hospitals of Leicester NHS Trust" - }, - { - "author_name": "I Jarrold", - "author_inst": "Asthma UK British Lung Foundation" - }, - { - "author_name": "SR Johnson", - "author_inst": "University of Nottingham" - }, - { - "author_name": "MG Jones", - "author_inst": "Faculty of Medicine, University of Southampton" - }, - { - "author_name": "F Khan", - "author_inst": "University of Nottingham" - }, - { - "author_name": "R Lawson", - "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust" - }, - { - "author_name": "OC Leavy", - "author_inst": "University of Leicester" - }, - { - "author_name": "N Lone", - "author_inst": "Usher Institute, University of Edinburgh" - }, - { - "author_name": "M Marks", - "author_inst": "University College London Hospital" - }, - { - "author_name": "H McAuley", - "author_inst": "University of Leicester" - }, - { - "author_name": "P Mehta", - "author_inst": "University College London Hospital" - }, - { - "author_name": "E Omer", - "author_inst": "University of Leicester" - }, - { - "author_name": "D Parekh", - "author_inst": "University of Birmingham" - }, - { - "author_name": "K Piper Hanley", - "author_inst": "University of Manchester" - }, - { - "author_name": "M Plate", - "author_inst": "University College London Hospital" - }, - { - "author_name": "J Pearl", - "author_inst": "University of Leicester" - }, - { - "author_name": "K Poinasamy", - "author_inst": "British Lung Foundation" - }, - { - "author_name": "JK Quint", - "author_inst": "National Heart & Lung Institute, Imperial College London" - }, - { - "author_name": "B Raman", - "author_inst": "University of Oxford" - }, - { - "author_name": "M Richardson", - "author_inst": "University of Leicester" - }, - { - "author_name": "P Rivera-Ortega", - "author_inst": "University of Manchester" - }, - { - "author_name": "L Saunders", - "author_inst": "University of Sheffield" - }, - { - "author_name": "R Saunders", - "author_inst": "University of Leicester" - }, - { - "author_name": "MG Semple", - "author_inst": "Liverpool University" - }, - { - "author_name": "M Sereno", - "author_inst": "University of Leicester" - }, - { - "author_name": "A Shikotra", - "author_inst": "University Hospitals of Leicester NHS Trust" - }, - { - "author_name": "AJ Simpson", - "author_inst": "Newcastle University" - }, - { - "author_name": "A Singapuri", - "author_inst": "University of Leicester" - }, - { - "author_name": "DJF Smith", - "author_inst": "Royal Brompton and Harefield NHS Foundation Trust" - }, - { - "author_name": "M Spears", - "author_inst": "Perth Royal Infirmary, NHS Tayside" - }, - { - "author_name": "LG Spencer", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust" - }, - { - "author_name": "S Stanel", - "author_inst": "University of Manchester" - }, - { - "author_name": "D Thickett", - "author_inst": "University of Birmingham" - }, - { - "author_name": "AAR Thompson", - "author_inst": "University of Sheffield" - }, - { - "author_name": "M Thorpe", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "R Thwaites", - "author_inst": "National Heart & Lung Institute, Imperial College London" - }, - { - "author_name": "SLF Walsh", - "author_inst": "National Heart & Lung Institute, Imperial College London" - }, - { - "author_name": "S Walker", - "author_inst": "Sheffield Teaching NHS Foundation Trust" - }, - { - "author_name": "ND Weatherley", - "author_inst": "Sheffield Teaching NHS Foundation Trust" - }, - { - "author_name": "M Weeks", - "author_inst": "National Heart & Lung Institute, Imperial College London" - }, - { - "author_name": "JM Wild", - "author_inst": "Sheffield Teaching NHS Foundation Trust" - }, - { - "author_name": "DG Wootton", - "author_inst": "University of Liverpool" - }, - { - "author_name": "CE Brightling", - "author_inst": "University Hospitals of Leicester NHS Trust" - }, - { - "author_name": "LP Ho", - "author_inst": "University of Oxford" - }, - { - "author_name": "LV Wain", - "author_inst": "University of Leicester" + "author_name": "George J Milne", + "author_inst": "University of Western Australia" }, { - "author_name": "RG Jenkins", - "author_inst": "National Heart & Lung Institute, Imperial College London" + "author_name": "Julian Carrivick", + "author_inst": "University of Western Australia" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.03.09.22272098", @@ -380528,199 +380771,47 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2022.03.09.22271788", - "rel_title": "Comparison of influenza and COVID-19-associated hospitalizations among children < 18 years old in the United States - FluSurv-NET (October-April 2017-2021) and COVID-NET (October 2020-September 2021)", + "rel_doi": "10.1101/2022.03.08.22272041", + "rel_title": "Impacts of COVID-19 on glycemia and risk of diabetic ketoacidosis", "rel_date": "2022-03-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.09.22271788", - "rel_abs": "BackgroundInfluenza virus and SARS-CoV-2 are significant causes of respiratory illness in children.\n\nMethodsInfluenza and COVID-19-associated hospitalizations among children <18 years old were analyzed from FluSurv-NET and COVID-NET, two population-based surveillance systems with similar catchment areas and methodology. The annual COVID-19-associated hospitalization rate per 100 000 during the ongoing COVID-19 pandemic (October 1, 2020-September 30, 2021) was compared to influenza-associated hospitalization rates during the 2017-18 through 2019-20 influenza seasons. In-hospital outcomes, including intensive care unit (ICU) admission and death, were compared.\n\nResultsAmong children <18 years old, the COVID-19-associated hospitalization rate (48.2) was higher than influenza-associated hospitalization rates: 2017-18 (33.5), 2018-19 (33.8), and 2019-20 (41.7). The COVID-19-associated hospitalization rate was higher among adolescents 12-17 years old (COVID-19: 59.9; influenza range: 12.2-14.1), but similar or lower among children 5-11 (COVID-19: 25.0; influenza range: 24.3-31.7) and 0-4 (COVID-19: 66.8; influenza range: 70.9-91.5) years old. Among children <18 years old, a higher proportion with COVID-19 required ICU admission compared with influenza (26.4% vs 21.6%; p<0.01). Pediatric deaths were uncommon during both COVID-19- and influenza-associated hospitalizations (0.7% vs 0.5%; p=0.28).\n\nConclusionsIn the setting of extensive mitigation measures during the COVID-19 pandemic, the annual COVID-19-associated hospitalization rate during 2020-2021 was higher among adolescents and similar or lower among children <12 years old compared with influenza during the three seasons before the COVID-19 pandemic. COVID-19 adds substantially to the existing burden of pediatric hospitalizations and severe outcomes caused by influenza and other respiratory viruses.\n\nSummaryAnnual hospitalization rates and proportions of hospitalized children experiencing severe outcomes were as high or higher for COVID-19 during October 2020-September 2021 compared with influenza during the three seasons before the COVID-19 pandemic, based on U.S. population-based surveillance data.", - "rel_num_authors": 45, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.08.22272041", + "rel_abs": "BackgroundReports indicate that COVID-19 may impact pancreatic function and increase type 2 diabetes (T2D) risk, although real-world COVID-19 impacts on HbA1c and T2D are unknown. We tested whether COVID-19 increased HbA1c, risk of T2D, or diabetic ketoacidosis (DKA).\n\nMethodsWe compared pre- and post-COVID-19 HbA1c, and risk of developing T2D in a large real-world clinical cohort of 8,755 COVID-19(+) patients and a matched control cohort of 11,998 COVID-19(-) patients. We investigated if DKA risk was modified in COVID-19(+) patients with type 1 diabetes (T1D) (N=704) or T2D (N=22,904), or by race and sex.\n\nFindingsWe observed a statistically significant, albeit clinically insignificant, HbA1c increase post-COVID-19 (all patients {Delta}HbA1c=0.06%, P<.001; with T2D {Delta}HbA1c=0.1%; P<.001), and no increase among COVID-19(-) patients (P>.05). COVID-19(+) patients were 40% more likely to be diagnosed with T2D compared to COVID-19(-) patients (P<.001) and 28% more likely to be diagnosed with T2D for the same HbA1c change as COVID-19(-) patients (P<.001). COVID-19(+) patients with T2D on insulin were 34% more likely to develop DKA compared to COVID-19(-) patients on insulin (P<.05), and COVID-19(+) Black patients with T2D displayed disproportionately increased DKA risk (HR:1.63, P=.007). There was no significant difference in DKA risk between COVID-19(+) and COVID-19(-) patients with T1D.\n\nInterpretationDKA risk is increased in T2D patients on insulin and in Black patients with T2D after COVID-19 infection.T2D risk is greater in COVID-19(+) patients for the same HbA1c increase in COVID-19(-) patients, indicating that T2D risk attributed to COVID-19 may be due to increased recognition during COVID-19 management.\n\nFundingNo funding to report.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Miranda Delahoy", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Dawud Ujamaa", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Christopher A. Taylor", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Charisse Cummings", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Onika Anglin", - "author_inst": "CDC" - }, - { - "author_name": "Rachel A Holstein", - "author_inst": "Centers for Disease Control and Prevention (CDC)" - }, - { - "author_name": "Jennifer Milucky", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Alissa O'Halloran", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Kadam Patel", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Huong Pham", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Michael Whitaker", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Arthur Reingold", - "author_inst": "University of California Berkeley" - }, - { - "author_name": "Shua J. Chai", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Nisha B. Alden", - "author_inst": "Colorado Department of Public Health and Environment" - }, - { - "author_name": "Breanna Kawasaki", - "author_inst": "Colorado Department of Public Health and Environment" - }, - { - "author_name": "James Meek", - "author_inst": "Connecticut Emerging Infections Program, Yale School of Public Health" - }, - { - "author_name": "Kimberly Yousey-Hindes", - "author_inst": "Connecticut Emerging Infections Program, Yale School of Public Health" - }, - { - "author_name": "Evan J. Anderson", - "author_inst": "Emory University School of Medicine Emerging Infections Program, Georgia Department of Health Veterans Affairs Medical Center" - }, - { - "author_name": "Kyle P. Openo", - "author_inst": "Georgia EIP" - }, - { - "author_name": "Andy Weigel", - "author_inst": "Iowa Department of Public Health" - }, - { - "author_name": "Kenzie Teno", - "author_inst": "Iowa Department of Public Health" - }, - { - "author_name": "Libby Reeg", - "author_inst": "Michigan Department of Health and Human Services" - }, - { - "author_name": "Lauren Leegwater", - "author_inst": "Michigan Department of Health and Human Services" - }, - { - "author_name": "Ruth Lynfield", - "author_inst": "Minnesota Department of Health" - }, - { - "author_name": "Melissa McMahon", - "author_inst": "Minnesota Department of Health" - }, - { - "author_name": "Susan Ropp", - "author_inst": "New Mexico Department of Health" - }, - { - "author_name": "Dominic Rudin", - "author_inst": "University of New Mexico Health Sciences Center" - }, - { - "author_name": "Alison Muse", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "Nancy Spina", - "author_inst": "New York State Department of Health" - }, - { - "author_name": "Nancy M. Bennett", - "author_inst": "University of Rochester School of Medicine and Dentistry" - }, - { - "author_name": "Kevin Popham", - "author_inst": "University of Rochester School of Medicine and Dentistry" - }, - { - "author_name": "Laurie M. Billing", - "author_inst": "Ohio Department of Health" - }, - { - "author_name": "Eli Shiltz", - "author_inst": "Ohio Department of Health" - }, - { - "author_name": "Melissa Sutton", - "author_inst": "Oregon Health Authority" - }, - { - "author_name": "Ann Thomas", - "author_inst": "Public Health Division, Oregon Health Authority" - }, - { - "author_name": "William Schaffner", - "author_inst": "Vanderbilt University of Medicine" - }, - { - "author_name": "H. Keipp Talbot", - "author_inst": "Vanderbilt University of Medicine" - }, - { - "author_name": "Melanie T. Crossland", - "author_inst": "Salt Lake County Health Department" - }, - { - "author_name": "Keegan McCaffrey", - "author_inst": "Utah Department of Health" + "author_name": "Anukriti Sharma", + "author_inst": "Cleveland Clinic Lerner Research Institute" }, { - "author_name": "Aron J. Hall", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Anita D. Misra-Herbert", + "author_inst": "Cleveland Clinic Lerner Research Institute" }, { - "author_name": "Erin Burns", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Arshiya Mariam", + "author_inst": "Cleveland Clinic Lerner Research Institute" }, { - "author_name": "Meredith McMorrow", - "author_inst": "U.S. Public Health Services" + "author_name": "Alex Milinovich", + "author_inst": "Cleveland Clinic Lerner Research Institute" }, { - "author_name": "Carrie Reed", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Michael W. Kattan", + "author_inst": "Cleveland Clinic Lerner Research Institute" }, { - "author_name": "Fiona P. Havers", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Kevin M. Pantalone", + "author_inst": "Endocrinology and Metabolism Institute" }, { - "author_name": "Shikha Garg", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Daniel M. Rotroff", + "author_inst": "Cleveland Clinic Lerner Research Institute" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "endocrinology" }, { "rel_doi": "10.1101/2022.03.09.22271973", @@ -382458,103 +382549,75 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2022.03.06.22271809", - "rel_title": "Defining factors that influence vaccine-induced, cross-variant neutralizing antibodies for SARS-CoV-2 in Asians", + "rel_doi": "10.1101/2022.03.08.483381", + "rel_title": "Hetero-bivalent Nanobodies Provide Broad-spectrum Protection against SARS-CoV-2 Variants of Concern including Omicron", "rel_date": "2022-03-08", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.06.22271809", - "rel_abs": "The scale and duration of neutralizing antibody responses targeting SARS-CoV-2 viral variants represents a critically important serological parameter that predicts protective immunity for COVID-19. In this study, we present longitudinal data illustrating the impact of age, sex and comorbidities on the kinetics and strength of vaccine-induced neutralizing antibody responses for key variants in an Asian volunteer cohort. We demonstrate a reduction in neutralizing antibody titres across all groups six months post-vaccination and show a marked reduction in the serological binding and neutralizing response targeting Omicron compared to other viral variants. We also highlight the increase in cross-protective neutralizing antibody responses against Omicron induced by a third dose (booster) of vaccine. These data illustrate how key virological factors such as immune escape mutation combined with host factors such as age and sex of the vaccinated individuals influence the strength and duration of cross-protective serological immunity for COVID-19.", - "rel_num_authors": 21, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.03.08.483381", + "rel_abs": "Following Delta, Omicron variant triggered a new wave of SARS-CoV-2 infection globally, adaptive evolution of the virus may not stop, the development of broad-spectrum antivirals is still urgent. We previously developed two hetero-bivalent nanobodies with potent neutralization against original WT SARS-CoV-2, termed aRBD-2-5 and aRBD-2-7, by fusing aRBD-2 with aRBD-5 or aRBD-7, respectively. Here, we resolved crystal structures of these nanobodies in complex with RBD, and found the epitope of aRBD-2 differs from that of aRBD-5, aRBD-7. aRBD-2 binds to a conserved epitope which renders its binding activity to all variants of concern (VOCs) including Omicron. Interestingly, although monovalent aRBD-5 and aRBD-7 lost binding to some variants, they effectively improved the overall affinity when transformed into the hetero-bivalent form after being fused with aRBD-2. Consistent with the high binding affinities, aRBD-2-5-Fc and aRBD-2-7-Fc exhibited ultra-potent neutralization to all five VOCs; particularly, aRBD-2-5-Fc neutralized authentic virus of Beta, Delta and Omicron with the IC50of 5.98[~]9.65 ng/mL or 54.3[~]87.6 pM. Importantly, aRBD-2-5-Fc provided in vivo prophylactic protection for mice against WT and mouse-adapted SARS-CoV-2, and provided full protection against Omicron in hamster model when administrated either prophylactically or therapeutically. Taken together, we found a conserved epitope on RBD, and hetero-bivalent nanobodies had increased affinity for VOCs over its monovalent form, and provided potent and broad-spectrum protection both in vitro and in vivo against all tested major variants, and potentially future emerging variants. Our strategy provides a new solution in the development of therapeutic antibodies for COVID-19 caused by newly emergent VOCs.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Yue Gu", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Bhuvaneshwari D/O Shunmuganathan", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Xinlei Qian", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Rashi Gupta", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Rebecca S.W. Tan", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Mary Kozma", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Kiren Purushotorman", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Tanusya M. Murali", - "author_inst": "National University of Singapore" + "author_name": "Tengchuan Jin", + "author_inst": "University of Science and Technology of China" }, { - "author_name": "Nikki Y.J. Tan", - "author_inst": "National University of Singapore" + "author_name": "Huan Ma", + "author_inst": "University of Science and Technology of China" }, { - "author_name": "Peter R. Preiser", - "author_inst": "Nanyang Technological University" + "author_name": "Xinghai Zhang", + "author_inst": "Chinese Academy of Sciences" }, { - "author_name": "Julien Lescar", - "author_inst": "Nanyang Technological University" + "author_name": "Peiyi Zheng", + "author_inst": "University of Science and Technology of China" }, { - "author_name": "Haziq Nasir", - "author_inst": "National University Hospital" + "author_name": "Peter H. Dube", + "author_inst": "University of Texas Health Science Center at San Antonio" }, { - "author_name": "Jyoti Somani", - "author_inst": "National University Hospital" + "author_name": "Weihong Zeng", + "author_inst": "University of Science and Technology of China" }, { - "author_name": "Paul A. Tambyah", - "author_inst": "National University Hospital" + "author_name": "Shaohong Chen", + "author_inst": "Chinese Academy of Sciences" }, { - "author_name": "- SCOPE Cohort Study Group", - "author_inst": "-" + "author_name": "Yunru Yang", + "author_inst": "University of Science and Technology of China" }, { - "author_name": "Kenneth G.C. Smith", - "author_inst": "University of Cambridge" + "author_name": "Yan Wu", + "author_inst": "Chinese Academy of Sciences" }, { - "author_name": "Laurent Renia", - "author_inst": "Agency for Science, Technology and Research (A*STAR), Singapore" + "author_name": "Junhui Zhou", + "author_inst": "Chinese Academy of Sciences" }, { - "author_name": "Lisa F.P. Ng", - "author_inst": "Agency for Science, Technology and Research (A*STAR), Singapore" + "author_name": "Xiaowen Hu", + "author_inst": "University of Science and Technology of China" }, { - "author_name": "David C. Lye", - "author_inst": "National Centre of Infectious Diseases" + "author_name": "Yan Xiang", + "author_inst": "University of Texas Health Science Center at San Antonio" }, { - "author_name": "Barnaby E. Young", - "author_inst": "National Centre for Infectious Diseases" + "author_name": "Huajun Zhang", + "author_inst": "Chinese Academy of Sciences" }, { - "author_name": "Paul A. MacAry", - "author_inst": "National University of Singapore" + "author_name": "Sandra Chiu", + "author_inst": "University of Science and Technology of China" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2022.03.07.483373", @@ -384292,51 +384355,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.03.04.22271706", - "rel_title": "Remdesivir for the treatment of patients hospitalized with COVID-19 receiving supplemental oxygen: a targeted literature review and meta-analysis", + "rel_doi": "10.1101/2022.03.07.22271833", + "rel_title": "GWAS and meta-analysis identifies multiple new genetic mechanisms underlying severe Covid-19.", "rel_date": "2022-03-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.04.22271706", - "rel_abs": "This network meta-analysis (NMA) assessed the efficacy of remdesivir in hospitalized patients with COVID-19 requiring supplemental oxygen. Randomized controlled trials of hospitalized patients with COVID-19, where patients were receiving supplemental oxygen at baseline and at least one arm received treatment with remdesivir, were identified. Outcomes included mortality, recovery, and no longer requiring supplemental oxygen. NMAs were performed for low-flow oxygen (LFO2); high-flow oxygen (HFO2), including NIV; or oxygen at any flow (AnyO2) at early (day 14/15) and late (day 28/29) time points. Six studies were included (N=5,245 patients) in the NMA. Remdesivir lowered early and late mortality among AnyO2 patients (risk ratio (RR) 0.52, 95% credible interval (CrI) 0.34-0.79; RR 0.81, 95%CrI 0.69-0.95) and LFO2 patients (RR 0.21, 95%CI 0.09-0.46; RR 0.24, 95%CI 0.11-0.48); no improvement was observed among HFO2 patients. Improved early and late recovery was observed among LFO2 patients (RR 1.22, 95%CrI 1.09-1.38; RR 1.17, 95%CrI 1.09-1.28). Remdesivir also lowered the requirement for oxygen support among all patient subgroups. Among hospitalized patients with COVID-19 requiring supplemental oxygen at baseline, use of remdesivir compared to best supportive care is likely to improve the risk of mortality, recovery and need for oxygen support in AnyO2 and LFO2 patients.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.07.22271833", + "rel_abs": "Pulmonary inflammation drives critical illness in Covid-19, 1;2 creating a clinically homogeneous extreme phenotype, which we have previously shown to be highly efficient for discovery of genetic associations. 3;4 Despite the advanced stage of illness, we have found that immunomodulatory therapies have strong beneficial effects in this group. 1;5 Further genetic discoveries may identify additional therapeutic targets to modulate severe disease. 6 In this new data release from the GenOMICC (Genetics Of Mortality in Critical Care) study we include new microarray genotyping data from additional critically-ill cases in the UK and Brazil, together with cohorts of severe Covid-19 from the ISARIC4C 7 and SCOURGE 8 studies, and meta-analysis with previously-reported data. We find an additional 14 new genetic associations. Many are in potentially druggable targets, in inflammatory signalling (JAK1, PDE4A), monocyte-macrophage differentiation (CSF2), immunometabolism (SLC2A5, AK5), and host factors required for viral entry and replication (TMPRSS2, RAB2A). As with our previous work, these results provide tractable therapeutic targets for modulation of harmful host-mediated inflammation in Covid-19.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Rachel Beckerman", - "author_inst": "Maple Health Group" - }, - { - "author_name": "Andrea Gori", - "author_inst": "Universit\u00e0 degli Studi di Milano: Universita degli Studi di Milano" - }, - { - "author_name": "Sushanth Jeyakumar", - "author_inst": "Maple Health Group" + "author_name": "Erola Pairo-Castineira", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Jakob J. Malin", - "author_inst": "Department I of Internal Medicine, Division of Infectious Diseases, Medical Faculty and University Hospital Cologne, University of Cologne" + "author_name": "Konrad Rawlik", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Roger Paredes", - "author_inst": "Infectious Diseases Department & irsiCaixa AIDS Research Institute, Hospital Universitari Germans Trias i Pujol, Badalona, Catalonia, Spain" + "author_name": "Lucija Klaric", + "author_inst": "MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK." }, { - "author_name": "Pedro Povoa", - "author_inst": "Nova Medical School, CHRC, New University of Lisbon, Lisbon, Portugal" + "author_name": "Andy Law", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Nathaniel J. Smith", - "author_inst": "Maple Health Group" + "author_name": "Sara Clohisey Hendry", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Armando Teixeira-Pinto", - "author_inst": "School of Public Health, Faculty of Medicine and Health, University of Sydney, Sydney, Australia" + "author_name": "J. Kenneth Baillie", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2022.03.04.22271911", @@ -386002,35 +386057,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.03.01.22271611", - "rel_title": "Predicting missed health care visits during the COVID-19 pandemic using machine learning methods: Evidence from 55,500 individuals from 28 European Countries", + "rel_doi": "10.1101/2022.03.02.22271734", + "rel_title": "An observational study of the association between COVID-19 vaccination rates and participation in a vaccine lottery", "rel_date": "2022-03-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.01.22271611", - "rel_abs": "BackgroundThe COVID-19 pandemic has led many individuals to miss essential care. Machine-learning models that predict which patients are at greatest risk of missing care visits can help health administrators prioritize retentions efforts towards patients with the most need. Such approaches may be especially useful for efficiently targeting interventions for health systems overburdened by the COVID-19 pandemic.\n\nMethodsWe compare the performance of four machine learning algorithms to predict missed health care visits based on common patient characteristics available to most health care providers. We use data from 55,500 respondents of the Survey of Health, Ageing and Retirement in Europe (SHARE) COVID-19 survey (June - September 2020) in conjunction with longitudinal data from waves 1-8 (April 2004 - March 2020). We use stepwise selection, group lasso, random forest and neural network algorithms and employ 5-fold cross-validation to test the prediction accuracy, sensitivity, and specificity of the selected models.\n\nFindingsWithin our sample, 15.5% of the respondents reported any missed essential health care visit due to the COVID-19 pandemic. All four machine learning methods perform similarly in their predictive power. When classifying all individuals with a predicted probability for missed care above 17% as at risk of a missed visit, they correctly identify between 41% and 53% of the respondents at risk, while correctly identifying between 74% and 64% of the individuals not at risk. We find that the sensitivity and specificity of the models are strongly related to the risk threshold used to classify individuals; thus, the models can be calibrated depending on users resource constraints and targeting approach. All models had an area under the curve around 0.62, indicating that they outperform random prediction.\n\nInterpretationPandemics such as COVID-19 require rapid and efficient responses to reduce disruptions in health care. Based on characteristics available to health insurance providers, machine learning algorithms can be used to efficiently target efforts to reduce missed essential care.\n\nFundingResearch in this article is a part of the European Unions H2020 SHARE-COVID19 project (Grant Agreement No. 101015924).", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.02.22271734", + "rel_abs": "ObjectivesTo examine the association between financial incentives from entry into a vaccine competition with the probability of vaccination for COVID-19.\n\nDesignA cross-sectional study with adjustment for covariates using logistic regression\n\nSettingOctober and November 2021, Australia.\n\nParticipants2,375 respondents of the Taking the Pulse of the Nation Survey\n\nPrimary and secondary outcome measuresThe proportion of respondents who had any vaccination, a first dose only, or second dose after the competition opened.\n\nResultsThose who entered the competition were 2.27 (95% CI 1.73 to 2.99) times more likely to be vaccinated after the competition opened on October 1st than those who did not enter--an increase in the probability of having any dose of 0.16 (95 % CI 0.10 to 0.21) percentage points. This increase was mostly driven by those receiving second doses. Entrants were 2.39 (95% CI 1.80 to 3.17) times more likely to receive their second dose after the competition opened.\n\nConclusionsThose who entered the Million Dollar Vax competition were more likely to receive a vaccination after the competition opened compared to those who did not enter the competition, with this effect dominated by those receiving second doses.\n\nStrengths and limitations of this studyO_LIWe use a nationally representative sample of individual self-reported vaccination status and timings.\nC_LIO_LIWe distinguish between the association between competition entry and first and second doses.\nC_LIO_LIWe adjust for a rich set of individual characteristics associated with vaccination status, and examine the factors influencing competition entry\nC_LIO_LIThe strong association for second dose vaccinations may reflect some individuals who had already scheduled their second dose after the competition opened, potentially leading to an overestimate of the association.\nC_LI", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Anna Reuter", - "author_inst": "Heidelberg Institute of Global Health, Heidelberg University" - }, - { - "author_name": "\u0160ime Smoli\u0107", - "author_inst": "Department of Macroeconomics and Economic Development, University of Zagreb" - }, - { - "author_name": "Till B\u00e4rnighausen", - "author_inst": "Heidelberg Institute of Global Health, Heidelberg University" + "author_name": "Dajung Jun", + "author_inst": "University of Melbourne" }, { - "author_name": "Nikkil Sudharsanan", - "author_inst": "Technical University of Munich" + "author_name": "Anthony Scott", + "author_inst": "University of Melbourne" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health economics" }, { "rel_doi": "10.1101/2022.03.02.22271779", @@ -388108,51 +388155,91 @@ "category": "hematology" }, { - "rel_doi": "10.1101/2022.02.28.22271591", - "rel_title": "Ammonium Sulfate Addition Reduces the Need for Guanidinium Isothiocyanate in the Denaturing Transport Medium Used for SARS-COV-2 RNA Detection", + "rel_doi": "10.1101/2022.03.01.22271576", + "rel_title": "Transcriptomic clustering of critically ill COVID-19 patients", "rel_date": "2022-03-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.28.22271591", - "rel_abs": "Rapid identification of SARS-CoV-2 infected individuals through viral RNA detection followed by effective personal isolation remains the most effective way to prevent the spread of this virus. Large-scale RNA detection involves mass specimen collection and transportation. For biosafety reasons, denaturing viral transport medium has been extensively used during the pandemic. But the high concentrations of guanidinium isothiocyanate (GITC) in such media have raised issues around sufficient GITC supply and laboratory safety. Here, we tested whether supplementing media containing low concentrations of GITC with ammonium sulfate (AS) would affect the throat-swab detection of SARS-CoV-2 pseudovirus or a viral inactivation assay targeting both enveloped and non-enveloped viruses. Adding AS to the denaturing transport media reduced the need for high levels of GITC and improved SARS-COV-2 RNA detection without compromising virus inactivation.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.03.01.22271576", + "rel_abs": "Infections caused by SARS-CoV-2 may cause a severe disease, termed COVID-19, with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms, and their modulation is the only therapeutic strategy that has shown a mortality benefit. Herein, we used peripheral blood transcriptomes of critically-ill COVID-19 patients obtained at admission in an Intensive Care Unit (ICU), to identify two transcriptomic clusters characterized by expression of either interferon-related or immune checkpoint genes, respectively. These profiles have different ICU outcome, in spite of no major clinical differences at ICU admission. A transcriptomic signature was used to identify these clusters in an external validation cohort, yielding similar results. These findings reveal different underlying pathogenetic mechanisms and illustrate the potential of transcriptomics to identify patient endotypes in severe COVID-19, aimed to ultimately personalize their therapies.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Ge Liu", - "author_inst": "Shenzhen Technology University" + "author_name": "Cecilia Lopez-Martinez", + "author_inst": "Instituto de Investigacion Sanitaria del Principado de Asturias. Oviedo, Spain" }, { - "author_name": "Jiaoyan Jia", - "author_inst": "Shenzhen University" + "author_name": "Paula Martin-Vicente", + "author_inst": "Instituto de Investigacion Sanitaria del Principado de Asturias. Oviedo, Spain" }, { - "author_name": "Jianfeng Zhong", - "author_inst": "Shenzhen University" + "author_name": "Juan Gomez de Ona", + "author_inst": "Hospital Unviersitario Central de Asturias. Oviedo, Spain" }, { - "author_name": "Hanfang Jiang", - "author_inst": "Shenzhen Children's Hospital" + "author_name": "Ines Lopez-Alonso", + "author_inst": "Centro de Investigacion Biomedica en Red (CIBER)-Enfermedades Respiratorias. Madrid, Spain." }, { - "author_name": "Yongqi Yang", - "author_inst": "Shenzhen University" + "author_name": "Helena Gil-Pena", + "author_inst": "Hospital Unviersitario Central de Asturias. Oviedo, Spain" }, { - "author_name": "Xiujing Lu", - "author_inst": "GBCBIO Technologies Inc." + "author_name": "Elias Cuesta-Llavona", + "author_inst": "Hospital Unviersitario Central de Asturias. Oviedo, Spain" }, { - "author_name": "Zhendan He", - "author_inst": "Shenzhen Technology University" + "author_name": "Margarita Fernandez-Rodriguez", + "author_inst": "Instituto Universitario de Oncologia del Principado de Asturias. Oviedo, Spain." }, { - "author_name": "Qinchang Zhu", - "author_inst": "Shenzhen Technology University" + "author_name": "Irene Crespo", + "author_inst": "Universidad de Oviedo. Oviedo, Spain" + }, + { + "author_name": "Estefania Salgado del Riego", + "author_inst": "Hospital Unviersitario Central de Asturias. Oviedo, Spain" + }, + { + "author_name": "Raquel Rodriguez-Garcia", + "author_inst": "Instituto de Investigacion Sanitaria del Principado de Asturias. Oviedo, Spain" + }, + { + "author_name": "Diego Parra", + "author_inst": "Hospital Unviersitario Central de Asturias. Oviedo, Spain" + }, + { + "author_name": "Javier Fernandez", + "author_inst": "Hospital Unviersitario Central de Asturias. Oviedo, Spain" + }, + { + "author_name": "Javier Rodriguez-Carrio", + "author_inst": "Universidad de Oviedo. Oviedo, Spain" + }, + { + "author_name": "Alberto Davalos", + "author_inst": "Instituto Madrileno de Estudios Avanzados. (IMDEA) Alimentacion, CEI UAM + CSIC, Madrid, Spain." + }, + { + "author_name": "Luis A Chapado", + "author_inst": "Instituto Madrileno de Estudios Avanzados. (IMDEA) Alimentacion, CEI UAM + CSIC, Madrid, Spain." + }, + { + "author_name": "Eliecer Coto", + "author_inst": "Hospital Unviersitario Central de Asturias. Oviedo, Spain" + }, + { + "author_name": "Guillermo M Albaiceta", + "author_inst": "Instituto de Investigacion Sanitaria del Principado de Asturias. Oviedo, Spain" + }, + { + "author_name": "Laura Amado-Rodriguez", + "author_inst": "Instituto de Investigacion Sanitaria del Principado de Asturias. Oviedo, Spain" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2022.03.01.22271696", @@ -390246,29 +390333,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.02.27.22271579", - "rel_title": "Vaccine hesitancy strongly correlates with COVID-19 deaths underreporting", + "rel_doi": "10.1101/2022.02.21.22270847", + "rel_title": "COVID-19 testing: disparity between national and institution-based case detection", "rel_date": "2022-03-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.27.22271579", - "rel_abs": "Vaccine acceptance is a key factor in achieving high immunization coverage and reducing the death toll of COVID-19 pandemic. Analyzing data from Europe and Americas we demonstrated that vaccine hesitancy strongly correlates with underreporting of COVID-19 deaths and cases. This correlation cannot be explained by the differences in economic indexes: GDP and Gini coefficient (measure of income inequalities). There is no correlation of vaccination percentage and Gini coefficient and the correlation with GDP is decreasing in time. The most striking is the comparison of Eastern European and South American countries; the latter group of countries shows significantly higher vaccination percentage while having a lower or comparable GDP and higher Gini coefficient. The analysis suggests that timely and reliable information about the COVID-19 cases and the associated deaths plays a key role in achieving population-wide vaccine acceptance.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.21.22270847", + "rel_abs": "Reports of COVID-19 prevalence through national statistics, community surveys and targeted testing at places of work or study have guided national and institutional responses to the pandemic. The University of Edinburgh established a mass testing programme, TestEd, for detection of COVID-19 in asymptomatic staff and students who are studying or working on campus. The study has tested more than 100,000 samples with more than 170 confirmed positive results. Since the introduction of a change in policy in England and the UK devolved nations in early January 2022, to limit eligibility for PCR testing in the community to those with symptoms, we have noticed a divergence between the reports in Scottish and UK-wide prevalence, and the magnitude and frequency of positive results in the University datasets. While the national UK-wide and Scottish case figures show declining or stable prevalence, University case reports have risen more than five-fold since early December 2021 and continue to rise. These observations could be important in the face of future variants of concern and emphasise the need for continued access to high sensitivity PCR testing and other forms of surveillance.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Adam Sobieszek", - "author_inst": "Faculty of Psychology, University of Warsaw" + "author_name": "Timothy J Aitman", + "author_inst": "University of Edinburgh" }, { - "author_name": "Miriam Lipniacka", - "author_inst": "Inter-Faculty Individual Studies in Mathematics and Natural Sciences, The MISMaP College, University of Warsaw" + "author_name": "Linda Bauld", + "author_inst": "University of Edinburgh" }, { - "author_name": "Tomasz Lipniacki", - "author_inst": "Institute of Fundamental Technological Research, Polish Academy of Sciences" + "author_name": "Kathryn F Carruthers", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Nick Gilbert", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Neil Turok", + "author_inst": "University of Edinburgh" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -391992,47 +392087,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.25.22271529", - "rel_title": "Study on the usefulness of Direct Saliva sample Collection (DiSC) by polyester swab", + "rel_doi": "10.1101/2022.02.27.22271593", + "rel_title": "Vaccination and Variants: retrospective model for the evolution of Covid-19 in Italy", "rel_date": "2022-02-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.25.22271529", - "rel_abs": "Saliva sample can be self-collected and used in testing of SARS-CoV-2 nucleic acid amplification tests (NAATs) test in Japan. However, this may have difficulty collecting a proper specimen when collecting for the first time. We compared 2 collection methods, conventional methods and Direct Saliva Sample Collection method (DiSC) from 44 asymptomatic or symptomatic individuals who were in quarantine in Toho university hospital. RT-PCR by DiSC method showed about 70 % positive percent agreement compared to RT-PCR by conventional methods. In addition, comparing RT-PCR and TMA by DiSC method, TMA showed about 90 % positive percent agreement compared to RT-PCR. DiSC method is easy to perform by every person, does not have complicated restrictions/instructions and can be used in RT-PCR and TMA. This method allows for ease of saliva collection in certain patient populations.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.27.22271593", + "rel_abs": "The last year of Covid-19 pandemic has been characterized by the continuous chase between the vaccination campaign and the appearance of new variants that put further obstacles to the possibility of eradicating the virus and returning to normality in a short period. In the present paper we consider a deterministic compartmental model to discuss the evolution of the Covid-19 in Italy as a combined effect of vaccination campaign, new variant spreading, waning immunity and mobility restrictions. We analyze the role that different mechanisms, such as behavioral changes due to variable risk perception, variation of the population mobility, seasonal variability of the virus infectivity, and spreading of new variants have had in shaping the epidemiological curve. The fundamental impact of vaccines in drastically reducing the total increase in infections and deaths is also estimated. This work further underlines the crucial importance of vaccination and adoption of adequate individual protective measures in containing the pandemic.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Kotaro Aoki", - "author_inst": "Toho University" - }, - { - "author_name": "Mami Nagashima", - "author_inst": "Tokyo Metropolitan Institute of Public Health" - }, - { - "author_name": "Katsuhito Kashiwagi", - "author_inst": "Toho University Omori Medical Center" + "author_name": "Annalisa Fierro", + "author_inst": "CNR: Consiglio Nazionale delle Ricerche" }, { - "author_name": "Takashi Chiba", - "author_inst": "Tokyo Metropolitan Institute of Public Health" + "author_name": "Silvio Romano", + "author_inst": "University of Naples Federico II: Universita degli Studi di Napoli Federico II" }, { - "author_name": "Kenji Sadamasu", - "author_inst": "Tokyo Metropolitan Institute of Public Health" - }, - { - "author_name": "Yoshikazu Ishii", - "author_inst": "Toho University" - }, - { - "author_name": "Kazuhiro Tateda", - "author_inst": "Toho University" + "author_name": "Antonella Liccardo", + "author_inst": "University of Naples" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.02.28.22271467", @@ -393658,41 +393737,41 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.02.25.481997", - "rel_title": "Adenosine A2A Receptor (A2AR) agonists improve survival in K28-hACE2 mice following SARS CoV-2 infection", + "rel_doi": "10.1101/2022.02.24.481848", + "rel_title": "Discovery of a novel coronavirus in Swedish bank voles (Myodes glareolus)", "rel_date": "2022-02-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.25.481997", - "rel_abs": "Effective and available therapies for the treatment of COVID-19 disease are limited. Apadenoson is a highly potent selective anti-inflammatory adenosine A2A receptor (A2AR) agonist and potential treatment option for COVID-19 patients. Apadenoson, when administered after infection with SARS CoV-2, was found to decrease weight loss, improve clinical symptoms, reduce levels of a several proinflammatory cytokines and chemokines in bronchial lavage (BAL) fluid, and promote increased survival in K18hACE2 transgenic mice. Of note, administering apadenoson after, but not prior to Covid-19 infection, caused a rapid decrease in lung viral burden. The work presented provides the foundation for further examination of these drugs as a therapy option for COVID-19.\n\nSummaryApadenoson therapy improves COVID-19 outcome", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.24.481848", + "rel_abs": "We identified a novel Betacoronavirus from bank voles (Myodes glareolus) in Grimso, Sweden. Repeated detection over three years and an overall prevalence of 3.4% suggests the virus commonly occurs in bank voles. Furthermore, phylogenetic analyses indicate the virus belongs to a highly divergent Embecovirus lineage predominantly associated with bank voles.", "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Barbara J Mann", - "author_inst": "University of Virginia" + "author_name": "Anishia Wasberg", + "author_inst": "Uppsala University, Uppsala, Sweden" }, { - "author_name": "Preeti Chhabra", - "author_inst": "University of Virginia" + "author_name": "Jayna Raghwani", + "author_inst": "Department of Zoology, University of Oxford" }, { - "author_name": "Mingyang Ma", - "author_inst": "University of Virginia" + "author_name": "JInlin Li", + "author_inst": "Uppsala University" }, { - "author_name": "Savannah G Brovero", - "author_inst": "University of Virginia" + "author_name": "John H.-O. Pettersson", + "author_inst": "Uppsala University" }, { - "author_name": "Marieka K Jones", - "author_inst": "University of Virginia" + "author_name": "Johanna Lindahl", + "author_inst": "Zoonosis Science Center, Department of Medical Biochemistry and Microbiology, Uppsala University, Sweden." }, { - "author_name": "Joel M Linden", - "author_inst": "University of Virginia" + "author_name": "Ake Lundkvist", + "author_inst": "Uppsala University" }, { - "author_name": "Kenneth L Brayman", - "author_inst": "University of Virginia" + "author_name": "Jiaxin Ling", + "author_inst": "Department of Medical Biochemistry and Microbiology, Zoonosis Science Center, University of Uppsala" } ], "version": "1", @@ -395508,49 +395587,49 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2022.02.22.22270091", - "rel_title": "Abdominal Imaging Associates Body Composition with COVID-19 Severity", + "rel_doi": "10.1101/2022.02.18.22271189", + "rel_title": "Avoiding false positive SARS-CoV-2 rapid antigen test results with point-of-care molecular testing on residual test buffer", "rel_date": "2022-02-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.22.22270091", - "rel_abs": "The main drivers of COVID-19 disease severity and the impact of COVID-19 on long-term health after recovery are yet to be fully understood. Medical imaging studies investigating COVID-19 to date have mostly been limited to small datasets and post-hoc analyses of severe cases. The UK Biobank recruited recovered SARS-CoV-2 positive individuals (n=967) and matched controls (n=913) who were extensively imaged prior to the pandemic and underwent follow-up scanning. In this study, we investigated longitudinal changes in body composition, as well as the associations of pre-pandemic image-derived phenotypes with COVID-19 severity. Our longitudinal analysis, in a population of mostly mild cases, associated a decrease in lung volume with SARS-CoV-2 positivity. We also observed that increased visceral adipose tissue and liver fat, and reduced muscle volume, prior to COVID-19, were associated with COVID-19 disease severity. Finally, we trained a machine classifier with demographic, anthropometric and imaging traits, and showed that visceral fat, liver fat and muscle volume have prognostic value for COVID-19 disease severity beyond the standard demographic and anthropometric measurements. This combination of image-derived phenotypes from abdominal MRI scans and ensemble learning to predict risk may have future clinical utility in identifying populations at-risk for a severe COVID-19 outcome.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.18.22271189", + "rel_abs": "ObjectivesAntigen-based rapid diagnostic tests (Ag-RDTs) have been widely used for the detection of SARS-CoV-2 during the Covid-19 pandemic. In settings of low disease prevalence, such as asymptomatic community testing, national guidelines recommend molecular confirmation of positive Ag-RDT results. This often requires patients to be recalled for repeat specimen recollection and subsequent testing in reference laboratories. This project assessed the use of a point-of-care molecular method for SARS-CoV-2 detection on-site at a volunteer-led asymptomatic community testing site, using the residual test buffer (RTB) from positive Ag-RDTs.\n\nMethodsThe Abbott COVID-19 ID NOW assay was performed on RTB from two Ag-RDTs: the Abbott Panbio COVID-19 Ag Rapid Test Device and the BTNX Rapid Response COVID-19 Antigen Rapid Test Device. All RTBs were tested using real-time RT-PCR at a reference laboratory using the ThermoFisher TaqPath COVID-19 Combo kit which was used to assign positive Ag-RDTs results as true or false positives. Analytical specificity of the ID NOW was assessed with a panel of various respiratory organisms.\n\nResultsOf 419 positive Ag-RDTs from 5148 tests performed, ID NOW testing of the RTB was positive in 100% of the samples characterized as true positives by RT-PCR. No SARS-CoV-2 detections by ID NOW were observed from 10 specimens characterized as false positive Ag-RDTs, or from contrived specimens with various respiratory organisms.\n\nConclusionsThe use of on-site molecular testing on RTB provides a suitable option for rapid confirmatory testing of positive Ag-RDTs, thereby obviating the need for specimen recollection for molecular testing at local reference laboratories.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Nicolas Basty", - "author_inst": "Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK" + "author_name": "Jason J LeBlanc", + "author_inst": "Division of Microbiology, Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, Nova Scotia, Canada" }, { - "author_name": "Elena P Sorokin", - "author_inst": "Calico Life Sciences LLC, South San Francisco, California, USA" + "author_name": "Greg R McCracken", + "author_inst": "Division of Microbiology, Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, Nova Scotia, Canada" }, { - "author_name": "Marjola Thanaj", - "author_inst": "Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK" + "author_name": "Barbara Goodall", + "author_inst": "Department of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada." }, { - "author_name": "Ramprakash Srinivasan", - "author_inst": "Calico Life Sciences LLC, South San Francisco, California, USA" + "author_name": "Todd F Hatchette", + "author_inst": "Division of Microbiology, Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, Nova Scotia, Canada." }, { - "author_name": "Brandon Whitcher", - "author_inst": "Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK" + "author_name": "Lisa Barrett", + "author_inst": "Department of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada." }, { - "author_name": "Jimmy D Bell", - "author_inst": "Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK" + "author_name": "John Ross", + "author_inst": "Praxes Medical Group" }, { - "author_name": "Madeleine Cule", - "author_inst": "Calico Life Sciences LLC, South San Francisco, California, USA" + "author_name": "Ross J Davidson", + "author_inst": "Division of Microbiology, Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, Nova Scotia, Canada." }, { - "author_name": "E. Louise Thomas", - "author_inst": "Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK" + "author_name": "Glenn Patriquin", + "author_inst": "Division of Microbiology, Department of Pathology and Laboratory Medicine, Nova Scotia Health, Halifax, Nova Scotia, Canada." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -397098,71 +397177,91 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2022.02.21.22271127", - "rel_title": "Favourable vaccine-induced SARS-CoV-2 specific T cell response profile in patients undergoing immune-modifying therapies", + "rel_doi": "10.1101/2022.02.21.22271234", + "rel_title": "Cell-Mediated Immune Response after COVID 19 Vaccination in Patients with Inflammatory Bowel Disease", "rel_date": "2022-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.21.22271127", - "rel_abs": "Patients undergoing immune-modifying therapies demonstrate a reduced humoral response after COVID-19 vaccination, but we lack a proper evaluation of the impact of such therapies on vaccine-induced T cell responses. Here, we longitudinally characterised humoral and Spike-specific T cell responses in inflammatory bowel disease (IBD) patients who are on antimetabolite therapy (azathioprine or methotrexate), TNF inhibitors and/or other biologic treatment (anti-integrin or anti-p40) after mRNA vaccination up to 3 months after completing two vaccine doses. We demonstrated that a Spike-specific T cell response is not only induced in treated IBD patients at levels similar to healthy individuals, but also sustained at higher magnitude, particularly in those treated with TNF inhibitor therapy. Furthermore, the Spike-specific T cell response in these patients is mainly preserved against mutations present in SARS-CoV-2 B.1.1.529 (Omicron) and characterized by a Th1/IL-10 cytokine profile. Thus, despite the humoral response defects, the favourable profile of vaccine-induced T cell responses might still provide a layer of COVID-19 protection to patients under immune-modifying therapies.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.21.22271234", + "rel_abs": "IntroductionMost patients with IBD mount an antibody response to mRNA COVID-19 vaccines, but few studies have evaluated the cell mediated immune response (CMIR).\n\nMethodsWe performed a prospective study (HERCULES) to evaluate CMIR among patients with IBD and healthy controls (HC) after completion of the primary series of mRNA COVID-19 vaccines.\n\nResultsOne hundred 158 patients with IBD and 20 HC were enrolled. The majority (89%) of IBD patients developed a CMIR which was not different than HC (94%, p=0.6667). There was no significant difference (p=0.5488) in CMIR response between those not immunosuppressed (median 255 Spike T cells/million PBMC, IQR 146, 958) and immunosuppressed (median 377, IQR 123, 1440). There was also no correlation between antibody responses and CMIR (p=0.5215)\n\nDiscussionMost patients with IBD achieved CMIR to a COVID-19 vaccine. Future studies are needed evaluating sustained CMIR and clinical outcomes.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Martin QI", - "author_inst": "Programme in Emerging Infectious Diseases, Duke-NUS Medical School; Singapore" + "author_name": "Freddy Caldera", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Nina Le Bert", - "author_inst": "Programme in Emerging Infectious Diseases, Duke-NUS Medical School; Singapore." + "author_name": "Francis Farraye", + "author_inst": "Inflammatory Bowel Disease Center, Department of Gastroenterology and Hepatology, Mayo Clinic, Jacksonville, Florida, United States" }, { - "author_name": "Webber Chan", - "author_inst": "Department of Gastroenterology and Hepatology, Singapore General Hospital; Singapore" + "author_name": "Brian Necela", + "author_inst": "Department of Immunology, Mayo Clinic, Jacksonville, Florida, United States" }, { - "author_name": "Malcom Tan", - "author_inst": "Department of Gastroenterology and Hepatology, Singapore General Hospital; Singapore" + "author_name": "Davitte Cogen", + "author_inst": "Department of Immunology, Mayo Clinic, Jacksonville, Florida, United States" }, { - "author_name": "Shou Kit Hang", - "author_inst": "Programme in Emerging Infectious Diseases, Duke-NUS Medical School; Singapore" + "author_name": "Sumona Saha", + "author_inst": "Department of Medicine, Division of Gastroenterology and Hepatology, University of Wisconsin School of Medicine & Public Health, Madison, Wisconsin, United Stat" }, { - "author_name": "Smrithi Hariharaputran", - "author_inst": "Programme in Emerging Infectious Diseases, Duke-NUS Medical School; Singapore" + "author_name": "Arnold Wald", + "author_inst": "Department of Medicine, Division of Gastroenterology and Hepatology, University of Wisconsin School of Medicine & Public Health, Madison, Wisconsin, United Stat" }, { - "author_name": "Jean Xiang Ying Sim", - "author_inst": "Department of Infectious Disease, Singapore General Hospital; Singapore" + "author_name": "Nader Daoud", + "author_inst": "Division of Gastroenterology & Hepatology, Mayo Clinic, Jacksonville, FL, United States" }, { - "author_name": "Jenny Low", - "author_inst": "Department of Infectious Disease, Singapore General Hospital; Singapore" + "author_name": "Kelly Chun", + "author_inst": "LabCorp, R&D and Specialty Medicine" }, { - "author_name": "Wei Ling Ng", - "author_inst": "Department of Microbiology, Singapore General Hospital; Singapore" + "author_name": "Ian Grimes", + "author_inst": "Department of Medicine, Division of Gastroenterology and Hepatology, University of Wisconsin School of Medicine & Public Health, Madison, Wisconsin, United Stat" }, { - "author_name": "Wei Yee Wan", - "author_inst": "Department of Microbiology, Singapore General Hospital; Singapore" + "author_name": "Megan Lutz", + "author_inst": "Department of Medicine, Division of Gastroenterology and Hepatology, University of Wisconsin School of Medicine & Public Health, Madison, Wisconsin, United Stat" }, { - "author_name": "Tiing Leong Ang", - "author_inst": "Department of Gastroenterology and Hepatology, Changi General Hospital; Singapore" + "author_name": "Melanie D Swift", + "author_inst": "Division of Public Health, Infectious Diseases and Occupational Medicine, Mayo Clinic, Rochester, Minnesota, United States" }, { - "author_name": "Antonio Bertoletti", - "author_inst": "Duke-Nus Medical School" + "author_name": "Abinash Virk", + "author_inst": "Division of Infectious Disease, Mayo Clinic, Rochester, Minnesota, United States" + }, + { + "author_name": "Adil E Bharucha", + "author_inst": "Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, Minnesota, United States" + }, + { + "author_name": "Tushar Patel", + "author_inst": "Division of Gastroenterology & Hepatology, Mayo Clinic, Jacksonville, FL, United States" }, { - "author_name": "Ennaliza Salazar", - "author_inst": "Department of Gastroenterology and Hepatology, Singapore General Hospital; Singapore" + "author_name": "Gregory J Gores", + "author_inst": "Division of Gastroenterology & Hepatology, Mayo Clinic, Rochester, Minnesota, United States" + }, + { + "author_name": "Saranya Chumsri", + "author_inst": "Division of Hematology and Medical Oncology, Mayo Clinic, Jacksonville, Florida, United States" + }, + { + "author_name": "Mary S. Hayney", + "author_inst": "School of Pharmacy, University of Wisconsin School of Medicine & Public Health, Madison, Wisconsin, United States" + }, + { + "author_name": "Keith L Knuttson", + "author_inst": "Department of Immunology, Mayo Clinic, Jacksonville, Florida, United States" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "gastroenterology" }, { "rel_doi": "10.1101/2022.02.21.481269", @@ -398967,41 +399066,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.21.22271298", - "rel_title": "Effectiveness of Covid-19 vaccines against symptomatic and asymptomatic SARS-CoV-2 infections in an urgent care setting", + "rel_doi": "10.1101/2022.02.19.22271230", + "rel_title": "A role for Nucleocapsid-specific antibody function in Covid-19 Convalescent plasma therapy", "rel_date": "2022-02-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.21.22271298", - "rel_abs": "BackgroundIt is critical to monitor changes in vaccine effectiveness against COVID-19 outcomes for various vaccine products in different population subgroups.\n\nMethodsWe conducted a retrospective study in patients [≥]12 years who underwent testing for the SARS-CoV-2 virus from April 1 - October 25, 2021 at urgent care centers in the New York City metropolitan area. Patients self-reported vaccination status at the time of testing. We used a test-negative design to estimate vaccine effectiveness (VE) by comparing odds of a positive test for SARS-CoV-2 infection among vaccinated (n=484,468), partially vaccinated (n=107,573), and unvaccinated (n=466,452) patients, adjusted for demographic factors and calendar time.\n\nResultsVE against symptomatic infection after 2 doses of mRNA vaccines was 96% (95% Confidence Interval [CI]: 95%, 97%) in the pre-delta period and reduced to 79% (95% CI: 77%, 81%) in the delta period. In the delta period, VE for 12-15-year-olds (85%; [95% CI: 81%, 89%]) was higher compared to older age groups (<65% for all other age groups). VE estimates did not differ by sex, race/ethnicity, and comorbidity. VE against symptomatic infection was the highest for individuals with a prior infection followed by full vaccination. VE against symptomatic infection after the mRNA-1273 vaccine (83% [95% CI: 81%, 84%]) was higher compared to the BNT162b2 vaccine (76% [95% CI: 74%, 78%]) in the delta period. VE after the single-dose Ad26.COV2.S vaccine was the lowest compared to other vaccines (29% [95% CI: 26%, 32%]) in the delta period.\n\nConclusionsVE against infection after two doses of the mRNA vaccine was high initially, but significantly reduced against the delta variant for all three FDA-approved vaccines.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.19.22271230", + "rel_abs": "COVID-19 convalescent plasma (CCP), a passive polyclonal antibody therapeutic, has exhibited mixed results in the treatment of COVID-19. Given that the therapeutic effect of CCP may extend beyond the ability of SARS-CoV-2-specific antibody binding and neutralization to influence the evolution of the endogenous antibody response, we took a systematic and comprehensive approach to analyze SARS-CoV-2 functional antibody profiles of participants in a randomized controlled trial of CCP treatment of individuals hospitalized with COVID-19 pneumonia where CCP was associated with both decreased mortality and improved clinical severity. Using systems serology, we found that the clinical benefit of CCP is related to a shift towards reduced inflammatory Spike (S) responses and enhanced Nucleocapsid (N) humoral responses. We found CCP had the greatest clinical benefit in participants with low pre-existing anti-SARS-CoV-2 antibody function, rather than S or N antibody levels or participant demographic features. Further, CCP induced immunomodulatory changes to recipient humoral profiles persisted for at least two months, marked by the selective evolution of anti-inflammatory Fc-glycan profiles and persistently expanded nucleocapsid-specific humoral immunity following CCP therapy. Together, our findings identify a novel mechanism of action of CCP, suggest optimal patient characteristics for CCP treatment, identify long-last immunomodulatory effects of CCP, and provide guidance for development of novel N-focused antibody therapeutics for severe COVID-19 hyperinflammation.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Madhura S. Rane", - "author_inst": "Institute for Implementation Science in Population Health, City University of New York. New York, NY USA" + "author_name": "Jonathan D Herman", + "author_inst": "Ragon Institute of MGH, MIT, and Harvard" }, { - "author_name": "McKaylee Robertson", - "author_inst": "Institute for Implementation Science in Population Health, City University of New York. New York, NY USA" + "author_name": "Chuangqi Wang", + "author_inst": "Department of Biological Engineering, Massachusetts Institute of Technology" }, { - "author_name": "Sarah Kulkarni", - "author_inst": "Institute for Implementation Science in Population Health, City University of New York. New York, NY USA" + "author_name": "John Stephen Burke", + "author_inst": "Ragon Institute of MGH, MIT, and Harvard" }, { - "author_name": "Daniel Frogel", - "author_inst": "CityMD/Summit Medical Group, New York, NY, USA" + "author_name": "Yonatan Zur", + "author_inst": "Ragon Institute of MGH, MIT, and Harvard" }, { - "author_name": "Chris Gainus", - "author_inst": "CityMD/Summit Medical Group, New York, NY, USA" + "author_name": "Hacheming Compere", + "author_inst": "Ragon Institute of MGH, MIT, and Harvard" }, { - "author_name": "Denis Nash", - "author_inst": "CUNY Graduate School of Public Health; Institute for Implementation Science in Population Health, City University of New York. New York, NY USA" + "author_name": "Jaewon Kang", + "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + }, + { + "author_name": "Ryan Macvicar", + "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + }, + { + "author_name": "Sally Shin", + "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + }, + { + "author_name": "Ian Frank", + "author_inst": "Department of Medicine, University of Pennsylvania" + }, + { + "author_name": "Don Siegel", + "author_inst": "Department of Pathology and Laboratory Medicine, University of Pennsylvania" + }, + { + "author_name": "Pablo Tebas", + "author_inst": "Department of Medicine, University of Pennsylvania" + }, + { + "author_name": "Grace H Choi", + "author_inst": "Department of Biostatistics, Epidemiology, and Informatics, University of Pennsylvania" + }, + { + "author_name": "Pamela A Shaw", + "author_inst": "Kaiser Permanente Washington Health Research Group" + }, + { + "author_name": "Hyunah Yoon", + "author_inst": "Division of Infectious Diseases, Department of Medicine. Albert Einstein College of Medicine and Montefiore Medical Center" + }, + { + "author_name": "Liise-anne Pirofski", + "author_inst": "Division of Infectious Diseases, Department of Medicine. Albert Einstein College of Medicine and Montefiore Medical Center" + }, + { + "author_name": "Boris Juelg", + "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + }, + { + "author_name": "Katharine J Bar", + "author_inst": "Department of Medicine, University of Pennsylvania" + }, + { + "author_name": "Douglas Lauffenburger", + "author_inst": "Department of Biological Engineering, Massachusetts Institute of Technology" + }, + { + "author_name": "Galit Alter", + "author_inst": "Ragon Institute of MGH, MIT, and Harvard" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -401101,47 +401252,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.19.22271221", - "rel_title": "Risk of SARS-CoV-2 reinfection 18 months after primary infection: population-level observational study.", + "rel_doi": "10.1101/2022.02.15.22271010", + "rel_title": "The level of liver and renal function biomarker abnormalities among hospitalized COVID-19 patients in Ethiopia", "rel_date": "2022-02-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.19.22271221", - "rel_abs": "Current data suggest that SARS-CoV-2 reinfections are rare, but uncertainties remain on the duration of the natural immunity, its protection against Omicron variant, finally the impact of vaccination to reduce reinfection rates. In this retrospective cohort analysis of the entire population of an Italian Region, we followed 1,293,941 subjects from the beginning of the pandemic to the current scenario of Omicron predominance (up to mid-January 2022). After an average of 334 days, we recorded 260 reinfections among 84,907 previously infected subjects (overall rate: 0.31%), two hospitalizations (2.4 x100,000), and one death. Importantly, the incidence of reinfection did not vary substantially over time: after 18-22 months from the primary infection, the reinfection rate was still 0.32%, suggesting that protection conferred by natural immunity may last beyond 12 months. The risk of reinfection was significantly higher among the unvaccinated subjects, and during the Omicron wave.", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.15.22271010", + "rel_abs": "BackgroundCOVID-19 pandemic is unprecedented public health emergency and added burden to developing countries. The pandemic cause multi organ failures (MOF) predominantly affects lung, cardiac, renal and liver organs as severity of the disease exacerbates. That is the rationale to execute this study with the aim to determine the magnitude of abnormal organ function test parameters and its association between markers of organ failure and disease severity in patients infected with COVID-19 admitted at Millennium COVID-19 Care Center (CCC).\n\nMethodsA cross-sectional study was conducted among COVID-19 patients admitted at Millennium COVID-19 Care and Treatment Center (MCCTC) from May 2021 up to Oct 2021. In this study 500 participants information were collected from the laboratory database of Millennium COVID-19 care center. Data were analyzed using SPSS version 25. P-value <0.05 was considered significantly associated.\n\nResultThe median age of the 500 study participants was 55.6{+/-}7.7 years, and from these 67.6% of patients were males. Liver function parameters Aspartae transferase (AST),) alanine aminotransferase (ALT) and Alakaline phosphatase (ALP) the mean value of overall patients were elevated and three of these parameters were highly elevated among critical patients (56.9{+/-}57.7, 58.5{+/-}6, and 114.6{+/-}6) respectively. All study participants had an elevated Creatinine. 66.8% males, 65% Intensive care unit (ICU), had an elevated serum value of ALT and AST respectively. Troponin was found elevated among males (54%) and 59% among ICU (critical) patients.\n\nConclusionLiver and renal function test biomarkers such as creatine kinase muscle-brain isoenzymes (CK-MB), troponin, AST, ALT and Creatinine serum value was found elevated among ICU than non ICU patients. Organ function biomarkers are a candidate for predicting COVID-19 disease severity in order to guide clinical care.", "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Maria Elena Flacco", - "author_inst": "University of Ferrara" + "author_name": "Yakob Tsegay", + "author_inst": "University of Gondar" }, { - "author_name": "Graziella Soldato", - "author_inst": "Local Health Unit of Pescara" + "author_name": "Molalegne Bitew", + "author_inst": "Ethiopian Biotechnology Institute" }, { - "author_name": "Cecilia Acuti Martellucci", - "author_inst": "University of Ferrara" + "author_name": "Asegidew Atlaw", + "author_inst": "Addis Ababa University college of health science department of medical laboratory science" }, { - "author_name": "Giuseppe Di Martino", - "author_inst": "Local Health Unit of Pescara" + "author_name": "Mintesnot Aragaw", + "author_inst": "Addis Ababa University college of health science department of medical laboratory science" }, { - "author_name": "Roberto Carota", - "author_inst": "Local Health Unit of Pescara" + "author_name": "Tigist Workneh", + "author_inst": "Millennium COVID-19 Care Center Research Center St. Paul hospital millennium medical college (SPHMMC), Addis Ababa, Ethiopia" }, { - "author_name": "Antonio Caponetti", - "author_inst": "Local Health Unit of Pescara" + "author_name": "Messay Gemechu", + "author_inst": "Millennium COVID-19 Care Center Research Center St. Paul hospital millennium medical college (SPHMMC), Addis Ababa, Ethiopia" }, { - "author_name": "Lamberto Manzoli", - "author_inst": "University of Bologna" + "author_name": "Nega Berhane", + "author_inst": "Fondation Campus Biotech" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.02.17.22271126", @@ -402959,139 +403110,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.15.22270954", - "rel_title": "Validation of the RT-LAMP assay in a large cohort of nasopharyngeal swab samples shows that it is a useful screening method for detecting SARS-CoV-2 and its VOC variants", + "rel_doi": "10.1101/2022.02.17.479764", + "rel_title": "Biomechanical dependence of SARS-CoV-2 infections", "rel_date": "2022-02-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.15.22270954", - "rel_abs": "The COVID-19 pandemic is challenging the global supply chain and equipment needed for mass testing with RT-qPCR, the gold standard for SARS-CoV-2 diagnosis. Here, we propose the RT-LAMP assay as an additional strategy for rapid virus diagnosis. However, its validation as a diagnostic method remains uncertain. In this work, we validated the RT-LAMP assay in 1,266 nasopharyngeal swab samples with confirmed diagnosis by CDC 2019-nCoV RT-qPCR. Our cohort was divided, the first (n=984) was used to evaluate two sets of oligonucleotides (S1 and S3) and the second (n=281) to determine whether RT-LAMP could detect samples with several types of variants. This assay can identify positive samples by color change or fluorescence within 40 minutes and shows high concordance with RT-qPCR in samples with CT [≤]35. Also, S1 and S3 are able to detect SARS-CoV-2 with a sensitivity of 68.4% and 65.8%, and a specificity of 98.9% and 97.1%, respectively. Furthermore, RT-LAMP assay identified 279 sequenced samples as positive (99.3% sensitivity) corresponding to the Alpha, Beta, Gamma, Delta, Epsilon, Iota, Kappa, Lambda, Mu and Omicron variants. In conclusion, RT-LAMP is able to identify SARS-CoV-2 with good sensitivity and excellent specificity, including all VOC, VOI, VUM and FMV variants.", - "rel_num_authors": 30, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.17.479764", + "rel_abs": "Older people have been disproportionately vulnerable to the current SARS-CoV-2 pandemic, with an increased risk of severe complications and death compared to other age groups. A mix of underlying factors has been speculated to give rise to this differential infection outcome, including changes in lung physiology, weakened immunity, and severe immune response. Our study focuses on the impact of biomechanical changes in lungs that occur as individuals age, i.e., the stiffening of the lung parenchyma and increased matrix fiber density. We used hydrogels with an elastic modulus of 0.2 and 50 kPa and conventional tissue culture surfaces to investigate how infection rate changes with parenchymal tissue stiffness in lung epithelial cells challenged with SARS-CoV-2 Spike (S) protein pseudotyped lentiviruses. Further, we employed electrospun fiber matrices to isolate the effect of matrix density. Given the recent data highlighting the importance of alternative virulent strains, we included both the native strain identified in early 2020 and an early S protein variant (D614G) that was shown to increase the viral infectivity markedly. Our results show that cells on softer and sparser scaffolds, closer resembling younger lungs, exhibit higher infection rates by the WT and D614G variant. This suggests that natural changes in lung biomechanics do not increase the propensity for SARS-CoV-2 infection and that other factors, such as a weaker immune system, may contribute to increased disease burden in the elderly.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Mireya Cisneros-Villanueva", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Sugela S Blancas", - "author_inst": "Catedras CONACYT-Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Alberto Cedro-Tanda", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Magdalena Rios-Romero", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Eduardo Hurtado-Cordova", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Oscar Almaraz-Rojas", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Diana R Ortiz-Soriano", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Victor Alvarez-Hernandez", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Ivonne E Arriaga-Guzman", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Laura Tolentino-Garcia", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Antonia Sanchez-Vizcarra", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Laura F Lozada-Rodriguez", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Irlanda Peralta-Arrieta", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Jose E Perez-Aquino", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Marco A Andonegui-Elguera", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Mariana Cendejas-Orozco", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Alfredo Mendoza-Vargas", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Juan P Reyes-Grajeda", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Abraham Campos-Romero", - "author_inst": "Innovation and Research Department, Salud Digna" - }, - { - "author_name": "Jonathan Alcantar-Fernandez", - "author_inst": "Innovation and Research Department, Salud Digna" - }, - { - "author_name": "Jose L Moreno-Camacho", - "author_inst": "Clinical Laboratory Division, Salud Digna," - }, - { - "author_name": "Jorge Gallegos-Rodriguez", - "author_inst": "Clinical Laboratory Division, Salud Digna," - }, - { - "author_name": "Marco Esparza-Luna-Ruiz", - "author_inst": "Clinical Laboratory Division, Salud Digna," + "author_name": "Alexandra Paul", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Jesus Ortiz-Ramirez", - "author_inst": "Hospital General Ajusco Medio" + "author_name": "Sachin Kumar", + "author_inst": "Max Planck Institute for Polymer Research" }, { - "author_name": "Mariana Benitez-Gonzalez", - "author_inst": "Hospital General Ajusco Medio" + "author_name": "Tamer Kaoud", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Laura Uribe-Figueroa", - "author_inst": "Laboratorio Arion Genetica" + "author_name": "Madison R Pickett", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Ofelia Angulo", - "author_inst": "Secretaria de Educacion, Ciencia, Tecnologia e Innovacion de la Ciudad de Mexico" + "author_name": "Amanda L Bohanon", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Rosaura Ruiz", - "author_inst": "Secretaria de Educacion, Ciencia, Tecnologia e Innovacion de la Ciudad de Mexico" + "author_name": "Janet Zoldan", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Luis A Herrera", - "author_inst": "Instituto Nacional de Medicina Genomica" + "author_name": "Kevin N Dalby", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Alfredo Hidalgo-Miranda", - "author_inst": "Instituto Nacional de Medicina Genomica" + "author_name": "Sapun H. Parekh", + "author_inst": "University of Texas at Austin" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "license": "cc_by", + "type": "new results", + "category": "bioengineering" }, { "rel_doi": "10.1101/2022.02.16.480759", @@ -404745,115 +404808,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.13.22270755", - "rel_title": "Co-infection with SARS-COV-2 Omicron and Delta Variants Revealed by Genomic Surveillance", + "rel_doi": "10.1101/2022.02.07.22270630", + "rel_title": "COVID-19 onset reduced the sex ratio at birth in South Africa", "rel_date": "2022-02-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.13.22270755", - "rel_abs": "We identified the co-infection of the SARS-CoV-2 Omicron and Delta variants in two epidemiologically unrelated patients with chronic kidney disease requiring haemodialysis. Both SARS-CoV-2 variants were co-circulating locally at the time of detection. Amplicon- and probe-based sequencing using short- and long-read technologies identified and quantified Omicron and Delta subpopulations in respiratory samples from the two patients. These findings highlight the importance of genomic surveillance in vulnerable populations.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.07.22270630", + "rel_abs": "BackgroundThe sex ratio at birth [defined as male/(male+female) live births] is anticipated to approximate 0.510 with a slight male excess. Following sudden unexpected stressful events, this ratio has been observed to decrease transiently around 3-5 months following such events. We hypothesised that stress engendered by the onset of the COVID-19 pandemic may have caused such a decrease in South Africa 3-5 months after March 2020 since in this month, South Africa reported its first COVID-19 case, death and nationwide lockdown restrictions were instituted.\n\nMethodsWe used publicly available recorded monthly live birth data from Statistics South Africa. The most recent month for which data was available publicly was December 2020. We analysed live births for a 100-month period from September 2012 to December 2020, taking seasonality into account. Chi-squared tests were applied.\n\nResultsOver this 100-month period, there were 8,151,364 live births. The lowest recorded monthly sex ratio at birth of 0.499 was in June 2020, 3 months after March 2020. This June was the only month during this period where the sex ratio inverted i.e., fewer male live births occurred. The predicted June 2020 ratio was 0.504. The observed June 2020 decrease was statistically significant p = 0.045.\n\nConclusionsThe sex ratio at birth decreased and inverted in South Africa in June 2020, for the first time, during the most recent 100-month period. This decline occurred 3 months after the March 2020 onset of COVID-19 in South Africa. As June 2020 is within the critical window when population stressors are known to impact the sex ratio at birth, these findings suggest that the onset of the COVID-19 pandemic engendered population stress with notable effects on pregnancy and public health in South Africa. These findings have implications for future pandemic preparedness and social policy.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Rebecca J Rockett", - "author_inst": "Sydney Institute for Infectious Diseases, University of Sydney, Sydney, New South Wales, Australia" - }, - { - "author_name": "Jenny Draper", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Mailie Gall", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Eby M Sim", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Alicia Arnott", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Jessica E Agius", - "author_inst": "Sydney Institute for Infectious Diseases, University of Sydney, Sydney, New South Wales, Australia" - }, - { - "author_name": "Jessica Johnson-Mackinnon", - "author_inst": "Sydney Institute for Infectious Diseases, University of Sydney, Sydney, New South Wales, Australia" - }, - { - "author_name": "Elena Martinez", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Alexander P Drew", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Clement Lee", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Christine Ngo", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Marc Ramsperger", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Andrew N Ginn", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Qinning Wang", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Michael Fennell", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Danny Ko", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Linda Huston", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" - }, - { - "author_name": "Lukas Kairaitis", - "author_inst": "Renal Services, Blacktown Hospital, Western Sydney Local Health District, Sydney, New South Wales, Australia" - }, - { - "author_name": "Edward C Holmes", - "author_inst": "School of Life & Environmental Sciences and School of Medical Sciences, University of Sydney, Sydney, New South Wales, Australia" + "author_name": "Gwinyai Masukume", + "author_inst": "Academic Department of Paediatrics, Medical School, Mater Dei Hospital, Malta" }, { - "author_name": "Matthew N O'Sullivan", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" + "author_name": "Margaret Ryan", + "author_inst": "School of Social Work and Social Policy, Trinity College Dublin, Dublin, Ireland" }, { - "author_name": "Sharon C-A Chen", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" + "author_name": "Rumbidzai Masukume", + "author_inst": "Department of Obstetrics and Gynaecology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa" }, { - "author_name": "Jen Kok", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" + "author_name": "Dorota Zammit", + "author_inst": "National Statistics Office, Malta" }, { - "author_name": "Dominic E Dwyer", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, Institute for Clinical Pathology and Medical Research, New South Wales Health Pathology Wes" + "author_name": "Victor Grech", + "author_inst": "Academic Department of Paediatrics, Medical School, Mater Dei Hospital, Malta" }, { - "author_name": "Vitali Sintchenko", - "author_inst": "Sydney Institute for Infectious Diseases, University of Sydney, Sydney, New South Wales, Australia" + "author_name": "Witness Mapanga", + "author_inst": "Division of Medical Oncology, Department of Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, So" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.02.10.22270797", @@ -406983,95 +406974,115 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.14.22270845", - "rel_title": "Quantitative, multiplexed, targeted proteomics for ascertaining variant specific SARS-CoV-2 antibody response", + "rel_doi": "10.1101/2022.02.14.22270934", + "rel_title": "SARS-CoV-2 infection in Africa: A systematic review and meta-analysis of standardised seroprevalence studies, from January 2020 to December 2021", "rel_date": "2022-02-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.14.22270845", - "rel_abs": "Determining the protection an individual has to SARS-CoV-2 variants of concern (VoC) will be crucial for future immune surveillance and understanding the changing immune response. As further variants emerge, current serology tests are becoming less effective in reflecting neutralising capability of the immune system. A better measure of an evolving antigen-antibody immune response is needed. We describe a multiplexed, baited, targeted-proteomic assay for direct detection of multiple proteins in the SARS-CoV-2 anti-spike antibody immunocomplex. This enables a more sophisticated and informative characterisation of the antibody response to vaccination and infection against VoC. Using this assay, we detail different and specific responses to each variant by measuring several antibody classes, isotypes and associated complement binding. Furthermore, we describe how these proteins change using serum from individuals collected after infection, first and second dose vaccination. We show complete IgG1 test concordance with gold standard ELISA (r>0.8) and live virus neutralisation against Wuhan Hu-1, Alpha B.1.1.7, Beta B.1.351, and Delta B.1.617.1 variants (r>0.79). We also describe a wide degree of heterogeneity in the immunocomplex of individuals and a greater IgA response in those patients who had a previous infection. Significantly, our test points to an important role the complement system may play particularly against VoC. Where we observe altered Complement C1q association to the Delta VoC response and a stronger overall association with neutralising antibodies than IgG1. A detailed understanding of an individuals antibody response could benefit public health immunosurveillance, vaccine design and inform vaccination dosing using a personalised medicine approach.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.14.22270934", + "rel_abs": "IntroductionEstimating COVID-19 cumulative incidence in Africa remains problematic due to challenges in contact tracing, routine surveillance systems and laboratory testing capacities and strategies. We undertook a meta-analysis of population-based seroprevalence studies to estimate SARS-CoV-2 seroprevalence in Africa to inform evidence-based decision making on Public Health and Social Measures (PHSM) and vaccine strategy.\n\nMethodsWe searched for seroprevalence studies conducted in Africa published 01-01-2020 to 30-12-2021 in Medline, Embase, Web of Science, and Europe PMC (preprints), grey literature, media releases and early results from WHO Unity studies. All studies were screened, extracted, assessed for risk of bias and evaluated for alignment with the WHO Unity protocol for seroepidemiological investigations. We conducted descriptive analyses of seroprevalence and meta-analysed seroprevalence differences by demographic groups, place and time. We estimated the extent of undetected infections by comparing seroprevalence and cumulative incidence of confirmed cases reported to WHO. PROSPERO: CRD42020183634.\n\nResultsWe identified 54 full texts or early results, reporting 151 distinct seroprevalence studies in Africa Of these, 95 (63%) were low/moderate risk of bias studies. SARS-CoV-2 seroprevalence rose from 3.0% [95% CI: 1.0-9.2%] in Q2 2020 to 65.1% [95% CI: 56.3-73.0%] in Q3 2021. The ratios of seroprevalence from infection to cumulative incidence of confirmed cases was large (overall: 97:1, ranging from 10:1 to 958:1) and steady over time. Seroprevalence was highly heterogeneous both within countries - urban vs. rural (lower seroprevalence for rural geographic areas), children vs. adults (children aged 0-9 years had the lowest seroprevalence) - and between countries and African sub-regions (Middle, Western and Eastern Africa associated with higher seroprevalence).\n\nConclusionWe report high seroprevalence in Africa suggesting greater population exposure to SARS-CoV-2 and protection against COVID-19 disease than indicated by surveillance data. As seroprevalence was heterogeneous, targeted PHSM and vaccination strategies need to be tailored to local epidemiological situations.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Ivan Doykov", - "author_inst": "UCL Institute of Child Health, London" + "author_name": "Hannah C Lewis Mrs.", + "author_inst": "World Health Organization Regional Office for Africa, Brazzaville, Congo" }, { - "author_name": "Justyna Spiewak", - "author_inst": "UCL Institute of Child Health, London" + "author_name": "Harriet Ware Ms.", + "author_inst": "Cumming School of Medicine, University of Calgary, Canada" }, { - "author_name": "Kimberly C Gilmour", - "author_inst": "Great Ormond Street Children's Hospital NHS Foundation Trust, Great Ormond Street, London; WC1N 3JH, UK" + "author_name": "Mairead G Whelan Ms.", + "author_inst": "Centre for Health Informatics, Cumming School of Medicine, University of Calgary, Calgary, Canada" }, { - "author_name": "Joseph M Gibbons", - "author_inst": "Barts and The London School of Medicine and Dentistry Blizard Institute" + "author_name": "Lorenzo Subissi Dr.", + "author_inst": "World Health Organization, Geneva, Switzerland" }, { - "author_name": "Corinna Pade", - "author_inst": "Barts and The London School of Medicine and Dentistry Blizard Institute" + "author_name": "Zihan Li Mr.", + "author_inst": "University of Waterloo, University of Calgary, Canada" }, { - "author_name": "Aine McKnight", - "author_inst": "Barts and The London School of Medicine and Dentistry Blizard Institute" + "author_name": "Xiaomeng Ma Ms.", + "author_inst": "Institute of Health Policy, Management and Evaluation, University of Toronto, Canada" }, { - "author_name": "Mahdad Noursadeghi", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Anthony Nardone Dr.", + "author_inst": "Epiconcept, France; World Health Organization, Geneva, Switzerland" }, { - "author_name": "Mala Maini", - "author_inst": "Division of Infection and Immunity, University College London, London, UK" + "author_name": "Marta Valenciano Dr.", + "author_inst": "Epiconcept, France; World Health Organization, Geneva, Switzerland" }, { - "author_name": "Charlotte Manisty", - "author_inst": "University College London and Barts Heart Centre" + "author_name": "Brianna Cheng Dr.", + "author_inst": "World Health Organization, Geneva, Switzerland" }, { - "author_name": "Thomas A Treibel", - "author_inst": "University College London and Barts Heart Centre" + "author_name": "Kim C Noel Mrs.", + "author_inst": "Department of Epidemiology, Biostatistics, and Occupational Health, Faculty of Medicine and Health Sciences, McGill University, Canada" }, { - "author_name": "Gabriella Captur", - "author_inst": "Institute of Cardiovascular Science, University College London, London, UK" + "author_name": "Christian Cao Mr.", + "author_inst": "Cumming School of Medicine, University of Calgary, Canada" }, { - "author_name": "Marianna Fontana", - "author_inst": "Institute of Cardiovascular Science, University College London, London, UK" + "author_name": "Mercedes Yanes-Lane Dr.", + "author_inst": "COVID-19 Immunity Task Force, Montreal, Canada" }, { - "author_name": "Rosemary Boyton", - "author_inst": "Imperial College London" + "author_name": "Belinda L Herring Dr.", + "author_inst": "World Health Organization Regional Office for Africa, Brazzaville, Congo" }, { - "author_name": "Daniel M Altmann", - "author_inst": "Imperial College" + "author_name": "Ambrose Otau Talisuna Dr.", + "author_inst": "World Health Organization Regional Office for Africa, Brazzaville, Congo" }, { - "author_name": "Tim Brooks", - "author_inst": "UK Health Security Agency; Porton Down, UK" + "author_name": "Ngoy Nsenga Dr.", + "author_inst": "World Health Organization Regional Office for Africa, Brazzaville, Congo" }, { - "author_name": "Amanda Semper", - "author_inst": "UK Health Security Agency; Porton Down, UK" + "author_name": "Thierno Balde Dr.", + "author_inst": "World Health Organization Regional Office for Africa, Brazzaville, Congo" }, { - "author_name": "James Moon", - "author_inst": "University College London and Barts Heart Centre" + "author_name": "David Clifton Prof.", + "author_inst": "Institute of Biomedical Engineering, University of Oxford, UK" }, { - "author_name": "Kevin Mills", - "author_inst": "UCL Institute of Child Health, London" + "author_name": "Maria Van Kerkhove Dr.", + "author_inst": "World Health Organization, Geneva, Switzerland" }, { - "author_name": "Wendy E Heywood", - "author_inst": "UCL Institute of Child Health, London" + "author_name": "David Buckeridge Dr.", + "author_inst": "Division of Infectious Diseases and Medical Microbiology, McGill University Health Centre, Montreal, Quebec, Canada" + }, + { + "author_name": "Niklas Bobrovitz Dr.", + "author_inst": "Temerty Faculty of Medicine, University of Toronto, Canada" + }, + { + "author_name": "Joseph C Okeibunor Prof.", + "author_inst": "World Health Organization Regional Office for Africa, Brazzaville, Congo" + }, + { + "author_name": "Rahul K Arora Mr", + "author_inst": "Institute for Biomedical Engineering, University of Oxford, Oxford, UK" + }, + { + "author_name": "Isabel BERGERI Dr.", + "author_inst": "World Health Organization, Geneva, Switzerland" + }, + { + "author_name": "- the UNITY Studies Collaborator Group", + "author_inst": "World Health Organization, Geneva, Switzerland" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.02.15.22270931", @@ -408973,97 +408984,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.11.22270854", - "rel_title": "Persistence of SARS-CoV-2 immunity, Omicron's footprints, and projections of epidemic resurgences in South African population cohorts.", + "rel_doi": "10.1101/2022.02.11.22269594", + "rel_title": "Syndromic surveillance for severe acute respiratory infections (SARI) enables valid estimation of COVID-19 hospitalization incidence and reveals underreporting of hospitalizations during pandemic peaks of three COVID-19 waves in Germany, 2020-2021", "rel_date": "2022-02-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.11.22270854", - "rel_abs": "Understanding the build-up of immunity with successive SARS-CoV-2 variants and the epidemiological conditions that favor rapidly expanding epidemics will facilitate future pandemic control. High-resolution infection and serology data from longitudinal household cohorts in South Africa reveal high cumulative infection rates and durable cross-protective immunity conferred by prior infection in the pre-Omicron era. Building on the cohorts history of past exposures to different SARS-CoV-2 variants and vaccination, we use mathematical models to explore the fitness advantage of the Omicron variant and its epidemic trajectory. Modelling suggests the Omicron wave infected a large fraction of the population, leaving a complex landscape of population immunity primed and boosted with antigenically distinct variants. Future SARS-CoV-2 resurgences are likely under a range of scenarios of viral characteristics, population contacts, and residual cross-protection.\n\nOne Sentence SummaryClosely monitored population in South Africa reveal high cumulative infection rates and durable protection by prior infection against pre-Omicron variants. Modelling indicates that a large fraction of the population has been infected with Omicron; yet epidemic resurgences are plausible under a wide range of epidemiologic scenarios.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.11.22269594", + "rel_abs": "ObjectiveThe emergence of coronavirus disease 2019 (COVID-19) required countries to establish COVID-19 surveillance by adapting existing systems, such as mandatory notification and syndromic surveillance systems. We estimated age-specific COVID-19 hospitalization and intensive care unit (ICU) burden from existing severe acute respiratory infections (SARI) surveillance and compared the results to COVID-19 notification data.\n\nMethodsUsing data on SARI cases with ICD-10 diagnosis codes for COVID-19 (COVID-SARI) from the ICD-10 based SARI sentinel, we estimated age-specific incidences for COVID-SARI hospitalization and ICU for the first five COVID-19 waves in Germany and compared these to incidences from notification data on COVID-19 cases using relative change {Delta}r at the peak of each wave.\n\nFindingsThe COVID-SARI incidence from sentinel data matched the notified COVID-19 hospitalization incidence in the first wave with {Delta}r=6% but was higher during second to fourth wave ({Delta}r =20% to 39%). In the fifth wave, the COVID-SARI incidence was lower than the notified COVID-19 hospitalization incidence ({Delta}r =-39%). For all waves and all age groups, the ICU incidence estimated from COVID-SARI was more than twice the estimation from notification data.\n\nConclusionThe use of validated SARI sentinel data adds robust and important information for assessing the true disease burden of severe COVID-19. Mandatory notifications of COVID-19 for hospital and ICU admission may underestimate (work overload in local health authorities) or overestimate (hospital admission for other reasons than the laboratory-confirmed SARS-CoV-2 infection) disease burden. Syndromic ICD-10 based SARI surveillance enables sustainable cross-pathogen surveillance for seasonal epidemics and pandemic preparedness of respiratory viral diseases.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Kaiyuan Sun", - "author_inst": "Division of International Epidemiology and Population Studies, Fogarty International Center, NIH" - }, - { - "author_name": "Stefano Tempia", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Jackie Kleynhans", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Anne von Gottberg", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Meredith L McMorrow", - "author_inst": "Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America." - }, - { - "author_name": "Nicole Wolter", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Jinal N. Bhiman", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Jocelyn Moyes", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Mignon du Plessis", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Maimuna Carrim", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Amelia Buys", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Neil A Martinson", - "author_inst": "Perinatal HIV Research Unit, University of the Witwatersrand, South Africa." - }, - { - "author_name": "Kathleen Kahn", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" - }, - { - "author_name": "Stephen Tollman", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" + "author_name": "Kristin Tolksdorf", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Limakatso Lebina", - "author_inst": "Perinatal HIV Research Unit, University of the Witwatersrand, South Africa." + "author_name": "Walter Haas", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Floidy Wafawanaka", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" + "author_name": "Ekkehard Schuler", + "author_inst": "Helios Kliniken GmbH" }, { - "author_name": "Jacques du Toit", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" + "author_name": "Lothar H. Wieler", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Francesc Xavier G\u00f3mez-Oliv\u00e9", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" + "author_name": "Julia Schilling", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Thulisa Mkhencele", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" + "author_name": "Osamah Hamouda", + "author_inst": "Robert Koch Institute" }, { - "author_name": "C\u00e9cile Viboud", - "author_inst": "Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, Maryland, United States of" + "author_name": "Michaela Diercke", + "author_inst": "Robert Koch Institute" }, { - "author_name": "Cheryl Cohen", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" + "author_name": "Silke Buda", + "author_inst": "Robert Koch Institute" } ], "version": "1", @@ -410602,129 +410561,149 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2022.02.10.479867", - "rel_title": "Lyophilized mRNA-lipid nanoparticles vaccine with long-term stability and high antigenicity against SARS-CoV-2", + "rel_doi": "10.1101/2022.02.09.479588", + "rel_title": "Epigenetic Memory of COVID-19 in Innate Immune Cells and Their Progenitors", "rel_date": "2022-02-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.10.479867", - "rel_abs": "Advanced mRNA vaccines play vital roles against SARS-CoV-2. However, due to their poor stability, most current mRNA delivery platforms need to be stored at -20{degrees}C or -70{degrees}C, which severely limits their distribution. Herein, we present lyophilized SARS-CoV-2 mRNA-lipid nanoparticle vaccines, which can be stored at room temperature with long-term thermostability. In the in vivo Delta virus challenge experiment, lyophilized Delta variant mRNA vaccine successfully protected mice from infection and cleared the virus. Lyophilized omicron mRNA vaccine enabled to elicit both potent humoral and cellular immunity. In booster immunization experiments in mice and old monkeys, lyophilized omicron mRNA vaccine could effectively increase the titers of neutralizing antibodies against wild-type coronavirus and omicron variants. In humans, lyophilized omicron mRNA vaccine as a booster shot could also engender excellent immunity and had less severe adverse events. This lyophilization platform overcomes the instability of mRNA vaccines without affecting their bioactivity, and significantly improved their accessibility, particularly in remote regions.", - "rel_num_authors": 28, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.09.479588", + "rel_abs": "Severe coronavirus disease 2019 (COVID-19) is characterized by systemic inflammation and can result in protracted symptoms. Robust systemic inflammation may trigger persistent changes in hematopoietic cells and innate immune memory through epigenetic mechanisms. We reveal that rare circulating hematopoietic stem and progenitor cells (HSPC), enriched from human blood, match the diversity of HSPC in bone marrow, enabling investigation of hematopoiesis and HSPC epigenomics. Following COVID-19, HSPC retain epigenomic alterations that are conveyed, through differentiation, to progeny innate immune cells. Epigenomic changes vary with disease severity, persist for months to a year, and are associated with increased myeloid cell differentiation and inflammatory or antiviral programs. Epigenetic reprogramming of HSPC may underly altered immune function following infection and be broadly relevant, especially for millions of COVID-19 survivors.\n\nOne Sentence SummaryTranscriptomic and epigenomic analysis of blood reveal sustained changes in hematopoiesis and innate immunity after COVID-19.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC=\"FIGDIR/small/479588v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (54K):\norg.highwire.dtl.DTLVardef@1ffe42dorg.highwire.dtl.DTLVardef@dd4868org.highwire.dtl.DTLVardef@1bcae8borg.highwire.dtl.DTLVardef@674e85_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 33, "rel_authors": [ { - "author_name": "Liangxia Ai", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Jin Gyu Cheong", + "author_inst": "Laboratory of Epigenetics and Immunity, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Yafei Li", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Arjun Ravishankar", + "author_inst": "Laboratory of Epigenetics and Immunity, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Li Zhou", - "author_inst": "Animal Biosafety Level 3 Laboratory, Wuhan University" + "author_name": "Siddhartha Sharma", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA" }, { - "author_name": "Hao Zhang", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Christopher Parkhurst", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Wenrong Yao", - "author_inst": "Jiangsu Rec-biotechnology Co. Ltd" + "author_name": "Djamel Nehar-Belaid", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA" }, { - "author_name": "Jinyu Han", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Sai Ma", + "author_inst": "Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA." }, { - "author_name": "Junmiao Wu", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Lucinda Paddock", + "author_inst": "Laboratory of Epigenetics and Immunity, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Ruiyue Wang", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Emin Karakaslar", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA" }, { - "author_name": "Weijie Wang", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Asa Thibodeau", + "author_inst": "The Jackson Laboratory for Genomic Medicine" }, { - "author_name": "Pan Xu", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Michael Bale", + "author_inst": "Laboratory of Epigenetics and Immunity, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Zhouwang Li", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Vinay Kartha", + "author_inst": "Gene Regulation Observatory, Broad Institute of MIT and Harvard, Cambridge, MA, USA." }, { - "author_name": "Chengliang Wei", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Jim Yee", + "author_inst": "Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Haobo Chen", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Minh Yen Mays", + "author_inst": "Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Jianqun Liang", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Louise Leyre", + "author_inst": "Immunology and Microbial Pathogenesis Program, Weill Cornell Graduate School, New York, NY, USA." }, { - "author_name": "Ming Guo", - "author_inst": "State Key Laboratory of Virology College of Life Sciences, Wuhan University" + "author_name": "Alexia Martinez de Paz", + "author_inst": "Laboratory of Epigenetics and Immunity, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Zhixiang Huang", - "author_inst": "Animal Biosafety Level 3 Laboratory, Wuhan University" + "author_name": "Andrew Daman", + "author_inst": "Laboratory of Epigenetics and Immunity, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Xin Wang", - "author_inst": "State Key Laboratory of Virology College of Life Sciences, Wuhan University" + "author_name": "Sergio Alvarez-Mulett", + "author_inst": "Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Zhen Zhang", - "author_inst": "State Key Laboratory of Virology College of Life Sciences, Wuhan University" + "author_name": "Lexi Robbins", + "author_inst": "Laboratory of Epigenetics and Immunity, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Wenjie Xiang", - "author_inst": "State Key Laboratory of Virology College of Life Sciences, Wuhan University" + "author_name": "Elyse LaFond", + "author_inst": "NYU Langone Health, New York City, NY, USA" }, { - "author_name": "Bin Lv", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Karissa Weidman", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Peiqi Peng", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Sabrina Racine-Brzostek", + "author_inst": "10Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Shangfeng Zhang", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "He Yang", + "author_inst": "Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Xuhao Ji", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "David Price", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Zhangyi Li", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "R. Brad Jones", + "author_inst": "Infectious Diseases Division, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Huiyi Luo", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd" + "author_name": "Edward Schenck", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Jianping Chen", - "author_inst": "Jiangsu Rec-biotechnology Co. Ltd, Wuhan Recogen Biotechnology Co. Ltd" + "author_name": "Rob Kaner", + "author_inst": "Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Ke Lan", - "author_inst": "State Key Laboratory of Virology College of Life Sciences, Animal Biosafety Level 3 Laboratory, Wuhan University" + "author_name": "Amy Chadburn", + "author_inst": "Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." }, { - "author_name": "Yong Hu", - "author_inst": "Shenzhen Rhegen Biotechnology Co. Ltd, Wuhan Recogen Biotechnology Co. Ltd" + "author_name": "Zhen Zhao", + "author_inst": "Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." + }, + { + "author_name": "Jason Buenrostro", + "author_inst": "Broad Institute of MIT and Harvard" + }, + { + "author_name": "Rachel Niec", + "author_inst": "Robin Chemers Neustein Laboratory of Mammalian Cell Biology and Development, The Rockefeller University, NY, USA" + }, + { + "author_name": "Lindsay Lief", + "author_inst": "Department and Immunology, Weill Cornell Medicine, New York, NY, USA." + }, + { + "author_name": "Duygu Ucar", + "author_inst": "The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA" + }, + { + "author_name": "Steven Josefowicz", + "author_inst": "Laboratory of Epigenetics and Immunity, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, USA." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -412508,95 +412487,75 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.02.08.479661", - "rel_title": "N-acylethanolamine acid amide hydrolase is a novel target for drugs against SARS-CoV-2 and Zika virus", + "rel_doi": "10.1101/2022.02.08.22270506", + "rel_title": "Symptoms and severity in vaccinated and unvaccinated patients hospitalised with SARS-CoV-2 delta (B.1.617.2) variant infection", "rel_date": "2022-02-09", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.02.08.479661", - "rel_abs": "Several compounds have been tested against SARS-CoV-2; at present, COVID-19 treatments decrease the deleterious inflammatory response and acute lung injury. However, the best therapeutic response would be expected by combining anti-inflammatory properties, while concomitantly blocking viral replication. These combined effects should drastically reduce both infection rate and severe complications induced by novel SARS-CoV-2 variants. Therefore, we explored the antiviral potency of a class of anti-inflammatory compounds that inhibit the N-Acylethanolamine acid amidase (NAAA). This enzyme catalyzes the hydrolysis of palmitoylethanolamide (PEA), a bioactive lipid that mediates anti-inflammatory and analgesic activity through the activation of peroxisome proliferator receptor- (PPAR-). Similarly, this pathway is likely to be a significant target to impede viral replication since PPAR- activation leads to dismantling of lipid droplets, where viral replication of Flaviviruses and Coronaviruses occurs.\n\nHere, we show that either genetic or pharmacological inhibition of the NAAA enzyme leads to five-fold reduction in the replication of both SARS-CoV-2 and ZIKV in various cell lines. Once NAAA enzyme is blocked, both ZIKV and SARS CoV-2 replication decrease, which parallels a sudden five-fold decrease in virion release. These effects induced by NAAA inhibition occurs concomitantly with stimulation of autophagy during infection. Remarkably, parallel antiviral and anti-inflammatory effects of NAAA antagonism were confirmed in ex-vivo experiments, within SARS-CoV-2 infected human PBMC cells, in which both viral genomes and TNF- production drop by ~60%. It is known that macrophages contribute to viral spread, excessive inflammation and macrophage activation syndrome that NAAA inhibitors might prevent, reducing the macrophage-induced acute respiratory distress syndrome and subsequent death of COVID-19 patients.", - "rel_num_authors": 19, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.08.22270506", + "rel_abs": "BackgroundThe diffusion of the SARS-CoV-2 delta (B.1.617.2) variant and the waning of immune response after primary Covid-19 vaccination favoured the breakthrough SARS-CoV-2 infections in vaccinated subjects. To assess the impact of vaccination, we determined the severity of infection in hospitalised patients according to vaccine status.\n\nMethodsWe retrospectively analysed data from patients hospitalised in 10 centres with a SARS-CoV-2 infection (delta variant) from July to November 2021: i) all patients who had completed their primary vaccination at least 14 days before hospital admission; and ii) the same number of completely unvaccinated patients. We assessed the impact of vaccination and other risk factors through logistic regression.\n\nFindingsWe included 955 patients (474 vaccinated and 481 unvaccinated). Vaccinated patients were significantly older, more frequently males, and with more comorbidities. They were less often admitted for Covid-19 (59{middle dot}3% vs. 75{middle dot}1%, p<0{middle dot}001), showed fewer lung lesions, and required oxygen less frequently (57{middle dot}5% vs. 73{middle dot}0%, p<0{middle dot}001), at a lower flow (3{middle dot}0 vs. 6{middle dot}0 L/min, p<0{middle dot}001), and for a shorter duration (3 vs. 6 days, p<0{middle dot}001). They less frequently required intensive care unit admission (16{middle dot}2 % vs. 36{middle dot}0 %, p<0{middle dot}001). Mortality at day 28 was not different between the two groups (16{middle dot}7% vs. 12.2%, p=0{middle dot}075), but multivariate logistic regression showed that vaccination significantly decreased the risk of negative outcomes, including mortality, even when considering older patients, and those with comorbidities.\n\nConclusionsAmong patients hospitalised with a delta variant SARS-CoV-2 infection, vaccination was associated with less severe forms, even in the presence of comorbidities.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Michele Lai", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" - }, - { - "author_name": "Veronica La Rocca", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" - }, - { - "author_name": "Rachele Amato", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" - }, - { - "author_name": "Elena Iacono", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" - }, - { - "author_name": "carolina filipponi", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Olivier Epaulard", + "author_inst": "CHU Grenoble-Alpes, Grenoble, France" }, { - "author_name": "Elisa Catelli", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Sophie Abgrall", + "author_inst": "Hopital Beclere, APHP, France" }, { - "author_name": "Lucia Bogani", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Maeva Lefebvre", + "author_inst": "CHU de Nantes, Nantes, France" }, { - "author_name": "Rossella Fonnesu", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Jean-Francois Faucher", + "author_inst": "CHU de Limoges, Limoges, France" }, { - "author_name": "giulia lottini", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Jocelyn Michon", + "author_inst": "CHU de Caen, Caen, France" }, { - "author_name": "Alessandro De Carli", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Emilia Frentiu", + "author_inst": "CHU de Nancy, Nancy, France" }, { - "author_name": "Alessandro Mengozzi", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Cecile Janssen", + "author_inst": "CH Annecy-Genevois, Annecy, France" }, { - "author_name": "Stefano Masi", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Gabrielle Charbonnier", + "author_inst": "CHU Grenoble-Alpes, Grenoble, France" }, { - "author_name": "Paola Quaranta", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Audrey Fresse", + "author_inst": "CHU de Nancy, Nancy, France" }, { - "author_name": "Pietro Giorgio Spezia", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Simon Laurent", + "author_inst": "CHU de Caen, Caen, France" }, { - "author_name": "Giulia Freer", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Lena Sandjakian", + "author_inst": "CHU de Limoges, Limoges, France" }, { - "author_name": "Paola Lenzi", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Pierre Casez", + "author_inst": "CH Annecy-Genevois, Annecy, France" }, { - "author_name": "Francesco Fornai", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Aba Mahamat", + "author_inst": "CH Ajaccio, Ajaccio, France" }, { - "author_name": "Daniele Piomelli", - "author_inst": "University of California Irvine" - }, - { - "author_name": "Mauro Pistello", - "author_inst": "University of Pisa School of Medicine and Surgery: Universita degli Studi di Pisa" + "author_name": "Guillaume Beraud", + "author_inst": "CHU de Poitiers, Poitiers, France" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.02.08.22270465", @@ -414738,43 +414697,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.02.07.22270596", - "rel_title": "Role of Covid vaccine in determining ICU admission and death due to Covid -19 in Tamil Nadu", + "rel_doi": "10.1101/2022.02.07.22270557", + "rel_title": "History of SARS-CoV-2 infection, anti-spike IgG antibody kinetics and neutralization capacities following the second and third dose of BNT162b2 vaccine in nursing home residents", "rel_date": "2022-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.07.22270596", - "rel_abs": "COVID-19 pandemic threatened the world in terms of its rapid spread, strain on health infrastructure and many people lost their lives due to COVID. Mass Vaccination of public against Covid-19 were done with the notion that it protects against the severe form of the disease and death due to Covid-19. Covid vaccination was rolled out in Tamil Nadu from 16th January 2021 in a phased manner. This study was done using secondary data to assess the role of COVID vaccination in preventing ICU admission and death due to Covid-19 in Tamil Nadu for the period of August - December 2021. Unvaccinated individuals contributed to a higher proportion of hospitalization (60.9%) and ICU admission (65.5%) among Covid-19 infected during this period. Similarly, among patients who died due to Covid-19, 75.5% were unvaccinated. Odds of ICU admission and death among unvaccinated was 2.01 and 3.19 - times higher compared to fully vaccinated individuals infected with Covid-19. Unvaccinated Covid-19 patients had 2.73- and 1.46- times increased odds of dying and ICU admission respectively, compared to partially vaccinated. Population Attributable Risk showed that receiving at least one dose of vaccine could have reduced the mortality among Covid patients by 54% and ICU admission by 23.3%. This article emphasizes the need for vaccination against Covid-19 to reduce ICU admission and death among those infected with Covid-19.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.07.22270557", + "rel_abs": "ImportanceDuration of post-vaccination protection against COVID-19 in individuals is a critical issue, especially in nursing home (NH) residents, i.e. one of the most vulnerable populations.\n\nObjectiveTo estimate the duration of the IgG(S) response to the mRNA BNT162b2 vaccine in NH residents with (COV-Yes) or without (COV-No) history of natural infection with SARS-CoV-2.\n\nDesign, setting and participantsIgG(S) quantification was carried out at 3 different time periods following administration of the Pfizer BioNtech vaccine: three then seven months after the 2nd dose and one month after the 3rd dose. 574 COV-Yes and COV-No NH residents were included in 2 cohorts: Main (n=115, mean age 84 years) or Confirmatory (n=459, mean age 88 years).\n\nExposureAll subjects received the BNT162b2 vaccine.\n\nMain outcomes and measurementsIgG(S) antibodies and seroneutralization capacity.\n\nResultsNeutralization capacity was strongly correlated with IgG(S) levels (R2:76%) without any difference between COV-Yes and COV-No groups for the same levels of IgG(S). COV-Yes, compared to the COV-No subjects showed 5-fold and 15-fold higher IgG(S) titers 3 and 7 months after the 2nd dose, but less than 2-fold higher IgG(S) after the 3rd dose, due to a more pronounced effect of the 3rd dose in the COV-No group. These results were similar in both cohorts. After the 2nd dose, duration of assumed robust protection (IgG(S) >264 BAU/ml) was 2-fold higher in the COV-Yes vs. COV-No group: 12.60 (10.69-14.44) vs 5.76 (3.91-8.64) months, and this advantage was mainly due to the higher IgG(S) titers after the 2nd dose and secondary to a slower decay over time. After the 3rd dose, duration (months) of robust protection was estimated at 11.87 (9.88-14.87) (COV-Yes) and 8.95 (6.85-11.04) (COV-No).\n\nConclusions and relevanceIn old subjects living in NH, history of SARS-CoV-2 infection provides a clear advantage in the magnitude and duration of high IgG(S) titers following the 2nd dose. Importantly, the 3rd dose induces a much more pronounced IgG(S) response than the 2nd dose in COV-No subjects, the effect of which should be able to ensure in these subjects a prolonged protection against severe forms of COVID-19.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Selvavinayagam T.S", - "author_inst": "Directorate of Public Health and Preventive Medicine, Teynampet, Anna Salai, Chennai-06" + "author_name": "Helene Jeulin", + "author_inst": "Centre Hospitalier Regional Universitaire de Nancy/University of Lorraine" }, { - "author_name": "Parthipan Kumarasamy", - "author_inst": "Directorate of Public Health and Preventive Medicine, Teynampet, Chennai-06" + "author_name": "Carlos Labat", + "author_inst": "Inserm" }, { - "author_name": "sudharshini subramaniam", - "author_inst": "Madras Medical College" + "author_name": "Kevin Duarte", + "author_inst": "CHRU de Nancy" }, { - "author_name": "Somasundaram A", - "author_inst": "Institute of Community Medicine, Madras Medical College" + "author_name": "Simon Toupance", + "author_inst": "INSERM" }, { - "author_name": "Sampath P", - "author_inst": "Directorate of Public Health and Preventive Medicine, Teynampet, Chennai-06" + "author_name": "Gregoire Nadin", + "author_inst": "Sorbonne University" + }, + { + "author_name": "Denis Craus", + "author_inst": "Maison Medicale F-54110 Rosieres-aux-Salines," + }, + { + "author_name": "Ioannis Georgiopoulosh", + "author_inst": "CHRU de Nancy" + }, + { + "author_name": "Isabelle Gantois", + "author_inst": "CHRU de Nancy" }, { - "author_name": "Vinay Kumar Krishnamurthy", - "author_inst": "Directorate of Public Health and Preventive Medicine, Teynampet, Chennai -06" + "author_name": "Francois Goehringer", + "author_inst": "CHRU de Nancy" + }, + { + "author_name": "Athanase Benetos", + "author_inst": "Universite de Lorraine" } ], "version": "1", "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "geriatric medicine" }, { "rel_doi": "10.1101/2022.02.06.22270359", @@ -416768,109 +416743,77 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2022.02.06.22270482", - "rel_title": "Early genomic, epidemiological, and clinical description of the SARS-CoV-2 Omicron variant in Mexico City", + "rel_doi": "10.1101/2022.02.06.22270533", + "rel_title": "Comparable Neutralization of the SARS-CoV-2 Omicron BA.1 and BA.2 Variants", "rel_date": "2022-02-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.06.22270482", - "rel_abs": "BackgroundOmicron is the most mutated SARS-CoV-2 variant that has emerged, resulting in viral phenotype alterations, which can affect transmissibility, disease severity, and immune evasiveness. Genomic surveillance of a highly transmissible variant is important in cities with millions of inhabitants and an economic center such as Mexico City. In this work, we describe the early effects of the Omicron variant in Mexico City, exploring its genomic profile and clinical description.\n\nMethodologyWe sequenced SARS-CoV-2-positive samples in November and December 2021 and we using the public database GISAID. Haplotype and phylogenetic analyses were performed to genomically characterize Omicron. We used the Mexican federal database toexplore the association with clinical information such as symptoms and vaccination status.\n\nFindingsThe first case of Omicron was detected on November 16, 2022, and until December 31, 2021, we observed an increase from 88% in sequenced samples. Nineteen nonsynonymous mutations were found in the Omicron RBD, and we further explored the R346K substitution, which was prevalent in 42% of the samples and associated with immune escape by monoclonal antibodies. In the phylogenetic analysis, we found that there were several independent exchanges between Mexico and the world, and there was an event followed by local transmission that gave rise to most of the Omicron diversity in Mexico City. The haplotype analysis allowed us to observe that there was no association between haplotype and vaccination status. Of the patients with clinical data, 66% were vaccinated, none of the reported comorbidities were associated with Omicron, the presence of odynophagia and absence of dysgeusia were significant predictor symptoms for Omicron, and the Ct value on RT-qPCR was lower in Omicron.\n\nConclusionsGenomic surveillance in highly populated and fast-moving urban regions such as Mexico City is key to detecting the emergence and spread of SARS-CoV-2 variants in a timely manner, even weeks before the onset of an infection wave, to detect patterns that can inform public health decisions. It is also necessary to continue sequencing to detect the spread of any mutation that may affect the therapeutic efficacy or guide it.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.06.22270533", + "rel_abs": "The SARS-CoV-2 Omicron variant (B.1.1.529) has three major lineages BA.1, BA.2, and BA.31. BA.1 rapidly became dominant and has demonstrated substantial escape from neutralizing antibodies (NAbs) induced by vaccination2-4. BA.2 has recently increased in frequency in multiple regions of the world, suggesting that BA.2 has a selective advantage over BA.1. BA.1 and BA.2 share multiple common mutations, but both also have unique mutations1 (Fig. 1A). The ability of BA.2 to evade NAbs induced by vaccination or infection has not yet been reported. We evaluated WA1/2020, Omicron BA.1, and BA.2 NAbs in 24 individuals who were vaccinated and boosted with the mRNA BNT162b2 vaccine5 and in 8 individuals who were infected with SARS-CoV-2 (Table S1).\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=61 SRC=\"FIGDIR/small/22270533v1_fig1.gif\" ALT=\"Figure 1\">\nO_LINKSMALLFIG WIDTH=200 HEIGHT=79 SRC=\"FIGDIR/small/22270533v1_fig1a.gif\" ALT=\"Figure 1\">\nView larger version (26K):\norg.highwire.dtl.DTLVardef@1b39fc8org.highwire.dtl.DTLVardef@1bf16ceorg.highwire.dtl.DTLVardef@7248ecorg.highwire.dtl.DTLVardef@111a215_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Neutralizing antibody responses to Omicron BA.1 and BA.2. A. Cartoon showing BA.1 and BA.2 mutations in the SARS-CoV-2 Spike. NTD, N-terminal domain; RBD, receptor binding domain; RBM, receptor binding motif; SD1, subdomain 1; SD2, subdomain 2; FP, fusion peptide; HR1, heptad repeat 1; HR2, heptad repeat 2. B. Neutralizing antibody (NAb) titers by a luciferase-based pseudovirus neutralization assay in individuals two weeks following initial BNT162b2 vaccination (Prime), prior to boost (Pre-Boost), and two weeks following the third boost with BNT162b2 (Boost). C. NAb titers in 8 individuals following infection with SARS-CoV-2 Omicron BA.1, of whom 7 were vaccinated. The individual with negative NAb titers was unvaccinated and was sampled 4 days following diagnosis and hospitalization with severe COVID-19 pneumonia. Responses were measured against the SARS-CoV-2 WA1/2020, Omicron BA.1, and BA.2 variants. Medians (red bars) are depicted and shown numerically with fold differences.\n\nC_FIG O_TBL View this table:\norg.highwire.dtl.DTLVardef@a84ecborg.highwire.dtl.DTLVardef@1cd2d42org.highwire.dtl.DTLVardef@1567410org.highwire.dtl.DTLVardef@ddcf54org.highwire.dtl.DTLVardef@56b617_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable S1.C_FLOATNO O_TABLECAPTIONStudy population.\n\nC_TABLECAPTION C_TBL", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Alberto Cedro-Tanda", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Laura Gomez-Romero", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Guillermo de Anda-Jauregui", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Dora Garnica-Lopez", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Yair Alfaro-Mora", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Sonia Sanchez-Xochipa", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Eulices F Garcia-Garcia", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Alfredo Mendoza-Vargas", - "author_inst": "Instituto Nacional de Medicina Genomica" - }, - { - "author_name": "Emmanuel J Frias-Jimenez", - "author_inst": "Instituto Nacional de Medicina Genomica" + "author_name": "Jingyou Yu", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Bernardo Moreno-Quiroga", - "author_inst": "Instituto Nacional de Medicina Genomica" + "author_name": "Ai-ris Collier", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Abraham Campos-Romero", - "author_inst": "Innovation and Research Department, Salud Digna" + "author_name": "Marjorie Rowe", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Jose L Moreno-Camacho", - "author_inst": "Clinical Laboratory Division, Salud Digna," + "author_name": "Fatima Mardas", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Jonathan Alcantar-Fernandez", - "author_inst": "Innovation and Research Department, Salud Digna" + "author_name": "John Ventura", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Jesus Ortiz-Ramirez", - "author_inst": "Hospital General Ajusco Medio" + "author_name": "Huahua Wan", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Mariana Benitez Gonzalez", - "author_inst": "Hospital General Ajusco Medio" + "author_name": "Jessica Miller", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Roxana Trejo-Gonzalez", - "author_inst": "Centro Medico ABC" + "author_name": "Olivia Powers", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Daniel Aguirre-Chavarria", - "author_inst": "Centro Medico ABC" + "author_name": "Benjamin Chung", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Marcela E Nunez-Martinez", - "author_inst": "Centro Medico ABC" + "author_name": "Mazuba Siamatu", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Laura Uribe-Figueroa", - "author_inst": "Laboratorio Arion Genetica" + "author_name": "Nicole Hachmann", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Ofelia Angulo", - "author_inst": "Secretaria de Educacion, Ciencia, Tecnologia e Innovacion de la Ciudad de Mexico" + "author_name": "Nehalee Surve", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Rosaura Ruiz", - "author_inst": "Secretaria de Educacion, Ciencia, Tecnologia e Innovacion de la Ciudad de Mexico" + "author_name": "Felix Nampanya", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Alfredo Hidalgo-Miranda", - "author_inst": "Instituto Nacional de Medicina Genomica" + "author_name": "Abishek Chandrashekar", + "author_inst": "Beth Israel Deaconess Medical Center" }, { - "author_name": "Luis A Herrera", - "author_inst": "Instituto Nacional de Medicina Genomica" + "author_name": "Dan H. Barouch", + "author_inst": "Beth Israel Deaconess Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -419094,99 +419037,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.05.22269021", - "rel_title": "Wastewater Surveillance of U.S. Coast Guard Installations and Seagoing Military Vessels to Mitigate the Risk of COVID-19 Outbreaks", + "rel_doi": "10.1101/2022.02.04.22270479", + "rel_title": "Comparative effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections: A time-varying cohort analysis using trial emulation in the Virus Watch community cohort", "rel_date": "2022-02-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.05.22269021", - "rel_abs": "Military training centers may be high risk environments for the spread of disease such as COVID-19. Individuals arrive after traveling from many parts of the country, live in communal settings, and undergo high-interaction training. A pilot study of wastewater testing was initiated in February, 2021 to determine its feasibility as a sentinel surveillance tool in the U.S. Coast Guard for SARS-CoV-2. Wastewater was analyzed for the presence of two viral genes, N and E, and quantified relative to levels of a fecal indicator virus, Pepper Mild Mottle Virus (PMMoV). A stability control, Bovine Syncytial Respiratory Virus vaccine, was added to samples to assess sample stability and degradation. Wastewater data was validated by comparison with concomitant screening and surveillance programs that identified asymptomatic individuals infected with SARS-CoV-2 by diagnostic testing at on site medical clinics using PCR. Elevated levels of SARS-CoV-2 in wastewater were frequently associated with diagnosed cases, and in several instances, led to screenings of asymptomatic individuals that identified infected personnel, mitigating the risk of spread of disease. Wastewater screening also successfully indicated the presence of breakthrough cases in vaccinated individuals. A method for assessing blackwater from Coast Guard vessels was also developed, allowing detection of SARS-CoV-2 virus in shipboard populations. In one instance, virus was detected in the blackwater four weeks following the diagnosis of a single person on a Coast Guard cutter. These data show that wastewater testing is an effective tool for measuring the presence and prevalence of SARS-CoV-2 in military populations so that mitigation can occur and suggest other diseases may be assessed similarly. As a result, the Coast Guard has established three laboratories with wastewater testing capability at strategic locations and is actively continuing its wastewater testing program.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.04.22270479", + "rel_abs": "ImportanceThe Omicron (B.1.1.529) variant has increased SARs-CoV-2 infections in double vaccinated individuals globally, particularly in ChAdOx1 recipients. To tackle rising infections, the UK accelerated booster vaccination programmes used mRNA vaccines irrespective of an individuals primary course vaccine type with booster doses rolled out according to clinical priority. There is limited understanding of the effectiveness of different primary vaccination courses on mRNA based booster vaccines against SARs-COV-2 infections and how time-varying confounders can impact the evaluations comparing different vaccines as primary courses for mRNA boosters.\n\nObjectiveTo evaluate the comparative effectiveness of ChAdOx1 versus BNT162b2 as primary doses against SARs-CoV-2 in booster vaccine recipients whilst accounting for time-varying confounders.\n\nDesignTrial emulation was used to reduce time-varying confounding-by-indication driven by prioritising booster vaccines based upon age, vulnerability and exposure status e.g. healthcare worker. Trial emulation was conducted by meta-analysing eight cohort results whose booster vaccinations were staggered between 16/09/2021 to 05/01/2022 and followed until 23/01/2022. Time from booster vaccination until SARS-CoV-2 infection, loss of follow-up or end-of-study was modelled using Cox proportional hazards models for each cohort and adjusted for age, sex, minority ethnic status, clinically vulnerability, and deprivation.\n\nSettingProspective observational study using the Virus Watch community cohort in England and Wales.\n\nParticipantsPeople over the age of 18 years who had their booster vaccination between 16/09/2021 to 05/01/2022 without prior natural immunity.\n\nExposuresChAdOx1 versus BNT162b2 as a primary dose, and an mRNA booster vaccine.\n\nResultsAcross eight cohorts, 19,692 mRNA vaccine boosted participants were analysed with 12,036 ChAdOx1 and 7,656 BNT162b2 primary courses with a median follow-up time of 73 days (IQR:54-90). Median age, clinical vulnerability status and infection rates fluctuate through time. 7.2% (n=864) of boosted adults with ChAdOx1 primary course experienced a SARS-CoV-2 infection compared to 7.6% (n=582) of those with BNT162b2 primary course during follow-up. The pooled adjusted hazard ratio was 0.99 [95%CI:0.88-1.11], demonstrating no difference between the incidence of SARs-CoV-2 infections based upon the primary vaccine course.\n\nConclusion and RelevanceIn mRNA boosted individuals, we found no difference in protection comparing those with a primary course of BNT162b2 to those with aChAdOx1 primary course. This contrasts with pre-booster findings where previous research shows greater effectiveness of BNT162b2 than ChAdOx1 in preventing infection.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Gregory J Hall", - "author_inst": "U.S. Coast Guard Academy" - }, - { - "author_name": "Eric J Page", - "author_inst": "U.S. Coast Guard Academy" - }, - { - "author_name": "Min Rhee", - "author_inst": "U.S. Coast Guard Academy" - }, - { - "author_name": "Clara M Hay", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Vincent Nguyen", + "author_inst": "University College London" }, { - "author_name": "Amelia Krause", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Alexei Yavlinsky", + "author_inst": "University College London" }, { - "author_name": "Emma Langenbacher", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Sarah Beale", + "author_inst": "University College London" }, { - "author_name": "Allison Ruth", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Susan J Hoskins", + "author_inst": "Univerity College London" }, { - "author_name": "Stephen Grenier", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Vasileios J Lampos", + "author_inst": "University College London" }, { - "author_name": "Alexander P Duran", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Isobel Braithwaite", + "author_inst": "University College London" }, { - "author_name": "Ibrahim Kamara", - "author_inst": "U.S. Coast Guard" + "author_name": "Thomas Edward Byrne", + "author_inst": "University College London" }, { - "author_name": "John K Iskander", - "author_inst": "U.S. Coast Guard" + "author_name": "Wing Lam Erica Fong", + "author_inst": "University College London, London School of Hygiene &Tropical Medicine" }, { - "author_name": "Dana L Thomas", - "author_inst": "U.S. Coast Guard" + "author_name": "Ellen Fragaszy", + "author_inst": "UCL, London School of Hygiene & Tropical Medicine" }, { - "author_name": "Edward Bock", - "author_inst": "U.S. Coast Guard" + "author_name": "Cyril Geismar", + "author_inst": "University College London" }, { - "author_name": "Nicholas Porta", - "author_inst": "U.S. Coast Guard" + "author_name": "Jana Kovar", + "author_inst": "University College London" }, { - "author_name": "Jessica Pharo", - "author_inst": "U.S. Coast Guard" + "author_name": "Annalan Mathew Dwight Navaratnam", + "author_inst": "University College London" }, { - "author_name": "Beth A. Osterink", - "author_inst": "U.S. Coast Guard" + "author_name": "Parth Patel", + "author_inst": "University College London" }, { - "author_name": "Sharon Zelmanowitz", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Madhumita Shrotri", + "author_inst": "Univeristy College London" }, { - "author_name": "Corinna Fleischmann", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Sophie Weber", + "author_inst": "University College London" }, { - "author_name": "Dilhara Liyanage", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Andrew Hayward", + "author_inst": "University College London" }, { - "author_name": "Joshua P Gray", - "author_inst": "U.S. Coast Guard Academy" + "author_name": "Robert W Aldridge", + "author_inst": "University College London" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.02.04.22270120", @@ -421100,59 +421031,47 @@ "category": "dentistry and oral medicine" }, { - "rel_doi": "10.1101/2022.02.02.22269952", - "rel_title": "Serious hospital events following symptomatic infection with Sars-CoV-2 Omicron and Delta variants: an exposed-unexposed cohort study in December 2021 from the COVID-19 surveillance databases in France", + "rel_doi": "10.1101/2022.02.02.22270222", + "rel_title": "Pediatric Croup during the COVID-19 Omicron Variant Surge", "rel_date": "2022-02-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.02.22269952", - "rel_abs": "BackgroundA rapid increase in incidence of the SARS-CoV-2 Omicron variant occurred in France in December 2021, while the Delta variant was prevailing since July 2021. We aimed to determine whether the risk of a severe hospital event following symptomatic SARS-CoV-2 infection differs for Omicron versus Delta.\n\nMethodsWe conducted a retrospective cohort study to compare severe hospital events (admission to intensive care unit or death) between Omicron and Delta symptomatic cases matched according to week of virological diagnosis and age. The analysis was adjusted for age, sex, vaccination status, presence of comorbidities and region of residence, using Cox proportional hazards model.\n\nFindingsBetween 06/12/2021-28/01/2022, 184 364 cases were included, of which 931 had a severe hospital event (822 Delta, 109 Omicron). The risk of severe event was lower among Omicron versus Delta cases; the difference in severity between the two variants decreased with age (aHR=0{middle dot}11 95%CI: 0{middle dot}07-0{middle dot}17 among 40-64 years, aHR=0{middle dot}51 95%CI: 0{middle dot}26-1{middle dot}01 among 80+ years). The risk of severe event increased with the presence of comorbidities (for very-high-risk comorbidity, aHR=4{middle dot}18 95%CI: 2{middle dot}88-6{middle dot}06 among 40-64 years) and in males (aHR=2{middle dot}29 95%CI: 1{middle dot}83-2{middle dot}86 among 40-64 years) and was higher in unvaccinated compared to primo-vaccinated (aHR=6{middle dot}90 95%CI: 5{middle dot}26-9{middle dot}05 among 40-64 years). A booster dose reduced the risk of severe hospital event in 80+ years infected with Omicron (aHR=0{middle dot}27; 95%CI: 0{middle dot}11-0{middle dot}65).\n\nInterpretationThis study confirms the lower severity of Omicron compared to Delta. However, the difference in disease severity is less marked in the elderly.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.02.22270222", + "rel_abs": "Croup is a common upper respiratory disease usually associated with parainfluenza virus, resulting in stridor, hoarse voice, barky cough, and variable respiratory distress. Here we examine the data at our center confirming a sharp increase in cases of croup associated with the Omicron variant. Data was retrospectively extracted from patient charts among those seen in the Emergency Department at Seattle Childrens Hospital. Inclusion criteria were patients who were assigned a diagnosis containing \"croup\" during either 5/30/2021-11/30/2021, a time period correlating with predominance of the COVID-19 Delta variant (B.1.617.2), or the initial phase of the Omicron variant surge (12/1/2021-1/15/2022). Contemporaneous publicly available local data on the proportion of SARS-CoV-2 samples in surrounding King County, Washington, with spike gene target failure on TaqPath PCR assays was used as a proxy for the proportion of infections caused by the Omicron variant. A total of 401 patients were diagnosed with croup during the Delta surge and 107 patients were diagnosed with croup during the Omicron surge. Patients who presented during the Omicron surge were more likely to test positive for COVID-19 (48.2% vs 2.8%, p < 0.0001). Children with a clinical diagnosis of croup during the Omicron surge were more likely to be prescribed racemic epinephrine as part of their care (21.5% vs 13.0%, p = 0.032). There were no differences in presenting age, rate of admission, rate of return to the ED within 72 hours, or admission among those who returned within 72 hours. During the Omicron surge, the incidence of croup nearly doubled compared to the rate in prior months, while at the same time the number of cases of parainfluenza virus identified decreased. Consistent with prior case reports, we have identified a sharp rise in cases of croup seen in our pediatric ED in parallel with the replacement of the SARS-CoV-2 Delta variant by Omicron as the dominant variant in our community.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Vincent Auvigne", - "author_inst": "Sante publique France" - }, - { - "author_name": "Sophie Vaux", - "author_inst": "Sante publique France" - }, - { - "author_name": "Yann Le Strat", - "author_inst": "Sante publique France" - }, - { - "author_name": "Justine Schaeffer", - "author_inst": "Sante publique France" + "author_name": "Emine M Tunc", + "author_inst": "University of Washington" }, { - "author_name": "Lucie Fournier", - "author_inst": "Sante publique France" + "author_name": "Cassandra Koid Jia Shin", + "author_inst": "University of Washington" }, { - "author_name": "Cynthia Tamandjou", - "author_inst": "Sante publique France" + "author_name": "Etiowo Usoro", + "author_inst": "Seattle Children's Hospital" }, { - "author_name": "Charline Montagnat", - "author_inst": "Sully" + "author_name": "Siobhan E Thomas-Smith", + "author_inst": "University of Washington" }, { - "author_name": "Bruno Coignard", - "author_inst": "Sante publique France" + "author_name": "Indi Trehan", + "author_inst": "University of Washington" }, { - "author_name": "Daniel Levy-Bruhl", - "author_inst": "Sante publique France" + "author_name": "Russell T Migita", + "author_inst": "University of Washington" }, { - "author_name": "Isabelle Parent du Chatelet", - "author_inst": "Sante publique France" + "author_name": "Ashley E Keilman", + "author_inst": "University of Washington" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pediatrics" }, { "rel_doi": "10.1101/2022.02.02.22270298", @@ -423062,77 +422981,101 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.02.01.22270285", - "rel_title": "Association study of HLA with the kinetics of SARS-CoV-2 spike specific IgG antibody responses to BNT162b2 mRNA vaccine", + "rel_doi": "10.1101/2022.01.29.22270016", + "rel_title": "Exposing and Overcoming Limitations of Clinical Laboratory Tests in COVID-19 by Adding Immunological Parameters", "rel_date": "2022-02-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.02.01.22270285", - "rel_abs": "BNT162b2, an mRNA-based SARS-CoV-2 vaccine (Pfizer-BioNTech), is one of the most effective COVID-19 vaccines and has been approved by more than 130 countries worldwide. However, several studies have reported that the COVID-19 vaccine shows high interpersonal variability in terms of humoral and cellular responses, such as those with respect to SARS-CoV-2 spike protein immunoglobulin (Ig)G, IgA, IgM, neutralizing antibodies, and CD4+ & CD8+ T cells. The objective of this study is to investigate the kinetic changes in anti-SARS-CoV-2 spike IgG (IgG-S) profiles and adverse reactions and their associations with HLA profiles among 100 hospital workers from the Center Hospital of the National Center for Global Health and Medicine (NCGM), Tokyo, Japan. DQA1*03:03:01 (P = 0.017; Odd ratio (OR) 2.80, 95%Confidence interval (CI) 1.05-7.25) was significantly associated with higher IgG-S production after two doses of BNT162b2 while DQB1*06:01:01:01 (P = 0.028, OR 0.27, 95%CI 0.05-0.94) was significantly associated with IgG-S declines after two doses of BNT162b2. No HLA alleles were significantly associated with either local symptoms or fever. However, C*12:02:02 (P = 0.058; OR 0.42, 95%CI 0.15-1.16), B*52:01:01 (P = 0.031; OR 0.38, 95%CI 0.14-1.03), DQA1*03:02:01 (P = 0.028; OR 0.39, 95%CI 0.15-1.00) and DPB1*02:01:02 (P = 0.024; OR 0.45, 95%CI 0.21-0.97) appeared significantly associated with protection against systemic symptoms after two doses of BNT162b2 vaccination. Further studies with larger sample sizes are clearly warranted to determine HLA allele associations with the production and long-term sustainability of IgG-S after COVID-19 vaccination.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.29.22270016", + "rel_abs": "BackgroundAlmost two years since the onset of the COVID-19 pandemic no predictive algorithm has been generally adopted, nor new tests identified to improve the prediction and management of SARS-CoV-2 infection.\n\nMethodsRetrospective observational analysis of the predictive performance of clinical parameters and laboratory tests in hospitalised patients with COVID-19. Outcomes were 28-day survival and maximal severity in a cohort of 1,579 patients and two validation cohorts of 598 and 434 patients. A pilot study conducted in a patient subgroup measured 17 cytokines and 27 lymphocyte phenotypes to explore additional predictive laboratory tests.\n\nFindings1) Despite a strong association of 22 clinical and laboratory variables with the outcomes, their joint prediction power was limited due to redundancy. 2) Eight variables: age, comorbidity index, oxygen saturation to fraction of inspired oxygen ratio, neutrophil-lymphocyte ratio, C-reactive protein, aspartate aminotransferase/alanine aminotransferase ratio, fibrinogen, and glomerular filtration rate captured most of the statistical predictive power. 3) The interpretation of clinical and laboratory variables was improved by grouping them in categories. 4) Age and organ damage-related tests were the best predictors of survival, and inflammatory-related tests were the best predictors of severity. 5) The pilot study identified several immunological tests (including chemokine ligand 10, chemokine ligand 2, and interleukin 1 receptor antagonist), that performed better than currently used tests.\n\nConclusionsCurrently used tests for clinical management of COVID-19 patients are of limited predictive value due to redundancy, as all measure aspects of two major processes: inflammation, and organ damage. There are no independent predictors based on the quality of the nascent adaptive immune response. Understanding the limitations of current tests would improve their interpretation and simplify clinical management protocols. A systematic search for better biomarkers is urgent and feasible.\n\nThis study was funded by Instituto de Salud Carlos III, Madrid, Spain, grants COV20/00416, Cov20/00654 and COV20/00388 to R.P-B, ATS and JBM respectively and co-financed by the European Regional Development Fund (ERDF). DA-S is recipient of a doctoral fellowship from the Vall dHebron Research Institute, Barcelona, Spain. ASM was supported by a postdoctoral grant \"Juan Rodes\" (JR18/00022) from Instituto de Salud Carlos III through the Ministry of Economy and Competitiveness, Spain", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Seik-Soon Khor", - "author_inst": "Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Adrian Sanchez-Montalva", + "author_inst": "Infectious Disease Department, Hospital Universitari Vall Hebron; International Health Programme Institut Catala de la Salut, Vall Hebron Research, Institute (V" }, { - "author_name": "Yosuke Omae", - "author_inst": "Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Daniel Alvarez-Sierra", + "author_inst": "Translational Immunology Research Group, Vall Hebron Research Institute (VHIR), Campus Valle Hebron, Barcelona, Spain." }, { - "author_name": "Junko S. Takeuchi", - "author_inst": "Department of Academic-Industrial Partnerships Promotion, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Monica Martinez-Gallo", + "author_inst": "Immunology Department, Hospital Universitari Vall Hebron; Traslational Immunology Research Group, Vall Hebron Research Institute (VHIR); Department of Cell Biol" }, { - "author_name": "Ami Fukunaga", - "author_inst": "Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Janire Perurena-Prieto", + "author_inst": "Immunology Department, Hospital Universitari Vall Hebron; Department of Cell Biology, Physiology and Immunology, Universitat Autonoma de Barcelona, Campus Vall " }, { - "author_name": "Shohei Yamamoto", - "author_inst": "Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Iria Arrese-Munoz", + "author_inst": "Immunology Department, Hospital Universitario Valle Hebron; Campus Vall Hebron, Barcelona, Spain." }, { - "author_name": "Akihito Tanaka", - "author_inst": "Department of Laboratory Testing, Center Hospital of the National Center for the Global Health and Medicine, Tokyo, Japan" + "author_name": "Juan Carlos Ruiz-Rodriguez", + "author_inst": "Intensive Medicine Department, Valle Hebron University Hospital; Shock, Organ Dysfunction and Resuscitation Research Group, Vall Hebron Research Institute (VHIR" }, { - "author_name": "Kouki Matsuda", - "author_inst": "Department of Refractory Viral Infection, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Juan Espinosa-Pereiro", + "author_inst": "Infectious Disease Department, Hospital Universitari Vall Hebron; International Health Programme Institut Catala de la Salut, Vall Hebron Research, Institute (V" }, { - "author_name": "Moto Kimura", - "author_inst": "Department of Academic-Industrial Partnerships Promotion, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Pau Bosch-Nicolau", + "author_inst": "Infectious Disease Department, Hospital Universitari Vall Hebron; International Health Programme Institut Catala de la Salut, Vall Hebron Research, Institute (V" }, { - "author_name": "Kenji Maeda", - "author_inst": "Department of Refractory Viral Infection, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Xavier Martinez-Gomez", + "author_inst": "Epidemiology & Pub Health Department, Hospital Universitari Vall Hebron; Epidemiology & Pub Health Group, Vall Hebron Research Institute (VHIR); Dept of Pediatr" }, { - "author_name": "Gohzoh Ueda", - "author_inst": "Division of Core Diagnostics, Abbott Japan LLC, Tokyo, Japan" + "author_name": "Andres Anton", + "author_inst": "Microbiology Dept, Hospital Universitari Vall Hebron; Microbiology Research Group, Valle Hebron Research Institute (VHIR); Department of Genetics and Microbiolo" }, { - "author_name": "Tetsuya Mizoue", - "author_inst": "Department of Epidemiology and Prevention, Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Ferran Martinez-Valle", + "author_inst": "Department Internal Medicine, Hospital Universitari Vall Hebron; Systemic Disease Research Group, Valle Hebron Research Institute (VHIR); Department Medicine, U" }, { - "author_name": "Mugen Ujiie", - "author_inst": "Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Mar Riveiro-Barciela", + "author_inst": "Liver Unit, Department Internal Medicine, Hospital Universitari Vall Hebron; Liver Disease Research Group, Valle Hebron Research Institute (VHIR); Department M" }, { - "author_name": "Hiroaki Mitsuya", - "author_inst": "Department of Refractory Viral Infection, Research Institute, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Francisco Rodriguez-Frias", + "author_inst": "Division Biochemistry,, Clinical Laboratory Department, Hospital Universitari Vall Hebron; Liver Disease Research Group, Valle Hebron Research Institute (VHIR);" }, { - "author_name": "Norio Ohmagari", - "author_inst": "Disease Control and Prevention Center, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Pol Castellano-Escuder", + "author_inst": "Bioinformatics and Statistics Group, University of Barcelona, Barcelona, Spain" }, { - "author_name": "Wataru Sugiura", - "author_inst": "Center for Clinical Sciences, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Elisabet Poyatos-Canton", + "author_inst": "Department Immunology, Hospital Universitari Bellvige, Hospitalet de Llobregat, Barcelona, Spain" }, { - "author_name": "Katsushi Tokunaga", - "author_inst": "Genome Medical Science Project, National Center for Global Health and Medicine, Tokyo, Japan" + "author_name": "Jordi Bas-Minguet", + "author_inst": "Department Immunology, Hospital Universitari Bellvige, Hospitalet de Llobregat, Barcelona, Spain" + }, + { + "author_name": "Eva Maria Martinez-Caceres", + "author_inst": "Immunology Department, Hospital Universitari Germans Trias Pujol; Immunology Research Group, Germans Trias Pujol Health Sciencies Institute, Badalona, Departmen" + }, + { + "author_name": "Alex Sanchez-Pla", + "author_inst": "Statistics and Bioinformatics Unit, Vall Hebron Research Institute (VHIR); Bioinformatics and Statistics Group, University of Barcelona, Barcelona, Spain." + }, + { + "author_name": "Coral Zurera-Egea", + "author_inst": "Immunology Group, Health Sciences Research Institute, Germans Trias i Pujol (IGTP), Badalona, Barcelona, Spain" + }, + { + "author_name": "Aina Teniente-Serra", + "author_inst": "Immunology Department, Hospital Universitari Germans Trias Pujol; Immunology Group, Health Sciences Research Institute Germans Trias Pujol (IGPT), Badalona; D" + }, + { + "author_name": "Manuel Hernandez-Gonzalez", + "author_inst": "Department Immunology, Hospital Universitari Vall Hebron; Translational Immunology Research Group, Vall Hebron Research Institute (VHIR); Department of Cell Bio" + }, + { + "author_name": "Ricardo Pujol Borrell", + "author_inst": "Department Immunology, Hospital Universitari Vall Hebron; Translational Immunology Research Group, Vall Hebron Research Institute (VHIR); Department of Cell Bio" } ], "version": "1", @@ -424776,31 +424719,71 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2022.01.30.478380", - "rel_title": "Using Unassigned NMR Chemical Shifts to Model RNA Secondary Structure", + "rel_doi": "10.1101/2022.01.31.478476", + "rel_title": "SARS-CoV-2 invades cognitive centers of the brain and induces Alzheimer's-like neuropathology", "rel_date": "2022-02-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.30.478380", - "rel_abs": "NMR-derived chemical shifts are sensitive probes of RNA structure. However, the need to assign NMR spectra hampers their utility as a direct source of structural information. In this report, we describe a simple method that uses unassigned 2D NMR spectra to model the secondary structure of RNAs. Similar to assigned chemical shifts, we could use unassigned chemical shift data to reweight conformational libraries such that the highest weighted structure closely resembles their reference NMR structure. Furthermore, the application of our approach to the 3- and 5-UTR of the SARS-CoV-2 genome yields structures that are, for the most part, consistent with the secondary structure models derived from chemical probing data. Therefore, we expect the framework we describe here will be useful as a general strategy for rapidly generating preliminary structural RNA models directly from unassigned 2D NMR spectra. As we demonstrated for the 337-nt and 472-nt UTRs of SARS-CoV-2, our approach could be especially valuable for modeling the secondary structures of large RNA.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.31.478476", + "rel_abs": "The neurotropism of SARS-CoV-2 and the phenotypes of infected neurons are still in debate. Long COVID manifests with \"brain diseases\" and the cause of these brain dysfunction is mysterious. Here, we analyze 34 age- and underlying disease-matched COVID-19 or non-COVID-19 human brains. SARS-CoV-2 RNA, nucleocapsid, and spike proteins are present in neurons of the cognitive centers of all COVID-19 patients, with its non-structural protein NSF2 detected in adult cases but not in the infant case, indicating viral replications in mature neurons. In adult COVID-19 patients without underlying neurodegeneration, SARS-CoV-2 infection triggers A{beta} and p-tau deposition, degenerating neurons, microglia activation, and increased cytokine, in some cases with A{beta} plaques and p-tau pretangles. The number of SARS-CoV-2+ cells is higher in patients with neurodegenerative diseases than in those without such conditions. SARS-CoV-2 further activates microglia and induces A{beta} and p-tau deposits in non-Alzheimers neurodegenerative disease patients. SARS-CoV-2 infects mature neurons derived from inducible pluripotent stem cells from healthy and Alzheimers disease (AD) individuals through its receptor ACE2 and facilitator neuropilin-1. SARS-CoV-2 triggers AD-like gene programs in healthy neurons and exacerbates AD neuropathology. An AD infectious etiology gene signature is identified through SARS-CoV-2 infection and silencing the top three downregulated genes in human primary neurons recapitulates the neurodegenerative phenotypes of SARS-CoV-2. Thus, our data suggest that SARS-CoV-2 invades the brain and activates an AD-like program.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Neel Moudgal", - "author_inst": "Saline High School" + "author_name": "Wei-Bin Shen", + "author_inst": "University of Maryland School of medicine" }, { - "author_name": "Grace Arhin", - "author_inst": "University of Michigan" + "author_name": "Montasir Elahi", + "author_inst": "University of Maryland School of Medicine" }, { - "author_name": "Aaron Terrence Frank", - "author_inst": "University of Michigan" + "author_name": "James Logue", + "author_inst": "University of Maryland School of Medicine" + }, + { + "author_name": "Penghua Yang", + "author_inst": "University of Maryland School of Medicine" + }, + { + "author_name": "Lauren Baracco", + "author_inst": "University of Maryland School of Medicine" + }, + { + "author_name": "E. Albert Reece", + "author_inst": "University of Maryland Baltimore" + }, + { + "author_name": "BingBing Wang", + "author_inst": "University of Maryland School of Medicine" + }, + { + "author_name": "Ling Li", + "author_inst": "University of Maryland School of Medicine" + }, + { + "author_name": "Thomas Blanchard", + "author_inst": "University of Maryland School of Medicine" + }, + { + "author_name": "Zhe Han", + "author_inst": "University of Maryland School of Medicine" + }, + { + "author_name": "Matthew Frieman", + "author_inst": "University of Maryland School of Medicine" + }, + { + "author_name": "Robert A. Rissman", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Peixin Yang", + "author_inst": "University of Maryland School of Medicine" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "biophysics" + "category": "neuroscience" }, { "rel_doi": "10.1101/2022.01.30.478400", @@ -426750,35 +426733,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.01.29.22269971", - "rel_title": "Estimating COVID-19 Vaccination Effectiveness Using Electronic Health Records of an Academic Medical Center in Michigan", + "rel_doi": "10.1101/2022.01.29.22270080", + "rel_title": "Are high urea values before intravenous immunoglobulin replacement a risk factor for COVID-related mortality?", "rel_date": "2022-01-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.29.22269971", - "rel_abs": "ImportanceSystematic characterization of the protective effect of vaccinations across time and at-risk populations is needed to inform public health guidelines and personalized interventions.\n\nObjectiveTo evaluate the vaccine effectiveness (VE) over time and determine differences across demographic and clinical risk factors of COVID-19.\n\nDesign, Setting, and ParticipantsThis test negative design consisted of adult patients who were tested or diagnosed for COVID-19 at Michigan Medicine in 2021. Variables extracted from Electronic Health Records included vaccination status, age, gender, race/ethnicity, comorbidities, body mass index, residential-level socioeconomic characteristics, past COVID-19 infection, being immunosuppressed, and health care worker status.\n\nExposureThe primary exposure was vaccination status and was categorized into fully vaccinated with and without booster, partially vaccinated, or unvaccinated.\n\nMain Outcomes and MeasuresThe main outcomes were infection with COVID-19 (positive test or diagnosis) and having severe COVID-19, i.e., either being hospitalized or deceased. Based on these, VE was calculated by quarter, vaccine, and patient characteristics.\n\nResultsOf 170,487 COVID-19 positive adult patients, 78,002 (45.8%) were unvaccinated, and 92,485 (54.2%) were vaccinated, among which 74,060 (80.1%) were fully vaccinated. COVID-19 positivity and severity rates were substantially higher among unvaccinated (12.1% and 1.4%, respectively) compared to fully vaccinated individuals (4.7% and 0.4%, respectively). Among 7,187 individuals with a booster, only 18 (0.3%) had a severe outcome. The covariate-adjusted VE against an infection was 62.1% (95%CI 60.3-63.8%), being highest in the Q2 of 2021 (90.9% [89.5-92.1%]), lowest in Q3 (60.1% [55.9-64.0%]), and rebounding in Q4 to 68.8% [66.3- 71.1%]). Similarly, VE against severe COVID-19 overall was 73.7% (69.6-77.3%) and remained high throughout 2021: 87.4% (58.1-96.3%), 92.2% (88.3-94.8%), 74.4% (64.8-81.5%) and 83.0% (78.8-86.4%), respectively. Data on fully vaccinated individuals from Q4 indicated additional protection against infection with an additional booster dose (VE-Susceptibility: 64.0% [61.1-66.7%] vs. 87.3% [85.0-89.2%]) and severe outcomes (VE-Severity: 78.8% [73.5-83.0%] vs. 94.0% [89.5-96.6%]). Comparisons between Pfizer-BioNTech and Moderna vaccines indicated similar protection against susceptibility (82.9% [80.7-84.9%] versus 88.1% [85.5- 90.2%]) and severity (87.1% [80.3-91.6%]) vs. (84.9% [76.2-90.5%]) after controlling for vaccination timing and other factors. There was no significant effect modification by all the factors we examined.\n\nConclusions and RelevanceOur findings suggest that COVID-19 vaccines offered high protection against infection and severe COVID-19, and showed decreasing effectiveness over time and improved protection with a booster.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSHow do the rates of COVID-19 outcomes (infections or mild/severe disease) compare across vaccination status and quarters of 2021, after adjusting for confounders?\n\nFindingsIn this cohort of 170,487 adult patients tested for or diagnosed with COVID-19 during 2021, both COVID-19 positivity and severity rates were substantially higher in unvaccinated compared to fully vaccinated individuals. Vaccine effectiveness estimation was adjusted for covariates potentially related to both being vaccinated and COVID-19 outcomes; this also allowed us to determine if effectiveness differed across patient subgroups. The estimated vaccine effectiveness across the four quarters of 2021 was 62.1% against infection and was 73.7% against severe COVID-19 (defined as hospitalization, ICU admission, or death). There was no significant effect modification by all the factors we examined.\n\nMeaningThese findings suggest COVID-19 vaccines had relatively high protection against infection and severe COVID-19 during 2021 for those who received two doses of an mRNA vaccine (Moderna or Pfizer-BioNTech) or one dose of the Janssen vaccine, of which the effectiveness decreased over time and improved with a booster.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.29.22270080", + "rel_abs": "ObjectiveSince the World Health Organization accepted The Coronavirus Disease 2019 (COVID-19) as a pandemic and there is still no effective treatment, it becomes crucial that the physicians interested in COVID-19 treatment share all the data they acquire, particularly in vulnerable patient groups, to reduce morbidity and mortality.\n\nMethodsThe study included 81 adult (Female: 27, Male: 54) COVID-19 patients who were hospitalized for the treatment of COVID-19 between April 2020 and September 2020 and were followed-up, treated and consulted in the immunology clinic for intravenous immunoglobulin (IVIG) treatment.\n\nResultsThe univariate analysis found that the number of days of hospitalization in service, being intubated, number of IVIG treatment days, and the urea value before IVIG treatment were independent risk factors for mortality (p:0.043, p:0.001, p:0.074, p:0.004, respectively). As a result of multivariate analysis, being intubated and urea value before IVIG treatment were found to be independent risk factors for mortality (p:0.001 and p:0.009).\n\nIt was found that for 60 mg/dL level of urea value before IVIG treatment, the sensitivity value for mortality in COVID-19 patients was 46.2%, and the specificity was 35.5% (p:0.029)\n\nConclusionThe study found that urea values before IVIG treatment were a risk factor for mortality in patients who received IVIG treatment for COVID-19. This is important as it indicates that BUN values should be closely monitored in patients given IVIG treatment for COVID-19. It also suggests that when resources are limited and risk stratification is required in COVID-19 patients, BUN values can be helpful.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Emily Roberts", - "author_inst": "University of Michigan" - }, - { - "author_name": "Tian Gu", - "author_inst": "University of Michigan" - }, - { - "author_name": "Bhramar Mukherjee", - "author_inst": "University of Michigan" + "author_name": "Gokhan Aytekin", + "author_inst": "Konya City Hospital" }, { - "author_name": "Lars G. Fritsche", - "author_inst": "University of Michigan School of Public Health" + "author_name": "EMEL ATAYIK", + "author_inst": "Konya City Hospital" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2022.01.30.22270133", @@ -428532,63 +428507,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.29.22270066", - "rel_title": "Evaluation of the systemic and mucosal immune response induced by COVID-19 and the BNT162b2 mRNA vaccine for SARS-CoV-2", + "rel_doi": "10.1101/2022.01.28.22269987", + "rel_title": "Genome surveillance of SARS-CoV-2 variants and their role in pathogenesis focusing on second wave of COVID-19 in India", "rel_date": "2022-01-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.29.22270066", - "rel_abs": "BackgroundCurrently used vaccines to protect from COVID-19 mostly focus on the receptor-binding domain (RBD) of the viral spike protein, and induced neutralizing antibodies have shown to be protective. However, functional relevance of vaccine-generated antibodies are poorly understood on variants-of-concern (VOCs) and mucosal immunity.\n\nMethodsWe compared specific antibody production against the S1 subunit and the RBD of the spike protein, the whole virion of SARS-CoV-2, and monitored neutralizing antibodies in sera and saliva of 104 BNT162b2 vaccinees and 57 individuals with natural SARS-CoV-2 infection. Furthermore, we included a small cohort of 11 individuals which received a heterologous ChAdOx1-S/BNT162b2 prime-boost vaccination.\n\nResultsVaccinated individuals showed higher S1-IgG antibodies in comparison to COVID-19 patients, followed by a significant decrease 3 months later. Neutralizing antibodies (nAbs) were poorly correlated with initial S1-IgG levels, indicating that these might largely be non-neutralizing. In contrast, RBD IgGAM was strongly correlated to nAbs, suggesting that RBD-IgGAM is a surrogate marker to estimate nAb concentrations after vaccination. The protective effect of vaccine- and infection-induced nAbs was found reduced towards B.1.617.2 and B.1.351 VOCs. NAb titers are significantly higher after third vaccination compared to second vaccination. In contrast to COVID-19 patients, no relevant levels of RBD specific antibodies were detected in saliva samples from vaccinees.\n\nConclusionsOur data demonstrate that BNT162b2 vaccinated individuals generate relevant neutralizing antibodies, which begin to decrease within three months after immunization and show lower neutralizing potential to VOCs as compared to the original Wuhan virus strain. A third booster vaccination provides a stronger nAb antibody response than the second vaccination. The systemic vaccine does not seem to elicit readily detectable mucosal immunity.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.28.22269987", + "rel_abs": "India had witnessed unprecedented surge in SARS-CoV-2 infections and the dire consequences during the second wave of COVID-19, but the detailed report of the epidemiological based spatiotemporal incidences of the disease is missing. Here in, we have applied various statistical methods like correlation, hierarchical clustering to know the pattern of pathogenesis of the circulating VoCs. B.1.617.1 (Kappa) was the predominant VoC during the early phase of second wave. Delta (B.1.617.2) or Delta-like (AY.x) VoC constitutes majority (>90.17) of the cases during the peak of second wave. The correlation plot showed Delta/Delta-like lineage is inversely correlated with other lineages including B.1.617.1 (kappa), B.1.1.7, B.1, B.1.36.29 and B.1.36. Delta/Delta-like surge coincided with second wave whereas all other lineages (B.1.617.1, B.1.36.29, etc.) occurred during the prior phase of the second wave. The spatiotemporal analysis showed that most of the Indian states were affected during the peak of the second wave due to delta surge and fall under the same cluster. The second cluster populated mostly by north-eastern states and islands of India were minimally affected. The presence of signature mutations (T478K, D950N, E156G) along with L452K, D614G and P681R within the spike protein of Delta or Delta-like might cause elevation in host cell attachment, increased transmission and altered antigenicity which in due course of time has replaced the other circulating variants. The timely assessment of new VoCs will provide a rationale for updating the diagnostic, vaccine development by medical industries and decision making by various agencies including government, educational institutions, and corporate industries.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Olaf Nickel", - "author_inst": "Klinikum Sankt Georg gGmbH Akademisches Lehrkrankenhaus der Universitat Leipzig: Klinikum Sankt Georg gGmbH" - }, - { - "author_name": "Alexandra Rockstroh", - "author_inst": "Fraunhofer Institute for Cell Therapy and Immunology IZI: Fraunhofer-Institut fur Zelltherapie und Immunologie IZI" - }, - { - "author_name": "Johannes Wolf", - "author_inst": "Klinikum Sankt Georg gGmbH Akademisches Lehrkrankenhaus der Universitat Leipzig: Klinikum Sankt Georg gGmbH" + "author_name": "Poulomi Sarkar", + "author_inst": "CSIR-Indian Institute of Chemical Biology, Translational Research Unit of Excellence" }, { - "author_name": "Susann Landgraf", - "author_inst": "Klinikum Sankt Georg gGmbH Akademisches Lehrkrankenhaus der Universitat Leipzig: Klinikum Sankt Georg gGmbH" + "author_name": "Sarthak Banerjee", + "author_inst": "CSIR-Indian Institute of Chemical Biology, Translational Research Unit of Excellence" }, { - "author_name": "Sven Kalbitz", - "author_inst": "Klinikum Sankt Georg gGmbH Akademisches Lehrkrankenhaus der Universitat Leipzig: Klinikum Sankt Georg gGmbH" + "author_name": "Sarbar Ali Saha", + "author_inst": "CSIR-Indian Institute of Chemical Biology, Translational Research Unit of Excellence" }, { - "author_name": "Nils Kellner", - "author_inst": "Klinikum Sankt Georg gGmbH Akademisches Lehrkrankenhaus der Universitat Leipzig: Klinikum Sankt Georg gGmbH" + "author_name": "Pralay Mitra", + "author_inst": "Indian Institute of Technology (IIT) Kharagpur" }, { - "author_name": "Michael Borte", - "author_inst": "Klinikum Sankt Georg gGmbH Akademisches Lehrkrankenhaus der Universitat Leipzig: Klinikum Sankt Georg gGmbH" - }, - { - "author_name": "Jasmin Fertey", - "author_inst": "Fraunhofer Institute for Cell Therapy and Immunology: Fraunhofer-Institut fur Zelltherapie und Immunologie IZI" - }, - { - "author_name": "Christoph L\u00fcbbert", - "author_inst": "Klinikum Sankt Georg gGmbH Akademisches Lehrkrankenhaus der Universitat Leipzig: Klinikum Sankt Georg gGmbH" - }, - { - "author_name": "Sebastian Ulbert", - "author_inst": "Fraunhofer Institute for Cell Therapy and Immunology: Fraunhofer-Institut fur Zelltherapie und Immunologie IZI" - }, - { - "author_name": "Stephan Borte", - "author_inst": "Klinikum Sankt Georg gGmbH Akademisches Lehrkrankenhaus der Universitat Leipzig: Klinikum Sankt Georg gGmbH" + "author_name": "Siddik Sarkar", + "author_inst": "CSIR- Indian Institute of Chemical Biology, Translational Research Unit of Excellence" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.01.28.21268186", @@ -430334,27 +430285,119 @@ "category": "rehabilitation medicine and physical therapy" }, { - "rel_doi": "10.1101/2022.01.27.22269909", - "rel_title": "How dangerous is omicron and how effective are vaccinations?", + "rel_doi": "10.1101/2022.01.25.22269808", + "rel_title": "The inactivated NDV-HXP-S COVID-19 vaccine induces a significantly higher ratio of neutralizing to non-neutralizing antibodies in humans as compared to mRNA vaccines", "rel_date": "2022-01-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.27.22269909", - "rel_abs": "The sharp increase in the number of new COVID-19 cases in late 2021 and early 2022, which is associated with the spread of a new strain of coronavirus - omicron - is of great concern and makes it necessary to make at least approximate forecasts for the pandemic dynamics of the epidemic. As this rapid growth occurs even in countries with high levels of vaccinations, the question arises as to their effectiveness. The smoothed daily number of new cases and deaths per capita and the ratio of these characteristics were used to reveal the appearance of new coronavirus strains and to estimate the effectiveness of quarantine, testing and vaccination. The third year of the pandemic allowed us to compare the pandemic dynamics in the period from September 2020 to January 2021 with the same period one year later for Ukraine, EU, the UK, USA, India, Brazil, South Africa, Argentina, Australia, and in the whole world. Record numbers of new cases registered in late 2021 and early 2022 once again proved that existing vaccines cannot prevent new infections, and vaccinated people can spread the infection as intensively as non-vaccinated ones. Fortunately, the daily number of new cases already diminishes in EU, the UK, USA, South Africa, and Australia. In late January - early February 2022,the maximum averaged numbers of new cases are expected in Brazil, India, EU, and worldwide. \"Omicron\" waves can increase the numbers of deaths per capita, but in highly vaccinated countries, the deaths per case ratio significantly decreases.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.25.22269808", + "rel_abs": "NDV-HXP-S is a recombinant Newcastle disease virus based-vaccine against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which expresses an optimized (HexaPro) spike protein on its surface. The vaccine can be produced in embryonated chicken eggs using the same process as that employed for the production of influenza virus vaccines. Here we performed a secondary analysis of the antibody responses after vaccination with inactivated NDV-HXP-S in a Phase I clinical study in Thailand.\n\nThe SARS-CoV-2 neutralizing and spike binding activity of NDV-HXP-S post-vaccination serum samples was compared to that of matched samples from mRNA BNT162b2 (Pfizer) vaccinees. Neutralizing activity of sera from NDV-HXP-S vaccinees was comparable to that of individuals vaccinated with BNT162b2. Interstingly, the spike binding activity of the NDV-HXP-S vaccinee samples was lower than that of sera obtained from individuals vaccinated with the mRNA vaccine. This let us to calculate ratios between binding and neutralizing antibody titers. Samples from NDV-HXP-S vaccinees had binding to neutralizing activity ratios similar to those of convalescent sera suggesting a very high proportion of neutralizing antibodies and low non-neutralizing antibody titers. Further analysis showed that, in contrast to mRNA vaccination, which induces strong antibody titers to the receptor binding domain (RBD), the N-terminal domain, and the S2 domain, NDV-HXP-S vaccination induces a very RBD focused response with little reactivity to S2. This explains the high proportion of neutralizing antibodies since most neutralizing epitopes are located in the RBD. In conclusion, vaccination with inactivated NDV-HXP-S induces a high proportion of neutralizing antibodies and absolute neutralizing antibody titers comparable to those after mRNA vaccination.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Igor Nesteruk", - "author_inst": "Institute of Hydromechanics National Academy of sciences of Ukraine" + "author_name": "Juan Manuel Carreno", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Oleksii Rodionov", - "author_inst": "Private consulting office, Kyiv, Ukraine" + "author_name": "Ariel Raskin", + "author_inst": "ISMMS" + }, + { + "author_name": "Gagandeep Singh", + "author_inst": "ISMMS" + }, + { + "author_name": "Johnstone Tcheou", + "author_inst": "ISMMS" + }, + { + "author_name": "Hisaaki Kawabata", + "author_inst": "ISMMS" + }, + { + "author_name": "Charles Gleason", + "author_inst": "ISMMS" + }, + { + "author_name": "Komal Srivastava", + "author_inst": "ISMMS" + }, + { + "author_name": "Vladimir Vigdorovich", + "author_inst": "Seattle Childrens Research Institute" + }, + { + "author_name": "Nicholas Dambrauskas", + "author_inst": "Seattle Childrens Research Institute" + }, + { + "author_name": "Sneh Lata Gupta", + "author_inst": "Emory University" + }, + { + "author_name": "Irene Gonzalez", + "author_inst": "ISMMS" + }, + { + "author_name": "Jose Luis Martinez", + "author_inst": "ISMMS" + }, + { + "author_name": "Stefan Slamanig", + "author_inst": "ISMMS" + }, + { + "author_name": "D. Noah Sather", + "author_inst": "Seattle Childrens Research Institute" + }, + { + "author_name": "Rama Raghunandan", + "author_inst": "PATH" + }, + { + "author_name": "Ponthip Wirachwong", + "author_inst": "GPO" + }, + { + "author_name": "Sant Muangnoicharoen", + "author_inst": "Mahidol University" + }, + { + "author_name": "Punnee Pitisuttithum", + "author_inst": "Mahidol University" + }, + { + "author_name": "Jens Wrammert", + "author_inst": "Emory University" + }, + { + "author_name": "Mehul S Suthar", + "author_inst": "Emory University" + }, + { + "author_name": "Weina Sun", + "author_inst": "ISMMS" + }, + { + "author_name": "Peter Palese", + "author_inst": "ISMMS" + }, + { + "author_name": "Adolfo Garcia-Sastre", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Viviana Simon", + "author_inst": "Icahn School of Medicine" + }, + { + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.01.25.22269843", @@ -432416,35 +432459,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.27.22269299", - "rel_title": "Detection of SARS-CoV-2 Omicron, Delta, Alpha and Gamma variants using a rapid antigen test", + "rel_doi": "10.1101/2022.01.26.22269917", + "rel_title": "Viral Cultures for Assessing Fomites Transmission of SARS-CoV-2: a Systematic Review Protocol", "rel_date": "2022-01-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.27.22269299", - "rel_abs": "Throughout the coronavirus disease 2019 (COVID-19) pandemic, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have emerged with different infection and disease dynamics. Testing strategies, including clinical diagnosis, surveillance, and screening, have been deployed to help limit the spread of SARS-CoV-2 variants. Rapid antigen tests, in particular, have been approved for self-testing in many countries and governments are supporting their manufacturing and distribution. However, studies demonstrating the accuracy of rapid antigen tests in detecting SARS-CoV-2 variants, especially the new Omicron variant, are limited. We determined the analytical sensitivity of a CE-marked rapid antigen test against the Omicron, Delta, Alpha and Gamma variants. The rapid antigen test had the most sensitive limit of detection (10 plaque forming units [PFU]/mL) when tested with the Alpha and Gamma variants, followed by the Omicron (100 PFU/mL) and Delta (1,000 PFU/mL) variants. Given the increasing numbers of breakthrough infections and the need to surveil infectiousness, rapid antigen tests are effective public health tools to detect SARS-CoV-2 variants.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.26.22269917", + "rel_abs": "This is a protocol for a systematic review to assess fomite transmission in SARS-CoV-2. Our research questions are as follows: O_LIAre fomite samples infectious?\nC_LIO_LIIf so, what proportion are infectious, and what is the distance and duration of infectiousness in the air?\nC_LIO_LIWhat is the relationship between fomites, infectiousness and PCR cycle threshold (Ct)?\nC_LIO_LIIs there evidence of a chain of transmission that establishes an actual instance of fomite transmission of SARS-CoV-2?\nC_LI\n\nWe will include studies of any design (and in any setting) that investigate fomite transmission (defined as any inanimate object that, when contaminated with or exposed to infectious agents, can transfer the agent to a new host). We will only include studies that performed viral culture which assessed cytopathic effect and verification techniques to ensure the cultured virus is SARS-CoV-2. We will assess the risk of bias using a checklist modified from the QUADAS-2 criteria.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Nol Salcedo", - "author_inst": "E25Bio, Inc." + "author_name": "IGHO J. ONAKPOYA", + "author_inst": "UNIVERSITY OF OXFORD" }, { - "author_name": "Nidhi Nandu", - "author_inst": "E25Bio, Inc." + "author_name": "Carl J. Heneghan", + "author_inst": "University of Oxford" }, { - "author_name": "Julie Boucau", - "author_inst": "Ragon Institute of MGH, Harvard and MIT" + "author_name": "Elizabeth A Spencer", + "author_inst": "University of Oxford" }, { - "author_name": "Bobby Brooke Herrera", - "author_inst": "E25Bio, Inc." + "author_name": "Jon Brassey", + "author_inst": "Trip Database Ltd., Newport NP20 3PS, UK" + }, + { + "author_name": "Elena C. Rosca", + "author_inst": "Victor Babes University of Medicine and Pharmacy of Timisoara" + }, + { + "author_name": "Susanna Maltoni", + "author_inst": "Research and Innovation Unit, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy" + }, + { + "author_name": "Annette Pluddemann", + "author_inst": "University of Oxford, Centre for Evidence Based Medicine, UK" + }, + { + "author_name": "David H. Evans", + "author_inst": "University of Alberta" + }, + { + "author_name": "John M. Conly", + "author_inst": "Depts. of Medicine, Microbiology, Immunology and Infectious Diseases, and Pathology and Lab. Medicine, Synder Inst. for Chronic Diseases and O Brien Inst. for P" + }, + { + "author_name": "Tom Jefferson", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.01.26.22269901", @@ -434474,107 +434541,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.25.22269670", - "rel_title": "TNF\u03b1-producing CD4+ T cells dominate the SARS-CoV-2-specific T cell response in COVID-19 outpatients and are associated with durable antibodies", + "rel_doi": "10.1101/2022.01.24.22269791", + "rel_title": "Predictive and analysis of COVID-19 cases cumulative total\uff1aARIMA model based on machine learning", "rel_date": "2022-01-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.25.22269670", - "rel_abs": "SARS-CoV-2-specific CD4+ T cells are likely important in immunity against COVID-19, but our understanding of CD4+ longitudinal dynamics following infection and specific features that correlate with the maintenance of neutralizing antibodies remains limited. We characterized SARS-CoV-2-specific CD4+ T cells in a longitudinal cohort of 109 COVID-19 outpatients. The quality of the SARS-CoV-2-specific CD4+ response shifted from cells producing IFN{gamma} to TNF+ from five days to four months post-enrollment, with IFN{gamma}-IL21-TNF+ CD4+ T cells the predominant population detected at later timepoints. Greater percentages of IFN{gamma}-IL21-TNF+ CD4+ T cells on day 28 correlated with SARS-CoV-2 neutralizing antibodies measured seven months post-infection ({rho}=0.4, P=0.01). mRNA vaccination following SARS-CoV-2 infection boosted both IFN{gamma} and TNF producing, spike protein-specific CD4+ T cells. These data suggest that SARS-CoV-2-specific, TNF-producing CD4+ T cells may play an important role in antibody maintenance following COVID-19.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.24.22269791", + "rel_abs": "At present, COVID-19 poses a serious threat to global human health, and the cumulative confirmed cases in America, Brazil and India continue to grow rapidly. Therefore, the prediction models of cumulative confirmed cases in America, Brazil and India from August 1, 2021 to December 31, 2021 were established. In this study, the prevalence data of COVID-19 from 1 August 2021 to 31 December 2021 were collected from the World Health Organization website. Several ARIMA models were formulated with different ARIMA parameters. ARIMA (7,2,0), ARIMA (3,2,1), and ARIMA (10,2,4) models were selected as the best models for America, Brazil, and India, respectively. Initial combinations of model parameters were selected using the automated ARIMA model, and the optimized model parameters were then found based on Bayesian information criterion (BIC). The analytical tools autocorrelation function (ACF), and partial autocorrelation function (PACF) were used to evaluate the reliability of the model. The performance of different models in predicting confirmed cases from January 1, 2022 to January 5, 2022 was compared by using root mean square error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). This study shows that ARIMA models are suitable for predicting the prevalence of COVID-19 in the future. The results of the analysis can shed light on understanding the trends of the outbreak and give an idea of the epidemiological stage of these regions. Besides, the prediction of COVID-19 prevalence trends of America, Brazil, and India can help take precautions and policy formulation for this epidemic in other countries.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Kattria van der Ploeg", - "author_inst": "Stanford University" - }, - { - "author_name": "Adam S Kirosingh", - "author_inst": "Stanford University" - }, - { - "author_name": "Diego A M Mori", - "author_inst": "Stanford University" - }, - { - "author_name": "Saborni Chakraborty", - "author_inst": "Stanford University" - }, - { - "author_name": "Zicheng Hu", - "author_inst": "University of California, San Francisco; Bakar Computational Health Sciences Institute" - }, - { - "author_name": "Benjamin L Seivers", - "author_inst": "J. Craig Venter Institute" - }, - { - "author_name": "Karen B Jacobson", - "author_inst": "Stanford University" - }, - { - "author_name": "Hector Bonilla", - "author_inst": "Stanford University" + "author_name": "Zehui Yan", + "author_inst": "Department of Child and Adolescent Health, School of Public Health, China Medical University, Shenyang, 110122, China." }, { - "author_name": "Julie Parsonnet", - "author_inst": "Stanford University" + "author_name": "Yanding Wang", + "author_inst": "Department of Epidemiology and Statistics, School of Public Health, China Medical University, Shenyang, 110122, China." }, { - "author_name": "Jason R Andrews", - "author_inst": "Stanford University" + "author_name": "Meitao Yang", + "author_inst": "Department of Epidemiology and Statistics, School of Public Health, China Medical University, Shenyang, 110122, China." }, { - "author_name": "Kathleen D Press", - "author_inst": "Stanford University" - }, - { - "author_name": "Maureen C Ty", - "author_inst": "Stanford university" - }, - { - "author_name": "Daniel R Ruiz-Betancourt", - "author_inst": "Stanford University" - }, - { - "author_name": "Lauren de la Parte", - "author_inst": "Stanford University" - }, - { - "author_name": "Gene S Tan", - "author_inst": "J. Craig Venter Institute" - }, - { - "author_name": "Catherine A Blish", - "author_inst": "Stanford University" - }, - { - "author_name": "Saki Takahashi", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Isabel Rodriguez-Barraquer", - "author_inst": "University of California, San Francisco" + "author_name": "Zhiqiang Li", + "author_inst": "Department of Epidemiology and Statistics, School of Public Health, China Medical University, Shenyang, 110122, China." }, { - "author_name": "Bryan Greenhouse", - "author_inst": "University of California, San Francisco" + "author_name": "Xinran Gong", + "author_inst": "Department of Epidemiology and Statistics, School of Public Health, China Medical University, Shenyang, 110122, China." }, { - "author_name": "Upinder Singh", - "author_inst": "Stanford University" + "author_name": "Di Wu", + "author_inst": "Department of Epidemiology and Statistics, School of Public Health, China Medical University, Shenyang, 110122, China." }, { - "author_name": "Taia T Wang", - "author_inst": "Stanford University" + "author_name": "Wenyi Zhang", + "author_inst": "Chinese PLA Center for Disease Control and Prevention, 100071, China." }, { - "author_name": "Prasanna Jagannathan", - "author_inst": "Stanford University" + "author_name": "Yong Wang", + "author_inst": "Chinese PLA Center for Disease Control and Prevention, 100071, China." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2022.01.25.22269794", @@ -436484,25 +436495,77 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.24.477469", - "rel_title": "Design of immunogens for eliciting antibody responses that may protect against SARS-CoV-2 variants", + "rel_doi": "10.1101/2022.01.20.477163", + "rel_title": "Mutations of SARS-CoV-2 variants of concern escaping Spike-specific T cells", "rel_date": "2022-01-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.24.477469", - "rel_abs": "The rise of SARS-CoV-2 variants and the history of outbreaks caused by zoonotic coronaviruses point to the need for next-generation vaccines that confer protection against variant strains. Here, we combined analyses of diverse sequences and structures of coronavirus spikes with data from deep mutational scanning to design SARS-CoV-2 variant antigens containing the most significant mutations that may emerge. We trained a neural network to predict RBD expression and ACE2 binding from sequence, which allowed us to determine that these antigens are stable and bind to ACE2. Thus, they represent viable variants. We then used a computational model of affinity maturation (AM) to study the antibody response to immunization with different combinations of the designed antigens. The results suggest that immunization with a cocktail of the antigens is likely to promote evolution of higher titers of antibodies that target SARS-CoV-2 variants than immunization or infection with the wildtype virus alone. Finally, our analysis of 12 coronaviruses from different genera identified the S2 cleavage site and fusion peptide as potential pan-coronavirus vaccine targets.\n\nAuthor SummarySARS-CoV-2 variants have already emerged and future variants may pose greater threats to the efficacy of current vaccines. Rather than using a reactive approach to vaccine development that would lag behind the evolution of the virus, such as updating the sequence in the vaccine with a current variant, we sought to use a proactive approach that predicts some of the mutations that could arise that could evade current immune responses. Then, by including these mutations in a new vaccine antigen, we might be able to protect against those potential variants before they appear. Toward this end, we used various computational methods including sequence analysis and machine learning to design such antigens. We then used simulations of antibody development, and the results suggest that immunization with our designed antigens is likely to result in an antibody response that is better able to target SARS-CoV-2 variants than current vaccines. We also leveraged our sequence analysis to suggest that a particular site on the spike protein could serve as a useful target for a pan-coronavirus vaccine.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.20.477163", + "rel_abs": "The amino acid (AA) mutations that characterise the different variants of concern (VOCs), which replaced the ancestral SARS-CoV-2 Wuhan-Hu-1 isolate worldwide, provide biological advantages such as increased infectivity and partial escape from humoral immunity. Here we analysed the impact of these mutations on vaccination- and infection-induced Spike-specific T cells. We confirmed that, in the majority of infected or vaccinated individuals, different mutations present in a single VOC (Delta) or a combined mosaic of more than 30 AA substitutions and deletions found in Alpha, Beta, Gamma, Delta and Omicron VOCs cause modest alteration in the global Spike-specific T cell response. However, distinct numerically dominant Spike-specific CD4 and CD8 T cells preferentially targeted regions affected by AA mutations and do not recognise the mutated peptides. Importantly, some of these mutations, such as N501Y (present in Alpha, Beta, Gamma, and Omicron) and L452R (present in Delta), known to provide biological advantage to SARS-CoV-2 in terms of infectivity also abolished CD8 T cell recognition.\n\nTaken together, our data show that while global mRNA vaccine- and infection-induced Spike-specific T cells largely tolerate the diverse mutations present in VOCs, single Spike-specific T cells might contribute to the natural selection of SARS-CoV-2 variants.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Eric Wang", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Nina Le Bert", + "author_inst": "Duke-NUS Medical School" }, { - "author_name": "Arup K Chakraborty", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Anthony T Tan", + "author_inst": "Duke-NUS Medical School" + }, + { + "author_name": "Kamini Kunasegaran", + "author_inst": "Duke-NUS Medical School" + }, + { + "author_name": "Adeline Chia", + "author_inst": "Duke-NUS Medical School" + }, + { + "author_name": "Nicole Tan", + "author_inst": "Duke-NUS Medical School" + }, + { + "author_name": "Qi Chen", + "author_inst": "Duke-NUS Medical School" + }, + { + "author_name": "Shou Kit Hang", + "author_inst": "Duke-NUS Medical School" + }, + { + "author_name": "Martin DC Qui", + "author_inst": "Duke-NUS Medical School" + }, + { + "author_name": "Bianca SW Chan", + "author_inst": "KK Women and Children Hospital" + }, + { + "author_name": "Jenny GH Low", + "author_inst": "Singapore General Hospital" + }, + { + "author_name": "Barnaby Young", + "author_inst": "National Center of Infectious Diseases" + }, + { + "author_name": "Kee Chong Ng", + "author_inst": "KK Women and Children Hospital" + }, + { + "author_name": "Derrick Wei Shih Chan", + "author_inst": "KK Women and Children Hospital" + }, + { + "author_name": "David Chien Boon Lye", + "author_inst": "National Centre of Infectious Diseases" + }, + { + "author_name": "Antonio Bertoletti", + "author_inst": "Duke-NUS Medical School" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -438274,99 +438337,47 @@ "category": "geriatric medicine" }, { - "rel_doi": "10.1101/2022.01.20.477164", - "rel_title": "Severe acute respiratory disease in American mink (Neovison vison) experimentally infected with SARS-CoV-2", + "rel_doi": "10.1101/2022.01.21.477274", + "rel_title": "Host Chitinase 3-like-1 is a Universal Therapeutic Target for the Delta, Omicron and Other SARS-CoV-2 Viral Variants in COVID 19", "rel_date": "2022-01-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.20.477164", - "rel_abs": "An animal model that fully recapitulates severe COVID-19 presentation in humans has been a top priority since the discovery of SARS-CoV-2 in 2019. Although multiple animal models are available for mild to moderate clinical disease, a non-transgenic model that develops severe acute respiratory disease has not been described. Mink experimentally infected with SARS-CoV-2 developed severe acute respiratory disease, as evident by clinical respiratory disease, radiological, and histological changes. Virus was detected in nasal, oral, rectal, and fur swabs. Deep sequencing of SARS-CoV-2 from oral swabs and lung tissue samples showed repeated enrichment for a mutation in the gene encoding for nonstructural protein 6 in open reading frame 1a/1ab. Together, these data indicate that American mink develop clinical features characteristic of severe COVID19 and as such, are uniquely suited to test viral countermeasures.\n\nOne Sentence SummarySARS-CoV-2 infected mink develop severe respiratory disease that recapitulates some components of severe acute respiratory disease, including ARDS.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.21.477274", + "rel_abs": "COVID 19 is the disease caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2; SC2) which has caused a world-wide pandemic with striking morbidity and mortality. Evaluation of SC2 strains demonstrated impressive genetic variability and many of these viral variants are now defined as variants of concern (VOC) that cause enhanced transmissibility, decreased susceptibility to antibody neutralization or therapeutics and or the ability to induce severe disease. Currently, the delta ({delta}) and omicron (o) variants are particularly problematic based on their impressive and unprecedented transmissibility and ability to cause break through infections. The delta variant also accumulates at high concentrations in host tissues and has caused waves of lethal disease. Because studies from our laboratory have demonstrated that chitinase 3-like-1 (CHI3L1) stimulates ACE2 and Spike (S) priming proteases that mediate SC2 infection, studies were undertaken to determine if interventions that target CHI3L1 are effective inhibitors of SC2 viral variant infection. Here we demonstrate that CHI3L1 augments epithelial cell infection by pseudoviruses that express the alpha, beta, gamma, delta or omicron S proteins and that the CHI3L1 inhibitors anti-CHI3L1 and kasugamycin inhibit epithelial cell infection by these VOC pseudovirus moieties. Thus, CHI3L1 is a universal, VOC-independent therapeutic target in COVID 19.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Danielle R Adney", - "author_inst": "Lovelace Biomedical Research Institute" - }, - { - "author_name": "Jamie Lovaglio", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Jonathan E Schulz", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Claude Kwe Yinda", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Victoria A Avanzato", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Elaine Haddock", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Julia R Port", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Myndi Holbrook", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Patrick W Hanley", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Greg Saturday", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Dana Scott", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Jessica R Spengler", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Cassandra Tansey", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Caitlin Cossaboom", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Suchitra Kamle", + "author_inst": "Brown University" }, { - "author_name": "Natalie Wendling", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Bing Ma", + "author_inst": "Brown University" }, { - "author_name": "Craig Martens", - "author_inst": "National Institute of Allergy and Infectious Diseases" + "author_name": "Chang Min Lee", + "author_inst": "Brown University" }, { - "author_name": "John Easley", - "author_inst": "Mink Veterinary Consulting and Research Service" + "author_name": "Gail Schor", + "author_inst": "Brown University" }, { - "author_name": "Seng Wai Yap", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Yang Zhou", + "author_inst": "Brown University" }, { - "author_name": "Stephanie N. Seifert", - "author_inst": "Washington State University" + "author_name": "Chun Geun Lee", + "author_inst": "Brown University" }, { - "author_name": "Vincent J Munster", - "author_inst": "National Institute of Allergy and Infectious Diseases" + "author_name": "Jack A. Elias", + "author_inst": "Brown University" } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2022.01.20.477067", @@ -439956,55 +439967,27 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.01.18.22269467", - "rel_title": "The Effects of Messaging on Expectations and Understanding of Long COVID: An Online Randomised Trial", + "rel_doi": "10.1101/2022.01.21.22269631", + "rel_title": "Proteomic deconvolution reveals distinct immune cell fractions in different body sites in SARS-Cov-2 positive individuals", "rel_date": "2022-01-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.18.22269467", - "rel_abs": "ObjectivesWe examined whether providing different types of information about Long COVID would affect expectations about the illness.\n\nDesignA 2 (Illness description: Long COVID vs ongoing COVID-19 recovery) x 2 (Illness uncertainty: uncertainty emphasised vs uncertainty not emphasised) x 2 (Efficacy of support: enhanced support vs basic support) between-subjects randomised online experimental study.\n\nSettingThe online platform Prolific, collected in October 2021.\n\nParticipantsA representative sample of 1110 members of the public in the UK.\n\nInterventionsParticipants were presented with a scenario describing a positive COVID-19 test result and then presented with one of eight scenarios describing a Long COVID diagnosis.\n\nPrimary and Secondary Outcome MeasuresVarious outcome measures relating to illness expectations were captured including: symptom severity, symptom duration, quality of life, personal control, treatment control and illness coherence.\n\nResultsWe ran a series of 2 x 2 x 2 ANOVAs on the outcome variables. We found a main effect of illness description: individuals reported longer symptom duration and less illness coherence when the illness was described as Long COVID (compared to ongoing COVID-19 recovery). There was a main effect of illness uncertainty: when uncertainty was emphasised, participants reported longer expected symptom duration, less treatment control, and less illness coherence than when uncertainty was not emphasised. There was also a main effect of efficacy of support: participants reported higher personal control and higher treatment control when support was enhanced (compared to basic support). We also found an interaction between illness description and efficacy of support: when support was enhanced, participants reported less illness coherence for Long COVID (compared to ongoing COVID-19 recovery).\n\nConclusionsCommunications around Long COVID should not emphasise symptom uncertainty and should provide people with information on how they can facilitate their recovery and where they can access additional support. The findings also suggest that use of the term ongoing COVID-19 recovery, where possible, may reduce negative expectations associated with the illness.\n\nStrengths and Limitations of this studyO_LIThis is one of the first experimental designed studies to assess the impact of different types of communication about Long COVID.\nC_LIO_LIParticipants were a UK representative sample, although these findings are not necessarily applicable to all population groups (i.e., ethnic minorities).\nC_LIO_LIThis study is one of the first applications of the IPQ-R in a hypothetical, online experiment, with high reliability.\nC_LIO_LIThis was an online experiment, with hypothetical scenarios and participants with no experience of COVID-19 or Long COVID, therefore outcomes may be different in a real-world context.\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.21.22269631", + "rel_abs": "BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to be a significant public health challenge globally. SARS-CoV-2 is a novel virus, and what constitutes immunological responses in different human body sites in infected individuals is yet to be presented. We set to determine the various immune cell fractions in gargle solution, bronchoalveolar lavage fluid, nasopharyngeal, and urine samples post-SARS-CoV-2 infection in humans.\n\nMaterials and methodsWe downloaded proteomics data from (https://www.ebi.ac.uk/pride/) with the following identifiers: PXD019423, n=3 (gargle solution), PXD018970, n=15 (urine), PXD022085, n=5 (Bronchoalveolar lavage fluid), PXD022889, n=18 (nasopharyngeal). MaxQuant was used for the peptide spectral matching using humans, and SARS-CoV-2 was downloaded from the UniProt database (Access date 9th January 2022). The protein count matrix was extracted from the proteins group file and used as an input for the cibersort for the immune cells fraction determination.\n\nResultsThe body of individuals infected with the SARS-CoV-2 virus is characterized by different fractions of immune cells in Bronchoalveolar lavage fluid (BALF), nasopharyngeal, urine, and gargle solution. BALF has more abundant memory B cells, CD8, activated mast cells, and resting macrophages than urine, nasopharyngeal, and gargle solution. Our analysis also demonstrates that each body site comprises different immune cell fractions post-SARS-CoV-2 infection in humans.\n\nConclusionDifferent body sites are characterized by different immune cells fractions in SARS-CoV-2 infected individuals. The findings in this study can inform public health policies and health professionals on treatment strategies and drive SARS-CoV-2 diagnosis procedures.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Jaskiran Kaur Bhogal", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Freya Mills", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Amelia Dennis", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Cristina Spoiala", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Joanna Milward", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Sidra Saeed", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Leah Ffion Jones", - "author_inst": "UK Health Security Agency" - }, - { - "author_name": "Dale Weston", - "author_inst": "UK Health Security Agency" + "author_name": "Javan Okendo", + "author_inst": "Systems and Chemical Biology Division, Department of Integrative Biomedical Sciences, Institute of Infectious Disease and Molecular Medicine, Faculty of Health " }, { - "author_name": "Holly Carter", - "author_inst": "UK Health Security Agency" + "author_name": "David Okanda", + "author_inst": "Research, Innovations, and Academics Unit, Tunacare Services Health Providers Limited, Nairobi, Kenya" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health informatics" }, { "rel_doi": "10.1101/2022.01.20.22269599", @@ -442038,95 +442021,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.19.22269510", - "rel_title": "Microbial GWAS studies revealing combinations of Omicron RBD mutations existed and may contribute to antibody evasion and ACE2 binding", + "rel_doi": "10.1101/2022.01.20.477056", + "rel_title": "Sialic acid and fucose residues on the SARS-CoV-2 receptor binding domain modulate IgG reactivity", "rel_date": "2022-01-21", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.19.22269510", - "rel_abs": "Since Omicron variant of SARS-CoV-2 was first detected in South Africa (SA), it has now dominated in United Kingdom (UK) of Europe and United State (USA) of North America. A prominent feature of this variant is the gathering of spike protein mutations, in particularly at the receptor binding domain (RBD). These RBD mutations essentially contribute to antibody resistance of current immune approaches. During global spillover, combinations of RBD mutations may exist and synergistically contribute to antibody resistance in fact. Using three geographic-stratified genome wide association studies (GWAS), we observed that RBD combinations exhibited a geographic pattern and genetical associated, such as five common mutations in both UK and USA Omicron, six or two specific mutations in UK or USA Omicron. Although the UK specific RBD mutations can be further classified into two separated sub-groups of combination based on linkage disequilibrium analysis. Functional analysis indicated that the common RBD combinations (fold change, -11.59) alongside UK or USA specific mutations significantly reduced neutralization (fold change, -38.72, -18.11). As RBD overlaps with angiotensin converting enzyme 2(ACE2) binding motif, protein-protein contact analysis indicated that the common RBD mutations enhanced ACE2 binding accessibility and were further strengthened by UK or USA-specific RBD mutations. Spatiotemporal evolution analysis indicated that UK-specific RBD mutations largely contribute to global spillover. Collectively, we have provided genetic evidence of RBD combinations and estimated their effects on antibody evasion and ACE2 binding accessibility.", - "rel_num_authors": 19, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.20.477056", + "rel_abs": "The receptor binding domain (RBD) of the SARS-CoV-2 spike protein is a conserved domain and a target for neutralizing antibodies. We defined the carbohydrate content of recombinant RBD produced in different mammalian cells. We found a higher degree of complex type N-linked glycans, with less sialylation and more fucosylation, when the RBD was produced in Human embryonic kidney cells compared to the same protein produced in Chinese hamster ovary cells. The carbohydrates on the RBD proteins were enzymatically modulated and the effect on antibody reactivity was evaluated with serum samples from SARS-CoV-2 positive patients. Removal of all carbohydrates diminished antibody reactivity while removal of only sialic acids or terminal fucoses improved the reactivity. The RBD produced in Lec3.2.8.1-cells, which generate carbohydrate structures devoid of sialic acids and with reduced fucose content, exhibited enhanced antibody reactivity verifying the importance of these specific monosaccharides. The results can be of importance for the design of future vaccine candidates, indicating that it might be possible to enhance the immunogenicity of recombinant viral proteins.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Xumin Ou", - "author_inst": "Sichuan Agricultural University" - }, - { - "author_name": "Zhishuang Yang", - "author_inst": "College of Veterinary Medicine, Sichuan Agricultural University" - }, - { - "author_name": "Dekang Zhu", - "author_inst": "SICAU" - }, - { - "author_name": "Sai Mao", - "author_inst": "SICAU" - }, - { - "author_name": "Mingshu Wang", - "author_inst": "SICAU" - }, - { - "author_name": "Renyong Jia", - "author_inst": "Sichuan Agricultural University" - }, - { - "author_name": "Shun Chen", - "author_inst": "SICAU" - }, - { - "author_name": "Mafeng Liu", - "author_inst": "SICAU" - }, - { - "author_name": "Qiao Yang", - "author_inst": "SICAU" - }, - { - "author_name": "Ying Wu", - "author_inst": "SICAU" - }, - { - "author_name": "Xinxin Zhao", - "author_inst": "SICAU" - }, - { - "author_name": "Shaqiu Zhang", - "author_inst": "SICAU" - }, - { - "author_name": "Juan Huang", - "author_inst": "SICAU" - }, - { - "author_name": "Qun Gao", - "author_inst": "SICAU" + "author_name": "Ebba Samuelsson", + "author_inst": "University of Gothenburg" }, { - "author_name": "Yunya Liu", - "author_inst": "SICAU" + "author_name": "Ekaterina Mirgorodskaya", + "author_inst": "University of Gothenburg" }, { - "author_name": "Ling Zhang", - "author_inst": "SICAU" + "author_name": "Kristina Nystr\u00f6m", + "author_inst": "University of Gothenburg" }, { - "author_name": "Maikel Peppelenbosch", - "author_inst": "Erasmus MC" + "author_name": "Malin B\u00e4ckstr\u00f6m", + "author_inst": "University of Gothenburg" }, { - "author_name": "Qiuwei Pan", - "author_inst": "Erasmus MC" + "author_name": "Jan-\u00c5ke Liljeqvist", + "author_inst": "University of Gothenburg" }, { - "author_name": "An-chun Cheng", - "author_inst": "Sichuan Agricultural University" + "author_name": "Rickard Nord\u00e9n", + "author_inst": "University of Gothenburg" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "molecular biology" }, { "rel_doi": "10.1101/2022.01.20.477133", @@ -443828,63 +443759,39 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.01.21.22269636", - "rel_title": "Using Survey Data to Estimate the Impact of the Omicron Variant on Vaccine Efficacy against COVID-19 Infection", - "rel_date": "2022-01-21", + "rel_doi": "10.1101/2022.01.18.22269349", + "rel_title": "Long-Term Persistence of IgG Antibodies in recovered COVID-19 individuals at 18 months and the impact of two-dose BNT162b2 (Pfizer-BioNTech) mRNA vaccination on the antibody response", + "rel_date": "2022-01-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.21.22269636", - "rel_abs": "Data collected in the Global COVID-19 Trends and Impact Surveys (UMD Global CTIS), and data on variants sequencing from GISAID, are used to evaluate the impact of the Omicron variant (in South Africa and other countries) on the prevalence of COVID-19 among unvaccinated and vaccinated population, in general and discriminating by the number of doses. In South Africa, we observe that the prevalence of COVID-19 in December (with strong presence of Omicron) among the unvaccinated population is comparable to the prevalence during the previous wave (in August-September), in which Delta was the variant with the largest presence. However, among vaccinated, the prevalence of COVID-19 in December is much higher than in the previous wave. In fact, a significant reduction of the vaccine efficacy is observed from August-September to December. For instance, the efficacy drops from 0.81 to 0.30 for those vaccinated with 2 doses, and from 0.51 to 0.09 for those vaccinated with one dose. The study is then extended to other countries in which Omicron has been detected, comparing the situation in October (before Omicron) with that of December. While the reduction measured is smaller than in South Africa, we still found, for instance, an average drop in vaccine efficacy from 0.53 to 0.45 among those vaccinated with two doses. Moreover, we found a significant negative (Pearson) correlation of around -0.6 between the measured prevalence of Omicron and the vaccine efficacy.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.18.22269349", + "rel_abs": "This era of emerging variants needs a thorough evaluation of data on the long-term efficacy of immune responses in vaccinated as well as recovered individuals, to understand the overall evolution of the pandemic. In this study, we aimed to assess the dynamics of IgG titers over 18 months in n=36 patients from the Umbria region in Italy, who had a documented history of COVID-19 infection in March 2020, and then compared the impact of two-dose BNT162b2 (Pfizer-BioNTech) vaccination on the antibody titers of these patients with the ones who did not receive any dose of vaccine. This is the longest observation (March 2020-September 2021) for the presence of antibodies against SARS-CoV-2 in recovered individuals along with the impact of 2 dose-BNT162b2 vaccination on the titers. Fixed-effect regression models were used for statistical analysis which could be also used to predict future titer trends. At 18 months, 97% participants tested positive for anti-NCP hinting towards the persistence of infection-induced immunity even for the vaccinated individuals. Our study findings demonstrate that while double dose vaccination boosted the IgG titers in recovered individuals 161 times, this \"boost\" was relatively short-lived. The unvaccinated recovered individuals, in contrast, continued to show a steady decline but detectable antibody levels. Further studies are required to re-evaluate the timing and dose regimen of vaccines for an adequate immune response in recovered individuals.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Jesus Rufino", - "author_inst": "IMDEA Networks Institute & CoronaSurveys Team, Spain" - }, - { - "author_name": "Carlos Baquero", - "author_inst": "U. Porto & INESC TEC, Portugal, & CoronaSurveys Team" - }, - { - "author_name": "Davide Frey", - "author_inst": "Univ Rennes, IRISA, CNRS, Inria, 35042 Rennes, France & CoronaSurveys Team" - }, - { - "author_name": "Christin A. Glorioso", - "author_inst": "Academics for the Future of Science, Inc. & U. of California San Francisco, USA, & CoronaSurveys Team" - }, - { - "author_name": "Antonio Ortega", - "author_inst": "U. Southern California, USA, & CoronaSurveys Team" - }, - { - "author_name": "Nina Rescic", - "author_inst": "Jozef Stefan Institute, Department of Intelligent Systems, Ljubljana, Slovenia, & CoronaSurveys Team" - }, - { - "author_name": "Julian Charles Roberts", - "author_inst": "Gearu LTD, UK, & CoronaSurveys Team" + "author_name": "Puya Dehgani-Mobaraki", + "author_inst": "Associazione Naso Sano, Italy" }, { - "author_name": "Rosa E. Lillo", - "author_inst": "U. Carlos III de Madrid, Spain, & CoronaSurveys Team" + "author_name": "Chao Wang", + "author_inst": "Faculty of Health, Social Care and Education, Kingston University and St George's, University of London, London, SW17 0RE, UK." }, { - "author_name": "Raquel Menezes", - "author_inst": "Centre of Mathematics of U. Minho, Portugal, & CoronaSurveys Team" + "author_name": "Alessandro Floridi", + "author_inst": "Laboratory of Nuclear Lipid BioPathology, Centro Ricerche Analisi Biochimico Specialistiche, Perugia, Italy" }, { - "author_name": "Jaya Prakash Champati", - "author_inst": "IMDEA Networks Institute, Spain, & CoronaSurveys Team" + "author_name": "Emanuela Floridi", + "author_inst": "Laboratory of Nuclear Lipid BioPathology, Centro Ricerche Analisi Biochimico Specialistiche, Perugia, Italy" }, { - "author_name": "Antonio Fernandez Anta", - "author_inst": "IMDEA Networks Institute, Spain, & CoronaSurveys Team" + "author_name": "Asiya K Zaidi", + "author_inst": "Associazione Naso Sano, Italy" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.01.18.476801", @@ -445902,91 +445809,107 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.18.476863", - "rel_title": "SARS-CoV-2 Delta variant induces enhanced pathology and inflammatory responses in K18-hACE2 mice", - "rel_date": "2022-01-19", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.18.476863", - "rel_abs": "The COVID-19 pandemic has been fueled by novel variants of concern (VOC) that have increased transmissibility, receptor binding affinity, and other properties that enhance disease. The goal of this study is to characterize unique pathogenesis of the Delta VOC strain in the K18-hACE2-mouse challenge model. Challenge studies suggested that the lethal dose of Delta was higher than Alpha or Beta strains. To characterize the differences in the Delta strains pathogenesis, a time-course experiment was performed to evaluate the overall host response to Alpha or Delta variant challenge. qRT-PCR analysis of Alpha- or Delta- challenged mice revealed no significant difference between viral RNA burden in the lung, nasal wash or brain. However, histopathological analysis revealed high lung tissue inflammation and cell infiltration following Delta- but not Alpha-challenge at day 6. Additionally, pro-inflammatory cytokines were highest at day 6 in Delta-challenged mice suggesting enhanced pneumonia. Total RNA-sequencing analysis of lungs comparing infected to uninfected mice revealed that Alpha-challenged mice have more total genes differentially activated, conversely, Delta-challenged mice have a higher magnitude of differential gene expression. Delta-challenged mice have increased interferon-dependent gene expression and IFN-{gamma} production compared to Alpha. Analysis of TCR clonotypes suggested that Delta challenged mice have increased T-cell infiltration compared to Alpha challenged. Our data suggest that Delta has evolved to engage interferon responses in a manner that may enhance pathogenesis. The in vivo and in silico observations of this study underscore the need to conduct experiments with VOC strains to best model COVID-19 when evaluating therapeutics and vaccines.\n\nImportanceThe Delta variant of SARS-CoV-2 is known to be more transmissible and cause severe disease in human hosts due to mutations in its genome that are divergent from previous variants of concern (VOC). Our study evaluates the pathogenesis of Delta in the K18-hACE2 mouse model compared to the Alpha VOC. We observed that relative to Alpha, Delta challenge results in enhanced inflammation and tissue damage with stronger antiviral responses. These observations provide insight into Deltas unique pathogenesis.", - "rel_num_authors": 18, + "rel_doi": "10.1101/2022.01.17.22269263", + "rel_title": "Multisystemic inflammatory syndrome following COVID-19 mRNA vaccine in children: a national post-authorization pharmacovigilance study", + "rel_date": "2022-01-18", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.17.22269263", + "rel_abs": "ImportanceMultisystem inflammatory syndrome in children (MIS-C) is the most severe life-threatening clinical entity associated with pediatric SARS-CoV-2 infection. Whether COVID-19 mRNA vaccine can induce this complication in children is unknown.\n\nObjectiveTo assess the risk of hyper-inflammatory syndrome following COVID-19 mRNA vaccine in children.\n\nDesign, Setting, and ParticipantsPost-authorization national population-based surveillance using the French enhanced pharmacovigilance surveillance system for COVID-19 vaccines. All cases of suspected hyper-inflammatory syndrome following COVID-19 mRNA vaccine in 12- 17-year-old children between June 15th, 2021 and January 1st, 2022, were reported. Each case was assessed for WHO MIS-C criteria. Causality assessment followed 2019 WHO recommendations.\n\nExposureCOVID-19 mRNA vaccine.\n\nMain Outcome and MeasuresThe main outcome was the reporting rate of post-vaccine hyper-inflammatory syndrome per 1,000,000 COVID-19 mRNA vaccine doses in 12-17-year-old children. This reporting rate was compared to the MIS-C rate per 1,000,000 12-17-year-old children infected by SARS-CoV-2. Secondary outcomes included the comparison of clinical features between post-vaccine hyper-inflammatory syndrome and post SARS-CoV-2 MIS-C.\n\nResultsFrom June 2021 to January 2022, 8,113,058 COVID-19 mRNA vaccine doses were administered to 4,079,234 12-17-year-old children. Among them, 9 presented a multisystemic hyper-inflammatory syndrome. All cases fulfilled MIS-C WHO criteria. Main clinical features included male predominance (8/9, 89%), cardiac involvement (8/9, 89%), digestive symptoms (7/9, 78%), coagulopathy (5/9, 54%), cytolytic hepatitis (4/9, 46%), and shock (3/9, 33%). 3/9 (33%) required intensive care unit transfer, and 2/9 (22%) hemodynamic support. All cases recovered. Only three cases had evidence of previous SARS-CoV-2 infection. The reporting rate was 1.1 (95%CI [0.5; 2.1]) per 1,000,000 doses injected. As a comparison, 113 MIS-C (95%CI [95; 135]) occurred per 1,000,000 12-17-year-old children infected by SARS-CoV-2. Clinical features (inflammatory parameters, cytopenia) slightly differed from post-SARS-CoV-2 MIS-C, along with short-term outcomes (less PICU transfer than MIS-C).\n\nConclusion and RelevanceVery few cases of hyper-inflammatory syndromes with multi-organ involvement occurred following COVID-19 mRNA vaccine in 12-17-year-old children. The low reporting rate of this syndrome, compared to the rate of MIS-C among same age children infected by SARS-CoV-2, supports the benefit of SARS-CoV-2 vaccination in children. Further studies are required to explore specific pathways of this entity compared to post-SARS-CoV-2 MIS-C.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSIs COVID-19 mRNA vaccine in 12-17-year-old children associated with subsequent multisystemic hyper-inflammatory syndrome?\n\nFindingsThe French national pharmacovigilance system identified 9 children with a hyper-inflammatory syndrome with multi-organ involvement following COVID-19 mRNA vaccination (reporting rate 1.1 [0.5; 2.1] per 1,000,000 doses), of which only three had evidence of previous SARS-CoV-2 infection. All cases fulfilled WHO definition for MIS-C, but clinical and immunological features, along with short-term outcomes, slightly differed from classical post SARS-CoV-2 MIS-C.\n\nMeaningVery rare cases of hyper-inflammatory syndrome can occur following COVID-19 mRNA vaccine in 12-17-year-old children. The very low rate of this entity, compared to classical post-SARS-CoV-2 MIS-C, supports the benefit of SARS-CoV-2 vaccination in children.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Katherine S Lee", - "author_inst": "West Virginia University" + "author_name": "Naim Ouldali", + "author_inst": "Robert Debre hospital" }, { - "author_name": "Ting Y. Wong", - "author_inst": "West Virginia University" + "author_name": "Haleh Bagheri", + "author_inst": "Regional Pharmacovigilance Center of Toulouse" }, { - "author_name": "Brynnan P Russ", - "author_inst": "West Virginia University" + "author_name": "Francesco Salvo", + "author_inst": "Team Pharmacoepidemiology, University of Bordeaux" }, { - "author_name": "Alexander M Horspool", - "author_inst": "West Virginia University" + "author_name": "Denise Antona", + "author_inst": "Sante publique France" }, { - "author_name": "Olivia Miller", - "author_inst": "West Virginia University" + "author_name": "Antoine Pariente", + "author_inst": "Team Pharmacoepidemiology, Bordeaux University" }, { - "author_name": "Nathaniel Rader", - "author_inst": "West Virginia University" + "author_name": "Claire Leblanc", + "author_inst": "Robert Debre hospital" }, { - "author_name": "Jerome P Givi", - "author_inst": "West Virginia University" + "author_name": "Martine Tebacher", + "author_inst": "Regional pharmacovigilance center of Strasbourg" }, { - "author_name": "Michael T Winters", - "author_inst": "West Virginia University" + "author_name": "Joelle Micallef", + "author_inst": "Marseille University hospital" }, { - "author_name": "Zeriel YA Wong", - "author_inst": "West Virginia University" + "author_name": "Corinne Levy", + "author_inst": "ACTIV" }, { - "author_name": "Holly A. Cyphert", - "author_inst": "Marshall University" + "author_name": "Robert Cohen", + "author_inst": "ACTIV" }, { - "author_name": "James Denvir", - "author_inst": "Marshall University" + "author_name": "Etienne Javouhey", + "author_inst": "Lyon hospital" }, { - "author_name": "Peter G Stoilov", - "author_inst": "West Virginia University" + "author_name": "Brigitte Bader-Meunier", + "author_inst": "Necker hospital" }, { - "author_name": "Mariette Barbier", - "author_inst": "West Virginia University" + "author_name": "Caroline Ovaert", + "author_inst": "Timone enfants hospital" }, { - "author_name": "Nadia Roan", - "author_inst": "Gladstone Institutes" + "author_name": "Sylvain Renolleau", + "author_inst": "Necker hospital" }, { - "author_name": "Md Shahrier Amin", - "author_inst": "West Virginia University" + "author_name": "Veronique Hengten", + "author_inst": "Versailles Hospital" }, { - "author_name": "Ivan Martinez", - "author_inst": "West Virginia University Cancer Institute" + "author_name": "Isabelle Kone-Paut", + "author_inst": "Kremlin Bicetre hospital" }, { - "author_name": "Justin R. Bevere", - "author_inst": "West Virginia University" + "author_name": "Nina Deschamps", + "author_inst": "Saint Malo hospital" }, { - "author_name": "F. Heath Damron", - "author_inst": "West Virginia University" + "author_name": "Loic De Pontual", + "author_inst": "Jean Verdier hospital" + }, + { + "author_name": "Xavier Iriart", + "author_inst": "Bordeaux hospital" + }, + { + "author_name": "Christelle Gras-Le Guen", + "author_inst": "Nantes hospital" + }, + { + "author_name": "Francois Angoulvant", + "author_inst": "Robert Debre hospital" + }, + { + "author_name": "Alexandre Belot", + "author_inst": "Hospices Civils de Lyon" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "pediatrics" }, { "rel_doi": "10.1101/2022.01.13.476252", @@ -447751,55 +447674,111 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2022.01.17.22269412", - "rel_title": "EFCAB4B (CRACR2A) genetic variants associated with COVID-19 fatality", + "rel_doi": "10.1101/2022.01.17.22269136", + "rel_title": "Phylodynamic analysis of SARS-CoV-2 spread in Rio de Janeiro, Brazil, highlights how metropolitan areas act as dispersal hubs for new variants.", "rel_date": "2022-01-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.17.22269412", - "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in more than 235 million cases worldwide and 4.8 million deaths (October 2021). Severe COVID-19 is characterised in part by vascular thrombosis and a cytokine storm due to increased plasma concentrations of factors secreted from endothelial and T-cells. Here, using patient data recorded in the UK Biobank, we demonstrate the importance of variations in Rab46 (CRACR2A) with clinical outcomes. Using logistic regression analysis, we determined that three single nucleotide polymorphisms (SNPs) in the gene EFCAB4B cause missense mutations in Rab46, which are associated with COVID-19 fatality independently of risk factors. All three SNPs cause changes in amino acid residues that are highly conserved across species, indicating their importance in protein structure and function. Two SNPs, rs17836273 (A98T) and rs36030417 (H212Q), cause amino acid substitutions in important functional domains: the EF-hand and coiled-coil domain respectively. By using molecular modelling, we suggest that the substitution of threonine at position 98 causes structural changes in the EF-hand calcium binding domain. Since Rab46 is a Rab GTPase that regulates both endothelial cell secretion and T-cell signalling, these missense variations may play a role in the molecular mechanisms underlying the thrombotic and inflammatory characteristics observed in patients with severe COVID-19 outcomes.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.17.22269136", + "rel_abs": "During the first semester of 2021, all of Brazil has suffered an intense wave of COVID-19 associated with the Gamma variant. In July, the first cases of Delta variant were detected in the state of Rio de Janeiro. In this work, we have employed phylodynamic methods to analyze more than 1,600 genomic sequences of Delta variant collected until September in Rio de Janeiro to reconstruct how this variant has surpassed Gamma and dispersed throughout the state. After the introduction of Delta, it has initially spread mostly in the homonymous city of Rio de Janeiro, the most populous of the state. In a second stage, dispersal occurred to mid- and long-range cities, which acted as new close-range hubs for spread. We observed that the substitution of Gamma by Delta was possibly caused by its higher viral load, a proxy for transmissibility. This variant turnover prompted a new surge in cases, but with lower lethality than was observed during the peak caused by Gamma. We reason that high vaccination rates in the state of Rio de Janeiro were possibly what prevented a higher number of deaths.\n\nImpact statementUnderstanding how SARS-CoV-2 spreads is vital to propose efficient containment strategies, especially when under the perspective of new variants emerging in the next year. Still, models of SARS-CoV-2 dispersal are still largely based in large cities from high-income countries, resulting in an incomplete view of the possible scenarios consequent of a new variant introduction. The work improves this discussion by reconstructing the spatio-temporal dispersal of Delta variant since its introduction in Rio de Janeiro, a densely populated region in South America. We also analyzed the epidemiological outcome of this spread, with a decrease in lethality rate uncommon to the observed in other countries.\n\nData summaryFour supplementary figures, one supplementary table and one supplementary file are available with the online version of this article. Raw short reads of the newly sequenced genomes are available at SRA-NCBI database (https://www.ncbi.nlm.nih.gov/sra) under the BioProject PRJNA774631 and the assembled genomes are deposited at GISAID database (https://www.gisaid.org/) under the accession numbers listed in Table S1. Other genomic sequences used in the analyses are listed in Table S2. Epidemiological data for the state of Rio de Janeiro was obtained from https://www.saude.rj.gov.br/informacao-sus/dados-sus/2020/11/covid-19.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Dapeng Wang", - "author_inst": "Imperial" + "author_name": "Alessandra P Lamarca", + "author_inst": "Laboratorio de Bioinformatica, Laboratorio Nacional de Computacao Cientifica, Petropolis, Brazil" }, { - "author_name": "Sabina D Wiktor", - "author_inst": "University of Leeds" + "author_name": "Luiz G P de Almeida", + "author_inst": "Laboratorio de Bioinformatica, Laboratorio Nacional de Computacao Cientifica, Petropolis, Brazil" }, { - "author_name": "Chew W Cheng", - "author_inst": "University of Leeds" + "author_name": "Ronaldo da Silva Francisco Junior", + "author_inst": "Laboratorio de Bioinformatica, Laboratorio Nacional de Computacao Cientifica, Petropolis, Brazil" }, { - "author_name": "Katie J Simmons", - "author_inst": "University of Leeds" + "author_name": "Liliane Cavalcante", + "author_inst": "Laboratorio de Bioinformatica, Laboratorio Nacional de Computacao Cientifica, Petropolis, Brazil" }, { - "author_name": "Ashley Money", - "author_inst": "University of Leeds" + "author_name": "Otavio Brustolini", + "author_inst": "Laboratorio de Bioinformatica, Laboratorio Nacional de Computacao Cientifica, Petropolis, Brazil" }, { - "author_name": "Lucia Pedicini", - "author_inst": "University of Leeds" + "author_name": "Alexandra L Gerber", + "author_inst": "Laboratorio de Bioinformatica, Laboratorio Nacional de Computacao Cientifica, Petropolis, Brazil" }, { - "author_name": "Asya Carlton", - "author_inst": "University of Leeds" + "author_name": "Ana Paula de C Guimaraes", + "author_inst": "Laboratorio de Bioinformatica, Laboratorio Nacional de Computacao Cientifica, Petropolis, Brazil" }, { - "author_name": "Alexander L Breeze", - "author_inst": "University of Leeds" + "author_name": "Thiago Henrique de Oliveira", + "author_inst": "Departamento de Genetica, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil" }, { - "author_name": "Lynn McKeown", - "author_inst": "University of Leeds" + "author_name": "Erica Ramos dos Santos Nascimento", + "author_inst": "Departamento de Genetica, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil" + }, + { + "author_name": "Cintia Policarpo", + "author_inst": "Departamento de Genetica, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil" + }, + { + "author_name": "Isabelle Vasconcellos de Souza", + "author_inst": "Unidades de Apoio ao Diagnostico da Covid-19, Rio de Janeiro, Brazil" + }, + { + "author_name": "Erika Martins de Carvalho", + "author_inst": "Unidades de Apoio ao Diagnostico da Covid-19, Rio de Janeiro, Brazil" + }, + { + "author_name": "Mario Sergio Ribeiro", + "author_inst": "Secretaria Estadual de Saude do Rio de Janeiro, Rio de Janeiro, Brazil" + }, + { + "author_name": "Silvia Carvalho", + "author_inst": "Secretaria Estadual de Saude do Rio de Janeiro, Rio de Janeiro, Brazil" + }, + { + "author_name": "Flavio Dias da Silva", + "author_inst": "Secretaria Municipal de Saude Rio de Janeiro, Rio de Janeiro, Brazil" + }, + { + "author_name": "Marcio Henrique de Oliveira Garcia", + "author_inst": "Secretaria Municipal de Saude Rio de Janeiro, Rio de Janeiro, Brazil" + }, + { + "author_name": "Leandro Magalhaes de Souza", + "author_inst": "Laboratorio Central de Saude Publica Noel Nutels, Rio de Janeiro, Brazil" + }, + { + "author_name": "Cristiane Gomes da Silva", + "author_inst": "Laboratorio Central de Saude Publica Noel Nutels, Rio de Janeiro, Brazil" + }, + { + "author_name": "Caio Luiz Pereira Ribeiro", + "author_inst": "Secretaria Municipal de Saude Rio de Janeiro, Rio de Janeiro, Brazil" + }, + { + "author_name": "Andrea Cony Cavalcanti", + "author_inst": "Laboratorio Central de Saude Publica Noel Nutels, Rio de Janeiro, Brazil" + }, + { + "author_name": "Claudia Maria Braga de Mello", + "author_inst": "Unidades de Apoio ao Diagnostico da Covid-19, Rio de Janeiro, Brazil" + }, + { + "author_name": "Amilcar Tanuri", + "author_inst": "Departamento de Genetica, Instituto de Biologia, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Brazil" + }, + { + "author_name": "Ana Tereza R Vasconcelos", + "author_inst": "Laboratorio de Bioinformatica, Laboratorio Nacional de Computacao Cientifica, Petropolis, Brazil" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2022.01.12.22269167", @@ -449217,39 +449196,35 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2022.01.13.21268270", - "rel_title": "Health and Economic Consequences of Universal Paid Sick Leave Policies During the COVID-19 Pandemic", + "rel_doi": "10.1101/2022.01.13.22268948", + "rel_title": "Algorithmic Fairness and Bias Mitigation for Clinical Machine Learning: Insights from Rapid COVID-19 Diagnosis by Adversarial Learning", "rel_date": "2022-01-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.13.21268270", - "rel_abs": "ImportanceUniversal paid sick-leave (PSL) policies have been implemented in jurisdictions to mitigate the spread of SARS-CoV-2. However empirical data regarding health and economic consequences of PSL policies is scarce.\n\nObjectiveTo estimate effects of a universal PSL policy in Ontario, Canadas most populous province.\n\nDesignAn agent-based model (ABM) to simulate SARS-CoV-2 transmission informed by data from Statistics Canada, health administrative sources, and from the literature.\n\nSettingOntario from January 1st to May 1st, 2021.\n\nParticipantsA synthetic population (1 million) with occupation and household characteristics representative of Ontario residents (14.5 million).\n\nExposureA base case of existing employer-based PSL alone versus the addition of a 3-or 10-day universal PSL policy to facilitate testing and self-isolation among workers infected with SARS-CoV-2 themselves or because of infected household members.\n\nMain Outcome(s) and Measure(s)Number of SARS-CoV-2 infections and COVID-19 hospitalizations, worker productivity, lost wages, and presenteeism (going to a workplace while infected).\n\nResultsIf a 3- and 10-day universal PSL were implemented over the 4-month study period, then compared with the base-case, the PSL policies were estimated to reduce cumulative SARS-CoV-2 cases by 85,531 (95% credible interval, CrI -2,484; 195,318) and 215,302 (81,500; 413,742), COVID-19 hospital admissions by 1,307 (-201; 3,205) and 3,352 (1,223; 6,528), numbers of workers forgoing wages by 558 (-327;1,608) and 7,406 (6,764; 8,072), and numbers of workers engaged in presenteeism by 24,499 (216; 54,170) and 279,863 (262,696; 295,449). Hours of productivity loss were estimated to be 10,854,379 (10,212,304; 11,465,635) in the base case, 17,446,525 (15,934,321; 18,854,683) in the 3-day scenario, and 26,127,165 (20,047,239; 29,875,161) in the 10-day scenario. Lost wages were $5,256,316 ($4,077,280; $6,804,983) and $12,610,962 ($11,463,128; $13,724,664) lower in the 3 day and 10 day scenarios respectively, relative to the base case.\n\nConclusions and RelevanceExpanded access to PSL is estimated to reduce total numbers of COVID-19 cases, reduce presenteeism of workers with SARS-CoV-2 at workplaces, and mitigate wage loss experienced by workers.\n\nCompeting interestsThe authors have no competing interests relevant to this article to disclose.\n\nFundingSupported by COVID-19 Rapid Research Funding (C-291-2431272-SANDER). This research was further supported, in part, by a Canada Research Chair in Economics of Infectious Diseases held by Beate Sander (CRC-950-232429). The study sponsor had no role in the design, collection, analysis, interpretation of the data, manuscript preparation or the decision to submit for publication.\n\nAuthor ContributionsConceptualization: PP, JDR, BS, DN\n\nData Curation: PP, JDR, BS, DN\n\nFormal Analysis: PP, JDR, DN\n\nMethodology: PP, JDR, BS, DN\n\nSupervision: PP, DN, BS\n\nValidation: PP, JDR, BS, DN\n\nFirst Draft: PP, JDR, BS, DN\n\nReview and Edit\n\nPP, JDR, BS, DN\n\nKey pointsO_ST_ABSQuestionC_ST_ABSWhat could be the health and economic consequence of more generous paid sick leave policies in the context of the COVID-19 pandemic?\n\nFindingsMore generous policies are estimated to reduce SARS-CoV-2 infections (and thus COVID-19 hospitalizations), lost wages and presence of individuals with infection at workplaces.\n\nMeaningMore generous paid sick leave can be a valuable addition to other COVID-19 public health interventions.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.13.22268948", + "rel_abs": "Machine learning is becoming increasingly prominent in healthcare. Although its benefits are clear, growing attention is being given to how machine learning may exacerbate existing biases and disparities. In this study, we introduce an adversarial training framework that is capable of mitigating biases that may have been acquired through data collection or magnified during model development. For example, if one class is over-presented or errors/inconsistencies in practice are reflected in the training data, then a model can be biased by these. To evaluate our adversarial training framework, we used the statistical definition of equalized odds. We evaluated our model for the task of rapidly predicting COVID-19 for patients presenting to hospital emergency departments, and aimed to mitigate regional (hospital) and ethnic biases present. We trained our framework on a large, real-world COVID-19 dataset and demonstrated that adversarial training demonstrably improves outcome fairness (with respect to equalized odds), while still achieving clinically-effective screening performances (NPV>0.98). We compared our method to the benchmark set by related previous work, and performed prospective and external validation on four independent hospital cohorts. Our method can be generalized to any outcomes, models, and definitions of fairness.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "David MJ Naimark", - "author_inst": "University of Toronto" - }, - { - "author_name": "Juan David Rios", - "author_inst": "The Hospital for Sick Children" + "author_name": "Jenny Yang", + "author_inst": "The University of Oxford" }, { - "author_name": "Sharmistha Mihsra", - "author_inst": "St. Michael's Hospital, Unity Health Toronto, Toronto, Canada" + "author_name": "Andrew AS Soltan", + "author_inst": "University of Oxford" }, { - "author_name": "Beate Sander", - "author_inst": "University Health Network" + "author_name": "Yang Yang", + "author_inst": "The University of Oxford" }, { - "author_name": "Petros Pechlivanoglou", - "author_inst": "THE HOSPITAL FOR SICK CHILDREN" + "author_name": "David A Clifton", + "author_inst": "The University of Oxford" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health informatics" }, { "rel_doi": "10.1101/2022.01.13.22269211", @@ -451555,101 +451530,109 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2022.01.12.476120", - "rel_title": "An antibody targeting the N-terminal domain of SARS-CoV-2 disrupts the spike trimer", + "rel_doi": "10.1101/2022.01.13.475409", + "rel_title": "Immunogenicity of convalescent and vaccinated sera against clinical isolates of ancestral SARS-CoV-2, beta, delta, and omicron variants", "rel_date": "2022-01-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.12.476120", - "rel_abs": "The protective human antibody response to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus focuses on the spike (S) protein which decorates the virion surface and mediates cell binding and entry. Most SARS-CoV-2 protective antibodies target the receptor- binding domain or a single dominant epitope ( supersite) on the N terminal domain (NTD). Here, using the single B cell technology LIBRA-seq, we isolated a large panel of NTD-reactive and SARS-CoV-2 neutralizing antibodies from an individual who had recovered from COVID-19. We found that neutralizing antibodies to the NTD supersite commonly are encoded by the IGHV1-24 gene, forming a genetic cluster that represents a public B cell clonotype. However, we also discovered a rare human antibody, COV2-3434, that recognizes a site of vulnerability on the SARS-CoV-2 S protein in the trimer interface and possesses a distinct class of functional activity. COV2-3434 disrupted the integrity of S protein trimers, inhibited cell-to-cell spread of virus in culture, and conferred protection in human ACE2 transgenic mice against SARS-CoV-2 challenge. This study provides insight about antibody targeting of the S protein trimer interface region, suggesting this region may be a site of virus vulnerability.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.13.475409", + "rel_abs": "The omicron variant of concern (VOC) of SARS-CoV-2 was first reported in November 2021 in Botswana and South Africa. Omicron has evolved multiple mutations within the spike protein and the receptor binding domain (RBD), raising concerns of increased antibody evasion. Here, we isolated infectious omicron from a clinical specimen obtained in Canada. The neutralizing activity of sera from 65 coronavirus disease (COVID-19) vaccine recipients and convalescent individuals against clinical isolates of ancestral SARS-CoV-2, beta, delta, and omicron VOCs was assessed. Convalescent sera from unvaccinated individuals infected by the ancestral virus during the first wave of COVID-19 in Canada (July, 2020) demonstrated reduced neutralization against beta and omicron VOCs. Convalescent sera from unvaccinated individuals infected by the delta variant (May-June, 2021) neutralized omicron to significantly lower levels compared to the delta variant. Sera from individuals that received three doses of the Pfizer or Moderna vaccines demonstrated reduced neutralization of the omicron variant relative to ancestral SARS-CoV-2. Sera from individuals that were naturally infected with ancestral SARS-CoV-2 and subsequently received two doses of the Pfizer vaccine induced significantly higher neutralizing antibody levels against ancestral virus and all VOCs. Importantly, infection alone, either with ancestral SARS-CoV-2 or the delta variant was not sufficient to induce high neutralizing antibody titers against omicron. This data will inform current booster vaccination strategies, and we highlight the need for additional studies to identify longevity of immunity against SARS-CoV-2 and optimal neutralizing antibody levels that are necessary to prevent infection and/or severe COVID-19.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Naveenchandra Suryadevara", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Arinjay Banerjee", + "author_inst": "Vaccine and Infectious Disease Organization" }, { - "author_name": "Andrea Shiakolas", - "author_inst": "Vanderbilt University" + "author_name": "Jocelyne Lew", + "author_inst": "Vaccine and Infectious Disease Organization" }, { - "author_name": "Laura VanBlargan", - "author_inst": "Washington University in St. Louis" + "author_name": "Andrea Kroeker", + "author_inst": "Vaccine and Infectious Disease Organization" }, { - "author_name": "Elad Binshtein", - "author_inst": "Vanderbilt University" + "author_name": "Kaushal Baid", + "author_inst": "Vaccine and Infectious Disease Organization" }, { - "author_name": "Rita Chen", - "author_inst": "Washington University in St. Louis" + "author_name": "Patryk Aftanas", + "author_inst": "Shared Hospital Laboratory" }, { - "author_name": "James Brett Case", - "author_inst": "Washington University School of Medicine" + "author_name": "Kuganya Nirmalarajah", + "author_inst": "Sunnybrook Research Institute" }, { - "author_name": "Kevin Kramer", - "author_inst": "Vanderbilt University" + "author_name": "Finlay Maguire", + "author_inst": "Faculty of Computer Science, Dalhousie University" }, { - "author_name": "Erica Armstrong", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Robert Kozak", + "author_inst": "Sunnybrook Research Institute" }, { - "author_name": "Luke Myers", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Ryan McDonald", + "author_inst": "Roy Romanow Provincial Laboratory, Saskatchewan Health Authority" }, { - "author_name": "Andrew Trivette", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Amanda Lang", + "author_inst": "Roy Romanow Provincial Laboratory, Saskatchewan Health Authority" }, { - "author_name": "Christopher Gainza", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Volker Gerdts", + "author_inst": "Vaccine and Infectious Disease Organization" }, { - "author_name": "Rachel Nargi", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Sharon E. Straus", + "author_inst": "Unity Health; Toronto" }, { - "author_name": "Christopher Selverian", - "author_inst": "Integral Molecular" + "author_name": "Lois Gilbert", + "author_inst": "Sinai Health System" }, { - "author_name": "Edgar Davidson", - "author_inst": "Integral Molecular" + "author_name": "Angel Xinliu Li", + "author_inst": "Sinai Health System" }, { - "author_name": "Benjamin Doranz", - "author_inst": "Integral Molecular" + "author_name": "Mohammad Mozafarihasjin", + "author_inst": "Sinai Health System" }, { - "author_name": "Summer Diaz", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Sharon Walmsley", + "author_inst": "University Health Network" }, { - "author_name": "Laura Handal", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Anne-Claude Gingras", + "author_inst": "Sinai Health System" }, { - "author_name": "Robert H. Carnahan", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Jeffrey L Wrana", + "author_inst": "Samuel Lunenfeld Research Inst." }, { - "author_name": "Michael S. Diamond", - "author_inst": "Washington University in St. Louis" + "author_name": "Tony Mazzulli", + "author_inst": "Department of Laboratory Medicine and Pathobiology, University of Toronto" }, { - "author_name": "Ivelin Georgiev", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Karen Colwill", + "author_inst": "Sinai Health System" }, { - "author_name": "James E. Crowe Jr.", - "author_inst": "Vanderbilt University Medical Center" + "author_name": "Allison J. McGeer", + "author_inst": "Sinai Health System" + }, + { + "author_name": "Samira Mubareka", + "author_inst": "Sunnybrook Research Institute" + }, + { + "author_name": "Darryl Falzarano", + "author_inst": "Vaccine and Infectious Disease Organization" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -453433,223 +453416,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2022.01.10.22269002", - "rel_title": "Cardiopulmonary imaging utilization and findings among hospitalized COVID-19 patients in Latin America (From RIMAC: Registry IMAging Cardiopulmonary among hospitalized COVID-19 patients in LATAM)", + "rel_doi": "10.1101/2022.01.10.22269033", + "rel_title": "Analytic sensitivity of the Abbott BinaxNOW lateral flow immunochromatographic assay for the SARS-CoV-2 Omicron variant", "rel_date": "2022-01-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.10.22269002", - "rel_abs": "ObjectivesTo describe the use and findings of cardiopulmonary imaging - chest X-ray (cX-ray), echocardiography (cEcho), chest CT (cCT), lung ultrasound (LUS)) and/or cardiac magnetic resonance imaging (cMRI) - in COVID-19-associated hospitalizations in Latin America (LATAM)\n\nBackgroundThe SARS-Cov-2 is one of the largest and most active threats to healthcare in living memory. There is an information gap on imaging services resources (ISR) used and their findings during the pandemic in LATAM.\n\nMethodsThis was a multicenter, prospective, observational study of COVID-19 inpatients conducted from March to December 2020 from 12 high-complexity centers in nine LATAM countries. Adults (> 18 yrs) with at least one imaging modality performed, followed from admission until discharge and/or in-hospital death, were included.\n\nResultsWe studied 1435 hospitalized patients (64% males) with a median age of 58 years classified into three regions: 262 from Mexico (Mx), 428 from Central America and Caribbean (CAC), and 745 from South America (SAm). More frequent comorbidities were overweight/obesity (61%), hypertension (45%), and diabetes (27%). During hospitalization, 58% were admitted to ICU. The in-hospital mortality was 28% (95%CI 25-30) highest in Mx (37%).\n\nThe most frequent cardiopulmonary imaging performed were cCT (61%)-more frequent in Mx and SAm-, and cX-ray (46%) -significantly used in CAC-. The cEcho was carried out in 18%, similarly among regions, and LUS in 7%, more frequently in Mx. The cMRI was performed in only one patient in the cohort. Abnormal findings on the cX-ray were related to peripheral (63%) or basal infiltrates (52%), and in cCT with ground glass infiltrates (89%). Both were more commonly in Mx. In LUS, interstitial syndrome (56%) was the most related abnormal finding, predominantly in Mx and CAC.\n\nConclusionsThe use and findings of cardiopulmonary imaging in LATAM varied between regions and may have been influenced by clinical needs, the personnel protection measures and/or hospitalization location.\n\nCondensed AbstractThe SARS-Cov-2 is one of the largest and most active threats to healthcare in living memory. There is limited information on imaging services resources (ISR) used and their findings during the pandemic in LATAM.\n\nTo our knowledge, RIMAC aimed the first international, multicenter study at registering the use and findings of cardiopulmonary imaging modalities performed for the diagnosis, prognosis, and treatment of patients hospitalized for infection with SARS-CoV-2 in Latin America. We studied their demographic parameters, comorbidities, in-hospital events, laboratory results, and treatments focusing on their impact in clinical complications.", - "rel_num_authors": 51, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.10.22269033", + "rel_abs": "The emergence of the SARS-CoV-2 Omicron variant has motivated a re-evaluation of the test characteristics for lateral flow immunochromatographic assays (LFIAs), commonly referred to as rapid antigen tests. To address this need, we evaluated the analytic sensitivity of one of the most widely used LFIAs in the US market, the Abbott BinaxNOW COVID-19 Ag At-Home Card using 32 samples of Omicron and 30 samples of the Delta variant. Samples were chosen to intentionally over-represent the range of viral loads where differences are most likely to appear. We found no changes in the analytic sensitivity of the BinaxNOW assay by variant even after controlling for variation in cycle threshold values in the two populations. Similar to prior studies, the sensitivity of the assay is highly dependent on the amount of virus present in the sample. While the analytic sensitivity of the BinaxNOW LFIA remains intact versus the Omicron variant, its clinical sensitivity is influenced by the interaction between viral replication, the dynamics of tissue tropism and the timing of sampling. Further research is necessary to optimally adapt current testing strategies to robustly detect early infection by the Omicron variant to prevent transmission.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Salvador Vicente Spina", - "author_inst": "Hospital Aeronautico Central, Buenos Aires, Argentina" - }, - { - "author_name": "Marcelo Luiz Campos Vieira", - "author_inst": "Hospital Israelita Albert Einstein, Sao Paulo, Brazil." - }, - { - "author_name": "Cesar Herrera", - "author_inst": "CEDIMAT, Santo Domingo, Republica Dominicana" - }, - { - "author_name": "Ana Munera Echeverri", - "author_inst": "Hospital General de Medellin, Medellin, Colombia" - }, - { - "author_name": "Pamela Rojo", - "author_inst": "Clinica Davila, Santiago de Chile, Chile" - }, - { - "author_name": "Alma Sthela Arrioja Salazar", - "author_inst": "Clinica Davila, Santiago de Chile, Chile." - }, - { - "author_name": "Zuilma Vazquez Ortiz", - "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion \"Salvador Zubiran\", Ciudad de Mexico, Mexico" - }, - { - "author_name": "Roberto Baltodano", - "author_inst": "HNG Almenara Irigoyen, Lima, Peru" - }, - { - "author_name": "Graciela Reyes", - "author_inst": "Hospital El Cruce, Provincia Buenos Aires, Argentina" - }, - { - "author_name": "Rocio Aceves Millan", - "author_inst": "Centro Medico Nacional 20 de Noviembre, Ciudad de Mexico, Mexico" - }, - { - "author_name": "Juan Calderon Gonzalez", - "author_inst": "Hospital general de Zona Numero 4, Monterrey, Mexico" - }, - { - "author_name": "Ana Camarozano", - "author_inst": "Hospital Nossa Senhora das Gracas y Universidade Federal do Parana, Brazil" - }, - { - "author_name": "Edgar Aviles", - "author_inst": "Complejo Hospitalario Dr Arnulfo Arias Madrid, Ciudad de Panama, Panama" - }, - { - "author_name": "Marco Antonio Cabrera", - "author_inst": "TECNISCAN Hospitalia, Ciudad de Guatemala, Guatemala" - }, - { - "author_name": "Maria Florencia Grande Ratti", - "author_inst": "Internal Medicine Research Area, Hospital Italiano de Buenos Aires, Argentina" - }, - { - "author_name": "Jorge Lowenstein", - "author_inst": "Instituto de Investigaciones Medicas, Buenos Aires, Argentina" - }, - { - "author_name": "Rodrigo Hernandez Vyhmeister", - "author_inst": "Hospital de la Fuerza Aerea, Santiago de Chile, Chile" - }, - { - "author_name": "Pamela Pina Santana", - "author_inst": "CEDIMAT, Santo Domingo, Republica Dominicana" - }, - { - "author_name": "Jaime Ibarra Burgos", - "author_inst": "Medicina Interna Universidad CES, Medellin, Colombia" - }, - { - "author_name": "Alejandra Rivera", - "author_inst": "Clinica Davila, Santiago de Chile, Chile." - }, - { - "author_name": "Beatriz Fernandez Campos", - "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion \"Salvador Zubiran\", Ciudad de Mexico, Mexico" - }, - { - "author_name": "Kelly Cupe Chacalcaje", - "author_inst": "HNG Almenara Irigoyen, Lima, Peru" - }, - { - "author_name": "Mariela De Santos", - "author_inst": "Hospital El Cruce, Provincia Buenos Aires, Argentina" - }, - { - "author_name": "Tania Regina Afonso", - "author_inst": "Hospital Israelita Albert Einstein, Sao Paulo, Brazil" - }, - { - "author_name": "Tomas Miranda Aquino", - "author_inst": "Centro Medico Nacional 20 de Noviembre, Ciudad de Mexico, Mexico" - }, - { - "author_name": "Ana Lalyre Acosta", - "author_inst": "Complejo Hospitalario Dr Arnulfo Arias Madrid, Ciudad de Panama, Panama" - }, - { - "author_name": "Beatriz Dominguez", - "author_inst": "TECNISCAN Hospitalia, Ciudad de Guatemala, Guatemala" - }, - { - "author_name": "Federico Campos", - "author_inst": "CEDIMAT, Santo Domingo, Republica Dominicana" - }, - { - "author_name": "Sergio Alday Ramirez", - "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion \"Salvador Zubiran\", Ciudad de Mexico, Mexico" - }, - { - "author_name": "Angela Cachicatari Beltran", - "author_inst": "HNG Almenara Irigoyen, Lima, Peru" - }, - { - "author_name": "Daniela Alvarez", - "author_inst": "Hospital El Cruce, Provincia Buenos Aires, Argentina" - }, - { - "author_name": "Patricia Oliveira Roveri", - "author_inst": "Hospital Israelita Albert Einstein, Sao Paulo, Brazil" - }, - { - "author_name": "Carlos Rosales Ixcamparij", - "author_inst": "Centro Medico Nacional 20 de Noviembre, Ciudad de Mexico, Mexico" - }, - { - "author_name": "Ender Otoniel Gonzalez", - "author_inst": "TECNISCAN Hospitalia, Ciudad de Guatemala, Guatemala" - }, - { - "author_name": "Pedro Vargas", - "author_inst": "CEDIMAT, Santo Domingo, Republica Dominicana" - }, - { - "author_name": "Maximiliano Flores Flamand", - "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion \"Salvador Zubiran\", Ciudad de Mexico, Mexico" - }, - { - "author_name": "Rosa Lopez Martinez", - "author_inst": "HNG Almenara Irigoyen, Lima, Peru" - }, - { - "author_name": "Luciana Meza", - "author_inst": "Hospital El Cruce, Provincia Buenos Aires, Argentina" - }, - { - "author_name": "Samira Saady Morthy", - "author_inst": "Hospital Israelita Albert Einstein, Sao Pablo, Brazil" - }, - { - "author_name": "Rudy Ovalle", - "author_inst": "TECNISCAN Hospitalia, Ciudad de Guatemala, Guatemala" - }, - { - "author_name": "Stalin Martinez", - "author_inst": "CEDIMAT, Santo Domingo, Republica Dominicana" - }, - { - "author_name": "Oscar Perez Orpinel", - "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion \"Salvador Zubiran\", Ciudad de Mexico, Mexico" - }, - { - "author_name": "Mauricio Potito", - "author_inst": "Hospital El Cruce, Provincia Buenos Aires, Argentina" - }, - { - "author_name": "Otto Orellana", - "author_inst": "TECNISCAN Hospitalia, Ciudad de Guatemala," - }, - { - "author_name": "Jorge Marte Baez", - "author_inst": "CEDIMAT, Santo Domingo, Republica Dominicana" + "author_name": "Sanjat Kanjilal", + "author_inst": "Harvard Medical School / Harvard Pilgrim Healthcare Institute / Brigham & Women's Hospital" }, { - "author_name": "Consuelo Orihuela Sandoval", - "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion \"Salvador Zubiran\", Ciudad de Mexico, Mexico" + "author_name": "Sujata Chalise", + "author_inst": "Brigham & Women's Hospital / Harvard Medical School" }, { - "author_name": "Marcos Granillo Fernandez", - "author_inst": "Hospital El Cruce, Provincia Buenos Aires, Argentina" + "author_name": "Adnan Shami Shah", + "author_inst": "Brigham & Women's Hospital / Harvard Medical School" }, { - "author_name": "Rohit Loomba", - "author_inst": "Advocate Children's Hospital/Rosalind Franklin University of Medicine and Science, Chicago, IL, USA" + "author_name": "Chi-An Cheng", + "author_inst": "Brigham & Women's Hospital / Harvard Medical School" }, { - "author_name": "Saul Flores", - "author_inst": "Texas Children's Hospital/Baylor School of Medicine, Houston, TX, USA" + "author_name": "Yasmeen Senussi", + "author_inst": "Brigham & Women's Hospital / Harvard Medical School" }, { - "author_name": "Jose Maria Hernandez Hernandez", - "author_inst": "Cardiolink Estudios Cardiovasculares, Monterrey, Mexico" + "author_name": "Michael Springer", + "author_inst": "Harvard Medical School" }, { - "author_name": "Ricardo Pignatelli", - "author_inst": "Children`s Hospital, Baylor College of Medicine, Houston, USA" + "author_name": "David R. Walt", + "author_inst": "Brigham and Women's Hospital / Harvard Medical School" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.01.11.22269077", @@ -455395,35 +455202,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2022.01.08.22268950", - "rel_title": "Modelling COVID-19 Vaccine Breakthrough Infections in Highly Vaccinated Israel - the effects of waning immunity and third vaccination dose", + "rel_doi": "10.1101/2022.01.08.22268928", + "rel_title": "Adaptation and validation of a scale to evaluate the quality of virtual courses developed for medical students in Peru during the COVID-19 pandemic", "rel_date": "2022-01-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.08.22268950", - "rel_abs": "In August 2021, a major wave of the SARS-CoV-2 Delta variant erupted in the highly vaccinated population of Israel. The Delta variant has a transmission advantage over the Alpha variant, and thus replaced it in approximately two months. The outbreak led to an unexpectedly large proportion of breakthrough infections (BTI)-- a phenomenon that received worldwide attention. The BTI proportion amongst cases in the age group of 60+ years reached levels as high as [~]85% in August 2021. Most of the Israeli population, especially those 60+ age, received their second dose of the vaccination, four months before the invasion of the Delta variant. Hence, either the vaccine induced immunity dropped significantly or the Delta variant possesses immunity escaping abilities. In this work, we analyzed and model age-structured cases, vaccination coverage, and vaccine BTI data obtained from the Israeli Ministry of Health, to help understand the epidemiological factors involved in the outbreak. We propose a mathematical model which captures a multitude of factors, including age structure, the time varying vaccine efficacy, time varying transmission rate, BTIs, reduced susceptibility and infectivity of vaccinated individuals, protection duration of the vaccine induced immunity, and the vaccine distribution. We fitted our model to the cases among vaccinated and unvaccinated, for <60 and 60+ age groups, to address the aforementioned factors. We found that the transmission rate was driven by multiple factors including the invasion of Delta variant and the mitigation measures. Through a model reconstruction of the reproductive number R0(t), it was found that the peak transmission rate of the Delta variant was 1.96 times larger than the previous Alpha variant. The model estimated that the vaccine efficacy dropped significantly from >90% to [~]40% over 6 months, and that the immunity protection duration has a peaked Gamma distribution (rather than exponential). We further performed model simulations quantifying the important role of the third vaccination booster dose in reducing the levels of breakthrough infections. This allowed us to explore \"what if\" scenarios should the booster not have been rolled out. Application of this framework upon invasion of new pathogens, or variants of concern, can help elucidate important factors in the outbreak dynamics and highlight potential routes of action to mitigate their spread.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.08.22268928", + "rel_abs": "BackgroundDuring the COVID-19 pandemic, medical education migrated to digital environments, without clear guidelines for virtual courses or evaluations of how these courses have been developed.\n\nObjectiveTo adapt and validate a scale to evaluate the quality of virtual courses developed for human medicine students in Peru.\n\nMethodsCross-sectional study that adapted a scale to assess the quality of virtual courses to the context of Peruvian medical students during the COVID-19 pandemic, using the Delphi methodology and pilot tests for a rigorous evaluation of the items, resulting in a scale of 30 items that were described with summary statistics. In addition to the exploratory factor analysis (EFA) with Oblimin rotation, together with the adequacy and sample fit with Bartlett test and Kaiser-Meyer-Olkin (KMO), while the internal consistency was estimated with the alpha coefficient.\n\nResultsA total of 297 medical students in Peru were surveyed. The descriptive statistics for the items showed a normal distribution, while the Bartlett test showed no inadequacy (X2=6134.34, p<0.01) and with the KMO test an overall value greater than 0.92 was found, therefore an AFE was performed where five factors were identified (General Quality and Didactic Methodology, Design and Navigation of the Virtual Platform, Multimedia Resources, Academic Materials) with 30 items. In the internal consistency, an alpha coefficient greater than 0.85 was estimated for the factors evaluated.\n\nConclusionsThe adapted scale of 30 items grouped into five factors or domains, show adequate evidence of validity and reliability to be used in the evaluation of the quality of virtual courses developed for Peruvian human medicine students during the context of the COVID-19 pandemic.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Anyin Feng", - "author_inst": "Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China" + "author_name": "Claudio Intimayta-Escalante", + "author_inst": "Sociedad Cientifica de San Fernando (SCSF), Universidad Nacional Mayor de San Marcos, Lima, Peru" }, { - "author_name": "Uri Obolski", - "author_inst": "School of Public Health, Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Rubi Plasencia-Duenas", + "author_inst": "Sociedad Cientifica de Estudiantes de Medicina de la Universidad Nacional Pedro Ruiz Gallo - SOCIEM UNPRG, Lambayeque, Peru" }, { - "author_name": "Lewi Stone", - "author_inst": "Porter School of the Environment and Earth Sciences, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel" + "author_name": "Kevin Alexis Flores-Lovon", + "author_inst": "Universidad Nacional de San Agustin de Arequipa, Arequipa, Peru" }, { - "author_name": "Daihai He", - "author_inst": "Department of Applied Mathematics, The Hong Kong Polytechnic University, Hong Kong, China" + "author_name": "Janeth N. Nunez-Lupaca", + "author_inst": "Universidad Nacional Jorge Basadre Grohmann, Tacna, Peru" + }, + { + "author_name": "Mario Chavez-Hermosilla", + "author_inst": "Sociedad Cientifica de San Fernando (SCSF), Universidad Nacional Mayor de San Marcos, Lima, Peru" + }, + { + "author_name": "Ronald Castillo-Blanco", + "author_inst": "Universidad del Pacifico, Lima, Peru" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "medical education" }, { "rel_doi": "10.1101/2022.01.07.22268729", @@ -457328,101 +457143,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2022.01.05.22268777", - "rel_title": "Persistence of immunity and impact of a third (booster) dose of an inactivated SARS-CoV-2 vaccine, BBV152; a phase 2, double-blind, randomised controlled trial", + "rel_doi": "10.1101/2022.01.07.22268919", + "rel_title": "Effectiveness of mRNA-1273 against SARS-CoV-2 omicron and delta variants", "rel_date": "2022-01-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.05.22268777", - "rel_abs": "BackgroundNeutralising antibody responses to SARS-CoV-2 vaccines have been reported to decline within 6 months of vaccination, particularly against Variants of Concern (VOC). We assessed the immunogenicity and safety of a booster dose of BBV152 administered 6 months after the second of a two-dose primary vaccination series.\n\nMethodsIn an ongoing phase 2 trial (ClinicalTrials.gov: NCT04471519) the protocol was amended after six months to re-consent and randomise 184 previously vaccinated participants to receive a third dose of vaccine or placebo on Day 215. The primary outcome was to measure neutralising antibody titres by plaque-reduction neutralisation test (PRNT50) four weeks after the booster; safety as serious adverse events (SAE) was the key secondary outcome.\n\nFindingsFour weeks after a second BBV152 vaccination geometric mean titres (GMTs) of neutralising antibodies were 197{middle dot}0 PRNT50 (95% CI: 155{middle dot}6-249{middle dot}4); this level declined to 23{middle dot}9 PRNT50 (14{middle dot}0-40{middle dot}6) six months later, with a seroconversion rate of 75{middle dot}4% (95% CI: 68{middle dot}4-81{middle dot}6). Four weeks after booster vaccination the GMT increased on Day 243 to 746{middle dot}6 PRNT50 (514{middle dot}9-1081) compared with 100{middle dot}7 PRNT50 (43{middle dot}6-232{middle dot}6) in the placebo group. Corresponding seroconversion rates were 98{middle dot}7% (92{middle dot}8-99{middle dot}9) and 79{middle dot}8% (69{middle dot}6-87{middle dot}8). Increased titres in the placebo group were attributed to natural infection as the study was conducted during the second wave of COVID-19 in India. PRNT50 titres against the SARS-CoV-2 variants increased--Alpha (32{middle dot}6-fold), Beta (161{middle dot}0-fold), Delta (264{middle dot}7-fold), and Delta plus (174{middle dot}2-fold)--after the booster vaccination. We found that vaccine induces both memory B and T cells with a distinct AIM+ specific CD4+T central and effector memory phenotype, including CD8+ TEMRA phenotype. Reactogenicity after vaccine and placebo was minimal and comparable, and no SAEs were reported.\n\nInterpretationSix months after a two-dose BBV152 vaccination series cell mediated immunity and neutralising antibodies to both homologous (D614G) and heterologous strains (Alpha, Beta, Delta and Delta plus) persisted above baseline, although the magnitude of the responses had declined. Neutralising antibodies against homologous and heterologous SARS-CoV-2 variants increased 19- to 97-fold after a third vaccination. Booster BBV152 vaccination is safe and may be necessary to ensure persistent immunity to prevent breakthrough infections.\n\nFundingThis work was supported and funded by Bharat Biotech International Limited.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.07.22268919", + "rel_abs": "SARS-CoV-2 omicron (B.1.1.529) variant is highly transmissible with potential immune escape. We conducted a test-negative case-control study to evaluate mRNA-1273 vaccine effectiveness (VE) against infection and hospitalization with omicron or delta. The large, diverse study population included 26,683 SARS-CoV-2 test-positive cases with variant determined by spike gene status (16% delta, 84% omicron). The 2-dose VE against omicron infection at 14-90 days was 44.0% (95% CI, 35.1-51.6%) but declined quickly. The 3-dose VE was 93.7% (92.2-94.9%) and 86.0% (78.1-91.1%) against delta infection and 71.6% (69.7-73.4%) and 47.4% (40.5-53.5%) against omicron infection at 14-60 days and >60 days, respectively. The 3-dose VE was 29.4% (0.3-50.0%) against omicron infection in immunocompromised individuals. The 3-dose VE against hospitalization with delta or omicron was >99%. Our findings demonstrate high, durable 3-dose VE against delta infection but lower effectiveness against omicron infection, particularly among immunocompromised people. However, 3-dose VE was high against hospitalization with delta or omicron.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Krishna Mohan Vadrevu", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Brunda Ganneru", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Siddharth Reddy", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Harsh Jogdand", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Raju Dugyala", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Usha Praturi", - "author_inst": "Bharat Biotech" - }, - { - "author_name": "Gajanan N Sapkal", - "author_inst": "ICMR-National Institute of Virology" + "author_name": "Hung Fu Tseng", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Pragya Yadav", - "author_inst": "ICMR-National Institute of Virology" + "author_name": "Bradley K Ackerson", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Prabhakar Reddy", - "author_inst": "Nizam's Institute of Medical Sciences" + "author_name": "Yi Luo", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Savita Verma", - "author_inst": "P t B D Sharma, PGIMS/UHS Rohtak" + "author_name": "Lina S Sy", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Chandramani Singh", - "author_inst": "AIIMS-Patna" + "author_name": "Carla Talarico", + "author_inst": "Moderna Inc" }, { - "author_name": "Sagar Vivek Redkar", - "author_inst": "Redkar Hospital" + "author_name": "Yun Tian", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Chandra Sekhar Gillurkar", - "author_inst": "Gillurkar Multispecilaity Hospitals, Nagpur" + "author_name": "Katia Bruxvoort", + "author_inst": "University of Alabama at Birmingham" }, { - "author_name": "Jitendra Singh Kushwaha", - "author_inst": "Prakhar Hospital" + "author_name": "Julia E Tupert", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Satyajit Mohapatra", - "author_inst": "SRM Medical College Hospital & Research center, Tamilnadu" + "author_name": "Ana Florea", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Amit Bhate", - "author_inst": "Jeevan Rekha Hospital, Belagavi" + "author_name": "Jennifer H Ku", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Sanjay Rai", - "author_inst": "AIIMS-New Delhi" + "author_name": "Gina S Lee", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Raches Ella", - "author_inst": "Independent Clinical Development Consultant" + "author_name": "Soon Kyu Choi", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Priya Abraham", - "author_inst": "Indian Council of Medical Research-National Institute of Virology" + "author_name": "Harpreet S Takhar", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Sai Prasad", - "author_inst": "Bharat Biotech" + "author_name": "Michael Aragones", + "author_inst": "Kaiser Permanente Southern California" }, { - "author_name": "Krishna Ella", - "author_inst": "Bharat Biotech" + "author_name": "Lei Qian", + "author_inst": "Kaiser Permanente Southern California" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -459130,29 +458921,65 @@ "category": "primary care research" }, { - "rel_doi": "10.1101/2022.01.05.22268808", - "rel_title": "Adherence of SARS-CoV-2 delta variant to surgical mask and N95 respirators", + "rel_doi": "10.1101/2022.01.06.22268809", + "rel_title": "Mental health assessment of Israeli adolescents before and during the COVID-19 pandemic", "rel_date": "2022-01-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.05.22268808", - "rel_abs": "The use of facial protection, including masks and respirators, has been adopted globally due to the COVID-19 pandemic. These products have been demonstrated to be effective in reducing the transmission of the virus. To determine whether or not the virus adheres to masks and respirators, we dissected four respirators and one surgical mask into layers. These individual layers were contaminated with the SARS-CoV-2 delta variant, and its release by vortexing was performed. Samples were used to infect Vero cells, and a plaque assay was used to determine to evaluate the adherence of the virus. Results showed that a cumulative log reduction of the layers reduced the load of the virus six-folds. Our study confirms the effectiveness of facial protection in reducing the transmission and or infection of the virus.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.06.22268809", + "rel_abs": "ImportanceAdolescents mental health and well-being were severely compromised during the COVID-19 pandemic. Longitudinal follow-up studies, based on real-world data, assessing the changes in mental health of adolescents during the later phase of the COVID-19 pandemic are needed.\n\nObjectiveTo quantify the effect of COVID-19 on the incidence of Israeli adolescents mental health outcomes from electronic health record (EHR) data.\n\nDesign, Setting and ParticipantsRetrospective cohort study analyzing EHR data of Maccabi Healthcare Services members, the second largest Health Maintenance Organization in Israel. Eligible subjects were 12-17 years old, during 2017-2021 with no previous diagnosis or psychiatric drug dispensation of those analyzed in this study. This resulted in over 200,000 eligible participants each year.\n\nExposureCOVID-19 pandemic and the measures taken to mitigate it.\n\nMain Outcomes and MeasuresIncidence rates of mental health diagnoses (depression; anxiety; obsessive-compulsive disorder; stress; eating disorders; ADHD), and psychiatric drugs dispensation (antidepressants; anxiolytics; antipsychotics; ADHD agents) were measured, and relative risks were computed between the years. Subgroup analyses were performed for age, gender, population sector and socioeconomic status. Interrupted time series (ITS) analysis evaluated changes in monthly incidence rates of psychiatric outcomes.\n\nResultsDuring the COVID-19 period a 36% increase was observed in the incidence of depression (95%CI: 25-47), 31% in anxiety (95%CI: 23-39), 20% in stress (95%CI: 13-27), 50% in eating disorders (95%CI: 35-67), 25% in antidepressants (95%CI: 25-33) and 28% in antipsychotics dispensation (95%CI: 18-40). Decreased rate of 26% (95% CI: 0.80-0.88) was observed in ADHD diagnoses and 10% (95% CI: 0.86-0.93) in prescriptions of ADHD agents. The increase was mostly attributed to females in the general Israeli population; nevertheless, a 24% increase in anxiety was seen in males (95%CI: 13-37), 64% in Israeli Arabs (95%CI: 12-140) and 31% in ultra-orthodox (95%CI: 3-67). ITS analysis revealed a significantly higher growth in the incidence of psychiatric outcomes during the COVID-19 period, compared to previous years.\n\nConclusions and RelevanceEHR data of adolescents shows increased incidence rates of mental health diagnoses and medications during the COVID-19 pandemic, specifically identified females as those with the highest mental health burden. Our study highlights that the deteriorating mental health of children should be considered by decision-makers when actions and policies are put in place entering the third year of the pandemic.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSHas the COVID-19 pandemic and the strategies to contain it affected adolescents mental health?\n\nFindingsIn this retrospective cohort study of over 200,000 adolescents 12-17 years old, the incidence rates of several measured mental health diagnoses and psychiatric medications increased significantly during the COVID-19 pandemic compared to the period before. This increase was mostly attributed to females.\n\nMeaningThis real-world study highlights the deterioration of adolescents mental health during the COVID-19 pandemic and suggests that the mental health of this young population should be considered during management and health policy decision making.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Ana C Lorenzo-Leal", - "author_inst": "University of British Columbia" + "author_name": "Yonatan Bilu", + "author_inst": "KI Research Institute" }, { - "author_name": "Selvarani Vimalanathan", - "author_inst": "University of British Columbia" + "author_name": "Natalie Flaks-Manov", + "author_inst": "KI Research Institute" }, { - "author_name": "Horacio Bach", - "author_inst": "University of British Columbia" + "author_name": "Maytal Bivas-Benita", + "author_inst": "KI Research Institute" + }, + { + "author_name": "Pinchas Akiva", + "author_inst": "KI Research Institute" + }, + { + "author_name": "Nir Kalkstein", + "author_inst": "KI Research Institute" + }, + { + "author_name": "Yoav Yehezkelli", + "author_inst": "KI Research Institute" + }, + { + "author_name": "Miri Mizrahi-Reuveni", + "author_inst": "Maccabi Healthcare Services" + }, + { + "author_name": "Anat Ekka-Zohar", + "author_inst": "Maccabi Healthcare Services" + }, + { + "author_name": "Shirley Shapiro Ben David", + "author_inst": "Maccabi Healthcare Services" + }, + { + "author_name": "Uri Lerner", + "author_inst": "Maccabi Healthcare Services" + }, + { + "author_name": "Gilad Bodenheimer", + "author_inst": "Maccabi Healthccare Services" + }, + { + "author_name": "Shira Greenfeld", + "author_inst": "Maccabi Healthcare Services" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -460879,75 +460706,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2022.01.04.474979", - "rel_title": "SIRT5 is a proviral factor that interacts with SARS-CoV-2 Nsp14 protein", + "rel_doi": "10.1101/2022.01.05.22268626", + "rel_title": "Fully Vaccinated and Boosted Patients Requiring Hospitalization for COVID-19: an Observational Cohort Analysis", "rel_date": "2022-01-05", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.04.474979", - "rel_abs": "SARS-CoV-2 non-structural protein Nsp14 is a highly conserved enzyme necessary for viral replication. Nsp14 forms a stable complex with non-structural protein Nsp10 and exhibits exoribonuclease and N7-methyltransferase activities. Protein-interactome studies identified human sirtuin 5 (SIRT5) as a putative binding partner of Nsp14. SIRT5 is an NAD-dependent protein deacylase critical for cellular metabolism that removes succinyl and malonyl groups from lysine residues. Here we investigated the nature of this interaction and the role of SIRT5 during SARS-CoV-2 infection. We showed that SIRT5 stably interacts with Nsp14, but not with Nsp10, suggesting that SIRT5 and Nsp10 are parts of separate complexes. We found that SIRT5 catalytic domain is necessary for the interaction with Nsp14, but that Nsp14 does not appear to be directly deacylated by SIRT5. Furthermore, knock-out of SIRT5 or treatment with specific SIRT5 inhibitors reduced SARS-CoV-2 viral levels in cell-culture experiments. SIRT5 knock-out cells expressed higher basal levels of innate immunity markers and mounted a stronger antiviral response. Our results indicate that SIRT5 is a proviral factor necessary for efficient viral replication, which opens novel avenues for therapeutic interventions.", - "rel_num_authors": 14, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2022.01.05.22268626", + "rel_abs": "ObjectiveReal-world data on the effectiveness of boosters against COVID-19, especially as new variants continue to emerge, is limited. It is our objective to assess demographic, clinical, and outcome variables of patients requiring hospitalization for severe SARS-CoV-2 infection comparing fully vaccinated and boosted (FV&B) and unvaccinated (UV) patients.\n\nMethodsThis multicenter observational cohort analysis compared demographic, clinical, and outcome variables in FV&B and UV adults hospitalized for COVID-19. A sub-analysis of FV&B patients requiring intensive care (ICU) care versus non-ICU care was performed to describe and analyze common symptom presentations, initial vital signs, initial laboratory workup, and pertinent medication use in these two groups.\n\nResultsBetween August 12th, 2021 and December 6th, 2021, 4,571 patient encounters had a primary diagnosis of COVID-19 and required inpatient treatment at an acute-care hospital system in Southeastern Michigan. Of the 4,571 encounters requiring hospitalization, 65(1.4%) were FV&B and 2,935(64%) were UV. FV&B individuals were older (74 [67, 81] vs 58 [45, 70]; p <0.001) with a higher proportion of immunocompromised individuals (32.3% vs 10.4%; p<0.001). Despite a significantly higher baseline risk of in-hospital mortality in the FV&B group compared to the UV (Elixhauser 16 vs 8 (p <0.001)), there was a trend toward lower in-hospital mortality (7.7% vs 12.1%; p=0.38) among FV&B patients. Other severe outcomes followed this same trend, with 7.7% of FV&B vs 11.1% UV patients needing mechanical ventilation and 4.6% vs 10.6% of patients needing vasopressors in each group, respectively (p=0.5 and 0.17).\n\nConclusionsFully vaccinated and boosted individuals requiring hospital-level care for breakthrough COVID-19 tended to have less severe outcomes despite appearing to be higher risk at baseline when compared to unvaccinated individuals during the same time period. Specifically, there was a trend that FV&B group had lower rates of mechanical ventilation, use of vasopressors, and in-hospital mortality. As COVID-19 continues to spread, larger expansive trials are needed to further identify risk factors for severe outcomes among the FV&B population.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Marius Walter", - "author_inst": "Buck Institute for Research on Aging, Novato, CA, United States." - }, - { - "author_name": "Irene P Chen", - "author_inst": "Gladstone Institutes, San Francisco, CA, United States; University of California San Francisco, San Francisco, CA, United States." - }, - { - "author_name": "Albert Vallejo-Gracia", - "author_inst": "Gladstone Institutes, San Francisco, CA, United States; University of California San Francisco, San Francisco, CA, United States." - }, - { - "author_name": "Ik-Jung Kim", - "author_inst": "Buck Institute for Research on Aging, Novato, CA, United States." - }, - { - "author_name": "Olga Bielska", - "author_inst": "Buck Institute for Research on Aging, Novato, CA, United States." - }, - { - "author_name": "Victor L Lam", - "author_inst": "University of California San Francisco, San Francisco, CA, United States." - }, - { - "author_name": "Jennifer M Hayashi", - "author_inst": "Gladstone Institutes, San Francisco, CA, United States; University of California San Francisco, San Francisco, CA, United States." - }, - { - "author_name": "Andrew Cruz", - "author_inst": "Buck Institute for Research on Aging, Novato, CA, United States." - }, - { - "author_name": "Samah Shah", - "author_inst": "Buck Institute for Research on Aging, Novato, CA, United States." - }, - { - "author_name": "John D Gross", - "author_inst": "University of California San Francisco, San Francisco, CA, United States; Quantitative Biosciences Institute (QBI), University of California San Francisco, San " - }, - { - "author_name": "Nevan J Krogan", - "author_inst": "University of California San Francisco, San Francisco, CA, United States; Quantitative Biosciences Institute (QBI), University of California San Francisco, San " - }, - { - "author_name": "Birgit Schilling", - "author_inst": "Buck Institute for Research on Aging, Novato, CA, United States." + "author_name": "Nicholas Mielke", + "author_inst": "Oakland University William Beaumont School of Medicine" }, { - "author_name": "Melanie Ott", - "author_inst": "Gladstone Institutes, San Francisco, CA, United States; University of California San Francisco, San Francisco, CA, United States." + "author_name": "Steven Johnson", + "author_inst": "Beaumont Hospital" }, { - "author_name": "Eric Verdin", - "author_inst": "Buck Institute for Research on Aging, Novato, CA, United States." + "author_name": "Amit Bahl", + "author_inst": "Beaumont Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2022.01.04.22268652", @@ -462805,75 +462588,87 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2022.01.04.474803", - "rel_title": "A synthetic bispecific antibody capable of neutralizing SARS-CoV-2 Delta and Omicron", + "rel_doi": "10.1101/2022.01.03.474779", + "rel_title": "Host kinase CSNK2 is a target for inhibition of pathogenic \u03b2-coronaviruses including SARS-CoV-2", "rel_date": "2022-01-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.04.474803", - "rel_abs": "Bispecific antibodies have emerged as a promising strategy for curtailing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) immune escape. This brief report highlights RBT-0813 (also known as TB493-04), a synthetic, humanized, receptor-binding domain (RBD)-targeted bispecific antibody that retains picomolar affinity to the Spike (S) trimers of all major variants of concern and neutralizes both SARS-CoV-2 Delta and Omicron in vitro.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2022.01.03.474779", + "rel_abs": "Inhibition of the protein kinase CSNK2 with any of 30 specific and selective inhibitors representing different chemotypes, blocked replication of pathogenic human and murine {beta}-coronaviruses. The potency of in-cell CSNK2A target engagement across the set of inhibitors correlated with antiviral activity and genetic knockdown confirmed the essential role of the CSNK2 holoenzyme in {beta}-coronavirus replication. Spike protein uptake was blocked by CSNK2A inhibition, indicating that antiviral activity was due in part to a suppression of viral entry. CSNK2A inhibition may be a viable target for development of new broad spectrum anti-{beta}-coronavirus drugs.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC=\"FIGDIR/small/474779v3_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (19K):\norg.highwire.dtl.DTLVardef@5d2799org.highwire.dtl.DTLVardef@1d2de35org.highwire.dtl.DTLVardef@fa852eorg.highwire.dtl.DTLVardef@13da300_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Tom Z Yuan", - "author_inst": "Twist Bioscience" + "author_name": "Xuan Yang", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Carolina Lucas", - "author_inst": "Yale University" + "author_name": "Rebekah J Dickmander", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Valter S Monteiro", - "author_inst": "Yale University" + "author_name": "Armin Bayati", + "author_inst": "Montreal Neurological Institute" }, { - "author_name": "Akiko Iwasaki", - "author_inst": "Yale University, Howard Huges Medical Institute" + "author_name": "Sharon A Taft-Benz", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Marisa L Yang", - "author_inst": "Twist Bioscience" + "author_name": "Jeffrey L Smith", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Hector F Nepita", - "author_inst": "Twist Bioscience" + "author_name": "Carrow I Wells", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Ana G Lujan Hernandez", - "author_inst": "Twist Bioscience" + "author_name": "Emily A Madden", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Joseph M Taft", - "author_inst": "EHT Zurich" + "author_name": "Jason W Brown", + "author_inst": "Takeda San Diego" }, { - "author_name": "Lester Frei", - "author_inst": "ETH Zurich" + "author_name": "Erik M Lenarcic", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Sai T Reddy", - "author_inst": "ETH Zurich" + "author_name": "Boyd L Yount Jr.", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Edcon Chang", + "author_inst": "Takeda San Diego" }, { - "author_name": "Cedric Weber", - "author_inst": "Alloy Therapeutics" + "author_name": "Alison D Axtman", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Kevin P Malobisky", - "author_inst": "Revelar Biotherapeutics" + "author_name": "Ralph S Baric", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Rodrigo Mesquita", - "author_inst": "Revelar Biotherapeutics" + "author_name": "Mark T Heise", + "author_inst": "University of North Carolina at Chapel Hill" }, { - "author_name": "Aaron Sato", - "author_inst": "Twist Bioscience" + "author_name": "Peter S McPherson", + "author_inst": "Montreal Neurological Institute" + }, + { + "author_name": "Nathaniel J Moorman", + "author_inst": "University of North Carolina at Chapel Hill" + }, + { + "author_name": "Timothy M Willson", + "author_inst": "University of North Carolina at Chapel Hill" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "cell biology" }, { "rel_doi": "10.1101/2022.01.03.474855", @@ -464743,39 +464538,31 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.12.30.474580", - "rel_title": "SARS-CoV-2 entry sites are present in all structural elements of the human glossopharyngeal and vagal nerves: clinical implications", + "rel_doi": "10.1101/2021.12.30.474613", + "rel_title": "Nonself Mutations in the Spike Protein Suggest an Increase in the Antigenicity and a Decrease in the Virulence of the Omicron Variant of SARS-CoV-2", "rel_date": "2022-01-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.30.474580", - "rel_abs": "Severe acute respiratory syndrome coronavirus (SARS-CoV-2) infections result in the temporary loss of smell and taste (anosmia and dysgeusia) in about one third of confirmed cases. Several investigators have reported that the viral spike protein receptor is present in olfactory neurons. However, no study has been published to date showing the presence of viral entry sites angiotensin-converting enzyme 2 (ACE2), neuropilin1 (NRP1), and TMPRSS2, the serine protease necessary for priming the viral proteins, in human nerves that are responsible for taste sensation (cranial nerves: VII, IX and X). We used immunocytochemistry to examine three postmortem donor samples of the IXth (glossopharyngeal) and Xth (vagal) cranial nerves where they leave/join the medulla from three donors to confirm the presence of ACE2, NRP1 and TMPRSS2. Two samples were paraffin embedded; one was a frozen sample. In addition to staining sections from the latter, we isolated RNA from it, made cDNA, and performed PCR to confirm the presence of the mRNAs that encode the proteins visualized. All three of the proteins required for SARS-CoV-2 infections appear to be present in the human IXth and Xth nerves near the medulla. Direct infection of these nerves by the COVID-19 virus is likely to cause the loss of taste experienced by many patients. In addition, potential viral spread through these nerves into the adjacent brainstem respiratory centers might also aggravate the respiratory problems patients are experiencing.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.30.474613", + "rel_abs": "Despite extensive worldwide vaccination, the current COVID-19 pandemic caused by SARS-CoV-2 continues. The Omicron variant is a recently emerged variant of concern and is now taking over the Delta variant. To characterize the potential antigenicity of the Omicron variant, we examined the distributions of SARS-CoV-2 nonself mutations (in reference to the human proteome) as 5 amino acid stretches of short constituent sequences (SCSs) in the Omicron and Delta proteomes. The number of nonself SCSs did not differ much throughout the Omicron, Delta, and Reference Sequence (RefSeq) proteomes but markedly increased in the receptor binding domain (RBD) of the Omicron spike protein compared to those of the Delta and RefSeq proteins. In contrast, the number of nonself SCSs decreased in non-RBD regions in the Omicron spike protein, compensating for the increase in the RBD. Several nonself SCSs were tandemly present in the RBD of the Omicron spike protein, likely as a result of selection for higher binding affinity to the ACE2 receptor (and hence higher infectivity and transmissibility) at the expense of increased antigenicity. Taken together, the present results suggest that the Omicron variant has evolved to have higher antigenicity and less virulence in humans despite increased infectivity and transmissibility.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Lynn Vitale-Cross", - "author_inst": "NIDCR, NIH" - }, - { - "author_name": "Ildiko Szalayova", - "author_inst": "NIDCR, NIH" - }, - { - "author_name": "Aiden Scoggins", - "author_inst": "NIDCR, NIH" + "author_name": "Joji M. Otaki", + "author_inst": "University of the Ryukyus" }, { - "author_name": "Miklos Palkovits", - "author_inst": "Human Brain Tissue Bank, Semmelweis University, Budapest, Hungary" + "author_name": "Wataru Nakasone", + "author_inst": "University of the Ryukyus" }, { - "author_name": "Eva Mezey", - "author_inst": "NIDCR, NIH" + "author_name": "Morikazu Nakamura", + "author_inst": "University of the Ryukyus" } ], "version": "1", - "license": "cc0", + "license": "cc_by", "type": "new results", - "category": "neuroscience" + "category": "immunology" }, { "rel_doi": "10.1101/2021.12.31.21268587", @@ -466865,43 +466652,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.31.21268596", - "rel_title": "Social isolation and psychological distress among southern US college students in the era of COVID-19", + "rel_doi": "10.1101/2021.12.29.21268505", + "rel_title": "Head-to-head comparison of nasal and nasopharyngeal sampling using SARS-CoV-2 rapid antigen testing in Lesotho", "rel_date": "2022-01-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.31.21268596", - "rel_abs": "ObjectiveTo examine the prevalence of psychological distress and its association with social isolation among University of North Carolina Chapel Hill (UNC-CH) students.\n\nMethodsA cross-sectional survey was emailed to all students in June 2020. Students reported self-isolating none, some, most, or all of the time and were screened for clinically significant symptoms of depression (CSSD). Data were weighted to the UNC-CH population.\n\nResults7,012 students completed surveys-64% reported self-isolating most or all of the time and 64% reported CSSD. Compared to those self-isolating none of the time, students self-isolating some of the time were 1.78 (95% CI 1.37-2.30) times as likely to report CSSD, and students self-isolating most and all of the time were 2.12 (95% CI 1.64-2.74) and 2.27 (95% CI 1.75-2.94) times as likely to report CSSD, respectively.\n\nConclusionsUniversities should prioritize student mental health and prepare support services to mitigate mental health consequences of the pandemic.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.29.21268505", + "rel_abs": "ObjectivesTo assess the real-world diagnostic performance of nasal and nasopharyngeal swabs for SD Biosensor STANDARD Q COVID-19 Antigen Rapid Diagnostic Test (Ag-RDT).\n\nMethodsIndividuals [≥]5 years with COVID-19 compatible symptoms or history of exposure to SARS-CoV-2 presenting at hospitals in Lesotho received two nasopharyngeal and one nasal swab. Ag-RDT from nasal and nasopharyngeal swabs were performed as point-of-care on site, the second nasopharyngeal swab used for polymerase chain reaction (PCR) as the reference standard.\n\nResultsOut of 2198 participants enrolled, 2131 had a valid PCR result (61% female, median age 41 years, 8% children), 84.5% were symptomatic. Overall PCR positivity rate was 5.8%. The sensitivity for nasopharyngeal, nasal, and combined nasal and nasopharyngeal Ag-RDT result was 70.2% (95%CI: 61.3-78.0), 67.3% (57.3-76.3) and 74.4% (65.5-82.0), respectively. The respective specificity was 97.9% (97.1-98.4), 97.9% (97.2-98.5) and 97.5% (96.7-98.2). For both sampling modalities, sensitivity was higher in participants with symptom duration [≤] 3days versus [≤] 7days. Agreement between nasal and nasopharyngeal Ag-RDT was 99.4%.\n\nConclusionsThe STANDARD Q Ag-RDT showed high specificity. Sensitivity was, however, below the WHO recommended minimum requirement of [≥] 80%. The high agreement between nasal and nasopharyngeal sampling suggests that for Ag-RDT nasal sampling is a good alternative to nasopharyngeal sampling.\n\nHighlights- Prospective study on real-world diagnostic performance of nasal and nasopharyngeal SD Biosensor STANDARD Q COVID-19 Ag Test in 2131 participants in a rural African setting\n- The sensitivity of the STANDARD Q COVID-19 Ag Test was below the World Health Organization requirement of [≥] 80% but met the specificity requirement of [≥]97%.\n- Sensitivity was higher in the following subpopulations: persons with symptoms [≤]3 days, and Ct value < 25.\n- In head-to-head comparison nasal and nasopharyngeal sampling had comparable sensitivity and specificity and an overall test agreement of 99.4%, indicating that the more convenient nasal sampling could be used for SARS-CoV-2 rapid antigen tests.\n- 24 of the 2131 participants with COVID-19 symptoms had pulmonary tuberculosis with a positive Xpert Ultra test on sputum.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Danielle Giovenco", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Niklaus Daniel Labhardt", + "author_inst": "Swiss Tropical and Public Health Institute" }, { - "author_name": "Bonnie E Shook-Sa", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Lucia Gonzalez Fernandez", + "author_inst": "Swiss Tropical and Public Health Institute" }, { - "author_name": "Bryant Hutson", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Bulemba Katende", + "author_inst": "SolidarMed, Partnerships for Health" }, { - "author_name": "Laurie Buchanan", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Josephine Muhairwe", + "author_inst": "SolidarMed, Partnerships for Health" }, { - "author_name": "Edwin B Fisher", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Moniek Bresser", + "author_inst": "Swiss Tropical and Public Health Institute" }, { - "author_name": "Audrey Pettifor", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Alain Amstutz", + "author_inst": "Swiss Tropical and Public Health Institute" + }, + { + "author_name": "Tracy R Glass", + "author_inst": "Swiss Tropical and Public Health Institute" + }, + { + "author_name": "Morten Ruhwald", + "author_inst": "Foundation for Innovative New Diagnostics (FIND)" + }, + { + "author_name": "Jilian A Sacks", + "author_inst": "Foundation for Innovative New Diagnostics (FIND)" + }, + { + "author_name": "Camille Escadafal", + "author_inst": "Foundation for Innovative New Diagnostics" + }, + { + "author_name": "Mathabo Mareka", + "author_inst": "Ministry of Health of Lesotho" + }, + { + "author_name": "Mooko Sekhele Mookho", + "author_inst": "Ministry of Health of Lesotho" + }, + { + "author_name": "Margaretha Daniel de Vos", + "author_inst": "Foundation for Innovative New Diagnostics" + }, + { + "author_name": "Klaus Reither", + "author_inst": "Swiss Tropical and Public Health Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.31.21268575", @@ -468879,105 +468698,97 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.12.30.474453", - "rel_title": "Preserved T cell reactivity to the SARS-CoV-2 Omicron variant indicates continued protection in vaccinated individuals.", + "rel_doi": "10.1101/2021.12.29.474491", + "rel_title": "Molecular probes of spike ectodomain and its subdomains for SARS-CoV-2 variants, Alpha through Omicron", "rel_date": "2021-12-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.30.474453", - "rel_abs": "ImportanceThe emergence of the highly contagious Omicron variant of SARS-CoV-2 and the findings of a significantly reduced neutralizing potency of sera from convalescent or vaccinated individuals imposes the study of cellular immunity to predict the degree of immune protection to the yet again new coronavirus.\n\nDesignProspective monocentric observational study.\n\nSettingConducted between December 20-21 at the Santa Lucia Foundation IRCCS.\n\nParticipants61 volunteers (Mean age 41.62, range 21-62; 38F/23M) with different vaccination and SARS-CoV-2 infection backgrounds donated 15 ml of blood. Of these donors, one had recently completed chemotherapy, and one was undergoing treatment with monoclonal antibodies; the others reported no known health issue.\n\nMain Outcome(s) and Measure(s)The outcomes were the measurement of T cell reactivity to the mutated regions of the Spike protein of the Omicron SARS-CoV-2 variant and the assessment of remaining T cell immunity to the spike protein by stimulation with peptide libraries.\n\nResultsLymphocytes from freshly drawn blood samples were isolated and immediately tested for reactivity to the Spike protein of SARS-CoV-2. T cell responses to peptides covering the mutated regions in the Omicron variant were decreased by over 47% compared to the same regions of the ancestral vaccine strain. However, overall reactivity to the peptide library of the full-length protein was largely maintained (estimated 83%). No significant differences in loss of immune recognition were identified between groups of donors with different vaccination and/or infection histories.\n\nConclusions and RelevanceWe conclude that despite the mutations in the Spike protein, the SARS-CoV-2 Omicron variant is nonetheless recognized by the cellular component of the immune system. It is reasonable to assume that protection from hospitalization and severe disease is maintained.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDoes the Omicron variant of SARS-CoV-2 escape cellular immunity?\n\nFindingsThis observational study was performed on 61 vaccinated donors with established immunity to SARS-CoV-2. Cellular responses to the mutated regions of the Omicron Spike protein were detected in 80% of donors. The mutations reduced T cell recognition by 47% compared to the vaccine strain. Reactivity to the whole Spike protein, however, was present in 100% of donors, and the fraction of remaining immunity to SARS-CoV-2 was estimated to be 83%.\n\nMeaningCellular immunity to the Omicron variant is maintained despite the mutations in its Spike protein, and may thus confer protection from severe COVID-19 in vaccinated individuals.", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.29.474491", + "rel_abs": "Since the outbreak of the COVID-19 pandemic, widespread infections have allowed SARS-CoV-2 to evolve in human, leading to the emergence of multiple circulating variants. Some of these variants show increased resistance to vaccines, convalescent plasma, or monoclonal antibodies. In particular, mutations in the SARS-CoV-2 spike have drawn attention. To facilitate the isolation of neutralizing antibodies and the monitoring the vaccine effectiveness against these variants, we designed and produced biotin-labeled molecular probes of variant SARS-CoV-2 spikes and their subdomains, using a structure-based construct design that incorporated an N-terminal purification tag, a specific amino acid sequence for protease cleavage, the variant spike-based region of interest, and a C-terminal sequence targeted by biotin ligase. These probes could be produced by a single step using in-process biotinylation and purification. We characterized the physical properties and antigenicity of these probes, comprising the N-terminal domain (NTD), the receptor-binding domain (RBD), the RBD and subdomain 1 (RBD-SD1), and the prefusion-stabilized spike ectodomain (S2P) with sequences from SARS-CoV-2 variants of concern or of interest, including variants Alpha, Beta, Gamma, Epsilon, Iota, Kappa, Delta, Lambda, Mu, and Omicron. We functionally validated probes by using yeast expressing a panel of nine SARS-CoV-2 spike-binding antibodies and confirmed sorting capabilities of variant probes using yeast displaying libraries of plasma antibodies from COVID-19 convalescent donors. We deposited these constructs to Addgene to enable their dissemination. Overall, this study describes a matrix of SARS-CoV-2 variant molecular probes that allow for assessment of immune responses, identification of serum antibody specificity, and isolation and characterization of neutralizing antibodies.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Lorenzo De Marco", - "author_inst": "Santa Lucia Foundation IRCCS; Rome, Italy." - }, - { - "author_name": "Marta Pirronello", - "author_inst": "Santa Lucia Foundation IRCCS; Rome, Italy." - }, - { - "author_name": "Alice Verdiani", - "author_inst": "Santa Lucia Foundation IRCCS; Rome, Italy." + "author_name": "I-Ting Teng", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Andrea Termine", - "author_inst": "Fondazione Santa Lucia IRCCS, Rome, Italy" + "author_name": "Misook Choe", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Carlo Fabrizio", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Tracy Liu", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Alessia Capone", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Matheus Oliveira de Souza", + "author_inst": "University of Kansas" }, { - "author_name": "Andrea Sabatini", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Yuliya Petrova", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Gisella Guerrera", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Yaroslav Tsybovsky", + "author_inst": "Frederick National Laboratory for Cancer Research" }, { - "author_name": "Roberta Placido", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Shuishu Wang", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Manolo Sambucci", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Baoshan Zhang", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Daniela F Angelini", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Mykhaylo Artamonov", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Flavia Giannessi", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Bharat Madan", + "author_inst": "University of Kansas" }, { - "author_name": "Mario Picozza", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Aric Huang", + "author_inst": "University of Kansas" }, { - "author_name": "Carlo Caltagirone", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Sheila N. Lopez Acevedo", + "author_inst": "University of Kansas" }, { - "author_name": "Antonino Salvia", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Xiaoli Pan", + "author_inst": "University of Kansas" }, { - "author_name": "Elisabetta Volpe", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Tracy J. Ruckwardt", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Maria Pia Balice", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Brandon J. DeKosky", + "author_inst": "University of Kansas" }, { - "author_name": "Angelo Rossini", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "John R. Mascola", + "author_inst": "Vaccine Research Center, NIAID, NIH" }, { - "author_name": "Olaf Rotzschke", - "author_inst": "Singapore Immunology Network, Agency for Science, Technology and Research, Singapore, Singapore" + "author_name": "John Misasi", + "author_inst": "National Institutes of Health" }, { - "author_name": "Emiliano Giardina", - "author_inst": "Santa Lucia Foundation, Rome, Italy; Tor Vergata University, Rome, Italy" + "author_name": "Nancy Sullivan", + "author_inst": "VRC, NIH" }, { - "author_name": "Luca Battistini", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Tongqing Zhou", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Giovanna Borsellino", - "author_inst": "Santa Lucia Foundation, Rome, Italy" + "author_name": "Peter D. Kwong", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" } ], "version": "1", - "license": "cc_no", + "license": "cc0", "type": "new results", "category": "immunology" }, @@ -470961,59 +470772,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.12.28.21268472", - "rel_title": "Neutralizing antibody responses to SARS-CoV-2: a population based seroepidemiological analysis in Delhi, India", + "rel_doi": "10.1101/2021.12.22.21268176", + "rel_title": "A preliminary study of commercially available general-purpose chest radiography artificial intelligence-based software for detecting airspace opacity lesions in COVID-19 patients", "rel_date": "2021-12-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.28.21268472", - "rel_abs": "We conducted this study to estimate seroprevalence of neutralizing antibodies in the general population and to further correlate it with the IgG SARS-CoV-2 IgG levels. This present cross-sectional analysis was conducted as a sequel to a state level community-based seroepidemiological study in Delhi, India. A total of 2564 seropositive samples were selected from 25622 seropositive samples through simple random sampling. Neutralizing capacity was estimated by performing a surrogate virus neutralization test with the sVNT (GenScript) assay. Neutralizing antibody against the SARS-CoV-2 virus was operationally considered as detected when the signal inhibition was [≥]30%.\n\nA total of 2233 (87.1%, 95% C.I. 85.7, 88.3) of the 2564 SARS-CoV-2 seropositive samples had detectable neutralizing antibodies. On bi-variate analysis but not on adjusted analysis, Covid-19 vaccination showed a statistically significant association with the presence of neutralizing antibodies (p<0.001). The signal/ cut off (S/CO) of SARS-CoV-2 IgG ranged from 1.00 to 22.8 (median 11.40). In samples with S/CO [≥]4.00, the neutralizing antibodies ranged from 94.5 to 100%, while in samples with S/CO <4.00, it ranged from 52.0 to 79.2%. The neutralizing antibody seroprevalence strongly correlated with the S/CO range (r=0.62, p=0.002). In conclusion, in populations with high SARS-CoV-2 seroprevalence, neutralizing antibodies are generated in nearly 9 of 10 seropositive individuals.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268176", + "rel_abs": "PurposeTo validate commercially available general-purpose artificial intelligence (AI)-based software for detecting airspace opacity in chest radiographs (CXRs) of COVID-19 patients.\n\nMaterials and MethodsWe used the ieee8023-covid-chestxray-dataset to validate commercial AI software capable of detecting \"Nodule/Mass\" and \"Airspace opacity\" as regions of interest with probability scores. From this dataset, we excluded computed tomography images and CXR images taken using an anteroposterior spine view and analyzed CXR images tagged with \"Pneumonia/Viral/COVID-19\" and \"no findings.\" A radiologist then reviewed the images and rated them on a 3-point opacity score for the presence of airspace opacity. The maximum probability score of airspace opacity for each image was calculated using this software. The difference in each maximum probability for each opacity score was evaluated using Wilcoxons rank sum test. The threshold of the probability score was determined by receiver operator characteristic curve analysis for the presence or absence of COVID-19, and the true positive rate (TPR) and false positive rate (FPR) were determined for the individual and overall opacity scores.\n\nResultsImages from 342 patients with COVID-19 and 15 normal images were included. Opacity scores of 1, 2, and 3 were observed in 44, 70, and 243 images, respectively, of which 33 (75%), 66 (94.2%), and 243 (100%), respectively, were from COVID-19 patients. The overall TPR and FPR were 0.82 and 0.13, respectively, at an area under the curve of 0.88 and a threshold of 0.06, while the FPR for opacity score 1 was 0.18 and the TPR for score 3 was 0.97.\n\nConclusionUsing a public database containing CXR images of COVID-19 patients, commercial AI software was shown to be able to detect airspace opacity in severe pneumonia.\n\nSummaryCommercially available AI software was capable of detecting airspace opacity in CXR images of COVID-19 patients in a public database.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Pragya Sharma", - "author_inst": "Maulana Azad Medical College, New Delhi" - }, - { - "author_name": "Ekta Gupta", - "author_inst": "Institute of Liver and Biliary Sciences" - }, - { - "author_name": "Saurav Basu", - "author_inst": "Maulana Azad Medical College, New Delhi; Indian Institute of Public Health - Delhi" - }, - { - "author_name": "Reshu Aggarwal", - "author_inst": "Institute of Liver and Biliary Sciences" - }, - { - "author_name": "Suruchi Mishra", - "author_inst": "Maulana Azad Medical College, New Delhi" - }, - { - "author_name": "Pratibha Kale", - "author_inst": "Institute of Liver and Biliary Sciences, New Delhi" - }, - { - "author_name": "Nutan Mundeja", - "author_inst": "Directorate General Health Services, Government of NCT, Delhi" + "author_name": "Munemura Suzuki", + "author_inst": "Plusman LLC" }, { - "author_name": "B S Charan", - "author_inst": "Directorate General Health Services, Government of NCT, Delhi" + "author_name": "Aruta Niimura", + "author_inst": "Plusman LLC" }, { - "author_name": "Gautam Kumar Singh", - "author_inst": "Directorate General Health Services, Government of NCT, Delhi" + "author_name": "Yusuke Nakamura", + "author_inst": "Plusman LLC" }, { - "author_name": "Mongjam MEGHACHANDRA SINGH", - "author_inst": "Maulana Azad Medical College, New Delhi" + "author_name": "Yujiro Otsuka", + "author_inst": "Plusman LLC" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2021.12.27.21268455", @@ -473115,123 +472902,127 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.12.27.474273", - "rel_title": "Structures of the Omicron Spike trimer with ACE2 and an anti-Omicron antibody", + "rel_doi": "10.1101/2021.12.28.474359", + "rel_title": "In contrast to TH2-biased approaches, TH1 COVID-19 vaccines protect Syrian hamsters from severe disease in the absence of dexamethasone-treatable vaccine-associated enhanced respiratory pathology", "rel_date": "2021-12-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.27.474273", - "rel_abs": "The Omicron variant of SARS-CoV-2 has rapidly become the dominant infective strain and the focus efforts against the ongoing COVID-19 pandemic. Here we report an extensive set of structures of the Omicron spike trimer by its own or in complex with ACE2 and an anti-Omicron antibody. These structures reveal that most Omicron mutations are located on the surface of the spike protein, which confer stronger ACE2 binding by nearly 10 folds but become inactive epitopes resistant to many therapeutic antibodies. Importantly, both RBD and the closed conformation of the Omicron spike trimer are thermodynamically unstable, with the melting temperature of the Omicron RBD decreased by as much as 7{degrees}C, making the spiker trimer prone to random open conformations. An unusual RBD-RBD interaction in the ACE2-spike complex unique to Omicron is observed to support the open conformation and ACE2 binding, serving the basis for the higher infectivity of Omicron. A broad-spectrum therapeutic antibody JMB2002, which has completed Phase 1 clinical trial, is found to interact with the same two RBDs to inhibit ACE2 binding, in a mode that is distinguished from all previous antibodies, thus providing the structural basis for the potent inhibition of Omicron by this antibody. Together with biochemical data, our structures provide crucial insights into higher infectivity, antibody evasion and inhibition of Omicron.", - "rel_num_authors": 26, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.28.474359", + "rel_abs": "Since December 2019, the novel human coronavirus SARS-CoV-2 has spread globally, causing millions of deaths. Unprecedented efforts have enabled development and authorization of a range of vaccines, which reduce transmission rates and confer protection against the associated disease COVID-19. These vaccines are conceptually diverse, including e.g. classical adjuvanted whole-inactivated virus, viral vectors, and mRNA vaccines.\n\nWe have analysed two prototypic model vaccines, the strongly TH1-biased measles vaccine-derived candidate MeVvac2-SARS2-S(H) and a TH2-biased Alum-adjuvanted, non-stabilized Spike (S) protein side-by-side, for their ability to protect Syrian hamsters upon challenge with a low-passage SARS-CoV-2 patient isolate. As expected, the MeVvac2-SARS2-S(H) vaccine protected the hamsters safely from severe disease. In contrast, the protein vaccine induced vaccine-associated enhanced respiratory disease (VAERD) with massive infiltration of eosinophils into the lungs. Global RNA-Seq analysis of hamster lungs revealed reduced viral RNA and less host dysregulation in MeVvac2-SARS2-S(H) vaccinated animals, while S protein vaccination triggered enhanced host gene dysregulation compared to unvaccinated control animals. Of note, mRNAs encoding the major eosinophil attractant CCL-11, the TH2 response-driving cytokine IL-19, as well as TH2-cytokines IL-4, IL-5, and IL-13 were exclusively up-regulated in the lungs of S protein vaccinated animals, consistent with previously described VAERD induced by RSV vaccine candidates. IL-4, IL-5, and IL-13 were also up-regulated in S-specific splenocytes after protein vaccination. Using scRNA-Seq, T cells and innate lymphoid cells were identified as the source of these cytokines, while Ccl11 and Il19 mRNAs were expressed in lung macrophages displaying an activated phenotype. Interestingly, the amount of viral reads in this macrophage population correlated with the abundance of Fc-receptor reads. These findings suggest that VAERD is triggered by induction of TH2-type helper cells secreting IL-4, IL-5, and IL-13, together with stimulation of macrophage subsets dependent on non-neutralizing antibodies. Via this mechanism, uncontrolled eosinophil recruitment to the infected tissue occurs, a hallmark of VAERD immunopathogenesis. These effects could effectively be treated using dexamethasone and were not observed in animals vaccinated with MeVvac2-SARS2-S(H).\n\nTaken together, our data validate the potential of TH2-biased COVID-19 vaccines and identify the transcriptional mediators that underlie VAERD, but confirm safety of TH1-biased vaccine concepts such as vector-based or mRNA vaccines. Dexamethasone, which is already in use for treatment of severe COVID-19, may alleviate such VAERD, but in-depth scrutiny of any next-generation protein-based vaccine candidates is required, prior and after their regulatory approval.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Wanchao Yin", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Aileen Ebenig", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Youwei Xu", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Samada Muraleedharan", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Peiyu Xu", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Julia Kazmierski", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Xiaodan Cao", - "author_inst": "Jemincare" + "author_name": "Daniel Todt", + "author_inst": "Department of Molecular and Medical Virology, Ruhr-University Bochum" }, { - "author_name": "Canrong Wu", - "author_inst": "Shanghai" + "author_name": "Arne Auste", + "author_inst": "Paul-Ehrlich-Institut; German Center for Infection Research, Giessen-Marburg-Langen" }, { - "author_name": "Chunyin Gu", - "author_inst": "Shanghai Jemincare Pharmaceuticals Co., Ltd." + "author_name": "Martina Anzaghe", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Xinheng He", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Andr\u00e9 G\u00f6mer", + "author_inst": "Department for Molecular and Medical Virology, Ruhr-University Bochum; Institute of Virology, University of Veterinary Medicine Hannover" }, { - "author_name": "Xiaoxi Wang", - "author_inst": "Shanghai Institute of Materia Medica Chinese Academy of Sciences" + "author_name": "Dylan Postmus", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "Sijie Huang", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Patricia Gogesch", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Qingning Yuan", - "author_inst": "The Shanghai Advanced Electron Microscope Center" + "author_name": "Marc Niles", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Kai Wu", - "author_inst": "The Shanghai Advanced Electron Microscope Center" + "author_name": "Roland Plesker", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Wen Hu", - "author_inst": "The Shanghai Advanced Electron Microscope Center" + "author_name": "Csaba Miskey", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Zifu Huang", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Michelle Gellhorn Serra", + "author_inst": "Institute for Virology, Phillipps-University Marburg" }, { - "author_name": "Jia Liu", - "author_inst": "Shanghai Jemincare Pharmaceuticals Co., Ltd." + "author_name": "Angele Breithaupt", + "author_inst": "Friedrich-Loeffler-Institut, Federal Research Institute for Animal Health" }, { - "author_name": "Zongda Wang", - "author_inst": "Shanghai Jemincare Pharmaceuticals Co., Ltd." + "author_name": "Cindy H\u00f6rner", + "author_inst": "Paul-Ehrlich-Institut; German Center for Infection Research, Giessen-Marburg-Langen" }, { - "author_name": "Fangfang Jia", - "author_inst": "Shanghai Jemincare Pharmaceuticals Co., Ltd." + "author_name": "Carina Kruip", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Kaiwen Xia", - "author_inst": "Shanghai Jemincare Pharmaceuticals Co., Ltd." + "author_name": "Rosina Ehmann", + "author_inst": "Institute for Microbiology, Bundeswehr" }, { - "author_name": "Peipei Liu", - "author_inst": "Shanghai Jemincare Pharmaceuticals Co., Ltd." + "author_name": "Zoltan Ivics", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Xueping Wang", - "author_inst": "Shanghai Jemincare Pharmaceuticals Co., Ltd." + "author_name": "Zoe Waibler", + "author_inst": "Paul-Ehrlich-Institut" }, { - "author_name": "Bin Song", - "author_inst": "Immunological Disease Research Center" + "author_name": "Stephanie Pfaender", + "author_inst": "Department for Molecular & Medical Virology, Ruhr-Universit\u00e4t Bochum, Germany" }, { - "author_name": "Jie Zheng", - "author_inst": "Immunological Disease Research Center" + "author_name": "Emanuel Wyler", + "author_inst": "Max Delbruck Center for Molecular Medicine" }, { - "author_name": "Hualiang Jiang", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Markus Landthaler", + "author_inst": "Max-Delbrueck Center for Molecular Medicine" }, { - "author_name": "Xi Cheng", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Alexandra Kupke", + "author_inst": "Institute for Virology, Phillipps-University Marburg; German Center for Infection Research, Giessen-Marbrug-Langen" }, { - "author_name": "Yi Jiang", - "author_inst": "Shanghai Institute of Materia Medica Chinese Academy of Sciences" + "author_name": "Geraldine Nouailles", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Corporate Member of Freie Universit\u00e4t Berlin and Humboldt-Universit\u00e4t zu Berlin, Division of Pulmonary Inflammation, Depar" }, { - "author_name": "Su-Jun Deng", - "author_inst": "Shanghai Jemincare Pharmaceuticals Co., Ltd." + "author_name": "Christine GOFFINET", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin" }, { - "author_name": "H. Eric Xu", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Richard J.P. Brown", + "author_inst": "Paul-Ehrlich-Institut" + }, + { + "author_name": "Michael D M\u00fchlebach", + "author_inst": "Paul-Ehrlich-Institut" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "immunology" }, { "rel_doi": "10.1101/2021.12.23.474030", @@ -475693,59 +475484,59 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2021.12.20.21268066", - "rel_title": "Persisting Chemosensory Impairments in 366 Healthcare Workers Following COVID-19: An 11-Month Follow-up.", + "rel_doi": "10.1101/2021.12.26.21268358", + "rel_title": "Can individuals with low antibody responses to vaccines against other viruses acquire adequate SARS-CoV-2 antibody after vaccination with the BNT162b2 mRNA vaccine?", "rel_date": "2021-12-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.20.21268066", - "rel_abs": "Background and ObjectivesOlfactory and gustatory dysfunctions (OD, GD) are prevalent symptoms following COVID-19 and persist in 6%-44% of individuals in the first months after the infection. As only few reports have described their prognosis more than 6 months later, the main objective of this study was to assess the prevalence of OD and GD 11 months after COVID-19. We also aimed to determine test-retest reliability of subjective chemosensory ratings for the follow-up of chemosensory sensitivity, as this measure is often used for remote follow-up.\n\nMethodsInclusion criteria included a PCR-confirmed SARS-CoV-2 infection; exclusion criteria were the presence of other respiratory infections and chronic sinusitis. To assess whether OD and GD had changed compared to pre-pandemic levels, we designed an observational study and distributed an online questionnaire assessing quantitative chemosensory function to healthcare workers 5 and 11 months after COVID-19. Specifically, we assessed olfaction, gustation, and trigeminal sensitivity (10-point visual analog scale) and function (4-point Likert scale) separately. We further assessed clinically relevant OD using the Chemosensory Perception Test, a psychophysical test designed to provide a reliable remote olfactory evaluation. Qualitative chemosensory dysfunction was also assessed.\n\nResultsWe included a total of 366 participants (mean age of 44.8 years old (SD: 11.7)). They completed the last online questionnaire 10.6 months (SD: 0.7) after the onset of COVID-19 symptoms. Of all participants, 307 (83.9%) and 301 (82.2%) individuals retrospectively reported lower olfactory or gustatory sensitivity during the acute phase of COVID-19. Eleven months later, 184 (50.3%) and 163 (44.5%) indicated reduced chemosensory sensitivity, 32.2% reported impairment of olfactory function while 24.9% exhibited clinically relevant OD. Three variables predicted OD at follow-up, namely chest pain and GD during COVID-19 and presence of phantosmia at 5 months. Olfactory sensitivity ratings had a high test-retest reliability (intraclass correlation coefficient: 0.818 (95% CI: 0.760 - 0.860))\n\nDiscussionThis study suggests that chemosensory dysfunctions persist in a third of COVID-19 patients 11 months after COVID-19. Subjective measures have a high test-retest reliability and thus can be used to monitor post-COVID-19 OD. OD appears to be a common long-term symptom of COVID-19 important to consider when treating patients.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.26.21268358", + "rel_abs": "ObjectiveIn Japan, healthcare workers (HCWs) are vaccinated against contagious viruses (measles, rubella, chickenpox, mumps, and hepatitis B) to prevent nosocomial infection; however, some do not produce sufficient antibodies (suboptimal responders). Whether suboptimal responders to live attenuated viruses or inactivated viruses vaccines can produce adequate antibodies to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNA vaccines remains to be elucidated.\n\nMethodsIn this prospective cohort study, SARS-CoV-2 anti-spike antibodies were measured 11 times, from before the first BNT162b2 vaccination to 5 months after the second vaccination. Antibody titers of suboptimal and normal responders were compared. SARS-CoV-2 neutralizing antibody activity was measured twice in suboptimal responders, 1 week to 1 month, and 5 months after the second vaccination.\n\nPatientsThis study included 50 HCWs who received two doses of mRNA BNT162b2 vaccine 3 weeks apart.\n\nResultsAfter vaccination, the SARS-CoV-2 anti-spike antibody was detectable in the samples from suboptimal and normal responders at each timepoint. The median SARS-CoV-2 anti-spike antibody titer was higher in suboptimal responders than in normal responders 1 week after receiving the second dose of BNT162b2 vaccine (3721.0 vs. 2251.5, P=0.029). Suboptimal responders had SARS-CoV-2 neutralizing antibody activity 1 week to 1 month, and 5 months after the second vaccination, which exceeded the positive threshold 5 months after the second vaccination.\n\nConclusionAfter BNT162b2 vaccination, suboptimal responders acquired adequate SARS-CoV-2 anti-spike and SARS-CoV-2 neutralizing antibodies to prevent SARS-CoV-2. These results suggest that vaccination with mRNA vaccine against SARS-CoV-2 should also be recommended for suboptimal responders to conventional vaccines.", "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Nicholas Bussiere", - "author_inst": "Universite du Quebec a Trois-Rivieres" + "author_name": "Wataru Ogura", + "author_inst": "Department of Clinical Laboratory, Kyorin University Hospital" }, { - "author_name": "Jie Mei", - "author_inst": "Universite du Quebec a Trois-Rivieres" + "author_name": "Kouki Ohtsuka", + "author_inst": "Department of Laboratory Medicine, Kyorin University School of Medicine" }, { - "author_name": "Cindy Levesque-Boissonneault", - "author_inst": "Universite du Quebec a Trois-Rivieres" + "author_name": "Sachiko Matsuura", + "author_inst": "Department of Clinical Laboratory, Kyorin University Hospital" }, { - "author_name": "Mathieu Blais", - "author_inst": "Centre de recherche CHU de Quebec Universite Laval" + "author_name": "Takahiro Okuyama", + "author_inst": "Department of Clinical Laboratory, Kyorin University Hospital" }, { - "author_name": "Sara Carazo", - "author_inst": "Centre de Recherche CHU de Quebec - Universite Laval" + "author_name": "Satsuki Matsushima", + "author_inst": "Department of Laboratory Medicine, Kyorin University School of Medicine" }, { - "author_name": "Francois Gros-Louis", - "author_inst": "Centre de recherche CHU de Quebec Universite Laval" + "author_name": "Satoko Yamasaki", + "author_inst": "Department of Laboratory Medicine, Kyorin University School of Medicine" }, { - "author_name": "Robert Laforce Jr.", - "author_inst": "Centre de recherche CHU de Quebec Universite Laval" + "author_name": "Hiroyuki Miyagi", + "author_inst": "Department of Clinical Laboratory, Kyorin University Hospital" }, { - "author_name": "Gaston DeSerres", - "author_inst": "Centre de recherche CHU de Quebec Universite Laval" + "author_name": "Kumiko Sekiguchi", + "author_inst": "Department of Clinical Laboratory, Kyorin University Hospital" }, { - "author_name": "Nicolas Dupre", - "author_inst": "Centre de recherche CHU de Quebec Universite Laval" + "author_name": "Hiroaki Ohnishi", + "author_inst": "Department of Laboratory Medicine, Kyorin University School of Medicine" }, { - "author_name": "Johannes Frasnelli", - "author_inst": "Universite du Quebec a Trois-Rivieres" + "author_name": "Takashi Watanabe", + "author_inst": "Department of Laboratory Medicine, Kyorin University School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "otolaryngology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.23.21268040", @@ -477515,75 +477306,23 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2021.12.23.21268276", - "rel_title": "Risk of myocarditis following sequential COVID-19 vaccinations by age and sex", + "rel_doi": "10.1101/2021.12.24.21268373", + "rel_title": "Are COVID-19 data reliable? The case of the European Union", "rel_date": "2021-12-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.23.21268276", - "rel_abs": "In an updated self-controlled case series analysis of 42,200,614 people aged 13 years or more, we evaluate the association between COVID-19 vaccination and myocarditis, stratified by age and sex, including 10,978,507 people receiving a third vaccine dose. Myocarditis risk was increased during 1-28 days following a third dose of BNT162b2 (IRR 2.02, 95%CI 1.40, 2.91). Associations were strongest in males younger than 40 years for all vaccine types with an additional 3 (95%CI 1, 5) and 12 (95% CI 1,17) events per million estimated in the 1-28 days following a first dose of BNT162b2 and mRNA-1273, respectively; 14 (95%CI 8, 17), 12 (95%CI 1, 7) and 101 (95%CI 95, 104) additional events following a second dose of ChAdOx1, BNT162b2 and mRNA-1273, respectively; and 13 (95%CI 7, 15) additional events following a third dose of BNT162b2, compared with 7 (95%CI 2, 11) additional events following COVID-19 infection. An association between COVID-19 infection and myocarditis was observed in all ages for both sexes but was substantially higher in those older than 40 years. These findings have important implications for public health and vaccination policy.\n\nFundingHealth Data Research UK.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.24.21268373", + "rel_abs": "Previous studies have used Benfords distribution to assess whether there is misreporting of COVID-19 cases and deaths. Data inaccuracies provide false information to the media, undermine global response, and hinder the preventive measures taken by countries worldwide. In this study, daily new cases and deaths from all the countries of the European Union were analyzed and the conformance to Benfords distribution was estimated. For each country, two statistical tests and two measures of deviation were calculated to determine whether the reported statistics comply with the expected distribution. Four country-level developmental indexes were also included, the GDP per capita, health expenditures, the Universal Health Coverage index, and the full vaccination rate. Regression analysis was implemented to show whether the deviation from Benfords distribution is affected by the aforementioned indexes. The findings indicate that four countries were in line with the expected distribution, Bulgaria, Croatia, Lithuania, and Romania. For the daily cases, Denmark, Greece, and Ireland, showed the greatest deviation from Benfords distribution and for deaths, Malta, Cyprus, Greece, Italy, and Luxemburg exhibited the highest deviation from Benfords law. Furthermore, it was found that the vaccination rate is positively associated with deviation from Benfords distribution. These results suggest that overall, official data provided by authorities are not confirming Benfords law, yet this approach is not conclusive; it acts as a preliminary tool for data verification. More extensive studies should be made with a more thorough investigation of countries that showed the greatest deviation.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Martina Patone", - "author_inst": "University of Oxford" - }, - { - "author_name": "Winnie Xue Mei", - "author_inst": "University of Oxford" - }, - { - "author_name": "Lahiru Handunnetthi", - "author_inst": "University of Oxford" - }, - { - "author_name": "Sharon Dixon", - "author_inst": "University of Oxford" - }, - { - "author_name": "Francesco Zaccardi", - "author_inst": "University of Leicester" - }, - { - "author_name": "Manu Shankar-Hari", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Peter Watkinson", - "author_inst": "University of Oxford" - }, - { - "author_name": "Kamlesh Khunti", - "author_inst": "University of Leicester" - }, - { - "author_name": "Anthony Harnden", - "author_inst": "University of Oxford" - }, - { - "author_name": "Carol AC Coupland", - "author_inst": "University of Oxford" - }, - { - "author_name": "Keith M. Channon", - "author_inst": "University of Oxford" - }, - { - "author_name": "Nicholas L Mills", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Aziz Sheikh", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Julia Hippisley-Cox", - "author_inst": "University of Oxford" + "author_name": "Pavlos Kolias", + "author_inst": "Aristotle University of Thessaloniki" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.12.23.474055", @@ -479393,47 +479132,87 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2021.12.22.21268045", - "rel_title": "Essential Workers COVID-19 Vaccine Hesitancy, Misinformation and Informational Needs in the Republic of North Macedonia.", + "rel_doi": "10.1101/2021.12.22.21268268", + "rel_title": "CMV seropositivity is a potential novel risk factor for severe COVID-19 in non-geriatric patients", "rel_date": "2021-12-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268045", - "rel_abs": "IntroductionThe COVID-19 pandemic is a global health crisis that as of December 2021 has resulted in the death of over 5.2 million people. Despite the unprecedented development and distribution of vaccines, hesitancy to take the vaccine remains a wide-spread public health challenge, especially in Eastern European countries. In this study we focus on a sample of essential workers living in the Republic of North Macedonia to: 1) Describe rates of vaccine acceptance, risk perception and sources of COVID-19 information, 2) Explore predictors of vaccine hesitancy, and 3) Describe informational needs of hesitant and non-hesitant workers.\n\nMethodsDescriptive statistics were used to present frequencies of vaccine acceptance. Logistic regression was used to explore predictors of vaccine hesitancy based on sociodemographic characteristics, hesitancy to take other vaccines in the past, previous diagnosis of COVID-19, and individual risk perception of getting COVID-19. Chi square analysis was used to compare differences in informational needs between hesitant and non-hesitant individuals across socio-demographic groups.\n\nResultsFrom a sample of 1003 individuals, 439 (44%) reported that they were very likely to get the vaccine, and the rest (66%) reported some level of hesitancy. Older age, Albanian ethnicity, post-secondary school education, previous diagnosis of COVID-19, previous vaccine acceptance of other vaccines, and increased risk perception of COVID-19 infection were all found to be negatively associated with vaccine hesitancy. In particular hesitant individuals, compared to the non-hesitant, wanted to have more information and reassurance that all main international agencies (i.e. FDA, WHO, EMA) were all in accordance in recommending the vaccine and that they would be free to choose if getting the vaccine or not without consequences (p<0.01).", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.22.21268268", + "rel_abs": "BackgroundCOVID-19 has so far affected more than 250 million individuals worldwide, causing more than 5 million deaths. Several risk factors for severe disease have been identified, most of which coincide with advanced age. In younger individuals, severe COVID-19 often occurs in the absence of obvious comorbidities. Guided by the finding of cytomegalovirus (CMV)-specific T cells with some cross-reactivity to SARS-CoV-2 in a COVID-19 intensive care unit (ICU) patient, we decided to investigate whether CMV seropositivity is associated with severe or critical COVID-19.\n\nMethodsNational German COVID-19 bio-sample and data banks were used to retrospectively analyze the CMV serostatus of patients who experienced mild (n=101), moderate (n=130) or severe to critical (n=80) disease by CMV IgG serology. We then investigated the relationship between disease severity and CMV serostatus via statistical models.\n\nResultsNon-geriatric patients (< 70 years) with severe COVID-19 were found to have a very high prevalence of CMV-seropositivity, while CMV status distribution in individuals with mild disease was similar to the prevalence in the German population; interestingly, this was not detectable in older patients. Prediction models support the hypothesis that the CMV serostatus might be a strong biomarker in identifying younger individuals with a higher risk of developing severe COVID-19.\n\nConclusionsWe identified CMV-seropositivity as a potential novel risk factor for severe COVID-19 in non-geriatric individuals in the studied cohorts. More mechanistic analyses as well as confirmation of similar findings in cohorts representing the currently most relevant SARS-CoV-2 variants should be performed shortly.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Stephen Fucaloro", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Simone Weber", + "author_inst": "Institute for Medical Microbiology, Immunology and Hygiene, Technical University of Munich, Munich, Germany" }, { - "author_name": "Vahe Yacoubian", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Victoria Kehl", + "author_inst": "Institute for AI and Informatics in Medicine, School of Medicine, Technical University of Munich, Munich, Germany" }, { - "author_name": "Nigel Harriman", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Johanna Erber", + "author_inst": "Department of Internal Medicine II, University Hospital Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany German Center for " }, { - "author_name": "Rachael Pitch-Loeb", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Karolin I. Wagner", + "author_inst": "Institute for Medical Microbiology, Immunology and Hygiene, Technical University of Munich, Munich, Germany" }, { - "author_name": "Metodi Hadji-Janev", - "author_inst": "University Goce Delcev" + "author_name": "Ana-Marija Jetzlsperger", + "author_inst": "Institute of Virology, School of Medicine, Technical University of Munich, Munich, Germany" }, { - "author_name": "Tea Burmaz", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Theresa Burrell", + "author_inst": "Institute for Medical Microbiology, Immunology and Hygiene, Technical University of Munich, Munich, Germany" }, { - "author_name": "Elena Savoia", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Kilian Schober", + "author_inst": "Institute for Microbiology - Clinical Microbiology, Immunology and Hygiene, University Hospital Erlangen" + }, + { + "author_name": "Philipp Schommers", + "author_inst": "Department I of Internal Medicine, Medical Faculty and University Hospital Cologne, University of Cologne, Cologne, Germany German Center for Infection Research" + }, + { + "author_name": "Max Augustin", + "author_inst": "Department I of Internal Medicine, Medical Faculty and University Hospital Cologne, University of Cologne, Cologne, Germany German Center for Infection Research" + }, + { + "author_name": "Claudia S. Crowell", + "author_inst": "Institute for Medical Microbiology, Immunology and Hygiene, Technical University of Munich, Munich, Germany German Center for Infection Research (DZIF), partner" + }, + { + "author_name": "Markus Gerhard", + "author_inst": "Institute for Medical Microbiology, Immunology and Hygiene, Technical University of Munich, Munich, Germany German Center for Infection Research (DZIF), partner" + }, + { + "author_name": "Christof Winter", + "author_inst": "Institute of Clinical Chemistry and Pathobiochemistry, School of Medicine, Technical University of Munich, Germany" + }, + { + "author_name": "Christoph D Spinner", + "author_inst": "Department of Internal Medicine II, University Hospital Rechts Der Isar, School of Medicine, Technical University of Munich, Munich, Germany German Center for " + }, + { + "author_name": "Ulrike Protzer", + "author_inst": "Institute of Virology, School of Medicine, Technical University of Munich, Munich, Germany" + }, + { + "author_name": "Dieter Hoffmann", + "author_inst": "Institute of Virology, School of Medicine, Technical University of Munich, Munich, Germany" + }, + { + "author_name": "Elvira DIppolito", + "author_inst": "Institute for Medical Microbiology, Immunology and Hygiene, Technical University of Munich, Munich, Germany" + }, + { + "author_name": "Dirk Busch", + "author_inst": "Technical University of Munich" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.23.21268324", @@ -481442,73 +481221,53 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.12.20.473471", - "rel_title": "Nucleocapsid 203 mutations enhance SARS-CoV-2 immune evasion", + "rel_doi": "10.1101/2021.12.21.473268", + "rel_title": "Efficacy of antiviral drugs against the omicron variant of SARS-CoV-2.", "rel_date": "2021-12-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.20.473471", - "rel_abs": "Previous work indicated that the nucleocapsid 203 mutation increase the virulence and transmission of the SARS-CoV-2 Alpha variant. However, Delta later outcompeted Alpha and other lineages, promoting a new wave of infections. Delta also possesses a nucleocapsid 203 mutation, R203M. Large-scale epidemiological analyses suggest a synergistic effect of the 203 mutation and the spike L452R mutation, associated with Delta expansion. Viral competition experiments demonstrate the synergistic effect in fitness and infectivity. More importantly, we found that the combination of R203M and L452R brings in a 3.2-fold decrease in neutralizing titers to the neutralizing serum relative to L452R-only virus. R203M/L452R show an increased fitness after the initiation of global vaccination programmes, possibly associated with the enhanced immune evasion. Another rapidly emerging variant Omicron also bears the 203 mutation. Thus, we proposed that nucleocapsid mutations play an essential role for the rise and predominance of variants in concern.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.21.473268", + "rel_abs": "The Omicron variant of the SARS-CoV-2 virus was first detected in South Africa in November 2021. The analysis of the sequence data in the context of earlier variants suggested that it may show very different characteristics, including immune evasion and increased transmission. These assumptions were partially confirmed, and the reduction in protection in convalescent patients and vaccinated individuals have been confirmed. Here, we have evaluated the efficacy of antivirals against SARS-CoV-2 variants, Omicron, Delta, and the early 2020 isolate.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Xiaoyuan Lin", - "author_inst": "School of Life Sciences, Chongqing University" - }, - { - "author_name": "Weiwei Xue", - "author_inst": "School of Pharmaceutical Sciences, Chongqing University" - }, - { - "author_name": "Yueping Zhang", - "author_inst": "College of Veterinary Medicine, China Agricultural University" - }, - { - "author_name": "Beibei Fu", - "author_inst": "School of Life Sciences, Chongqing University" - }, - { - "author_name": "Jakob Trimpert", - "author_inst": "Institute of Virology, Free University of Berlin" - }, - { - "author_name": "Na Xing", - "author_inst": "Institute of Virology, Free University of Berlin" + "author_name": "Agnieszka Dabrowska", + "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-387, Krakow, Poland" }, { - "author_name": "Dusan Kunec", - "author_inst": "Institute of Virology, Free University of Berlin" + "author_name": "Artur Szczepanski", + "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-387, Krakow, Poland" }, { - "author_name": "Wanyan Tang", - "author_inst": "Chongqing Key Laboratory of Translational Research for Cancer Metastasis and Individualized Treatment, Chongqing University Cancer Hospital" + "author_name": "Pawel Botwina", + "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-387, Krakow, Poland" }, { - "author_name": "Yang Xiao", - "author_inst": "School of Life Sciences, Chongqing University" + "author_name": "Natalia Mazur-Panasiuk", + "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-387, Krakow, Poland" }, { - "author_name": "Kaiwen Meng", - "author_inst": "College of Veterinary Medicine, China Agricultural University" + "author_name": "Helena Jirincova", + "author_inst": "National Reference Laboratory for Influenza and Other Respiratory Viruses, National Institute of Public Health, Srobarova 49/48, 100-00, Prague, Czech Republic." }, { - "author_name": "Shuobo Shi", - "author_inst": "College of Life Science and Technology, Beijing University of Chemical Technology" + "author_name": "Lukasz Rabalski", + "author_inst": "Laboratory of Recombinant Vaccines, Intercollegiate Faculty of Biotechnology of University of Gdansk and Medical University of Gdansk, Abrahama 58, 80-307, Gdan" }, { - "author_name": "Haibo Wu", - "author_inst": "School of Life Sciences, Chongqing University" + "author_name": "Tomas Zajic", + "author_inst": "Liberec Regional Hospital, Husova 357/10, 460 01 Liberec, Czech Republic." }, { - "author_name": "Geng Meng", - "author_inst": "College of Veterinary Medicine, China Agricultural University" + "author_name": "Grzegorz Popowicz", + "author_inst": "Institute of Structural Biology, Helmholtz Zentrum Munchen, Ingolstadter Landstrasse 1, 85764 Neuherberg, Germany." }, { - "author_name": "Zhenglin Zhu", - "author_inst": "School of Life Sciences, Chongqing University" + "author_name": "Krzysztof Pyrc", + "author_inst": "Virogenetics Laboratory of Virology, Malopolska Centre of Biotechnology, Jagiellonian University, Gronostajowa 7A, 30-387, Krakow, Poland" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -483988,27 +483747,99 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.12.19.21268042", - "rel_title": "Government messaging about COVID-19 vaccination in Canada and Australia: a Narrative Policy Framework study", + "rel_doi": "10.1101/2021.12.17.21267976", + "rel_title": "Sputnik Light booster after Sputnik V vaccination induces robust neutralizing antibody response to B.1.1.529 (Omicron) SARS-CoV-2 variant", "rel_date": "2021-12-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.19.21268042", - "rel_abs": "BackgroundStorytelling and narratives are critical components to public policy and have been central to public policy communicators throughout the COVID-19 pandemic.\n\nAimThis study applied the Narrative Policy Framework to compare and contrast the policy narratives of the Canadian and Australian Prime Ministers regarding COVID-19 vaccination.\n\nMethodsOfficial media releases, transcripts and speeches published on the websites of Prime Minister Morrison and Prime Minister Trudeau between 31 August 2020 and 10 September 2021 relating to COVID-19 vaccines were thematically analysed according to the Narrative Policy Framework.\n\nResultsThe policy narratives of Scott Morrison and Justin Trudeau tended towards describing both governments as heroes for securing and rolling out vaccines. Trudeau tended to focus on the villain of COVID-19 while Morrison regularly described other countries as victims of COVID-19 to position Australia as superior in its decision-making. These findings also demonstrate how narratives shifted over time due to changing COVID-19 case numbers, emergence of rare complications associated with the AstraZeneca vaccine and as new information arose.\n\nConclusionThese findings offer lessons for COVID-19 times as well as future pandemics and disease outbreaks by providing insight into how policy narratives influenced policy processes in both Australia and Canada.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.17.21267976", + "rel_abs": "COVID-19 vaccination campaign has been launched around the world. More than 8 billion vaccines doses have been administered, according to the WHO. Published studies shows that vaccination reduces the number of COVID-19 cases and dramatically reduces COVID-19-associated hospitalizations and deaths worldwide. In turn, the emergence of SARS-CoV-2 variants of concern (VOC) with mutations in the receptor-binding domain (RBD) of S glycoprotein poses risks of diminishing the effectiveness of the vaccination campaign. In November 2021, the first information appeared about a new variant of the SARS-CoV-2 virus, which was named Omicron. The Omicron variant is of concern because it contains a large number of mutations, especially in the S glycoprotein (16 mutation in RBD), which could be associated with resistance to neutralizing antibodies (NtAB) and significantly reduce the effectiveness of COVID-19 vaccines. Neutralizing antibodies are one of the important parameters characterizing the protective properties of a vaccine. We conducted a study of neutralizing antibodies in the blood serum of people vaccinated with Sputnik V, as well as those revaccinated with Sputnik Light after Sputnik V. Results showed that a decrease in the level of neutralizing antibodies was observed against SARS-CoV-2 Omicron (B.1.1.529) variant in comparison to B.1.1.1 variant. Analysis of the sera of individuals vaccinated with Sputnik V 6-12 months ago showed that there was a decrease in the level of neutralizing antibodies by 11.76 folds. While no direct comparison with other vaccines declines has been done in this study, we note their reported decline in antibody neutralization at a much more significant level of 40-84 times. At the same time, the analysis of sera of individuals who were vaccinated with Sputnik V, and then revaccinated Sputnik Light, showed that 2-3 months after revaccination the decrease in the level of neutralizing antibodies against the Omicron variant was 7.13 folds. Despite the decrease in NtAb, we showed that all revaccinated individuals had NtAb to Omicron variant. Moreover, the NtAb level to Omicron variant in revaccinated sera are slightly higher than NtAb to B.1.1.1 in vaccinated sera.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Freya Saich", - "author_inst": "University of Sydney" + "author_name": "Inna V Dolzhikova", + "author_inst": "Gamaleya NRCEM" }, { - "author_name": "Alexandra Martiniuk", - "author_inst": "University of Sydney" + "author_name": "Anna A Iliukhina", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Anna V Kovyrshina", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Alexandra V Kuzina", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Vladimir A Gushchin", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Andrey E Siniavin", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Andrey A Pochtovyi", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Elena V Shidlovskaya", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Nadezhda A Kuznetsova", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Manuel M Megeryan", + "author_inst": "SBHI Moscow region Podolsk children's city hospital" + }, + { + "author_name": "Alina S Dzharullaeva", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Alina S Erokhova", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Fatima M Izhaeva", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Daria M Grousova", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Andrey G Botikov", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Dmitry V Shcheblyakov", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Amir I Tukhvatulin", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Olga V Zubkova", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Denis Y Logunov", + "author_inst": "Gamaleya NRCEM" + }, + { + "author_name": "Alexander L Gintsburg", + "author_inst": "Gamaleya NRCEM" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.17.21268008", @@ -486113,121 +485944,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.18.21267628", - "rel_title": "RESISTANCE CONFERRING MUTATIONS IN SARS-CoV-2 DELTA FOLLOWING SOTROVIMAB INFUSION", + "rel_doi": "10.1101/2021.12.17.21267927", + "rel_title": "Evaluation of the Roche SARS-CoV-2 Rapid Antibody Test in samples from vaccinated individuals", "rel_date": "2021-12-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.18.21267628", - "rel_abs": "Several Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) neutralising monoclonal antibodies (mAbs) have received emergency use authorisation by regulatory agencies for treatment and prevention of Coronavirus Disease 2019 (COVID-19), including in patients at risk for progression to severe disease. Here we report the persistence of viable SARS-CoV-2 in patients treated with sotrovimab and the rapid development of spike gene mutations that have been shown to confer high level resistance to sotrovimab in vitro. We highlight the need for SARS-CoV-2 genomic surveillance in at risk individuals to inform stewardship of mAbs use and prevent potential treatment failures.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.17.21267927", + "rel_abs": "ObjectiveThe study aimed to establish the performance of the SARS-CoV-2 Rapid Antibody Test (IgG and IgM) and the Elecsys(R) Anti-SARS-CoV-2 S assay in vaccinated individuals.\n\nMethodsA panel of serum samples from Boca Biolistics was utilized to assess antibodies following vaccination, consisting of samples drawn prior to vaccination, after the first dose, or at least 14 days after the second dose of Moderna mRNA-1273 or Pfizer-BioNTech BNT162b2 COVID-19 vaccines. Agreement between the two methods was measured and stratified by test evaluator and assay lot.\n\nResultsAgreement between the SARS-CoV-2 Rapid Antibody Test (IgG) and Elecsys Anti-SARS-CoV-2 S assay qualitative measurements at the different assessment points for both mRNA-1273 and BNT162b2 ranged between 97.06% (95% confidence interval [CI] 84.67, 99.93) to 100% (95% CI 82.35, 100). Agreement of the SARS-CoV-2 Rapid Antibody Test (IgG) with the Elecsys Anti-SARS-CoV-2 S assay was not highly influenced by either lot or evaluator. There was a medium-to-strong correlation between the semi-quantitative SARS-CoV-2 Rapid Antibody Test (IgG) result and quantitative Elecsys Anti-SARS-CoV-2 S assay in samples taken after both doses of the vaccines, with higher intensity bands being associated with higher total anti-S antibody titer (mRNA-1273, p=0.0019; BNT162b2, p<0.0001).\n\nConclusionSemi-quantitative SARS-CoV-2 Rapid Antibody Test (IgG) and quantitative Elecsys Anti-SARS-CoV-2 S assay correlated well, suggesting that the SARS-CoV-2 Rapid Antibody Test (IgG) is helpful in understanding the immune response post-vaccination. The current data support the use of the SARS-CoV-2 Rapid Antibody Test (IgG) in the vaccinated population.\n\nImportanceSerologic assays are an essential tool for seroprevalence surveys, for quality control of vaccines, and to determine the response to vaccination. Although a correlate of immunity has not yet been established for COVID-19 vaccines, antibody titers after natural infection and vaccination have been associated with protection from symptomatic SARS-CoV-2 infection. Rapid point-of-care assays can be of use in this context with advantages over centralized testing, such as speed and ease of use. The point-of-care SARS-CoV-2 Rapid Antibody Test (IgG) compared favorably to the Elecsys Anti-SARS-CoV-2 S assay with agreement rates above 97.06%, after one or two doses of Moderna mRNA-1273 or Pfizer-BioNTech BNT162b2. Semi-quantitative SARS-CoV-2 Rapid Antibody Test (IgG) and quantitative Elecsys Anti-SARS-CoV-2 S assay results correlated well, suggesting that SARS-CoV-2 Rapid Antibody Test (IgG) is helpful in understanding the immune response post-vaccination. The current data support the use of the SARS-CoV-2 Rapid Antibody Test (IgG) in the vaccinated population.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Rebecca J Rockett", - "author_inst": "Sydney Institute of Infectious Diseases, University of Sydney, Sydney, New South Wales, Australia" - }, - { - "author_name": "Kerri Basile", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Susan Maddocks", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Winkie Fong", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" - }, - { - "author_name": "Jessica E Agius", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" - }, - { - "author_name": "Jessica Johnson-Mackinnon", - "author_inst": "Sydney Institute of Infectious Diseases, University of Sydney, Sydney, New South Wales, Australia" - }, - { - "author_name": "Alicia Arnott", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Shona Chandra", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" - }, - { - "author_name": "Mailie Gall", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" - }, - { - "author_name": "Jenny L Draper", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Elena Martinez", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Eby M Sim", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" - }, - { - "author_name": "Clement Lee", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Christine Ngo", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Marc Ramsperger", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Andrew N Ginn", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Qinning Wang", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Michael Fennell", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Danny Ko", - "author_inst": "Centre for Infectious Diseases and Microbiology Laboratory Services, New South Wales Health Pathology, Institute for Clinical Pathology and Medical Research, We" - }, - { - "author_name": "Ling Lim", - "author_inst": "Parramatta Public Health Unit, Western Sydney Local Health District, Parramatta, New South Wales, Australia" - }, - { - "author_name": "Nicky Gilroy", - "author_inst": "Department of Infectious Diseases, Westmead Hospital, Western Sydney Local Health District, Sydney, New South Wales, Australia" - }, - { - "author_name": "Matthew VN Sullivan", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" - }, - { - "author_name": "Sharon C-A Chen", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" - }, - { - "author_name": "Jen Kok", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" - }, - { - "author_name": "Dominic E Dwyer", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" + "author_name": "Eva Urlaub", + "author_inst": "Roche Diagnostics GmbH" }, { - "author_name": "Vitali L Sintchenko", - "author_inst": "Centre for Infectious Diseases and Microbiology-Public Health, Westmead Hospital, Westmead, New South Wales, Australia" + "author_name": "Johannes Hayer", + "author_inst": "Roche Diagnostics GmbH" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -487999,23 +487734,119 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.12.17.473179", - "rel_title": "Disrupted Peyer's patch microanatomy in COVID-19 including germinal centre atrophy independent of local virus", + "rel_doi": "10.1101/2021.12.17.473180", + "rel_title": "Insights into standards of care: dexamethasone and antibodies against COVID-19 in hamster models", "rel_date": "2021-12-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.17.473179", - "rel_abs": "Confirmed SARS-coronavirus-2 infection with gastrointestinal symptoms and changes in microbiota associated with coronavirus disease 2019 (COVID-19) severity have been previously reported, but the disease impact on the architecture and cellularity of ileal Peyers patches (PP) remains unknown. Here we analysed post-mortem tissues from throughout the gastrointestinal (GI) tract of patients who died with COVID-19. When virus was detected by PCR in the GI tract, immunohistochemistry identified virus in epithelium and lamina propria macrophages, but not in lymphoid tissues. Immunohistochemistry and imaging mass cytometry (IMC) analysis of ileal PP revealed depletion of germinal centres (GC), disruption of B cell/T cell zonation and decreased potential B and T cell interaction and lower nuclear density in COVID-19 patients. This occurred independent of the local viral levels. The changes in PP demonstrate that the ability to mount an intestinal immune response is compromised in severe COVID-19, which could contribute to observed dysbiosis.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.17.473180", + "rel_abs": "RationaleIn face of the ongoing SARS-CoV-2 pandemic, effective and well-understood treatment options are still scarce. While vaccines have proven instrumental in fighting SARS-CoV-2, their efficacy is challenged by vaccine hesitancy, novel variants and short-lasting immunity. Therefore, understanding and optimization of therapeutic options remains essential.\n\nObjectivesWe aimed at generating a deeper understanding on how currently used drugs, specifically dexamethasone and anti-SARS-CoV-2 antibodies, affect SARS-CoV-2 infection and host responses. Possible synergistic effects of both substances are investigated to evaluate combinatorial treatments.\n\nMethodsBy using two COVID-19 hamster models, pulmonary immune responses were analyzed to characterize effects of treatment with either dexamethasone, anti-SARS-CoV-2 spike monoclonal antibody or a combination of both. scRNA sequencing was employed to reveal transcriptional response to treatment on a single cell level.\n\nMeasurements and main resultsDexamethasone treatment resulted in similar or increased viral loads compared to controls. Anti-SARS-CoV-2 antibody treatment alone or combined with dexamethasone successfully reduced pulmonary viral burden. Dexamethasone exhibited strong anti-inflammatory effects and prevented fulminant disease in a severe COVID-19-like disease model. Combination therapy showed additive benefits with both anti-viral and anti-inflammatory potency. Bulk and single-cell transcriptomic analyses confirmed dampened inflammatory cell recruitment into lungs upon dexamethasone treatment and identified a candidate subpopulation of neutrophils specifically responsive to dexamethasone.\n\nConclusionsOur analyses i) confirm the anti-inflammatory properties and indicate possible modes of action for dexamethasone, ii) validate anti-viral effects of anti-SARS-CoV-2 antibody treatment, and iii) reveal synergistic effects of a combination therapy and can thus inform more effective COVID-19 therapies.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Manu Shankar-Hari", - "author_inst": "The University of Edinburgh" + "author_name": "Emanuel Wyler", + "author_inst": "Berlin Institute for Medical Systems Biology (BIMSB), Max Delbruck Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany" + }, + { + "author_name": "Julia M. Adler", + "author_inst": "Institute of Virology, Freie Universit\u00e4t Berlin, Berlin, Germany and Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Division of Pulmonary Inflammation, Berlin, Germany" + }, + { + "author_name": "Kathrin Eschke", + "author_inst": "Institute of Virology, Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Gustavo Teixeira Alves", + "author_inst": "Berlin Institute for Medical Systems Biology (BIMSB), Max Delbruck Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany" + }, + { + "author_name": "Stefan Peidli", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Institute of Pathology, Berlin, Germany and IRI Life Sciences, Institute for Biology, Humboldt-Universit\u00e4t zu Berlin, Berl" + }, + { + "author_name": "Fabian Pott", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Institute of Virology, Berlin, Germany and Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Julia Kazmierski", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Institute of Virology, Berlin, Germany and Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Laura Michalik", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Institute of Physiology, Berlin, Germany" + }, + { + "author_name": "Olivia Kershaw", + "author_inst": "Institute of Veterinary Pathology, Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Judith Bushe", + "author_inst": "Institute of Veterinary Pathology, Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Sandro Andreotti", + "author_inst": "Bioinformatics Solution Center, Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Peter Pennitz", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Division of Pulmonary Inflammation and Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany" + }, + { + "author_name": "Azza Abdelgawad", + "author_inst": "Institute of Virology, Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Dylan Postmus", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Institute of Virology, Berlin, Germany and Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Christine Goffinet", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Institute of Virology, Berlin, Germany and Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Jakob Kreye", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE), and Helmholtz Innovation Lab BaoBab, and Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Department of Neurology and " + }, + { + "author_name": "S. Momsen Reincke", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE), and Helmholtz Innovation Lab BaoBab, and Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Department of Neurology and " + }, + { + "author_name": "Harald Pr\u00fcss", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE), and Helmholtz Innovation Lab BaoBab, and Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Department of Neurology and " + }, + { + "author_name": "Nils Bl\u00fcthgen", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Institute of Pathology, Berlin, Germany and IRI Life Sciences, Institute for Biology, Humboldt-Universit\u00e4t zu Berlin, Berl" + }, + { + "author_name": "Achim D. Gruber", + "author_inst": "Institute of Veterinary Pathology, Freie Universit\u00e4t Berlin, Berlin, Germany" + }, + { + "author_name": "Wolfgang M. Kuebler", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Institute of Physiology, Berlin, Germany" + }, + { + "author_name": "Martin Witzenrath", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Division of Pulmonary Inflammation and Department of Infectious Diseases and Respiratory Medicine, Berlin, Germany" + }, + { + "author_name": "Markus Landthaler", + "author_inst": "Berlin Institute for Medical Systems Biology (BIMSB), Max Delbruck Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany and IRI Lif" + }, + { + "author_name": "Geraldine Nouailles", + "author_inst": "Charit\u00e9 - Universit\u00e4tsmedizin Berlin, Division of Pulmonary Inflammation, Berlin, Germany" + }, + { + "author_name": "Jakob Trimpert", + "author_inst": "Institute of Virology, Freie Universit\u00e4t Berlin, Berlin, Germany" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.12.17.473178", @@ -489657,123 +489488,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.15.472838", - "rel_title": "A third vaccination with a single T cell epitope protects against SARS-CoV-2 infection in the absence of neutralizing antibodies", - "rel_date": "2021-12-18", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.15.472838", - "rel_abs": "Understanding the mechanisms and impact of booster vaccinations can facilitate decisions on vaccination programmes. This study shows that three doses of the same synthetic peptide vaccine eliciting an exclusive CD8+ T cell response against one SARS-CoV-2 Spike epitope protected all mice against lethal SARS-CoV-2 infection in the K18-hACE2 transgenic mouse model in the absence of neutralizing antibodies, while only a second vaccination with this T cell vaccine was insufficient to provide protection. The third vaccine dose of the single T cell epitope peptide resulted in superior generation of effector-memory T cells in the circulation and tissue-resident memory T (TRM) cells, and these tertiary vaccine-specific CD8+ T cells were characterized by enhanced polyfunctional cytokine production. Moreover, fate mapping showed that a substantial fraction of the tertiary effector-memory CD8+ T cells developed from remigrated TRM cells. Thus, repeated booster vaccinations quantitatively and qualitatively improve the CD8+ T cell response leading to protection against otherwise lethal SARS-CoV-2 infection.\n\nSummaryA third dose with a single T cell epitope-vaccine promotes a strong increase in tissue-resident memory CD8+ T cells and fully protects against SARS-CoV-2 infection, while single B cell epitope-eliciting vaccines are unable to provide protection.", - "rel_num_authors": 26, + "rel_doi": "10.1101/2021.12.16.21267959", + "rel_title": "Social mixing patterns relevant to infectious diseases spread by close contact in urban Blantyre, Malawi.", + "rel_date": "2021-12-17", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.16.21267959", + "rel_abs": "IntroductionUnderstanding human mixing patterns relevant to infectious diseases spread through close contact is vital for modelling transmission dynamics and optimisation of disease control strategies. Mixing patterns in low-income countries like Malawi are not well understood.\n\nMethodologyWe conducted a social mixing survey in urban Blantyre, Malawi between April and July 2021 (between the 2nd and 3rd wave of COVID-19 infections). Participants living in densely-populated neighbourhoods were randomly sampled and, if they consented, reported their physical and non-physical contacts within and outside homes lasting at least 5 minutes during the previous day. Age-specific mixing rates were calculated, and a negative binomial mixed effects model was used to estimate determinants of contact behaviour.\n\nResultsOf 1,201 individuals enrolled, 702 (58.5%) were female, the median age was 15 years (interquartile range [IQR] 5-32) and 127 (10.6%) were HIV-positive. On average, participants reported 10.3 contacts per day (range: 1-25). Mixing patterns were highly age-assortative, particularly those within the community and with skin-to-skin contact. Adults aged 20-49y reported the most contacts (median:11, IQR: 8-15) of all age groups; 38% (95%CI: 16-63) more than infants (median: 8, IQR: 5-10), who had the least contacts. Household contact frequency increased by 3% (95%CI 2-5) per additional household member. Unemployed participants had 15% (95%CI: 9-21) fewer contacts than other adults. Among long range (>30 meters away from home) contacts, secondary school children had the largest median contact distance from home (257m, IQR 78-761). HIV-positive status in adults >18 years-old was not associated with increased contact patterns (1%, 95%CI -9-12). During this period of relatively low COVID-19 incidence in Malawi, 301 (25.1%) individuals stated that they had limited their contact with others due to COVID-19 precautions; however, their reported contacts were not fewer (8%, 95%CI 1-13).\n\nConclusionIn urban Malawi, contact rates, are high and age-assortative, with little behavioural change due to either HIV-status or COVID-19 circulation. This highlights the limits of contact-restriction-based mitigation strategies in such settings and the need for pandemic preparedness to better understand how contact reductions can be enabled and motivated.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Iris N. Pardieck", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Esme T.I. van der Gracht", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Dominique M.B. Veerkamp", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Felix M. Behr", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Suzanne van Duikeren", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Guillaume Beyrend", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Jasper Rip", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Reza Nadafi", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Tetje C. van der Sluis", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Elham Beyranvand Nejad", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Nils Mulling", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Dena J. Brasem", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Marcel G.M. Camps", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Sebenzile K. Myeni", - "author_inst": "Leiden University Medical Center" - }, - { - "author_name": "Peter J. Bredenbeek", - "author_inst": "Leiden University Medical Center" + "author_name": "Deus Thindwa", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Marjolein Kikkert", - "author_inst": "Leiden University Medical Center" + "author_name": "Kondwani C Jambo", + "author_inst": "Malawi Liverpool Wellcome Trust Clinical Research Programme" }, { - "author_name": "Yeonsu Kim", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "John Ojal", + "author_inst": "KEMRI-Wellcome Trust Research Programme" }, { - "author_name": "Luka Cicin-Sain", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Peter MacPherson", + "author_inst": "Liverpool School Of Tropical Medicine" }, { - "author_name": "Tamim Abdelaal", - "author_inst": "Leiden University Medical Center" + "author_name": "Mphatso D Phiri", + "author_inst": "Malawi Liverpool Wellcome Trust Clinical Research Programme" }, { - "author_name": "Klaas P.J.M. van Gisbergen", - "author_inst": "Sanquin Research and Landsteiner Laboratory" + "author_name": "McEwen Khundi", + "author_inst": "Malawi Liverpool Wellcome Trust Clinical Research Programme" }, { - "author_name": "Kees L.M.C. Franken", - "author_inst": "Leiden University Medical Center" + "author_name": "Lingstone Chiume", + "author_inst": "Malawi-Liverpool-Wellcome Trust Clinical Research Programme" }, { - "author_name": "Jan Wouter Drijfhout", - "author_inst": "Leiden University Medical Center" + "author_name": "Katherine Gallagher", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Cornelius J.M. Melief", - "author_inst": "ISA Pharmaceuticals" + "author_name": "Robert S HEYDERMAN", + "author_inst": "University College London" }, { - "author_name": "Gerben C.M. Zondag", - "author_inst": "Immunetune" + "author_name": "Elizabeth L Corbett", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Ferry Ossendorp", - "author_inst": "Leiden University Medical Center" + "author_name": "Neil French", + "author_inst": "University of Liverpool" }, { - "author_name": "Ramon Arens", - "author_inst": "Leiden University Medical Center" + "author_name": "Stefan Flasche", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "immunology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.12.16.21267937", @@ -491803,27 +491578,43 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.12.16.472920", - "rel_title": "Amyloidogenesis of SARS-CoV-2 Spike Protein", - "rel_date": "2021-12-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.16.472920", - "rel_abs": "SARS-CoV-2 infection is associated with a surprising number of morbidities. Uncanny similarities with amyloid-disease associated blood coagulation and fibrinolytic disturbances together with neurologic and cardiac problems led us to investigate the amyloidogenicity of the SARS-CoV-2 Spike protein (S-protein). Amyloid fibril assays of peptide library mixtures and theoretical predictions identified seven amyloidogenic sequences within the S-protein. All seven peptides in isolation formed aggregates during incubation at 37{degrees}C. Three 20-amino acid long synthetic Spike peptides (sequence 191-210, 599-618, 1165-1184) fulfilled three amyloid fibril criteria: nucleation dependent polymerization kinetics by ThT, Congo red positivity and ultrastructural fibrillar morphology. Full-length folded S-protein did not form amyloid fibrils, but amyloid-like fibrils with evident branching were formed during 24 hours of S-protein co-incubation with the protease neutrophil elastase (NE) in vitro. NE efficiently cleaved S-protein rendering exposure of amyloidogenic segments and accumulation of the peptide 193-202, part of the most amyloidogenic synthetic Spike peptide. NE is overexpressed at inflamed sites of viral infection and at vaccine injection sites. Our data propose a molecular mechanism for amyloidogenesis of SARS-CoV-2 S-protein in humans facilitated by endoproteolysis. The potential implications of S-protein amyloidogenesis in COVID-19 disease associated pathogenesis and consequences following S-protein based vaccines should be addressed in understanding the disease, long COVID-19, and vaccine side effects.", - "rel_num_authors": 2, + "rel_doi": "10.1101/2021.12.14.21267810", + "rel_title": "Early detection and improved genomic surveillance of SARS-CoV-2 variants from deep sequencing data", + "rel_date": "2021-12-16", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.14.21267810", + "rel_abs": "In the definition of fruitful strategies to contrast the worldwide diffusion of SARS-CoV-2, maximum efforts must be devoted to the early detection of dangerous variants. An effective help to this end is granted by the analysis of deep sequencing data of viral samples, which are typically discarded after the creation of consensus sequences. Indeed, only with deep sequencing data it is possible to identify intra-host low-frequency mutations, which are a direct footprint of mutational processes that may eventually lead to the origination of functionally advantageous variants. Accordingly, a timely and statistically robust identification of such mutations might inform political decision-making with significant anticipation with respect to standard analyses based on con-sensus sequences.\n\nTo support our claim, we here present the largest study to date of SARS-CoV-2 deep sequencing data, which involves 220,788 high quality samples, collected over 20 months from 137 distinct studies. Importantly, we show that a rele-vant number of spike and nucleocapsid mutations of interest associated to the most circulating variants, including Beta, Delta and Omicron, might have been intercepted several months in advance, possibly leading to different public-health decisions. In addition, we show that a refined genomic surveillance system involving high- and low-frequency mutations might allow one to pin-point possibly dangerous emerging mutation patterns, providing a data-driven automated support to epidemiologists and virologists.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Sofie Nystrom", - "author_inst": "Linkoping University" + "author_name": "Daniele Ramazzotti", + "author_inst": "University of Milano-Bicocca" }, { - "author_name": "Per Hammarstrom", - "author_inst": "Linkoping University" + "author_name": "Davide Maspero", + "author_inst": "University of Milano-Bicocca" + }, + { + "author_name": "Fabrizio Angaroni", + "author_inst": "University of Milano-Bicocca" + }, + { + "author_name": "Marco Antoniotti", + "author_inst": "University of Milano-Bicocca" + }, + { + "author_name": "Rocco Piazza", + "author_inst": "University of Milano-Bicocca" + }, + { + "author_name": "Alex Graudenzi", + "author_inst": "Institute of Molecular Bioimaging and Physiology, Consiglio Nazionale delle Ricerche (IBFM-CNR)" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "biochemistry" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.12.14.21267757", @@ -493465,67 +493256,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.14.21267199", - "rel_title": "The COVID-19 pandemic amplified long-standing racial disparities in the United States criminal justice system", + "rel_doi": "10.1101/2021.12.14.21267809", + "rel_title": "mRNA COVID-19 vaccine effectiveness against SARS-CoV-2 infection in a prospective community cohort, rural Wisconsin, November 2020-December 2021", "rel_date": "2021-12-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.14.21267199", - "rel_abs": "The criminal legal system in the United States drives an incarceration rate that is the highest on the planet, with disparities by class and race among its signature features [1-3]. During the first year of the COVID-19 pandemic, the number of incarcerated people in the U.S. decreased by at least 17%--the largest, fastest reduction in prison population in American history [4]. In this study, we ask how this reduction influenced the racial com-position of U.S. prisons, and consider possible mechanisms for these dynamics. Using an original dataset curated from public sources on prison demographics across all 50 states and the District of Columbia, we show that incarcerated white people benefited disproportionately from the decrease in the U.S. prison population, and that the fraction of incarcerated Black and Latino people sharply increased. This pattern of increased racial disparity exists across prison systems in nearly every state and reverses a decades-long trend before 2020 and the onset of COVID-19, when the proportion of incarcerated white people was increasing amid declining numbers of incarcerated Black people [5]. Although a variety of factors underlie these trends, we find that racial inequities in average sentence length are a major contributor. Ultimately, this study reveals how disruptions caused by COVID-19 exacer-bated racial inequalities in the criminal legal system, and highlights key forces that sustain mass incarceration.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.14.21267809", + "rel_abs": "Reduced COVID-19 vaccine effectiveness (VE) has been observed with increasing predominance of the Delta variant. In a prospective rural community cohort of 1265 participants, VE against symptomatic and asymptomatic SARS-CoV-2 infection was 56% for mRNA COVID-19 vaccines.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Brennan Klein", - "author_inst": "Northeastern University Network Science Institute" - }, - { - "author_name": "C. Brandon Ogbunugafor", - "author_inst": "Yale University" - }, - { - "author_name": "Benjamin J. Schafer", - "author_inst": "Yale University" - }, - { - "author_name": "Zarana Bhadricha", - "author_inst": "Northeastern University" + "author_name": "Huong Q McLean", + "author_inst": "Marshfield Clinic Research Institute" }, { - "author_name": "Preeti Kori", - "author_inst": "Northeastern University" + "author_name": "David L McClure", + "author_inst": "Marshfield Clinic Research Institute" }, { - "author_name": "Jim Sheldon", - "author_inst": "Northeastern University" + "author_name": "Jennifer P King", + "author_inst": "Marshfield Clinic Research Institute" }, { - "author_name": "Nitish Kaza", - "author_inst": "Northeastern University" + "author_name": "Jennifer K Meece", + "author_inst": "Marshfield Clinic Research Institute" }, { - "author_name": "Arush Sharma", - "author_inst": "Northeastern University" + "author_name": "David Pattinson", + "author_inst": "University of Wisconsin - Madison" }, { - "author_name": "Emily A. Wang", - "author_inst": "Yale University" + "author_name": "Gabriele Neumann", + "author_inst": "University of Wisconsin - Madison" }, { - "author_name": "Tina Eliassi-Rad", - "author_inst": "Northeastern University Network Science Institute" + "author_name": "Yoshihiro Kawaoka", + "author_inst": "University of Wisconsin - Madison" }, { - "author_name": "Samuel V. Scarpino", - "author_inst": "Northeastern University" + "author_name": "Melissa A Rolfes", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Elizabeth Hinton", - "author_inst": "Yale University" + "author_name": "Edward A Belongia", + "author_inst": "Marshfield Clinic Research Institute" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.12.13.21267471", @@ -495906,77 +495685,21 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2021.12.14.21267460", - "rel_title": "Differential Risk of SARS-CoV-2 Infection by Occupation: Evidence from the Virus Watch prospective cohort study in England and Wales", + "rel_doi": "10.1101/2021.12.14.21267771", + "rel_title": "Final sizes and durations of new COVID-19 pandemic waves in Poland and Germany predicted by generalized SIR model", "rel_date": "2021-12-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.14.21267460", - "rel_abs": "BackgroundWorkers differ in their risk of SARS-CoV-2 infection according to their occupation, but the direct contribution of occupation to this relationship is unclear. This study aimed to investigate how infection risk differed across occupational groups in England and Wales up to April 2022, after adjustment for potential confounding and stratification by pandemic phase.\n\nMethodsData from 15,190 employed/self-employed participants in the Virus Watch prospective cohort study were used to generate risk ratios for virologically- or serologically-confirmed SARS-CoV-2 infection using robust Poisson regression, adjusting for socio-demographic and health-related factors and non-work public activities. We calculated attributable fractions (AF) amongst the exposed for belonging to each occupational group based on adjusted risk ratios (aRR).\n\nFindingsIncreased risk was seen in nurses (aRR=1.44, 1.25-1.65; AF=30%, 20-39%), doctors (aRR=1.33, 1.08-1.65; AF=25%, 7-39%), carers (1.45, 1.19-1.76; AF=31%, 16-43%), primary school teachers (aRR=1.67, 1.42-1.96; AF=40%, 30-49%), secondary school teachers (aRR=1.48, 1.26-1.72; AF=32%, 21-42%), and teaching support occupations (aRR=1.42, 1.23-1.64; AF=29%, 18-39%) compared to office-based professional occupations. Differential risk was apparent in the earlier phases (Feb 2020 - May 2021) and attenuated later (June - October 2021) for most groups, although teachers and teaching support workers demonstrated persistently elevated risk across waves.\n\nInterpretationOccupational differentials in SARS-CoV-2 infection risk vary over time and are robust to adjustment for socio-demographic, health-related, and non-workplace activity-related potential confounders. Direct investigation into workplace factors underlying elevated risk and how these change over time is needed to inform occupational health interventions.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.14.21267771", + "rel_abs": "New waves of the COVID-19 pandemic in Europe, which began in the autumn of 2021, are a matter of great concern and the need to immediately predict the epidemic dynamics in order to assess the possible maximum values of new cases, the risk of infection and the number of deaths. The generalized SIR-model and corresponding parameter identification procedure was used to simulate and predict the dynamics of new epidemic waves in Poland and Germany. Results of calculations show that new cases in these countries will not stop to appear in 2022.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Sarah Beale", - "author_inst": "University College London" - }, - { - "author_name": "Susan J Hoskins", - "author_inst": "Univerity College London" - }, - { - "author_name": "Thomas Edward Byrne", - "author_inst": "University College London" - }, - { - "author_name": "Erica Wing Lam Fong", - "author_inst": "University College London" - }, - { - "author_name": "Ellen Fragaszy", - "author_inst": "University College London" - }, - { - "author_name": "Cyril Geismar", - "author_inst": "University College London" - }, - { - "author_name": "Jana Kovar", - "author_inst": "University College London" - }, - { - "author_name": "Annalan MD Navaratnam", - "author_inst": "University College London" - }, - { - "author_name": "Vincent Nguyen", - "author_inst": "University College London" - }, - { - "author_name": "Parth Patel", - "author_inst": "University College London" - }, - { - "author_name": "Alexei Yavlinsky", - "author_inst": "University College London" - }, - { - "author_name": "Anne Johnson", - "author_inst": "University College London" - }, - { - "author_name": "Martie Van Tongeren", - "author_inst": "University of Manchester" - }, - { - "author_name": "Robert W Aldridge", - "author_inst": "University College London" - }, - { - "author_name": "Andrew Hayward", - "author_inst": "University College London" + "author_name": "Igor Nesteruk", + "author_inst": "Institute of Hydromechanics National Academy of sciences of Ukraine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -498104,37 +497827,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.12.21267681", - "rel_title": "COVID-19 in French Nursing Homes during the Second Pandemic Wave: A Mixed-Methods Cross-Sectional Study", + "rel_doi": "10.1101/2021.12.13.21267267", + "rel_title": "Genomics-informed outbreak investigations of SARS-CoV-2 using civet", "rel_date": "2021-12-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.12.21267681", - "rel_abs": "IntroductionFrench nursing homes were deeply affected by the first wave of the COVID-19 pandemic, with 38% of all residents infected and 5% dying. Yet, little was done to prepare these facilities for the second pandemic wave, and subsequent outbreak response strategies largely duplicated what had been done in the spring of 2020, regardless of the unique needs of the care home environment.\n\nMethodsA cross-sectional, mixed-methods study using retrospective, quantitative data from residents of 14 nursing homes between November 2020 and mid-January 2021. Four facilities were purposively selected as qualitative study sites for additional in-person, in-depth interviews in January and February 2021.\n\nResultsThe average attack rate in the 14 participating nursing facilities was 39% among staff and 61% among residents. One-fifth (20) of infected residents ultimately died from COVID-19 and its complications. Failure-to-Thrive-Syndrome (FTTS) was diagnosed in 23% of COVID-positive residents. Those at highest risk of death were men (HR=1.78; IC95: 1.18 - 2.70; p=0.006) with FTTS (HR=4.04; IC95: 1.93 - 8.48; p<0.001) in facilities with delayed implementation of universal FFP2 masking policies (HR=1.05; IC95: 1.02 - 1.07; p<0.001). The lowest mortality was found in residents of facilities with a partial (HR=0.30; IC95: 0.18 - 0.51; p<0.001) or full-time physician on staff (HR=0.20; IC95: 0.08 - 0.53; p=0.001). Significant themes emerging from qualitative analysis centered on (i) the structural, chronic neglect of nursing homes, (ii) the negative effects of the top-down, bureaucratic nature of COVID-19 crisis response, and (iii) the counterproductive effects of lockdowns on both residents and staff.\n\nConclusionDespite high resident mortality during the first pandemic wave, French nursing homes were ill-prepared for the second, with risk factors (especially staffing, lack of medical support, isolation/quarantine policy etc) that affected case fatality and residents and caregivers overall well-being and mental health.\n\nSUMMARY BOXO_ST_ABSWhat is already known?C_ST_ABSO_LIThough much was learned about COVID-19 in nursing homes during the first pandemic wave (Spring 2020), descriptions of the second wave in these facilities is nearly absent from the scientific literature.\nC_LIO_LIPrior COVID-19 research in nursing homes has rarely been qualitative and has almost never interviewed care home residents themselves.\nC_LIO_LIFirst-wave research indicated that much stronger outbreak and infection prevention was urgently needed to bolster nursing facilities preparedness. Higher staff-to-resident ratios, less staff turnover, more masks, better organization, more medical support, and more epidemiological tools were found to reduce COVID-19s impact.\nC_LI\n\nWhat are the new findings?O_LIOur results document a lack of preparedness for the second wave, with attack rates among staff (39% overall) and residents (61% overall) similar to levels seen during the first wave peak.\nC_LIO_LIDespite authorities claims to have reinforced these structures readiness, and despite much research into the needs in these environments, preventive measures (like strict lockdowns) remained largely unchanged and had a direct impact on residents, with 23% of COVID-positives also diagnosed with Failure-to-Thrive Syndrome.\nC_LIO_LIQualitative results detailed how ill-suited and inflexible some preventive measures were for residents and staff alike. Participants described precarious and understaffed living and working conditions as substantial and long-standing difficulties that became critical risks during the COVID-19 outbreak, and compromised the response.\nC_LI\n\nWhat do the new findings imply?O_LIThese results suggest that knowledge gained during the first pandemic wave was not consistently applied to care home policy or practice in France, and that these nursing homes were not always safe environments that considered residents mental health and well-being alongside infection prevention.\nC_LIO_LIDespite the high mortality of the first pandemic wave, French nursing homes were ill-prepared for the second. As a 5th wave descends on France (albeit with much higher COVID-19 vaccination rates), applying the lessons from previous periods (especially with regard to staffing, isolation of the elderly, medical supplies, standard of care procedures) must be prioritized.\nC_LI", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.13.21267267", + "rel_abs": "The scale of data produced during the SARS-CoV-2 pandemic has been unprecedented, with more than 5 million sequences shared publicly at the time of writing. This wealth of sequence data provides important context for interpreting local outbreaks. However, placing sequences of interest into national and international context is difficult given the size of the global dataset. Often outbreak investigations and genomic surveillance efforts require running similar analyses again and again on the latest dataset and producing reports. We developed civet (cluster investigation and virus epidemiology tool) to aid these routine analyses and facilitate virus outbreak investigation and surveillance. Civet can place sequences of interest in the local context of background diversity, resolving the query into different catchments and presenting the phylogenetic results alongside metadata in an interactive, distributable report. Civet can be used on a fine scale for clinical outbreak investigation, for local surveillance and cluster discovery, and to routinely summarise the virus diversity circulating on a national level. Civet reports have helped researchers and public health bodies feedback genomic information in the appropriate context within a timeframe that is useful for public health.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Morgane Dujmovic", - "author_inst": "Epicentre" + "author_name": "Aine N O'Toole", + "author_inst": "University of Edinburgh" }, { - "author_name": "Thomas Roederer", - "author_inst": "Epicentre" + "author_name": "Verity Hill", + "author_inst": "The University of Edinburgh" }, { - "author_name": "Severine Frison", - "author_inst": "Epicentre" + "author_name": "Ben Jackson", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Rebecca Dewar", + "author_inst": "Department of Clinical Microbiology, NHS Lothian, Edinburgh, UK" }, { - "author_name": "Carla Melki", - "author_inst": "Medecins Sans Frontieres - France" + "author_name": "Nikita Sahadeo", + "author_inst": "Department of Preclinical Sciences, The University of the West Indies, St. Augustine, Trinidad & Tobago" }, { - "author_name": "Thomas Lauvin", - "author_inst": "Medecins Sans Frontieres - France" + "author_name": "Rachel Colquhoun", + "author_inst": "University of Edinburgh" }, { - "author_name": "Emmanuel Grellety-Bosviel", - "author_inst": "Epicentre" + "author_name": "Stefan Rooke", + "author_inst": "Public Health Scotland, UK" + }, + { + "author_name": "John T McCrone", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Martin McHugh", + "author_inst": "Department of Clinical Microbiology, NHS Lothian, Edinburgh, UK" + }, + { + "author_name": "Sam Nicholls", + "author_inst": "Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK" + }, + { + "author_name": "Radoslaw Poplawski", + "author_inst": "Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK" + }, + { + "author_name": "- The COVID-19 Genomics UK (COG-UK) Consortium", + "author_inst": "-" + }, + { + "author_name": "- COVID-19 Impact Project (Trinidad & Tobago Group)", + "author_inst": "-" + }, + { + "author_name": "David Aanensen", + "author_inst": "The Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, UK" + }, + { + "author_name": "Matt Holden", + "author_inst": "School of Medicine, University of St Andrews, St Andrews, UK" + }, + { + "author_name": "Thomas R Connor", + "author_inst": "Cardiff University" + }, + { + "author_name": "Nicholas Loman", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Ian G. Goodfellow", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Christine Carrington", + "author_inst": "Department of Preclinical Sciences, The University of the West Indies, St. Augustine, Trinidad & Tobago" + }, + { + "author_name": "Kate Templeton", + "author_inst": "Department of Clinical Microbiology, NHS Lothian, Edinburgh, UK" + }, + { + "author_name": "Andrew Rambaut", + "author_inst": "University of Edinburgh" } ], "version": "1", @@ -499942,29 +499725,117 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.11.21267259", - "rel_title": "Time-Varying Mortality Risk Suggests Increased Impact of Thrombosis in Hospitalized Covid-19 Patients", + "rel_doi": "10.1101/2021.12.10.21267523", + "rel_title": "Human serum from SARS-CoV-2 vaccinated and COVID-19 patients shows reduced binding to the RBD of SARS-CoV-2 Omicron variant in comparison to the original Wuhan strain and the Beta and Delta variants", "rel_date": "2021-12-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.11.21267259", - "rel_abs": "Treatment protocols, treatment availability, disease understanding, and viral characteristics have changed over the course of the Covid-19 pandemic; as a result, the risks associated with patient comorbidities and biomarkers have also changed. We add to the ongoing conversation regarding inflammation, hemostasis and vascular function in Covid-19 by performing a time-varying observational analysis of over 4000 patients hospitalized for Covid-19 in a New York City hospital system from March 2020 to August 2021 to elucidate the changing impact of thrombosis, inflammation, and other risk factors on in-hospital mortality. We find that the predictive power of biomarkers of thrombosis risk have increased over time, suggesting an opportunity for improved care by identifying and targeting therapies for patients with elevated thrombophilic propensity.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.10.21267523", + "rel_abs": "The COVID-19 pandemic is caused by the betacoronavirus SARS-CoV-2. In November 2021, the Omicron variant was discovered and classified as a variant of concern (VOC). Omicron shows substantially more mutations in the spike protein than any previous variant, mostly in the receptor binding domain (RBD). We analyzed the binding of the Omicron RBD to the human ACE2 receptor (hACE2) and the ability of human sera from COVID-19 patients or vaccinees in comparison to Wuhan, Beta or Delta RBDs variants.\n\nAll RBDs were produced in insect cells. RBD binding to hACE2 was analyzed by ELISA and microscale thermophoresis (MST). Similarly, sera from 27 COVID-19 patients, 58 fully vaccinated individuals and 16 booster recipients were titrated by ELISA on the fixed RBDs from the original Wuhan strain, Beta, Delta and Omicron VOC.\n\nSurprisingly, the Omicron RBD showed a weaker binding to ACE2 compared to Beta and Delta, arguing that improved ACE2 binding is not a likely driver of Omicron evolution. Serum antibody titers were significantly lower against Omicron RBD compared to the original Wuhan strain. However, a difference of 2.5 times was observed in RBD binding while in other studies the neutralization of Omicron SARS-CoV-2 was reduced by a magnitude of 10x and more. These results indicate an immune escape focused on neutralizing antibodies.\n\nThe reduced binding of sera to Omicron RBD adds evidence that current vaccination protocols may be less efficient against the Omicron variant.", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Benjamin J Lengerich", - "author_inst": "MIT" + "author_name": "Maren Schubert", + "author_inst": "Technische Universitaet Braunschweig" }, { - "author_name": "Mark E. Nunnally", - "author_inst": "NYU Langone Health" + "author_name": "Federico Bertoglio", + "author_inst": "Technische Universitaet Braunschweig" }, { - "author_name": "Yin J Aphinyanaphongs", - "author_inst": "NYU Langone Health" + "author_name": "Stephan Steinke", + "author_inst": "Technische Universitaet Braunschweig" }, { - "author_name": "Rich Caruana", - "author_inst": "Microsoft Research" + "author_name": "Philip Alexander Heine", + "author_inst": "Technische Universitaet Braunschweig" + }, + { + "author_name": "Mario Alberto Ynga-Durand", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Fanglei Zuo", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Likun Du", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Janin Korn", + "author_inst": "Technische Universitaet Braunschweig" + }, + { + "author_name": "Marko Milosevic", + "author_inst": "University of Rijeka" + }, + { + "author_name": "Esther Veronika Wenzel", + "author_inst": "Technische Universitaet Braunschweig" + }, + { + "author_name": "Henrike Maass", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Fran Krstanovic", + "author_inst": "University of Rijeka" + }, + { + "author_name": "Saskia Polten", + "author_inst": "Technische Universitaet Braunschweig" + }, + { + "author_name": "Marina Pribanic-Matesic", + "author_inst": "University of Rijeka" + }, + { + "author_name": "Ilija Brizic", + "author_inst": "University of Rijeka" + }, + { + "author_name": "Antonio Piralla", + "author_inst": "Policlinico San Matteo" + }, + { + "author_name": "Fausto Baldanti", + "author_inst": "University of Pavia" + }, + { + "author_name": "Lennart Hammarstrom", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Stefan Dubel", + "author_inst": "Technische Universitaet Braunschweig" + }, + { + "author_name": "Alan Sustic", + "author_inst": "University of Rijeka" + }, + { + "author_name": "Harold Marcotte", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Monika Strengert", + "author_inst": "Helmholtz Center for Infection Research" + }, + { + "author_name": "Alen Protic", + "author_inst": "University of Rijeka" + }, + { + "author_name": "Qiang Pan Hammarstrom", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Luka Cicin-Sain", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Michael Hust", + "author_inst": "Technische Universitaet Braunschweig" } ], "version": "1", @@ -501780,109 +501651,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.09.21267539", - "rel_title": "Food for thought: Eating before saliva collection and interference with SARS-CoV-2 detection", + "rel_doi": "10.1101/2021.12.08.21267491", + "rel_title": "SARS-CoV-2 B.1.1.529 variant (Omicron) evades neutralization by sera from vaccinated and convalescent individuals", "rel_date": "2021-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.09.21267539", - "rel_abs": "BackgroundSaliva is an optimal specimen for detection of viruses that cause upper respiratory infections including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) due to its cost-effectiveness and non-invasive collection. However, together with intrinsic enzymes and oral microbiota, childrens unique dietary habits may introduce substances that interfere with diagnostic testing.\n\nMethodsTo determine whether childrens dietary choices impact SARS-CoV-2 detection in saliva, we performed a diagnostic study that simulates testing of real-life specimens provided from healthy children (n=5) who self-collected saliva at home before and at 0, 20, and 60 minutes after eating from 20 foods they selected. Each of seventy-two specimens was split into two volumes and spiked with SARS-CoV-2-negative or -positive standards prior to side-by-side testing by reverse-transcription polymerase chain reaction matrix-assisted laser desorption ionization time-of-flight (RT-PCR/MALDI-TOF) assay.\n\nResultsDetection of internal extraction control and SARS-CoV-2 nucleic acids was reduced in replicates of saliva collected at 0 minutes after eating 11 of 20 foods. Interference resolved at 20 and 60 minutes after eating all foods except hot dog in one participant. This represented a significant improvement in detection of nucleic acids compared to saliva collected at 0 minutes after eating (P=0.0005).\n\nConclusionsWe demonstrate successful detection of viral nucleic acids in saliva self-collected by children before and after eating a variety of foods. Fasting is not required before saliva collection for SARS-CoV-2 testing by RT-PCR/MALDI-TOF, but waiting 20 minutes after eating is sufficient for accurate testing. These findings should be considered for SARS-CoV-2 testing and broader viral diagnostics in saliva specimens.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.08.21267491", + "rel_abs": "Recently, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant B.1.1.529 (Omicron) has been described.\n\nHere, we analyze titers of neutralizing antibodies of sera from convalescent or vaccinated individuals against the new B.1.1.529 variant and compared them with titers against other Variants of Concern (B.1.1.7, B.1.351, B.1617.2) using replication competent SARS-CoV-2 variants.\n\nWe found that sera from vaccinated individuals neutralized the B.1.1.529 variant to a much lesser extent than any other variant analyzed. Neutralization capacity against B.1.1.529 was maintained best against sera from super immune individuals (infected and vaccinated or vaccinated and infected).", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Matthew M. Hernandez", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Mariawy Riollano-Cruz", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Mary C. Boyle", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Radhika Banu", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Paras Shrestha", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Brandon Gray", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Liyong Cao", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Feng Chen", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Huanzhi Shi", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Daniel E. Paniz-Perez", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Kids Laboratory and Science Hub, Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Paul A. Paniz-Perez", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Kids Laboratory and Science Hub, Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Aryan L. Rishi", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Kids Laboratory and Science Hub, Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Jacob Dubinsky", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Kids Laboratory and Science Hub, Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Dylan Dubinsky", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Kids Laboratory and Science Hub, Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Owen Dubinsky", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Kids Laboratory and Science Hub, Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Sophie Baine", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Kids Laboratory and Science Hub, Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Lily Baine", - "author_inst": "Department of Pathology, Molecular and Cell-Based Medicine, Kids Laboratory and Science Hub, Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Suzanne Arinsburg", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Ian Baine", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Annika Roessler", + "author_inst": "Institute of Virology, Department of Hygiene, Microbiology and Public Health, Medical University of Innsbruck, Peter-Mayr-Str. 4b, 6020 Innsbruck, Austria" }, { - "author_name": "Juan David Ramirez", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Lydia Riepler", + "author_inst": "Institute of Virology, Department of Hygiene, Microbiology and Public Health, Medical University of Innsbruck, Peter-Mayr-Str. 4b, 6020 Innsbruck, Austria" }, { - "author_name": "Carlos Cordon-Cardo", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "David Bante", + "author_inst": "Institute of Virology, Department of Hygiene, Microbiology and Public Health, Medical University of Innsbruck, Peter-Mayr-Str. 4b, 6020 Innsbruck, Austria" }, { - "author_name": "Emilia M Sordillo", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Dorothee von Laer", + "author_inst": "Institute of Virology, Department of Hygiene, Microbiology and Public Health, Medical University of Innsbruck, Peter-Mayr-Str. 4b, 6020 Innsbruck, Austria" }, { - "author_name": "Alberto E Paniz Mondolfi", - "author_inst": "Icahn School of Medicine" + "author_name": "Janine Kimpel", + "author_inst": "Institute of Virology, Department of Hygiene, Microbiology and Public Health, Medical University of Innsbruck, Peter-Mayr-Str. 4b, 6020 Innsbruck, Austria" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -503870,103 +503669,67 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.09.21267355", - "rel_title": "Estimating Active Cases of COVID-19", - "rel_date": "2021-12-10", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.09.21267355", - "rel_abs": "Having accurate and timely data on active COVID-19 cases is challenging, since it depends on the availability of an appropriate infrastructure to perform tests and aggregate their results. In this paper, we consider a case to be active if it is infectious, and we propose methods to estimate the number of active infectious cases of COVID-19 from the official data (of confirmed cases and fatalities) and from public survey data. We show that the latter is a viable option in countries with reduced testing capacity or infrastructures.", - "rel_num_authors": 21, + "rel_doi": "10.1101/2021.12.06.471527", + "rel_title": "SARS-CoV-2 variants of concern are dependent on IFITM2 for efficient replication in human lung cells", + "rel_date": "2021-12-09", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.06.471527", + "rel_abs": "The authors have withdrawn this manuscript due to a duplicate posting of manuscript number BIORXIV/2021/468942. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Javier Alvarez", - "author_inst": "IMDEA Networks Institute, Spain" - }, - { - "author_name": "Carlos Baquero", - "author_inst": "U. Porto & INESC TEC, Portugal" - }, - { - "author_name": "Elisa Cabana", - "author_inst": "IMDEA Networks Institute, Spain" - }, - { - "author_name": "Jaya Prakash Champati", - "author_inst": "IMDEA Networks Institute, Spain" - }, - { - "author_name": "Antonio Fernandez Anta", - "author_inst": "IMDEA Networks Institute, Spain" - }, - { - "author_name": "Davide Frey", - "author_inst": "Univ. Rennes, IRISA, CNRS, INRIA, France" - }, - { - "author_name": "Augusto Garcia-Agundez Garcia", - "author_inst": "Brown University, USA" - }, - { - "author_name": "Chryssis Georgiou", - "author_inst": "U. of Cyprus, Cyprus" - }, - { - "author_name": "Mathieu Goessens", - "author_inst": "Consulting, France" - }, - { - "author_name": "Harold Hernandez", - "author_inst": "U. Carlos III de Madrid, Spain" + "author_name": "Rayhane Nchioua", + "author_inst": "Ulm University Medical Center" }, { - "author_name": "Rosa Lillo", - "author_inst": "U. Carlos III de Madrid, Spain" + "author_name": "Annika Schundner", + "author_inst": "Ulm University Medical Center" }, { - "author_name": "Raquel Menezes", - "author_inst": "U. Minho, Portugal" + "author_name": "Dorota Kmiec", + "author_inst": "Ulm University Medical Center" }, { - "author_name": "Raul Moreno", - "author_inst": "Madox Viajes, Spain" + "author_name": "Caterina Prelli Bozzo", + "author_inst": "Ulm University Medical Center" }, { - "author_name": "Nicolas Nicolaou", - "author_inst": "Algolysis Ltd, Cyprus" + "author_name": "Fabian Zech", + "author_inst": "Ulm University Medical Center" }, { - "author_name": "Oluwasegun Ojo", - "author_inst": "IMDEA Networks Institute & U. Carlos III de Madrid, Spain" + "author_name": "Lennart Koepke", + "author_inst": "Ulm University Medical Center" }, { - "author_name": "Antonio Ortega", - "author_inst": "U. Southern California, USA" + "author_name": "Alexander Graf", + "author_inst": "Gene Center, LMU M\u00fcnchen" }, { - "author_name": "Estrella Rausell", - "author_inst": "U. Autonoma de Madrid, Spain" + "author_name": "Stefan Krebs", + "author_inst": "Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, Ludwig-Maximilians-University Munich" }, { - "author_name": "Jesus Rufino", - "author_inst": "IMDEA Network Institute, Spain" + "author_name": "Helmut Blum", + "author_inst": "Laboratory for Functional Genome Analysis (LAFUGA), Gene Center, Ludwig-Maximilians-University Munich" }, { - "author_name": "Efstathios Stavrakis", - "author_inst": "Algolysis Ltd, Cyprus" + "author_name": "Manfred Frick", + "author_inst": "Ulm University" }, { - "author_name": "Govind Jeevan", - "author_inst": "Academics for the Future of Science, Inc. & DICE Institute, Pathcheck Foundation, USA" + "author_name": "Konstantin Maria Johannes Sparrer", + "author_inst": "Ulm University" }, { - "author_name": "Christin Glorioso", - "author_inst": "Academics for the Future of Science, Inc., University of California San Francisco, & DICE Institute, Pathcheck Foundation, USA" + "author_name": "Frank Kirchhoff", + "author_inst": "Ulm University Medical Center" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.12.08.21267454", @@ -505720,53 +505483,57 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.12.09.21267516", - "rel_title": "Changes in the trajectory of Long Covid symptoms following COVID-19 vaccination: community-based cohort study", + "rel_doi": "10.1101/2021.12.09.21267507", + "rel_title": "Superspreading of SARS-CoV-2 infections: A Systematic Review and Meta-analysis", "rel_date": "2021-12-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.09.21267516", - "rel_abs": "ObjectiveTo estimate associations between COVID-19 vaccination and Long Covid symptoms in adults who were infected with SARS-CoV-2 prior to vaccination.\n\nDesignObservational cohort study using individual-level interrupted time series analysis.\n\nSettingRandom sample from the community population of the UK.\n\nParticipants28,356 COVID-19 Infection Survey participants (mean age 46 years, 56% female, 89% white) aged 18 to 69 years who received at least their first vaccination after test-confirmed infection.\n\nMain outcome measuresPresence of long Covid symptoms at least 12 weeks after infection over the follow-up period 3 February to 5 September 2021.\n\nResultsMedian follow-up was 141 days from first vaccination (among all participants) and 67 days from second vaccination (84% of participants). First vaccination was associated with an initial 12.8% decrease (95% confidence interval: -18.6% to -6.6%) in the odds of Long Covid, but increasing by 0.3% (-0.6% to +1.2%) per week after the first dose. Second vaccination was associated with an 8.8% decrease (-14.1% to -3.1%) in the odds of Long Covid, with the odds subsequently decreasing by 0.8% (-1.2% to -0.4%) per week. There was no statistical evidence of heterogeneity in associations between vaccination and Long Covid by socio-demographic characteristics, health status, whether hospitalised with acute COVID-19, vaccine type (adenovirus vector or mRNA), or duration from infection to vaccination.\n\nConclusionsThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second dose. Vaccination may contribute to a reduction in the population health burden of Long Covid, though longer follow-up time is needed.\n\nSummary boxWhat is already known on this topic\n\nO_LICOVID-19 vaccines are effective at reducing rates of SARS-CoV-2 infection, transmission, hospitalisation, and death\nC_LIO_LIThe incidence of Long Covid may be reduced if infected after vaccination, but the relationship between vaccination and pre-existing long COVID symptoms is unclear, as published studies are generally small and with self-selected participants\nC_LI\n\nWhat this study adds\n\nO_LIThe likelihood of Long Covid symptoms reduced after COVID-19 vaccination, and the improvement was sustained over the follow-up period after the second dose\nC_LIO_LIThere was no evidence of differences in this relationship by socio-demographic characteristics, health-related factors, vaccine type, or duration from infection to vaccination\nC_LIO_LIAlthough causality cannot be inferred from this observational evidence, vaccination may contribute to a reduction in the population health burden of Long Covid; further research is needed to understand the biological mechanisms that may ultimately contribute to the development of therapeutics for Long Covid\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.09.21267507", + "rel_abs": "Superspreading in transmission is a feature of SARS-CoV-2 transmission. We conducted a systematic review and meta-analysis on globally reported dispersion parameters of SARS-CoV-2. The pooled estimate was 0.55 (95% CI: 0.30, 0.79). The study location and method were found to be important drivers for its diversity.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Daniel Ayoubkhani", - "author_inst": "Office for National Statistics" + "author_name": "Zhanwei Du", + "author_inst": "University of Hong Kong" }, { - "author_name": "Charlotte Bermingham", - "author_inst": "Office for National Statistics" + "author_name": "Chunyu Wang", + "author_inst": "University of Hong Kong" }, { - "author_name": "Koen B Pouwels", - "author_inst": "University of Oxford" + "author_name": "Caifen Liu", + "author_inst": "University of Hong Kong" }, { - "author_name": "Myer Glickman", - "author_inst": "Office for National Statistics" + "author_name": "Yuan Bai", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Vahe Nafilyan", - "author_inst": "Office for National Statistics" + "author_name": "Pei Sen", + "author_inst": "Columbia University" }, { - "author_name": "Francesco Zaccardi", - "author_inst": "University of Leicester" + "author_name": "Dillon Adam", + "author_inst": "University of Hong Kong" }, { - "author_name": "Kamlesh Khunti", - "author_inst": "University of Leicester" + "author_name": "Lin Wang", + "author_inst": "University of Cambridge" }, { - "author_name": "Nisreen A Alwan", - "author_inst": "University of Southampton" + "author_name": "Peng Wu", + "author_inst": "University of Hong Kong" }, { - "author_name": "Ann Sarah Walker", - "author_inst": "University of Oxford" + "author_name": "Eric Lau", + "author_inst": "University of Hong Kong" + }, + { + "author_name": "Benjamin J Cowling", + "author_inst": "The University of Hong Kong" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -507230,147 +506997,79 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.12.08.21266760", - "rel_title": "Humoral and cellular responses to SARS-CoV-2 vaccination in patients with lymphoid malignancies", + "rel_doi": "10.1101/2021.12.08.21267458", + "rel_title": "Relative contribution of leaving home for work or education, transport, shopping and other activities on risk of acquiring COVID-19 infection outside the household in the second wave of the pandemic in England and Wales", "rel_date": "2021-12-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.08.21266760", - "rel_abs": "SARS-CoV-2 vaccination protects against COVID-19. Antibodies and antigen-specific T-cell responses against the spike domain can be used to measure vaccine immune response. Individuals with lymphoma have defects in humoral and cellular immunity that may compromise vaccine response. In this prospective observational study of 457 participants with lymphoma, 52% of participants vaccinated on treatment had undetectable anti-spike IgG antibodies compared to 9% who were not on treatment. Marked impairment was observed in those receiving anti- CD20 antibody within 12 months where 60% had undetectable antibodies compared to 11% on chemotherapy, which persisted despite three vaccine doses. Overall, 63% had positive T-cell responses irrespective of treatment. Individuals with indolent B-cell lymphoma have impaired antibody and cellular responses that were independent of treatment. The significant reduction and heterogeneity in immune responses in these individuals emphasise the urgent need for immune response monitoring and alternative prophylactic strategies to protect against COVID- 19.", - "rel_num_authors": 32, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.08.21267458", + "rel_abs": "BackgroundWith the potential for and emergence of new COVID-19 variants, such as the reportedly more infectious Omicron, and their potential to escape the existing vaccines, understanding the relative importance of which non-household activities increase risk of acquisition of COVID-19 infection is vital to inform mitigation strategies.\n\nMethodsWithin an adult subset of the Virus Watch community cohort study, we sought to identify which non-household activities increased risk of acquisition of COVID-19 infection and which accounted for the greatest proportion of non-household acquired COVID-19 infections during the second wave of the pandemic. Among participants who were undertaking antibody tests and self-reporting PCR and lateral flow tests taken through the national testing programme, we identified those who were thought to be infected outside the household during the second wave of the pandemic. We used exposure data on attending work, using public or shared transport, using shops and other non-household activities taken from monthly surveys during the second wave of the pandemic. We used multivariable logistic regression models to assess the relative independent contribution of these exposures on risk of acquiring infection outside the household. We calculated Adjusted Population Attributable Fractions (APAF - the proportion of non-household transmission in the cohort thought to be attributable to each exposure) based on odds ratios and frequency of exposure in cases.\n\nResultsBased on analysis of 10475 adult participants including 874 infections acquired outside the household, infection was independently associated with: leaving home for work (AOR 1.20 (1.02 - 1.42) p=0.0307, APAF 6.9%); public transport use (AOR for use more than once per week 1.82 (1.49 - 2.23) p<0.0001, APAF for public transport 12.42%); and shopping (AOR for shopping more than once per week 1.69 (1.29 - 2.21) P=0.0003, APAF for shopping 34.56%). Other non-household activities such as use of hospitality and leisure venues were rare due to restrictions and there were no significant associations with infection risk.\n\nConclusionsA high proportion of the second wave of the pandemic was spent under conditions where people were being advised to work from home where possible, and to minimize exposure to shops, and a wide range of other businesses were subject to severe restrictions. Vaccines were being rolled out to high-risk groups. During this time, going to work was an important risk factor for infection but public transport use likely accounted for a lot of this risk. Only a minority of the cohort left home for work or used public or shared transport. By contrast, the majority of participants visited shops and this activity accounted for about one-third of non-household transmission.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Sean Hua Lim", - "author_inst": "University of Southampton" - }, - { - "author_name": "Nicola Campbell", - "author_inst": "University Hospital Southampton NHS Foundation Trust" - }, - { - "author_name": "Beth Stuart", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton" - }, - { - "author_name": "Marina Johnson", - "author_inst": "Great Ormond Street Institute Of Child Health Biomedical Research Centre, University College London" - }, - { - "author_name": "Debora Joseph-Pietras", - "author_inst": "NIHR/Cancer Research UK Southampton Experimental Cancer Medicine Centre, WISH Laboratory" - }, - { - "author_name": "Adam Kelly", - "author_inst": "NIHR/Cancer Research UK Southampton Experimental Cancer Medicine Centre, WISH Laboratory" - }, - { - "author_name": "Danielle Jeffrey", - "author_inst": "NIHR/Cancer Research UK Southampton Experimental Cancer Medicine Centre, WISH Laboratory" - }, - { - "author_name": "Anna H Turaj", - "author_inst": "University of Southampton" - }, - { - "author_name": "Kate Rolfvondenbaumen", - "author_inst": "NIHR/Cancer Research UK Southampton Experimental Cancer Medicine Centre, WISH Laboratory" - }, - { - "author_name": "Celine Galloway", - "author_inst": "NIHR/Cancer Research UK Southampton Experimental Cancer Medicine Centre, WISH Laboratory" - }, - { - "author_name": "Thomas Wynn", - "author_inst": "NIHR/Cancer Research UK Southampton Experimental Cancer Medicine Centre, WISH Laboratory" - }, - { - "author_name": "Adam R Coleman", - "author_inst": "NIHR/Cancer Research UK Southampton Experimental Cancer Medicine Centre, WISH Laboratory" - }, - { - "author_name": "Ben Ward", - "author_inst": "NIHR/Cancer Research UK Southampton Experimental Cancer Medicine Centre, WISH Laboratory" - }, - { - "author_name": "Karen Long", - "author_inst": "University of Southampton Clinical Informatics Research Unit" - }, - { - "author_name": "Andrew T Bates", - "author_inst": "University Hospital Southampton NHS Foundation Trust" - }, - { - "author_name": "Diana Ayres", - "author_inst": "University Hospital Southampton NHS Foundation Trust" - }, - { - "author_name": "Robert Lown", - "author_inst": "University Hospital Southampton NHS Foundation Trust" - }, - { - "author_name": "Janlyn Falconer", - "author_inst": "University Hospital Southampton NHS Foundation Trust" + "author_name": "Susan J Hoskins", + "author_inst": "Univerity College London" }, { - "author_name": "Oliver Brake", - "author_inst": "University Hospital Southampton NHS Foundation Trust" + "author_name": "Sarah Beale", + "author_inst": "University College London" }, { - "author_name": "James Batchelor", - "author_inst": "University of Southampton Clinical Informatic Research Unit" + "author_name": "Robert W Aldridge", + "author_inst": "UCL" }, { - "author_name": "Victoria Willimott", - "author_inst": "Norfolk and Norwich University Hospital NHS Foundation Trust" + "author_name": "Colette Smith", + "author_inst": "University College London" }, { - "author_name": "Anna Bowzyk Al-Naeeb", - "author_inst": "Bedford Hospital" + "author_name": "Clare French", + "author_inst": "University of Bristol" }, { - "author_name": "Lisa Robinson", - "author_inst": "County Hospital Hereford" + "author_name": "Alex Yavlinksky", + "author_inst": "University College London" }, { - "author_name": "Ann O'Callaghan", - "author_inst": "Portsmouth Hospitals NHS Foundation Trust" + "author_name": "Vincent Nguyen", + "author_inst": "University College London" }, { - "author_name": "Graham P Collins", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" + "author_name": "Thomas Edward Byrne", + "author_inst": "University College London" }, { - "author_name": "Tobias Menne", - "author_inst": "Newcastle upon Tyne Hospitals NHS Foundation Trust" + "author_name": "Jana Kovar", + "author_inst": "University College London" }, { - "author_name": "Saul Faust", - "author_inst": "NIHR Southampton Clinical Research Facility and NIHR Southampton Biomedical Research Centre" + "author_name": "Ellen Fragaszy", + "author_inst": "University College London" }, { - "author_name": "Christopher P Fox", - "author_inst": "Nottingham University Hospital NHS Trust" + "author_name": "W Fong", + "author_inst": "University College London" }, { - "author_name": "Matthew Ahearne", - "author_inst": "University Hospitals Leicester NHS Trust" + "author_name": "Cyril Geismar", + "author_inst": "University College London" }, { - "author_name": "Peter W.M. Johnson", - "author_inst": "University of Southampton" + "author_name": "Parth Patel", + "author_inst": "University College London" }, { - "author_name": "Andrew J Davies", - "author_inst": "University of Southampton" + "author_name": "Ann Johnson", + "author_inst": "University College London" }, { - "author_name": "David Goldblatt", - "author_inst": "Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London" + "author_name": "Andrew Edward Hayward", + "author_inst": "UCL" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "hematology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.12.05.21267215", @@ -509368,39 +509067,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.04.471153", - "rel_title": "Elucidating design principles for engineering cell-derived vesicles to inhibit SARS-CoV-2 infection", + "rel_doi": "10.1101/2021.12.06.471394", + "rel_title": "Insertions in the SARS-CoV-2 Spike N-Terminal Domain May Aid COVID-19 Transmission", "rel_date": "2021-12-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.04.471153", - "rel_abs": "The ability of pathogens to develop drug resistance is a global health challenge. The SARS-CoV-2 virus presents an urgent need wherein several variants of concern resist neutralization by monoclonal antibody therapies and vaccine-induced sera. Decoy nanoparticles--cell-mimicking particles that bind and inhibit virions--are an emerging class of therapeutics that may overcome such drug resistance challenges. To date, we lack quantitative understanding as to how design features impact performance of these therapeutics. To address this gap, here we perform a systematic, comparative evaluation of various biologically-derived nanoscale vesicles, which may be particularly well-suited to sustained or repeated administration in the clinic due to low toxicity, and investigate their potential to inhibit multiple classes of model SARS-CoV-2 virions. A key finding is that such particles exhibit potent antiviral efficacy across multiple manufacturing methods, vesicle subclasses, and virus-decoy binding affinities. In addition, these cell-mimicking vesicles effectively inhibit model SARS-CoV-2 variants that evade monoclonal antibodies and recombinant protein-based decoy inhibitors. This study provides a foundation of knowledge that may guide the design of decoy nanoparticle inhibitors for SARS-CoV-2 and other viral infections.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.06.471394", + "rel_abs": "Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 is an ongoing pandemic that causes significant health/socioeconomic burden. Variants of concern (VOCs) have emerged which may affect transmissibility, disease severity and re-infection risk. Most studies focus on the receptor-binding domain (RBD) of the Spike protein. However, some studies suggest that the Spike N-terminal domain (NTD) may have a role in facilitating virus entry via sialic-acid receptor binding. Furthermore, most VOCs include novel NTD variants. Recent analyses demonstrated that NTD insertions in VOCs tend to lie close to loop regions likely to be involved in binding sialic acids. We extended the structural characterisation of these putative sugar binding pockets and explored whether variants could enhance the binding to sialic acids and therefore to the host membrane, thereby contributing to increased transmissibility. We found that recent NTD insertions in VOCs (i.e., Gamma, Delta and Omicron variants) and emerging variants of interest (VOIs) (i.e., Iota, Lambda, Theta variants) frequently lie close to known and putative sugar-binding pockets. For some variants, including the recent Omicron VOC, we find increases in predicted sialic acid binding energy, compared to the original SARS-CoV-2, which may contribute to increased transmission. We examined the similarity of NTD across a range of related Betacoronaviruses to determine whether the putative sugar-binding pockets are sufficiently similar to be exploited in drug design. Despite global sequence and structure similarity, most sialic-acid binding pockets of NTD vary across related coronaviruses. Typically, SARS-CoV-2 possesses additional loops in these pockets that increase contact with polysaccharides. Our work suggests ongoing evolutionary tuning of the sugar-binding pockets in the virus. Whilst three of the pockets are too structurally variable to be amenable to pan Betacoronavirus drug design, we detected a fourth pocket that is highly structurally conserved and could therefore be investigated in pursuit of a generic drug. Our structure-based analyses help rationalise the effects of VOCs and provide hypotheses for experiments. For example, the Omicron variant, which has increased binding to sialic acids in pocket 3, has a rather unique insertion near pocket 3. Our work suggests a strong need for experimental monitoring of VOC changes in NTD.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Taylor Franklin Gunnels", - "author_inst": "Northwestern University" - }, - { - "author_name": "Devin M Stranford", - "author_inst": "Northwestern University" + "author_name": "Su Datt Lam", + "author_inst": "University College London" }, { - "author_name": "Roxana E Mitrut", - "author_inst": "Northwestern University" + "author_name": "Vaishali P Waman", + "author_inst": "University College London" }, { - "author_name": "Neha Kamat", - "author_inst": "Northwestern University" + "author_name": "Christine Orengo", + "author_inst": "University College London" }, { - "author_name": "Joshua Nathaniel Leonard", - "author_inst": "Northwestern University" + "author_name": "Jonathan Lees", + "author_inst": "Oxford Brookes University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "bioengineering" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.12.07.21267410", @@ -511242,31 +510937,51 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2021.12.06.21267391", - "rel_title": "The Impact of Mass Exodus on the Resurgence of COVID19 Cases: Study Case of Regions in Indonesia", + "rel_doi": "10.1101/2021.12.04.471206", + "rel_title": "Engineering RNA viruses with unnatural amino acid to evoke adjustable immune response in mice", "rel_date": "2021-12-07", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.06.21267391", - "rel_abs": "The inclusion of the human mobility aspect is essential for understanding the behavior of COVID-19 spread, especially when millions of people travel across borders near Eid Al-Fitr. This study aims at grasping the effect of mass exodus among regions on the active cases of COVID-19 in a mathematical perspective. We construct a multi-region SIQRD (Susceptible-Infected-Quarantined-Recovered-Death) model that accommodates the direct transfer of people from one region to others. The mobility rate is estimated using the proposed Dawson-like function, which requires the Origin-Destination Matrix data. Assuming only susceptible, unapparent infected, and recovered individuals travel near Eid Al-Fitr, the rendered model is well-depicting the actual data at that time, giving either a significant spike or decline in the number of active cases due to the mass exodus. Most agglomerated regions like Jakarta and Depok City experienced the fall of active cases number, both in actual data and the simulated model. However, most rural areas experienced the opposite, like Bandung District and Cimahi City. This study should confirm that most travelers originated from big cities to the rural regions and scientifically justifies that massive mobility affects the COVID-19 transmission among areas.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.04.471206", + "rel_abs": "Ribonucleic acid (RNA) viruses pose heavy burdens on public-health systems. Synthetic biology holds great potential for artificially controlling their replication, a strategy that could be used to attenuate infectious viruses but is still in the exploratory stage. Herein, we used the genetic-code expansion technique to convert Enterovirus 71 (EV71), a model of RNA virus, into a controllable EV71 strain carrying the unnatural amino acid (UAA) N{varepsilon}-2-azidoethyloxycarbonyl-L-lysine (NAEK), which we termed an EV71-NAEK virus. EV71-NAEK could recapitulate an authentic NAEK time- and dose-dependent infection in vitro and in vivo, which could serve as a novel method to manipulate virulent viruses in conventional laboratories. We further validated the prophylactic effect of EV71-NAEK in two mouse models. In susceptible parent mice, vaccination with EV71-NAEK elicited a strong immune response and potentially protected their neonatal offspring from lethal challenge similar to that of commercial vaccines. Meanwhile, in transgenic mice harboring a PylRS-tRNAPyl pair, substantial elements of genetic-code expansion technology, EV71-NAEK evoked an adjustable neutralizing-antibody response in a strictly external NAEK dose-dependent manner. These findings suggested that EV71-NAEK could be the basis of a feasible immunization program for populations with different levels of immunity. Moreover, we expanded the strategy to generate controllable coxsackieviruses and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) for conceptual verification. In combination, these results could underlie a competent strategy for attenuating viruses and priming the immune system via artificial control, which might be a promising direction for the development of amenable vaccine candidates and be broadly applied to other RNA viruses.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Nuning Nuraini", - "author_inst": "Institut Teknologi Bandung" + "author_name": "Zhetao Zheng", + "author_inst": "Peking University" }, { - "author_name": "Kamal Khairudin Sukandar", - "author_inst": "Institut Teknologi Bandung" + "author_name": "Yu Wang", + "author_inst": "Peking University" }, { - "author_name": "Wirdatul Aini", - "author_inst": "Institut Teknologi Bandung" + "author_name": "Xuesheng Wu", + "author_inst": "Peking University" + }, + { + "author_name": "Haoran Zhang", + "author_inst": "Peking University" + }, + { + "author_name": "Hongmin Chen", + "author_inst": "Peking University" + }, + { + "author_name": "Haishuang Lin", + "author_inst": "Peking University" + }, + { + "author_name": "Yuxuan Shen", + "author_inst": "Peking University" + }, + { + "author_name": "Qing Xia", + "author_inst": "Peking University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "bioengineering" }, { "rel_doi": "10.1101/2021.12.06.471455", @@ -512920,33 +512635,145 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.12.02.21267164", - "rel_title": "Estimation of heterogeneous instantaneous reproduction numbers with application to characterize SARS-CoV-2 transmission in Massachusetts counties", + "rel_doi": "10.1101/2021.12.01.21266960", + "rel_title": "Comparative magnitude and persistence of SARS-CoV-2 vaccination responses on a population level in Germany", "rel_date": "2021-12-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.02.21267164", - "rel_abs": "The reproductive number is an important metric that has been widely used to quantify the infectiousness of communicable diseases. The time-varying instantaneous reproductive number is useful for monitoring the real time dynamics of a disease to inform policy making for disease control. Local estimation of this metric, for instance at a county or city level, allows for more targeted interventions to curb transmission. However, simultaneous estimation of local reproductive numbers must account for potential sources of heterogeneity in these time-varying quantities - a key element of which is human mobility. We develop a statistical method that incorporates human mobility between multiple regions for estimating region-specific instantaneous reproductive numbers. The model also can account for exogenous cases imported from outside of the regions of interest. We propose two approaches to estimate the reproductive numbers, with mobility data used to adjust incidence in the first approach and to inform a formal priori distribution in the second (Bayesian) approach. Through a simulation study, we show that region-specific reproductive numbers can be well estimated if human mobility is reasonably well approximated by available data. We use this approach to estimate the instantaneous reproductive numbers of COVID-19 for 14 counties in Massachusetts using CDC case report data and the human mobility data collected by SafeGraph. We found that, accounting for mobility, our method produces estimates of reproductive numbers that are distinct across counties. In contrast, independent estimation of county-level reproductive numbers tends to produce similar values, as trends in county case-counts for the state are fairly concordant. These approaches can also be used to estimate any heterogeneity in transmission, for instance, age-dependent instantaneous reproductive number estimates. As people are more mobile and interact frequently in ways that permit transmission, it is important to account for this in the estimation of the reproductive number.\n\nAuthor summaryTo control the spreading of an infectious disease, it is very important to understand the real-time infectiousness of the pathogen that causes the disease. An existing metric called instantaneous reproductive number is often used to quantify the average number of secondary cases generated by individuals who are infectious at a certain time point, assuming no changes to current conditions. In practice, we might be interested in using the metric to describe the infectiousness in multiple regions. However, this is challenging when there are visitors traveling between these regions, since this could lead to a misclassification of where an individual is actually infected and create biased estimates for the instantaneous reproductive numbers. We developed a method that takes account of human mobility to estimate the instantaneous reproductive numbers for multiple regions simultaneously, which could reveal the heterogeneity of the metric. This method aims to provide helpful information on region-specific infectiousness for disease control measures that focus on the region with higher pathogen infectiousness. This approach is also applicable for estimating the reproductive number in the presence of other sources of heterogeneity, including by age.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.01.21266960", + "rel_abs": "BackgroundWhile SARS-CoV-2 vaccinations were successful in decreasing COVID-19 caseloads, recent increases in SARS-CoV-2 infections have led to questions about duration and quality of the subsequent immune response. While numerous studies have been published on immune responses triggered by vaccination, these often focused on the initial peak response generated in specific population subgroups (e.g. healthcare workers or immunocompromised individuals) and have often only examined the effects of one or two different immunisation schemes.\n\nMethods and FindingsWe analysed serum samples from participants of a large German seroprevalence study (MuSPAD) who had received all available vaccines and dose schedules (mRNA-1273, BNT162b2, AZD1222, Ad26.CoV2S.2 or a combination of AZD1222 plus either mRNA-1273 or BNT162b2). Antibody titers against various SARS-CoV-2 antigens and ACE2 binding inhibition against SARS-CoV-2 wild-type and the Alpha, Beta, Gamma and Delta variants of concern were analysed using a previously published multiplex immunoassay MULTICOV-AB and an ACE2-RBD competition assay. Among the different vaccines and their dosing regimens, homologous mRNA-based or heterologous prime-boost vaccination produced significantly higher antibody responses than vector-based homologous vaccination. Ad26.CoV2S.2 performance was significantly reduced, even compared to AZD1222, with 91.67% of samples being considered non-responsive forACE2 binding inhibition. mRNA-based vaccination induced a higher ratio of RBD- and S1-targeting antibodies than vector-based vaccination, which resulted in an increased proportion of S2-targeting antibodies. Previously infected individuals had a robust immune response once vaccinated, regardless of which vaccine they received. When examining antibody kinetics post-vaccination after homologous immunisation regimens, both titers and ACE2 binding inhibition peaked approximately 28 days post-vaccination and then decreased as time increased.\n\nConclusionsAs one of the first and largest population-based studies to examine vaccine responses for all currently available immunisation schemes in Germany, we found that homologous mRNA or heterologous vaccination elicited the highest immune responses. The high percentage of non-responders for Ad26.CoV2.S requires further investigation and suggests that a booster dose with an mRNA-based vaccine may be necessary. The high responses seen in recovered and vaccinated individuals could aid future dose allocation, should shortages arise for certain manufacturers. Given the role of RBD- and S1-specific antibodies in neutralising SARS-CoV-2, their relative over-representation after mRNA vaccination may explain why mRNA vaccines have an increased efficacy compared to vector-based formulations. Further investigation on these differences will be of particular interest for vaccine development and efficacy, especially for the next-generation of vector-based vaccines.", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Zhenwei Zhou", - "author_inst": "Boston University" + "author_name": "Alex Dulovic", + "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" }, { - "author_name": "Eric Kolaczyk", - "author_inst": "Boston University" + "author_name": "Barbora Kessel", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" }, { - "author_name": "Robin N Thompson", - "author_inst": "University of Warwick" + "author_name": "Manuela Harries", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" }, { - "author_name": "Laura F White", - "author_inst": "Boston University" + "author_name": "Matthias Becker", + "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + }, + { + "author_name": "Julia Ortmann", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Johanna Griesbaum", + "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + }, + { + "author_name": "Jennifer Juengling", + "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + }, + { + "author_name": "Daniel Junker", + "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + }, + { + "author_name": "Pilar Hernandez", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Daniela Gornyk", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Stephan Gloeckner", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Vanessa Melhorn", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Stefanie Castell", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Jana-Kristin Heise", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Yvonne Kemmling", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Torsten Tonn", + "author_inst": "Institute of Transfusion Medicine and Immunohematology, German Red Cross, Plauen, Germany" + }, + { + "author_name": "Kerstin Frank", + "author_inst": "Institute of Transfusion Medicine and Immunohematology, German Red Cross, Plauen, Germany" + }, + { + "author_name": "Thomas Illig", + "author_inst": "Hannover Unified Biobank, Hannover Medical School, Hannover, Germany" + }, + { + "author_name": "Norman Klopp", + "author_inst": "Hannover Unified Biobank, Hannover Medical School, Hannover, Germany" + }, + { + "author_name": "Neha Warikoo", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Angelika Rath", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Christina Suckel", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Anne Ulrike Marzian", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Nicole Grupe", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Philipp D. Kaiser", + "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + }, + { + "author_name": "Bjoern Traenkle", + "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + }, + { + "author_name": "Ulrich Rothbauer", + "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + }, + { + "author_name": "Tobias Kerrinnes", + "author_inst": "Helmholtz Institute for RNA-based Infection Research, Wuerzburg, Germany" + }, + { + "author_name": "Gerard Krause", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Berit Lange", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" + }, + { + "author_name": "Nicole Schneiderhan-Marra", + "author_inst": "NMI Natural and Medical Sciences Institute at the University of Tuebingen, Reutlingen, Germany" + }, + { + "author_name": "Monika Strengert", + "author_inst": "Helmholtz Centre for Infection Research, Braunschweig, Germany" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -514670,71 +514497,31 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.12.01.470697", - "rel_title": "Macaque-human differences in SARS-CoV-2 Spike antibody response elicited by vaccination or infection", + "rel_doi": "10.1101/2021.12.02.470930", + "rel_title": "Investigating the human host - ssRNA virus interaction landscape using the SMEAGOL toolbox", "rel_date": "2021-12-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.01.470697", - "rel_abs": "Macaques are a commonly used model for studying immunity to human viruses, including for studies of SARS-CoV-2 infection and vaccination. However, it is unknown whether macaque antibody responses recapitulate, and thus appropriately model, the response in humans. To answer this question, we employed a phage-based deep mutational scanning approach (Phage- DMS) to compare which linear epitopes are targeted on the SARS-CoV-2 Spike protein in humans and macaques following either vaccination or infection. We also used Phage-DMS to determine antibody escape pathways within each epitope, enabling a granular comparison of antibody binding specificities at the locus level. Overall, we identified some common epitope targets in both macaques and humans, including in the fusion peptide (FP) and stem helix- heptad repeat 2 (SH-H) regions. Differences between groups included a response to epitopes in the N-terminal domain (NTD) and C-terminal domain (CTD) in vaccinated humans but not vaccinated macaques, as well as recognition of a CTD epitope and epitopes flanking the FP in convalescent macaques but not convalescent humans. There was also considerable variability in the escape pathways among individuals within each group. Sera from convalescent macaques showed the least variability in escape overall and converged on a common response with vaccinated humans in the SH-H epitope region, suggesting highly similar antibodies were elicited. Collectively, these findings suggest that the antibody response to SARS-CoV-2 in macaques shares many features with humans, but with substantial differences in the recognition of certain epitopes and considerable individual variability in antibody escape profiles, suggesting a diverse repertoire of antibodies that can respond to major epitopes in both humans and macaques.\n\nAuthor summaryNon-human primates, including macaques, are considered the best animal model for studying infectious diseases that infect humans. Vaccine candidates for SARS-CoV-2 are first tested in macaques to assess immune responses prior to advancing to human trials, and macaques are also used to model the human immune response to SARS-CoV-2 infection. However, there may be differences in how macaque and human antibodies recognize the SARS-CoV-2 entry protein, Spike. Here we characterized the locations on Spike that are recognized by antibodies from vaccinated or infected macaques and humans. We also made mutations to the viral sequence and assessed how these affected antibody binding, enabling a comparison of antibody binding requirements between macaques and humans at a very precise level. We found that macaques and humans share some responses, but also recognize distinct regions of Spike. We also found that in general, antibodies from different individuals had unique responses to viral mutations, regardless of species. These results will yield a better understanding of how macaque data can be used to inform human immunity to SARS-CoV-2.", - "rel_num_authors": 13, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.12.02.470930", + "rel_abs": "Viruses are intracellular parasites that need their host cell to reproduce. Consequently, they have evolved numerous mechanisms to exploit the molecular machinery of their host cells, including the broad spectrum of host RNA-binding proteins (RBPs). However, the RBP interactome of viral genomes and the consequences of these interactions for infection are still to be mapped for most RNA viruses. To facilitate these efforts we have developed SMEAGOL, a fast and user-friendly toolbox to analyze the enrichment or depletion of RBP binding motifs across RNA sequences (https://github.com/gruber-sciencelab/SMEAGOL). To shed light on the interaction landscape of RNA viruses with human host cell RBPs at a large scale, we applied SMEAGOL to 197 single-stranded RNA (ssRNA) viral genome sequences. We find that the majority of ssRNA virus genomes are significantly enriched or depleted in binding motifs for human RBPs, suggesting selection pressure on these interactions. Our analysis provides an overview of potential virus - RBP interactions, covering the majority of ssRNA viral genomes fully sequenced to date, and represents a rich resource for studying host interactions vital to the virulence of ssRNA viruses. Our resource and the SMEAGOL toolbox will support future studies of virus / host interactions, ultimately feeding into better treatments.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Alexandra Willcox", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Kevin Sung", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Meghan E. Garrett", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Jared G. Galloway", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Megan A. O\u2019Connor", - "author_inst": "University of Washington" - }, - { - "author_name": "Jesse H. Erasmus", - "author_inst": "University of Washington" - }, - { - "author_name": "Jennifer K. Logue", - "author_inst": "University of Washington" - }, - { - "author_name": "David W. Hawman", - "author_inst": "National Institute of Allergy and Infectious Diseases Division of Intramural Research" - }, - { - "author_name": "Helen Y. Chu", - "author_inst": "University of Washington" - }, - { - "author_name": "Kim J. Hasenkrug", - "author_inst": "National Institute of Allergy and Infectious Diseases Division of Intramural Research" - }, - { - "author_name": "Deborah H. Fuller", - "author_inst": "University of Washington" + "author_name": "Avantika Lal", + "author_inst": "Insitro, South San Francisco, CA, USA" }, { - "author_name": "Frederick A. Matsen", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Mariana Galvao Ferrarini", + "author_inst": "Univ Lyon, INSA Lyon, INRAE, BF2I, UMR 203, 69621 Villeurbanne, France" }, { - "author_name": "Julie Overbaugh", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Andreas J Gruber", + "author_inst": "University of Konstanz" } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.12.02.470924", @@ -516272,45 +516059,41 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2021.12.01.21267147", - "rel_title": "Comparison of Saliva and Mid-Turbinate Swabs for Detection of COVID-19", + "rel_doi": "10.1101/2021.11.29.21267028", + "rel_title": "A simple model of COVID-19 explains disease severity and the effect of treatments", "rel_date": "2021-12-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.12.01.21267147", - "rel_abs": "BackgroundSaliva is an attractive sample for detecting SARS-CoV-2. However, contradictory reports exist concerning the sensitivity of saliva versus nasal swabs.\n\nMethodsWe followed close contacts of COVID-19 cases for up to 14 days from last exposure and collected self-reported symptoms, mid-turbinate swabs (MTS), and saliva every two or three days. Ct values, viral load, and frequency of viral detection by MTS and saliva were compared.\n\nResults58 contacts provided 200 saliva-MTS pairs; 14 contacts (13 with symptoms) had one or more positive samples. Saliva and MTS had similar rates of viral detection (p=0.78) and substantial agreement ({kappa}=0.83). However, sensitivity varied significantly with time since symptom onset. Early on (days -3 to 2), saliva had 12 times (95%CI: 1.2, 130) greater likelihood of viral detection and 3.2 times (95% CI: 2.8, 3.8) higher RNA copy numbers compared to MTS. After day 2 post-symptoms, there was a non-significant trend toward greater sensitivity using MTS.\n\nConclusionSaliva and MTS demonstrated high agreement making saliva a suitable alternative to MTS for COVID-19 detection. Saliva was more sensitive early in the infection when transmission is most likely to occur, suggesting that it may be a superior and cost-effective screening tool for COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.29.21267028", + "rel_abs": "Considerable effort was made to better understand why some people suffer from severe COVID-19 while others remain asymptomatic. This has led to important clinical findings; people with severe COVID-19 generally experience persistently high levels of inflammation, slower viral load decay, display a dysregulated type-I interferon response, have less active natural killer cells and increased levels of neutrophil extracellular traps. How these findings are connected to the pathogenesis of COVID-19 remains unclear. We propose a mathematical model that sheds light on this issue. The model focuses on cells that trigger inflammation through molecular patterns: infected cells carrying pathogen-associated molecular patterns (PAMPs) and damaged cells producing damage-associated molecular patterns (DAMPs). The former signals the presence of pathogens while the latter signals danger such as hypoxia or the lack of nutrients. Analyses show that SARS-CoV-2 infections can lead to a self-perpetuating feedback loop between DAMP expressing cells and inflammation. It identifies the inability to quickly clear PAMPs and DAMPs as the main contributor to hyperinflammation. The model explains clinical findings and the conditional impact of treatments on disease severity. The simplicity of the model and its high level of consistency with clinical findings motivate its use for the formulation of new treatment strategies.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Jianyu Lai", - "author_inst": "Department of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, Maryland, USA" - }, - { - "author_name": "Jennifer Rebecca German", - "author_inst": "Public Health Aerobiology and Biomarker Laboratory, Institute for Applied Environmental Health, University of Maryland School of Public Health, College Park, Ma" + "author_name": "Steven Sanche", + "author_inst": "Los Alamos National Laboratory" }, { - "author_name": "Filbert H. Hong", - "author_inst": "Public Health Aerobiology and Biomarker Laboratory, Institute for Applied Environmental Health, University of Maryland School of Public Health, College Park, Ma" + "author_name": "Tyler Cassidy", + "author_inst": "Los Alamos National Laboratory" }, { - "author_name": "S.-H. Sheldon Tai", - "author_inst": "Public Health Aerobiology and Biomarker Laboratory, Institute for Applied Environmental Health, University of Maryland School of Public Health, College Park, Ma" + "author_name": "Pinghan Chu", + "author_inst": "Los Alamos National Laboratory" }, { - "author_name": "Kathleen M. McPhaul", - "author_inst": "Public Health Aerobiology and Biomarker Laboratory, Institute for Applied Environmental Health, University of Maryland School of Public Health, College Park, Ma" + "author_name": "Alan S. Perelson", + "author_inst": "Los Alamos National Laboratory" }, { - "author_name": "Donald K. Milton", - "author_inst": "Public Health Aerobiology and Biomarker Laboratory, Institute for Applied Environmental Health, University of Maryland School of Public Health, College Park, Ma" + "author_name": "Ruy M Ribeiro", + "author_inst": "Los Alamos National Laboratory" }, { - "author_name": "- University of Maryland StopCOVID Research Group", - "author_inst": "" + "author_name": "Ruian Ke", + "author_inst": "Los Alamos National Laboratory" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -518490,107 +518273,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.11.28.468932", - "rel_title": "Case Study of High-Throughput Drug Screening and Remote Data Collection for SARS-CoV-2 Main Protease by Using Serial Femtosecond X-ray Crystallography", + "rel_doi": "10.1101/2021.11.28.470226", + "rel_title": "Main protease mutants of SARS-CoV-2 variants remain susceptible to PF-07321332", "rel_date": "2021-11-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.28.468932", - "rel_abs": "Since early 2020, COVID-19 has grown to affect the lives of billions globally. A worldwide investigation has been ongoing for characterizing the virus and also for finding an effective drug and developing vaccines. As time has been of the essence, a crucial part of this research has been drug repurposing; therefore, confirmation of in-silico drug screening studies has been carried out for this purpose. Here we demonstrated the possibility of screening a variety of drugs efficiently by leveraging a high data collection rate of 120 images/second with the new low-noise, high dynamic range ePix10k2M Pixel Array Detector installed at the Macromolecular Femtosecond Crystallography (MFX) instrument at the Linac Coherent Light Source (LCLS). The X-ray Free-Electron Laser (XFEL) is used for remote high-throughput data collection for drug repurposing of the main protease (Mpro) of SARS-CoV-2 at ambient temperature with mitigated X-ray radiation damage. We obtained multiple structures soaked with 9 drug candidate molecules in two crystal forms. Although our drug binding attempts failed, we successfully established a high-throughput Serial Femtosecond X-ray crystallographic (SFX) data collection protocol.", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.28.470226", + "rel_abs": "The COVID-19 pandemic continues to be a public health threat. Multiple mutations in the spike protein of emerging variants of SARS-CoV-2 appear to impact on the effectiveness of available vaccines. Specific antiviral agents are keenly anticipated but their efficacy may also be compromised in emerging variants. One of the most attractive coronaviral drug targets is the main protease (Mpro). A promising Mpro inhibitor of clinical relevance is the peptidomimetic nirmatrelvir (PF-07321332). We expressed Mpro of six SARS-CoV-2 lineages (C.37 Lambda, B.1.1.318, B.1.2, B.1.351 Beta, B.1.1.529 Omicron, P.2 Zeta), each of which carries a strongly prevalent missense mutation (G15S, T21I, L89F, K90R, P132H, L205V). Enzyme kinetics showed that these Mpro variants are similarly catalytically competent as the wildtype. We show that nirmatrelvir has similar potency against the variants as against the wildtype. Our in vitro data suggest that the efficacy of the specific Mpro inhibitor nirmatrelvir is not compromised in current COVID-19 variants.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=138 SRC=\"FIGDIR/small/470226v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (33K):\norg.highwire.dtl.DTLVardef@182cc6org.highwire.dtl.DTLVardef@1239d10org.highwire.dtl.DTLVardef@11ca6d9org.highwire.dtl.DTLVardef@df53b_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Omur Guven", - "author_inst": "Koc University" - }, - { - "author_name": "Mehmet Gul", - "author_inst": "Koc University" - }, - { - "author_name": "Esra Ayan", - "author_inst": "Koc University" - }, - { - "author_name": "J. Austin Johnson", - "author_inst": "Koc University" - }, - { - "author_name": "Baris Cakilkaya", - "author_inst": "Koc University" - }, - { - "author_name": "Gozde Usta", - "author_inst": "Koc University" - }, - { - "author_name": "Fatma Betul Ertem", - "author_inst": "Koc University" - }, - { - "author_name": "Nurettin Tokay", - "author_inst": "Koc University" - }, - { - "author_name": "Busra Yuksel", - "author_inst": "Koc University" - }, - { - "author_name": "Oktay Gocenler", - "author_inst": "Koc University" - }, - { - "author_name": "Cengizhan Buyukdag", - "author_inst": "Koc University" - }, - { - "author_name": "Sabine Botha", - "author_inst": "Arizona State University" - }, - { - "author_name": "Gihan Ketawala", - "author_inst": "Arizona State University" - }, - { - "author_name": "Zhen Su", - "author_inst": "SLAC National Accelerator Laboratory" - }, - { - "author_name": "Brandon Hayes", - "author_inst": "SLAC National Accelerator Laboratory" - }, - { - "author_name": "Frederic Poitevin", - "author_inst": "SLAC National Accelerator Laboratory" - }, - { - "author_name": "Alexander Batyuk", - "author_inst": "SLAC National Accelerator Laboratory" - }, - { - "author_name": "Chun Hong Yoon", - "author_inst": "SLAC National Accelerator Laboratory" - }, - { - "author_name": "Christopher Kupitz", - "author_inst": "SLAC National Accelerator Laboratory" + "author_name": "Sven Ullrich", + "author_inst": "Australian National University" }, { - "author_name": "Serdar Durdagi", - "author_inst": "Bahcesehir University" + "author_name": "Kasuni B Ekanayake", + "author_inst": "Australian National University" }, { - "author_name": "Raymond G. Sierra", - "author_inst": "SLAC National Accelerator Laboratory" + "author_name": "Gottfried Otting", + "author_inst": "Australian National University" }, { - "author_name": "Hasan DeMirci", - "author_inst": "SLAC National Laboratory" + "author_name": "Christoph Nitsche", + "author_inst": "Australian National University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "molecular biology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.11.30.470527", @@ -520216,47 +519927,83 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.25.470044", - "rel_title": "Anticipating future SARS-CoV-2 variants of concern through ab initio quantum mechanical modeling", + "rel_doi": "10.1101/225151", + "rel_title": "Proof of concept continuous event logging in living cells", "rel_date": "2021-11-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.25.470044", - "rel_abs": "Evolved SARS-CoV-2 variants are currently challenging the efficacy of first-generation vaccines, largely through the emergence of spike protein mutants. Among these variants, Delta is presently the most concerning. We employ an ab initio quantum mechanical model based on Density Functional Theory to characterize the spike protein Receptor Binding Domain (RBD) interaction with host cells and gain mechanistic insight into SARS-CoV-2 evolution. The approach is illustrated via a detailed investigation of the role of the E484K RBD mutation, a signature mutation of the Beta and Gamma variants. The simulation is employed to: predict the depleting effect of the E484K mutation on binding the RBD with select antibodies; identify residue E484 as a weak link in the original interaction with the human receptor hACE2; and describe SARS-CoV-2 Wuhan strand binding to the bat Rhinolophus macrotis ACE2 as more optimized than the human counterpart. Finally, we predict the hACE2 binding efficacy of a hypothetical E484K mutation added to the Delta variant RBD, identifying a potential future variant of concern. Results can be generalized to other mutations, and provide useful information to complement existing experimental datasets of the interaction between randomly generated libraries of hACE2 and viral spike mutants. We argue that ab initio modeling is at the point of being aptly employed to inform and predict events pertinent to viral and general evolution.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/225151", + "rel_abs": "Cells must detect and respond to molecular events such as the presence or absence of specific small molecules. To accomplish this, cells have evolved methods to measure the presence and concentration of these small molecules in their environment and enact changes in gene expression or behavior. However, cells dont usually change their DNA in response to such outside stimuli. In this work, we have engineered a genetic circuit that can enact specific and controlled genetic changes in response to changing small molecule concentrations. Known DNA sequences can be repeatedly integrated into a genomic array such that their identity and order encodes information about past small molecule concentrations that the cell has experienced. To accomplish this, we use catalytically inactive CRISPR-Cas9 (dCas9) to bind to and block attachment sites for the integrase Bxb1. Therefore, through the co-expression of dCas9 and guide RNA, Bxb1 can be directed to integrate one of two engineered plasmids, which correspond to two orthogonal small molecule inducers that can be recorded with this system. We identified the optimal location of guide RNA binding to the Bxb1 attP integrase attachment site, and characterized the detection limits of the system by measuring the minimal small molecule concentration and shortest induction time necessary to produce measurable differences in array composition as read out by Oxford Nanopore long read sequencing technology.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Marco Zaccaria", - "author_inst": "Boston College" + "author_name": "Fadi Jacob", + "author_inst": "Johns Hopkins University School of Medicine" }, { - "author_name": "Luigi Genovese", - "author_inst": "CEA, Grenoble, France" + "author_name": "Sarshan Pather", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Michael Farzan", + "author_name": "Wei-Kai Huang", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Samuel Zheng Hao Wong", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Haowen Zhou", + "author_inst": "Sanford Burnham Prebys Medical Discovery Institute" + }, + { + "author_name": "Feng Zhang", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Beatrice Cubitt", "author_inst": "The Scripps Research Institute" }, { - "author_name": "William Dawson", - "author_inst": "RIKEN Center for Computational Science, Kobe, Japan" + "author_name": "Catherine Z Chen", + "author_inst": "National Institutes of Health" }, { - "author_name": "Takahito Nakajima", - "author_inst": "RIKEN Center for Computational Science, Kobe, Japan" + "author_name": "Miao Xu", + "author_inst": "National Institutes of Health" }, { - "author_name": "Welkin E Johnson", - "author_inst": "Boston College" + "author_name": "Manisha Pradhan", + "author_inst": "National Institutes of Health" }, { - "author_name": "Babak Momeni", - "author_inst": "Boston College" + "author_name": "Daniel Y Zhang", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Wei Zheng", + "author_inst": "National Institutes of Health" + }, + { + "author_name": "Anne G Bang", + "author_inst": "Sanford Burnham Prebys Medical Discovery Institute" + }, + { + "author_name": "Hongjun Song", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Juan Carlos de la Torre", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Guo-li Ming", + "author_inst": "University of Pennsylvania" } ], - "version": "1", + "version": "5", "license": "cc_no", "type": "new results", - "category": "biophysics" + "category": "synthetic biology" }, { "rel_doi": "10.1101/2021.11.28.21266882", @@ -522138,41 +521885,45 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.11.24.21266837", - "rel_title": "Changes in antidepressant use in Australia: A nationwide analysis prior to and during the COVID-19 pandemic (2015-2021)", + "rel_doi": "10.1101/2021.11.25.21266856", + "rel_title": "The COVID-19 pandemic and temporal change in metabolic risk factors for cardiovascular disease: a natural experiment within the HELIUS study.", "rel_date": "2021-11-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.24.21266837", - "rel_abs": "BackgroundDepression and anxiety affect 4% to 14% of Australians every year; symptoms may have been exacerbated during the COVID-19 pandemic. We examined recent patterns of antidepressant use in Australia in the period 2015 to 2021, which includes the first year of the pandemic.\n\nMethodsWe used national dispensing claims for people aged [≥]10 years to investigate annual trends in prevalent and new antidepressant use (no antidepressants dispensed in the year prior). We conducted stratified analyses by sex, age group and antidepressant class. We report outcomes from 2015 to 2019 and used time series analysis to quantify changes during the first year of the COVID-19 pandemic (March 2020 to February 2021).\n\nResultsIn 2019 the annual prevalence of antidepressant use was 170.4 per 1,000 women and 101.8 per 1,000 men, an increase of 7.0% and 9.2% from 2015, respectively. New antidepressant use also increased for both sexes (3.0% for women and 4.9% for men) and across most age groups, particularly among adolescents (aged 10-17 years; 46%-57%). During the first year of the COVID-19 pandemic, we observed higher than expected prevalent use (+2.2%, 95%CI 0.3%, 4.2%) among females, corresponding to a predicted excess of 45,217 (95%CI 5,819, 84,614) females dispensed antidepressants. The largest increases during the first year of the pandemic occurred among female adolescents for both prevalent (+11.7%, 95%CI 4.1%, 20.5%) and new antidepressant use (+15.6%, 95%CI 8.5%, 23.7%).\n\nConclusionAntidepressant use continues to increase in Australia overall and especially among young people. We found a differential impact of the COVID-19 pandemic in treated depression and anxiety, greater among females than males, and greater among young females than other age groups, suggesting an increased mental health burden in populations already on a trajectory of increased use of antidepressants prior to the pandemic. Reasons for these differences require further investigation.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.25.21266856", + "rel_abs": "ObjectiveWe studied the association between the coronavirus disease 2019 (COVID-19) pandemic, including the restrictive measures, and metabolic risk factors for cardiovascular disease (CVD) in women and men. Next, we analysed whether changes in these metabolic risk factors were mediated by psychological and behavioural mechanisms.\n\nDesignIn this natural experiment, we assessed changes from baseline in metabolic CVD risk factors in the exposed group (whose follow-up measurements were taken during the pandemic), and compared these to the changes in the control group (whose follow-up measurements were taken before the pandemic).\n\nParticipantsThis study used data from 6962 participants from six different ethnic groups (Dutch, South-Asian Surinamese, African Surinamese, Ghanaian, Turkish and Moroccan) of the HELIUS study, based in Amsterdam, the Netherlands. We included women and men without prior CVD, who participated in both the baseline (2011-2015) and follow-up measurements (2019-2021).\n\nOutcome measuresChanges between baseline and follow-up measurements in six metabolic CVD risk factors were calculated for systolic and diastolic blood pressure (SBP, DBP), total cholesterol (TC), fasting plasma glucose (FPG), haemoglobin A1c (HbA1c), and estimated glomerular filtration rate (eGFR).\n\nResultsThe exposed group experienced somewhat less favourable changes over time in SBP, DBP and FPG (the latter only in women) than the control group, while temporal changes in HbA1c and eGFR were more favourable among the control group. For instance, SBP was 1.119 mmHg [0.046, 2.193] higher in exposed than non-exposed women, and 1.380 [0.288, 2.471] in men. Changes in SBP and DBP were partially mediated by changes in behavioural factors, most notably BMI and alcohol consumption.\n\nConclusionsThe COVID-19 pandemic, including the restrictive lockdown measures, is associated with a deterioration of several CVD risk factors in women and men. These findings may aid in decision making concerning the management of and the recovery following the pandemic.\n\nArticle SummaryO_ST_ABSStrengths and limitations of this studyC_ST_ABSO_LIThe COVID19 pandemic lockdown measures led to a pause in the data collection for the prospective, population-based HELIUS study, which shaped a natural experiment.\nC_LIO_LINatural experiments, as quasi-experimental designs, are generally considered stronger than cross-sectional studies.\nC_LIO_LIThrough inverse-probability weighting, this study aimed to account for baseline differences between the control and exposed group.\nC_LIO_LIWe could not adjust for differences in follow-up time that occurred as a result of the restrictive measures, which may have affected estimates of variables that change with age.\nC_LIO_LIThe effects of certain mediators may be underestimated, as the data available for defining these variables were largely based on self-reports.\nC_LI", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Juliana de Oliveira Costa", - "author_inst": "Medicines Policy Research Unit, Centre for Big Data Research in Health, Faculty of Medicine/ UNSW Sydney" + "author_name": "Bryn Hummel", + "author_inst": "Amsterdam UMC" }, { - "author_name": "Malcolm B. Gilles", - "author_inst": "Medicines Policy Research Unit, Centre for Big Data Research in Health, Faculty of Medicine/ UNSW Sydney" + "author_name": "Mara Yerkes", + "author_inst": "Utrecht University" }, { - "author_name": "Andrea L Schaffer", - "author_inst": "Medicines Policy Research Unit, Centre for Big Data Research in Health, Faculty of Medicine/ UNSW Sydney" + "author_name": "Ralf E Harskamp", + "author_inst": "Amsterdam UMC" }, { - "author_name": "David Peiris", - "author_inst": "The George Institute for Global Health, Faculty of Medicine/ UNSW Sydney" + "author_name": "Henrike Galenkamp", + "author_inst": "Amsterdam UMC" }, { - "author_name": "Helga Zoega", - "author_inst": "Medicines Policy Research Unit, Centre for Big Data Research in Health, Faculty of Medicine/ UNSW Sydney. Centre of Public Health Sciences, Faculty of Medicine," + "author_name": "Anton E Kunst", + "author_inst": "Amsterdam UMC" }, { - "author_name": "Sallie-Anne Pearson", - "author_inst": "Medicines Policy Research Unit, Centre for Big Data Research in Health, Faculty of Medicine/ UNSW Sydney" + "author_name": "Anja Lok", + "author_inst": "Amsterdam UMC" + }, + { + "author_name": "Irene G M van Valkengoed", + "author_inst": "Amsterdam UMC" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -523808,69 +523559,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.23.21266734", - "rel_title": "Establishing and characterising large COVID-19 cohorts after mapping the Information System for Research in Primary Care in Catalonia to the OMOP Common Data Model", + "rel_doi": "10.1101/2021.11.21.21266655", + "rel_title": "Determining international spread of novel B.1.1.523 SARS-CoV-2 lineage", "rel_date": "2021-11-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.23.21266734", - "rel_abs": "BackgroundFew datasets have been established that capture the full breadth of COVID-19 patient interactions with a health system. Our first objective was to create a COVID-19 dataset that linked primary care data to COVID-19 testing, hospitalisation, and mortality data at a patient level. Our second objective was to provide a descriptive analysis of COVID-19 outcomes among the general population and describe the characteristics of the affected individuals.\n\nMethodsWe mapped patient-level data from Catalonia, Spain, to the Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM). More than 3,000 data quality checks were performed to assess the readiness of the database for research. Subsequently, to summarise the COVID-19 population captured, we established a general population cohort as of the 1st March 2020 and identified outpatient COVID-19 diagnoses or positive test results for SARS-CoV-2, hospitalisations with COVID-19, and COVID-19 deaths during follow-up, which went up until 30th June 2021.\n\nFindingsMapping data to the OMOP CDM was performed and high data quality was observed. The mapped database was used to identify a total of 5,870,274 individuals, who were included in the general population cohort as of 1st March 2020. Over follow up, 604,472 had either an outpatient COVID-19 diagnosis or positive test result, 58,991 had a hospitalisation with COVID-19, 5,642 had an ICU admission with COVID-19, and 11,233 had a COVID-19 death. People who were hospitalised or died were more commonly older, male, and with more comorbidities. Those admitted to ICU with COVID-19 were generally younger and more often male than those hospitalised in general and those who died.\n\nInterpretationWe have established a comprehensive dataset that captures COVID-19 diagnoses, test results, hospitalisations, and deaths in Catalonia, Spain. Extensive data checks have shown the data to be fit for use. From this dataset, a general population cohort of 5.9 million individuals was identified and their COVID-19 outcomes over time were described.\n\nFundingGeneralitat de Catalunya and European Health Data and Evidence Network (EHDEN).", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.21.21266655", + "rel_abs": "Here we report the emergence of variant lineage B.1.1.523 that contains a set of mutations including 156_158del, E484K and S494P in Spike protein. E484K and S494P are known to significantly reduce SARS-CoV-2 neutralization by convalescent and vaccinee sera and are considered as mutations of concern. Lineage B.1.1.523 has presumably originated in Russian Federation and spread across European countries with the peak of transmission in April - May 2021. The B.1.1.523 lineage has now been reported from 27 countries.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Edward Burn", - "author_inst": "University of Oxford" - }, - { - "author_name": "Sergio Fern\u00e1ndez-Bertol\u00edn", - "author_inst": "IDIAPJGol, Barcelona, Spain" - }, - { - "author_name": "Erica A Voss", - "author_inst": "Janssen Pharmaceutical Research and Development, Titusville, NJ, USA" - }, - { - "author_name": "Clair Blacketer", - "author_inst": "Janssen Pharmaceutical Research and Development, Titusville, NJ, USA" - }, - { - "author_name": "Maria Arag\u00f3n", - "author_inst": "IDIAPJGol, Barcelona, Spain" - }, - { - "author_name": "Martina Recalde", - "author_inst": "IDIAPJGol, Barcelona, Spain" - }, - { - "author_name": "Elena Roel", - "author_inst": "IDIAPJGol, Barcelona, Spain" + "author_name": "Lukas Zemaitis", + "author_inst": "Lithuanian University of Health Sciences" }, { - "author_name": "Andrea Pistillo", - "author_inst": "IDIAPJGol, Barcelona, Spain" + "author_name": "Gediminas Alzbutas", + "author_inst": "Lithuanian University of Health Sciences" }, { - "author_name": "Berta Ravent\u00f3s", - "author_inst": "IDIAPJGol, Barcelona, Spain" + "author_name": "Dovydas Gecys", + "author_inst": "Lithuanian University of Health Sciences" }, { - "author_name": "Carlen Reyes", - "author_inst": "IDIAPJGol, Barcelona, Spain" + "author_name": "Andrey Komissarov", + "author_inst": "Research Institute of Influenza, Saint Petersburg State University" }, { - "author_name": "Sebastiaan van Sandijk", - "author_inst": "Odysseus Data Services s.r.o., Prague, Czech Republic" + "author_name": "Arnoldas Pautienius", + "author_inst": "Lithuanian University of Health Sciences" }, { - "author_name": "Lars Halvorsen", - "author_inst": "edenceHealth NV, Kontich, Belgium" + "author_name": "Rasa Ugenskiene", + "author_inst": "Lithuanian University of Health Sciences Hospital Kaunas Clinics" }, { - "author_name": "Peter R Rijnbeek", - "author_inst": "Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands" + "author_name": "Marius Sukys", + "author_inst": "Lithuanian University of Health Sciences Hospital Kaunas Clinics" }, { - "author_name": "Talita Duarte-Salles", - "author_inst": "IDIAPJGol, Barcelona, Spain" + "author_name": "Vaiva Lesauskaite", + "author_inst": "Lithuanian University of Health Sciences" } ], "version": "1", @@ -525518,71 +525245,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.11.17.21266441", - "rel_title": "Pausing methotrexate improves immunogenicity of COVID-19 vaccination in patients with rheumatic diseases", + "rel_doi": "10.1101/2021.11.20.469409", + "rel_title": "Airway epithelial interferon response to SARS-CoV-2 is inferior to rhinovirus and heterologous rhinovirus infection suppresses SARS-CoV-2 replication", "rel_date": "2021-11-23", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21266441", - "rel_abs": "ObjectiveTo study the effect of methotrexate (MTX) and its discontinuation on the humoral immune response after COVID-19 vaccination in patients with autoimmune rheumatic diseases (AIRD).\n\nMethodsIn this retrospective study, neutralising SARS-CoV-2 antibodies were measured after second vaccination in 64 rheumatic patients on methotrexate therapy, 31 of whom temporarily paused medication without a fixed regimen. The control group consisted of 21 AIRD patients without immunosuppressive medication.\n\nResultsMTX patients showed a significantly lower mean antibody response compared to AIRD patients without immunosuppressive therapy (71.8 % vs 92.4 %, p<0.001). For patients taking MTX, age correlated negatively with immune response (r=-0.49; p<0.001). All nine patients with antibody levels below the cut-off were older than 60 years. Patients who held MTX during at least one vaccination showed significantly higher mean neutralising antibody levels after second vaccination, compared to patients who continued MTX therapy during both vaccinations (83.1 % vs 61.2 %, p=0.001). This effect was particularly pronounced in patients older than 60 years (80.8 % vs 51.9 %, p=0.001). The impact of the time period after vaccination was greater than of the time before vaccination with the critical cut-off being 10 days.\n\nConclusionMTX reduces the immunogenicity of SARS-CoV-2 vaccination in an age-dependent manner. Our data further suggest that holding MTX for at least 10 days after vaccination significantly improves the antibody response in patients over 60 years of age.", - "rel_num_authors": 13, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.20.469409", + "rel_abs": "IntroductionCommon alphacoronaviruses and human rhinoviruses (HRV) induce type I and III interferon (IFN) responses important to limiting viral replication in the airway epithelium. In contrast, highly pathogenic betacoronaviruses including SARS-CoV-2 may evade or antagonize RNA-induced IFN I/III responses.\n\nMethodsIn airway epithelial cells (AECs) from children and older adults we compared IFN I/III responses to SARS-CoV-2 and HRV-16, and assessed whether pre-infection with HRV-16, or pretreatment with recombinant IFN-{beta} or IFN-{lambda}, modified SARS-CoV-2 replication. Bronchial AECs from children (ages 6-18 yrs.) and older adults (ages 60-75 yrs.) were differentiated ex vivo to generate organotypic cultures. In a biosafety level 3 (BSL-3) facility, cultures were infected with SARS-CoV-2 or HRV-16, and RNA and protein was harvested from cell lysates 96 hrs. following infection and supernatant was collected 48 and 96 hrs. following infection. In additional experiments cultures were pre-infected with HRV-16, or pre-treated with recombinant IFN-{beta}1 or IFN-{lambda}2 before SARS-CoV-2 infection.\n\nResultsDespite significant between-donor heterogeneity SARS-CoV-2 replicated 100 times more efficiently than HRV-16. IFNB1, INFL2, and CXCL10 gene expression and protein production following HRV-16 infection was significantly greater than following SARS-CoV-2. IFN gene expression and protein production were inversely correlated with SARS-CoV-2 replication. Treatment of cultures with recombinant IFN{beta}1 or IFN{lambda}2, or pre-infection of cultures with HRV-16, markedly reduced SARS-CoV-2 replication.\n\nDiscussionIn addition to marked between-donor heterogeneity in IFN responses and viral replication, SARS-CoV-2 elicits a less robust IFN response in primary AEC cultures than does rhinovirus, and heterologous rhinovirus infection, or treatment with recombinant IFN-{beta}1 or IFN-{lambda}2, markedly reduces SARS-CoV-2 replication.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Amanthi Nadira Arumahandi de Silva", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" + "author_name": "David F. Read", + "author_inst": "Department of Genome Sciences, University of Washington, Seattle, Washington" }, { - "author_name": "Leonie Maria Frommert", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" - }, - { - "author_name": "Fredrik N Albach", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" + "author_name": "Cole Trapnell", + "author_inst": "Department of Genome Sciences, University of Washington, Seattle, Washington" }, { - "author_name": "Jens Klotsche", - "author_inst": "German Rheumatism Research Center Berlin, Chariteplatz 1, 10117 Berlin, Germany" - }, - { - "author_name": "Veronika Scholz", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" - }, - { - "author_name": "Alexander ten Hagen", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" - }, - { - "author_name": "Lara Maria Jeworowski", - "author_inst": "Institute of Virology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" + "author_name": "Steven F. Ziegler", + "author_inst": "Center for Fundamental Immunology, Benaroya Research Institute at Virginia Mason, Seattle, Washington; Department of Immunology, University of Washington School" }, { - "author_name": "Tatjana Schwarz", - "author_inst": "Institute of Virology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" - }, - { - "author_name": "Jan Zernicke", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" - }, - { - "author_name": "Victor Max Corman", - "author_inst": "Institute of Virology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" - }, - { - "author_name": "Christian Drosten", - "author_inst": "Institute of Virology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" - }, - { - "author_name": "Gerd Ruediger Burmester", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" - }, - { - "author_name": "Robert Biesen", - "author_inst": "Department of Rheumatology and Clinical Immunology, Charite University Hospital, Chariteplatz 1, 10117 Berlin, Germany" + "author_name": "Teal S. Hallstrand", + "author_inst": "Division of Pulmonary, Critical Care, and Sleep Medicine and the Center for Lung Biology, University of Washington, Seattle, Washington" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "rheumatology" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.11.22.469492", @@ -527596,47 +527287,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.20.21266644", - "rel_title": "Immunogenicity of heterologous prime/boost inactivated and mRNA COVID-19 vaccine", + "rel_doi": "10.1101/2021.11.19.21266605", + "rel_title": "Myocarditis and Pericarditis following COVID-19 Vaccination: Rapid Systematic Review of Incidence, Risk Factors, and Clinical Course", "rel_date": "2021-11-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.20.21266644", - "rel_abs": "IntroductionIn August 2021, Thailand imported the BNT162b2 mRNA COVID-19 vaccine. The prioritised group to receive the BNT162b2 vaccine were health professionals. The BNT162b2 vaccine scheduled for healthcare workers were two-dose regimen administered three weeks apart, the third dose booster in two-dose inactivated CoronaVac vaccine recipients or as a second dose in health professionals who had received the CoronaVac or adenoviral-vectored (ChAdOx1-S) vaccine as the first dose regardless of the interval between the first and second dose.\n\nMethodsThis study aims to evaluate the immunogenicity of the heterologous prime boost CoronaVac followed by BNT162b2 in health professionals.\n\nResultsThe CoronaVac/BNT162b2 vaccine recipients elicited higher neutralizing activity against the original Wuhan and all variants of concern than in the recipients of the two-dose CoronaVac.\n\nConclusionsThe heterologous CoronaVac/BNT162b2 could be used as an alternative regimen in countries experiencing the vaccine shortages and in individuals experiencing the adverse events following CoronaVac.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.19.21266605", + "rel_abs": "ObjectivesMyocarditis and pericarditis are adverse events of special interest after vaccination with mRNA vaccines. This rapid systematic review examined incidence rates of myocarditis and pericarditis after COVID-19 vaccination, and the presentation and clinical course of cases.\n\nDesignRapid systematic review\n\nData sourcesMedline, Embase and the Cochrane Library were searched from October 2020 to October 6, 2021; reference lists and grey literature (to Oct 21, 2021).\n\nReview methodsRandomized controlled trials (RCTs) and large population-based/multisite observational studies and surveillance data reporting on myocarditis or pericarditis in people of any age after receiving any COVID-19 vaccine; systematic reviews of case series. A single reviewer completed screening and another verified 50% of exclusions, using a machine-learning program to prioritize records. A second reviewer verified all exclusions at full text, data extractions, and (for incidence) risk of bias assessments using Cochrane Risk of Bias 2.0 and Joanna Briggs Institute tools. Certainty of evidence ratings for incidence were based on team consensus using GRADE. Patient partners provided key messages from their interpretations of the findings.\n\nResults3457 titles/abstracts and 159 full texts were screened. For incidence rates we included 7 RCTs (n=3732 to 44,325) and 22 large observational studies/data sources using passive (n=10) and active (n=12) surveillance; for case presentation, we included 11 case series published as articles and three based on publicly available websites (n=12,636 cases). Mainly due to imprecision, the RCTs provided very low certainty evidence for incidence of myocarditis or pericarditis. From observational data, the incidence of myocarditis following mRNA vaccines is low but probably highest in males 12-17 years (55 [7-day risk] to 134 [30-day risk] cases per million; specific to Pfizer) and 18-29 years (40 [7-day risk] to 99 [21-30 day risk]) cases per million) (Moderate certainty evidence). Incidence is lower (<20 per million) or little-to-none in older ages and across all ages of females (Low certainty). Evidence for pericarditis was of very low certainty. Among adult males under 40 years, Moderna compared with Pfizer vaccine may be associated with a small increase (<20 per million) in risk for myocarditis or (one of) myocarditis or pericarditis following vaccination (Low certainty); the evidence for youth under 18 years was very uncertain. No study examined differences in incidence based on pre-existing condition(s) or risk factors apart from age and sex. The majority of myocarditis cases involved males (often >90%) in their 20s, with a short symptom onset of 2 to 4 days after a second dose (71-100%). The majority of cases presented with chest pain/pressure and troponin elevation; a minority (<30%) had left ventricular dysfunction. Most were hospitalized ([≥]84%), without stays in intensive care units, for a short duration (2-4 d) and treated with anti-inflammatory and/or other supportive therapies. Almost all reports of death are from unverified cases and of unclear cause. Most cases of pericarditis were unconfirmed; for this outcome there appears to be more variation in age, sex, onset timing and rate of hospitalization.\n\nConclusionsIncidence of myocarditis following mRNA vaccines is low but probably highest in males 12-29 years old. Existing evidence does not strongly support preference of one mRNA vaccine, even in young males. Continued active surveillance of myocarditis incidence out to 30 days from dosing is recommended with respect to i) new populations (i.e., children <12y), ii) third and subsequent doses, and iii) affected individuals receiving subsequent mRNA vaccine doses. Future research is needed to examine other risk factors and long-term effects.\n\nFunding and Registration noThis project was funded in part by the Canadian Institutes of Health Research (CIHR) through the COVID-19 Evidence Network to support Decision-making (COVID-END) at McMaster University. Not registered.\n\nO_TEXTBOXSummary boxO_ST_ABSWhat is already known about this topic?C_ST_ABSCase reports and surveillance signals of myocarditis (inflammation of the heart muscle) and pericarditis (inflammation of the two-layered sac surrounding the heart) after COVID-19 vaccination appeared as early as April 2021.\n\nThese have prompted ongoing surveillance and research of these complications to investigate their incidence, possible attribution to the vaccines, and clinical course.\n\nWhat this study addsThis review critically appraises and synthesizes the available evidence to-date on the incidence of myocarditis and pericarditis after COVID-19 vaccination in multiple countries. It summarizes the presentation and clinical course of over 12,000 reported cases.\n\nThough low, the incidence in young males 12-29 years of age is probably the highest and appears to be similar across mRNA vaccines. Most cases present with chest pain and are mild and self-limiting. Continued active surveillance is warranted especially with vaccine rollout to young children and use of third doses, and to learn of any long-term consequences.\n\nC_TEXTBOX", "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Nasamon Wanlapakorn", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand." + "author_name": "Jennifer Pillay", + "author_inst": "University of Alberta" }, { - "author_name": "Ritthideach Yorsaeng", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand" + "author_name": "Liza Bialy", + "author_inst": "University of Alberta" }, { - "author_name": "Harit Phowatthanasathian", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand" + "author_name": "Lindsay Gaudet", + "author_inst": "University of Alberta" }, { - "author_name": "Nungruthai Suntronwong", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand" + "author_name": "Aireen Wingert", + "author_inst": "University of Alberta" }, { - "author_name": "Sitthichai Kanokudom", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand" + "author_name": "Andrew Mackie", + "author_inst": "University of Alberta" }, { - "author_name": "Natthinee Sudhinaraset", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand" + "author_name": "D. Ian Paterson", + "author_inst": "University of Alberta" }, { - "author_name": "Yong Poovorawan", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand, FRS(T), the Royal Society" + "author_name": "Lisa Hartling", + "author_inst": "University of Alberta" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2021.11.18.21266507", @@ -529170,57 +528861,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.17.21266410", - "rel_title": "COVID-19 management in social care in England: a systematic review of changing policies and newspaper reported staff perspectives.", + "rel_doi": "10.1101/2021.11.17.21266392", + "rel_title": "Impact of dexamethasone on persistent symptoms of COVID-19: an observational study", "rel_date": "2021-11-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21266410", - "rel_abs": "Adult social care has been a major focus of public attention and infection control guidance during the COVID-19 pandemic, with a high mortality both for carers and those receiving care. To protect themselves and others from infection, staff in residential and domiciliary care settings had to quickly adapt to infection control measures that heavily impacted on their working and every-day life, whilst navigating new responsibilities, uncertainties and anxieties. We sought to explore the production and reception of guidance and look at ways these can be adapted to improve the working life of care staff in domiciliary and residential care whilst reducing the risk of SARS-CoV-2 transmission amid this pandemic and of future emerging infections.\n\nWe conducted two complementary and integrated systematic reviews of published documents in the pre-vaccination era: (1) National guidance for social care (conducted between 29 July to 28 October 2020), and (2) Newspaper coverage of infection control issues in social care (conducted between 27th July to 10th September 2020).\n\nThree higher order common themes emerged in the integrated systematic review of guidance documents and newspaper articles: a) Testing, b) Personal Protective Equipment, c) Employment. The reviews revealed a sharp disjunction between the content of infection control guidance and its usability and applicability in social care settings. We suggest that infection control guidance needs to be better adapted to social care settings and informed by the sector. The practicalities of care work and care settings need to be at the core of the process for guidance to be relevant and effective. Modes and timings of communications also need to be optimised.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.17.21266392", + "rel_abs": "IntroductionDexamethasone has been shown to reduce mortality for patients hospitalised with acute COVID-19 pneumonia. However, a significant proportion of patients suffer persistent symptoms following COVID-19 and little is known about the longer-term impact of this intervention on symptom burden.\n\nMethodsPatients initially hospitalised with COVID-19 were prospectively recruited to an observational study (April-August 2020) with follow-up at 8 months (Dec 2020-April 2021) post-admission. A review of ongoing symptoms using a standardised systems-based proforma was performed alongside health-related quality of life assessment. In the UK, patients with COVID-19 (requiring oxygen) only received dexamethasone following the pre-print of the RECOVERY trial (June 2020), or as part of randomisation to that trial, allowing for a comparison between patients treated and not treated with dexamethasone.\n\nResultsBetween April to August 2020, 198 patients were recruited to this observational study. 87 required oxygen and were followed up at 8-months, so were eligible for this analysis. Of these 39 received an inpatient course of dexamethasone (cases) and 48 did not (controls). The groups were well matched at baseline in terms of age, comorbidity and frailty score. Over two-thirds of patients reported at least 1 ongoing symptom at 8-month follow-up. Patients in the dexamethasone group reported fewer symptoms (n=73, 1.9 per patient) than the non-dexamethasone group (n=152, 3.2 per patient) (p = 0.01).\n\nConclusionsIn conclusion, in this case-control observational study, patients who received oral dexamethasone for hospitalised COVID-19 were less likely to experience persistent symptoms at 8-month follow-up. These are reassuring results for physicians administering dexamethasone to this patient group.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Lavinia Bertini", - "author_inst": "Department of Primary Care and Public Health, Brighton and Sussex Medical School, Falmer, UK." - }, - { - "author_name": "Leanne Bogen-Johnston", - "author_inst": "School of Psychology, University of Sussex, Falmer, UK" - }, - { - "author_name": "Jo Middleton", - "author_inst": "Department of Primary Care and Public Health, Brighton and Sussex Medical School, Falmer, UK." - }, - { - "author_name": "Wendy Wood", - "author_inst": "School of Health Sciences, University of Brighton, UK." - }, - { - "author_name": "Shanu Sadhwani", - "author_inst": "Department of Primary Care and Public Health, Brighton and Sussex Medical School, Falmer, UK." - }, - { - "author_name": "Julien Forder", - "author_inst": "Personal Social Services Research Unit, University of Kent, Canterbury, UK." + "author_name": "Alice Milne", + "author_inst": "North Bristol NHS Trust" }, { - "author_name": "Daniel Roland", - "author_inst": "Personal Social Services Research Unit, University of Kent, Canterbury, UK." + "author_name": "Nick Maskell", + "author_inst": "University of Bristol" }, { - "author_name": "Rebecca Sharp", - "author_inst": "Kent Surrey Sussex Academic Health Science Network, Worthing, West Sussex, UK." + "author_name": "Charlie Sharp", + "author_inst": "Gloucestershire Hospitals NHS FT" }, { - "author_name": "John Drury", - "author_inst": "School of Psychology, University of Sussex, Falmer, UK." + "author_name": "Fergus W Hamilton", + "author_inst": "University of Bristol" }, { - "author_name": "Jackie A Cassell", - "author_inst": "Department of Primary Care and Public Health, Brighton and Sussex Medical School, Falmer, UK." + "author_name": "David T Arnold", + "author_inst": "University of Bristol" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -530760,89 +530431,85 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.11.15.468720", - "rel_title": "Susceptibility of sheep to experimental co-infection with the ancestral lineage of SARS-CoV-2 and its alpha variant", + "rel_doi": "10.1101/2021.11.15.468761", + "rel_title": "Microglia do not restrict SARS-CoV-2 replication following infection of the central nervous system of K18-hACE2 transgenic mice", "rel_date": "2021-11-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.15.468720", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for a global pandemic that has had significant impacts on human health and economies worldwide. SARS-CoV-2 is highly transmissible and the cause of coronavirus disease 2019 (COVID-19) in humans. A wide range of animal species have also been shown to be susceptible to SARS-CoV-2 infection by experimental and/or natural infections. Domestic and large cats, mink, ferrets, hamsters, deer mice, white-tailed deer, and non-human primates have been shown to be highly susceptible, whereas other species such as mice, dogs, pigs, and cattle appear to be refractory to infection or have very limited susceptibility. Sheep (Ovis aries) are a commonly farmed domestic ruminant that have not previously been thoroughly investigated for their susceptibility to SARS-CoV-2. Therefore, we performed in vitro and in vivo studies which consisted of infection of ruminant-derived cell cultures and experimental challenge of sheep to investigate their susceptibility to SARS-CoV-2. Our results showed that sheep-derived cell cultures support SARS-CoV-2 replication. Furthermore, experimental challenge of sheep demonstrated limited infection with viral RNA shed in nasal and oral swabs primarily at 1-day post challenge (DPC), and also detected in the respiratory tract and lymphoid tissues at 4 and 8 DPC. Sero-reactivity was also observed in some of the principal infected sheep but not the contact sentinels, indicating that transmission to co-mingled naive sheep was not highly efficient; however, viral RNA was detected in some of the respiratory tract tissues of sentinel animals at 21 DPC. Furthermore, we used challenge inoculum consisting of a mixture of two SARS-CoV-2 isolates, representatives of the ancestral lineage A and the B.1.1.7-like alpha variant of concern (VOC), to study competition of the two virus strains. Our results indicate that sheep show low susceptibility to SARS-CoV-2 infection, and that the alpha VOC outcompeted the ancestral lineage A strain.", - "rel_num_authors": 19, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.15.468761", + "rel_abs": "Unlike SARS-CoV-1 and MERS-CoV, infection with SARS-CoV-2, the viral pathogen responsible for COVID-19, is often associated with neurologic symptoms that range from mild to severe, yet increasing evidence argues the virus does not exhibit extensive neuroinvasive properties. We demonstrate SARS-CoV-2 can infect and replicate in human iPSC-derived neurons and that infection shows limited anti-viral and inflammatory responses but increased activation of EIF2 signaling following infection as determined by RNA sequencing. Intranasal infection of K18 human ACE2 transgenic mice (K18-hACE2) with SARS-CoV-2 resulted in lung pathology associated with viral replication and immune cell infiltration. In addition, [~]50% of infected mice exhibited CNS infection characterized by wide-spread viral replication in neurons accompanied by increased expression of chemokine (Cxcl9, Cxcl10, Ccl2, Ccl5 and Ccl19) and cytokine (Ifn-{lambda} and Tnf-) transcripts associated with microgliosis and a neuroinflammatory response consisting primarily of monocytes/macrophages. Microglia depletion via administration of colony-stimulating factor 1 receptor inhibitor, PLX5622, in SARS-CoV-2 infected mice did not affect survival or viral replication but did result in dampened expression of proinflammatory cytokine/chemokine transcripts and a reduction in monocyte/macrophage infiltration. These results argue that microglia are dispensable in terms of controlling SARS-CoV-2 replication in in the K18-hACE2 model but do contribute to an inflammatory response through expression of pro-inflammatory genes. Collectively, these findings contribute to previous work demonstrating the ability of SARS-CoV-2 to infect neurons as well as emphasizing the potential use of the K18-hACE2 model to study immunological and neuropathological aspects related to SARS-CoV-2-induced neurologic disease.\n\nImportanceUnderstanding the immunological mechanisms contributing to both host defense and disease following viral infection of the CNS is of critical importance given the increasing number of viruses that are capable of infecting and replicating within the nervous system. With this in mind, the present study was undertaken to evaluate the role of microglia in aiding in host defense following experimental infection of the central nervous system (CNS) of K18-hACE2 with SARS-CoV-2, the causative agent of COVID-19. Neurologic symptoms that range in severity are common in COVID-19 patients and understanding immune responses that contribute to restricting neurologic disease can provide important insight into better understanding consequences associated with SARS-CoV-2 infection of the CNS.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Natasha N Gaudreault", - "author_inst": "Kansas State University College of Veterinary Medicine" - }, - { - "author_name": "Konner Cool", - "author_inst": "Kansas State University" + "author_name": "Gema M Olivarria", + "author_inst": "University of California, Irvine" }, { - "author_name": "Jessie D Trujillo", - "author_inst": "Kansas State University College of Veterinary Medicine" + "author_name": "Yuting Cheng", + "author_inst": "University of California, Irvine" }, { - "author_name": "Igor Morozov", - "author_inst": "Kansas State University College of Veterinary Medicine" + "author_name": "Collin Pachow", + "author_inst": "University of California, Irvine" }, { - "author_name": "David A Meekins", - "author_inst": "Kansas State University College of Veterinary Medicine" + "author_name": "Lindsay A Hohsfield", + "author_inst": "University of California, Irvine" }, { - "author_name": "Chester D McDowell", - "author_inst": "Kansas State University College of Veterinary Medicine" + "author_name": "Charlene Smith-Geater", + "author_inst": "University of California, Irvine" }, { - "author_name": "Dashzeveg Bold", - "author_inst": "Kansas State University College of Veterinary Medicine" + "author_name": "Ricardo Miramontes", + "author_inst": "University of California, Irvine" }, { - "author_name": "Mariano Carossino", - "author_inst": "Louisiana State University" + "author_name": "Jie Wu", + "author_inst": "University of California, Irvine" }, { - "author_name": "Velmurugan Balaraman", - "author_inst": "Kanasas State University" + "author_name": "Mara S Burns", + "author_inst": "University of California, Irvine" }, { - "author_name": "Dana Mitzel", - "author_inst": "ARS-USDA" + "author_name": "Kate I Tsourmas", + "author_inst": "University of California, Irvine" }, { - "author_name": "Taeyong Kwon", - "author_inst": "Kansas State University" + "author_name": "Jennifer Stocksdale", + "author_inst": "University of California, Irvine" }, { - "author_name": "Daniel W Madden", - "author_inst": "Kansas State University" + "author_name": "Cynthia Manlapaz", + "author_inst": "University of California, Irvine" }, { - "author_name": "Bianca Libanori Artiaga", - "author_inst": "Kansas State University" + "author_name": "Susana Furman", + "author_inst": "University of California, Irvine" }, { - "author_name": "Roman Pogranichniy", - "author_inst": "Kansas State University" + "author_name": "William H Yong", + "author_inst": "University of California, Irvine" }, { - "author_name": "Gleyder Roman-Sosa", - "author_inst": "Kansas State University; Institut fur Virologie, Justus-Liebig-Universitat" + "author_name": "John Teijaro", + "author_inst": "Scripps Research Institute" }, { - "author_name": "William C Wilson", - "author_inst": "USDA-ARS" + "author_name": "Robert Andrew Edwards", + "author_inst": "UC Irvine" }, { - "author_name": "Udeni BR Balasuriya", - "author_inst": "Louisiana State University" + "author_name": "Kim Green", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Adolfo Garcia-Sastre", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Leslie M Thompson", + "author_inst": "University of California, Irvine" }, { - "author_name": "Juergen A Richt", - "author_inst": "Kansas State University" + "author_name": "Thomas Lane", + "author_inst": "University of California, Irvine" } ], "version": "1", @@ -532710,23 +532377,79 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.11.15.468283", - "rel_title": "Mutagenic distinction between the receptor-binding and fusion subunits of the SARS-CoV-2 spike glycoprotein", + "rel_doi": "10.1101/2021.11.12.468374", + "rel_title": "Full protection against all four SARS-CoV-2 variants of concern (VOC) in hamsters requires revision of spike antigen used for vaccination.", "rel_date": "2021-11-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.15.468283", - "rel_abs": "We observe that a residue R of the spike glycoprotein of SARS-CoV-2 which has mutated in one or more of the current Variants of Concern or Interest or under Monitoring rarely participates in a backbone hydrogen bond if R lies in the S1 subunit and usually participates in one if R lies in the S2 subunit. A partial explanation for this based upon free energy is explored as a potentially general principle in the mutagenesis of viral glycoproteins. This observation could help target future vaccine cargos for the evolving coronavirus as well as more generally. A study of the Delta and Omicron variants suggests that Delta was an energetically necessary intermediary in the evolution from Wuhan-Hu-1 to Omicron.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.12.468374", + "rel_abs": "Current first-generation COVID-19 vaccines are based on prototypic spike sequences from ancestral 2019 SARS-CoV-2 strains. However, the ongoing pandemic is fueled by variants of concern (VOC) that threaten to escape vaccine-mediated protection. Here we show in a stringent hamster model that immunization using prototypic spike expressed from a potent YF17D viral vector (1) provides vigorous protection against infection with ancestral virus (B lineage) and VOC Alpha (B.1.1.7), however, is insufficient to provide maximum protection against the Beta (B.1.351) variant. To improve vaccine efficacy, we created a revised vaccine candidate that carries an evolved spike antigen. Vaccination of hamsters with this updated vaccine candidate provides full protection against intranasal challenge with all four VOCs Alpha, Beta, Gamma (P.1) and Delta (B.1.617.2) resulting in complete elimination of infectious virus from the lungs and a marked improvement in lung pathology. Vaccinated hamsters did also no longer transmit the Delta variant to non-vaccinated sentinels. Hamsters immunized with our modified vaccine candidate also mounted marked neutralizing antibody responses against the recently emerged Omicron (B.1.1.529) variant, whereas the old vaccine employing prototypic spike failed to induce immunity to this antigenically distant virus. Overall, our data indicate that current first-generation COVID-19 vaccines need to be urgently updated to cover newly emerging VOCs to maintain vaccine efficacy and to impede virus spread at the community level.\n\nSignificance StatementSARS-CoV-2 keeps mutating rapidly, and the ongoing COVID-19 pandemic is fueled by new variants escaping immunity induced by current first-generation vaccines. There is hence an urgent need for universal vaccines that cover variants of concern (VOC). In this paper we show that an adapted version of our vaccine candidate YF-S0* provides full protection from infection, virus transmission and disease by VOCs Alpha, Beta, Gamma and Delta, and also results in markedly increased levels of neutralizing antibodies against recently emerged Omicron VOC in a stringent hamster model. Our findings underline the necessity to update COVID-19 vaccines to curb the pandemic, providing experimental proof on how to maintain vaccine efficacy in view of an evolving SARS-CoV-2 diversity.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Robert Clark Penner", - "author_inst": "Institut des Hautes Etudes Scientifiques" + "author_name": "Sapna Sharma", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology, Molecular Vaccinology and Vaccine Discovery, Leuve" + }, + { + "author_name": "Thomas Vercruysse", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Translational Platform Virology a" + }, + { + "author_name": "Lorena Sanchez-Felipe", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology, Molecular Vaccinology and Vaccine Discovery, Leuve" + }, + { + "author_name": "Winnie Kerstens", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Translational Platform Virology a" + }, + { + "author_name": "Piet Maes", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Clinical and Epidemiological Virology, Zoonotic Infectious D" + }, + { + "author_name": "Rana Abdelnabi", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology, Molecular Vaccinology and Vaccine Discovery, Leuve" + }, + { + "author_name": "Caroline Shi Foo", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology, Molecular Vaccinology and Vaccine Discovery, Leuve" + }, + { + "author_name": "Viktor Lemmens", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology, Molecular Vaccinology and Vaccine Discovery, Leuve" + }, + { + "author_name": "Dominique Van Looveren", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Translational Platform Virology a" + }, + { + "author_name": "Guy Baele", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Clinical and Epidemiological Virology, Evolutionary and Comp" + }, + { + "author_name": "Birgit Weynand", + "author_inst": "KU Leuven Department of Imaging and Pathology, Translational Cell and Tissue Research, B-3000 Leuven, Belgium" + }, + { + "author_name": "Philippe Lemey", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Clinical and Epidemiological Virology, Evolutionary and Comp" + }, + { + "author_name": "Johan Neyts", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology, Molecular Vaccinology and Vaccine Discovery, Leuve" + }, + { + "author_name": "Hendrik Jan Thibaut", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Translational Platform Virology a" + }, + { + "author_name": "Kai Dallmeier", + "author_inst": "KU Leuven Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology, Molecular Vaccinology and Vaccine Discovery, Leuve" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.11.14.468537", @@ -534768,107 +534491,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.10.467646", - "rel_title": "Total virome characterizations of game animals in China reveals a spectrum of emerging viral pathogens", + "rel_doi": "10.1101/2021.11.10.468174", + "rel_title": "Serum from COVID-19 patients early in the pandemic shows limited evidence of cross-neutralization against variants of concern", "rel_date": "2021-11-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.10.467646", - "rel_abs": "Game animals are wildlife species often traded and consumed as exotic food, and are potential reservoirs for SARS-CoV and SARS-CoV-2. We performed a meta-transcriptomic analysis of 1725 game animals, representing 16 species and five mammalian orders, sampled across China. From this we identified 71 mammalian viruses, with 45 described for the first time. Eighteen viruses were considered as potentially high risk to humans and domestic animals. Civets (Paguma larvata) carried the highest number of potentially high risk viruses. We identified the transmission of Bat coronavirus HKU8 from a bat to a civet, as well as cross-species jumps of coronaviruses from bats to hedgehogs and from birds to porcupines. We similarly identified avian Influenza A virus H9N2 in civets and Asian badgers, with the latter displaying respiratory symptoms, as well as cases of likely human-to-wildlife virus transmission. These data highlight the importance of game animals as potential drivers of disease emergence.\n\nHighlightsO_LI1725 game animals from five mammalian orders were surveyed for viruses\nC_LIO_LI71 mammalian viruses were discovered, 18 with a potential risk to humans\nC_LIO_LICivets harbored the highest number of potential high risk viruses\nC_LIO_LIA species jump of an alphacoronavirus from bats to a civet was identified\nC_LIO_LIH9N2 influenza virus was detected in a civet and an Asian badger\nC_LIO_LIHumans viruses were also identified in game animals\nC_LI", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.10.468174", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) results in a variety of clinical symptoms ranging from no or mild to severe disease. Currently, there are multiple postulated mechanisms that may push a moderate to severe disease into a critical state. Human serum contains abundant evidence of the immune status following infection. Cytokines, chemokines, and antibodies can be assayed to determine the extent to which a patient responded to a pathogen. We examined serum and plasma from a cohort of patients infected with SARS-CoV-2 early in the pandemic and compared them to negative-control sera. Cytokine and chemokine concentrations varied depending on the severity of infection, and antibody responses were significantly increased in severe cases compared to mild to moderate infections. Neutralization data revealed that patients with high titers against an early 2020 isolate had detectable but limited neutralizing antibodies against newly circulating SARS-CoV-2 variants of concern. This study highlights the potential of re-infection for recovered COVID-19 patients.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Wan-Ting He", - "author_inst": "Nanjing Agricultural University" - }, - { - "author_name": "Xin Hou", - "author_inst": "Sun Yat-sen University" - }, - { - "author_name": "Jin Zhao", - "author_inst": "Nanjing Agricultural University" - }, - { - "author_name": "Jiumeng Sun", - "author_inst": "Nanjing Agricultural University" - }, - { - "author_name": "Haijian He", - "author_inst": "Agricultural College, Jinhua Polytechnic" - }, - { - "author_name": "Wei Si", - "author_inst": "Zhejiang University" - }, - { - "author_name": "Jing Wang", - "author_inst": "Sun Yat-sen University" - }, - { - "author_name": "Zhiwen Jiang", - "author_inst": "Nanjing Agricultural University" - }, - { - "author_name": "Ziqing Yan", - "author_inst": "Nanjing Agricultural University" - }, - { - "author_name": "Gang Xing", - "author_inst": "Zhejiang University" - }, - { - "author_name": "Meng Lu", - "author_inst": "Nanjing Agricultural University" - }, - { - "author_name": "Marc A Suchard", - "author_inst": "University of California Los Angeles" - }, - { - "author_name": "Xiang Ji", - "author_inst": "University of California Los Angeles & Tulane University" - }, - { - "author_name": "Wenjie Gong", - "author_inst": "Chinese Academy of Agricultural Sciences" - }, - { - "author_name": "Biao He", - "author_inst": "Chinese Academy of Agricultural Sciences" - }, - { - "author_name": "Jun Li", - "author_inst": "City University of Hong Kong" + "author_name": "Andrea Marzi", + "author_inst": "National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Philippe Lemey", - "author_inst": "KU Leuven" + "author_name": "Amanda Griffin", + "author_inst": "National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Deyin Guo", - "author_inst": "Sun Yat-sen University" + "author_name": "Kyle Shifflett", + "author_inst": "NIAID, NIH" }, { - "author_name": "Changchun Tu", - "author_inst": "Chinese Academy of Agricultural Sciences" + "author_name": "John-Paul Lavik", + "author_inst": "Indiana University School of Medicine" }, { - "author_name": "Edward C Holmes", - "author_inst": "University of Sydney" + "author_name": "Patrick M Russell", + "author_inst": "Indiana University School of Medicine" }, { - "author_name": "Mang Shi", - "author_inst": "Sun Yat-sen University" + "author_name": "Michelle K. Zimmerman", + "author_inst": "Indiana University Bloomington" }, { - "author_name": "Shuo Su", - "author_inst": "Nanjing Agricultural University" + "author_name": "Ryan F. Relich", + "author_inst": "Indiana University School of Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc0", "type": "new results", - "category": "zoology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.11.10.467990", @@ -536430,71 +536093,151 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.11.10.21266195", - "rel_title": "Disparities in COVID-19 Fatalities among Working Californians", + "rel_doi": "10.1101/2021.11.10.21266168", + "rel_title": "Antibody decay, T cell immunity and breakthrough infections following two SARS-CoV-2 vaccine doses in infliximab- and vedolizumab-treated patients", "rel_date": "2021-11-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.10.21266195", - "rel_abs": "BackgroundInformation on the occupational distribution of COVID-19 mortality is limited.\n\nObjectiveTo characterize COVID-19 fatalities among working Californians.\n\nDesignRetrospective study of laboratory-confirmed COVID-19 fatalities with dates of death from January 1 to December 31, 2020.\n\nSettingCalifornia.\n\nParticipantsCOVID-19 accounted for 8,050 (9.9%) of 81,468 fatalities among Californians 18-64 years old. Of these decedents, 2,486 (30.9%) were matched to state employment records and classified as \"confirmed working.\" The remainder were classified as \"likely working\" (n=4,121 [51.2%]) or \"not working\" (n=1,443 [17.9%]) using death certificate and case registry data.\n\nMeasurementsWe calculated age-adjusted overall and occupation-specific COVID-19 mortality rates using 2019 American Community Survey denominators.\n\nResultsConfirmed and likely working COVID-19 decedents were predominantly male (76.3%), Latino (68.7%), and foreign-born (59.6%), with high school or less education (67.9%); 7.8% were Black. The overall age-adjusted COVID-19 mortality rate was 30.0 per 100,000 workers (95% confidence interval [CI], 29.3-30.8). Workers in nine occupational groups had mortality rates higher than this overall rate, including those in farming (78.0; 95% CI, 68.7-88.2); material moving (77.8; 95% CI, 70.2-85.9); construction (62.4; 95% CI, 57.7-67.4); production (60.2; 95% CI, 55.7-65.0); and transportation (57.2; 95% CI, 52.2-62.5) occupations. While occupational differences in mortality were evident across demographic groups, mortality rates were three-fold higher for male compared with female workers and three- to seven-fold higher for Latino and Black workers compared with Asian and White workers.\n\nLimitationsThe requirement that fatalities be laboratory-confirmed and the use of 2019 denominator data may underestimate the occupational burden of COVID-19 mortality.\n\nConclusionCalifornians in manual labor and in-person service occupations experienced disproportionate COVID-19 mortality, with the highest rates observed among male, Latino, and Black workers.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.10.21266168", + "rel_abs": "We report SARS-CoV-2 vaccine-induced immunity and risk of breakthrough infections in patients with inflammatory bowel disease treated with infliximab, a commonly used anti-TNF drug and those treated with vedolizumab, a gut-specific antibody targeting integrin a4b7 that does not impact systemic immunity. In infliximab-treated patients, the magnitude of anti-SARS-CoV2 antibodies was reduced 4-6-fold. One fifth of both infliximab- and vedolizumab-treated patients did not mount a T cell response. Antibody half-life was shorter in infliximab-treated patients. Breakthrough SARS-CoV-2 infections occurred more frequently in infliximab-treated patients and the risk was predicted by the level of antibody response after second vaccine dose. Overall, recipients of two doses of the BNT162b2 vaccine had higher anti-SARS-CoV-2 antibody concentrations, higher seroconversion rates, shorter antibody half-life and less breakthrough infections compared to ChAdOx1 nCoV-19 vaccine recipients. Irrespective of biologic treatment, higher, more sustained antibody levels were observed in patients with a history of SARS-CoV-2 infection prior to vaccination. Patients treated with anti-TNF therapy should be offered third vaccine doses.", + "rel_num_authors": 33, "rel_authors": [ { - "author_name": "Kristin J Cummings", - "author_inst": "California Department of Public Health" + "author_name": "Simeng Lin", + "author_inst": "Department of Gastroenterology, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK" }, { - "author_name": "John Beckman", - "author_inst": "California Department of Public Health" + "author_name": "Nicholas A Kennedy", + "author_inst": "Department of Gastroenterology, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK" }, { - "author_name": "Matthew Frederick", - "author_inst": "California Department of Public Health" + "author_name": "Aamir Saifuddin", + "author_inst": "Department of Gastroenterology, St Marks Hospital and Academic Institute, London, UK" }, { - "author_name": "Robert Harrison", - "author_inst": "California Department of Public Health" + "author_name": "Diana Mu\u00f1oz Sandoval", + "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" }, { - "author_name": "Alyssa Nguyen", - "author_inst": "California Department of Public Health" + "author_name": "Catherine J Reynolds", + "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" }, { - "author_name": "Robert Snyder", - "author_inst": "California Department of Public Health" + "author_name": "Rocio Castro Seoane", + "author_inst": "Department of Immunology and Inflammation, Imperial College London, London, United Kingdom" }, { - "author_name": "Elena Chan", - "author_inst": "California Department of Public Health" + "author_name": "Sherine H Kottoor", + "author_inst": "Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK" }, { - "author_name": "Kathryn Gibb", - "author_inst": "California Department of Public Health" + "author_name": "Franziska P Pieper", + "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" }, { - "author_name": "Andrea Rodriguez", - "author_inst": "California Department of Public Health" + "author_name": "Kai-Min Lin", + "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" }, { - "author_name": "Jessie Wong", - "author_inst": "California Department of Public Health" + "author_name": "David K Butler", + "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" }, { - "author_name": "Erin L Murray", - "author_inst": "California Department of Public Health" + "author_name": "Neil Chanchlani", + "author_inst": "Exeter Inflammatory Bowel Disease and Pharmacogenetics Research Group, University of Exeter, UK" }, { - "author_name": "Seema Jain", - "author_inst": "California Department of Public Health" + "author_name": "Rachel Nice", + "author_inst": "Exeter Inflammatory Bowel Disease and Pharmacogenetics Research Group, University of Exeter, UK" }, { - "author_name": "Ximena Vergara", - "author_inst": "California Department of Public Health" + "author_name": "Desmond Chee", + "author_inst": "Department of Gastroenterology, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK" + }, + { + "author_name": "Claire Bewshea", + "author_inst": "Exeter Inflammatory Bowel Disease and Pharmacogenetics Research Group, University of Exeter, UK" + }, + { + "author_name": "Malik Janjua", + "author_inst": "Department of Gastroenterology, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK" + }, + { + "author_name": "Timothy J McDonald", + "author_inst": "Department of Biochemistry, Exeter Clinical Laboratory International, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK" + }, + { + "author_name": "Shaji Sebastian", + "author_inst": "Department of Gastroenterology, Hull University Teaching Hospitals NHS Trust, Hull, UK" + }, + { + "author_name": "James L Alexander", + "author_inst": "Department of Gastroenterology, Imperial College Healthcare NHS Trust, London, UK" + }, + { + "author_name": "Laura Constable", + "author_inst": "Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK" + }, + { + "author_name": "James C Lee", + "author_inst": "Department of Gastroenterology, Royal Free London NHS Foundation Trust, London, UK" + }, + { + "author_name": "Charles D Murray", + "author_inst": "Department of Gastroenterology, Royal Free London NHS Foundation Trust, London, UK" + }, + { + "author_name": "Ailsa L Hart", + "author_inst": "Department of Gastroenterology, St Marks Hospital and Academic Institute, London, UK" + }, + { + "author_name": "Peter M Irving", + "author_inst": "Department of Gastroenterology, Guy's and St Thomas' NHS Foundation Trust, London, UK" + }, + { + "author_name": "Gareth-Rhys Jones", + "author_inst": "Department of Gastroenterology, Western General Hospital, NHS Lothian, Edinburgh, UK" + }, + { + "author_name": "Klaartje B Kok", + "author_inst": "Department of Gastroenterology, Royal London Hospital, Barts Health NHS Trust, London, UK" + }, + { + "author_name": "Christopher A Lamb", + "author_inst": "Department of Gastroenterology, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, UK" + }, + { + "author_name": "Charlie W Lees", + "author_inst": "Department of Gastroenterology, Western General Hospital, NHS Lothian, Edinburgh, UK" + }, + { + "author_name": "Daniel M Altmann", + "author_inst": "Department of Immunology and Inflammation, Imperial College London, London, United Kingdom" + }, + { + "author_name": "Rosemary J Boyton", + "author_inst": "Department of Infectious Disease, Imperial College London, London, UK" + }, + { + "author_name": "James R Goodhand", + "author_inst": "Department of Gastroenterology, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK" + }, + { + "author_name": "Nick Powell", + "author_inst": "Department of Gastroenterology, Imperial College Healthcare NHS Trust, London, UK" + }, + { + "author_name": "Tariq Ahmad", + "author_inst": "Department of Gastroenterology, Royal Devon and Exeter NHS Foundation Trust, Exeter, UK" + }, + { + "author_name": "- Contributors to the CLARITY IBD study", + "author_inst": "" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "gastroenterology" }, { "rel_doi": "10.1101/2021.11.09.21266105", @@ -538383,59 +538126,79 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.04.21265951", - "rel_title": "Validation of a rapid and sensitive SARS-CoV-2 screening system developed for pandemic-scale infection surveillance", + "rel_doi": "10.1101/2021.11.05.21265961", + "rel_title": "Three doses of COVID-19 mRNA vaccination are safe based on adverse events reported in electronic health records", "rel_date": "2021-11-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.04.21265951", - "rel_abs": "Without any realistic prospect of comprehensive global vaccine coverage and lasting immunity, control of pandemics such as COVID-19 will require implementation of large-scale, rapid identification and isolation of infectious individuals to limit further transmission. Here, we describe an automated, high-throughput integrated screening platform, incorporating saliva-based loop-mediated isothermal amplification (LAMP) technology, that is designed for population-scale sensitive detection of infectious carriers of SARS-CoV-2 RNA. Central to this surveillance system is the \"Sentinel\" testing instrument, which is capable of reporting results within 25 minutes of saliva sample collection with a throughput of up to 3,840 results per hour. It incorporates continuous flow loading of samples at random intervals to cost-effectively adjust for fluctuations in testing demand. Independent validation of our saliva-based RT-LAMP technology on an automated LAMP instrument coined the \"Sentinel\", found 98.7% sensitivity, 97.6% specificity, and 98% efficiency against a RT-PCR comparator assay, confirming its suitability for surveillance screening. This Sentinel surveillance system offers a feasible and scalable approach to complement vaccination, to curb the spread of COVID-19 variants, and control future pandemics to save lives.\n\nOne-Sentence SummaryDevelopment of a high-throughput LAMP-based automated continuous flow, random access SARS-CoV-2 screening platform with sufficient sensitivity and specificity to enable pandemic-scale population testing of infectious individuals using saliva sampling.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.05.21265961", + "rel_abs": "Recent reports on waning of COVID-19 vaccine induced immunity have led to the approval and roll-out of additional dose and booster vaccinations. At risk individuals are receiving additional vaccine dose(s), in addition to the regimen that was tested in clinical trials. The risks and the adverse event profiles associated with these additional vaccine doses are currently not well understood. Here, we performed a retrospective study analyzing vaccine-associated adverse events using electronic health records (EHRs) of individuals that have received three doses of mRNA-based COVID-19 vaccines (n = 47,999). By comparing symptoms reported in 2-week time periods after each vaccine dose and in a 2-week period before the 1st vaccine dose, we assessed the risk associated with 3rd dose vaccination, for both BNT162b2 and mRNA-1273. Reporting of severe adverse events remained low after the 3rd vaccine dose, with rates of pericarditis (0.01%, 0%-0.02% 95% CI), anaphylaxis (0.00%, 0%-0.01% 95% CI), myocarditis (0.00%, 0%-0.01% 95% CI), and cerebral venous sinus thrombosis (no cases), consistent with earlier studies. Significantly more individuals (p-value < 0.05) report low-severity adverse events after their 3rd dose compared with after their 2nd dose, including fatigue (4.92% after 3rd dose vs 3.47% after 2nd dose), lymphadenopathy (2.89% vs 2.07%), nausea (2.62% vs 2.04%), headache (2.47% vs 2.07%), arthralgia (2.12% vs 1.70%), myalgia (1.99% vs 1.63%), diarrhea (1.70% vs 1.24%), fever (1.11% vs 0.81%), vomiting (1.10% vs 0.80%), and chills (0.47% vs 0.36%). Our results show that although 3rd dose vaccination against SARS-CoV-2 infection led to increased reporting of low-severity adverse events, risk of severe adverse events remained comparable to the standard 2-dose regime. This study provides support for the safety of 3rd vaccination doses of individuals that are at high-risk of severe COVID-19 and breakthrough infection.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Robert Dewhurst", - "author_inst": "Perron Institute for Neurological and Translational Science" + "author_name": "Michiel J.M. Niesen", + "author_inst": "Nference" }, { - "author_name": "Tatjana Heinrich", - "author_inst": "Perron Institute for Neurological and Translational Science" + "author_name": "Colin Pawlowski", + "author_inst": "Nference" }, { - "author_name": "Paul Watt", - "author_inst": "Avicena Systems" + "author_name": "John C O'Horo", + "author_inst": "Mayo Clinic" }, { - "author_name": "Paul Ostergaard", - "author_inst": "Avicena Systems" + "author_name": "Doug W Challener", + "author_inst": "Mayo Clinic" }, { - "author_name": "Jose Maria Marimon", - "author_inst": "Donostialdea Integrated Health Organization" + "author_name": "Eli Silvert", + "author_inst": "Nference" }, { - "author_name": "Mariana Moreira", - "author_inst": "Lancs Lamp Laboratory" + "author_name": "Greg Donadio", + "author_inst": "Nference" }, { - "author_name": "Philip E Houldsworth", - "author_inst": "Lancs Lamp Laboratory" + "author_name": "Patrick J Lenehan", + "author_inst": "nference" }, { - "author_name": "Jack Dylan Rudrum", - "author_inst": "Perron Institute for Neurological and Translational Science" + "author_name": "Abinash Virk", + "author_inst": "Mayo Clinic" }, { - "author_name": "David Wood", - "author_inst": "University of Western Australia" + "author_name": "Melanie D. Swift", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Leigh Speicher", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Holly L. Geyer", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "John Halamka", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Aiveliagaram J Venkatakrishnan", + "author_inst": "Nference" + }, + { + "author_name": "Venky Soundararajan", + "author_inst": "nference" }, { - "author_name": "Sulev Koks", - "author_inst": "Perron Institute for Neurological and Translational Science" + "author_name": "Andrew D. Badley", + "author_inst": "Mayo Clinic" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.11.05.21265962", @@ -539893,59 +539656,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.08.467648", - "rel_title": "Phage-like particle vaccines are highly immunogenic and protect against pathogenic coronavirus infection and disease", + "rel_doi": "10.1101/2021.11.05.21265977", + "rel_title": "Waning, Boosting and a Path to Endemicity for SARS-CoV-2.", "rel_date": "2021-11-09", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.11.08.467648", - "rel_abs": "The response by vaccine developers to the COVID-19 pandemic has been extraordinary with effective vaccines authorized for emergency use in the U.S. within one year of the appearance of the first COVID-19 cases. However, the emergence of SARS-CoV-2 variants and obstacles with the global rollout of new vaccines highlight the need for platforms that are amenable to rapid tuning and stable formulation to facilitate the logistics of vaccine delivery worldwide. We developed a \"designer nanoparticle\" platform using phage-like particles (PLPs) derived from bacteriophage lambda for multivalent display of antigens in rigorously defined ratios. Here, we engineered PLPs that display the receptor binding domain (RBD) protein from SARS-CoV-2 and MERS-CoV, alone (RBDSARS-PLPs, RBDMERS-PLPs) and in combination (hCoV-RBD PLPs). Functionalized particles possess physiochemical properties compatible with pharmaceutical standards and retain antigenicity. Following primary immunization, BALB/c mice immunized with RBDSARS- or RBDMERS-PLPs display serum RBD-specific IgG endpoint and live virus neutralization titers that, in the case of SARS-CoV-2, were comparable to those detected in convalescent plasma from infected patients. Further, these antibody levels remain elevated up to 6 months post-prime. In dose response studies, immunization with as little as one microgram of RBDSARS-PLPs elicited robust neutralizing antibody responses. Finally, animals immunized with RBDSARS-PLPs, RBDMERS-PLPs, and hCoV-RBD PLPs were protected against SARS-CoV-2 and/or MERS-CoV lung infection and disease. Collectively, these data suggest that the designer PLP system provides a platform for facile and rapid generation of single and multi-target vaccines.", - "rel_num_authors": 10, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.05.21265977", + "rel_abs": "In many countries, an extensive vaccination programme has substantially reduced the public-health impact of SARS-CoV-2, limiting the number of hospital admissions and deaths compared to an unmitigated epidemic. Ensuring a low-risk transition from the current situation to one in which SARS-CoV-2 is endemic requires maintenance of high levels of population immunity. The observed waning of vaccine efficacy over time suggests that booster doses may be required to maintain population immunity especially in the most vulnerable groups. Here, using data and models for England, we consider the dynamics of COVID-19 over a two-year time-frame, and the role that booster vaccinations can play in mitigating the worst effects. We find that boosters are necessary to suppress the imminent wave of infections that would be generated by waning vaccine efficacy. Projecting further into the future, the optimal deployment of boosters is highly sensitive to their long-term action. If protection from boosters wanes slowly (akin to protection following infection) then a single booster dose to the over 50s may be all that is needed over the next two-years. However, if protection wanes more rapidly (akin to protection following second dose vaccination) then annual or even biannual boosters are required to limit subsequent epidemic peaks an reduce the pressure on public health services.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Bennett J Davenport", - "author_inst": "University of Colorado School of Medicine" - }, - { - "author_name": "Alexis Catala", - "author_inst": "University of Colorado School of Medicine" - }, - { - "author_name": "Stuart M Weston", - "author_inst": "University of Maryland School of Medicine" - }, - { - "author_name": "Robert M Johnson", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Matt J Keeling", + "author_inst": "University of Warwick" }, { - "author_name": "Jeremy Ardunay", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Amy C Thomas", + "author_inst": "University of Bristol" }, { - "author_name": "Holly L Hammond", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Edward M Hill", + "author_inst": "University of Warwick" }, { - "author_name": "Carly Dillen", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Robin N Thompson", + "author_inst": "University of Warwick" }, { - "author_name": "Matthew B Frieman", - "author_inst": "University of Maryland School of Medicine" + "author_name": "Louise Dyson", + "author_inst": "University of Warwick" }, { - "author_name": "Carlos E Catalano", - "author_inst": "University of Colorado Skaggs School of Pharmacy and Pharmaceutical Sciences" + "author_name": "Michael Tildesley", + "author_inst": "University of Warwick" }, { - "author_name": "Thomas E Morrison", - "author_inst": "University of Colorado School of Medicine" + "author_name": "Sam Moore", + "author_inst": "University of Warwick" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "immunology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.11.05.21265992", @@ -541923,99 +541674,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.11.04.21265780", - "rel_title": "Immunogenicity and safety of the homogenous booster shot of a recombinant fusion protein vaccine (V-01) against COVID-19 in healthy adult participants primed with a two-dose regimen", - "rel_date": "2021-11-08", + "rel_doi": "10.1101/2021.11.04.21265924", + "rel_title": "Can I Afford To Be On Campus?: Do College Students with Disabilities Understand COVID-19 Vaccination Costs?", + "rel_date": "2021-11-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.04.21265780", - "rel_abs": "BackgroundRising concerns over waning immunity and reduction in neutralizing activity against variants of concern (VOCs) have contributed to deploying booster doses by different strategies to tackle the COVID-19 pandemic. Preliminary findings from Phase I and II have shown that V-01, a recombinant fusion protein vaccine against COVID-19, exhibited favorable safety and immunogenicity profiles in 1060 adult participants of both younger and senior age. Herein, we aimed to assess the immunogenicity and safety for a booster dose in participants previously primed with a two-dose 10g V-01 regimen (day 0, 21) from phase I trial, providing reassuring data for necessity and feasibility of a homogenous booster dose.\n\nMethodsWe conducted a single-arm, open-label trial at the Guangdong Provincial Center for Disease Control and Prevention (Gaozhou, China). Forty-three eligible participants who were previously primed 4-5 months earlier with two-dose 10g V-01 regimen from phase I trial received booster vaccination. We primarily assessed the immunogenicity post-booster vaccination, measured by RBD-binding antibodies using ELISA and neutralizing activity against wild-type SARS-CoV-2 and emerging variants of concern (VOCs) using neutralization assays. We secondarily assessed the safety and reactogenicity of the booster vaccination.\n\nResultsThe third dose of V-01 exhibited significant boosting effects of humoral immune response in participants primed with two-dose 10g V-01 regimen regarding both wild-type SARS-CoV-2 and VOCs. We observed a 60.4-folds increase in neutralizing titres against SARS-CoV-2 of younger adults, with GMTs of 17 (95%CI: 12-23) prior to booster vaccination in comparison to 1017 (95%CI: 732-1413) at day 14 post booster vaccination; and a 53.6-folds increase in that of older adults, with GMTs of 14 (95%CI: 9-20) before booster vaccination in comparison to 729(95%CI: 397-1339) at day 14 post-booster vaccination. The neutralizing titres against SARS-CoV-2 Delta strain also demonstrated a sharp increase from the day of pre booster vaccination to day 14 post booster vaccination, with GMTs of 11 (95%CI:8-15) versus 383 (95%CI:277-531) in younger adults (35.4-folds increase), and 6.5(95%CI: 5-8) versus 300(95%CI:142-631) in older adults (46.0-folds increase), respectively. We also observed a considerable and consistent increase of pseudovirus neutralizing titres against emerging VOCs from day 28 post second vaccination to day 14 post booster vaccination, with GMTs of 206 (95%CI:163-259) versus 607 (95%CI: 478-771) for Alpha strain, 54 (95%CI:38-77) versus 329 (95%CI: 255-425) for Beta strain, 219 (95%CI:157-306) versus 647 (95%CI: 484-865) for Delta strain. Our preliminary findings indicate a homogenous booster dose of V-01 was safe and well-tolerated, with overall adverse reactions being absent or mild-to-moderate in severity, and no grade 3 or worse AEs were related to booster vaccination.\n\nConclusionsA homogenous booster immunization in participants receiving a primary series of two-dose V-01 elicited a substantial humoral immune response against wild-type SARS-CoV-2 and emerging VOCs, along with a favorable safety and reactogenicity profile. Our study provided promising data for a homogenous prime-boost strategy using recombinant protein vaccine to tackle the ongoing pandemic, potentially providing broad protection against emerging VOCs and overcoming waning immunity.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.04.21265924", + "rel_abs": "Institutions of higher education have mandated COVID-19 vaccinations for students wishing to return to an on-campus, in-person learning experience. However, college students with disabilities (SWDs) may be hesitant to take a COVID-19 vaccine for a variety of reasons, possibly delaying or denying these students access to higher education. Yet, an under-researched aspect of COVID-19 vaccinations and related communication is whether college students with disabilities understand that the COVID-19 vaccine is free and whether that understanding varies by intersectional identities. As a result, this studys research team surveyed 245 college students with disabilities to explore these students knowledge of vaccine costs and whether differences exist between groups. Data suggests many college students with disabilities do not know that COVID-19 vaccinations are free: White/Caucasian SWDs were most aware of COVID-19 vaccines being free (23.6%), while Latinx students were least aware (1.3%). Moreover, women were more aware of free COVID-19 vaccines (14.8%) than men (11.4%), first generation college students were more aware (15.6%) than non-first generation college students (12.2%), and full-time students (19%) were more aware than part-time students (8.9%). Overall, less than 25% of SWDs understood that COVID-19 vaccines are free. Implications for health communication, vaccine awareness, and higher education policy are addressed.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Yuan Li", - "author_inst": "Guangdong Provincial Institute of Biological Products and Materia Medica, Guangzhou, China" - }, - { - "author_name": "Xin Fang", - "author_inst": "National Institutes for Food and Drug Control, Beijing, China" - }, - { - "author_name": "Rongjuan Pei", - "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China" - }, - { - "author_name": "Renfeng Fan", - "author_inst": "Guangdong Provincial Institute of Biological Products and Materia Medica, Guangzhou, China" - }, - { - "author_name": "Shaomin Chen", - "author_inst": "Guangdong Provincial Institute of Biological Products and Materia Medica, Guangzhou, China" - }, - { - "author_name": "Peiyu Zeng", - "author_inst": "Gaozhou Center for Disease Control and Prevention, Maoming, China" - }, - { - "author_name": "Zhiqiang Ou", - "author_inst": "Guangdong Provincial Institute of Biological Products and Materia Medica, Guangzhou, China" - }, - { - "author_name": "Jinglong Deng", - "author_inst": "Gaozhou Center for Disease Control and Prevention, Maoming, China" - }, - { - "author_name": "Jian Zhou", - "author_inst": "Gaozhou Center for Disease Control and Prevention, Maoming, China" - }, - { - "author_name": "Zehui Sun", - "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China" - }, - { - "author_name": "Lishi Liu", - "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences, Wuhan, China" - }, - { - "author_name": "Hua Peng", - "author_inst": "Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China" - }, - { - "author_name": "Xujia Chen", - "author_inst": "LivzonBio Inc., Zhuhai, China" - }, - { - "author_name": "Zhipeng Su", - "author_inst": "LivzonBio Inc., Zhuhai, China" - }, - { - "author_name": "Xi Chen", - "author_inst": "LivzonBio Inc., Zhuhai, China" - }, - { - "author_name": "Jianfeng He", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China" - }, - { - "author_name": "Wuxiang Guan", - "author_inst": "Wuhan Institute of Virology Chinese Academy of Sciences" - }, - { - "author_name": "Zhongyu Hu", - "author_inst": "National Institutes for Food and Drug Control, Beijing, China" - }, - { - "author_name": "Yang-Xin Fu", - "author_inst": "Department of Basic Medical Sciences, School of Medicine, Tsinghua University, Beijing, China" + "author_name": "Zach W. Taylor", + "author_inst": "The University of Texas at Austin" }, { - "author_name": "Jikai Zhang", - "author_inst": "Guangdong Provincial Institute of Biological Products and Materia Medica, Guangzhou, China" + "author_name": "Chelseaia Charran", + "author_inst": "The University of Texas at Austin" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "health policy" }, { "rel_doi": "10.1101/2021.11.04.21265948", @@ -543757,117 +543436,65 @@ "category": "medical education" }, { - "rel_doi": "10.1101/2021.11.02.21265778", - "rel_title": "Plasma markers of neurologic injury and systemic inflammation in individuals with self-reported neurologic post-acute sequelae of SARS-CoV-2 infection (PASC)", + "rel_doi": "10.1101/2021.11.04.21265921", + "rel_title": "Prevalence of Antibodies to SARS-CoV-2 following natural infection and vaccination in Irish Hospital Healthcare Workers; changing epidemiology as the pandemic progresses", "rel_date": "2021-11-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.02.21265778", - "rel_abs": "BackgroundThe biologic mechanisms underlying neurologic post-acute-sequelae of SARS-CoV-2 infection (PASC) are incompletely understood.\n\nMethodsWe measured markers of neuronal injury (glial fibrillary acidic protein [GFAP], neurofilament light chain [NfL]) and soluble markers of inflammation among a cohort of people with prior confirmed SARS-CoV-2 infection at early and late recovery following the initial illness (defined as less than and greater than 90 days, respectively). The primary clinical outcome was the presence of self-reported central nervous system (CNS) PASC symptoms during the late recovery timepoint. We compared fold-changes in marker values between those with and without CNS PASC symptoms using linear mixed effects models and examined relationships between neurologic and immunologic markers using rank linear correlations.\n\nResultsOf 121 individuals, 52 reported CNS PASC symptoms. During early recovery, those who went on to report CNS PASC symptoms had elevations in GFAP (1.3-fold higher mean ratio, 95% CI 1.04-1.63, p=0.02), but not NfL (1.06-fold higher mean ratio, 95% CI 0.89-1.26, p=0.54). During late recovery, neither GFAP nor NfL levels were elevated among those with CNS PASC symptoms. Although absolute levels of NfL did not differ, those who reported CNS PASC symptoms demonstrated a stronger downward trend over time in comparison to those who did not report CNS PASC symptoms (p=0.041). Those who went on to report CNS PASC also exhibited elevations in IL-6 (48% higher during early recovery and 38% higher during late recovery), MCP-1 (19% higher during early recovery), and TNF-alpha (19% higher during early recovery and 13% higher during late recovery). GFAP and NfL correlated with levels of several immune activation markers during early recovery; these correlations were attenuated during late recovery.\n\nConclusionsSelf-reported neurologic symptoms present >90 days following SARS-CoV-2 infection are associated with elevations in markers of neurologic injury and inflammation at early recovery timepoints, suggesting that early injury can result in long-term disease. The correlation of GFAP and NfL with markers of systemic immune activation suggests one possible mechanism that might contribute to these symptoms. Additional work is needed to better characterize these processes and to identify interventions to prevent or treat this condition.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSDo individuals with and without self-reported neurologic symptoms following SARS-CoV-2 infection have different levels of biomarkers of neurologic injury or immune activationa\n\nFindingsIn this cohort study of 121 adults, individuals reporting neurologic symptoms beyond 90 days following SARS-CoV-2 infection had higher levels of glial fibrillary acidic protein but not neurofilament light chain. Levels of several markers of inflammation including interleukin-6, tumor necrosis factor-alpha, and monocyte chemoattractant protein-1 were also elevated.\n\nMeaningPost-acute neurologic symptoms following SARS-CoV-2 infection are associated with significant differences in levels of certain biomarkers. Further investigation may provide clues to the biologic pathways underlying these symptoms.", - "rel_num_authors": 25, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.04.21265921", + "rel_abs": "BackgroundIn October 2020 SARS-CoV-2 seroprevalence among hospital healthcare workers (HCW) of two Irish hospitals was 15% and 4.1% respectively. We compare seroprevalence in the same HCW population six months later, assess changes in risk factors for seropositivity with progression of the pandemic and serological response to vaccination.\n\nMethodsAll staff of both hospitals (N=9038) were invited to participate in an online questionnaire and SARS-CoV-2 antibody testing in April 2021. We measured anti-nucleocapsid and anti-spike antibodies. Frequencies and percentages for positive SARS-CoV-2 antibodies were calculated and adjusted relative risks for participant characteristics were calculated using multivariable regression analysis.\n\nResults5085 HCW participated. Seroprevalence increased to 21% and 13% respectively; 26% of infections were previously undiagnosed. Black ethnicity (aRR 1.7, 95% CI 1.3-2.2, p<.001), lower level of education (aRR 1.4 for secondary level education, 95% CI 1.1-1.8, p=0.002), living with other HCW (aRR 1.2, 95% CI 1.0-1.4, p=0.007) were significantly associated with seropositivity. Having direct patient contact also carried a significant risk (being a healthcare assistant (aRR 1.8, 95% CI 1.3-2.3, p<.001), being a nurse (aRR 1.4, 95% CI 1.1-1.5, p=0.022), daily contact with COVID-19 patients (aRR 1.4, 95% CI 1.1-1.7, p=0.002), daily contact with patients without suspected or confirmed COVID-19 (aRR 1.3, 95% CI 1.1- 1.5, p=0.013) Breakthrough infection occurred in 23/4111(0.6%) of fully vaccinated participants; all had anti-S antibodies.\n\nConclusionThe increase in seroprevalence reflects the magnitude of the third wave of the pandemic in Ireland. Genomic sequencing is needed to apportion risk to the workplace versus the household/community. Concerted efforts are needed to mitigate risk factors due to ethnicity and lower level of education, even at this stage of the pandemic. The undiagnosed and breakthrough infections call for ongoing infection prevention and control measures and testing of HCW in the setting of close contact. Vaccinated HCW with confirmed infection should be actively assessed, including SARS-CoV-2 whole genome sequencing (WGS), serology testing and assessment of host determinants, to advance understanding of the reasons for breakthrough infection.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Michael J Peluso", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Hannah M Sans", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Carrie A Forman", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Alyssa N Nylander", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Hsi-en Ho", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Scott Lu", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Sarah A Goldberg", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Rebecca Hoh", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Viva Tai", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Sadie E Munter", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Ahmed Chenna", - "author_inst": "Monogram Biosciences Inc." - }, - { - "author_name": "Brandon C Yee", - "author_inst": "Monogram Biosciences Inc." - }, - { - "author_name": "John W Winslow", - "author_inst": "Monogram Biosciences Inc." - }, - { - "author_name": "Christos J Petropoulos", - "author_inst": "Monogram Biosciences Inc." + "author_name": "niamh allen", + "author_inst": "St James's Hospital, Dublin, Ireland" }, { - "author_name": "Jeffrey N Martin", - "author_inst": "University of California, San Francisco" + "author_name": "Melissa Brady", + "author_inst": "Health Protection Surveillance Centre, Ireland" }, { - "author_name": "J. Daniel Kelly", - "author_inst": "University of California, San Francisco" + "author_name": "Una Ni Riain", + "author_inst": "Galway University Hospital, Ireland" }, { - "author_name": "Matthew S Durstenfeld", - "author_inst": "University of California, San Francisco" + "author_name": "Niall Conlon", + "author_inst": "St. James's Hospital, Dublin, Ireland" }, { - "author_name": "Priscilla Y Hsue", - "author_inst": "University of California, San Francisco" + "author_name": "LIsa Domegan", + "author_inst": "Health Protection Surveillance Centre" }, { - "author_name": "Peter W Hunt", - "author_inst": "University of California, San Francisco" + "author_name": "Isidro Carrion Martin", + "author_inst": "University of Murcia School of Medicine" }, { - "author_name": "Meredith Greene", - "author_inst": "University of California, San Francisco" + "author_name": "Cathal Walsh", + "author_inst": "University of Limerick" }, { - "author_name": "Felicia C Chow", - "author_inst": "University of California, San Francisco" + "author_name": "Lorraine Doherty", + "author_inst": "Health Protection Surveillance Centre, Ireland" }, { - "author_name": "Joanna Hellmuth", - "author_inst": "University of California, San Francisco" + "author_name": "Colm Kerr", + "author_inst": "St. James's Hospital" }, { - "author_name": "Timothy J Henrich", - "author_inst": "University of California, San Francisco" + "author_name": "Eibhlin Higgins", + "author_inst": "University Hospital Galway" }, { - "author_name": "David V Glidden", - "author_inst": "University of California, San Francisco" + "author_name": "Colm Bergin", + "author_inst": "St James's Hospital" }, { - "author_name": "Steven G Deeks", - "author_inst": "University of California, San Francisco" + "author_name": "Catherine Fleming", + "author_inst": "University Hospital Galway" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -545795,391 +545422,47 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.11.01.21265527", - "rel_title": "Effectiveness, Explainability and Reliability of Machine Meta-Learning Methods for Predicting Mortality in Patients with COVID-19: Results of the Brazilian COVID-19 Registry", + "rel_doi": "10.1101/2021.11.02.21265755", + "rel_title": "A combination of variant genotypes at two loci in the APOL1 gene is associated with adverse outcomes in SARS-CoV-2: a UK Biobank study.", "rel_date": "2021-11-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.01.21265527", - "rel_abs": "ObjectiveTo provide a thorough comparative study among state-of-the-art machine learning methods and statistical methods for determining in-hospital mortality in COVID-19 patients using data upon hospital admission; to study the reliability of the predictions of the most effective methods by correlating the probability of the outcome and the accuracy of the methods; to investigate how explainable are the predictions produced by the most effective methods.\n\nMaterials and MethodsDe-identified data were obtained from COVID-19 positive patients in 36 participating hospitals, from March 1 to September 30, 2020. Demographic, comorbidity, clinical presentation and laboratory data were used as training data to develop COVID-19 mortality prediction models. Multiple machine learning and traditional statistics models were trained on this prediction task using a folded cross-validation procedure, from which we assessed performance and interpretability metrics.\n\nResultsThe Stacking of machine learning models improved over the previous state-of-the-art results by more than 26% in predicting the class of interest (death), achieving 87.1% of AUROC and macro F1 of 73.9%. We also show that some machine learning models can be very interpretable and reliable, yielding more accurate predictions while providing a good explanation for the why.\n\nConclusionThe best results were obtained using the meta-learning ensemble model - Stacking. State-of the art explainability techniques such as SHAP-values can be used to draw useful insights into the patterns learned by machine-learning algorithms. Machine-learning models can be more explainable than traditional statistics models while also yielding highly reliable predictions.", - "rel_num_authors": 93, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.11.02.21265755", + "rel_abs": "Risk of hospitalisation or death from COVID-19 in the UK is disproportionately high in people of African ancestry. Two APOL1 haplotypes (G1 and G2) found at high frequency only in populations of African descent are associated with increased risk of non-communicable and infectious diseases. Here, we test the hypothesis that adverse COVID-19 outcomes are also associated with these APOL1 high-risk variants.\n\nWithin 9,433 individuals with African ancestry in the UK Biobank, there were 172 hospitalisations and 47 deaths attributed to COVID-19 as of December 2021. We examined APOL1 genotypes for association with hospitalisation and death while controlling for risk factors previously associated with poor COVID-19 outcomes.\n\nWe identified an association between carriage of two APOL1 high-risk variants and death from COVID-19 (OR=2.7, 95% CI: 1. 2-6.4). Stratified by genotype, those with G1/G2 had a higher odds of COVID-19 hospitalisation (OR=2.1, 95% CI: 1.1-3.8) and death (OR=5.9, 95% CI: 2.2-15.3) than G0/G0. There was no significant association detected in carriers of G1/G1 and G2/G2.\n\nThese data suggest that the APOL1 G1/G2 genotype contributes to the increased rates of hospitalisation and mortality from COVID-19 in people of African ancestry, and could help to identify those at higher risk of severe COVID-19. This is especially relevant to geographical regions where APOL1 G1 and G2 high-risk variants are common, such as West and Central Africa and their diaspora.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Bruno Barbosa Miranda de Paiva Sr.", - "author_inst": "Computer Science Department, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Polianna Delfino Pereira Sr.", - "author_inst": "Internal Medicine Department, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil; Institute for Health Technology Assessment (IATS/CNPq)" - }, - { - "author_name": "Claudio Moises Valiense de Andrade", - "author_inst": "Computer Science Department, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Virginia Mara Reis Gomes Sr.", - "author_inst": "Centro Universitario de Belo Horizonte (UniBH), Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Maria Clara Pontello Barbosa Lima Sr.", - "author_inst": "Universidade Federal de Ouro Preto, Ouro Preto, Minas Gerais, Brazil" - }, - { - "author_name": "Maira Viana Rego Souza Silva Sr.", - "author_inst": "Medical School and University Hospital, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Marcelo Carneiro Sr.", - "author_inst": "Hospital Santa Cruz, Santa Cruz do Sul, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Karina Paula Medeiros Prado Martins Sr.", - "author_inst": "Medical School and University Hospital, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Thais Lorenna Souza Sales Sr.", - "author_inst": "Universidade Federal de Sao Joao del Rey. R, Divinopolis, Minas Gerais, Brazil" - }, - { - "author_name": "Rafael Lima Rodrigues de Carvalho Sr.", - "author_inst": "Institute for Health Technology Assessment (IATS/CNPq), Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Magda C. Pires", - "author_inst": "Department of Statistics, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Lucas Emanuel F Ramos", - "author_inst": "Department of Statistics, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Rafael T Silva Sr.", - "author_inst": "Department of Statistics, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Adriana Falangola Benjamin Bezerra", - "author_inst": "Hospital das Clinicas da Universidade Federal de Pernambuco, Recife, Pernambuco, Brazil" - }, - { - "author_name": "Alexandre Vargas Schwarzbold", - "author_inst": "Hospital Universitario de Santa Maria, Santa Maria, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Aline Gabrielle Sousa Nunes", - "author_inst": "Hospital UNIMED BH, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Amanda de Oliveira Maurilio", - "author_inst": "Hospital Sao Joao de Deus, Sao Joao de Deus, Minas Gerais, Brazil" - }, - { - "author_name": "Ana Luiza Bahia Alves Scotton", - "author_inst": "Hospital Regional Antonio Dias, Patos de Minas, Minas Gerais, Brazil" - }, - { - "author_name": "Andre Soares de Moura Costa", - "author_inst": "Hospitais da Rede Mater Dei, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Andriele Abreu Castro", - "author_inst": "Hospital Moinhos de Vento, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Barbara Lopes Farace", - "author_inst": "Risoleta Tolentino Neves, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Christiane Correa Rodrigues Cimini", - "author_inst": "Mucuri Medical School, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Teofilo Otoni, Minas Gerais, Brazil; Hospital Santa Rosalia, Teofilo Otoni, Min" - }, - { - "author_name": "Cintia Alcantara De Carvalho", - "author_inst": "Hospital Joao XXIII, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Daniel Vitorio Silveira", - "author_inst": "Hospital UNIMED BH, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Daniela Ponce", - "author_inst": "Faculdade de Medicina de Botucatu - Universidade Estadual Paulista Julio de Mesquita Filho, Botucatu, Sao Paulo, Brazil" - }, - { - "author_name": "Elayne Crestani Pereira", - "author_inst": "Universidade do Sul de Santa Catarina (UNISUL), Florianopolis, Santa Catarina, Brazil; Hospital SOS Cardio, Florianopolis, Santa Catarina, Brazil" - }, - { - "author_name": "Euler Roberto Fernandes Manenti", - "author_inst": "Hospital Mae de Deus, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Evelin Paola de Almeida Cenci", - "author_inst": "Hospital Universitario Canoas, Canoas, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Fernanda Barbosa Lucas", - "author_inst": "Hospital Santo Antonio, Curvelo, Minas Gerais, Brazil" - }, - { - "author_name": "Fernanda D'Athayde Rodrigues", - "author_inst": "Hospital de Clinicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Fernando Anschau", - "author_inst": "Hospital Nossa Senhora da Conceicao, Porto Alegre, Rio Grande do Sul, Brazil; Hospital Cristo Redentor, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Fernando Antonio Botoni", - "author_inst": "Medical School and University Hospital, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Fernando Graca Aranha", - "author_inst": "Hospital SOS Cardio, Florianopolis, Santa Catarina, Brazil" - }, - { - "author_name": "Frederico Bartolazzi", - "author_inst": "Hospital Santo Antonio, Curvelo, Minas Gerais, Brazil" - }, - { - "author_name": "Gisele Alsina Nader Bastos", - "author_inst": "Hospital Moinhos de Vento, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Giovanna Grunewald Vietta", - "author_inst": "Universidade do Sul de Santa Catarina (UNISUL), Florianopolis, Santa Catarina, Brazil; Hospital SOS Cardio, Florianopolis, Santa Catarina, Brazil" - }, - { - "author_name": "Guilherme Fagundes Nascimento", - "author_inst": "Hospital UNIMED BH, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Helena Carolina Noal", - "author_inst": "Hospital Universitario de Santa Maria, Santa Maria, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Helena Duani", - "author_inst": "Medical School and University Hospital, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Heloisa Reniers Vianna", - "author_inst": "Universitario Ciencias Medicas, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Henrique Cerqueira Guimaraes", - "author_inst": "Risoleta Tolentino Neves, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Isabela Moraes Gomes", - "author_inst": "Medical School and University Hospital, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Jamille Hemetrio Salles Martins Costa", - "author_inst": "Hospital Marcio Cunha, Ipatinga, Minas Gerais, Brazil" - }, - { - "author_name": "Jessica Rayane Correa Silva da Fonseca", - "author_inst": "Hospital Semper, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Julia Di Sabatino Santos Guimaraes", - "author_inst": "Pontifica Universidade Catolica de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Julia Drumond Parreiras de Morais", - "author_inst": "Universitario Ciencias Medicas, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Juliana Machado Rugolo", - "author_inst": "Faculdade de Medicina de Botucatu - Universidade Estadual Paulista Julio de Mesquita Filho, Botucatu, Sao Paulo, Brazil" - }, - { - "author_name": "Joanna D'arc Lyra Batista", - "author_inst": "Universidade Federal da Fronteira Sul, Chapeco, Santa Catarina, Brazil" - }, - { - "author_name": "Joice Coutinho de Alvarenga", - "author_inst": "Hospital Joao XXIII, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Jose Miguel Chatkin", - "author_inst": "Schoolof Medicine, Pontificia Universidade Catolica do Rio Grande do Sul, Porto Alegre, Rio Grande do Sul, Brazil; Hospital Sao Lucas PUCRS, Porto Alegre, Brazi" - }, - { - "author_name": "Karen Brasil Ruschel", - "author_inst": "Institute for Health Technology Assessment (IATS/CNPq), Porto Alegre, Rio Grande do Sul, Brazil; Hospital Mae de Deus, Porto Alegre, Rio Grande do Sul, Brazil; " - }, - { - "author_name": "Leila Beltrami Moreira", - "author_inst": "Hospital de Clinicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Leonardo Seixas de Oliveira", - "author_inst": "Hospital Bruno Born, Lajeado, Rio Grande do Sul,Brazil" - }, - { - "author_name": "Liege Barella Zandona", - "author_inst": "Hospital Bruno Born, Lajeado, Rio Grande do Sul,Brazil" - }, - { - "author_name": "Lilian Santos Pinheiro", - "author_inst": "Mucuri Medical School, Universidade Federal dos Vales do Jequitinhonha e Mucuri, Teofilo Otoni, Minas Gerais, Brazil; Hospital Santa Rosalia, Teofilo Otoni, Min" - }, - { - "author_name": "Luanna da Silva Monteiro", - "author_inst": "Hospital Metropolitano Odilon Behrens, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Lucas de Deus Sousa", - "author_inst": "Hospital Regional Antonio Dias, Patos de Minas, Minas Gerais, Brazil" - }, - { - "author_name": "Luciane Kopittke", - "author_inst": "Hospital Nossa Senhora da Conceicao, Porto Alegre, Rio Grande do Sul, Brazil; Hospital Cristo Redentor, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Luciano de Souza Viana", - "author_inst": "Hospital Marcio Cunha, Ipatinga, Minas Gerais, Brazil" - }, - { - "author_name": "Luis Cesar de Castro", - "author_inst": "Hospital Tacchini, Bento Goncalves, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Luisa Argolo Assis", - "author_inst": "Pontifica Universidade Catolica de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Luisa Elem Almeida Santos", - "author_inst": "Centro Universitario de Patos de Minas, Patos de Minas, Minas Gerais, Brazil" - }, - { - "author_name": "Maderson Alvares de Souza Cabral", - "author_inst": "Hospital Moinhos de Vento, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Magda Cesar Raposo", - "author_inst": "Universidade Federal de Sao Joao del Rey. R, Divinopolis, Minas Gerais, Brazil" - }, - { - "author_name": "Maiara Anschau Floriani", - "author_inst": "Moinhos Research Institute, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Maria Angelica Pires Ferreira", - "author_inst": "Hospital de Clinicas de Porto Alegre, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Maria Aparecida Camargos Bicalho", - "author_inst": "Fundacao Hospitalar do Estado de Minas Gerais (FHEMIG), Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Mariana Frizzo de Godoy", - "author_inst": "Hospital Sao Lucas PUCRS, Porto Alegre, Brazil. Rua Joao Cateano, 79/503. Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Matheus Carvalho Alves Nogueira", - "author_inst": "Hospitais da Rede Mater Dei, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Meire Pereira de Figueiredo", - "author_inst": "Hospital Santo Antonio, Curvelo, Minas Gerais, Brazil" - }, - { - "author_name": "Milton Henriques Guimaraes Junior", - "author_inst": "Hospital Marcio Cunha, Ipatinga, Minas Gerais, Brazil" - }, - { - "author_name": "Monica Aparecida de Paula De Sordi", - "author_inst": "Faculdade de Medicina de Botucatu - Universidade Estadual Paulista Julio de Mesquita Filho, Botucatu, Sao Paulo, Brazil" - }, - { - "author_name": "Natalia da Cunha Severino Sampaio", - "author_inst": "Hospital Eduardo de Menezes, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Neimy Ramos de Oliveira", - "author_inst": "Hospital Eduardo de Menezes, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Pedro Ledic Assaf", - "author_inst": "Hospital Metropolitano Doutor Celio de Castro, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Raquel Lutkmeier", - "author_inst": "Hospital Nossa Senhora da Conceicao, Porto Alegre, Rio Grande do Sul, Brazil; Hospital Cristo Redentor, Porto Alegre, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Reginaldo Aparecido Valacio", - "author_inst": "Hospital Metropolitano Odilon Behrens, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Renan Goulart Finger", - "author_inst": "Hospital Regional do Oeste, Chapeco, Santa Catarina,Brazil" - }, - { - "author_name": "Roberta Senger", - "author_inst": "Hospital Universitario de Santa Maria, Santa Maria, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Rochele Mosmann Menezes", - "author_inst": "Hospital Santa Cruz, Santa Cruz do Sul, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Rufino de Freitas Silva", - "author_inst": "Hospital Sao Joao de Deus, Sao Joao de Deus, Minas Gerais, Brazil" - }, - { - "author_name": "Saionara Cristina Francisco", - "author_inst": "Hospital Metropolitano Doutor Celio de Castro, Belo Horizonte, Minas Gerais, Brazil" - }, - { - "author_name": "Silvana Mangeon Mereilles Guimaraes", - "author_inst": "Hospital Marcio Cunha, Ipatinga, Minas Gerais, Brazil" - }, - { - "author_name": "Silvia Ferreira Araujo", - "author_inst": "Hospital Marcio Cunha, Ipatinga, Minas Gerais, Brazil" - }, - { - "author_name": "Talita Fischer Oliveira", - "author_inst": "Hospital Santa Cruz, Santa Cruz do Sul, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Tatiana Kurtz", - "author_inst": "Hospital Santa Cruz, Santa Cruz do Sul, Rio Grande do Sul, Brazil" - }, - { - "author_name": "Tatiani Oliveira Fereguetti", - "author_inst": "Hospital Eduardo de Menezes, Belo Horizonte, Minas Gerais, Brazil" + "author_name": "Walt E Adamson", + "author_inst": "University of Glasgow" }, { - "author_name": "Thainara Conceicao de Oliveira", - "author_inst": "Hospital Universitario Canoas, Canoas, Rio Grande do Sul, Brazil" + "author_name": "Harry Noyes", + "author_inst": "University of Liverpool" }, { - "author_name": "Thulio Henrique Oliveira Diniz", - "author_inst": "Hospital Sao Joao de Deus, Sao Joao de Deus, Minas Gerais, Brazil" + "author_name": "Anneli Cooper", + "author_inst": "University of Glasgow" }, { - "author_name": "Yara Neves Marques Barbosa Ribeiro", - "author_inst": "Hospital Metropolitano Doutor Celio de Castro, Belo Horizonte, Minas Gerais, Brazil" + "author_name": "Georgia Beckett-Hill", + "author_inst": "University of Glasgow" }, { - "author_name": "Yuri Carlotto Ramires", - "author_inst": "Hospital Bruno Born, Lajeado, Rio Grande do Sul,Brazil" + "author_name": "John Ogunsola", + "author_inst": "University of Glasgow" }, { - "author_name": "Marcos Andre Goncalves", - "author_inst": "Computer Science Department, Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" + "author_name": "Rulan Parekh", + "author_inst": "University of Toronto" }, { - "author_name": "Milena Soriano Marcolino", - "author_inst": "Institute for Health Technology Assessment (IATS/CNPq), Porto Alegre, Rio Grande do Sul, Brazil; Medical School and University Hospital, Universidade Federal de" + "author_name": "Annette MacLeod", + "author_inst": "University of Glasgow" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.11.01.21265384", @@ -547989,27 +547272,107 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.10.29.466519", - "rel_title": "A biosafety level 2 surrogate for studying SARS-CoV-2 survival in food processing environmental biofilms", + "rel_doi": "10.1101/2021.10.29.466418", + "rel_title": "SARS-CoV-2 mechanistic correlates of protection: insight from modelling response to vaccines", "rel_date": "2021-11-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.29.466519", - "rel_abs": "Meat processing plants have been at the center of the SARS-CoV-2 pandemic. There are several factors that contribute to the persistence of SARS-CoV-2 in meat processing plants and one of the factors is the formation of a multi-species biofilm with virus. Biofilm can act as a reservoir in protecting, harboring, and dispersing SARS-CoV-2 from biofilm to the meat processing facility environment. We used Murine Hepatitis Virus (MHV) as a surrogate for SARS-CoV-2 virus and meat processing facility drain samples to develop mixed-species biofilms on commonly found materials in processing facilities (Stainless-Steel (SS), PVC and tiles). The results showed that MHV was able to integrate into the environmental biofilm and survived for a period of 5 days at 7{degrees}C. There was no significate difference between the viral-environmental biofilm biovolumes developed on different materials SS, PVC, and tiles. There was a 2-fold increase in the virus-environmental biofilm biovolume when compared to environmental biofilm by itself. These results indicate a complex virus-environmental biofilm interaction which is providing enhanced protection for the survival of viral particles with the environmental biofilm community.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.29.466418", + "rel_abs": "The definition of correlates of protection is critical for the development of next generation SARS-CoV-2 vaccine platforms. Here, we propose a new framework for identifying mechanistic correlates of protection based on mathematical modelling of viral dynamics and data mining of immunological markers. The application to three different studies in non-human primates evaluating SARS-CoV-2 vaccines based on CD40-targeting, two-component spike nanoparticle and mRNA 1273 identifies and quantifies two main mechanisms that are a decrease of rate of cell infection and an increase in clearance of infected cells. Inhibition of RBD binding to ACE2 appears to be a robust mechanistic correlate of protection across the three vaccine platforms although not capturing the whole biological vaccine effect. The model shows that RBD/ACE2 binding inhibition represents a strong mechanism of protection which required significant reduction in blocking potency to effectively compromise the control of viral replication.\n\nOne Sentence SummaryA framework for modelling the immune control of viral dynamics is applied to quantify the effect of several SARS-CoV-2 vaccine platforms and to define mechanistic correlates of protection.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Austin Blake Featherstone", - "author_inst": "Texas A&M" + "author_name": "Marie Alexandre", + "author_inst": "Univ. Bordeaux, Department of Public Health, Inserm Bordeaux Population Health Research Centre, Inria SISTM, UMR 1219" }, { - "author_name": "Sapna Chitlapilly Dass", - "author_inst": "Texas A&M" + "author_name": "Romain Marlin", + "author_inst": "Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA-HB/IDMIT), Universite Paris-Saclay, Inserm, CEA" + }, + { + "author_name": "Melanie Prague", + "author_inst": "Univ. Bordeaux, Department of Public Health, Inserm Bordeaux Population Health Research Centre, Inria SISTM, UMR 1219" + }, + { + "author_name": "Coleon Severin", + "author_inst": "Vaccine Research Institute, Inserm U955, Equipe 16" + }, + { + "author_name": "Nidhal Kahlaoui", + "author_inst": "Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA-HB/IDMIT), Universite Paris-Saclay, Inserm, CEA" + }, + { + "author_name": "Sylvain Cardinaud", + "author_inst": "Vaccine Research Institute, Inserm U955, Equipe 16" + }, + { + "author_name": "Thibaut Naninck", + "author_inst": "Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA-HB/IDMIT), Universite Paris-Saclay, Inserm, CEA" + }, + { + "author_name": "Benoit Delache", + "author_inst": "Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA-HB/IDMIT), Universite Paris-Saclay, Inserm, CEA" + }, + { + "author_name": "Mathieu Surenaud", + "author_inst": "Vaccine Research Institute, Inserm U955, Equipe 16" + }, + { + "author_name": "Mathilde Galhaut", + "author_inst": "Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA-HB/IDMIT), Universite Paris-Saclay, Inserm, CEA" + }, + { + "author_name": "Nathalie Dereuddre-Bosquet", + "author_inst": "Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA-HB/IDMIT), Universite Paris-Saclay, Inserm, CEA" + }, + { + "author_name": "Mariangela Cavarelli", + "author_inst": "Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA-HB/IDMIT), Universite Paris-Saclay, Inserm, CEA" + }, + { + "author_name": "Pauline Maisonnasse", + "author_inst": "Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA-HB/IDMIT), Universite Paris-Saclay, Inserm, CEA" + }, + { + "author_name": "Mireille Centlivre", + "author_inst": "Vaccine Research Institute, Inserm U955, Equipe 16" + }, + { + "author_name": "Christine Lacabaratz", + "author_inst": "Vaccine Research Institute, Inserm U955, Equipe 16" + }, + { + "author_name": "Aurelie Wiedemann", + "author_inst": "Vaccine research Institute, Inserm U955, Equipe 16" + }, + { + "author_name": "Sandra Zurawski", + "author_inst": "Baylor Scott and White Research Institute and INSERM U955" + }, + { + "author_name": "Gerard Zurawski", + "author_inst": "Baylor Scott and White Research Institute and INSERM U955" + }, + { + "author_name": "Olivier Schwartz", + "author_inst": "Virus & Immunity Unit, Department of Virology, Institut Pasteur; CNRS UMR 3569; Vaccine Research Institute" + }, + { + "author_name": "Rogier W Sanders", + "author_inst": "Department of Medical Microbiology, Amsterdam UMC, University of Amsterdam, Amsterdam Infection & Immunity Institute" + }, + { + "author_name": "Roger Le Grand", + "author_inst": "Center for Immunology of Viral, Auto-immune, Hematological and Bacterial diseases (IMVA-HB/IDMIT), Universite Paris-Saclay, Inserm, CEA" + }, + { + "author_name": "Rodolphe Thiebaut", + "author_inst": "Univ. Bordeaux, Department of Public Health, Inserm Bordeaux Population Health Research Centre, Inria SISTM, UMR 1219; Vaccine Research Institute; CHU Bordeaux," } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.10.29.21265678", @@ -549551,67 +548914,195 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.29.21265248", - "rel_title": "Safety and immunogenicity of a high-dose quadrivalent influenza vaccine administered concomitantly with a third dose of the mRNA-1273 SARS-CoV-2 vaccine in adults >= 65 years of age: a Phase II, open-label study", + "rel_doi": "10.1101/2021.10.28.21265616", + "rel_title": "Risk factors for severe PCR-positive SARS-CoV-2 infection in hospitalized children: a multicenter cohort study", "rel_date": "2021-10-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.29.21265248", - "rel_abs": "BackgroundConcomitant seasonal influenza vaccination with a COVID-19 vaccine booster could help to minimise potential disruption to the seasonal influenza vaccination campaign and maximise protection against both diseases among individuals at risk of severe disease and hospitalisation. This study assesses the safety and immunogenicity of concomitant administration of high-dose quadrivalent influenza vaccine (QIV-HD) and a mRNA-1273 vaccine booster dose in older adults.\n\nMethodsThis is an ongoing Phase II, multi-centre, open-label study (NCT04969276). We describe interim results up to 21 days after vaccination (July 2021-August 2021). Adults aged [≥] 65 years living in the community, who were to have received a second mRNA-1273 dose at least five months previously, were randomised (1:1:1) to concomitant QIV-HD and mRNA-1273 vaccination (Coad), QIV-HD alone, or mRNA-1273 vaccine alone. Unsolicited adverse events (AEs) occurring immediately, solicited local and systemic reactions up to day (D)8, and unsolicited AEs, serious AEs (SAEs), AEs of special interest (AESIs) and medically attended AEs (MAAEs) up to D22 were reported. Haemagglutination inhibition (HAI) antibody responses to influenza A/H1N1, A/H3N2, B/Yamagata and B/Victoria strains and SARS CoV-2 binding antibody responses (SARS-CoV-2 Pre-Spike IgG ELISA) were assessed at D1 and D22.\n\nFindingsOf 306 participants randomised, 296 were included for analysis (Coad, n=100; QIV-HD, n=92; mRNA-1273, n=104). Reactogenicity profiles were similar between the Coad and mRNA-1273 groups, with lower reactogenicity rates in the QIV-HD group (frequency [95% CIs] of solicited injection site reactions: 86{middle dot}0% [77{middle dot}6-92{middle dot}1], 91{middle dot}3% [84{middle dot}2-96{middle dot}0] and 61{middle dot}8% [50{middle dot}9-71{middle dot}9]; solicited systemic reactions: 80{middle dot}0% [70{middle dot}8-87{middle dot}3], 83{middle dot}7% [75{middle dot}1-90{middle dot}2] and 49{middle dot}4% [38{middle dot}7-60{middle dot}2], respectively). Up to D22, unsolicited AEs were reported for 17{middle dot}0% and 14{middle dot}4% participants in the Coad and mRNA-1273 groups, respectively, with a lower rate (10{middle dot}9%) in the QIV-HD group. Seven MAAEs were reported (Coad, n=3; QIV-HD, n=1; mRNA-1273, n=3). There were no SAEs, AESIs or deaths. HAI antibody geometric mean titres (GMTs) increased from D1 to D22 to similar levels for each influenza strain in the Coad and QIV-HD groups (GMTs [95% confidence interval], range across strains: Coad, 286 [233-352] to 429 [350-525]; QIV-HD, 315 [257-386] to 471 [378-588]). SARS-CoV-2 binding antibody geometric mean concentrations (GMCs) also increased to similar levels in the Coad and mRNA-1273 groups (D22 GMCs [95% confidence interval]: 7634 [6445-9042] and 7904 [6883- 9077], respectively).\n\nInterpretationNo safety concerns or immune interference were observed for concomitant administration of QIV-HD with mRNA-1273 booster in adults aged [≥] 65 years, supporting co-administration recommendations.\n\nFundingSanofi Pasteur", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.28.21265616", + "rel_abs": "ImportanceChildren are less likely than adults to have severe outcomes from SARS-CoV-2 infection and the corresponding risk factors are not well established.\n\nObjectiveTo identify risk factors for severe disease in symptomatic children hospitalized for PCR-positive SARS-CoV-2 infection.\n\nDesignCohort study, enrollment from February 1, 2020 until May 31, 2021\n\nSetting15 childrens hospitals in Canada, Iran, and Costa Rica\n\nParticipantsPatients <18 years of age hospitalized with symptomatic SARS-CoV-2 infection, including PCR-positive multisystem inflammatory syndrome in children (MIS-C)\n\nExposuresVariables assessed for their association with disease severity included patient demographics, presence of comorbidities, clinical manifestations, laboratory parameters and chest imaging findings.\n\nMain Outcomes and MeasuresThe primary outcome was severe disease defined as a WHO COVID-19 clinical progression scale of [≥]6, i.e., requirement of non-invasive ventilation, high flow nasal cannula, mechanical ventilation, vasopressors, or death. Multivariable logistic regression was used to evaluate factors associated with severe disease.\n\nResultsWe identified 403 hospitalizations. Median age was 3.78 years (IQR 0.53-10.77). At least one comorbidity was present in 46.4% (187/403) and multiple comorbidities in 18.6% (75/403). Severe disease occurred in 33.8% (102/403). In multivariable analyses, presence of multiple comorbidities (adjusted odds ratio 2.24, 95% confidence interval 1.04-4.81), obesity (2.87, 1.19-6.93), neurological disorder (3.22, 1.37-7.56), anemia, and/or hemoglobinopathy (5.88, 1.30-26.46), shortness of breath (4.37, 2.08-9.16), bacterial and/or viral coinfections (2.26, 1.08-4.73), chest imaging compatible with COVID-19 (2.99, 1.51-5.92), neutrophilia (2.60, 1.35-5.02), and MIS-C diagnosis (3.86, 1.56-9.51) were independent risk factors for severity. Comorbidities, especially obesity (40.9% vs 3.9%, p<0.001), were more frequently present in adolescents [≥]12 years of age. Neurological disorder (3.16, 1.19-8.43) in children <12 years of age and obesity (3.21, 1.15-8.93) in adolescents were the specific comorbidities associated with disease severity in age-stratified adjusted analyses. Sensitivity analyses excluding the 81 cases with MIS-C did not substantially change the identified risk factors.\n\nConclusions and RelevancePediatric risk factors for severe SARS-CoV-2 infection vary according to age and can potentially guide vaccination programs and treatment approaches in children.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSWhat are the risk factors for severe disease in children hospitalized for PCR-positive SARS-CoV-2 infection?\n\nFindingsIn this multinational cohort study of 403 children, multiple comorbidities, obesity, neurological disorder, anemia, and/or hemoglobinopathy, shortness of breath, bacterial and/or viral coinfections, chest imaging compatible with COVID-19, neutrophilia, and MIS-C diagnosis were independent risk factors for severity. The risk profile and presence of comorbidities differed between pediatric age groups, but age itself was not associated with severe outcomes.\n\nMeaningThese results can inform targeted treatment approaches and vaccine programs that focus on patient groups with the highest risk of severe outcomes.", + "rel_num_authors": 44, "rel_authors": [ { - "author_name": "Ruvim Izikson", - "author_inst": "Sanofi Pasteur, Swiftwater, Pennsylvania, USA" + "author_name": "Tilmann Schober", + "author_inst": "Department of Pediatrics, McGill University, Montreal, Quebec, Canada" }, { - "author_name": "Daniel Brune", - "author_inst": "Accelerated Enrollment Solutions, Peoria, Illinois, USA" + "author_name": "Chelsea Caya", + "author_inst": "Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada" }, { - "author_name": "Jean-S\u00e9bastien Bolduc", - "author_inst": "Sanofi Pasteur, Marcy l Etoile, France" + "author_name": "Michelle Barton", + "author_inst": "Department of Pediatrics, Western University, London, Ontario, Canada" }, { - "author_name": "Pierre Bourron", - "author_inst": "Sanofi Pasteur, Lyon, France" + "author_name": "Ann Bayliss", + "author_inst": "Department of Pediatrics, Trillium Health Partners, Mississauga, Ontario, Canada" }, { - "author_name": "Marion Fournier", - "author_inst": "Sanofi Pasteur, Lyon, France" + "author_name": "Ari Bitnun", + "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada" }, { - "author_name": "Tamala Mallett Moore", - "author_inst": "Sanofi Pasteur, Swiftwater, Pennsylvania, USA" + "author_name": "Jennifer Bowes", + "author_inst": "Department of Pediatrics, University of Ottawa, Ottawa, Ontario, Canada" }, { - "author_name": "Aseem Pandey", - "author_inst": "Sanofi Pasteur, Swiftwater, Pennsylvania, USA" + "author_name": "Helena Brenes-Chacon", + "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" }, { - "author_name": "Lucia Perez", - "author_inst": "Sanofi Pasteur, Swiftwater, Pennsylvania, USA" + "author_name": "Jared Bullard", + "author_inst": "Department of Pediatrics, University of Manitoba, Winnipeg, Manitoba, Canada" }, { - "author_name": "Nessryne Sater", - "author_inst": "Sanofi Pasteur, Marcy l Etoile, France" + "author_name": "Suzette Cooke", + "author_inst": "Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada" }, { - "author_name": "Anju Shrestha", - "author_inst": "Sanofi Pasteur, Swiftwater, Pennsylvania, USA" + "author_name": "Tammie Dewan", + "author_inst": "Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada" }, { - "author_name": "Sophie Wague", - "author_inst": "Sanofi Pasteur, Lyon, France" + "author_name": "Rachel Dwilow", + "author_inst": "Department of Pediatrics, University of Manitoba, Winnipeg, Manitoba, Canada" }, { - "author_name": "Sandrine I Samson", - "author_inst": "Sanofi Pasteur, Lyon, France" + "author_name": "Tala El Tal", + "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Cheryl Foo", + "author_inst": "Department of Pediatrics, Memorial University, St John's, Newfoundland and Labrador, Canada" + }, + { + "author_name": "Peter Gill", + "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Behzad Haghighi Aski", + "author_inst": "Department of Pediatrics, Iran University of Medical Sciences, Tehran, Iran" + }, + { + "author_name": "Fatima Kakkar", + "author_inst": "Department of Pediatrics, Universite de Montreal, Montreal, Quebec, Canada" + }, + { + "author_name": "Janell Lautermilch", + "author_inst": "Department of Pediatrics, University of Saskatchewan, Saskatoon, Saskatchewan, Canada" + }, + { + "author_name": "Ronald M. Laxer", + "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Marie-Astrid Lefebvre", + "author_inst": "Department of Pediatrics, McGill University, Montreal, Quebec, Canada" + }, + { + "author_name": "Kirk Leifso", + "author_inst": "Department of Pediatrics, Queen's University, Kingston, Ontario, Canada" + }, + { + "author_name": "Nicole Le Saux", + "author_inst": "Department of Pediatrics, University of Ottawa, Ottawa, Ontario, Canada" + }, + { + "author_name": "Alison Lopez", + "author_inst": "British Columbia Children's Hospital, Vancouver, British Columbia, Canada" + }, + { + "author_name": "Ali Manafi", + "author_inst": "Department of Pediatrics, Iran University of Medical Sciences, Tehran, Iran" + }, + { + "author_name": "Shaun K. Morris", + "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Alireza Nateghian", + "author_inst": "Department of Pediatrics, Iran University of Medical Sciences, Tehran, Iran" + }, + { + "author_name": "Luc Panetta", + "author_inst": "Department of Pediatrics, Universite de Montreal, Montreal, Quebec, Canada" + }, + { + "author_name": "Dara Petel", + "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Dominique Piche", + "author_inst": "Department of Pediatrics, Dalhousie University, Halifax, Nova Scotia, Canada" + }, + { + "author_name": "Rupeena Purewal", + "author_inst": "Department of Pediatrics, University of Saskatchewan, Saskatoon, Saskatchewan, Canada" + }, + { + "author_name": "Lea Restivo", + "author_inst": "Department of Pediatrics, University of Calgary, Calgary, Alberta, Canada" + }, + { + "author_name": "Ashley Roberts", + "author_inst": "British Columbia Children's Hospital, Vancouver, British Columbia, Canada; Department of Pediatrics, University of British Columbia, Vancouver, British Columbia" + }, + { + "author_name": "Manish Sadarangani", + "author_inst": "British Columbia Children's Hospital, Vancouver, British Columbia, Canada; Department of Pediatrics, University of British Columbia, Vancouver, British Columbia" + }, + { + "author_name": "Rosie Scuccimarri", + "author_inst": "Department of Pediatrics, McGill University, Montreal, Quebec, Canada" + }, + { + "author_name": "Alejandra Soriano-Fallas", + "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" + }, + { + "author_name": "Sarah Tehseen", + "author_inst": "Department of Pediatrics, University of Saskatchewan, Saskatoon, Saskatchewan, Canada" + }, + { + "author_name": "Karina A. Top", + "author_inst": "Department of Pediatrics, Dalhousie University, Halifax, Nova Scotia, Canada" + }, + { + "author_name": "Rolando Ulloa-Gutierrez", + "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" + }, + { + "author_name": "Isabelle Viel-Theriaul", + "author_inst": "Department of Pediatrics, CHU de Quebec-Universite Laval, Quebec, Quebec, Canada" + }, + { + "author_name": "Jacqueline K. Wong", + "author_inst": "Department of Pediatrics, McMaster University, Hamilton, Ontario, Canada" + }, + { + "author_name": "Carmen Yea", + "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Ann Yeh", + "author_inst": "Department of Pediatrics, University of Toronto, Toronto, Ontario, Canada" + }, + { + "author_name": "Adriana Yock-Corrales", + "author_inst": "Department of Pediatrics, Hospital Nacional de Ninos \"Dr. Carlos Saenz Herrera\", Caja Costarricense de Seguro Social (CCSS); San Jose, Costa Rica" + }, + { + "author_name": "Joan Robinson", + "author_inst": "Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada" + }, + { + "author_name": "Jesse Papenburg", + "author_inst": "Department of Pediatrics, McGill University, Montreal, Quebec, Canada; Research Institute of the McGill University Health Centre, Montreal, Quebec, Canada" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "pediatrics" }, { "rel_doi": "10.1101/2021.10.27.465224", @@ -551341,59 +550832,171 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.23.21265429", - "rel_title": "Use of serology immunoassays for predicting SARS-CoV-2 infection: a serology-based diagnostic algorithm", + "rel_doi": "10.1101/2021.10.21.21265140", + "rel_title": "Seroprevalence, prevalence, and genomic surveillance: monitoring the initial phases of the SARS-CoV-2 pandemic in Betim, Brazil", "rel_date": "2021-10-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.23.21265429", - "rel_abs": "BackgroundDetection of viral RNA by nucleic acid amplification testing (NAAT) remains the gold standard for diagnosis of SARS-CoV-2 infection but is limited by high cost and other factors. Whether serology-based assays can be effectively incorporated into a diagnostic algorithm remains to be determined. Herein we describe the development of a serology-based testing algorithm for SARS-CoV-2 infection.\n\nPatients and MethodsBetween July 2020 and February 2021, we included symptomatic unvaccinated patients evaluated in the Emergency Department of our institution for suspected SARS-CoV-2. All patients had testing by real-time Reverse Transcription Polymerase Chain Reaction. The performance characteristics of five commercial enzymatic serology assays testing for different antibody isotypes were evaluated in a derivation cohort and the assay with the best performance was further tested on a validation cohort. Optimal cut-off points were determined using receiver operating characteristic (ROC) curves and further tested using logistic regression.\n\nResultsThe derivation and validations cohorts included 72 and 319 patients, respectively. Based on its initial performance, the Elecsys Anti-SARS-CoV-2 assay (Roche Diagnostics) was further tested in the validation cohort. Using ROC curve analysis, we estimated the diagnostic performance for different cut-off points assuming a prevalence of positive tests of 5%. At any given cut-off point the NPV was over 97%.\n\nDiscussionThis study suggests that an initial diagnostic strategy using the Elecsys Anti-SARS-CoV-2 serology test in symptomatic unvaccinated patients could help to rule out an acute SARS-CoV2 infection and potentially lead to appropriately tailored infection control measures or rational guidance for further testing with a potential cost reduction and increased availability.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.21.21265140", + "rel_abs": "The Covid-19 pandemic has created an unprecedented need for epidemiological monitoring using diverse strategies. We conducted a project combining prevalence, seroprevalence, and genomic surveillance approaches to describe the initial pandemic stages in Betim City, Brazil. We collected 3239 subjects in a population-based age-, sex- and neighbourhood-stratified, household, prospective; cross-sectional study divided into three surveys 21 days apart sampling the same geographical area. In the first survey, overall prevalence (participants positive in serological or molecular tests) reached 0.46% (90% CI 0.12% - 0.80%), followed by 2.69% (90% CI 1.88% - 3.49%) in the second survey and 6.67% (90% CI 5.42% - 7.92%) in the third. The underreporting reached 11, 19.6, and 20.4 times in each survey, respectively. We observed increased odds to test positive in females compared to males (OR 1.88 95% CI 1.25 - 2.82), while the single best predictor for positivity was ageusia/ anosmia (OR 8.12, 95% CI 4.72 - 13.98). Thirty-five SARS-CoV-2 genomes were sequenced, of which 18 were classified as lineage B.1.1.28, while 17 were B.1.1.33. Multiple independent viral introductions were observed. Integration of multiple epidemiological strategies was able to describe Covid-19 dispersion in the city adequately. Presented results have helped local government authorities to guide pandemic management.", + "rel_num_authors": 38, "rel_authors": [ { - "author_name": "Alejandro Lazo-Langner MD MSc", - "author_inst": "Division of Hematology, Department of Medicine, Western University, London, Ontario, Canada" + "author_name": "Ana Valesca Fernandes Gilson Silva", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" }, { - "author_name": "Benjamin Chin-Yee MD", - "author_inst": "Division of Hematology, Department of Medicine, Western University, London, Ontario, Canada" + "author_name": "Diego Menezes", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" }, { - "author_name": "Jaryd Tong BMSc", - "author_inst": "Department of Pathology and Laboratory Medicine, Western University, and London Health Sciences Centre, London, Ontario, Canada" + "author_name": "Filipe Romero Rebello Moreira", + "author_inst": "Departamento de Genetica, Instituto de Biologia, Universidade Federal do Rio de Janeiro, RJ, Brazil" }, { - "author_name": "Lori Lowes PhD", - "author_inst": "Department of Pathology and Laboratory Medicine, Western University, and London Health Sciences Centre, London, Ontario, Canada" + "author_name": "Octavio Alcantara Torres", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" }, { - "author_name": "Benjamin D. Hedley PhD", - "author_inst": "Department of Pathology and Laboratory Medicine, Western University, and London Health Sciences Centre, London, Ontario, Canada" + "author_name": "Paula Luize Camargos Fonseca", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" }, { - "author_name": "Michael Silverman MD", - "author_inst": "Division of Infectious Diseases, Department of Medicine, Western University, London, Ontario, Canada" + "author_name": "Rennan Garcias Moreira", + "author_inst": "Centro de Laboratorios Multiusuarios, Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" }, { - "author_name": "Johan Delport MBChB", - "author_inst": "Department of Pathology and Laboratory Medicine, Western University, and London Health Sciences Centre, London, Ontario, Canada" + "author_name": "Hugo Jose Alves", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" }, { - "author_name": "Vipin Bhayana PhD", - "author_inst": "Department of Pathology and Laboratory Medicine, Western University, and London Health Sciences Centre, London, Ontario, Canada" + "author_name": "Vivian Ribeiro Alves", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" }, { - "author_name": "Michael Knauer PhD", - "author_inst": "Department of Pathology and Laboratory Medicine, Western University, and London Health Sciences Centre, London, Ontario, Canada" + "author_name": "Tania Maria de Resende Amaral", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" }, { - "author_name": "Ian Chin-Yee MD", - "author_inst": "Department of Pathology and Laboratory Medicine, Western University, and London Health Sciences Centre, London, Ontario, Canada" + "author_name": "Adriano Neves Coelho", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Julia Maria Saraiva-Duarte", + "author_inst": "Programa de Pos Graduacao em Genetica; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Be" + }, + { + "author_name": "Augusto Viana da Rocha", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Luiz Gonzaga Paula de Almeida", + "author_inst": "Laboratorio Nacional de Computacao Cientifica, Petropolis, RJ, Brazil" + }, + { + "author_name": "Joao Locke Ferreira de Araujo", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" + }, + { + "author_name": "Hilton Soares de Oliveira", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Nova Jersey Claudio de Oliveira", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Camila Zolini de Sa", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" + }, + { + "author_name": "Josy Hubner de Souza", + "author_inst": "Programa de Pos-graduacao em Biologia Celular, Departamento de Morfologia; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo Horizont" + }, + { + "author_name": "Elizangela Goncalves de Souza", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Rafael Marques de Souza", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" + }, + { + "author_name": "Luciana de Lima Ferreira", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" + }, + { + "author_name": "Alexandra Lehmkuhl Gerber", + "author_inst": "Laboratorio Nacional de Computacao Cientifica, Petropolis, RJ, Brazil" + }, + { + "author_name": "Ana Paula de Campos Guimaraes", + "author_inst": "Laboratorio Nacional de Computacao Cientifica, Petropolis, RJ, Brazil" + }, + { + "author_name": "Paulo Henrique Silva Maia", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Fernanda Martins Marim", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" + }, + { + "author_name": "Lucyene Miguita", + "author_inst": "Departamento de Patologia, Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + }, + { + "author_name": "Cristiane Campos Monteiro", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Tuffi Saliba Neto", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Fabricia Soares Freire Pugedo", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Daniel Costa Queiroz", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" + }, + { + "author_name": "Damares Nigia Alborguetti Cuzzuol Queiroz", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Luciana Cunha Resende-Moreira", + "author_inst": "Departamento de Botanica, Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil" + }, + { + "author_name": "Franciele Martins Santos", + "author_inst": "Programa de Pos-graduacao em Biologia Celular, Departamento de Morfologia; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo Horizont" + }, + { + "author_name": "Erika Fernanda Carlos Souza", + "author_inst": "Escola de Saude Publica de Betim, Betim, MG, Brazil" + }, + { + "author_name": "Carolina Moreira Voloch", + "author_inst": "Departamento de Genetica, Instituto de Biologia, Universidade Federal do Rio de Janeiro, RJ, Brazil" + }, + { + "author_name": "Ana Tereza Vasconcelos", + "author_inst": "Laboratorio Nacional de Computacao Cientifica, Petropolis, RJ, Brazil" + }, + { + "author_name": "Renato Santana de Aguiar", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" + }, + { + "author_name": "Renan Pedra de Souza", + "author_inst": "Laboratorio de Biologia Integrativa; Departamento de Genetica, Ecologia e Evolucao; Instituto de Ciencias Biologicas; Universidade Federal de Minas Gerais, Belo" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.10.23.21265415", @@ -552943,39 +552546,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.25.21265493", - "rel_title": "Modeling the impact of vaccination strategies for nursing homes in the context of increased SARS-CoV-2 community transmission and variants", + "rel_doi": "10.1101/2021.10.24.21265444", + "rel_title": "A biological variation-based approach to the day-to-day changes of D-dimer, Fibrinogen, and Ferritin levels that are crucial in the clinical course of COVID-19 in healthy smokers and non-smokers", "rel_date": "2021-10-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.25.21265493", - "rel_abs": "Nursing homes (NH) were among the first settings to receive COVID-19 vaccines in the United States, but staff vaccination coverage remains low at an average of 64%. Using an agent-based model, we examined the impact of community prevalence, the Delta variant, staff vaccination coverage, and boosters for residents on outbreak dynamics in nursing homes. We found that increased staff primary series coverage and high booster vaccine effectiveness (VE) in residents leads to fewer infections and that the cumulative incidence is highly dependent on community transmission. Despite high VE, high community transmission resulted in continued symptomatic infections in NHs.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.24.21265444", + "rel_abs": "ObjectiveD-dimer, ferritin, and fibrinogen parameters in COVID-19 patients are essential, particularly in inpatients and intensive care unit patients. It is vital to know the changes that occur due to the biological structure of the person than the disease effect in these tests in order to manage the fatal disease better.\n\nMethodBlood samples were taken on the first, third, and fifth days from 30 healthy volunteers, 15 of whom were smokers, 15 were non-smokers, and D-dimer, ferritin, and fibrinogen tests were studied with repeated measurements. After the data processed for normality and homogeneity and removing extreme values, CVA, CVI, CVG, CVT, RCV, II, I%, B%, TE% values were calculated via a full nested ANOVA design, according to Callum G, Fraser, and EFLM.\n\nResultsCVI and CVG values of D-dimer were calculated as 49.07% and 40.69% for all individuals, 49.26% and 27.71% for smokers, 48.80% and 51.67% for non-smokers, respectively. In terms of fibrinogen, the same analyzes for all individuals were calculated as 11.18% and 10.62%, 3.25% and 20.17% for smokers, 9.11% and 6.79% for non-smokers, respectively. The same analyzes for ferritin were calculated as 23.74% and 63.31% for all individuals, 34.98% and 35.24% for smokers, 30.53% and 74.87% for non-smokers, respectively.\n\nConclusionChanges in D-dimer measurements every other day in healthy individuals can be observed depending on the biological characteristics of the individuals, and the population-based reference interval may be insufficient for clinical evaluation. Each individual should be evaluated within himself/herself. When evaluating the results of ferritin and fibrinogen in non-smoking individuals, it should be taken into account that significant differences may occur between individuals. Besides, it should be kept in mind that there may be significant changes due to biological variation in the repeated measurements of ferritin every other day.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Inga Holmdahl", - "author_inst": "Harvard T.H. Chan School of Public Health" - }, - { - "author_name": "Rebecca Kahn", - "author_inst": "Harvard T.H. Chan School of Public Health" - }, - { - "author_name": "Kara Jacobs Slifka", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Elif MENEKSE", + "author_inst": "Amasya University Sabuncuoglu Serefeddin Training and Research Hospital" }, { - "author_name": "Kathleen Dooling", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Muhammed Emin DUZ", + "author_inst": "Amasya Sabuncuo\u011flu \u015eerefeddin Training ABD Research Hospital" }, { - "author_name": "Rachel B Slayton", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "AYDIN BALCI", + "author_inst": "Afyon Health Sciences Unicersity Medical Faculty Respiratory Diseases" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.10.25.21265503", @@ -555101,29 +554696,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.22.21265371", - "rel_title": "Social mixing patterns in the UK following the relaxation of COVID-19 pandemic restrictions: a cross-sectional online survey", + "rel_doi": "10.1101/2021.10.22.21264706", + "rel_title": "Modeling the impact of school reopening and contact tracing strategies on Covid-19 dynamics in different epidemiologic settings in Brazil", "rel_date": "2021-10-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.22.21265371", - "rel_abs": "BackgroundSince 23 March 2020, social distancing measures have been implemented in the UK to reduce SARS-CoV-2 transmission. We conducted a cross-sectional survey to quantify and characterize non-household contact and to identify the effect of shielding and isolating on contact patterns.\n\nMethodsThrough an online questionnaire, the CoCoNet study measured daily interactions and mobility of 5143 participants between 28 July and 14 August 2020. Negative binomial regression modelling identified participant characteristics associated with contact rates.\n\nResultsThe mean rate of non-household contacts per person was 2.9 d-1. Participants attending a workplace (adjusted incidence rate ratio (aIRR) 3.33, 95%CI 3.02 to 3.66), self-employed (aIRR 1.63, 95%CI 1.43 to 1.87) or working in healthcare (aIRR 5.10, 95%CI 4.29 to 6.10) reported significantly higher non-household contact rates than those working from home. Participants self-isolating as a precaution or following Test and Trace instructions had a lower non-household contact rate than those not self-isolating (aIRR 0.58, 95%CI 0.43 to 0.79). We found limited evidence that those shielding had reduced non-household contacts compared to non-shielders.\n\nConclusionThe daily rate of non-household interactions remains lower than pre-pandemic levels, suggesting continued adherence to social distancing guidelines. Individuals attending a workplace in-person or employed as healthcare professionals were less likely to maintain social distance and had a higher non-household contact rate, possibly increasing their infection risk. Shielding and self-isolating individuals required greater support to enable them to follow the government guidelines and reduce non-household contact and therefore their risk of infection.\n\nSummary boxO_ST_ABSWhat is already known on this subject?C_ST_ABSO_LIThe introduction of social distancing guidelines in March 2020 reduced social contact rates in the UK.\nC_LIO_LIEvidence of low levels of adherence to self-isolation.\nC_LI\n\nWhat does this study add?O_LIThis study provides quantitative insight into the social mixing patterns in the UK at the beginning of the second wave of SARS-CoV2 infection.\nC_LIO_LIHealthcare professionals and individuals attending their workplace in-person were less able to follow social distancing guidelines and made more contact with people outside their household than those working from home.\nC_LIO_LIShielding individuals did not make fewer non-household contacts than those not shielding.\nC_LI", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.22.21264706", + "rel_abs": "Among the various non-pharmaceutical interventions implemented in response to the COVID-19 pandemic during 2020, school closures have been in place in several countries to reduce infection transmission. Nonetheless, the significant short and long-term impacts of prolonged suspension of in-person classes is a major concern. There is still considerable debate around the best timing for school closure and reopening, its impact on the dynamics of disease transmission, and its effectiveness when considered in association with other mitigation measures. Despite the erratic implementation of mitigation measures in Brazil, school closures were among the first measures taken early in the pandemic in most of the 27 states in the country. Further, Brazil delayed the reopening of schools and stands among the countries in which schools remained closed for the most prolonged period in 2020. To assess the impact of school reopening and the effect of contact tracing strategies in rates of COVID-19 cases and deaths, we model the epidemiological dynamics of disease transmission in 3 large urban centers in Brazil under different epidemiological contexts. We implement an extended SEIR model stratified by age and considering contact networks in different settings - school, home, work, and elsewhere, in which the infection transmission rate is affected by various intervention measures. After fitting epidemiological and demographic data, we simulate scenarios with increasing school transmission due to school reopening.\n\nOur model shows that reopening schools results in a non-linear increase of reported COVID-19 cases and deaths, which is highly dependent on infection and disease incidence at the time of reopening. While low rates of within-school transmission resulted in small effects on disease incidence (cases/100,000 pop), intermediate or high rates can severely impact disease trends resulting in escalating rates of new cases even if other interventions remain unchanged. When contact tracing and quarantining are restricted to school and home settings, a large number of daily tests is required to produce significant effects of reducing the total number of hospitalizations and deaths. Our results suggest that policymakers should carefully consider the epidemiological context and timing regarding the implementation of school closure and return of in-person school activities. Also, although contact tracing strategies are essential to prevent new infections and outbreaks within school environments, our data suggest that they are alone not sufficient to avoid significant impacts on community transmission in the context of school reopening in settings with high and sustained transmission rates.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Jessica R E Bridgen", - "author_inst": "Lancaster University" + "author_name": "Marcelo Eduardo Borges", + "author_inst": "Observat\u00f3rio Covid-19 BR" }, { - "author_name": "Chris P Jewell", - "author_inst": "Lancaster University" + "author_name": "Leonardo Souto Ferreira", + "author_inst": "Universidade Estadual Paulista, S\u00e3o Paulo, SP, Brazil" }, { - "author_name": "Jonathan M Read", - "author_inst": "Lancaster University" + "author_name": "Silas Poloni", + "author_inst": "Universidade Estadual Paulista, S\u00e3o Paulo, SP, Brazil" + }, + { + "author_name": "\u00c2ngela Maria Bagattini", + "author_inst": "Universidade Federal de Goi\u00e1s, Goi\u00e2nia, GO, Brazil" + }, + { + "author_name": "Caroline Franco", + "author_inst": "Universidade Estadual Paulista, S\u00e3o Paulo, SP, Brazil" + }, + { + "author_name": "Michelle Quarti Machado da Rosa", + "author_inst": "Universidade Federal de Goi\u00e1s Goi\u00e2nia, GO, Brazil" + }, + { + "author_name": "Lorena Mendes Simon", + "author_inst": "Universidade Federal de Goi\u00e1s, Goi\u00e2nia, GO, Brazil" + }, + { + "author_name": "Suzy Alves Camey", + "author_inst": "Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil" + }, + { + "author_name": "Ricardo de Souza Kuchenbecker", + "author_inst": "Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil" + }, + { + "author_name": "Paulo In\u00e1cio Prado", + "author_inst": "Universidade de S\u00e3o Paulo, S\u00e3o Paulo ,SP, Brazil." + }, + { + "author_name": "Jos\u00e9 Alexandre Felizola Diniz Filho", + "author_inst": "Universidade de S\u00e3o Paulo, S\u00e3o Paulo, SP, Brazil" + }, + { + "author_name": "Roberto Andr\u00e9 Kraenkel", + "author_inst": "Universidade Estadual Paulista, S\u00e3o Paulo, SP, Brazil" + }, + { + "author_name": "Renato Mendes Coutinho", + "author_inst": "Universidade Federal do ABC, Santo Andr\u00e9, SP, Brazil" + }, + { + "author_name": "Cristiana Maria Toscano", + "author_inst": "Universidade Federal de Goi\u00e1s, Goi\u00e3nia, GO, Brazil" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -557347,47 +556986,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.21.21265216", - "rel_title": "Generation time of the Alpha and Delta SARS-CoV-2 variants", + "rel_doi": "10.1101/2021.10.20.21265288", + "rel_title": "COVID-19 Vaccine Perceptions and Uptake in a National Prospective Cohort of Essential Workers", "rel_date": "2021-10-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.21.21265216", - "rel_abs": "BackgroundIn May 2021, the Delta SARS-CoV-2 variant became dominant in the UK. This variant is associated with increased transmissibility compared to the Alpha variant that was previously dominant. To understand ongoing transmission and interventions, a key question is whether the Delta variant generation time (the time between infections in infector- infectee pairs) is typically shorter-i.e., transmissions are happening more quickly-or whether infected individuals simply generate more infections.\n\nMethodsWe analysed transmission data from a UK Health Security Agency household study. By fitting a mathematical transmission model to the data, we estimated the generation times for the Alpha and Delta variants.\n\nResultsThe mean intrinsic generation time (the generation time if there had been a constant supply of susceptibles throughout infection) was shorter for the Delta variant (4{middle dot}6 days, 95% CrI 4{middle dot}0-5{middle dot}4 days) than the Alpha variant (5{middle dot}5 days, 95% CrI 4{middle dot}6-6{middle dot}4 days), although within uncertainty ranges. However, there was a larger difference in the realised mean household generation time between the Delta (3{middle dot}2 days, 95% CrI 2{middle dot}4-4{middle dot}2 days) and Alpha (4{middle dot}5 days, 95% CrI 3{middle dot}7-5{middle dot}4 days) variants. This is because higher transmissibility led to faster susceptible depletion in households, in addition to the reduced intrinsic generation time.\n\nConclusionsThe Delta variant transmits more quickly than previously circulating variants. This has implications for interventions such as contact tracing, testing and isolation, which are less effective if the virus is transmitted quickly. Epidemiological models of interventions should be updated to include the shorter generation time of the Delta variant.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.20.21265288", + "rel_abs": "IntroductionIn a multi-center prospective cohort of essential workers, we assessed knowledge, attitudes, and practices (KAP) by vaccine intention, prior SARS-CoV-2 positivity, and occupation, and their impact on vaccine uptake over time.\n\nMethodsInitiated in July 2020, HEROES-RECOVER cohort provided socio-demographics and COVID-19 vaccination data. Using follow-up two surveys approximately three months apart, COVID-19 vaccine KAP, intention, and receipt was collected; the first survey categorized participants as reluctant, reachable, or endorsers.\n\nResultsA total of 4,803 participants were included in the analysis. Most (70%) were vaccine endorsers, 16% were reachable, and 14% were reluctant. By May 2021, 77% had received at least one vaccine dose. KAP responses strongly predicted vaccine uptake, particularly positive attitudes about safety (aOR=5.46, 95% CI: 1.4-20.8) and effectiveness (aOR=5.0, 95% CI: 1.3-19.1). Participants prior SARS-CoV-2 infection were 22% less likely to believe the COVID-19 vaccine was effective compared with uninfected participants (aOR 0.78, 95% CI: 0.64-0.96). This was even more pronounced in first responders compared with other occupations, with first responders 42% less likely to believe in COVID-19 vaccine effectiveness (aOR=0.58, 95% CI 0.40-0.84). KAP responses shifted positively, with reluctant and reachable participant scores modestly increasing in positive responses for perceived vaccine effectiveness (7% and 12%, respectively) on the second follow-up survey; 25% of initially reluctant participants received the COVID-19 vaccine.\n\nDiscussionOur study demonstrates attitudes associated with COVID-19 vaccine uptake and a positive shift in attitudes over time. First responders, despite potential high exposure to SARS-CoV-2, and participants with a history of SARS-CoV-2 infection were more vaccine reluctant.\n\nConclusionsCOVID-19 vaccine KAP responses predicted vaccine uptake and associated attitudes improved over time. Perceptions of the COVID-19 vaccine can shift over time. Targeting messages about the vaccines safety and effectiveness in reducing SARS-CoV-2 virus infection and illness severity may increase vaccine uptake for reluctant and reachable participants.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "William S Hart", - "author_inst": "University of Oxford" + "author_name": "Karen Lutrick", + "author_inst": "University of Arizona" }, { - "author_name": "Liz Miller", - "author_inst": "LSHTM" + "author_name": "Holly Groom", + "author_inst": "Kaiser Permanente Northwest" }, { - "author_name": "Nick J Andrews", - "author_inst": "UK Health Security Agency" + "author_name": "Ashley Fowlkes", + "author_inst": "Centers of Disease Control and Prevention" }, { - "author_name": "Pauline Waight", - "author_inst": "UK Health Security Agency" + "author_name": "Kimberly Groover", + "author_inst": "Abt Associates" }, { - "author_name": "Philip K Maini", - "author_inst": "University of Oxford" + "author_name": "Manjusha Gaglani", + "author_inst": "Baylor Scott and White Health" }, { - "author_name": "Seb Funk", - "author_inst": "LSHTM" + "author_name": "Patrick Rivers", + "author_inst": "University of Arizona" }, { - "author_name": "Robin N Thompson", - "author_inst": "University of Warwick" + "author_name": "Allison Naleway", + "author_inst": "Kaiser Permanente Northwest" + }, + { + "author_name": "Kimberly Nguyen", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Meghan Herring", + "author_inst": "Abt Associates" + }, + { + "author_name": "Kayan Dunnigan", + "author_inst": "Baylor Scott and White Health" + }, + { + "author_name": "Andrew Phillips", + "author_inst": "University of Utah" + }, + { + "author_name": "Joel Parker", + "author_inst": "University of Arizona" + }, + { + "author_name": "Khaila Prather", + "author_inst": "Abt Associates" + }, + { + "author_name": "Matthew S Thiese", + "author_inst": "University of Utah" + }, + { + "author_name": "Zoe Baccam", + "author_inst": "University of Arizona" + }, + { + "author_name": "Harmony Tyner", + "author_inst": "St. Luke Hospital" + }, + { + "author_name": "Sarang Yoon", + "author_inst": "University of Utah" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.10.19.21265219", @@ -559076,65 +558755,65 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.10.20.21265269", - "rel_title": "Effect of the third dose of BNT162b2 vaccine in quantitative SARS-CoV-2 spike 1-2 IgG antibody titers in healthcare workers", - "rel_date": "2021-10-21", + "rel_doi": "10.1101/2021.10.18.21264783", + "rel_title": "SARS-CoV-2 variant transmission in a community-health population (Mexico City, Mexico)", + "rel_date": "2021-10-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.20.21265269", - "rel_abs": "BackgroundVaccination is our main strategy to control SARS-CoV-2 infection. Given a decrease in the quantitative SARS-CoV-2 spike 1-2 IgG antibody titers three months following the second BNT162b2 dose, healthcare workers got a third booster dose after six months of completing the original scheme. This study aimed to analyze quantitative SARS-CoV-2 spike 1-2 IgG antibody titers and safety of the third dose.\n\nMaterial and methodsA prospective longitudinal cohort study included healthcare workers who received a third booster dose after six months of the complete BNT162b2 regimen. We assessed the quantitative SARS-CoV-2 spike 1-2 IgG antibody titers 21-28 days after the first and second dose, three months after the complete scheme, 1-7 days following the third dose, and 21-28 days after the boost.\n\nResultsThe cohort comprised 168 non-immunocompromised participants of 41(10) years old, 67% being women. The third dose was associated with increasing the quantitative antibody titers, regardless of previous SARS-CoV-2 history. In negative SARS-CoV-2 history, the median (IQR) antibody titers increased from 379 (645.4) to 2960 (2010), while in positive SARS-CoV-2 history, from 590 (1262) to 3090 (2080). The third dose had less number of total side effects compared to the other two shots. The most common side effect after the third BNT162b2 shot was pain at the injection site (n=82, 84.5%), followed by tiredness (n=45, 46.4%), with a mild severity (n=36, 37.1%). Tiredness, myalgias, arthralgias, fever, and adenopathy were proportionally higher following the third dose than the two-dose regimen (p<0.05).\n\nConclusionThe third dose applied after six months of the original BNT162b2 regimen provided a good humoral immune response by elevating the quantitative SARS-CoV-2 spike 1-2 IgG antibody titers. The booster dose was well tolerated with no severe side effects after the additional BNT162b2 dose.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.18.21264783", + "rel_abs": "The SARS-CoV-2 variant, B.1.1.519, arose in North and Central America, circulating primarily in Mexico. We demonstrate that this variant peaked during the second wave of COVID-19 in Mexico City in the spring of 2021. This variant is likely more infectious, attributed to mutation in the RBD of the spike protein T478K also seen in the alpha variant (B.1.1.7). However the time dynamics of the spread of this variant drastically changed upon the introduction of delta (B.1.617.2) to the country in which we observe a shift from 0% in May 2021 to 55% delta in the span of one month. Since the delta variant has dominantly spread across the globe, we investigated the increasing frequency of the Mexico variant, B.1.1.519, in the public community within Mexico City. Once present, the delta variant was 78% of the Mexico City catchment in July 2021, a time which marked the commencement of Mexicos third wave. Our data supports the growing concern that the delta variant is closely associated with the massive infection spread of the VOC in Central and South America. While the T478K mutation, also seen in the alpha variant, has evidence for increased transmissibility, these data suggest that the delta variant shows overall increased fitness seeing as it outcompeted the B.1.1519 this Mexico community.", "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Maria Elena Romero-Ibarguengoitia", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Wenjuan Zhang", + "author_inst": "Cedars Sinai" }, { - "author_name": "Diego Rivera-Salinas", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Marcela Martinez", + "author_inst": "Biomedica de Referencia" }, { - "author_name": "Yodira Guadalupe Hernandez-Ruiz", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Brian D Davis", + "author_inst": "Cedars Sinai" }, { - "author_name": "Ana Gabriela Armendariz-Vazquez", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Stephanie S Chen", + "author_inst": "Cedars Sinai" }, { - "author_name": "Arnulfo Gonzalez-Cantu", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Jorge Sincuir Martinez", + "author_inst": "Cedars Sinai" }, { - "author_name": "Irene Antonieta Barco-Flores", - "author_inst": "Hospital Clinica Nova de Monterrey" + "author_name": "Clara Corona", + "author_inst": "Biomedica de Referencia" }, { - "author_name": "Rosalinda Gonzalez-Facio", - "author_inst": "Hospital Clinica Nova de Monterrey" + "author_name": "Guadalupe Diaz", + "author_inst": "Biomedica de Referencia" }, { - "author_name": "Laura Patricia Montelongo-Cruz", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Elias Makhoul", + "author_inst": "Cedars Sinai" }, { - "author_name": "Gerardo Francisco Del Rio-Parra", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Saleh Heneidi", + "author_inst": "Cedars Sinai" }, { - "author_name": "Mauricio Rene Garza-Herrera", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Jorge Goldberg", + "author_inst": "Cedars Sinai" }, { - "author_name": "Jessica Andrea Leal Melendez", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Jasmine T Plummer", + "author_inst": "Cedars Sinai Medical Center" }, { - "author_name": "Miguel Angel Sanz-Sanchez", - "author_inst": "Hospital Clinica Nova de Monterrey and Vicerrectoria de Ciencias de la Salud, Escuela de Medicina, Universidad de Monterrey" + "author_name": "Eric Vail", + "author_inst": "Cedars Sinai" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -561238,59 +560917,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.11.21264694", - "rel_title": "A cohort of 222 anti-CD20 treated patients with multiple sclerosis followed through the COVID-19 pandemic: Attenuated humoral but robust cellular immune responses after vaccination and infection", + "rel_doi": "10.1101/2021.10.16.464647", + "rel_title": "BugSplit: highly accurate taxonomic binning of metagenomic assemblies enables genome-resolved metagenomics", "rel_date": "2021-10-19", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.11.21264694", - "rel_abs": "ObjectiveTo analyze humoral and cellular immune responses to SARS-CoV-2 vaccinations and infections in anti-CD20 treated patients with multiple sclerosis (pwMS).\n\nMethods181 pwMS on anti-CD20 therapy and 41 pwMS who began anti-CD20 therapy were included in a prospective, observational, single-center cohort study between March 2020 and August 2021. 51 pwMS under anti-CD20 treatment, 14 anti-CD20 therapy-naive pwMS and 19 healthy controls (HC) were vaccinated twice against SARS-CoV-2. We measured SARS-CoV-2 spike protein (full-length, S1 domain and receptor binding domain) immunoglobulin (Ig)G and S1 IgA and virus neutralizing capacity and avidity of SARS-CoV-2 antibodies. SARS-CoV-2 specific T cells were determined by interferon-{gamma} release assays.\n\nResultsFollowing two SARS-CoV-2 vaccinations, levels of IgG and IgA antibodies to SARS-CoV-2 spike protein as well as neutralizing capacity and avidity of SARS-CoV-2 IgG were lower in anti-CD20 treated pwMS than in anti-CD20 therapy-naive pwMS and in HC (p<0.003 for all pairwise comparisons). However, in all anti-CD20 treated pwMS vaccinated twice (n=26) or infected with SARS-CoV-2 (n=2), in whom SARS-CoV-2 specific T cells could be measured, SARS-CoV-2 specific T cells were detectable, at levels similar to those of twice-vaccinated anti-CD20 therapy-naive pwMS (n=7) and HC (n=19). SARS-CoV-2 S1 IgG levels (r=0.42, p=0.002), antibody avidity (r=0.7, p<0.001) and neutralizing capacity (r=0.44, p=0.03) increased with time between anti-CD20 infusion and second vaccination. Based on detection of SARS-CoV-2 antibodies, SARS-CoV-2 infections occurred in 4/175 (2.3%) anti-CD20 treated pwMS, all of whom recovered fully.\n\nInterpretationThese findings should inform treatment decisions and SARS-CoV-2 vaccination management in pwMS.", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.16.464647", + "rel_abs": "A large gap remains between sequencing a microbial community and characterizing all of the organisms inside of it. Here we develop a novel method to taxonomically bin metagenomic assemblies through alignment of contigs against a reference database. We show that this workflow, BugSplit, bins metagenome-assembled contigs to species with a 33% absolute improvement in F1-score when compared to alternative tools. We perform nanopore mNGS on patients with COVID-19, and using a reference database predating COVID-19, demonstrate that BugSplits taxonomic binning enables sensitive and specific detection of a novel coronavirus not possible with other approaches. When applied to nanopore mNGS data from cases of Klebsiella pneumoniae and Neisseria gonorrhoeae infection, BugSplits taxonomic binning accurately separates pathogen sequences from those of the host and microbiota, and unlocks the possibility of sequence typing, in silico serotyping, and antimicrobial resistance prediction of each organism within a sample. BugSplit is available at https://bugseq.com/academic.", "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Tatjana Schwarz", - "author_inst": "Institute of Virology, Charite - Universitaetsmedizin" + "author_name": "Induja Chandrakumar", + "author_inst": "BugSeq Bioinformatics Inc." }, { - "author_name": "Carolin Otto", - "author_inst": "Department of Neurology, Charite - Universitaetsmedizin" + "author_name": "Nick PG Gauthier", + "author_inst": "Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada" }, { - "author_name": "Terry C Jones", - "author_inst": "Institute of Virology, Charite - Universitaetsmedizin" + "author_name": "Cassidy Nelson", + "author_inst": "Mathematical Ecology Research Group, Department of Zoology, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Florence Pache", - "author_inst": "Department of Neurology, Charite - Universitaetsmedizin Berlin" + "author_name": "Michael B Bonsall", + "author_inst": "Mathematical Ecology Research Group, Department of Zoology, University of Oxford, Oxford, United Kingdom" }, { - "author_name": "Patrick Schindler", - "author_inst": "Department of Neurology, Charite - Universitaetsmedizin Berlin" + "author_name": "Kerstin Locher", + "author_inst": "Division of Medical Microbiology, Vancouver General Hospital, Vancouver, British Columbia, Canada; Department of Pathology and Laboratory Medicine, University o" }, { - "author_name": "Moritz Niederschweiberer", - "author_inst": "Department of Neurology, Charite - Universitaetsmedizin Berlin" + "author_name": "Marthe Charles", + "author_inst": "Division of Medical Microbiology, Vancouver General Hospital, Vancouver, British Columbia, Canada; Department of Pathology and Laboratory Medicine, University o" }, { - "author_name": "Felix Schmidt", - "author_inst": "Department of Neurology, Charite- Universitaetsmedizin" + "author_name": "Clayton MacDonald", + "author_inst": "Division of Medical Microbiology, Vancouver General Hospital, Vancouver, British Columbia, Canada; Department of Pathology and Laboratory Medicine, University o" }, { - "author_name": "Christian Drosten", - "author_inst": "Institute of Virology, Charite Universitaetsmedizin Berlin" + "author_name": "Mel Krajden", + "author_inst": "Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada; British Columbia Centre for Disease Contro" }, { - "author_name": "Victor M Corman", - "author_inst": "Institute of Virology, Charite - Universitaetsmedizin Berlin" + "author_name": "Amee Manges", + "author_inst": "British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada; School of Population and Public Health, University of British Columbia, Vancou" }, { - "author_name": "Klemens Ruprecht", - "author_inst": "Department of Neurology, Charite - Universitaetsmedizin Berlin" + "author_name": "Samuel D Chorlton", + "author_inst": "Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, British Columbia, Canada; BugSeq Bioinformatics Inc." } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "license": "cc_by_nd", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.10.13.21264920", @@ -562879,49 +562558,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.10.15.21265059", - "rel_title": "CoWWAn: Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis", + "rel_doi": "10.1101/2021.10.14.21264980", + "rel_title": "Incidence of SARS-CoV-2 infection in a cohort of workers from the University of Porto", "rel_date": "2021-10-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.15.21265059", - "rel_abs": "We present COVID-19 Wastewater Analyser (CoWWAn) to reconstruct the epidemic dynamics from SARS-CoV-2 viral load in wastewater. As demonstrated for various regions and sampling protocols, this mechanistic model-based approach quantifies the case numbers, provides epidemic indicators and accurately infers future epidemic trends. In situations of reduced testing capacity, analysing wastewater data with CoWWAn is a robust and cost-effective alternative for real-time surveillance of local COVID-19 dynamics.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.14.21264980", + "rel_abs": "BackgroundRepeated serosurveys in the same population provide more accurate estimates of the frequency of SARS-CoV-2 infection and more comparable data than notified cases. We aimed to estimate the incidence of SARS-CoV-2 infection, identify associated risk factors, and assess time trends in the ratio of serological/molecular diagnosis in a cohort of university workers.\n\nMethodsParticipants had a serological rapid test for SARS-CoV-2 Immunoglobulins M and G, and completed a questionnaire, in May-July 2020 (n=3628) and November 2020-January 2021 (n=2661); 1960 participated in both evaluations and provided data to compute the incidence proportion and the incident rate. Crude and adjusted incidence rate ratios (aIRR) and 95% confidence intervals (CI) were computed using generalised linear models with Poisson regression.\n\nResultsThe incidence rate was 1.8/100 person-month (95%CI 1.6-2.1), and the 6 months cumulative incidence was 10.7%. The serological/molecular diagnosis ratio was 10:1 in the first evaluation and 3:1 in the second. Considering newly identified seropositive cases at the first (n=69) and second evaluation (n=202), 29.0% and 9.4% never reported symptoms, respectively, 14.5% and 33.3% reported contact with a confirmed case and 82.6%, and 46.0% never had a molecular test. Males (aIRR: 0.59; 95%CI: 0.42-0.83) and \"high-skilled white-collar\" workers (aIRR: 0.73, 95%CI: 0.52-1.02) had lower incidence of infection.\n\nConclusionUniversity workers presented a high SARS-CoV-2 incidence while restrictive measures were in place. The time decrease in the proportion of undiagnosed cases reflected the increased access to testing, but opportunities continued to be missed, even in the presence of COVID-19 like symptoms.\n\nWhat is already known on this subjectO_LIThe median ratio of seroprevalence to the corresponding cumulative incidence is 18, however, there is great variability between studies.\nC_LIO_LISeroprevalence studies are essential to estimate the true burden of the infection.\nC_LIO_LIFew cohort studies focused on essential non-healthcare workers, such as university workers.\nC_LI\n\nWhat this study addsO_LIThis longitudinal seroprevalence study among university workers found a SARS-CoV-2-specific IgM or IgG incidence rate of 1.8/100 person-month, and a 6 months cumulative incidence of 10.7%.\nC_LIO_LIThe undiagnosed fraction was 3:1 in the second evaluation, representing a decrease from a 10:1 in the first evaluation in the same population showing that a gap to test-trace-isolate remained in this highly educated working population.\nC_LIO_LISeropositive participants were mostly pauci- or symptomatic with no known contact with a COVID-19 confirmed case; \"high-skilled white-collar\" workers were at lower risk of being an incident seropositive case.\nC_LI", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Daniele Proverbio", - "author_inst": "University of Luxembourg" - }, - { - "author_name": "Fran\u00e7oise Kemp", - "author_inst": "University of Luxembourg" - }, - { - "author_name": "Stefano Magni", - "author_inst": "University of Luxembourg" - }, - { - "author_name": "Leslie Ogorzaly", - "author_inst": "Luxembourg Institute of Science and Technology" - }, - { - "author_name": "Henry-Michel Cauchie", - "author_inst": "Luxembourg Institute of Scienceand Technology" + "author_name": "Joana Pinto Costa", + "author_inst": "EPIUnit - Instituto de Saude Publica da Universidade do Porto" }, { - "author_name": "Jorge Gon\u00e7alves", - "author_inst": "University of Luxembourg" + "author_name": "Paula Meireles", + "author_inst": "EPIUnit - Instituto de Saude Publica da Universidade do Porto" }, { - "author_name": "Alexander Skupin", - "author_inst": "University of Luxembourg" + "author_name": "Pedro N S Rodrigues", + "author_inst": "i3S - Instituto de Investigacao e Inovacao em Saude" }, { - "author_name": "Atte Aalto", - "author_inst": "University of Luxembourg" + "author_name": "Henrique Barros", + "author_inst": "EPIUnit - Instituto de Saude Publica da Universidade do Porto" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -564517,59 +564180,31 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.10.13.21264894", - "rel_title": "Memory B cell and humoral responses elicited by Sputnik V in nai\u0308ve and COVID-19-recovered vaccine recipients", + "rel_doi": "10.1101/2021.10.14.21264861", + "rel_title": "Interactions among common non-SARS-CoV-2 respiratory viruses and influence of the COVID-19 pandemic on their circulation in New York City", "rel_date": "2021-10-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.13.21264894", - "rel_abs": "The development of effective vaccines against SARS-CoV-2 remains a global health priority. Despite extensive use, the effects of Sputnik V on B cell immunity need to be explored in detail. We show that B memory cell (MBC) and antibody responses to Sputnik V were heavily dependent on whether the vaccinee had a history of SARS-CoV-2 infection or not. In vitro stimulated MBCs from previously infected recipients of Sputnik V secreted a significant amount of anti-RBD IgG both on days 28 and 85 from the beginning of vaccination. These antibodies demonstrated robust neutralization of the Wuhan Spike-pseudotyped lentivirus. In the naive group of vaccinees, the level of anti-RBD IgG secretion was five- to six-fold reduced compared to that of the recovered group, and maximum virus neutralization (Wuhan spike) was achieved only on day 85. Sera from all the recovered and most naive Sputnik V recipients were neutralizing against the ancestral Wuhan and mutant B.1.351 viruses. Thus, our in-depth analysis of MBC responses in Sputnik V vaccinees complements traditional serological approaches and may provide important outlook into future B cell responses upon re-encounter with the emerging variants of SARS-CoV-2.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.14.21264861", + "rel_abs": "BackgroundNon-pharmaceutical interventions (NPIs) and voluntary behavioral changes during the COVID-19 pandemic have influenced the circulation of non-SARS-CoV-2 respiratory infections. We aimed to examine interactions among common non-SARS-CoV-2 respiratory virus and further estimate the impact of the COVID-19 pandemic on these viruses.\n\nMethodsWe analyzed incidence data for seven groups of respiratory viruses in New York City (NYC) during Oct 2015 - May 2021 (i.e., before and during the COVID-19 pandemic). We first used elastic net regression to identify potential virus interactions and further examined the robustness of the found interactions by comparing the performance of Auto Regressive Integrated Moving Average (ARIMA) models with and without the interactions. We then used the models to compute counterfactual estimates of cumulative incidence and estimate the reduction during the COVID-19 pandemic period from March 2020 to May 2021, for each virus.\n\nResultsWe identified potential interactions for three endemic human coronaviruses (CoV-NL63, CoV-HKU, and CoV-OC43), parainfluenza (PIV)-1, rhinovirus, and respiratory syncytial virus (RSV). We found significant reductions (by ~70-90%) in cumulative incidence of CoV-OC43, CoV-229E, human metapneumovirus, PIV-2, PIV-4, RSV, and influenza virus during the COVID-19 pandemic. In contrast, the circulation of adenovirus and rhinovirus was less affected.\n\nConclusionsCirculation of several respiratory viruses has been low during the COVID-19 pandemic, which may lead to increased population susceptibility. It is thus important to enhance monitoring of these viruses and promptly enact measures to mitigate their health impacts (e.g., influenza vaccination campaign and hospital infection prevention) in the coming months.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Maria G Byazrova", - "author_inst": "Institute of Immunology Moscow" - }, - { - "author_name": "Sergey V Kulemzin", - "author_inst": "Institute of Molecular and Cellular Biology" - }, - { - "author_name": "Ekaterina A Astakhova", - "author_inst": "Institute of Immunology Moscow" - }, - { - "author_name": "Tatyana N Belovezhets", - "author_inst": "Institute of Molecular and Cellular Biology" - }, - { - "author_name": "Grigory A Efimov", - "author_inst": "National Research Center for Hematology" - }, - { - "author_name": "Anton N Chikaev", - "author_inst": "Institute of Molecular and Cellular Biology" - }, - { - "author_name": "Ilya O Kolotygin", - "author_inst": "Institute of Molecular and Cellular Biology" - }, - { - "author_name": "Andrey A Gorchakov", - "author_inst": "Institute of Molecular and Cellular Biology" + "author_name": "Haokun Yuan", + "author_inst": "Columbia University" }, { - "author_name": "Alexander V Taranin", - "author_inst": "Institute of Molecular and Cellular Biology" + "author_name": "Alice Yeung", + "author_inst": "New York City Department of Health and Mental Hygiene" }, { - "author_name": "Alexander V Filatov", - "author_inst": "Institute of Immunology Moscow" + "author_name": "Wan Yang", + "author_inst": "Columbia University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.10.14.21265032", @@ -566670,23 +566305,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.11.21264869", - "rel_title": "Modeling and analysis of COVID-19 infected persons during repeated waves in Japan", + "rel_doi": "10.1101/2021.10.14.21264959", + "rel_title": "Vaccine effectiveness against SARS-CoV-2 transmission to household contacts during dominanceof Delta variant (B.1.617.2), August-September 2021, the Netherlands", "rel_date": "2021-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.11.21264869", - "rel_abs": "A model for estimating the number of COVID-19 infected persons (infecteds) is proposed based on the exponential function law of the SIR model. This model is composed of several equations expressing the number of infecteds, considering the onset after an incubation period, infectivity, wavy infection persistence with repeated infection spread and convergence with insufficient quarantine. This model is applied to the infection in Japan, which is currently suffering from the 5th wave, and the initial number of infecteds and various related parameters are calculated by curve fitting of the cumulative number of infecteds to the total cases in the database. As a minimum boundary of the number of infecteds for the infection continuation up to the 5th wave, the initial number of infecteds at the outbreak of infection is more than an order of magnitude higher than the actual initial cases. A convergence ratio (cumulative number of infecteds / total cases) at the end of the first wave is obtained as 1.5. The quarantine rate and social distancing ratio based on the SIQR model are evaluated, and the social distancing ratio increases sharply just after the governments declaration of emergency. The quarantine rate closely equals the positive rate by PCR tests, meaning that the number of infecteds, which had been unknown, is on the order of almost the same as the number of tests.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.14.21264959", + "rel_abs": "We estimated vaccine effectiveness against onward transmission by comparing secondary attack rates among household members between vaccinated and unvaccinated index cases, based on source and contact tracing data collected when Delta variant was dominant. Effectiveness of full vaccination of the index against transmission to fully vaccinated household contacts was 40% (95% confidence interval (CI) 20-54%), which is in addition to the direct protection of vaccination of contacts against infection. Effectiveness of full vaccination of the index against transmission to unvaccinated household contacts was 63% (95%CI 46-75%). We previously reported effectiveness of 73% (95%CI 65-79%) against transmission to unvaccinated household contacts for the Alpha variant.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Koichi Hashiguchi", - "author_inst": "None" + "author_name": "Brechje de Gier", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Stijn Andeweg", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Jantien A. Backer", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Susan J.M. Hahn\u00e9", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Susan van den Hof", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Hester E. de Melker", + "author_inst": "National Institute for Public Health and the Environment" + }, + { + "author_name": "Mirjam J. Knol", + "author_inst": "National Institute for Public Health and the Environment" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.10.13.21264968", @@ -568572,33 +568231,37 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.10.10.21264821", - "rel_title": "Modelling the effect of COVID-19 mass vaccination on acute admissions in a major English healthcare system", + "rel_doi": "10.1101/2021.10.10.21264817", + "rel_title": "Child mental and behavioral health services during the COVID-19 pandemic: Trends and implications for service outcomes during telehealth expansion", "rel_date": "2021-10-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.10.21264821", - "rel_abs": "BackgroundManaging high levels of severe COVID-19 in the acute setting can impact upon the quality of care provided to both affected patients and those requiring other hospital services. Mass vaccination has offered a route to reduce societal restrictions while protecting hospitals from being overwhelmed. Yet, early in the mass vaccination effort, the possible effect on future bed pressures remained subject to considerable uncertainty. This paper provides an account of how, in one healthcare system, operational decision-making and bed planning was supported through modelling the effect of a range of vaccination scenarios on future COVID-19 admissions.\n\nMethodsAn epidemiological model of the Susceptible-Exposed-Infectious-Recovered (SEIR) type was fitted to local data for the one-million resident healthcare system located in South West England. Model parameters and vaccination scenarios were calibrated through a system-wide multi-disciplinary working group, comprising public health intelligence specialists, healthcare planners, epidemiologists, and academics. From 4 March 2021 (the time of the study), scenarios assumed incremental relaxations to societal restrictions according to the envisaged UK Government timeline, with all restrictions to be removed by 21 June 2021.\n\nResultsAchieving 95% vaccine uptake in adults by 31 July 2021 would not avert a third wave in autumn 2021 but would produce a median peak bed requirement approximately 6% (IQR: 1% to 24%) of that experienced during the second wave (January 2021). A two-month delay in vaccine rollout would lead to significantly higher peak bed occupancy, at 66% (11% to 146%) of that of the second wave. If only 75% uptake was achieved (the amount typically associated with vaccination campaigns) then the second wave peak for acute and intensive care beds would be exceeded by 4% and 19% respectively, an amount which would seriously pressure hospital capacity.\n\nConclusionModelling provided support to senior managers in setting the number of acute and intensive care beds to make available for COVID-19 patients, as well as highlighting the importance of public health in promoting high vaccine uptake among the population. Forecast accuracy has since been supported by actual data collected following the analysis, with observed peak bed occupancy falling comfortably within the inter-quartile range of modelled projections.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.10.21264817", + "rel_abs": "Transportation to/from care is a significant barrier to healthcare access and utilization. The novel coronavirus pandemic prompted a widespread expansion of telehealth service delivery throughout much of 2020. We used propensity score matching to generate two comparison groups of children served in a large public mental and behavioral health system between (1) April-December 2019 (pre-pandemic; n=2,794), and (2) between April-December 2020 (during the COVID-19 pandemic, n=2,794), followed by longitudinal linear mixed-effects modelling to explore the relationship between caregiver transportation needs and child-level outcomes. Our analyses indicated a statistically significant association between the resolution of caregivers transportation needs and childrens clinical improvement in the 2019 (pre-pandemic) sample; there was no such association found in the 2020 (pandemic) sample. Our findings suggest that the use of telehealth may mitigate the effect of caregiver transportation needs on child-level clinical outcomes.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ross D Booton", - "author_inst": "University of Bristol" + "author_name": "Elizabeth N. Riley", + "author_inst": "University of Kentucky" }, { - "author_name": "Anna L Powell", - "author_inst": "UK National Health Service" + "author_name": "Kate Cordell", + "author_inst": "University of Kentucky" }, { - "author_name": "Katy ME Turner", - "author_inst": "University of Bristol" + "author_name": "Stephen Shimshock", + "author_inst": "University of Kentucky" }, { - "author_name": "Richard M Wood", - "author_inst": "UK National Health Service" + "author_name": "John Lyons", + "author_inst": "University of Kentucky" + }, + { + "author_name": "Olga A Vsevolozhskaya", + "author_inst": "University of Kentucky" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "health informatics" }, @@ -570249,47 +569912,35 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.10.08.21264765", - "rel_title": "The impact of heating, ventilation, and air conditioning design features on the transmission of viruses, including the 2019 novel coronavirus: a systematic review of ventilation and coronavirus", + "rel_doi": "10.1101/2021.10.08.21264708", + "rel_title": "The effect of training and workstation adjustability on teleworker discomfort during the COVID-19 pandemic", "rel_date": "2021-10-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.08.21264765", - "rel_abs": "Aerosol transmission has been a pathway for virus spread for many viruses. Similarly, emerging evidence regarding SARS-CoV-2, and the resulting pandemic as declared by WHO in March 2020, determined aerosol transmission for SARS-CoV-2 to be significant. As such, public health officials and professionals have sought data regarding the effect of Heating, Ventilation, and Air Conditioning (HVAC) features to control and mitigate viruses, particularly coronaviruses. A systematic review was conducted using international standards to identify and comprehensively synthesize research examining the effectiveness of ventilation for mitigating transmission of coronaviruses. The results from 32 relevant studies showed that: increased ventilation rate was associated with decreased transmission, transmission probability/risk, infection probability/risk, droplet persistence, virus concentration, and increased virus removal and virus particle removal efficiency; increased ventilation rate decreased risk at longer exposure times; some ventilation was better than no ventilation; airflow patterns affected transmission; ventilation feature (e.g., supply/exhaust, fans) placement influenced particle distribution. Some studies provided qualitative recommendations; however, few provided specific quantitative ventilation parameters suggesting a significant gap in current research. Adapting HVAC ventilation systems to mitigate virus transmission is not a one-solution-fits-all approach but instead requires consideration of factors such as ventilation rate, airflow patterns, air balancing, occupancy, and feature placement.\n\nPractical ImplicationsIncreasing ventilation, whether through ventilation rates (ACH, m3/h, m3/min, L/min) or as determined by CO2 levels (ppm), is associated with decreased transmission, transmission probability/risk, infection probability/risk, droplet persistence, and virus concentration, and increased virus removal and efficiency of virus particle removal. As well, professionals should consider the fact that changing ventilation rate or using mixing ventilation is not always the only way to mitigate and control viruses as varying airflow patterns and the use of ventilation resulted in better outcomes than situations without ventilation. Practitioners also need to consider occupancy, ventilation feature (supply/exhaust and fans) placement, and exposure time in conjunction with both ventilation rates and airflow patterns. Some recommendations with quantified data were made, including using an air change rate of 9 h-1 for a hospital ward; waiting six air changes or 2.5 hours before allowing different individuals into an unfiltered office with [~]2 fresh air changes (FCH) and one air change for a high-efficiency MERV or HEPA filtered laboratory; and using a pressure difference between -2 and -25 Pa in negative pressure isolation spaces. Other recommendations for practice included using or increasing ventilation, introducing fresh air, using maximum supply rates, avoiding poorly ventilated spaces, assessing fan placement and potentially increasing ventilation locations, and employing ventilation testing and air balancing checks.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.08.21264708", + "rel_abs": "Advancements in telework have increased occupational flexibility for employees and employers alike. However, while effective telework requires planning, the COVID-19 pandemic required many employees to quickly shift to working from home without making sure the requirements for telework were in place beforehand. This study evaluated the transition to telework on university faculty and staff and investigated the effect of ones telework setup and ergonomics training on work-related discomfort in the at-home environment. Respondents reported increases in new or worsening pain since working from home of 24% and 51%, respectively, suggesting an immediate need for ergonomic interventions, including workstation evaluations, ergonomic training, and individual ergonomic assessments, for those who work from home.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Gail M. Thornton", - "author_inst": "University of Alberta" - }, - { - "author_name": "Brian A Fleck", - "author_inst": "University of Alberta" - }, - { - "author_name": "Emily Kroeker", - "author_inst": "University of Alberta" - }, - { - "author_name": "Dhyey Dandnayak", - "author_inst": "University of Alberta" + "author_name": "Megan J McAllister", + "author_inst": "School of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, Canada" }, { - "author_name": "Natalie Fleck", - "author_inst": "University of Alberta" + "author_name": "Patrick A Costigan", + "author_inst": "School of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, Canada" }, { - "author_name": "Lexuan Zhong", - "author_inst": "University of Alberta" + "author_name": "Joshua P Davies", + "author_inst": "School of Kinesiology and Health Studies, Queen's University, Kingston, Ontario, Canada" }, { - "author_name": "Lisa A Hartling", - "author_inst": "University of Alberta" + "author_name": "Tara L Diesbourg", + "author_inst": "Public and Environmental Wellness, School of Health Sciences, Oakland University, Rochester, Michigan, USA" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.10.07.21264657", @@ -572187,55 +571838,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.10.09.21264771", - "rel_title": "Taste loss as a distinct symptom of COVID-19: A systematic review and meta-analysis", - "rel_date": "2021-10-09", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.09.21264771", - "rel_abs": "Chemosensory scientists have been skeptical that reports of COVID-19 taste loss are genuine, in part because before COVID-19, taste loss was rare and often confused with smell loss. Therefore, to establish the predicted prevalence rate of taste loss in COVID-19 patients, we conducted a systematic review and meta-analysis of 376 papers published in 2020-2021, with 241 meeting all inclusion criteria. Additionally, we explored how methodological differences (direct vs. self-report measures) may affect these estimates. We hypothesized that direct prevalence measures of taste loss would be the most valid because they avoid the taste/smell confusion of self-report. The meta-analysis showed that, among 138,897 COVID-19-positive patients, 39.2% reported taste dysfunction (95% CI: 35.34-43.12%), and the prevalence estimates were slightly but not significantly higher from studies using direct (n = 18) versus self-report (n = 223) methodologies (Q = 0.57, df = 1, p = 0.45). Generally, males reported lower rates of taste loss than did females and taste loss was highest in middle-aged groups. Thus, taste loss is a bona fide symptom COVID-19, meriting further research into the most appropriate direct methods to measure it and its underlying mechanisms.", - "rel_num_authors": 9, + "rel_doi": "10.1101/2021.10.06.463336", + "rel_title": "Compositional analysis of Sindbis virus ribonucleoproteins reveals an extensive co-opting of key nuclear RNA-binding proteins", + "rel_date": "2021-10-08", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.10.06.463336", + "rel_abs": "The expansion of tropical mosquito habitats and associated arboviruses is a risk for human health, and it thus becomes fundamental to identify new antiviral strategies. In this study we employ a new approach to elucidate the composition of the ribonucleoproteins (RNPs) of a prototypical arbovirus called Sindbis (SINV). SINV RNPs contain 453 cellular and 6 viral proteins, many of these proteins are nuclear in uninfected cells and redistribute to the cytoplasm upon infection. These findings suggest that SINV RNAs act as spiderwebs, capturing host factors required for viral replication and gene expression in the cytoplasm. Functional perturbation of several of these host proteins causes profound effects in virus infection, as illustrated here with the tRNA ligase complex. Moreover, inhibition of viral RNP components with available drugs hampers the infection of a wide range of viruses, opening new avenues for the development of broad-spectrum therapies.\n\nResearch highlightsO_LISINV RNA interactome includes 453 cellular and 6 viral proteins.\nC_LIO_LINuclear RBPs that interact with SINV RNA are selectively redistributed to the cytoplasm upon infection\nC_LIO_LIThe tRNA ligase complex plays major regulatory roles in SINV and SARS-CoV- 2 replication\nC_LIO_LIThe SINV RNA interactome is enriched in pan-viral regulators with therapeutic potential.\nC_LI", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Mackenzie R Hannum", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Wael Kamel", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, G61 1QH, Glasgow, Scotland (UK). Department of Biochemistry, University of Oxford, South Parks Road, OX1 3Q" }, { - "author_name": "Riley Koch", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Vincenzo Ruscica", + "author_inst": "Department of Biochemistry, University of Oxford, South Parks Road, OX1 3QU, Oxford, UK." }, { - "author_name": "Vicente Ramirez", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Manuel Garcia-Moreno", + "author_inst": "Department of Biochemistry, University of Oxford, South Parks Road, OX1 3QU, Oxford, UK." }, { - "author_name": "Sarah Marks", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Natasha Palmalux", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, G61 1QH, Glasgow, Scotland (UK)" }, { - "author_name": "Aurora Toskala", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Louisa Iselin", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, G61 1QH, Glasgow, Scotland (UK). Department of Biochemistry, University of Oxford, South Parks Road, OX1 3Q" }, { - "author_name": "Riley Herriman", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Maximilian Hannan", + "author_inst": "Department of Biochemistry, University of Oxford, South Parks Road, OX1 3QU, Oxford, UK." }, { - "author_name": "Cailu Lin", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Aino J\u00e4rvelin", + "author_inst": "Department of Biochemistry, University of Oxford, South Parks Road, OX1 3QU, Oxford, UK." }, { - "author_name": "Paule Valery Joseph", - "author_inst": "NIH/NIAAA" + "author_name": "Marko Noerenberg", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, G61 1QH, Glasgow, Scotland (UK)" }, { - "author_name": "Danielle R Reed", - "author_inst": "Monell Chemical Senses Center" + "author_name": "Samantha Moore", + "author_inst": "Department of Biochemistry, University of Oxford, South Parks Road, OX1 3QU, Oxford, UK" + }, + { + "author_name": "Andres Merits", + "author_inst": "Institute of Technology, University of Tartu, Tartu, 50411, Estonia" + }, + { + "author_name": "Ilan Davis", + "author_inst": "Department of Biochemistry, University of Oxford, South Parks Road, OX1 3QU, Oxford, UK" + }, + { + "author_name": "Javier Martinez", + "author_inst": "Center of Medical Biochemistry, Max Perutz Labs, Medical University of Vienna, Vienna, Austria" + }, + { + "author_name": "Shabaz Mohammed", + "author_inst": "Department of Biochemistry, University of Oxford, South Parks Road, OX1 3QU, Oxford, UK. Department of Chemistry, University of Oxford, Mansfield Road, Oxford, " + }, + { + "author_name": "Alfredo Castello", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, G61 1QH, Glasgow, Scotland (UK). Department of Biochemistry, University of Oxford, South Parks Road, OX1 3Q" } ], "version": "1", - "license": "cc_by_nc", - "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2021.10.07.463532", @@ -574285,55 +573956,71 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2021.10.05.21264597", - "rel_title": "Effect of workplace infection control practices on workers' psychological distress: a large-scale cohort study during the COVID-19 second state of emergency in Japan", + "rel_doi": "10.1101/2021.10.06.21264631", + "rel_title": "Genetic risk factors and Covid-19 severity in Brazil: results from BRACOVID Study", "rel_date": "2021-10-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.05.21264597", - "rel_abs": "BackgroundThe COVID-19 pandemic has dramatically transformed the work environment and work practices worldwide. Long-term infection control practices may increase the psychological stress on workers, and conversely, inadequate infection control practices at the working place may increase the fear of infection. This study aimed to determine the relationship between infection control practices at the workplace and employee mental health during the COVID-19 pandemic in Japan.\n\nMethodsThis study was conducted in December 2020 and February 2021. The participants had undergone a preliminary survey, which revealed that they were in good mental health. Their psychological distress was investigated via a second survey, and the factors associated with distress were studied using a logistic model.\n\nResultsThe results of the second survey indicated that 15.1% of participants demonstrated psychological distress. This was associated with leave-of-absence instructions, instructions for shortening business hours, and requests to avoid the workplace in case of any symptoms.\n\nConclusionThe study found that while some infection control practices reduce workers distress, others worsen it. Employers need to consider infection control practices as well as the worsening mental health of employees following a decrease in income caused by such measures. Follow-up studies may be necessary to clarify the long-term effects on workers mental health.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.06.21264631", + "rel_abs": "The Covid-19 pandemic has changed the paradigms for disease surveillance and rapid deployment of scientific-based evidence for understanding disease biology, susceptibility, and treatment. We have organized a large-scale genome-wide association study in Sars-Cov-2 infected individuals in Sao Paulo, Brazil, one of the most affected areas of the pandemic in the country, itself one of the most affected in the world. Here we present the results of the initial analysis in the first 5,233 participants of the BRACOVID study.\n\nWe have conducted a GWAS for Covid-19 hospitalization enrolling 3533 cases (hospitalized Covid-19 participants) and 1700 controls (non-hospitalized Covid-19 participants). Models were adjusted by age, sex and the 4 first principal components. A meta-analysis was also conducted merging BRACOVID hospitalization data with the Human Genetic Initiative (HGI) Consortia results.\n\nBRACOVID results validated most loci previously identified in the HGI meta-analysis. In addition, no significant heterogeneity according to ancestral group within the Brazilian population was observed for the two most important Covid-19 severity associated loci: 3p21.31 and Chr21 near IFNAR2. Using only data provided by BRACOVID a new genome-wide significant locus was identified on Chr1 near the genes DSTYK and RBBP5. The associated haplotype has also been previously associated with a number of blood cell related traits and might play a role in modulating the immune response in Covid-19 cases.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Toyohiko Kodama", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Alexandre Pereira", + "author_inst": "Harvard Medical School" }, { - "author_name": "Tomohiro Ishimaru", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Taniela M Bes", + "author_inst": "Harvard Medical School" }, { - "author_name": "Seiichiro Tateishi", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Mariliza Velho", + "author_inst": "Heart Institute (InCor) - University of Sao Paulo" }, { - "author_name": "Ayako Hino", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Emanuelle Marques", + "author_inst": "Heart Institute (InCor) - University of Sao Paulo" }, { - "author_name": "Mayumi Tsuji", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Cinthia Jannes", + "author_inst": "Heart Institute (InCor) - University of Sao Paulo" }, { - "author_name": "Akira OGami", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Karina Ramos Valino", + "author_inst": "Heart Institute (InCor) - University of Sao Paulo" }, { - "author_name": "Tomohisa Nagata", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Carla M Dinardo", + "author_inst": "FUNDACAO PRO-SANGUE" }, { - "author_name": "Shinya Matsuda", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Silvia F Costa", + "author_inst": "University of Sao Paulo" }, { - "author_name": "Yoshihisa Fujino", - "author_inst": "University of Occupational and Environmental Health, Japan" + "author_name": "Alberto J Duarte", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Alexandre R Santos", + "author_inst": "Grupo Fleury" + }, + { + "author_name": "Miguel Mitne-Neto", + "author_inst": "Grupo Fleury" + }, + { + "author_name": "Jose M Pestana", + "author_inst": "Universidade Federal de Sao Paulo" + }, + { + "author_name": "Jose E Krieger", + "author_inst": "Heart Institute (InCor) - University of Sao Paulo" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.10.05.21264583", @@ -576487,77 +576174,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.10.02.21264267", - "rel_title": "Year-long COVID-19 infection reveals within-host evolution of SARS-CoV-2 in a patient with B cell depletion", + "rel_doi": "10.1101/2021.10.02.21264415", + "rel_title": "Acquisition and onward transmission of a SARS-CoV-2 E484K variant among household contacts of a bamlanivimab-treated patient", "rel_date": "2021-10-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.02.21264267", - "rel_abs": "BackgroundB-cell depleting therapies may lead to protracted disease and prolonged viral shedding in individuals infected with SARS-CoV-2. Viral persistence in the setting of immunosuppression raises concern for viral evolution.\n\nMethodsAmplification of sub-genomic transcripts for the E gene (sgE) was done on nasopharyngeal samples over the course of 355 days in a patient infected with SARS-CoV-2 who had previously undergone CAR T cell therapy and had persistently positive SARS-CoV-2 nasopharyngeal swabs. Whole genome sequencing was performed on samples from the patients original presentation and 10 months later.\n\nResultsOver the course of almost a year, the virus accumulated a unique in-frame deletion in the amino-terminal domain of the spike protein, and complete deletion of ORF7b and ORF8, the first report of its kind in an immunocompromised patient. Also, minority variants that were identified in the early samples--reflecting the heterogeneity of the initial infection--were found to be fixed late in the infection. Remdesivir and high-titer convalescent plasma treatment were given, and the infection was eventually cleared after 335 days of infection.\n\nConclusionsThe unique viral mutations found in this study highlight the importance of analyzing viral evolution in protracted SARS-CoV-2 infection, especially in immunosuppressed hosts, and the implication of these mutations in the emergence of viral variants.\n\nSummaryWe report an immunocompromised patient with persistent symptomatic SARS-CoV-2 infection for 335 days. During this time, the virus accumulated a unique in-frame deletion in the spike, and a complete deletion of ORF7b and ORF8 which is the first report of its kind in an immunocompromised patient.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.02.21264415", + "rel_abs": "The implementation of monoclonal antibody therapeutics during the COVID19 pandemic has altered the selective pressures encountered by SARS-CoV-2, raising the possibility of selection for variants resistant to one or more monoclonal antibodies and subsequent transmission into the wider population. Early studies indicated that monoclonal antibody treatment in immunocompromised individuals could result in within-host viral evolution preferentially affecting epitopes recognized by these antibodies, although whether this signifies a real risk of transmissible antibody resistant virus is unclear.\n\nIn this study we have taken advantage of a regional SARS-CoV-2 genomic surveillance program encompassing regions in Wisconsin, Minnesota and Iowa to monitor the introduction or de novo emergence of SARS-Cov-2 lineages with clinically relevant variants. Here we describe a newly acquired E484K mutation in the SARS-CoV-2 spike protein detected within the B.1.311 lineage. Multiple individuals in two related households were infected. The timing and patterns of subsequent spread were consistent with de novo emergence of this E484K variant in the initially affected individual who had been treated with bamlanivimab monotherapy. The subsequent transmission to close contacts occurred several days after the resolution of symptoms and the end of this patients quarantine period. Our study suggests that the selective pressures introduced by the now widespread administration of these antibodies may warrant increased genomic surveillance to identify and mitigate spread of therapy-induced variants.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Veronique Nussenblatt", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Allison Roder", - "author_inst": "National Institute of Allergy and Infectious Diseases" - }, - { - "author_name": "Sanchita Das", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Emmie de Wit", - "author_inst": "NIAID, NIH" - }, - { - "author_name": "Jung-Ho Youn", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Stephanie Banakis", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Alexandra Muchegian", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Christopher Mederos", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Wei Wang", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Matt Chung", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Lizette Perez-Perez", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Tara Palmore", - "author_inst": "National Institutes of Health" - }, - { - "author_name": "Jennifer Brudno", - "author_inst": "National Cancer Institute" + "author_name": "Arick P Sabin", + "author_inst": "Gundersen Health System" }, { - "author_name": "James Kochenderfer", - "author_inst": "National Cancer Institute" + "author_name": "Craig S Richmond", + "author_inst": "Gundersen Medical Foundation" }, { - "author_name": "Elodie Ghedin", - "author_inst": "National Institute of Allergy and Infectious Diseases" + "author_name": "Paraic A Kenny", + "author_inst": "Gundersen Medical Foundation" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -578509,29 +578148,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.10.02.21264454", - "rel_title": "COVID-19 Vaccine: Newspaper Coverage of the side effects of the vaccine in Nigeria", + "rel_doi": "10.1101/2021.10.02.21264456", + "rel_title": "Using conditional inference to quantify interaction effects of socio-demographic covariates of US COVID-19 vaccine hesitancy", "rel_date": "2021-10-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.02.21264454", - "rel_abs": "BackgroundCOVID-19 Vaccine hesitancy is increasing globally, and this threatens the worlds ability to bring the pandemic under control. The way the media reports on the vaccine may influence or affect how the population perceive the safety and efficacy of the vaccine.\n\nMethodsThe aim of this study was to determine how newspapers in Nigeria report stories about the vaccine and the side effects of the vaccine amidst the growing fear on the safety of the vaccine. A total of 4 national daily newspapers were randomly selected for the study. These are Leadership, Guardian, Nation and Punch newspapers. The study was anchored on agenda setting theory. Quantitative content analysis research was used for the study. The duration of the study was the day the vaccine was introduced in Nigeria: March 1st, 2021 to July 31st, 2021. An Excel sheet served as the instrument for data collection and analysis done using SPSS version 25 with the level of significance predetermined at a p-value <0.05.\n\nResultsKey findings from this research were: Government officials and technical experts were predominantly used by the newspapers as the source of their information. There was a mixed reporting of vaccine side effects with a significant difference between those newspaper publications that reported vaccine side effects and those that didnt. Amongst those that reported side effects, there was also a significant difference between those that communicated how and where to report the side effects as against those that didnt.\n\nConclusionAs part of the effort to curtail vaccine hesitancy, a continuous improvement in communicating the vaccine efficacy and safety is needed.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.10.02.21264456", + "rel_abs": "COVID-19 vaccine hesitancy has become a major issue in the U.S. as vaccine supply has outstripped demand and vaccination rates slow down. At least one recent global survey has sought to study the covariates of vaccine acceptance, but an inferential model that makes simultaneous use of several socio-demographic variables has been lacking. In this article, we present such a model using US-based survey data collected by Gallup. Our study agrees with the global survey results in some respects, but is also found to exhibit significant differences. For example, women and people aged between 25-54 were found to be more vaccine hesitant. Our conditional inference tree model suggests that trust in government, age and ethnicity are the most important covariates for predicting vaccine hesitancy, and can interact in ways that make them useful for communication-based outreach, especially if conjoined with census data. In particular, we found that the most vaccine hesitant individuals were those who identified as Black Republicans with a high school (or lower) education and lower income levels, who were involuntarily unemployed and trusted in the Trump administration.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Kehinde Victor Soyemi", - "author_inst": "GlaxoSmithKline Pharrmaceuticals" - }, - { - "author_name": "Olagoke A Ewedairo", - "author_inst": "Medical Affairs, Global Public Health, Johnson and Johnson Pharmaceutical" + "author_name": "Ke Shen", + "author_inst": "University of Southern California" }, { - "author_name": "Charles Oluwatemitope Olomofe", - "author_inst": "College of Public Health, East Tennessee State University, Johnson City, United States" + "author_name": "Mayank Kejriwal", + "author_inst": "University of Southern California" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -580423,79 +580058,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.29.21264199", - "rel_title": "Effectiveness of mRNA-1273 against Delta, Mu, and other emerging variants", + "rel_doi": "10.1101/2021.09.30.21264356", + "rel_title": "Modelling of COVID-19 pandemic vis-a-vis some socioeconomic factors", "rel_date": "2021-10-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.29.21264199", - "rel_abs": "BackgroundReal-world studies have found high vaccine effectiveness (VE) of mRNA-based COVID-19 vaccines, but reduced VE against the Delta variant and waning protection have been reported, with few studies examining mRNA-1273 variant-specific VE.\n\nMethodsWe conducted a test-negative case-control study at Kaiser Permanente Southern California. Whole genome sequencing was conducted for SARS-CoV-2 positive specimens collected from 3/1/2021 to 7/27/2021. Test-positive cases were matched 1:5 to test-negative controls on age, sex, race/ethnicity, and specimen collection date. Outcomes included SARS-CoV-2 infection and hospitalization. Exposures were 2 doses or 1 dose of mRNA-1273 [≥]14 days prior to specimen collection versus no COVID-19 vaccination. Conditional logistic regression was used to compare odds of vaccination among cases versus controls, adjusting for confounders. VE was calculated as (1-odds ratio)x100%.\n\nResultsThe study included 8,153 cases and their matched controls. Two-dose VE (95% confidence interval) was 86.7% (84.3-88.7%) against Delta infection, 98.4% (96.9-99.1%) against Alpha, 90.4% (73.9-96.5%) against Mu, 96-98% against other identified variants, and 79.9% (76.9-82.5%) against unidentified variants. VE against Delta declined from 94.1% (90.5-96.3%) 14-60 days after vaccination to 80.0% (70.2-86.6%) 151-180 days after vaccination. Waning was less pronounced for non-Delta variants. VE against Delta was lower among individuals aged [≥]65 years (75.2% [59.6-84.8%]) than those aged 18-64 years (87.9% [85.5-89.9%]). VE against Delta hospitalization was 97.6% (92.8-99.2%). One-dose VE was 77.0% (60.7-86.5%) against Delta infection.\n\nConclusionsTwo doses of mRNA-1273 were highly effective against all SARS-CoV-2 variants. However, VE against Delta moderately declined with increasing time since vaccination.\n\nTrial Registration NumberNot applicable\n\nFundingModerna Inc.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.30.21264356", + "rel_abs": "The impacts of COVID-19 outbreak on socio-economic status of countries across the globe cannot be overemphasized as we examine the role it played in various countries. A lot of people were out of jobs, many households were careful of their spending and a greater social fracture of the population in fourteen different countries has emerged. We considered periods of infection spread during the first and second wave in Organization for Economic Co-operation and Development (OECD) countries and countries in Africa, that is developed and developing countries alongside their social-economic data. We established a mathematical and statistical relationship between Theil and Gini index, then we studied the relationship between the data from epidemiology and socio-economic determinants using several machine learning and deep learning methods. High correlations were observed between some of the socio-economic and epidemiologic parameters and we predicted three of the socio-economic variables in order to validate our results. These result shows a sharp difference between the first and second wave of the pandemic confirming the real dynamics of the spread of the outbreak in several countries and ways by which it was mitigated.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Katia Bruxvoort", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "Lina S. Sy", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Lei Qian", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Bradley K. Ackerson", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Yi Luo", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Gina S. Lee", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Yun Tian", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Ana Florea", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Michael Aragones", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Julia E. Tubert", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Harpreet S. Takhar", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Jennifer H. Ku", - "author_inst": "Kaiser Permanente Southern California" - }, - { - "author_name": "Yamuna D. Paila", - "author_inst": "Moderna Inc." + "author_name": "Kayode Oshinubi", + "author_inst": "University Grenoble Alpes" }, { - "author_name": "Carla A. Talarico", - "author_inst": "Moderna Inc." + "author_name": "Mustapha rachdi", + "author_inst": "University Grenoble Alpes" }, { - "author_name": "Hung Fu Tseng", - "author_inst": "Kaiser Permanente Southern California" + "author_name": "Jacques Demongeot", + "author_inst": "University Grenoble Alpes" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.09.29.21264325", @@ -582173,99 +581760,95 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.09.30.462449", - "rel_title": "Pyronaridine Protects Against SARS-CoV-2 in Mouse", + "rel_doi": "10.1101/2021.09.30.462488", + "rel_title": "Durability of immune responses to the BNT162b2 mRNA vaccine", "rel_date": "2021-09-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.30.462449", - "rel_abs": "There are currently relatively few small-molecule antiviral drugs that are either approved or emergency approved for use against SARS-CoV-2. One of these is remdesivir, which was originally repurposed from its use against Ebola and functions by causing early RNA chain termination. We used this as justification to evaluate three molecules we had previously identified computationally with antiviral activity against Ebola and Marburg. Out of these we previously identified pyronaridine, which inhibited the SARS-CoV-2 replication in A549-ACE2 cells. Herein, the in vivo efficacy of pyronaridine has now been assessed in a K18-hACE transgenic mouse model of COVID-19. Pyronaridine treatment demonstrated a statistically significant reduction of viral load in the lungs of SARS CoV-2 infected mice. Furthermore, the pyronaridine treated group reduced lung pathology, which was also associated with significant reduction in the levels of pro-inflammatory cytokines/chemokine and cell infiltration. Notably, pyronaridine inhibited the viral PLpro activity in vitro (IC50 of 1.8 {micro}M) without any effect on Mpro, indicating a possible molecular mechanism involved in its ability to inhibit SARS-CoV-2 replication. Interestingly, pyronaridine also selectively inhibits the host kinase CAMK1 (IC50 of 2.4 {micro}M). We have also generated several pyronaridine analogs to assist in understanding the structure activity relationship for PLpro inhibition. Our results indicate that pyronaridine is a potential therapeutic candidate for COVID-19.\n\nOne sentence summaryThere is currently intense interest in discovering small molecules with direct antiviral activity against the severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). Pyronaridine, an antiviral drug with in vitro activity against Ebola, Marburg and SARS-CoV-2 has now statistically significantly reduced the viral load in mice along with IL-6, TNF-, and IFN-{beta} ultimately demonstrating a protective effect against lung damage by infection to provide a new potential treatment for testing clinically.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.30.462488", + "rel_abs": "The development of the highly efficacious mRNA vaccines in less than a year since the emergence of SARS-CoV-2 represents a landmark in vaccinology. However, reports of waning vaccine efficacy, coupled with the emergence of variants of concern that are resistant to antibody neutralization, have raised concerns about the potential lack of durability of immunity to vaccination. We recently reported findings from a comprehensive analysis of innate and adaptive immune responses in 56 healthy volunteers who received two doses of the BNT162b2 vaccination. Here, we analyzed antibody responses to the homologous Wu strain as well as several variants of concern, including the emerging Mu (B.1.621) variant, and T cell responses in a subset of these volunteers at six months (day 210 post-primary vaccination) after the second dose. Our data demonstrate a substantial waning of antibody responses and T cell immunity to SARS-CoV-2 and its variants, at 6 months following the second immunization with the BNT162b2 vaccine. Notably, a significant proportion of vaccinees have neutralizing titers below the detection limit, and suggest a 3rd booster immunization might be warranted to enhance the antibody titers and T cell responses.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Ana C. Puhl", - "author_inst": "Collaborations Pharmaceuticals" - }, - { - "author_name": "Giovanni F. Gomes", - "author_inst": "Center for Research in Inflammatory Diseases (CRID), Ribeirao Preto Medical School, University of Sao Paulo" + "author_name": "Mehul Suthar", + "author_inst": "Emory University" }, { - "author_name": "Samara Damasceno", - "author_inst": "Center for Research in Inflammatory Diseases (CRID), Ribeirao Preto Medical School, University of Sao Paulo" + "author_name": "Prabhu S Arunachalam", + "author_inst": "Stanford University" }, { - "author_name": "Andre Schutzer de Godoy", - "author_inst": "University of Sao Paulo" + "author_name": "Mengyun Hu", + "author_inst": "Stanford University" }, { - "author_name": "Gabriela D. Noske", - "author_inst": "University of Sao Paulo" + "author_name": "Noah Reis", + "author_inst": "Stanford University" }, { - "author_name": "Aline M. Nakamura", - "author_inst": "University of Sao Paulo" + "author_name": "Meera Trisal", + "author_inst": "Stanford University" }, { - "author_name": "Victor O. Gawrijuk", - "author_inst": "University of Sao Paulo" + "author_name": "Olivia Raeber", + "author_inst": "Stanford University" }, { - "author_name": "Rafaela S. Fernandes", - "author_inst": "University of Sao Paulo" + "author_name": "Sharon Chinthrajah", + "author_inst": "Stanford University" }, { - "author_name": "Natalia Monakhova", - "author_inst": "Research Center of Biotechnology RAS, 119071 Moscow, Russia." + "author_name": "Meredith E Davis-Gardner", + "author_inst": "Emory University" }, { - "author_name": "Olga Riabova", - "author_inst": "Federal Research Center Fundamentals of Biotechnology Russian Academy of Science" + "author_name": "Kelly Manning", + "author_inst": "Emory University" }, { - "author_name": "Thomas R Lane", - "author_inst": "Collaborations Pharmaceuticals Inc." + "author_name": "Prakriti Mudvari", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Vadim Makarov", - "author_inst": "Federal Research Center Fundamentals of Biotechnology Russian Academy of Science" + "author_name": "Sucheta Godbole", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA" }, { - "author_name": "Flavio P. Veras", - "author_inst": "Center for Research in Inflammatory Diseases (CRID), Ribeirao Preto Medical School, University of Sao Paulo" + "author_name": "Eli Boritz", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Sabrina S. Batah", - "author_inst": "Ribeirao Preto Medical School, University of Sao Paulo" + "author_name": "Amy R Henry", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, USA" }, { - "author_name": "Alexandre T. Fabro", - "author_inst": "Department of Pathology and Legal Medicine, Ribeirao Preto Medical School, University of Sao Paulo" + "author_name": "Daniel Douek", + "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Glaucius Oliva", - "author_inst": "University of Sao Paulo" + "author_name": "Kari Nadeau", + "author_inst": "Stanford University" }, { - "author_name": "Fernando Cunha", - "author_inst": "Universidade de Sao Paulo Campus de Ribeirao Preto" + "author_name": "Yoshihiro Kawaoka", + "author_inst": "University of Wisconsin" }, { - "author_name": "Jose C. Alves-Filho", - "author_inst": "Center for Research in Inflammatory Diseases (CRID), Ribeirao Preto Medical School, University of Sao Paulo" + "author_name": "Veronika I Zarnitsyna", + "author_inst": "Emory University School of Medicine" }, { - "author_name": "Thiago M. Cunha", - "author_inst": "Center for Research in Inflammatory Diseases (CRID), Ribeirao Preto Medical School, University of Sao Paulo" + "author_name": "Bali Pulendran", + "author_inst": "Stanford University" }, { - "author_name": "Sean Ekins", - "author_inst": "Collaborations Pharmaceuticals, Inc." + "author_name": "Peter Halfmann", + "author_inst": "University of Wisconsin" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "pharmacology and toxicology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.09.28.462156", @@ -584379,109 +583962,205 @@ "category": "hiv aids" }, { - "rel_doi": "10.1101/2021.09.28.21264250", - "rel_title": "Reduced antibody activity against SARS-CoV-2 B.1.617.2 Delta virus in serum of mRNA-vaccinated patients receiving TNF-alpha inhibitors", + "rel_doi": "10.1101/2021.09.28.21263911", + "rel_title": "A MUC5B gene polymorphism, rs35705950-T, confers protective effects in COVID-19 infection", "rel_date": "2021-09-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.28.21264250", - "rel_abs": "Although vaccines effectively prevent COVID-19 in healthy individuals, they appear less immunogenic in individuals with chronic inflammatory diseases (CID) and/or under chronic immunosuppression, and there is uncertainty of their activity against emerging variants of concern in this population. Here, we assessed a cohort of 74 CID patients treated as monotherapy with chronic immunosuppressive drugs for functional antibody responses in serum against historical and variant SARS-CoV-2 viruses after immunization with Pfizer mRNA BNT162b2 vaccine. Longitudinal analysis showed the greatest reductions in neutralizing antibodies and Fc effector function capacity in individuals treated with TNF- inhibitors, and this pattern appeared worse against the B.1.617.2 Delta virus. Within five months of vaccination, serum neutralizing titers of the majority of CID patients fell below the presumed threshold correlate for antibody-mediated protection. Thus, further vaccine boosting or administration of long-acting prophylaxis (e.g., monoclonal antibodies) likely will be required to prevent SARS-CoV-2 infection in this susceptible population.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.28.21263911", + "rel_abs": "RationaleA common MUC5B gene polymorphism, rs35705950-T, is associated with idiopathic pulmonary fibrosis, but its role in the SARS-CoV-2 infection and disease severity is unclear.\n\nObjectivesTo assess whether rs35705950-T confers differential risk for clinical outcomes associated with COVID-19 infection among participants in the Million Veteran Program (MVP) and COVID-19 Host Genetics Initiative (HGI).\n\nMethodsMVP participants were examined for an association between the incidence or severity of COVID-19 and the presence of a MUC5B rs35705950-T allele. Comorbidities and clinical events were extracted from the electronic health records (EHR). The analysis was performed within each ancestry group in the MVP, adjusting for sex, age, age2, and first twenty principal components followed by a trans-ethnic meta-analysis. We then pursued replication and performed a meta-analysis with the trans-ethnic summary statistics from the HGI. A phenome-wide association study (PheWAS) of the rs35705950-T was conducted to explore associated pathophysiologic conditions.\n\nMeasurements and Main ResultsA COVID-19 severity scale was modified from the World Health Organization criteria, and phenotypes derived from the International Classification of Disease-9/10 were extracted from EHR. Presence of rs35705950-T was associated with fewer hospitalizations (Ncases=25353, Ncontrols=631,024; OR=0.86 [0.80-0.93], p=7.4 x 10-5) in trans-ethnic meta-analysis within MVP and joint meta-analyses with the HGI (N=1641311; OR=0.89 [0.85-0.93], p =1.9 x 10-6). Moreover, individuals of European Ancestry with at least one copy of rs35705950-T had fewer post-COVID-19 pneumonia events (OR=0.85 [0.76-0.96], p =0.008). PheWAS exclusively revealed pulmonary involvement.\n\nConclusionsThe MUC5B variant rs35705950-T is protective in COVID-19 infection.", + "rel_num_authors": 47, "rel_authors": [ { - "author_name": "Rita E Chen", - "author_inst": "Washington University School of Medicine" + "author_name": "Anurag Verma", + "author_inst": "Corporal Michael Crescenz VA Medical Center" }, { - "author_name": "Matthew J Gorman", - "author_inst": "Ragon Institute" + "author_name": "Jessica Minnier", + "author_inst": "Oregon Health & Science University" }, { - "author_name": "Daniel Y Zhu", - "author_inst": "MIT" + "author_name": "Jennifer E Huffman", + "author_inst": "VA Boston Healthcare System" }, { - "author_name": "Juan Manuel Carreno", - "author_inst": "Icahn School of Medicine" + "author_name": "Emily S Wan", + "author_inst": "VA Boston Healthcare System" }, { - "author_name": "Dansu Yuan", - "author_inst": "Ragon Institute" + "author_name": "Lina Gao", + "author_inst": "Oregon Health & Science University" }, { - "author_name": "Laura A VanBlargan", - "author_inst": "Washington University" + "author_name": "Jacob Joseph", + "author_inst": "VA Boston Healthcare System" }, { - "author_name": "Samantha Burdess", - "author_inst": "Washington University" + "author_name": "Yuk-Lam Ho", + "author_inst": "VA Boston Healthcare System" }, { - "author_name": "Douglas A Lauffenburger", - "author_inst": "MIT" + "author_name": "Wen-Chih Wu", + "author_inst": "Providence VA Healthcare System" }, { - "author_name": "Wooseob Kim", - "author_inst": "Washington University" + "author_name": "Kelly Cho", + "author_inst": "VA Boston Healthcare System" }, { - "author_name": "Jackson S Turner", - "author_inst": "Washington University" + "author_name": "Bryan R Gorman", + "author_inst": "VA Boston Healthcare System" }, { - "author_name": "Lindsay Droit", - "author_inst": "Washington University" + "author_name": "Nallakkandi Rajeevan", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Scott A Handley", - "author_inst": "Washington University" + "author_name": "Saiju Pyarajan", + "author_inst": "VA Boston Healthcare System" }, { - "author_name": "Salim Chahin", - "author_inst": "Washington University" + "author_name": "Helene Garcon", + "author_inst": "VA Boston Healthcare System" }, { - "author_name": "Parakkal Deepak", - "author_inst": "Washington University in St Louis School of Medicine" + "author_name": "James B Meigs", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Jane O'Halloran", - "author_inst": "Washington University in St. Louis School of Medicine" + "author_name": "Yan V Sun", + "author_inst": "Emory University School of Public Health" }, { - "author_name": "Michael Paley", - "author_inst": "Washington University" + "author_name": "Peter D Reaven", + "author_inst": "Phoenix VA Healthcare System" }, { - "author_name": "Rachel Presti", - "author_inst": "Wash U" + "author_name": "John E McGeary", + "author_inst": "Providence VA Medical Center" }, { - "author_name": "Gregory F Wu", - "author_inst": "Washington University" + "author_name": "Ayako Suzuki", + "author_inst": "Durham VA Medical Center" }, { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Joel Gelernter", + "author_inst": "Yale Univ. School of Medicine" }, { - "author_name": "Galit Alter", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Julie A Lynch", + "author_inst": "VA Salt Lake City Health Care System" }, { - "author_name": "Ali Ellebedy", - "author_inst": "Washington University School of Medicine" + "author_name": "Jeffrey M Petersen", + "author_inst": "Corporal Michael Crescenz VA Medical Center" }, { - "author_name": "Alfred Hyoungju Kim", - "author_inst": "Washington University School of Medicine" + "author_name": "Seyedeh Maryam Zekavat", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Michael S Diamond", - "author_inst": "Washington University School of Medicine" + "author_name": "Pradeep Natarajan", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Cecelia J Madison", + "author_inst": "Portland VA Medical Center" + }, + { + "author_name": "Sharvari Dalal", + "author_inst": "Corporal Michael J Crescenz VA Medical Center" + }, + { + "author_name": "Darshana N Jhala", + "author_inst": "Corporal Michael Crescenz VA Medical Center, Philadelphia, PA" + }, + { + "author_name": "Mehrdad Arjomandi", + "author_inst": "San Francisco VA Healthcare System; University of California San Francisco" + }, + { + "author_name": "Elise Gatsby", + "author_inst": "VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System" + }, + { + "author_name": "Kristine E Lynch", + "author_inst": "VA Informatics and Computing Infrastructure (VINCI), VA Salt Lake City Healthcare System" + }, + { + "author_name": "Robert A Bonomo", + "author_inst": "Case Western Reserve University" + }, + { + "author_name": "Mat Freiberg", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Gita A Pathak", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Jin J Zhou", + "author_inst": "University of California, Los Angeles" + }, + { + "author_name": "Curtis J Donskey", + "author_inst": "Louis Stokes Cleveland VA and Case Western Reserve University" + }, + { + "author_name": "Ravi K Madduri", + "author_inst": "Argonne National Laboratory" + }, + { + "author_name": "Quinn S Wells", + "author_inst": "Vanderbilt University Medical Center" + }, + { + "author_name": "Rose DL Huang", + "author_inst": "VA Boston Healthcare System" + }, + { + "author_name": "Renato Polimanti", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Kyong-Mi Chang", + "author_inst": "Corporal Michael J Crescenz VA Medical Center" + }, + { + "author_name": "Katherine P Liao", + "author_inst": "VA Boston Healthcare System" + }, + { + "author_name": "Philip S Tsao", + "author_inst": "VA Palo Alto Health Care System" + }, + { + "author_name": "Peter W.F. Wilson", + "author_inst": "Atlanta VA Health Care System" + }, + { + "author_name": "Christopher J O'Donnell", + "author_inst": "VA Boston Healthcare System" + }, + { + "author_name": "John M Gaziano", + "author_inst": "VA Boston Healthcare System" + }, + { + "author_name": "Richard L Hauger", + "author_inst": "VA San Diego Healthcare System" + }, + { + "author_name": "Sudha K. Iyengar", + "author_inst": "Case Western Reserve University" + }, + { + "author_name": "Shiuh-Wen Luoh", + "author_inst": "VA Portland Health Care System" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -586165,29 +585844,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.09.25.21264106", - "rel_title": "Functional Data Analysis: Transition from Daily Observation of COVID-19 Prevalence in France to Functional Curves", + "rel_doi": "10.1101/2021.09.25.21264118", + "rel_title": "Modeling of COVID-19 Transmission Dynamics on US Population: Inter-transfer Infection in Age Groups, Mutant Variants, and Vaccination Strategies", "rel_date": "2021-09-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.25.21264106", - "rel_abs": "In this paper we use the technique of functional data analysis to model daily hospitalized, deceased, ICU cases and return home patient numbers along the COVID-19 outbreak, considered as functional data across different departments in France while our response variables are numbers of vaccinations, deaths, infected, recovered and tests in France. These sets of data were considered before and after vaccination started in France. We used some smoothing techniques to smooth our data set, then analysis based on functional principal components method was performed, clustering using k-means techniques was done to understand the dynamics of the pandemic in different French departments according to their geographical location on France map and we also performed canonical correlations analysis between variables. Finally, we made some predictions to assess the accuracy of the method using functional linear regression models.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.25.21264118", + "rel_abs": "The in-depth understanding of the dynamics of COVID-19 transmission among different age groups is of great interest for governments and health authorities so that strategies can be devised to reduce the pandemics detrimental effects. We developed the SIRDV-Virulence epidemiological model based on a population balance equation to study the effect of mutants of the virus and the effect of vaccination strategies on mitigating the transmission among the population in the United States. Based on the available data from the Centers for Disease Control and Prevention (CDC), we obtain the key parameters governing the dynamic evolution of the spread of the COVID-19 pandemic. In the context studied, the results show that a large fraction of infected cases comes from the adult and children populations in the presence of a mutant variant of COVID-19 with high infection rates. We further investigate the optimum vaccine distribution strategy among different age groups. Given the current situation in the United States, the results show that prioritizing children and adult vaccinations over that of seniors can contain the spread of the active cases, thereby preventing the healthcare system from being overwhelmed and minimizing subsequent deaths. The model suggests that the only option to curb the effects of this pandemic is to reduce the population of unvaccinated individuals. A higher fraction of Anti/Non-vaxxers can lead to the resurgence of the pandemic.\n\nAuthor summaryThe changing dynamics of the COVID-19 pandemic are primarily due to the mutations of the SARS-CoV-2 virus. It is often seen that these mutants not only have a higher infection rate but also evade the presently administered vaccines. To consider the fact that different age population groups are affected to varied extent by these mutants, we build a mathematical model to account for the inter-transfer infection among age groups, which can predict the overall COVID-19 transmission in the United States. The parameter quantification of our mathematical model is based on the public data for infected cases, deaths and vaccinated from the Centers for Disease Control and Prevention (CDC). Additionally, our study shows that the vaccine distribution strategies should be developed with a priority given to the most infected age groups in order to curb the total infected and death cases. We also show how the Anti/Non-vaxxers can be a potential reason for resurgence of the pandemic. These results are of immediate practical application in determining future vaccine distribution regarding to the pandemic and ensuring the health care system is ready to deal with the worst-case scenario with a very high infection rate.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Kayode Oshinubi", - "author_inst": "University Grenoble Alpes" + "author_name": "Jyotirmoy Roy", + "author_inst": "Department of Chemical Engineering, Indian Institute of Technology, Powai, Mumbai 400076" }, { - "author_name": "Firas Ibrahim", - "author_inst": "University Grenoble Alpes" + "author_name": "Samuel Heath", + "author_inst": "Charles D. Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN 47907; Current Address: Department of Mechanical Engineering, Massachu" }, { - "author_name": "Mustapha Rachdi", - "author_inst": "University Grenoble Alpes" + "author_name": "Doraiswami Ramkrishna", + "author_inst": "Charles D. Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN 47907" }, { - "author_name": "Jacques Demongeot", - "author_inst": "University Grenoble Alpes" + "author_name": "Shiyan Wang", + "author_inst": "Charles D. Davidson School of Chemical Engineering, Purdue University, West Lafayette, IN 47907" } ], "version": "1", @@ -587923,71 +587602,63 @@ "category": "ophthalmology" }, { - "rel_doi": "10.1101/2021.09.23.21264036", - "rel_title": "Diagnostic Yield of Screening for SARS-CoV-2 among Patients Admitted for Alternate Diagnoses", + "rel_doi": "10.1101/2021.09.23.21263715", + "rel_title": "Prediction of long-term kinetics of vaccine-elicited neutralizing antibody and time-varying vaccine-specific efficacy against the SARS-CoV-2 Delta variant by clinical endpoint", "rel_date": "2021-09-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.23.21264036", - "rel_abs": "ObjectivesTo determine the diagnostic yield of screening patients for SARS-CoV-2 who were admitted with a diagnosis unrelated to COVID-19, and identify risk factors for positive tests.\n\nDesignCohort from the Canadian COVID-19 Emergency Department Rapid Response Network (CCEDRRN) registry\n\nSetting30 acute care hospitals across Canada\n\nParticipantsPatients hospitalized for non-COVID-19 related diagnoses who were tested for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between March 1, and December 29, 2020\n\nMain outcomePositive nucleic acid amplification test (NAAT) for SARS-CoV-2\n\nOutcome measureDiagnostic yield\n\nResultsWe enrolled 15,690 consecutive eligible adults who were admitted to hospital without clinically suspected COVID-19. Among these patients, 122 tested positive for COVID-19, resulting in a diagnostic yield of 0.8% (95% CI 0.64% - 0.92%). Factors associated with a positive test included presence of a fever, being a healthcare worker, having a positive household contact or institutional exposure, and living in an area with higher 7-day average incident COVID-19 cases.\n\nConclusionsUniversal screening of hospitalized patients for COVID-19 across two pandemic waves had a low diagnostic yield and should be informed by individual-level risk assessment in addition to regional COVID-19 prevalence.\n\nTrial registrationNCT04702945\n\nSUMMARY BOXESSection 1: Universal screening of admitted patients for SARS-CoV-2 was implemented in many hospitals at the beginning of the pandemic. The Infections Diseases Society of America (IDSA) recommended avoiding universal screening of asymptomatic hospitalized patients in areas and times of low-COVID prevalence (defined as <2% prevalence) with very low certainty of evidence, based on studies of COVID-19 prevalence among asymptomatic individuals in the community.\n\nSection 2: This study supports IDSA recommendations to avoid universal screening for COVID-19 in times and areas of low COVID prevalence and identifies patient-level risk factors strongly associated with positive testing that should be considered for screening.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.23.21263715", + "rel_abs": "Evidence on vaccine-specific protection over time and boosting impact against the Delta variant across different clinical endpoints and age groups is urgently needed. To address this, we used a previously published model, combined with neutralization data for four vaccines - mRNA-1273, BNT162b2, NVX-CoV2373, and CoronaVac - to evaluate long-term dynamics of neutralizing antibody and to predict time-varying efficacy against the Delta variant by specific vaccine, age group, and clinical severity. We found that booster vaccination produces higher neutralization titers compared with titers observed following primary-series vaccination for all vaccines studied. We estimate the efficacies of mRNA-1273 and BNT162b2 against Delta variant infection to be 63.5% (95%CI: 51.4-67.3%) and 78.4% (95%CI: 72.2-83.5%), respectively, 14-30 days after the second dose, and that efficacies decreased to 36.0% (95%CI: 24.1-58.0%) and 38.5% (95%CI: 28.7-49.1%) 6-8 months later. After administration of booster doses, efficacies against the Delta variant would be 97.0% (95%CI: 96.4-98.5%) and 97.2% (95.7-98.1%). All four vaccines are predicted to provide good protection against severe illness from the Delta variant after both primary and booster vaccination. Long-term monitoring and surveillance of antibody dynamics and vaccine protection, as well as further validation of neutralizing antibody or other markers that can serve as correlates of protection against SARS-CoV-2 and its variants are needed to inform COVID-19 pandemic preparedness.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Phil Davis", - "author_inst": "Department of Emergency Medicine, University of Saskatchewan, Saskatoon, SK, Canada" - }, - { - "author_name": "Rhonda J Rosychuk", - "author_inst": "Department of Pediatrics, University of Alberta, Edmonton, AB, Canada" - }, - { - "author_name": "Jeffrey P Hau", - "author_inst": "Centre for Clinical Epidemiology and Evaluation, Vancouver Coastal Health Research Institute, 828 W 10th Ave, Vancouver BC V5Z1M9" + "author_name": "Xinhua Chen", + "author_inst": "Fudan University" }, { - "author_name": "Ivy Cheng", - "author_inst": "Department of Emergency Medicine, Sunnybrook Health Sciences Center" + "author_name": "Wei Wang", + "author_inst": "Fudan University" }, { - "author_name": "Andrew D McRae", - "author_inst": "Department of Emergency Medicine, University of Calgary" + "author_name": "Xinghui Chen", + "author_inst": "Fudan University" }, { - "author_name": "Raoul Daoust", - "author_inst": "D\u00e9partement M\u00e9decine de Famille et M\u00e9decine d'Urgence, Facult\u00e9 de M\u00e9decine, Universit\u00e9 de Montr\u00e9al, Department of Emergency Medicine, Research Centre, CIUSSS-No" + "author_name": "Qianhui Wu", + "author_inst": "Fudan University" }, { - "author_name": "Eddy Lang", - "author_inst": "Department of Emergency Medicine, University of Calgary" + "author_name": "Ruijia Sun", + "author_inst": "Fudan University" }, { - "author_name": "Joel Turner", - "author_inst": "Department of Emergency Medicine, McGill University, Montreal, QC" + "author_name": "Shijia Ge", + "author_inst": "Fudan University" }, { - "author_name": "Jaspreet Khangura", - "author_inst": "Department of Emergency Medicine, University of British Columbia" + "author_name": "Nan Zheng", + "author_inst": "Fudan University" }, { - "author_name": "Patrick T Fok", - "author_inst": "Division of EMS, Department of Emergency Medicine, Dalhousie University" + "author_name": "Wanying Lu", + "author_inst": "Fudan University" }, { - "author_name": "Maja Stachura", - "author_inst": "Department of Emergency Medicine, University of British Columbia" + "author_name": "Juan Yang", + "author_inst": "Fudan University" }, { - "author_name": "Baljeet Brar", - "author_inst": "Department of Emergency Medicine, University of British Columbia" + "author_name": "Lance Rodewald", + "author_inst": "National Immunization Programme, Chinese Center for Disease Control and Prevention, Beijing, China" }, { - "author_name": "Corinne M Hohl", - "author_inst": "Department of Emergency Medicine, Faculty of Medicine, University of British Columbia, 2775 Laurel St., Vancouver BC V5Z 1M9." + "author_name": "Hongjie Yu", + "author_inst": "Fudan University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.09.20.21263172", @@ -589905,27 +589576,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.26.461851", - "rel_title": "Cytotoxic T-cell-based vaccine against SARS-CoV2: a hybrid immunoinformatic approach", + "rel_doi": "10.1101/2021.09.25.461766", + "rel_title": "Deactivation of SARS-CoV-2 surrogate porcine epidemic diarrhea virus with electron beam irradiation under the cold chain transportation condition", "rel_date": "2021-09-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.26.461851", - "rel_abs": "This paper presents an alternative vaccination platform that provides long-term cellular immune protection mediated by cytotoxic T-cells. The immune response via cellular immunity creates superior resistance to viral mutations, which are currently the greatest threat to the global vaccination campaign. Furthermore, we also propose a safer, more facile and physiologically appropriate immunization method using either intra-nasal or oral administration. The underlying technology is an adaptation of synthetic long peptides (SLPs) previously used in cancer immunotherapy. SLPs comprising HLA class I and class II epitopes are used to stimulate antigen cross-presentation and canonical class II presentation by dendritic cells. The result is a cytotoxic T cell-mediated prompt and specific immune response against the virus-infected epithelia and a rapid and robust virus clearance. Peptides isolated from COVID-19 convalescent patients were screened for the best HLA population coverage and were tested for toxicity and allergenicity. 3D peptide folding followed by molecular docking studies provided positive results, suggesting a favourable antigen presentation.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.25.461766", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has prevailed all over the world and emerged as a significant public health emergency. The rapid outbreak of SARS-CoV-2 is largely due to its high transmission capacity. Studies implied that the cold chain logistics would be a potential route for the spread of SARS-CoV-2. The low temperature condition of the cold chain is conducive to survival and transmission of virus. Thus, the virus disinfection in cold chain should not be neglected for controlling COVID-19. However, due to the low temperature feature of the cold-chain, the virus disinfecting methods suitable in cold chain are limited. Here the high-energy electron beam irradiation is proposed to disinfect the SARS-CoV-2 in cold chain logistics. We evaluated the impact of high-energy electron beam irradiation on porcine epidemic diarrhea virus (PEDV), an enveloped virus surrogate for SARS-CoV-2, and explored the possible mechanism of the action of high-energy electron beam irradiation on PEDV. The irradiation dose of 10 kGy inactivated 98.1 % PEDV on the both top and bottom surfaces of various packaging materials under cold chain frozen condition. High-energy electron beam inactivated PEDV by inducing damages on viral genome or even capsid.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Alexandru Tirziu", - "author_inst": "\"Victor Babes\" University of Medicine and Pharmacy Timisoara" + "author_name": "Yan Liu", + "author_inst": "State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences" + }, + { + "author_name": "Yang Shao", + "author_inst": "Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences" }, { - "author_name": "Virgil Paunescu", - "author_inst": "OncoGen Association, Timisoara, Romania" + "author_name": "Lu Wang", + "author_inst": "State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences" + }, + { + "author_name": "Weilai Lu", + "author_inst": "State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences" + }, + { + "author_name": "Shihua Li", + "author_inst": "CAS Key Laboratory of Pathogenic Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences" + }, + { + "author_name": "Diandou Xu", + "author_inst": "Beijing Engineering Research Center of Radiographic Techniques and Equipment, Institute of High Energy Physics, Chinese Academy of Sciences" + }, + { + "author_name": "Yu Vincent Fu", + "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.09.26.461873", @@ -591835,43 +591526,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.09.21.21263457", - "rel_title": "Real-world Effectiveness of 2-dose SARS-CoV-2 Vaccination in Kidney Transplant Recipients", + "rel_doi": "10.1101/2021.09.19.21263799", + "rel_title": "Spatial simulation of COVID-19 new cases development", "rel_date": "2021-09-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.21.21263457", - "rel_abs": "The humoral response to two doses of SARS-CoV-2 (Covid-19) vaccine among transplant recipients is inferior to immunocompetent individuals.1 Data on the real-world effectiveness of vaccination in kidney transplant recipients [KTRs] are lacking. We performed a cohort study to investigate the impact of vaccination on Covid-19 infection and outcomes in our kidney transplant program.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.19.21263799", + "rel_abs": "The time dependent SIR model is extended to simulate infection across spatial boundaries. We used New Jersey data as an example to test the extended SIR model. Infection from neighboring counties are modelled by connectivity matrix where each pair of neighboring counties has an element in the connectivity matrix. The magnitude of this matrix element represents the degree to which the infected from one county can affect the susceptible in one of its neighboring counties. Simulated result from the extended spatial SIR model is compared with observed new COVID-19 cases measured in the 21 counties in New Jersey. The extended model has to solve 84 simulated functions simultaneously and the large number of parameters involved in the spatial SIR model are auto tuned using genetic algorithm.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Caitriona M. McEvoy", - "author_inst": "St. Michael's Hospital and Temerty Faculty of Medicine, University of Toronto" - }, - { - "author_name": "Anna Lee", - "author_inst": "Temerty Faculty of Medicine, University of Toronto" - }, - { - "author_name": "Paraish S. Misra", - "author_inst": "Temerty Faculty of Medicine, University of Toronto" - }, - { - "author_name": "Gerald Lebovic", - "author_inst": "Applied Health Research Centre, LKSKI, Unity Health Toronto" - }, - { - "author_name": "Ron Wald", - "author_inst": "St. Michael's Hospital and Temerty Faculty of Medicine, University of Toronto" + "author_name": "Isaac Chen", + "author_inst": "Kent School" }, { - "author_name": "Darren A. Yuen", - "author_inst": "St. Michael's Hospital and Temerty Faculty of Medicine, University of Toronto" + "author_name": "Fei Liu", + "author_inst": "NJ Science Academy" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "transplantation" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.09.21.21263886", @@ -593353,47 +593028,63 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2021.09.20.21263808", - "rel_title": "Human Milk Antibodies Elicited by BNT162b2 Vaccination Target have reduced activity against SARS-CoV-2 Variants of Concern", + "rel_doi": "10.1101/2021.09.20.21263838", + "rel_title": "Childhood Asthma and COVID-19: A Nested Case-Control Study", "rel_date": "2021-09-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.20.21263808", - "rel_abs": "We detected the presence of SARS-CoV-2 specific IgA against all major VOCs in milk out to 6 weeks after D2 of BNT162b2. These likely confer some protection to the breastfed infants, who are ineligible for vaccination and are at risk of severe COVID-19.\n\nHowever, we detected significantly reduced milk IgA binding to VOCs, including the globally dominant Delta variant, suggesting reduced protection for breastfeeding infants. Additionally, these antibodies were significantly reduced by as early as 4-6 weeks after D2.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.20.21263838", + "rel_abs": "BackgroundMost pediatric studies of asthma and COVID-19 to date have been ecological, which offer limited insight. We evaluated the association between asthma and COVID-19 at an individual level.\n\nMethodsUsing data from prospective clinical registries, we conducted a nested case-control study comparing three groups: children with COVID-19 and underlying asthma (\"A+C\" cases); children with COVID-19 without underlying disease (\"C+\" controls); and children with asthma without COVID-19 (\"A+\" controls).\n\nResultsThe cohort included 142 A+C cases, 1110 C+ controls, and 140 A+ controls. A+C cases were more likely than C+ controls to present with dyspnea and wheezing, to receive pharmacologic treatment including systemic steroids (all p<0.01), and to be hospitalized (4.9% vs 1.7%, p=0.01). In the adjusted analysis, A+C cases were nearly 4 times more likely to be hospitalized than C+ controls (adjusted OR=3.95 [95%CI=1.4-10.9]); however, length of stay and respiratory support level did not differ between groups. Among A+C cases, 8.5% presented with an asthma exacerbation and another 6.3% developed acute exacerbation symptoms shortly after testing positive for SARS-CoV-2. Compared to historic A+ controls, A+C cases had less severe asthma, were less likely to be on controller medications, and had better asthma symptom control (all p<0.01).\n\nConclusionsIn our cohort, asthma was a risk factor for hospitalization in children with COVID-19, but not for worse COVID-19 outcomes. SARS-CoV-2 does not seem to be a strong trigger for pediatric asthma exacerbations. Asthma severity was not associated with higher risk of COVID-19.\n\nKey messagesIn this pediatric cohort, asthma was a risk factor for hospitalization in children with COVID-19, but not for worse COVID-19 outcomes. Baseline asthma severity was not associated with higher risk of COVID-19, and SARS-CoV-2 did not seem to be a strong trigger for pediatric asthma exacerbations.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Jia Ming Low", - "author_inst": "National University Hospital of Singapore" + "author_name": "Kristina Gaietto MD", + "author_inst": "Children's Hospital of Pittsburgh, Pulmonary Medicine" }, { - "author_name": "Yue Gu", - "author_inst": "Antibody Engineering Programme, Life Sciences Institute, National University of Singapore, Singapore, Singapore" + "author_name": "Megan Culler Freeman MD PhD", + "author_inst": "Children's Hospital of Pittsburgh, Infectious Diseases" }, { - "author_name": "Melissa Shu Feng Ng", - "author_inst": "Singapore Immunology Network, Agency for Science, Technology and Research, Singapore, Singapore" + "author_name": "Leigh Anne DiCicco MD", + "author_inst": "Children's Hospital of Pittsburgh, Hospital Medicine" }, { - "author_name": "Liang Wei Wang", - "author_inst": "Agency for Science, Technology and Research" + "author_name": "Sherry Rauenswinter RN", + "author_inst": "Children's Community Pediatrics" }, { - "author_name": "Amin Zubair", - "author_inst": "Department of Neonatology, Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore, Singapore" + "author_name": "Joseph R Squier BSN RN", + "author_inst": "Children's Community Pediatrics" }, { - "author_name": "Youjia Zhong", - "author_inst": "Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore" + "author_name": "Zachary Aldewereld MD", + "author_inst": "Children's Hospital of Pittsburgh, Critical Care Medicine" + }, + { + "author_name": "Jennifer Iagnemma DNP RN", + "author_inst": "Children's Community Pediatrics" }, { - "author_name": "Paul McAry", - "author_inst": "Antibody Engineering Programme, Life Sciences Institute, National University of Singapore, Singapore, Singapore" + "author_name": "Brian T Campfield MD", + "author_inst": "Children's Hospital of Pittsburgh, Infectious Diseases" + }, + { + "author_name": "David Wolfson MD", + "author_inst": "Children's Community Pediatrics" + }, + { + "author_name": "Traci M Kazmerski MD MS", + "author_inst": "Children's Hospital of Pittsburgh, Adolescent and Young Adult Medicine" + }, + { + "author_name": "Erick Forno MD MPH", + "author_inst": "Children's Hospital of Pittsburgh, Pulmonary Medicine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2021.09.15.21262846", @@ -595080,45 +594771,101 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.09.14.21263467", - "rel_title": "Information Theoretic Model Selection for Accurately Estimating Unreported COVID-19 Infections", + "rel_doi": "10.1101/2021.09.14.21263578", + "rel_title": "Monitoring the COVID-19 immunisation programme through a National Immunisation Management System- Englands experience", "rel_date": "2021-09-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.14.21263467", - "rel_abs": "One of the most significant challenges in the early combat against COVID-19 was the difficulty in estimating the true magnitude of infections. Unreported infections drove up disease spread in numerous regions, made it very hard to accurately estimate the infectivity of the pathogen, therewith hampering our ability to react effectively. Despite the use of surveillance-based methods such as serological studies, identifying the true magnitude is still challenging today. This paper proposes an information theoretic approach for accurately estimating the number of total infections. Our approach is built on top of Ordinary Differential Equations (ODE) based models, which are commonly used in epidemiology and for estimating such infections. We show how we can help such models to better compute the number of total infections and identify the parameterization by which we need the fewest bits to describe the observed dynamics of reported infections. Our experiments show that our approach leads to not only substantially better estimates of the number of total infections but also better forecasts of infections than standard model calibration based methods. We additionally show how our learned parameterization helps in modeling more accurate what-if scenarios with non-pharmaceutical interventions. Our results support earlier findings that most COVID-19 infections were unreported and non-pharmaceutical interventions indeed helped to mitigate the spread of the outbreak. Our approach provides a general method for improving epidemic modeling which is applicable broadly.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.14.21263578", + "rel_abs": "In England, the National Immunisation Management System (NIMS) has been used to deliver COVID-19 vaccinations across England, monitor vaccine coverage, and assess vaccine effectiveness and safety.\n\nThe NIMS was developed by a joint collaboration between a range of health and digital government agencies. Vaccinations delivered at large vaccination sites, pharmacies, hospitals and in primary care are entered on a point of care application which is verified using the unique NHS number in a centralised system containing information for everyone resident and registered with a GP in England. Vaccination details and additional data from hospital and GP records (such as priority groups) are sent to NHS Digital for data linkage. The NIMS constantly receives updated details from NHS Digital for all individuals and these data are provided to Public Health England (PHE) in a secure environment.\n\nPHE primarily use the NIMS for vaccine coverage, vaccine effectiveness and safety. Daily access to individual-level vaccine data has allowed PHE to rapidly and accurately estimate vaccine coverage and provide some of the worlds first vaccine effectiveness estimates.\n\nOther countries evaluating the roll-out and effect of COVID-19 vaccine programmes should consider a vaccine register or immunisation information system similar to the NIMS.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Jiaming Cui", - "author_inst": "Georgia Institute of Technology" + "author_name": "Elise Tessier", + "author_inst": "Public Health England" }, { - "author_name": "Arash Haddadan", - "author_inst": "University of Virginia" + "author_name": "Julia Stowe", + "author_inst": "Public Health England" }, { - "author_name": "A S M Ahsan-Ul Haque", - "author_inst": "University of Virginia" + "author_name": "Camille Tsang", + "author_inst": "Public Health England" }, { - "author_name": "Jilles Vreeken", - "author_inst": "CISPA Helmholtz Center for Information Security" + "author_name": "Yuma Rai", + "author_inst": "Public Health England" }, { - "author_name": "Bijaya Adhikari", - "author_inst": "The University of Iowa" + "author_name": "Eleanor Clarke", + "author_inst": "Public Health England" }, { - "author_name": "Anil Vullikanti", - "author_inst": "University of Virginia" + "author_name": "Anissa Lakhani", + "author_inst": "Public Health England" }, { - "author_name": "B. Aditya Prakash", - "author_inst": "Georgia Institute of Technology" + "author_name": "Ashley Makwana", + "author_inst": "Public Health England" + }, + { + "author_name": "Heather Heard", + "author_inst": "Public Health England" + }, + { + "author_name": "Tim Rickeard", + "author_inst": "Public Health England" + }, + { + "author_name": "Freja Kirsebom", + "author_inst": "Public Health England" + }, + { + "author_name": "Catherine Quinot", + "author_inst": "Public Health England" + }, + { + "author_name": "Shreya Lakhani", + "author_inst": "Public Health England" + }, + { + "author_name": "Linda Power", + "author_inst": "Public Health England" + }, + { + "author_name": "Michael Edelstein", + "author_inst": "Bar Ilan University" + }, + { + "author_name": "Andy Evans", + "author_inst": "System C & Graphnet Care Alliance" + }, + { + "author_name": "Mary Ramsay", + "author_inst": "Public Health England" + }, + { + "author_name": "Jamie Lopez Bernal", + "author_inst": "Public Health England" + }, + { + "author_name": "Joanne White", + "author_inst": "Public Health England" + }, + { + "author_name": "Charlotte Gower", + "author_inst": "Public Health England" + }, + { + "author_name": "Nick Andrews", + "author_inst": "Public Health England" + }, + { + "author_name": "Colin Campbell", + "author_inst": "Public Health England" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -596570,161 +596317,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.17.21263532", - "rel_title": "Strong humoral immune responses against SARS-CoV-2 Spike after BNT162b2 mRNA vaccination with a sixteen-week interval between doses", + "rel_doi": "10.1101/2021.09.17.21263759", + "rel_title": "Estimates of presumed population immunity to SARS-CoV-2 by state in the United States, August 2021", "rel_date": "2021-09-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.17.21263532", - "rel_abs": "While the standard regimen of the BNT162b2 mRNA vaccine includes two doses administered three weeks apart, some public health authorities decided to space them, raising concerns about vaccine efficacy. Here, we analyzed longitudinal humoral responses including antibody binding, Fc-mediated effector functions and neutralizing activity against the D614G strain but also variants of concern and SARS-CoV-1 in a cohort of SARS-CoV-2 naive and previously infected individuals, with an interval of sixteen weeks between the two doses. While the administration of a second dose to previously infected individuals did not significantly improve humoral responses, we observed a significant increase of humoral responses in naive individuals after the 16-weeks delayed second shot, achieving similar levels as in previously infected individuals. We compared these responses to those elicited in individuals receiving a short (4-weeks) dose interval. For the naive donors, these responses were superior to those elicited by the short dose interval.", - "rel_num_authors": 37, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.17.21263759", + "rel_abs": "BackgroundInformation is needed to monitor progress toward a level of population immunity to SARS-CoV-2 sufficient to disrupt viral transmission. We estimated the percentage of the United States (US) population with presumed immunity to SARS-CoV-2 due to vaccination, natural infection, or both as of August 26, 2021.\n\nMethodsPublicly available data as of August 26, 2021, from the Centers for Disease Control and Prevention (CDC) were used to calculate presumed population immunity by state. Seroprevalence data were used to estimate the percentage of the population previously infected with SARS-CoV-2, with adjustments for underreporting. Vaccination coverage data for both fully and partially vaccinated persons were used to calculate presumed immunity from vaccination. Finally, we estimated the percentage of the total population in each state with presumed immunity to SARS-CoV-2, with a sensitivity analysis to account for waning immunity, and compared these estimates to a range of population immunity thresholds.\n\nResultsPresumed population immunity varied among states (43.1% to 70.6%), with 19 states with 60% or less of their population having been infected or vaccinated. Four states have presumed immunity greater than thresholds estimated to be sufficient to disrupt transmission of less infectious variants (67%), and none were greater than the threshold estimated for more infectious variants (78% or higher).\n\nConclusionsThe US remains a distance below the threshold sufficient to disrupt viral transmission, with some states remarkably low. As more infectious variants emerge, it is critical that vaccination efforts intensify across all states and ages for which the vaccines are approved.\n\nSummaryAs of August 26, 2021, no state has reached a population level of immunity thought to be sufficient to disrupt transmission. (78% or higher), with some states having remarkably low presumed immunity.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Alexandra Tauzin", - "author_inst": "CRCHUM" - }, - { - "author_name": "Shang Yu Gong", - "author_inst": "CRCHUM" - }, - { - "author_name": "Guillaume Beaudoin-Bussieres", - "author_inst": "CRCHUM" - }, - { - "author_name": "Dani Vezina", - "author_inst": "CRCHUM" - }, - { - "author_name": "Romain Gasser", - "author_inst": "CRCHUM" - }, - { - "author_name": "Lauriane Nault", - "author_inst": "CRCHUM" - }, - { - "author_name": "Lorie Marchitto", - "author_inst": "CRCHUM" - }, - { - "author_name": "Mehdi Benlarbi", - "author_inst": "CRCHUM" - }, - { - "author_name": "Debashree Chatterjee", - "author_inst": "CRCHUM" - }, - { - "author_name": "Manon Nayrac", - "author_inst": "CRCHUM" - }, - { - "author_name": "Annemarie Laumaea", - "author_inst": "CRCHUM" - }, - { - "author_name": "Jeremie Prevost", - "author_inst": "CRCHUM" - }, - { - "author_name": "Marianne Boutin", - "author_inst": "CRCHUM" - }, - { - "author_name": "Geremy Sannier", - "author_inst": "CRCHUM" - }, - { - "author_name": "Alexandre Nicolas", - "author_inst": "CRCHUM" - }, - { - "author_name": "Catherine Bourassa", - "author_inst": "CRCHUM" - }, - { - "author_name": "Gabrielle Gendron-Lepage", - "author_inst": "CRCHUM" - }, - { - "author_name": "Halima Medjahed", - "author_inst": "CRCHUM" - }, - { - "author_name": "Guillaume Goyette", - "author_inst": "CRCHUM" - }, - { - "author_name": "Yuxia Bo", - "author_inst": "University of Ottawa" - }, - { - "author_name": "Josee Perreault", - "author_inst": "Hema-Quebec" - }, - { - "author_name": "Laurie Gokool", - "author_inst": "CRCHUM" - }, - { - "author_name": "Chantal Morrisseau", - "author_inst": "CRCHUM" - }, - { - "author_name": "Pascale Arlotto", - "author_inst": "CRCHUM" - }, - { - "author_name": "Renee Bazin", - "author_inst": "Hema-Quebec" - }, - { - "author_name": "Mathieu Dube", - "author_inst": "CRCHUM" - }, - { - "author_name": "Gaston De Serres", - "author_inst": "INSPQ" - }, - { - "author_name": "Nicholas Brousseau", - "author_inst": "INSPQ" + "author_name": "Marie C.D. Stoner", + "author_inst": "RTI International" }, { - "author_name": "Jonathan Richard", - "author_inst": "CRCHUM" + "author_name": "Frederick J. Angulo", + "author_inst": "Medical Development, Scientific, and Clinical Affairs, Pfizer Vaccines, Pfizer Inc., Collegeville, PA, United States" }, { - "author_name": "Roberta Rovito", - "author_inst": "University of Milan" + "author_name": "Sarah Rhea", + "author_inst": "RTI International" }, { - "author_name": "Marceline Cote", - "author_inst": "University of Ottawa" + "author_name": "Linda Morris Brown", + "author_inst": "RTI International" }, { - "author_name": "Cecile Tremblay", - "author_inst": "CRCHUM" + "author_name": "Jessica E. Atwell", + "author_inst": "Medical Development, Scientific, and Clinical Affairs, Pfizer Vaccines, Pfizer Inc., Collegeville, PA, United States" }, { - "author_name": "Giulia C Marchetti", - "author_inst": "University of Milan" + "author_name": "Jennifer L. Nguyen", + "author_inst": "Medical Development, Scientific, and Clinical Affairs, Pfizer Vaccines, Pfizer Inc., Collegeville, PA, United States" }, { - "author_name": "Ralf Duerr", - "author_inst": "New York University School of Medicine" - }, - { - "author_name": "Valerie Martel-Laferriere", - "author_inst": "CRCHUM" + "author_name": "John McLaughlin", + "author_inst": "Medical Development, Scientific, and Clinical Affairs, Pfizer Vaccines, Pfizer Inc., Collegeville, PA, United States" }, { - "author_name": "Daniel E Kaufmann", - "author_inst": "CRCHUM" + "author_name": "David L. Swerdlow", + "author_inst": "Medical Development, Scientific, and Clinical Affairs, Pfizer Vaccines, Pfizer Inc., Collegeville, PA, United States" }, { - "author_name": "Andres Finzi", - "author_inst": "CRCHUM" + "author_name": "Pia D.M. MacDonald", + "author_inst": "RTI International" } ], "version": "1", @@ -598536,79 +598171,187 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.09.15.21263654", - "rel_title": "Correlates of COVID-19 vaccination status among college students", + "rel_doi": "10.1101/2021.09.14.21263598", + "rel_title": "EFFICACY OF THE MEASLES-MUMPS-RUBELLA (MMR) VACCINE IN THE REDUCING THE SEVERITY OF COVID-19: AN INTERIM ANALYSIS OF A RANDOMISED CONTROLLED CLINICAL TRIAL", "rel_date": "2021-09-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.15.21263654", - "rel_abs": "ObjectivesDespite the widespread availability of COVID-19 vaccines in the United States, vaccine hesitancy remains high among certain groups. This study examined the correlates of being unvaccinated among a sample of university students (N=2900) during the spring and summer of 2021, when the campus had been closed for over a year and students were preparing to return to in-person learning.\n\nMethodsStudents responded to an email invitation and completed electronic surveys. Results. In multivariable logistic regression analyses, students were more likely to be unvaccinated if they were African American, identified with any political affiliation other than Democrat, were undergraduates or international students, had not traveled outside the Los Angeles during the pandemic, and/or had previously been ill with COVID-19.\n\nConclusionFindings indicate that culturally resonant educational interventions, and possibly vaccine requirements, are needed to promote vaccination among university students.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.14.21263598", + "rel_abs": "BackgroundCOVID-19 is still a challenge, both with regard to its treatment and to the actual efficacy of the vaccines available to date, especially with the emergence of new variants. We evaluated the efficacy of the measles-mumps-rubella (MMR) vaccine in preventing SARS-CoV-2 infection and severity of COVID-19 in health workers.\n\nMethodsThis analysis includes data from one ongoing blinded, randomized, placebo-controlled trial with participants aged 18-60 years were randomly assigned to receive the MMR vaccine or a placebo. The primary efficacy analysis included all participants with a positive nasopharyngeal RT-PCR test since their inclusion.\n\nResultsThe MMR vaccine did not prevent the SARS-CoV-2 infection. Participants in the MMR group, compared with those in the placebo group, had a 48% risk reduction in symptomatic COVID-19 (RR = 0.52; 95% CI: 0.33-0.83; p=0.004) and a 76% risk reduction in COVID-19 treatment (RR = 0.24; 95% CI: 0.06 - 0.88; p = 0.020) with one dose and a 51% risk reduction in COVID-19 symptoms (RR = 0.49; 95% CI: 0.31 - 0.78; p = 0.001) and a 78% risk reduction in COVID-19 treatment (RR = 0.22; 95% CI: 0.06 - 0.82; p = 0.015) with two doses.\n\nConclusionsThis interim analysis of an ongoing clinical trial suggests that compared with a placebo, the vaccine reduces the risk of COVID-19 symptoms and reduces the need for COVID-19 treatment.\n\nClinical Trials RegistryBrazilian Clinical Trials Registry (ReBEC n{degrees} RBR-2xd6dkj - https://ensaiosclinicos.gov.br/rg/RBR-2xd6dkj).\n\nHIGHLIGHTSO_LIThe MMR vaccine can stimulate the innate immunity inducing a nonspecific protection against other infections, called heterologous immunity.\nC_LIO_LIRepeated exposure to the antigen (innate immune response training) results in an extension of the action time of this immune response (innate immune response memory) and consequently in protection against other infections (heterologous immunity) for a longer time.\nC_LIO_LIThe MMR vaccine has been used by national immunization programs in the world for many years, it is very safe and can be stored and distributed at 2-8{degrees}C, making it particularly suitable for global distribution.\nC_LIO_LIAmong participants who received at least one dose, compared with those in the placebo group, participants in the MMR group had a significant risk reduction in symptomatic COVID-19 and of cases requiring treatment.\nC_LIO_LIThe use of MMR vaccine can be useful in several populations in the world that do not have access to the COVID-19 vaccine and in a future epidemic or pandemic as an emergency measure until specific treatments or vaccines for each case are available to the general population.\nC_LI", + "rel_num_authors": 42, "rel_authors": [ { - "author_name": "Michele Nicolo", - "author_inst": "University of Southern California" + "author_name": "EDISON Natal Fedrizzi", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Eric Kawaguchi", - "author_inst": "University of SouthernCalifornia" + "author_name": "Juliana Balbinot Reis Girondi", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Angie Ghanem-Uzqueda", - "author_inst": "University of Southern California" + "author_name": "Thiago Mamoru Sakae", + "author_inst": "University of South of the Santa Catarina (UNISUL), Florianopolis, Brazil" }, { - "author_name": "Andre E Kim", - "author_inst": "University of Southern California" + "author_name": "Sergio Murilo Steffens", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Daniel Soto", - "author_inst": "University of Southern California" + "author_name": "Aldanea Norma de Souza Silvestrin", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Sohini Deva", - "author_inst": "University of SouthernCalifornia" + "author_name": "Grace Serafim Claro", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Kush R Shanker", - "author_inst": "University of Southern California" + "author_name": "Hugo Alejandro Iskenderian", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Christopher Rogers", - "author_inst": "University of Southern California" + "author_name": "Bianca Hillmann", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Ryan Lee", - "author_inst": "University of Southern California" + "author_name": "Liliam Cristini Gervasi", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Frank Gilliland", - "author_inst": "University of Southern California" + "author_name": "Alberto Trapani Jr.", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Jeffrey Klausner", - "author_inst": "University of Southern California" + "author_name": "Patricia de Amorim Rodrigues", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" }, { - "author_name": "Andrea Kovacs", - "author_inst": "University of Southern California" + "author_name": "Amanda de Souza Vieira", + "author_inst": "Health Center Florianopolis City Hall, Florianopolis, Brazil" }, { - "author_name": "David V Conti", - "author_inst": "University of Southern California" + "author_name": "Scheila Monteiro Evaristo", + "author_inst": "Health Center Sao Jose City Hall, Sao Jose, Brazil" }, { - "author_name": "Howard Hu", - "author_inst": "University of Southern California" + "author_name": "Francisco Reis Tristao", + "author_inst": "Health Center Sao Jose City Hall, Sao Jose, Brazil" }, { - "author_name": "Jennifer B Unger", - "author_inst": "University of Southern California" + "author_name": "Fabiano da Silva Muniz", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Maria Veronica Nunes", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Nicole Zazula Beatriz", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Jhonathan Elpo", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Amanda Tiedje", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Louise Staudt Siqueira", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Marilin Sens", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Vitor Nandi", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Jessica Goedert Pereira", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Gustavo Costa Henrique", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Ana Paula Fritzen de Carvalho", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Ramon Carlos Pedroso de Morais", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Gustavo Giorgio de Cristo", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Maria Eduarda Hochsprung", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Ana Cristina Morais", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Rubens Centenaro", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Andrez Garcia", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Bettina Heidenreich Silva", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Eluze Luz Ouriques Neta", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Maria Eduarda Alves Ferreira", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Maria Eduarda Hames", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Maria Eduarda Paixao Gubert", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Milena Ronise Calegari", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Maria Luiza Baixo Martins", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Geovana Samuel Oliveira", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Marilia de Souza Marian", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Larissa Sell Sousa", + "author_inst": "Federal University of Santa Catarina (UFSC), Florianopolis, Brazil" + }, + { + "author_name": "Marcelo da Silva Fedrizzi", + "author_inst": "State University of Santa Catarina (UDESC), Florianopolis, Brazil" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.09.17.21263758", @@ -600634,67 +600377,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.13.21262182", - "rel_title": "mRNA COVID-19 Vaccination and Development of CMR-confirmed Myopericarditis", + "rel_doi": "10.1101/2021.09.13.21262360", + "rel_title": "Efficacy of two doses of COVID-19 vaccine against severe COVID-19 in those with risk conditions and residual risk to the clinically extremely vulnerable: the REACT-SCOT case-control study", "rel_date": "2021-09-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.13.21262182", - "rel_abs": "During the process of open peer review on MedRxiv we quickly received a number of messages from reviewers concerned that there was a problem with our reported incidence of myocarditis post mRNA vaccination. Our reported incidence appeared vastly inflated by an incorrectly small denominator (ie number of doses administered over the time period of the study). We reviewed the data available at Open Ottawa and found that there had indeed been a major underestimation, with the actual number of administered doses being more than 800,000 (much higher than quoted in the paper).\n\nIn order to avoid misleading either colleagues or the general public and press, we the authors unanimously wish to withdraw this paper on the grounds of incorrect incidence data. We thank the many peer reviewers who went out of their way to contact us and point out our error. We apologize to anyone who may have been upset or disturbed by our report.\n\nIn summary, the authors have withdrawn this manuscript because of a major error pertaining to the quoted incidence data. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.13.21262360", + "rel_abs": "ObjectivesTo determine whether COVID-19 efficacy varies with clinical risk category and to investigate risk factors for severe COVID-19 in those who have received two doses of vaccine.\n\nDesignMatched case-control study (REACT-SCOT).\n\nSettingPopulation of Scotland from 1 December 2020 to 8 September 2021.\n\nMain outcome measureSevere COVID-19, defined as cases with entry to critical care or fatal outcome.\n\nResultsEfficacy against severe COVID-19 of two doses of vaccine was 94% (95 percent CI 93% to 96%) in those without designated risk conditions, 89% (95 percent CI 86% to 91%) in those with moderate risk conditions, but only 73% (95 percent CI 64% to 79%) in those designated as clinically extremely vulnerable (CEV) and eligible for shielding. Of the 641 cases of severe COVID-19 in double-vaccinated individuals, 47% had moderate risk conditions and 38% were CEV. In the double-vaccinated CEV group, the rate ratio for severe disease (with no risk condition as reference category) was highest in solid organ transplants at 101 (95% CI 47 to 214) but even in this subgroup the absolute risk of severe COVID-19 was low (35 cases in 23678 person-months of follow-up).\n\nConclusionsTwo doses of vaccine protect against severe COVID-19 in CEV individuals but the residual risk in double-vaccinated individuals remains far higher in those who are CEV than in those who are not. These results lay a basis for determining eligibility for additional measures including passive immunization to protect those at highest risk.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Tahir Kafil", - "author_inst": "Ottawa Heart Institute" - }, - { - "author_name": "Mariana M Lamacie", - "author_inst": "Ottawa Heart Institute" - }, - { - "author_name": "Sophie Chenier", - "author_inst": "Ottawa Heart Institute" - }, - { - "author_name": "Heather Taggart", - "author_inst": "Ottawa Heart Institute" - }, - { - "author_name": "Nina Ghosh", - "author_inst": "Ottawa Heart Institute" - }, - { - "author_name": "Alexander Dick", - "author_inst": "Ottawa Heart Institute" + "author_name": "Paul M McKeigue", + "author_inst": "University of Edinburgh" }, { - "author_name": "Gary Small", - "author_inst": "Ottawa Heart Institute" + "author_name": "David McAllister", + "author_inst": "University of Glasgow" }, { - "author_name": "Peter Liu", - "author_inst": "Ottawa Heart Institute" + "author_name": "Chris Robertson", + "author_inst": "University of Strathclyde" }, { - "author_name": "Rob S Beanlands", - "author_inst": "Ottawa Heart Institute" + "author_name": "Sharon J Hutchinson", + "author_inst": "Glasgow Caledonian University" }, { - "author_name": "Lisa Mielniczuk", - "author_inst": "Ottawa Heart Institute" + "author_name": "Stuart McGurnaghan", + "author_inst": "University of Edinburgh" }, { - "author_name": "David Birnie", - "author_inst": "Ottawa Heart Institute" + "author_name": "Diane Stockton", + "author_inst": "Public Health Scotland" }, { - "author_name": "Andrew M Crean", - "author_inst": "Ottawa Heart Institute" + "author_name": "Helen M Colhoun", + "author_inst": "University of Edinburgh" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.09.13.21263414", @@ -602632,41 +602355,185 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.09.12.21263475", - "rel_title": "Spike Protein NTD mutation G142D in SARS-CoV-2 Delta VOC lineages is associated with frequent back mutations, increased viral loads, and immune evasion", + "rel_doi": "10.1101/2021.09.12.21263453", + "rel_title": "Spread of Gamma (P.1) sub-lineages carrying Spike mutations close to the furin cleavage site and deletions in the N-terminal domain drives ongoing transmission of SARS-CoV-2 in Amazonas, Brazil", "rel_date": "2021-09-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.12.21263475", - "rel_abs": "The significantly greater infectivity of the SARS-CoV-2 Delta variants of concern (VOC) is hypothesized to be driven by key mutations that result in increased transmissibility, viral load and/or evasion of host immune response. We surveyed the mutational profiles of Delta VOC genomes between September 2020 and mid-August 2021 and identified a previously unreported mutation pattern at amino acid position 142 in the N-terminal domain (NTD) of the spike protein which demonstrated multiple rounds of mutation from G142 to D142 and back. This pattern of frequent back mutations was observed at multiple time points and across Delta VOC sub-lineages. The etiology for these recurrent mutations is unclear but raises the possibility of host-directed editing of the SARS-CoV-2 genome. Within Delta VOC this mutation is associated with higher viral load, further enhanced in the presence of another NTD mutation (T95I) which was also frequently observed in these cases. Protein modeling of both mutations predicts alterations of the surface topography of the NTD by G142D, specifically disturbance of the super site epitope that binds NTD-directed neutralizing antibodies (NAbs). The appearance of frequent and repeated G142D followed by D142G back mutations is previously unreported in SARS-CoV-2 and may represent viral adaptation to evolving host immunity characterized by increasing frequency of spike NAbs, from both prior infection and vaccine-based immunity. The emergence of alterations of the NTD in and around the main NAb epitope is a concerning development in the ongoing evolution of SARS-CoV-2 which may contribute to increased infectivity, immune evasion and breakthrough infections characteristic of Delta VOC. Future vaccine and therapy development may benefit by recognizing the emergence of these novel spike NTD mutations and considering their impact on antibody recognition, viral neutralization, infectivity, replication, and viral load.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.12.21263453", + "rel_abs": "The Amazonas was one of the most heavily affected Brazilian states by the COVID-19 epidemic. Despite a large number of infected people, particularly during the second wave associated with the spread of the Variant of Concern (VOC) Gamma (lineage P.1), SARS-CoV-2 continues to circulate in the Amazonas. To understand how SARS-CoV-2 persisted in a human population with a high immunity barrier, we generated 1,188 SARS-CoV-2 whole-genome sequences from individuals diagnosed in the Amazonas state from 1st January to 6th July 2021, of which 38 were vaccine breakthrough infections. Our study reveals a sharp increase in the relative prevalence of Gamma plus (P.1+) variants, designated as Pango Lineages P.1.3 to P.1.6, harboring two types of additional Spike changes: deletions in the N-terminal (NTD) domain (particularly{Delta} 144 or{Delta} 141-144) associated with resistance to anti-NTD neutralizing antibodies or mutations at the S1/S2 junction (N679K or P681H) that probably enhance the binding affinity to the furin cleavage site, as suggested by our molecular dynamics simulations. As lineages P.1.4 (S:N679K) and P.1.6 (S:P681H) expanded (Re > 1) from March to July 2021, the lineage P.1 declined (Re < 1) and the median Ct value of SARS-CoV-2 positive cases in Amazonas significantly decreases. Still, we found no overrepresentation of P.1+ variants among breakthrough cases of fully vaccinated patients (71%) in comparison to unvaccinated individuals (93%). This evidence supports that the ongoing endemic transmission of SARS-CoV-2 in the Amazonas is driven by the spread of new local Gamma/P.1 sub-lineages that are more transmissible, although not more efficient to evade vaccine-elicited immunity than the parental VOC. Finally, as SARS-CoV-2 continues to spread in human populations with a declining density of susceptible hosts, the risk of selecting new variants with higher infectivity are expected to increase.", + "rel_num_authors": 42, "rel_authors": [ { - "author_name": "Lishuang Shen", - "author_inst": "Children's Hospital Los Angeles" + "author_name": "Felipe Gomes Naveca", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil; Laborat\u00f3rio de Flaviv\u00edrus, Institu" }, { - "author_name": "Timothy J Triche", - "author_inst": "Children's Hospital Los Angeles" + "author_name": "Valdinete Nascimento", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" }, { - "author_name": "Jennifer Dien Bard", - "author_inst": "Children's Hospital Los Angeles" + "author_name": "Victor Souza", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" }, { - "author_name": "Jaclyn A Biegel", - "author_inst": "Children's Hospital Los Angeles" + "author_name": "Andr\u00e9 Lima Corado", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" }, { - "author_name": "Alexander R Judkins", - "author_inst": "Children's Hospital Los Angeles" + "author_name": "Fernanda Nascimento", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" }, { - "author_name": "Xiaowu Gai", - "author_inst": "Children's Hospital Los Angeles" + "author_name": "George Silva", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil; Funda\u00e7\u00e3o Centro de Controle de Onc" + }, + { + "author_name": "Matilde Contreras Mej\u00eda", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" + }, + { + "author_name": "Maria J\u00falia Brand\u00e3o", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" + }, + { + "author_name": "\u00c1gatha Costa", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" + }, + { + "author_name": "D\u00e9bora Duarte", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" + }, + { + "author_name": "Karina Pessoa", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" + }, + { + "author_name": "Michele Jesus", + "author_inst": "Laborat\u00f3rio de Diversidade Microbiana da Amaz\u00f4nia com Import\u00e2ncia para a Sa\u00fade, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil" + }, + { + "author_name": "Luciana Gon\u00e7alves", + "author_inst": "Laborat\u00f3rio de Ecologia de Doen\u00e7as Transmiss\u00edveis na Amaz\u00f4nia, Instituto Le\u00f4nidas e Maria Deane, Fiocruz, Manaus, AM, Brazil; Funda\u00e7\u00e3o de Vigil\u00e2ncia em Sa\u00fade do" + }, + { + "author_name": "Cristiano Fernandes", + "author_inst": "Funda\u00e7\u00e3o de Vigil\u00e2ncia em Sa\u00fade do Amazonas - Dra. Rosemary Costa Pinto, Manaus, AM, Brazil" + }, + { + "author_name": "Tirza Mattos", + "author_inst": "Laborat\u00f3rio Central de Sa\u00fade P\u00fablica do Amazonas, Manaus, AM, Brazil" + }, + { + "author_name": "Ligia Abdalla", + "author_inst": "Universidade do Estado do Amazonas, Manaus, AM, Brazil" + }, + { + "author_name": "Jo\u00e3o Hugo Santos", + "author_inst": "Hospital Adventista de Manaus, Manaus, AM, Brazil" + }, + { + "author_name": "Alex Martins", + "author_inst": "Funda\u00e7\u00e3o de Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, AM, Brazil." + }, + { + "author_name": "Fabiola Mendon\u00e7a Chui", + "author_inst": "Universidade do Estado do Amazonas, Manaus, AM, Brazil" + }, + { + "author_name": "Fernando Fonseca Val", + "author_inst": "Funda\u00e7\u00e3o de Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, AM, Brazil" + }, + { + "author_name": "Gisely Cardoso de Melo", + "author_inst": "Funda\u00e7\u00e3o de Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, AM, Brazil; Universidade do Estado do Amazonas, Manaus, AM, Brazil" + }, + { + "author_name": "Mariana Xavier Sim\u00e3o", + "author_inst": "Funda\u00e7\u00e3o de Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, AM, Brazil" + }, + { + "author_name": "Vanderson de Souza Sampaio", + "author_inst": "Funda\u00e7\u00e3o de Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, AM, Brazil; Funda\u00e7\u00e3o de Vigil\u00e2ncia em Sa\u00fade do Amazonas - Dra. Rosemary Costa Pinto, Manaus, AM" + }, + { + "author_name": "Maria Paula Mour\u00e3o", + "author_inst": "Funda\u00e7\u00e3o de Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, AM, Brazil; Universidade do Estado do Amazonas, Manaus, AM, Brazil" + }, + { + "author_name": "Marcus Vin\u00edcius Lacerda", + "author_inst": "Funda\u00e7\u00e3o de Medicina Tropical Dr. Heitor Vieira Dourado, Manaus, AM, Brazil; Laborat\u00f3rio de Diagn\u00f3stico e Controle e Doen\u00e7as Infecciosas da Amaz\u00f4nia, Instituto " + }, + { + "author_name": "\u00c9rika Lopes Batista", + "author_inst": "Secretaria de Sa\u00fade de Aparecida de Goi\u00e2nia, GO, Brazil." + }, + { + "author_name": "Alessandro Leonardo Magalh\u00e3es", + "author_inst": "Secretaria de Sa\u00fade de Aparecida de Goi\u00e2nia, GO, Brazil." + }, + { + "author_name": "Nath\u00e2nia D\u00e1billa", + "author_inst": "Laborat\u00f3rio de Virologia e Cultivo Celular, Instituto de Patologia Tropical e Sa\u00fade P\u00fablica, Universidade Federal de Goi\u00e1s, Goi\u00e2nia, GO, Brazil" + }, + { + "author_name": "Lucas Carlos Gomes Pereira", + "author_inst": "HLAGYN-Laborat\u00f3rio de Imunologia de Transplantes de Goi\u00e1s, Aparecida de Goi\u00e2nia, GO, Brazil" + }, + { + "author_name": "Fernando Vinhal", + "author_inst": "HLAGYN-Laborat\u00f3rio de Imunologia de Transplantes de Goi\u00e1s, Aparecida de Goi\u00e2nia, GO, Brazil" + }, + { + "author_name": "Fabio Miyajima", + "author_inst": "Laborat\u00f3rio Analitico de Compet\u00eancias Moleculares e Epidemiol\u00f3gicas, Funda\u00e7\u00e3o Oswaldo Cruz Cear\u00e1, Fiocruz, Eus\u00e9bio, CE, Brazil" + }, + { + "author_name": "Fernando Stehling Dias", + "author_inst": "Laborat\u00f3rio Analitico de Compet\u00eancias Moleculares e Epidemiol\u00f3gicas, Funda\u00e7\u00e3o Oswaldo Cruz Cear\u00e1, Fiocruz, Eus\u00e9bio, CE, Brazil" + }, + { + "author_name": "Eduardo Ruback dos Santos", + "author_inst": "Unidade de Apoio Diagn\u00f3stico \u00e0 COVID19, Funda\u00e7\u00e3o Oswaldo Cruz Cear\u00e1, Fiocruz, Eus\u00e9bio, CE, Brazil" + }, + { + "author_name": "Danilo Co\u00ealho", + "author_inst": "Departamento de Virologia, Instituto Aggeu Magalh\u00e3es, Fiocruz, Recife, PE, Brazil" + }, + { + "author_name": "Matheus Ferraz", + "author_inst": "Departamento de Virologia, Instituto Aggeu Magalh\u00e3es, Fiocruz, Recife, PE, Brazil" + }, + { + "author_name": "Roberto Lins", + "author_inst": "Departamento de Virologia, Instituto Aggeu Magalh\u00e3es, Fiocruz, Recife, PE, Brazil" + }, + { + "author_name": "Gabriel Luz Wallau", + "author_inst": "Departamento de Entomologia e N\u00facleo de Bioinform\u00e1tica, Instituto Aggeu Magalh\u00e3es, Fiocruz, Recife, PE, Brazil" + }, + { + "author_name": "Edson Delatorre", + "author_inst": "Departamento de Biologia. Centro de Ci\u00eancias Exatas, Naturais e da Sa\u00fade, Universidade Federal do Esp\u00edrito Santo, Alegre, ES, Brazil" + }, + { + "author_name": "Tiago Gr\u00e4f", + "author_inst": "Instituto Gon\u00e7alo Moniz, Fiocruz, Salvador, BA, Brazil" + }, + { + "author_name": "Marilda Mendon\u00e7a Siqueira", + "author_inst": "Laborat\u00f3rio de V\u00edrus Respirat\u00f3rios e do Sarampo (LVRS), Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, RJ, Brazil" + }, + { + "author_name": "Paola Cristina Resende", + "author_inst": "Laborat\u00f3rio de V\u00edrus Respirat\u00f3rios e do Sarampo (LVRS), Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, RJ, Brazil" + }, + { + "author_name": "Gonzalo Bello", + "author_inst": "Laborat\u00f3rio de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, RJ, Brazil" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -604578,79 +604445,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.09.03.21262757", - "rel_title": "Asymptomatic SARS-CoV-2 infection and the demography of COVID-19", + "rel_doi": "10.1101/2021.09.09.21263342", + "rel_title": "Reports of myocarditis and pericarditis following mRNA COVID-19 vaccines: A review of spontaneously reported data from the UK, Europe, and the US", "rel_date": "2021-09-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.03.21262757", - "rel_abs": "Asymptomatic individuals carrying SARS-CoV-2 can transmit the virus and contribute to outbreaks of COVID-19, but it is not yet clear how the proportion of asymptomatic infections varies by age and geographic location. Here we use detailed surveillance data gathered during COVID-19 resurgences in six cities of China at the beginning of 2021 to investigate this question. Data were collected by multiple rounds of city-wide PCR test with detailed contact tracing, where each patient was monitored for symptoms through the whole course of infection. We find that the proportion of asymptomatic infections declines with age (coefficient =-0.006, P<0.01), falling from 56% in age group 0-9 years to 12% in age group >60 years. Using an age-stratified compartment model, we show that this age-dependent asymptomatic pattern together with the age distribution of overall cases can explain most of the geographic differences in reported asymptomatic proportions. Combined with demography and contact matrices from other countries worldwide, we estimate that a maximum of 22%-55% of SARS-CoV-2 infections would come from asymptomatic cases in an uncontrolled epidemic based on asymptomatic proportions in China. Our analysis suggests that flare-ups of COVID-19 are likely if only adults are vaccinated and that surveillance and possibly control measures among children will be still needed in the future to contain epidemic resurgence.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.09.21263342", + "rel_abs": "ObjectivesTo bring together spontaneously reported data from multiple countries to estimate reporting rate, and better understand risk factors for myocarditis and pericarditis following COVID-19 mRNA vaccines.\n\nDesignSystematic review of spontaneously reported data from United Kingdom (UK), United States (US), and European Union/European Economic Area (EU/EEA) and of the literature.\n\nData sourcesUK Yellow Card scheme, Vaccine Adverse Event Reporting System (VAERS), EudraVigilance were searched from date of vaccine launch to 14-16 March 2022. PubMed/MEDLINE and Embase were searched to 15 March 2022.\n\nEligibility criteriaWe included publicly available spontaneous reporting data for \"Myocarditis\" and \"Pericarditis\" from UK, US, and EU/EEA following COVID-19 mRNA vaccines. Pharmacoepidemiological observational studies investigating myocarditis/pericarditis following mRNA COVID-19 vaccines were included (no restrictions on language or date). Critical Appraisal Skills Programme (CASP) tools assessed study quality.\n\nData extraction and synthesisTwo researchers extracted data. Spontaneously reported events of myocarditis and pericarditis were presented for each data source, stratified by vaccine, age, sex, and dose (where available). Reporting rates were calculated for myocarditis and pericarditis for each population. For published pharmacoepidemiological studies, design, participant characteristics, and study results were tabulated.\n\nResultsOverall, 18,204 myocarditis and pericarditis events have been submitted to the UK, US, and EU/EEA regulators during the study period. Males represented 62.24% (n=11,331) of myocarditis and pericarditis reports. Most reports concerned vaccinees aged <40 years and were more frequent following a second dose. Reporting rates were consistent between the data sources. Thirty-two pharmacoepidemiological studies were included; results were consistent with our spontaneous report analyses.\n\nConclusionsYounger vaccinees more frequently report myocarditis and pericarditis following mRNA COVID-19 vaccines than older vaccinees. Results from published literature supported the results of our analyses.\n\nStrengths and Limitations of the StudyO_LIThis is the first study to bring together spontaneously reported data from the United Kingdom, United States, and Europe on myocarditis and pericarditis following mRNA COVID-19 vaccines.\nC_LIO_LIResults from this study provide evidence on the frequency of reported events of myocarditis and pericarditis following mRNA vaccines in different age groups, and by sex and vaccine dose; analyses of spontaneous reports were consolidated with results of published literature, identified by systematic review.\nC_LIO_LIResults may have been influenced by biases including different vaccination policies in each region examined, and publicity on events of myocarditis and pericarditis following mRNA vaccines.\nC_LIO_LIThe study relied on outputs from spontaneous reporting systems in which the level of detail differed between the systems examined; furthermore, it is not possible to estimate incidence rates using spontaneous reports due to the lack of data on the exposed population, and there is no unvaccinated comparison group.\nC_LIO_LIThere is an urgent need for further pharmacoepidemiological studies to be conducted to provide more accurate estimates of the frequency, clinical course, long term outcome, effects of treatment and impact on quality of life, to address many of the limitations of spontaneous reporting.\nC_LI", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Zengmiao Wang", - "author_inst": "Beijing Normal University" - }, - { - "author_name": "Peiyi Wu", - "author_inst": "Beijing Normal University" - }, - { - "author_name": "Jingyuan Wang", - "author_inst": "Beihang University" - }, - { - "author_name": "Jose Lourenco", - "author_inst": "University of Oxford" - }, - { - "author_name": "Bingying Li", - "author_inst": "Beijing Normal University" - }, - { - "author_name": "Benjamin Rader", - "author_inst": "Boston University" - }, - { - "author_name": "Marko Laine", - "author_inst": "Meteorological Research Unit" - }, - { - "author_name": "Hui Miao", - "author_inst": "Ohio State University" - }, - { - "author_name": "Ligui Wang", - "author_inst": "Center of Disease Control and Prevention, PLA" - }, - { - "author_name": "Hongbin Song", - "author_inst": "Center of Disease Control and Prevention, PLA" - }, - { - "author_name": "Nita Bharti", - "author_inst": "The Pennsylvania State University" - }, - { - "author_name": "John Brownstein", - "author_inst": "Harvard University" - }, - { - "author_name": "Ottar N Bjornstad", - "author_inst": "Penn State University" + "author_name": "Samantha Lane", + "author_inst": "Drug Safety Research Unit, Southampton, UK" }, { - "author_name": "Christopher Dye", - "author_inst": "University of Oxford" + "author_name": "Alison Yeomans", + "author_inst": "Drug Safety Research Unit, Southampton, UK" }, { - "author_name": "Huaiyu Tian", - "author_inst": "Beijing Normal University" + "author_name": "Saad Shakir", + "author_inst": "Drug Safety Research Unit, Southampton, UK" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pharmacology and therapeutics" }, { "rel_doi": "10.1101/2021.09.12.21263447", @@ -606472,45 +606291,117 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.07.21263200", - "rel_title": "Distinguishing Incubation and Acute Disease Stages of Mild-to-Moderate COVID-19", + "rel_doi": "10.1101/2021.09.08.21263057", + "rel_title": "State-wide Genomic Epidemiology Investigations of COVID-19 Infections in Healthcare Workers: Insights for Future Pandemic Preparedness", "rel_date": "2021-09-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.07.21263200", - "rel_abs": "ObjectiveWhile numerous studies have already compared the immune responses against SARS-CoV-2 in severely and mild-to-moderately ill COVID-19 patients, longitudinal trajectories are still scarce. We therefore set out to analyze serial blood samples from mild-to-moderately ill patients in order to define the immune landscapes for differently progressed disease stages.\n\nMethodsTwenty-two COVID-19 patients were subjected to consecutive venipuncture within seven days after diagnosis or admittance to hospital. Flow cytometry was performed to analyze peripheral blood immune cell compositions and their activation as were plasma levels of cytokines and SARS-CoV-2 specific immunoglobulins. Healthy donors served as controls.\n\nResultsIntegrating the kinetics of plasmablasts and SARS-CoV-2 specific antibodies allowed for the definition of three disease stages of early COVID-19. The incubation phase was characterized by a sharp increase in pro-inflammatory monocytes and terminally differentiated cytotoxic T cells. The latter correlated significantly with elevated concentrations of IP-10. Early acute infection featured a peak in PD-1+ cytotoxic T cells, plasmablasts and increasing titers of virus specific antibodies. During late acute infection, immature neutrophils were enriched whereas all other parameters returned to baseline.\n\nConclusionOur findings will help to define landmarks that are indispensable for the refinement of new anti-viral and anti-inflammatory therapeutics, and may also inform clinicians to optimize treatment and prevent fatal outcome.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.08.21263057", + "rel_abs": "BackgroundCOVID-19 has resulted in many infections in healthcare workers (HCWs) globally. We performed state-wide SARS-CoV-2 genomic epidemiological investigations to identify HCW transmission dynamics and provide recommendations to optimise healthcare system preparedness for future outbreaks.\n\nMethodsGenome sequencing was attempted on all COVID-19 cases in Victoria, Australia. We combined genomic and epidemiologic data to investigate the source of HCW infections across multiple healthcare facilities (HCFs) in the state. Phylogenetic analysis and fine-scale hierarchical clustering were performed for the entire Victorian dataset including community and healthcare cases. Facilities provided standardised epidemiological data and putative transmission links.\n\nFindingsBetween March and October 2020, approximately 1,240 HCW COVID-19 infection cases were identified; 765 are included here. Genomic sequencing was successful for 612 (80%) cases. Thirty-six investigations were undertaken across 12 HCFs. Genomic analysis revealed that multiple introductions of COVID-19 into facilities (31/36) were more common than single introductions (5/36). Major contributors to HCW acquisitions included mobility of staff and patients between wards and facilities, and characteristics and behaviours of individual patients including super-spreading events. Key limitations at the HCF level were identified.\n\nInterpretationGenomic epidemiological analyses enhanced understanding of HCW infections, revealing unsuspected clusters and transmission networks. Combined analysis of all HCWs and patients in a HCF should be conducted, supported by high rates of sequencing coverage for all cases in the population. Established systems for integrated genomic epidemiological investigations in healthcare settings will improve HCW safety in future pandemics.\n\nFundingThe Victorian Government, the National Health and Medical Research Council Australia, and the Medical Research Future Fund.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Michael M\u00fcller", - "author_inst": "Rostock University Medical Center" + "author_name": "Anne E Watt", + "author_inst": "The University of Melbourne" }, { - "author_name": "Johann Volzke", - "author_inst": "Rostock University Medical Center" + "author_name": "Norelle L Sherry", + "author_inst": "The University of Melbourne" }, { - "author_name": "Behnam Subin", - "author_inst": "Rostock University Medical Center" + "author_name": "Patiyan Andersson", + "author_inst": "The University of Melbourne" }, { - "author_name": "Christian Johann Schmidt", - "author_inst": "Rostock University Medical Center" + "author_name": "Courtney R Lane", + "author_inst": "The University of Melbourne" }, { - "author_name": "Hilte Geerdes-Fenge", - "author_inst": "Rostock University Medical Center" + "author_name": "Sandra Johnson", + "author_inst": "The University of Melbourne" }, { - "author_name": "Emil Christian Reisinger", - "author_inst": "Rostock University Medical Center" + "author_name": "Mathilda Wilmot", + "author_inst": "The University of Melbourne" }, { - "author_name": "Brigitte M\u00fcller-Hilke", - "author_inst": "Rostock Univsersity Medical Center" + "author_name": "Kristy Horan", + "author_inst": "The University of Melbourne" + }, + { + "author_name": "Michelle Sait", + "author_inst": "The University of Melbourne" + }, + { + "author_name": "Susan A Ballard", + "author_inst": "The University of Melbourne" + }, + { + "author_name": "Christina Crachi", + "author_inst": "The University of Melbourne" + }, + { + "author_name": "Diannw J Beck", + "author_inst": "The University of Melbourne" + }, + { + "author_name": "Caroline P Marshall", + "author_inst": "The University of Melbourne" + }, + { + "author_name": "Marion Kainer", + "author_inst": "Western Health" + }, + { + "author_name": "Rhonda Stuart", + "author_inst": "Monash Health" + }, + { + "author_name": "Christian McGrath", + "author_inst": "The Northern Hospital" + }, + { + "author_name": "Jason C Kwong", + "author_inst": "Austin Health" + }, + { + "author_name": "Pauline Bass", + "author_inst": "Alfred Health" + }, + { + "author_name": "Peter G Kelley", + "author_inst": "Peninsula Health" + }, + { + "author_name": "Amy Crowe", + "author_inst": "St Vincents Hospital Melbourne" + }, + { + "author_name": "Steven Guy", + "author_inst": "Eastern Health" + }, + { + "author_name": "Nenad Macesic", + "author_inst": "Epworth Hospital" + }, + { + "author_name": "Karen Smith", + "author_inst": "Ambulance Victoria" + }, + { + "author_name": "Deborah C Williamson", + "author_inst": "University of Melbourne" + }, + { + "author_name": "Torsten Seemann", + "author_inst": "The University of Melbourne" + }, + { + "author_name": "Benjamin P Howden", + "author_inst": "University of Melbourne at the Doherty Institute" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -607886,57 +607777,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.07.21263213", - "rel_title": "Comprehensive Evaluation of COVID-19 Patient Short- and Long-term Outcomes: Disparities in Healthcare Utilization and Post-Hospitalization Outcomes", + "rel_doi": "10.1101/2021.09.10.21263385", + "rel_title": "Effectiveness of the Single-Dose Ad26.COV2.S COVID Vaccine", "rel_date": "2021-09-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.07.21263213", - "rel_abs": "BackgroundUnderstanding risk factors for short- and long-term COVID-19 outcomes have implications for current guidelines and practice. We study whether early identified risk factors for COVID-19 persist one year later and through varying disease progression trajectories.\n\nMethodsThis was a retrospective study of 6,731 COVID-19 patients presenting to Michigan Medicine between March 10, 2020 and March 10, 2021. We describe disease progression trajectories from diagnosis to potential hospital admission, discharge, readmission, or death. Outcomes pertained to all patients: rate of medical encounters, hospitalization-free survival, and overall survival, and hospitalized patients: discharge versus in-hospital death and readmission. Risk factors included patient age, sex, race, body mass index, and 29 comorbidity conditions.\n\nResultsYounger, non-Black patients utilized healthcare resources at higher rates, while older, male, and Black patients had higher rates of hospitalization and mortality. Diabetes with complications, coagulopathy, fluid and electrolyte disorders, and blood loss anemia were risk factors for these outcomes. Diabetes with complications, coagulopathy, fluid and electrolyte disorders, and blood loss were associated with lower discharge and higher inpatient mortality rates.\n\nConclusionsThis study found differences in healthcare utilization and adverse COVID-19 outcomes, as well as differing risk factors for short- and long-term outcomes throughout disease progression. These findings may inform providers in emergency departments or critical care settings of treatment priorities, empower healthcare stakeholders with effective disease management strategies, and aid health policy makers in optimizing allocations of medical resources.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.10.21263385", + "rel_abs": "ImportanceVaccination against the SARS-CoV-2 virus is critical to control the pandemic. Randomized trials demonstrated efficacy of the single-dose Ad26.COV2.S COVID vaccine but data on longer-term protection in clinical practice and effectiveness against variants are needed.\n\nObjectiveTo assess the effectiveness of Ad26.COV2.S in preventing COVID infections and COVID-related hospitalizations in clinical practice, the longer-term stability of its protective effect and effectiveness against Delta variants.\n\nDesignCohort study of newly Ad26.COV2.S-vaccinated and unvaccinated individuals.\n\nSettingU.S. insurance claims data through July 2021.\n\nParticipantsIndividuals 18 years and older newly vaccinated with Ad26.COV2.S and up to 10 unvaccinated individuals matched exactly by age, sex, date, location, comorbidity index plus 17 COVID-19 risk factors via propensity score (PS) matching.\n\nInterventionVaccination with Ad26.COV2.S versus no vaccination.\n\nMain outcomesWe estimated vaccine effectiveness (VE) for observed COVID-19 infection and COVID-19-related hospitalization, nationwide and stratified by age, immunocompromised status, calendar time, and states with high incidence of the Delta variant. We corrected VE estimates for under-recording of vaccinations in insurance data.\n\nResultsAmong 390,517 vaccinated and 1,524,153 matched unvaccinated individuals, VE was 79% (95% CI, 77% to 80%) for COVID-19 and 81% (79% to 84%) for COVID-19-related hospitalizations. VE was stable over calendar time. Among states with high Delta variant incidence, VE during June/July 2021 was 78% (73% to 82%) for infections and 85% (73% to 91%) for hospitalizations. VE for COVID-19 was higher in individuals <50 years (83%; 81% to 85%) and lower in immunocompromised patients (64%; 57% to 70%). All estimates were corrected for under-recording; uncorrected VE was 69% (67% to 71%) and 73% (69% to 76%), for COVID-19 and COVID-19-related hospitalization, respectively.\n\nConclusionsThese non-randomized data across U.S. clinical practices show high and stable vaccine effectiveness of Ad26.COV2.S over time before the Delta variant emerged to when the Delta variant was dominant.", "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Stephen Salerno Jr.", - "author_inst": "University of Michigan" + "author_name": "Jennifer M. Polinski", + "author_inst": "Aetion Inc., New York, NY" }, { - "author_name": "Yuming Sun", - "author_inst": "University of Michigan" + "author_name": "Andrew R. Weckstein", + "author_inst": "Aetion Inc., New York, NY" }, { - "author_name": "Emily L Morris", - "author_inst": "University of Michigan" + "author_name": "Michael Batech", + "author_inst": "Aetion Inc., New York, NY" }, { - "author_name": "Xinwei He", - "author_inst": "University of Michigan" + "author_name": "Carly Kabelac", + "author_inst": "Aetion Inc., New York, NY" }, { - "author_name": "Yajing Li", - "author_inst": "University of Michigan" + "author_name": "Tripthi Kamath", + "author_inst": "Janssen R&D Data Science, Spring House, PA" }, { - "author_name": "Ziyang Pan Pan", - "author_inst": "University of Michigan" + "author_name": "Raymond Harvey", + "author_inst": "Janssen R&D Data Science, Spring House, PA" }, { - "author_name": "Peisong Han", - "author_inst": "University of Michigan" + "author_name": "Sid Jain", + "author_inst": "Janssen R&D Data Science, Spring House, PA" }, { - "author_name": "Jian Kang", - "author_inst": "University of Michigan" + "author_name": "Jeremy A. Rassen", + "author_inst": "Aetion Inc., New York, NY" }, { - "author_name": "Michael W Sjoding", - "author_inst": "University of Michigan" + "author_name": "Najat Khan", + "author_inst": "Janssen R&D Data Science, Spring House, PA" }, { - "author_name": "Yi Li", - "author_inst": "University of Michigan" + "author_name": "Sebastian Schneeweiss", + "author_inst": "Aetion Inc., New York, NY. Division of Pharmacoepidemiology, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -610252,39 +610143,43 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2021.09.08.459502", - "rel_title": "Digital Spatial Profiling of Collapsing Glomerulopathy", + "rel_doi": "10.1101/2021.09.09.459634", + "rel_title": "A thermostable oral SARS-CoV-2 vaccine induces mucosal and protective immunity", "rel_date": "2021-09-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.08.459502", - "rel_abs": "Collapsing glomerulopathy is a histologically distinct variant of focal and segmental glomerulosclerosis that presents with heavy proteinuria and portends a poor prognosis. Collapsing glomerulopathy can be triggered by viral infections such as HIV and SARS-CoV-2. Transcriptional profiling of collapsing glomerulopathy lesions is difficult since only a few glomeruli may exhibit this histology within a kidney biopsy and the mechanisms driving this heterogeneity are unknown. Therefore, we used recently developed digital spatial profiling (DSP) technology which permits quantification of mRNA at the level of individual glomeruli. Using DSP, we profiled 1,852 transcripts in glomeruli from HIV and SARS-CoV-2 infected patients with biopsy confirmed collapsing glomerulopathy. The increased resolution of DSP uncovered heterogeneity in glomerular transcriptional profiles that were missed in early laser capture microdissection studies of pooled glomeruli. Focused validation using immunohistochemistry and RNA in situ hybridization showed good concordance with DSP results. Therefore, DSP represents a powerful method to dissect transcriptional programs of pathologically discernible kidney lesions.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.09.459634", + "rel_abs": "An ideal protective vaccine against SARS-CoV-2 should not only be effective in preventing disease, but also in preventing virus transmission. It should also be well accepted by the population and have a simple logistic chain. To fulfill these criteria, we developed a thermostable, orally administered vaccine that can induce a robust mucosal neutralizing immune response. We used our platform based on retrovirus-derived enveloped virus-like particles (e-VLPs) harnessed with variable surface proteins (VSPs) from the intestinal parasite Giardia lamblia, affording them resistance to degradation and the triggering of robust mucosal cellular and antibody immune responses after oral administration. We made e-VLPs expressing various forms of the SARS-CoV-2 Spike protein (S), with or without membrane protein (M) expression. We found that prime-boost administration of VSP-decorated e-VLPs expressing a pre-fusion stabilized form of S and M triggers robust mucosal responses against SARS-CoV-2 in mice and hamsters, which translate into complete protection from a viral challenge. Moreover, they dramatically boosted the IgA mucosal response of intramuscularly injected vaccines. We conclude that our thermostable orally administered e-VLP vaccine could be a valuable addition to the current arsenal against SARS-CoV-2, in a stand-alone prime-boost vaccination strategy or as a boost for existing vaccines.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Kelly D. Smith", - "author_inst": "University of Washington" + "author_name": "Bertrand Bellier", + "author_inst": "Sorbonne universite" }, { - "author_name": "Kammi Henriksen", - "author_inst": "University of Chicago" + "author_name": "Alicia Saura", + "author_inst": "Universidad Catolica de Cordoba" }, { - "author_name": "Roberto F. Nicosia", - "author_inst": "University of Washington" + "author_name": "Lucas Lujan", + "author_inst": "Universidad Catolica de Cordoba" }, { - "author_name": "Charles E. Alpers", - "author_inst": "University of Washington" + "author_name": "Cecilia Molina", + "author_inst": "Universidad Catolica de Cordoba" }, { - "author_name": "Shreeram Akilesh", - "author_inst": "University of Washington" + "author_name": "Hugo D Lujan", + "author_inst": "Universidad Catolica de Cordoba" + }, + { + "author_name": "David Klatzmann", + "author_inst": "Sorbonne Universite" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "pathology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.09.08.459486", @@ -612362,33 +612257,33 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.09.02.21262599", - "rel_title": "Severe COVID-19 is associated with sustained biochemical disturbances and prolonged symptomatology; A retrospective single-centre cohort study", + "rel_doi": "10.1101/2021.09.02.21263046", + "rel_title": "The early impact of vaccination against SARS-CoV-2 in Region Stockholm, Sweden", "rel_date": "2021-09-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.02.21262599", - "rel_abs": "This manuscript has been withdrawn following a formal investigation by the Zan Mitrev Clinic Scientific Committee.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.02.21263046", + "rel_abs": "Vaccination against SARS-CoV-2 started in Region Stockholm, Sweden in December 2020 with those in long-term care facilities or receiving home care vaccinated first followed by those aged over 80 years. In this population-based, retrospective cohort study, we performed a Poisson regression to model the expected incidence of infections and deaths which we compared to the observed incidence and compared this to an unvaccinated control group of those aged 18-79 years. The aim of this study was to measure the early impact of the vaccination programme in Region Stockholm.\n\nInfections and deaths reduced substantially amongst the first two groups targeted for SARS-CoV-2 vaccination with an estimated total 3112 infections prevented, and 854 deaths prevented in these two groups from 4 weeks after the introduction of vaccination through to 2nd May 2021.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Marija Simjanoska", - "author_inst": "Columbia University in the City of New York" + "author_name": "Catherine Isitt", + "author_inst": "Karolinska University Hospital" }, { - "author_name": "Zan Mitrev", - "author_inst": "Zan Mitrev Clinic" + "author_name": "Daniel Sjoholm", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Gianluca Villa", - "author_inst": "University of Florence" + "author_name": "Maria-Pia Hergens", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Daniel Griffin", - "author_inst": "Columbia University College of Physicians and Surgeons" + "author_name": "Fredrik Granath", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Rodney Rosalia", - "author_inst": "Zan Mitrev Clinic" + "author_name": "Pontus Naucler", + "author_inst": "Karolinska Institutet" } ], "version": "1", @@ -613984,25 +613879,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.09.01.21262990", - "rel_title": "Impact and effectiveness of social distancing for COVID-19 mitigation -- A transnational and transregional study", + "rel_doi": "10.1101/2021.09.02.21263018", + "rel_title": "The pitfalls of inferring virus-virus interactions from co-detection prevalence data: Application to influenza and SARS-CoV-2", "rel_date": "2021-09-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.01.21262990", - "rel_abs": "We present an analysis of the relationship between SARS-CoV-2 infection rates and a social distancing metric from data for all the states and most populous cities in the United States and Brazil, all the 22 European Economic Community countries and the United Kingdom. We discuss why the infection rate, instead of the effective reproduction number or growth rate of cases, is a proper choice to perform this analysis when considering a wide span of time. We obtain a strong Spearmans rank order correlation between the social distancing metric and the infection rate in each locality. We show that mask mandates increase the values of Spearmans correlation in the United States, where a mandate was adopted. We also obtain an explicit numerical relation between the infection rate and the social distancing metric defined in the present work.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.09.02.21263018", + "rel_abs": "There is growing experimental evidence that many respiratory viruses--including influenza and SARS-CoV-2--can interact, such that their epidemiological dynamics may not be independent. To assess these interactions, standard statistical tests of independence suggest that the prevalence ratio--defined as the ratio of co-infection prevalence to the product of single-infection prevalences--should equal unity for non-interacting pathogens. As a result, earlier epidemiological studies aimed to estimate the prevalence ratio from co-detection prevalence data, under the assumption that deviations from unity implied interaction. To examine the validity of this assumption, we designed a simulation study that built on a broadly applicable epidemiological model of co-circulation of two respiratory viruses causing seasonal epidemics. By focusing on the pair influenza-SARS-CoV-2, we first demonstrate that the prevalence ratio systematically under-estimates the strength of interaction, and can even misclassify antagonistic or synergistic interactions that persist after clearance of infection. In a global sensitivity analysis, we further identify properties of viral infection--such as a high reproduction number or a short infectious period--that blur the interaction inferred from the prevalence ratio. Altogether, our results suggest that epidemiological studies based on co-detection prevalence data provide a poor guide to assess interactions among respiratory viruses.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Tarcisio Marciano Rocha Jr.", - "author_inst": "Universidade de Brasilia" + "author_name": "Matthieu Domenech de Cell\u00e8s", + "author_inst": "Max Planck Institute for Infection Biology" }, { - "author_name": "Jose Fernando Mendes", - "author_inst": "Universidade de Aveiro" + "author_name": "Elizabeth Goult", + "author_inst": "Max Planck Institute for Infection Biology" }, { - "author_name": "Marcelo Albano Moret", - "author_inst": "Universidade do Estado da Bahia" + "author_name": "Jean-S\u00e9bastien Casalegno", + "author_inst": "Virpath, Centre International de Recherche en Infectiologie (CIRI), Universite\u00e9 de Lyon" + }, + { + "author_name": "Sarah C Kramer", + "author_inst": "Max Planck Institute for Infection Biology" } ], "version": "1", @@ -615582,71 +615481,63 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.09.03.458829", - "rel_title": "Characterization of SARS-CoV-2 variants B.1.617.1 (Kappa), B.1.617.2 (Delta) and B.1.618 on cell entry, host range, and sensitivity to convalescent plasma and ACE2 decoy receptor", + "rel_doi": "10.1101/2021.09.02.458667", + "rel_title": "SARS-CoV-2 infection activates dendritic cells via cytosolic receptors rather than extracellular TLRs", "rel_date": "2021-09-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.03.458829", - "rel_abs": "Recently, highly transmissible SARS-CoV-2 variants B.1.617.1 (Kappa), B.1.617.2 (Delta) and B.1.618 were identified in India with mutations within the spike proteins. The spike protein of Kappa contains four mutations E154K, L452R, E484Q and P681R, and Delta contains L452R, T478K and P681R, while B.1.618 spike harbors mutations {Delta}145-146 and E484K. However, it remains unknown whether these variants have altered in their entry efficiency, host tropism, and sensitivity to neutralizing antibodies as well as entry inhibitors. In this study, we found that Kappa, Delta or B.1.618 spike uses human ACE2 with no or slightly increased efficiency, while gains a significantly increased binding affinity with mouse, marmoset and koala ACE2 orthologs, which exhibits limited binding with WT spike. Furthermore, the P618R mutation leads to enhanced spike cleavage, which could facilitate viral entry. In addition, Kappa, Delta and B.1.618 exhibits a reduced sensitivity to neutralization by convalescent sera owning to the mutation of E484Q, T478K, {Delta}145-146 or E484K, but remains sensitive to entry inhibitors-ACE2-lg decoy receptor. Collectively, our study revealed that enhanced human and mouse ACE2 receptor engagement, increased spike cleavage and reduced sensitivity to neutralization antibodies of Kappa, Delta and B.1.618 may contribute to the rapid spread of these variants and expanded host range. Furthermore, our result also highlighted that ACE2-lg could be developed as broad-spectrum antiviral strategy against SARS-CoV-2 variants.", - "rel_num_authors": 13, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.09.02.458667", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), an infectious disease characterized by strong induction of inflammatory cytokines, progressive lung inflammation and potentially multi-organ dysfunction. It remains unclear whether SARS-CoV-2 is sensed by pattern recognition receptors (PRRs) leading to immune activation. Several studies suggest that the Spike (S) protein of SARS-CoV-2 might interact with Toll-like receptor 4 (TLR4) and thereby activate immunity. Here we have investigated the role of TLR4 in SARS-CoV-2 infection and immunity. Neither exposure of isolated S protein, SARS-CoV-2 pseudovirus nor a primary SARS-CoV-2 isolate induced TLR4 activation in a TLR4-expressing cell line. Human monocyte-derived dendritic cells (DCs) express TLR4 but not ACE2, and DCs were not infected by a primary SARS-CoV-2 isolate. Notably, neither S protein nor the primary SARS-CoV-2 isolate induced DC maturation or cytokines, indicating that both S protein and SARS-CoV-2 virus particles do not trigger extracellular TLRs, including TLR4. Ectopic expression of ACE2 in DCs led to efficient infection by SARS-CoV-2. Strikingly, infection of ACE2-positive DCs induced type I IFN and cytokine responses, which was inhibited by antibodies against ACE2. These data strongly suggest that not extracellular TLRs but intracellular viral sensors are key players in sensing SARS-CoV-2. These data imply that SARS-CoV-2 escapes direct sensing by TLRs, which might underlie the lack of efficient immunity to SARS-CoV-2 early during infection.\n\nAuthor summaryThe immune system needs to recognize pathogens such as SARS-CoV-2 to initiate antiviral immunity. Dendritic cells (DCs) are crucial for inducing antiviral immunity and are therefore equipped with both extracellular and intracellular pattern recognition receptors to sense pathogens. However, it is unknown if and how SARS-CoV-2 activates DCs. Recent research suggests that SARS-CoV-2 is sensed by extracellular Toll-like receptor 4 (TLR4). We have previously shown that DCs do not express ACE2, and are therefore not infected by SARS-CoV-2. Here we show that DCs do not become activated by exposure to viral Spike proteins or SARS-CoV-2 virus particles. These findings suggest that TLR4 and other extracellular TLRs do not sense SARS-CoV-2. Next, we expressed ACE2 in DCs and SARS-CoV-2 efficiently infected these ACE2-positive DCs. Notably, infection of ACE2-positive DCs induced an antiviral immune response. Thus, our study suggests that infection of DCs is required for induction of immunity, and thus that intracellular viral sensors rather than extracellular TLRs are important in sensing SARS-CoV-2. Lack of sensing by extracellular TLRs might be an escape mechanism of SARS-CoV-2 and could contribute to the aberrant immune responses observed during COVID-19.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Wenlin Ren", - "author_inst": "Tsinghua University" - }, - { - "author_name": "Xiaohui Ju", - "author_inst": "Tsinghua University" - }, - { - "author_name": "Mingli Gong", - "author_inst": "Tsinghua University" + "author_name": "Lieve E.H. van der Donk", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Jun Lan", - "author_inst": "Tsinghua University" + "author_name": "Julia Eder", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Yanying Yu", - "author_inst": "Tsinghua University" + "author_name": "John L. van Hamme", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Quanxin Long", - "author_inst": "Chongqing Medical University" + "author_name": "Philip J.M. Brouwer", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Yu Zhang", - "author_inst": "Tsinghua University" + "author_name": "Mitch Brinkkemper", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Jin Zhong", - "author_inst": "Institut Pasteur of Shanghai" + "author_name": "Ad C. van Nuenen", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Guocai Zhong", - "author_inst": "Shenzhen Bay Laboratory" + "author_name": "Marit J. van Gils", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Xinquan Wang", - "author_inst": "Tsinghua University" + "author_name": "Rogier W. Sanders", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Ailong Huang", - "author_inst": "Chongqing Medical University" + "author_name": "Neeltje A. Kootstra", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Rong Zhang", - "author_inst": "Fudan University Shanghai Medical College" + "author_name": "Marta Bermejo-Jambrina", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" }, { - "author_name": "Qiang Ding", - "author_inst": "Tsinghua University" + "author_name": "Teunis B.H. Geijtenbeek", + "author_inst": "Amsterdam UMC - Locatie AMC: Amsterdam UMC Locatie AMC" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.09.03.458874", @@ -617700,59 +617591,63 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.08.29.21262798", - "rel_title": "Viral loads of Delta-variant SARS-CoV2 breakthrough infections following vaccination and booster with the BNT162b2 vaccine", + "rel_doi": "10.1101/2021.08.30.21262862", + "rel_title": "Sex-associated differences between body mass index and SARS-CoV-2 antibody titers following the BNT162b2 vaccine among 2,435 healthcare workers in Japan", "rel_date": "2021-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.29.21262798", - "rel_abs": "The BNT162b2 vaccine showed high real-life effectiveness both at preventing disease and in reducing viral loads of breakthrough infections, but coincidental with the rise of the Delta-variant SARS-CoV2, these protective effects have been decreasing, prompting a third, booster, vaccine inoculation. Here, analyzing viral loads of over 11,000 infections during the current wave in Israel, we find that even though this wave is dominated by the Delta-variant, breakthrough infections in recently vaccinated patients, still within 2 months post their second vaccine inoculation, do have lower viral loads compared to unvaccinated patients, with the extent of viral load reduction similar to pre-Delta breakthrough observations. Yet, this infectiousness protection starts diminishing for patients two months post vaccination and ultimately vanishes for patients 6 months or longer post vaccination. Encouragingly, we find that this diminishing vaccine effectiveness on breakthrough infection viral loads is restored following the booster vaccine. These results suggest that the vaccine is initially effective in reducing infectiousness of breakthrough infections even with the Delta variant, and that while this protectiveness effect declines with time it can be restored, at least temporarily, with a booster vaccine.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.30.21262862", + "rel_abs": "Obesity may downregulate vaccine-induced immunogenicity, but the epidemiological evidence for the COVID-19 vaccine is limited, and the sex-associated difference is unknown. It was observed that a higher body mass index was associated with lower titers of spike IgG antibodies against SARS-CoV-2 in men but not in women.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Matan Levine-Tiefenbrun", - "author_inst": "Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel" + "author_name": "Shohei Yamamoto", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Idan Yelin", - "author_inst": "Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel" + "author_name": "Tetsuya Mizoue", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Hillel Alapi", - "author_inst": "Maccabitech, Maccabi Health Services, Tel Aviv, Israel" + "author_name": "Akihito Tanaka", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Rachel Katz", - "author_inst": "Maccabitech, Maccabi Health Services, Tel Aviv, Israel" + "author_name": "Yusuke Oshiro", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Esma Herzel", - "author_inst": "Maccabitech, Maccabi Health Services, Tel Aviv, Israel" + "author_name": "Natsumi Inamura", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Jacob Kuint", - "author_inst": "Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel" + "author_name": "Maki Konishi", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Gabriel Chodick", - "author_inst": "Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv, Israel" + "author_name": "Mitsuru Ozeki", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Sivan Gazit", - "author_inst": "Maccabitech, Maccabi Health Services, Tel Aviv, Israel" + "author_name": "Kengo Miyo", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Tal Patalon", - "author_inst": "Maccabitech, Maccabi Health Services, Tel Aviv, Israel" + "author_name": "Wataru Sugiura", + "author_inst": "National Center for Global Health and Medicine" }, { - "author_name": "Roy Kishony", - "author_inst": "Faculty of Biology, Technion - Israel Institute of Technology, Haifa, Israel" + "author_name": "Haruhito Sugiyama", + "author_inst": "National Center for Global Health and Medicine" + }, + { + "author_name": "Norio Ohmagari", + "author_inst": "National Center for Global Health and Medicine" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.31.21262906", @@ -619558,27 +619453,143 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.30.21262821", - "rel_title": "The impact of pausing the Oxford-AstraZeneca COVID-19 vaccine on uptake in Europe: a difference-in-differences analysis", + "rel_doi": "10.1101/2021.08.30.21262666", + "rel_title": "AZD7442 demonstrates prophylactic and therapeutic efficacy in non-human primates and extended half-life in humans", "rel_date": "2021-08-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.30.21262821", - "rel_abs": "BackgroundSeveral countries paused their rollouts of the Oxford-AstraZeneca COVID-19 vaccine in mid-March 2021 due to concerns about vaccine-induced thrombosis and thrombocytopenia. Many warned that this risked damaging public confidence during a critical period of pandemic response. This study investigated whether the pause in the use of the Oxford-AstraZeneca vaccine had an impact on subsequent vaccine uptake in European countries.\n\nMethodsWe used a difference-in-differences approach capitalizing on the fact that some countries halted their rollouts whilst others did not. A longitudinal panel was constructed for European Economic Area countries spanning 15 weeks in early 2021. Media reports were used to identify countries that paused the Oxford-AstraZeneca vaccine and the timing of this. Data on vaccine uptake were available through the European Centre for Disease Control and Prevention COVID-19 Vaccine Tracker. Difference-in-differences linear regression models controlled for key confounders that could influence vaccine uptake, and country and week fixed effects. Further models and robustness checks were performed.\n\nResultsThe panel included 28 countries, with 19 in the intervention group and 9 in the control group. Pausing the Oxford-AstraZeneca vaccine was associated with a 0.52% decrease in uptake for the first dose of a COVID-19 vaccine and a 1.49% decrease in the uptake for both doses, comparing countries that paused to those that did not. These estimates are not statistically significant (p=0.86 and 0.39 respectively). For the Oxford-AstraZeneca vaccine only, the pause was associated with a 0.56% increase in uptake for the first dose and a 0.07% decrease in uptake for both doses. These estimates are also not statistically significant (p= 0.56 and 0.51 respectively). All our findings are robust to sensitivity analyses.\n\nConclusionAs new COVID-19 vaccines emerge, regulators should be cautious to deviate from usual protocols if further investigation on clinical or epidemiological grounds is warranted.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.30.21262666", + "rel_abs": "Despite the success of SARS-CoV-2 vaccines, there remains a need for more prevention and treatment options for individuals remaining at risk of COVID-19. Monoclonal antibodies (mAbs) against the viral spike protein have potential to both prevent and treat COVID-19, and reduce the risk of severe disease and death. Here, we describe AZD7442, a combination of two mAbs, AZD8895 (tixagevimab) and AZD1061 (cilgavimab), that simultaneously bind to distinct non-overlapping epitopes on the spike protein receptor binding domain to potently neutralize SARS-CoV-2. Initially isolated from individuals with prior SARS-CoV-2 infection, the two mAbs were designed to extend their half-lives and abrogate effector functions. The AZD7442 mAbs individually prevent the spike protein from binding to angiotensin-converting enzyme 2 receptor, blocking virus cell entry. Together, these two mAbs create a higher barrier to viral escape and a wider breadth of coverage, neutralizing all known SARS-CoV-2 variants of concern. In a non-human primate model of SARS-CoV-2 infection, prophylactic AZD7442 administration prevented infection, while therapeutic administration accelerated virus clearance from lung. In an ongoing Phase I study in healthy participants (NCT04507256), 300 mg intramuscular AZD7442 provided SARS-CoV-2 serum geometric mean neutralizing titers >10-fold above those of convalescent sera for [≥]3 months, which remained 3-fold above those of convalescent sera 9 months post-AZD7442 administration. Approximately 1-2% of serum AZD7442 levels were detected in nasal mucosa, a site of SARS-CoV-2 infection. Extrapolation of the time course of serum AZD7442 concentrations suggests AZD7442 may provide up to 12 months of protection and benefit individuals at high-risk of COVID-19.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Vageesh Jain", - "author_inst": "University College London" + "author_name": "Yueh-Ming Loo", + "author_inst": "Virology and Vaccine Discovery, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" }, { - "author_name": "Paula Lorgelly", - "author_inst": "University College London" + "author_name": "Patrick M McTamney", + "author_inst": "Virology and Vaccine Discovery, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Rosalinda H Arends", + "author_inst": "Clinical Pharmacology and Quantitative Pharmacology, Microbial Sciences, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaither" + }, + { + "author_name": "Robert A Gasser Jr", + "author_inst": "Clinical Development, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Michael E Abram", + "author_inst": "Translational Medicine, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Anastasia Aksyuk", + "author_inst": "Translational Medicine, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Seme Diallo", + "author_inst": "Virology and Vaccine Discovery, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Daniel J Flores", + "author_inst": "Virology and Vaccine Discovery, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Elizabeth J Kelly", + "author_inst": "Translational Medicine, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Kuishu Ren", + "author_inst": "Virology and Vaccine Discovery, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Richard Roque", + "author_inst": "Virology and Vaccine Discovery, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Kim Rosenthal", + "author_inst": "Virology and Vaccine Discovery, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Katie Streicher", + "author_inst": "Translational Medicine, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Kevin M Tuffy", + "author_inst": "Translational Medicine, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Nicholas J Bond", + "author_inst": "Analytical Sciences, BioPharmaceuticals R&D, AstraZeneca, Granta Park, Cambridge, UK" + }, + { + "author_name": "Owen Cornwell", + "author_inst": "Analytical Sciences, BioPharmaceuticals R&D, AstraZeneca, Granta Park, Cambridge, UK" + }, + { + "author_name": "Jerome Bouquet", + "author_inst": "Integrated Bioanalysis, Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, San Francisco, CA, USA" + }, + { + "author_name": "Lily I Cheng", + "author_inst": "Oncology Safety Pathology, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "James Dunyak", + "author_inst": "Clinical Pharmacology and Pharmacometrics, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Yue Huang", + "author_inst": "Integrated Bioanalysis, Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, San Francisco, CA, USA" + }, + { + "author_name": "Anton I Rosenbaum", + "author_inst": "Integrated Bioanalysis, Clinical Pharmacology and Quantitative Pharmacology, Clinical Pharmacology and Safety Sciences, R&D, AstraZeneca, San Francisco, CA, USA" + }, + { + "author_name": "Hanne Andersen", + "author_inst": "BIOQUAL Inc., Rockville, MD, USA" + }, + { + "author_name": "Robert H Carnahan", + "author_inst": "The Vanderbilt Vaccine Center, Vanderbilt University Medical Center, Nashville, TN, USA" + }, + { + "author_name": "James E Crowe Jr", + "author_inst": "The Vanderbilt Vaccine Center, Vanderbilt University Medical Center, Nashville, TN, USA" + }, + { + "author_name": "Ana I Kuehne", + "author_inst": "USAMRIID, Fort Detrick, MD, USA" + }, + { + "author_name": "Andrew S Herbert", + "author_inst": "USAMRIID, Fort Detrick, MD, USA" + }, + { + "author_name": "John M Dye", + "author_inst": "USAMRIID, Fort Detrick, MD, USA" + }, + { + "author_name": "Helen Bright", + "author_inst": "Virology and Vaccine Discovery, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Nicole L Kallewaard", + "author_inst": "Virology and Vaccine Discovery, Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" + }, + { + "author_name": "Menelas N Pangalos", + "author_inst": "BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK" + }, + { + "author_name": "Mark T Esser", + "author_inst": "Microbial Sciences, BioPharmaceuticals R&D, AstraZeneca, Gaithersburg, MD, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.08.30.21262536", @@ -621324,65 +621335,37 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.08.27.21262721", - "rel_title": "Short-Term Immune Response After Inactivated SARS-CoV-2 (CoronaVac, Sinovac) And ChAdOx1 nCoV-19 (Vaxzevria, Oxford-AstraZeneca) Vaccinations in Thai Health Care Workers", - "rel_date": "2021-08-30", + "rel_doi": "10.1101/2021.08.28.21262543", + "rel_title": "Antibodies anti-SARS-CoV2 time-course in patients and vaccinated subjects: an evaluation of the harmonization of two different methods", + "rel_date": "2021-08-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.27.21262721", - "rel_abs": "BackgroundInactivated SARS-CoV-2 (CoronaVac(R),Sinovac, or SV) and ChAdOx1 nCoV-19 (Vaxzevria(R),Oxford-Astra Zeneca, or AZ) vaccines have been administered to the health care workers (HCWs) in Thailand.\n\nObjectiveTo determine the short-term immune response after the SV and AZ vaccinations in HCWs.\n\nMethodsIn this prospective cohort study, HCWs who completed a 2-dose regimen of the SV or AZ were included. Immune response was evaluated by surrogate viral neutralization test (sVNT) and anti-SARS-CoV-2 total antibody. Blood samples were analyzed at 4 and 12 weeks after the complete SV vaccination and at 4 weeks after each dose of the AZ vaccination. The primary outcome was the seroconversion rate at 4-weeks after complete immunization.\n\nResultsOverall, 185 HCWs with a median (IQR) age of 40.5(30.3-55.8) years (94 HCWs in the SV group and 91 in the AZ group) were included. At 4 weeks after completing the SV vaccination, 60.6% (95%CI:50.0-70.6%) had seroconversion evaluated by sVNT([≥]68%inhibition), comparable to the patients recovered from mild COVID-19 infection(69.0%), with a rapid reduction to 12.2%(95%CI:6.3-20.8) at 12 weeks. In contrast, 85.7%(95%CI:76.8-92.2%) HCWs who completed the second dose of the AZ for 4 weeks had seroconversion, comparable to the COVID-19 pneumonia patients(92.5%). When using the anti-SAR-CoV-2 total antibody level([≥]132 U/ml) criteria, only 71.3% HCWs in the SV group had seroconversion, compared to 100% in the AZ group.\n\nConclusionA rapid decline of short-term immune response in the HCWs after the SV vaccination indicates the need for a vaccine booster, particularly during the ongoing spreading of the SAR-CoV-2 variants of concern.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.28.21262543", + "rel_abs": "The time-course of antibodies anti SARS-CoV2 is not yet well elucidated, especially in people who underwent a vaccination campaign. In this study we measured antibodies anti-S1 and anti-RBD with two different methods both in patients and in vaccinated subjects.\n\n108 specimens from 48 patients diagnosed as COVID-19 affected (time from the onset of symptoms from 3 to 368 days) and 60 specimens from 20 vaccinated subjects (collected after 14 days from the first dose, 14 days and 3 months after a second dose of Comirnaty) were evaluated.\n\nWe used an ELISA method that measure IgG against anti-Spike 1 and a chemiluminescence immunoassays that measure IgG anti-RBD.\n\nIn the patients, antibodies concentrations tend to decline after a few months with both methods, but persist relatively high up to nearly a year after symptoms.\n\nIn vaccinated subjects, antibodies were already detectable after the first dose, but after the booster they show a significant increase. However, the decrease is rapid, given that after 3 months after the second vaccination they are reduced to less than a quarter.\n\nThe conversion of the results into BAU units improves the relationship between the two methods. However, in vaccinated subjects there was no evidence of proportional error after the conversion, while in the patients the difference between the two methods remained significant.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Watsamon Jantarabenjakul", - "author_inst": "King Chulalongkorn Memorial Hospital" - }, - { - "author_name": "Napaporn Chantasrisawad", - "author_inst": "King Chulalongkorn Memorial Hospital" - }, - { - "author_name": "Thanyawee Puthanakit", - "author_inst": "Faculty of Medicine, Chulalongkorn University" - }, - { - "author_name": "Supaporn Wacharapluesadee", - "author_inst": "King Chulalongkorn Memorial Hospital" - }, - { - "author_name": "Nattiya Hirankarn", - "author_inst": "Faculty of Medicine, Chulalongkorn University" - }, - { - "author_name": "Vichaya Ruenjaiman", - "author_inst": "Faculty of Medicine, Chulalongkorn University" - }, - { - "author_name": "Leilani Paitoonpong", - "author_inst": "Faculty of Medicine, Chulalongkorn University" - }, - { - "author_name": "Gompol Suwanpimolkul", - "author_inst": "Faculty of Medicine, Chulalongkorn University" + "author_name": "Ruggero Dittadi", + "author_inst": "Laboratory Medicine, Ospedale dell'Angelo, ULSS3 Serenissima, Mestre, Venice, Italy" }, { - "author_name": "Pattama Torvorapanit", - "author_inst": "King Chulalongkorn Memorial Hospital" + "author_name": "Mara Seguso", + "author_inst": "Laboratory Medicine. Ospedale dell'Angelo, ULSS3 Serenissima, Mestre, Venezia" }, { - "author_name": "Rakchanok Pradit", - "author_inst": "King Chulalongkorn Memorial Hospital" + "author_name": "Bertoli Isabella", + "author_inst": "Laboratory Medicine, Ospedale dell'Angelo, ULSS3 Serenissima, Mestre, Venice, Italy" }, { - "author_name": "Jiratchaya Sophonphan", - "author_inst": "Thai Red Cross AIDS Research Centre" + "author_name": "Haleh Afshar", + "author_inst": "Laboratory Medicine, Ospedale dell'Angelo, ULSS3 Serenissima, Mestre, Venice, Italy" }, { - "author_name": "OPASS PUTCHAROEN", - "author_inst": "Faculty of Medicine, Chulalongkorn university" + "author_name": "Paolo Carraro", + "author_inst": "Laboratory Medicine, Ospedale dell'Angelo, ULSS3 Serenissima, Mestre, Venice, Italy" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -623322,55 +623305,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.08.25.21262627", - "rel_title": "History of suicide attempts and COVID-19 infection in Veterans with schizophrenia or schizoaffective disorder: effect modification by age and obesity", + "rel_doi": "10.1101/2021.08.26.21262693", + "rel_title": "Socioeconomic and comorbid factors affecting mortality and length of stay in COVID-19", "rel_date": "2021-08-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.25.21262627", - "rel_abs": "ImportanceAs patients with schizophrenia or schizoaffective disorder have a high risk of suicide, and a history of suicide attempt is a strong predictor of suicide, determining whether history of suicide attempt is associated with COVID-19 in patients with schizophrenia or schizoaffective disorder has implications for suicide prevention in this patient population.\n\nObjectiveTo determine whether a history of suicide attempt is associated with COVID-19 in Veterans with schizophrenia or schizoaffective disorder.\n\nDesignCross-sectional analyses of nation-wide electronic health records (EHR).\n\nSettingUnited States Veterans Health Administration.\n\nParticipantsVeterans with a diagnosis of schizophrenia or schizoaffective disorder that received treatment at any United States Veterans Affairs Medical Center from January 1, 2020 to January 31, 2021.\n\nExposureHistory of suicide attempt.\n\nMain OutcomeAdjusted and unadjusted odds ratios (ORs) for COVID-19 positivity in suicide attempters relative to non-attempters. Adjusted analyses included age, sex, race, marital status, BMI, and a medical comorbidity score.\n\nResultsA total of 101,032 Veterans [mean age 56.67 {+/-} 13.13 years; males 91,715 (90.8%)] were included in the analyses. There were 2,703 (2.7%) suicide attempters and 719 (0.7%) patients were positive for COVID-19. There was effect modification by age and BMI in the association of history of suicide attempt with COVID-19 positivity such that the association was only significant in obese (BMI [≥] 30) patients and patients younger than 59 years respectively. In the entire sample, the unadjusted OR for COVID-19 positivity in attempters was 1.42 (95% CI 0.97 to 2.10) and the adjusted odds ratio was 1.90 (95% CI 1.28 to 2.80). In patients younger than 59 years, and in the obese patients respectively, history of suicide attempt was associated with COVID-positive status in unadjusted analyses [OR 3.53 (95% CI 2.10 to 5.94); OR 2.22 (95% CI 1.29 to 3.81)] and adjusted analyses [OR 3.42 (95% CI 2.02 to 5.79); OR 2.85 (95% CI 1.65 to 4.94)].\n\nConclusions and RelevanceYoung or obese suicide attempters with a diagnosis of schizophrenia or schizoaffective disorders have higher rates of COVID-19 diagnosis; due to possible long-term neuropsychiatric sequelae of infection with SARS-CoV-2, such patients should be monitored closely.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.26.21262693", + "rel_abs": "BackgroundThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic exposed and exacerbated health disparities between socioeconomic groups. Our purpose was to determine which disparities are most prevalent and their impact on length of stay (LoS) and in hospital mortality in patients diagnosed with Covid-19.\n\nMethodsDe-Identified data for patients who tested positive for COVID-19 was abstracted from the HCA enterprise database. Data was binned into summary tables. A negative binomial regression with LoS as the dependent variable and a logistic regression of in-hospital mortality data, using age, insurance status, sex, comorbidities as the dependent variables, were performed.\n\nResultsFrom March 1, 2020 to August 23, 2020, of 111,849 covid testing patient records, excluding those with missing data (n=7), without confirmed COVID-19 (n=27,225), and those from a carceral environment (n=1,861), left 84,624 eligible patients. Compared to the US population, the covid cohort had more black patients (23.17% vs 13.4%). Compared to the white cohort, the black cohort had higher private insurance rates (28.52% vs. 23.68%), shorter LoS (IRR=0.97 CI=0.95-0.99, P<0.01) and lower adjusted mortality (OR 0.81, 95% CI 0.75-0.97). Increasing age was associated with increased mortality and LoS. Patients with Medicare or Medicaid had longer LoS (IRR=1.07, 95% CI=1.04-1.09) and higher adjusted mortality rates (OR=1.11, 95% CI=1-1.23) than those with private insurance\n\nConclusionConclusions We found that when blacks have higher rates of private insurance, they have shorter hospitalizations and lower mortality than whites, when diagnosed with Covid-19. Some other psychiatric and medical conditions also significantly impacted outcomes in patients with Covid-19.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhich social determinants of health and comorbidities are most prevalent and their impact on length of stay and in-hospital mortality in patients diagnosed with Covid-19?\n\nFindingsIn this retrospective cohort of 84,624 with the black cohort having higher private insurance rates (28.52% vs. 23.68%), there was shorter LoS (IRR=0.97 CI=0.95-0.99, P<0.01) and lower adjusted mortality (OR 0.81, 95% CI 0.75-0.97). Age and several other medical and psychiatric comorbidities were also found to correlate with length of stay and mortality.\n\nMeaningThe genetics of race is not important in predicting mortality and length of stay in COVID-19 patients, but age, comorbidities, and insurance status appear to have a significant difference in mortality and length of stay.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Olaoluwa O Okusaga", - "author_inst": "Michael E. DeBakey VA Medical Center/Baylor College of Medicine" - }, - { - "author_name": "Rachel L Kember", - "author_inst": "University of Pennsylvania" + "author_name": "Adam Delora", + "author_inst": "HCA Houston/University of Houston" }, { - "author_name": "Gina M Peloso", - "author_inst": "Department of Biostatistics, Boston University School of Public Health" - }, - { - "author_name": "Roseann E Peterson", - "author_inst": "Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University" + "author_name": "Ashlynn Mills", + "author_inst": "University of Houston College of Medicine" }, { - "author_name": "Marijana Vujkovic", - "author_inst": "University of Pennsylvania" + "author_name": "David Jacobson", + "author_inst": "University of Houston College of Medicine" }, { - "author_name": "Brian G Mitchell", - "author_inst": "Michael E. DeBakey VA Medical Center/Baylor College of Medicine" + "author_name": "Brendon Cornett", + "author_inst": "HCA healthcare" }, { - "author_name": "Jared Bernard", - "author_inst": "Michael E. DeBakey VA Medical Center/Baylor College of Medicine" + "author_name": "W. Frank Peacock", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Annette Walder", - "author_inst": "Michael E. DeBakey VA Medical Center/Baylor College of Medicine" + "author_name": "Anita Datta", + "author_inst": "HCA Houston/University of Houston Consortium" }, { - "author_name": "Tim B Bigdeli", - "author_inst": "SUNY Downstate Medical Center" + "author_name": "Shane Jenks", + "author_inst": "HCA Houston/University of Houston Consortium" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.08.25.21254738", @@ -625512,43 +625487,75 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2021.08.24.21262554", - "rel_title": "Impact of the early stages of the COVID-19 pandemic on coverage of RMNH interventions in Ethiopia", + "rel_doi": "10.1101/2021.08.24.21262336", + "rel_title": "Enhanced neutrophil extracellular trap formation in COVID-19 is inhibited by the PKC inhibitor ruboxistaurin.", "rel_date": "2021-08-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.24.21262554", - "rel_abs": "BackgroundThe COVID-19 pandemic and response have the potential to disrupt access and use of reproductive, maternal, and newborn health (RMNH) services. Numerous initiatives aim to gauge the indirect impact of COVID-19 on RMNH.\n\nMethodsWe assessed the impact of COVID-19 on RMNH coverage in the early stages of the pandemic using panel survey data from PMA-Ethiopia. Enrolled pregnant women were surveyed 6-weeks post-birth. We compared the odds of service receipt, coverage of RMNCH service indicators, and health outcomes within the cohort of women who gave birth prior to the pandemic and the COVID-19 affected cohort. We calculated impacts nationally and by urbanicity.\n\nResultsThis dataset shows little disruption of RMNH services in Ethiopia in the initial months of the pandemic. There were no significant reductions in women seeking health services or the content of services they received for either preventative or curative interventions. In rural areas, a greater proportion of women in the COVID-19 affected cohort sought care for peripartum complications, ANC, PNC, and care for sick newborns. Significant reductions in coverage of BCG vaccination and chlorohexidine use in urban areas were observed in the COVID-19 affected cohort. An increased proportion of women in Addis Ababa reported postpartum family planning in the COVID-19 affected cohort. Despite the lack of evidence of reduced health services, the data suggest increased stillbirths in the COVID-19 affected cohort.\n\nDiscussionThe government of Ethiopias response to control the COVID-19 pandemic and ensure continuity of essential health services appears to have successfully averted most negative impacts on maternal and neonatal care. This analysis cannot address the later effects of the pandemic and may not capture more acute or geographically isolated reductions in coverage. Continued efforts are needed to ensure that essential health services are maintained and even strengthened to prevent indirect loss of life.\n\nWhat is already known?O_LICOVID-19 pandemic and response have the potential to disrupt access and use of reproductive, maternal, and neonatal health services\nC_LIO_LIAnecdotal evidence suggests some disruptions to health system staffing and resources, service access, and health campaigns in Ethiopia early in the pandemic\nC_LI\n\nWhat are the new findings?O_LIOur analysis of PMA-Ethiopia panel survey data shows little disruption of RMNH services in Ethiopia in the initial months of the pandemic\nC_LIO_LICompared to immediately prior to the pandemic we observed an increase in care-seeking in rural areas, commodity-related intervention reductions in urban areas, and an increase in postpartum family planning in Addis Ababa\nC_LIO_LIDespite the lack of evidence of a reduction in health services, the data suggest increased stillbirths in the COVID-19 affected cohort\nC_LI\n\nWhat do the new findings imply?O_LIThe government of Ethiopia successfully maintained continuity of most RMNCH services during the early stages of the COVID-19 pandemic\nC_LIO_LIContinued efforts are needed to ensure that essential health services are maintained and even strengthened to prevent indirect loss of life\nC_LI", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.24.21262336", + "rel_abs": "Neutrophil extracellular traps (NETs) are web-like DNA and protein lattices which are expelled by neutrophils to trap and kill pathogens, but which cause significant damage to the host tissue. NETs have emerged as critical mediators of lung damage, inflammation and thrombosis in COVID-19 and other diseases, but there are no therapeutics to prevent or reduce NETs that are available to patients. Here, we show that neutrophils isolated from hospitalised patients with COVID-19 produce significantly more NETs in response to LPS compared to cells from healthy control subjects. A subset of patients were captured at follow-up clinics (3-4 month post-infection) and while LPS-induced NET formation is significantly lower at this time point, it remains elevated compared to healthy controls. LPS- and PMA-induced NETs were significantly inhibited by the protein kinase C (PKC) inhibitor ruboxistaurin. Ruboxistaurin-mediated inhibition of NETs in healthy neutrophils reduces NET-induced epithelial cell death. Our findings suggest ruboxistaurin could reduce proinflammatory and tissue-damaging consequences of neutrophils during disease, and since it has completed phase III trials for other indications without safety concerns, it is a promising and novel therapeutic strategy for COVID-19.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Emily D Carter", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Rebecca Dowey", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom" }, { - "author_name": "Linnea Zimmerman", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Joby Cole", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom & Sheffield Teaching Hospitals NHS Foundation T" }, { - "author_name": "Ellie Qian", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "A A Roger Thompson", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom" }, { - "author_name": "Tim Roberton", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Chenghao Huang", + "author_inst": "Faculty of Medicine, Dentistry and Health, University of Sheffield, Sheffield, United Kingdom" }, { - "author_name": "Assefa Seme", - "author_inst": "Addis Ababa University" + "author_name": "Jacob Whatmore", + "author_inst": "Faculty of Medicine, Dentistry and Health, University of Sheffield, Sheffield, United Kingdom" }, { - "author_name": "Solomon Shiferaw", - "author_inst": "Addis Ababa University" + "author_name": "Ahmed Iqbal", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom & Department of Oncology and Metabolism, University of Sheffield, Sheffield, United" + }, + { + "author_name": "Kirsty L Bradley", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom" + }, + { + "author_name": "Joanne McKenzie", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom" + }, + { + "author_name": "Rebecca C Hull", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom" + }, + { + "author_name": "Allan Lawrie", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom" + }, + { + "author_name": "Alison M Condliffe", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom" + }, + { + "author_name": "Endre Kiss-Toth", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom" + }, + { + "author_name": "Ian Sabroe", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust, Sheffield, United Kingdom" + }, + { + "author_name": "Lynne R Prince", + "author_inst": "Department of Infection, Immunity and Cardiovascular Disease, University of Sheffield, Sheffield, United Kingdom" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2021.08.25.457644", @@ -627510,43 +627517,95 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2021.08.23.457411", - "rel_title": "Woodsmoke particulates alter expression of antiviral host response genes in human nasal epithelial cells infected with SARS-CoV-2 in a sex-dependent manner", + "rel_doi": "10.1101/2021.08.24.457518", + "rel_title": "Yeast-expressed Recombinant SARS-CoV-2 Receptor Binding Domain, RBD203-N1 as a COVID-19 Protein Vaccine Candidate", "rel_date": "2021-08-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.23.457411", - "rel_abs": "We have previously shown that exposure to particulate air pollution, both from natural and anthropogenic sources, alters gene expression in the airways and increases susceptibility to respiratory viral infection. Additionally, we have shown that woodsmoke particulates (WSP) affect responses to influenza in a sex-dependent manner. In the present study, we used human nasal epithelial cells (hNECs) from both sexes to investigate how particulate exposure could modulate gene expression in the context of SARS-CoV-2 infection. We used diesel exhaust particulate (DEP) as well as WSP derived from eucalyptus or red oak wood. HNECs were exposed to particulates at a concentration of 22 g/cm2 for 2 h then immediately infected with SARS-CoV-2 at a MOI (multiplicity of infection) of 0.5. Exposure to particulates had no significant effects on viral load recovered from infected cells. Without particulate exposure, hNECs from both sexes displayed a robust upregulation of antiviral host response genes, though the response was greater in males. However, WSP exposure before infection dampened expression of genes related to the antiviral host response by 72 h post infection. Specifically, red oak WSP downregulated IFIT1, IFITM3, IFNB1, MX1, CCL3, CCL5, CXCL11, CXCL10, and DDX58, among others. After sex stratification of these results, we found that exposure to WSP prior to SARS-CoV-2 infection downregulated anti-viral gene expression in hNECs from females more so than males. These data indicate that WSP, specifically from red oak, alter virus-induced gene expression in a sex-dependent manner and potentially suppress antiviral host defense responses following SARS-CoV-2 infection.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.24.457518", + "rel_abs": "BackgroundSARS-CoV-2 protein subunit vaccines are being evaluated by multiple manufacturers to fill the need for low-cost, easy to scale, safe, and effective COVID-19 vaccines for global access. Vaccine candidates relying on the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein have been the focus of our development program. In this paper, we report on the generation of the RBD203-N1 yeast expression construct, which produces a recombinant protein that when formulated with alum and the TLR-9 agonist, CpG1826 elicits a robust immune response and protection in mice.\n\nMethodThe RBD203-N1 antigen was expressed in the yeast Pichia pastoris X33. After fermentation at the 5 L scale, the protein was purified by hydrophobic interaction chromatography followed by anion exchange chromatography. The purified protein was characterized biophysically and biochemically, and after its formulation, the immunogenicity and efficacy were evaluated in mice.\n\nResults, Conclusions, and SignificanceThe RBD203-N1 production process yielded 492.9 {+/-} 3.0 mg/L of protein in the fermentation supernatant. A two-step purification process produced a >96% pure protein with a recovery rate of 55 {+/-} 3% (total yield of purified protein: 270.5 {+/-} 13.2 mg/L fermentation supernatant). The protein was characterized as a homogeneous monomer with well-defined secondary structure, thermally stable, antigenic, and when adjuvanted on alum and CpG, it was immunogenic and induced robust levels of neutralizing antibodies against SARS-CoV-2 pseudovirus. These characteristics show that this vaccine candidate is well suited for technology transfer with feasibility of its transition into the clinic to evaluate its immunogenicity and safety in humans.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Stephanie A Brocke", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Wen-Hsiang Chen", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Grant T Billings", - "author_inst": "North Carolina State University, Raleigh NC" + "author_name": "Jeroen Pollet", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Sharon A Taft-Benz", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Ulrich Strych", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Neil E Alexis", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Jungsoon Lee", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Mark T Heise", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Zhuyun Liu", + "author_inst": "Baylor College of Medicine" }, { - "author_name": "Ilona Jaspers", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Rakhi Tyagi Kundu", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Leroy Versteeg", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Maria Jose Villar", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Rakesh Adhikari", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Junfei Wei", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Cristina Poveda", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Brian Keegan", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Aaron Oakley Bailey", + "author_inst": "The University of Texas Medical Branch" + }, + { + "author_name": "Yi-Lin Chen", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Portia M Gillespie", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Jason T Kimata", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Bin Zhan", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Peter J Hotez", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Maria Elena Bottazzi", + "author_inst": "Baylor College of Medicine" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "pharmacology and toxicology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.08.25.457626", @@ -629359,41 +629418,133 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.08.19.21262310", - "rel_title": "Predicting SARS-CoV-2 infections for children and youth with single symptom screening", + "rel_doi": "10.1101/2021.08.18.21262258", + "rel_title": "Immunological Insights Into the Therapeutic Roles of CD24Fc Against Severe COVID-19", "rel_date": "2021-08-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.19.21262310", - "rel_abs": "Symptom-based SARS-CoV-2 screening and testing decisions in children have important implications on daycare and school exclusion policies. Single symptoms account for a substantial volume of testing and disruption to in-person learning and childcare, yet their predictive value is unclear, given the clinical overlap with other circulating respiratory viruses and non-infectious etiologies. We aimed to determine the relative frequency and predictive value of single symptoms for paediatric SARS-CoV-2 infections from an Ottawa COVID-19 assessment centre from October 2020 through April 2021.\n\nOverall, 46.3% (n=10,688) of pediatric encounters were for single symptoms, and 2.7% of these tested positive. The most common presenting single symptoms were rhinorrhea (31.8%), cough (17.4%) and fever (14.0%). Among children with high-risk exposures children in each age group, the following single symptoms had a higher proportion of positive SARS-CoV-2 cases compared to no symptoms; fever and fatigue (0-4 years); fever, cough, headache, and rhinorrhea (5-12 years); fever, loss of taste or smell, headache, rhinorrhea, sore throat, and cough (13-17 years). There was no evidence that the single symptom of either rhinorrhea or cough predicted SARS-CoV-2 infections among 0-4 year olds, despite accounting for a large volume (61.1%) of single symptom presentations in the absence of high-risk exposures.\n\nSymptom-based screening needs to be responsive to changes in evidence and local factors, including the expected resurgence of other respiratory viruses following relaxation of social distancing/masking, to reduce infection-related risks in schools and daycare settings.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.18.21262258", + "rel_abs": "BACKGROUNDSARS-CoV-2 causes COVID-19 through direct lysis of infected lung epithelial cells, which releases damage-associated molecular patterns (DAMPs) and induces a pro-inflammatory cytokine milieu causing systemic inflammation. Anti-viral and anti-inflammatory agents have shown limited therapeutic efficacy. Soluble CD24 (CD24Fc) is able to blunt the broad inflammatory response induced by DAMPs in multiple models. A recent randomized phase III trial evaluating the impact of CD24Fc in patients with severe COVID-19 demonstrated encouraging clinical efficacy.\n\nMETHODSWe studied peripheral blood samples obtained from patients enrolled at a single institution in the SAC-COVID trial (NCT04317040) collected before and after treatment with CD24Fc or placebo. We performed high dimensional spectral flow cytometry analysis of peripheral blood mononuclear cells and measured the levels of a broad array of cytokines and chemokines. A systems analytical approach was used to discern the impact of CD24Fc treatment on immune homeostasis in patients with COVID-19.\n\nFINDINGSTwenty-two patients were enrolled, and the clinical characteristics from the CD24Fc vs. placebo groups were matched. Using high-content spectral flow cytometry and network-level analysis, we found systemic hyper-activation of multiple cellular compartments in the placebo group, including CD8+ T cells, CD4+ T cells, and CD56+ NK cells. By contrast, CD24Fc-treated patients demonstrated blunted systemic inflammation, with a return to homeostasis in both NK and T cells within days without compromising the ability of patients to mount an effective anti-Spike protein antibody response. A single dose of CD24Fc significantly attenuated induction of the systemic cytokine response, including expression of IL-10 and IL-15, and diminished the coexpression and network connectivity among extensive circulating inflammatory cytokines, the parameters associated with COVID-19 disease severity.\n\nINTERPRETATIONOur data demonstrates that CD24Fc treatment rapidly down-modulates systemic inflammation and restores immune homeostasis in SARS-CoV-2-infected individuals, supporting further development of CD24Fc as a novel therapeutic against severe COVID-19.\n\nFUNDINGNIH", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Richard J Webster", - "author_inst": "CHEO Research Institute" + "author_name": "No-Joon Song", + "author_inst": "The Ohio State University" }, { - "author_name": "Deepti Reddy", - "author_inst": "CHEO Research Institute" + "author_name": "Carter Allen", + "author_inst": "The Ohio State University" }, { - "author_name": "Mary-Ann Harrison", - "author_inst": "CHEO Research Institute" + "author_name": "Anna E. Vilgelm", + "author_inst": "The Ohio State University" }, { - "author_name": "Ken J Farion", - "author_inst": "CHEO" + "author_name": "Brian P. Riesenberg", + "author_inst": "The Ohio State University" }, { - "author_name": "Jacqueline Willmore", - "author_inst": "Ottawa Public Health" + "author_name": "Kevin P. Weller", + "author_inst": "The Ohio State University" }, { - "author_name": "Michelle Foote", - "author_inst": "Ottawa Public Health" + "author_name": "Kelsi Reynolds", + "author_inst": "The Ohio State University" }, { - "author_name": "Nisha Thampi", - "author_inst": "CHEO" + "author_name": "Karthik B. Chakravarthy", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Amrendra Kumar", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Aastha Khatiwada", + "author_inst": "Medical University of South Carolina" + }, + { + "author_name": "Zequn Sun", + "author_inst": "Medical University of South Carolina" + }, + { + "author_name": "Anjun Ma", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Yuzhou Chang", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Mohamed Yusuf", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Anqi Li", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Cong Zeng", + "author_inst": "The Ohio State University" + }, + { + "author_name": "John P. Evans", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Donna Bucci", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Manuja Gunasena", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Menglin Xu", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Namal P.M. Liyanage", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Chelsea Bolyard", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Maria Velegraki", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Shan-Lu Liu", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Qin Ma", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Martin Devenport", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Yang Liu", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Pan Zheng", + "author_inst": "OncoC4" + }, + { + "author_name": "Carlos D. Malvestutto", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Dongjun Chung", + "author_inst": "The Ohio State University" + }, + { + "author_name": "Zihai Li", + "author_inst": "The Ohio State University" } ], "version": "1", @@ -631485,27 +631636,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.08.17.21262165", - "rel_title": "Interpreting Wastewater SARS-CoV-2 Results using Bayesian Analysis", + "rel_doi": "10.1101/2021.08.17.21262196", + "rel_title": "Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY disease (CLARITY): Statistical analysis plan for a randomised controlled Bayesian adaptive sample size trial", "rel_date": "2021-08-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.17.21262165", - "rel_abs": "Wastewater surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has proven a practical complement to clinical data for assessing community-scale infection trends. Clinical assays, such as the CDC-promulgated N1, N2, and N3 have been used to detect and quantify viral RNA in wastewater but, to date, have not included estimates of reliability of true positive or true negative. Bayes Theorem was applied to estimate Type I and Type II error rates for detections of the virus in wastewater. Conditional probabilities of true positive or true negative were investigated when one assay was used, or multiple assays were run concurrently. Cumulative probability analysis was used to assess the likelihood of true SARS-CoV-2 detection using multiple samples. Results demonstrate highly reliable positive (>0.86 for priors >0.25) and negative (>0.80 for priors = 0.50) results using a single assay. Using N1 and N2 concurrently caused greater reliability (>0.99 for priors <0.05) when results concurred but generated potentially counterintuitive interpretations when results were discordant. Regional wastewater surveillance data was investigated as a means of setting prior probabilities. Probability of true detection with a single marker was investigated using cumulative probability across all combinations of positive and negative results for a set of three samples. Findings using a low (0.11) and uniformed (0.50) initial prior resulted in high probabilities of detection (>0.95) even when a set of samples included one or two negative results, demonstrating the influence of high sensitivity and specificity values. Analyses presented here provide a practical framework for understanding analytical results generated by wastewater surveillance programs.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.17.21262196", + "rel_abs": "The CLARITY trial (Controlled evaLuation of Angiotensin Receptor Blockers for COVID-19 respIraTorY Disease) investigates the effectiveness of angiotensin receptor blockers in addition to standard care compared to placebo (in Indian sites) with standard care in reducing the duration and severity of lung failure in patients with COVID-19. The CLARITY trial is a multi-centre, randomised controlled Bayesian adaptive trial with regular planned analyses where pre-specified decision rules will be assessed to determine whether the trial should be stopped due to sufficient evidence of treatment effectiveness or futility. Here we describe the statistical analysis plan for the trial, and define the pre-specified decision rules, including those that could lead to the trial being halted. The primary outcome is clinical status on a 7-point ordinal scale adapted from the WHO Clinical Progression scale assessed at Day 14. The primary analysis will follow the intention-to-treat principle. A Bayesian adaptive trial design was selected because there is considerable uncertainty about the extent of potential benefit of this treatment.\n\nTrial registrationClinicalTrials.gov, NCT04394117. Registered on 19 May 2020.\n\nhttps://clinicaltrials.gov/ct2/show/NCT04394117\n\nClinical Trial Registry of India: CTRI/2020/07/026831\n\nVersion and revisionsVersion 1.0. No revisions.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Kyle Curtis", - "author_inst": "Hampton Roads Sanitation District" + "author_name": "James McGree", + "author_inst": "Queensland University of Technology" }, { - "author_name": "Raul Alexander Gonzalez", - "author_inst": "Hampton Roads Sanitation District" + "author_name": "Carinna Hockham", + "author_inst": "Imperial College London" + }, + { + "author_name": "Sradha Kotwal", + "author_inst": "University of New South Wales" + }, + { + "author_name": "Arlen Wilcox", + "author_inst": "University of New South Wales" + }, + { + "author_name": "Abhinav Bassi", + "author_inst": "The George Institute for Global Health" + }, + { + "author_name": "Carol Pollock", + "author_inst": "Royal North Shore Hospital" + }, + { + "author_name": "Louise M Burrell", + "author_inst": "University of Melbourne" + }, + { + "author_name": "Tom Snelling", + "author_inst": "The University of Sydney" + }, + { + "author_name": "Vivek Jha", + "author_inst": "University of New South Wales" + }, + { + "author_name": "Meg Jardine", + "author_inst": "University of New South Wales" + }, + { + "author_name": "Mark Jones", + "author_inst": "The University of Sydney" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2021.08.18.21262207", @@ -633011,43 +633198,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.17.21262183", - "rel_title": "The association between immunosuppressants use and COVID-19 adverse outcome: National COVID-19 cohort in South Korea", + "rel_doi": "10.1101/2021.08.17.21262195", + "rel_title": "COVID-19 Incidence and Hospitalization Rates are Inversely Related to Vaccination Coverage Among the 112 Most Populous Counties in the United States", "rel_date": "2021-08-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.17.21262183", - "rel_abs": "PurposeThere is uncertainty of the effect of immunosuppression, including corticosteroids, before COVID-19 infection on COVID-19 outcomes. The aim of this study was to investigate the relationship between prehospitalization immunosuppressants use (exposure), and COVID-19 patient outcomes.\n\nMethodsWe conducted a population-based retrospective cohort study using a nationwide healthcare claims database of South Korea as of May 15, 2020. Confirmed COVID-19 infection in hospitalized individuals aged 40 years or older were included for analysis. We defined exposure variable by using inpatient and outpatient prescription records of immunosuppressants from the database. Our primary outcome was a composite endpoint of all-cause death, intensive care unit (ICU) admission, and mechanical ventilation use. Inverse probability of treatment weighting (IPTW)-adjusted logistic regression analyses were used, to estimate odds ratio (OR) and 95% confidence intervals, comparing immunosuppressants users and non-users.\n\nResultsWe identified 4,349 patients, for which 1,356 were immunosuppressants users and 2,903 were non-users. Patients who used immunosuppressants were at increased odds of the primary outcome of all-cause death, ICU admission and mechanical ventilation use (IPTW OR 1.32; 95% CI: 1.06 - 1.63). Patients who used corticosteroids were at increased odds of the primary outcome (IPTW OR 1.33; 95% CI: 1.07 - 1.64).\n\nConclusionWe support the latest guidelines from the CDC, that people on immunosuppressants are at high risk of severe COVID-19 and immunocompromised people may need booster COVID-19 vaccinations.\n\nFundingYGCs work was partially supported by 2020R1G1A1A01006229 awarded by the National Research Foundation of Korea.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.17.21262195", + "rel_abs": "We tested whether COVID-19 incidence and hospitalization rates during the Delta variant-related surge were inversely related to vaccination coverage among the 112 most populous counties in the United States, together comprising 44 percent of the countrys total population. We measured vaccination coverage as the percent of the county population fully vaccinated as of July 15, 2021. We measured COVID-19 incidence as the number of confirmed cases per 100,000 population during the 14-day period ending August 12, 2021 and hospitalization rates as the number of confirmed COVID-19 admissions per 100,000 population during the same 14-day period. In log-linear regression models, a 10-percentage-point increase in vaccination coverage was associated with a 28.3% decrease in COVID-19 incidence (95% confidence interval, 16.8 - 39.7%), a 44.9 percent decrease in the rate of COVID-19 hospitalization (95% CI, 28.8 - 61.0%), and a 16.6% decrease in COVID-19 hospitalizations per 100 cases (95% CI, 8.4 - 24.8%). Inclusion of demographic covariables, as well as county-specific diabetes prevalence, did not weaken the observed inverse relationship with vaccination coverage. A significant inverse relationship between vaccination coverage and COVID-19 deaths per 100,000 during August 20 - September 16 was also observed. The cumulative incidence of COVID-19 through June 30, 2021, a potential indicator of acquired immunity due to past infection, had no significant relation to subsequent case incidence or hospitalization rates in August. Higher vaccination coverage was associated not only with significantly lower COVID-19 incidence during the Delta surge, but also significantly less severe cases of the disease.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Hyun Joon Shin", - "author_inst": "Lemuel Shattuck Hospital, Massachusetts Department of Public Health" - }, - { - "author_name": "Ronald Chow", - "author_inst": "Hanyang Impact Science Research Center, Seoul, South Korea" - }, - { - "author_name": "Hyerim Noh", - "author_inst": "Department of Statistics, Sookmyung Women's University, Seoul, South Korea" - }, - { - "author_name": "Jongseong Lee", - "author_inst": "School of Social Work, Columbia University, New York, NY, USA" - }, - { - "author_name": "Jihui Lee", - "author_inst": "Department of Healthcare Policy & Research, Weill Cornell Medicine, New York, NY, USA" - }, - { - "author_name": "Young-Geun Choi", - "author_inst": "Department of Statistics, Sookmyung Women's University, Seoul, South Korea" + "author_name": "Jeffrey E Harris", + "author_inst": "Massachusetts Institute of Technology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.20.456972", @@ -634933,43 +635100,71 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.16.21262036", - "rel_title": "Comparison of Antibody Levels in Response to SARS-CoV-2 Infection and Vaccination Type in a Midwestern Cohort", + "rel_doi": "10.1101/2021.08.16.21262149", + "rel_title": "Effectiveness of COVID-19 Vaccines among Incarcerated People in California State Prisons: A Retrospective Cohort Study", "rel_date": "2021-08-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.16.21262036", - "rel_abs": "We present preliminary data in an ongoing observational study reporting SARS-CoV-2 spike protein reactive antibody levels from a convenience cohort of over 250 individuals in Kansas City. We observe stable antibody levels over one year in individuals who recovered from COVID19 infection caused by SARS-CoV-2. By comparison, our data reveals even higher antibody levels from naive individuals vaccinated with Pfizer or Moderna vaccines and slightly lower levels from Johnson & Johnson (J&J) recipients. For all vaccines, inoculation after recovery resulted in higher antibody levels than vaccination alone. Responses to Pfizer and Moderna vaccines decreased over time from high initial levels but at the time of publication remain higher than those for recovered or J&J recipients. Within our limited cohort we only see slight demographic trends including higher antibody levels in recovered female vs. male individuals. Booster doses and breakthrough infections both result in rapid increases in antibody levels.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.16.21262149", + "rel_abs": "BackgroundPrisons and jails are high-risk settings for COVID-19 transmission, morbidity, and mortality. COVID-19 vaccines may substantially reduce these risks, but evidence is needed of their effectiveness for incarcerated people, who are confined in large, risky congregate settings.\n\nMethodsWe conducted a retrospective cohort study to estimate effectiveness of mRNA vaccines, BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna), against confirmed SARS-CoV-2 infections among incarcerated people in California prisons from December 22, 2020 through March 1, 2021. The California Department of Corrections and Rehabilitation provided daily data for all prison residents including demographic, clinical, and carceral characteristics, as well as COVID-19 testing, vaccination status, and outcomes. We estimated vaccine effectiveness using multivariable Cox models with time-varying covariates that adjusted for resident characteristics and infection rates across prisons.\n\nFindingsAmong 60,707 residents in the cohort, 49% received at least one BNT162b2 or mRNA-1273 dose during the study period. Estimated vaccine effectiveness was 74% (95% confidence interval [CI], 64-82%) from day 14 after first dose until receipt of second dose and 97% (95% CI, 88-99%) from day 14 after second dose. Effectiveness was similar among the subset of residents who were medically vulnerable (74% [95% CI, 62-82%] and 92% [95% CI, 74-98%] from 14 days after first and second doses, respectively), as well as among the subset of residents who received the mRNA-1273 vaccine (71% [95% CI, 58-80%] and 96% [95% CI, 67-99%]).\n\nConclusionsConsistent with results from randomized trials and observational studies in other populations, mRNA vaccines were highly effective in preventing SARS-CoV-2 infections among incarcerated people. Prioritizing incarcerated people for vaccination, redoubling efforts to boost vaccination and continuing other ongoing mitigation practices are essential in preventing COVID-19 in this disproportionately affected population.\n\nFundingHorowitz Family Foundation, National Institute on Drug Abuse, Centers for Disease Control and Prevention, National Science Foundation, Open Society Foundation, Advanced Micro Devices.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Laura Remy", - "author_inst": "Stowers Institute for Medical Research" + "author_name": "Elizabeth T Chin", + "author_inst": "Stanford University" + }, + { + "author_name": "David T Leidner", + "author_inst": "California Department of Corrections and Rehabilitation" + }, + { + "author_name": "Yifan Zhang", + "author_inst": "Stanford University" }, { - "author_name": "Chieri Tomomori-Sato", - "author_inst": "Stowers Institute for Medical Research" + "author_name": "Elizabeth Long", + "author_inst": "Stanford University" }, { - "author_name": "Juliana Conkright-Fincham", - "author_inst": "Stowers Institute for Medical Research" + "author_name": "Lea Prince", + "author_inst": "Stanford University" }, { - "author_name": "Leanne M Wiedemann", - "author_inst": "Stowers Institute for Medical Research" + "author_name": "Stephanie J Schrag", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Jennifer R Verani", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Ryan E Wiegand", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Fernando Alarid-Escudero", + "author_inst": "Center for Research and Teaching in Economics (CIDE)" + }, + { + "author_name": "Jeremy D Goldhaber-Fiebert", + "author_inst": "Stanford University" + }, + { + "author_name": "David M Studdert", + "author_inst": "Stanford Law School" }, { - "author_name": "Joan W Conaway", - "author_inst": "University of Texas Southwestern" + "author_name": "Jason R Andrews", + "author_inst": "Stanford University" }, { - "author_name": "Jay R Unruh", - "author_inst": "Stowers Institute for Medical Research" + "author_name": "Joshua A Salomon", + "author_inst": "Stanford University" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.17.21262167", @@ -636747,95 +636942,23 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.08.15.456341", - "rel_title": "Infection and transmission of SARS-CoV-2 and its alpha variant in pregnant white-tailed deer", + "rel_doi": "10.1101/2021.08.16.456444", + "rel_title": "A time irreversible model of nucleotide substitution for the coronavirus evolution", "rel_date": "2021-08-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.15.456341", - "rel_abs": "SARS-CoV-2, a novel Betacoronavirus, was first reported circulating in human populations in December 2019 and has since become a global pandemic. Recent history involving SARS-like coronavirus outbreaks (SARS-CoV and MERS-CoV) have demonstrated the significant role of intermediate and reservoir hosts in viral maintenance and transmission cycles. Evidence of SARS-CoV-2 natural infection and experimental infections of a wide variety of animal species has been demonstrated, and in silico and in vitro studies have indicated that deer are susceptible to SARS-CoV-2 infection. White-tailed deer (Odocoileus virginianus) are amongst the most abundant, densely populated, and geographically widespread wild ruminant species in the United States. Human interaction with white-tailed deer has resulted in the occurrence of disease in human populations in the past. Recently, white-tailed deer fawns were shown to be susceptible to SARS-CoV-2. In the present study, we investigated the susceptibility and transmission of SARS-CoV-2 in adult white-tailed deer. In addition, we examined the competition of two SARS-CoV-2 isolates, representatives of the ancestral lineage A (SARS-CoV-2/human/USA/WA1/2020) and the alpha variant of concern (VOC) B.1.1.7 (SARS-CoV-2/human/USA/CA_CDC_5574/2020), through co-infection of white-tailed deer. Next-generation sequencing was used to determine the presence and transmission of each strain in the co-infected and contact sentinel animals. Our results demonstrate that adult white-tailed deer are highly susceptible to SARS-CoV-2 infection and can transmit the virus through direct contact as well as vertically from doe to fetus. Additionally, we determined that the alpha VOC B.1.1.7 isolate of SARS-CoV-2 outcompetes the ancestral lineage A isolate in white-tailed deer, as demonstrated by the genome of the virus shed from nasal and oral cavities from principal infected and contact animals, and from virus present in tissues of principal infected deer, fetuses and contact animals.", - "rel_num_authors": 19, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.16.456444", + "rel_abs": "SARS-CoV-2 is the cause of the worldwide epidemic of severe acute respiratory syndrome. Evolutionary studies of the virus genome will provide a predictor of the fate of COVID-19 in the near future. Recent studies of the virus genomes have shown that C to U substitutions are overrepresented in the genome sequences of SARS-CoV-2. Traditional time-reversible substitution models cannot be applied to the evolution of SARS-CoV-2 sequences. Therefore, in this study, I propose a new time-irreversible model and a new method for estimating the nucleotide substitution rate of SARS-CoV-2. Computer simulations showed that that the new method gives good estimates. I applied the new method to estimate nucleotide substitution rates of SARS-CoV-2 sequences. The result suggests that the rate of C to U substitution of SARS-Cov-2 is ten times higher than other types of substitutions.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Konner Cool", - "author_inst": "Kansas State University" - }, - { - "author_name": "Natasha N. Gaudreault", - "author_inst": "Kansas State University" - }, - { - "author_name": "Igor Morozov", - "author_inst": "Kansas State University" - }, - { - "author_name": "Jessie D. Trujillo", - "author_inst": "Kansas State University" - }, - { - "author_name": "David A. Meekins", - "author_inst": "Kansas State University" - }, - { - "author_name": "Chester McDowell", - "author_inst": "Kansas State University" - }, - { - "author_name": "Mariano Carossino", - "author_inst": "Louisiana State University" - }, - { - "author_name": "Dashzeveg Bold", - "author_inst": "Kansas State University" - }, - { - "author_name": "Taeyong Kwon", - "author_inst": "Kansas State University" - }, - { - "author_name": "Velmurugan Balaraman", - "author_inst": "Kansas State University" - }, - { - "author_name": "Daniel W. Madden", - "author_inst": "Kansas State University" - }, - { - "author_name": "Bianca Libanori Artiaga", - "author_inst": "Kansas State University" - }, - { - "author_name": "Roman M. Pogranichniy", - "author_inst": "Kansas State University" - }, - { - "author_name": "Gleyder Roman Sosa", - "author_inst": "Kansas State University" - }, - { - "author_name": "Jaimie Henningson", - "author_inst": "Kansas State University" - }, - { - "author_name": "William C. Wilson", - "author_inst": "Kansas State University" - }, - { - "author_name": "Udeni B. R. Balasuriya", - "author_inst": "Louisiana State University" - }, - { - "author_name": "Adolfo Garcia-Sastre", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Juergen A Richt", - "author_inst": "Kansas State University" + "author_name": "Kazuharu Misawa", + "author_inst": "Yokohama City University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "microbiology" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2021.08.16.456470", @@ -638357,43 +638480,155 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.11.21261732", - "rel_title": "COVID-19 in Connecticut institutions of higher education during the 2020-2021 academic year", + "rel_doi": "10.1101/2021.08.10.21261777", + "rel_title": "Testing Denmark: A Danish nationwide surveillance study of COVID-19", "rel_date": "2021-08-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.11.21261732", - "rel_abs": "BackgroundDuring the 2020-2021 academic year, many institutions of higher education reopened to residential students while pursuing strategies to mitigate the risk of SARS-CoV-2 transmission on campus. Reopening guidance emphasized PCR or antigen testing for residential students and social distancing measures to reduce the frequency of close interpersonal contact. Connecticut colleges and universities employed a variety of approaches to reopening campuses to residential students.\n\nMethodsWe used data on testing, cases, and social contact in 18 residential college and university campuses in Connecticut to characterize institutional reopening strategies and COVID-19 outcomes. We compared institutions fall 2020 COVID-19 plans, submitted to the Connecticut Department of Public Health, and analyzed contact rates and COVID-19 outcomes throughout the academic year.\n\nResultsIn census block groups containing residence halls, fall student move-in resulted in a 475% (95% CI 373%-606%) increase in average contact, and spring move-in resulted in a 561% (441%-713%) increase in average contact. The relationship between test frequency and case rate per residential student was complex: institutions that tested students infrequently detected few cases but failed to blunt transmission, while institutions that tested students more frequently detected more cases and prevented further spread. In fall 2020, each additional test per student per week was associated with a reduction of 0.0014 cases per student per week (95% CI: -0.0028, -0.000012). Residential student case rates were associated with higher case rates in the town where the school was located, but it is not possible to determine whether on-campus infections were transmitted to the broader community or vice versa.\n\nConclusionsCampus outbreaks among residential students might be avoided or mitigated by frequent testing, social distancing, and mandatory vaccination. Vaccination rates among residential students and surrounding communities may determine the necessary scale of residential testing programs and social distancing measures during the 2021-2022 academic year.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.10.21261777", + "rel_abs": "BackgroundNational data on the spread of SARS-CoV-2 infection and knowledge on associated risk factors are important for understanding the course of the pandemic. \"Testing Denmark\" is a national large-scale epidemiological surveillance study of SARS-CoV-2 in the Danish population.\n\nMethodsBetween September and October 2020, approximately 1.3 million of 5.8 million Danish citizens (age > 15 years) were randomly invited to fill in an electronic questionnaire covering COVID-19 exposures and symptoms. The prevalence of SARS-CoV-2 antibodies was determined by Point-of Care rapid Test (POCT) distributed to participants home addresses.\n\nFindingsIn total 318,552 participants (24.5% invitees) completed the questionnaire and provided the result of the POCT. Of these, 2,519 (0.79%) were seropositive (median age 55 years) and women were more often seropositive than men, interquartile range (IQR) 42-64, 40.2% males. Of participants with a prior positive Polymerase Chain Reaction (PCR) test (n=1,828), 29.1% were seropositive in the POCT. Seropositivity increased with age irrespective of sex. Elderly participants (>61 years) reported less symptoms and had less frequently been tested for SARS-CoV-2 compared to younger participants. Seropositivity was associated with physical contact with SARS-CoV-2 infected individuals (Risk ratio (RR) 7.43, 95% CI: 6.57-8.41) and in particular household members (RR 17.70, 95% CI: 15.60-20.10). Home care workers had a higher risk of seropositivity (RR 2.09 (95% CI: 1.58-2.78) as compared to office workers. Geographic population density was not associated to seropositivity. A high degree of compliance with national preventive recommendations was reported (e.g., > 80% use of face masks), but no difference was found between seropositive and seronegative participants.\n\nInterpretationThis study provides insight into the immunity of the Danish population seven to eight months after the first COVID-19 case in Denmark. The seroprevalence was lower than expected probably due to a low sensitivity of the POCT used or due to challenges relating to the reading of test results. Occupation or exposure in local communities were major routes of infection. As elderly participants were more often seropositive despite fewer symptoms and less PCR tests performed, more emphasis should be placed on testing this age group.", + "rel_num_authors": 34, "rel_authors": [ { - "author_name": "Olivia Schultes", - "author_inst": "Yale School of Public Health" + "author_name": "Kamille Fogh", + "author_inst": "Department of Cardiology and Department of Emergency Medicine, Herlev and Gentofte Hospital, Denmark" }, { - "author_name": "Victoria Clarke", - "author_inst": "Yale School of Public Health" + "author_name": "Jarl E Strange", + "author_inst": "Department of Cardiology, Copenhagen University Hospital, Herlev and Gentofte" }, { - "author_name": "A David Paltiel", - "author_inst": "Yale School of Public Health" + "author_name": "Bibi FSS Scharff", + "author_inst": "Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Denmark" }, { - "author_name": "Matthew Cartter", - "author_inst": "Connecticut Department of Public Health" + "author_name": "Alexandra RR Eriksen", + "author_inst": "Department of Cardiology, Copenhagen University Hospital, Herlev and Gentofte, Denmark and Department of Emergency Medicine, Copenhagen University Hospital, Her" }, { - "author_name": "Lynn Sosa", - "author_inst": "Connecticut Department of Public Health" + "author_name": "Rasmus B Hasselbalch", + "author_inst": "Department of Cardiology and Department of Emergency Medicine, Herlev and Gentofte Hospital, Denmark" }, { - "author_name": "Forrest W. Crawford", - "author_inst": "Yale School of Public Health" + "author_name": "Henning Bundgaard", + "author_inst": "Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Denmark" + }, + { + "author_name": "Susanne D Nielsen", + "author_inst": "Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Denmark" + }, + { + "author_name": "Charlotte S Joergensen", + "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + }, + { + "author_name": "Christian Erikstrup", + "author_inst": "Department of Clinical Microbiology, Aarhus University Hospital, Aarhus, Denmark" + }, + { + "author_name": "Jakob Norsk", + "author_inst": "Department of Cardiology and Department of Emergency Medicine, Herlev and Gentofte Hospital, Denmark" + }, + { + "author_name": "Pernille B Nielsen", + "author_inst": "Department of Cardiology and Department of Emergency Medicine, Herlev and Gentofte Hospital, Denmark" + }, + { + "author_name": "Jonas H Kristensen", + "author_inst": "Department of Cardiology and Department of Emergency Medicine, Herlev and Gentofte Hospital, Denmark" + }, + { + "author_name": "Lars Oestergaard", + "author_inst": "Department of Infectious Diseases, Aarhus University Hospital, Aarhus, Denmark" + }, + { + "author_name": "Svend Ellermann-Eriksen", + "author_inst": "Department of Clinical Microbiology, Aarhus University Hospital, Aarhus, Denmark" + }, + { + "author_name": "Berit Andersen", + "author_inst": "University Research Clinic for Cancer Screening, Randers Regional Hospital, Randers, Denmark" + }, + { + "author_name": "Henrik Nielsen", + "author_inst": "Department of Infectious Diseases, Aalborg University Hospital, Aalborg, Denmark" + }, + { + "author_name": "Isik S Johansen", + "author_inst": "Department of Infectious Diseases, Odense University Hospital, Odense, Denmark" + }, + { + "author_name": "Lothar Wiese", + "author_inst": "Department of Infectious Diseases, Zealand University Hospital, Roskilde, Denmark" + }, + { + "author_name": "Lone Simonsen", + "author_inst": "Department of Science and Environment, University of Roskilde, Denmark" + }, + { + "author_name": "Thea K Fischer", + "author_inst": "Department of Clinical Research, North Zealand Hospital, Hilleroed, Denmark" + }, + { + "author_name": "Fredrik Folke", + "author_inst": "Copenhagen Emergency Medical Services, Copenhagen, Denmark" + }, + { + "author_name": "Freddy Lippert", + "author_inst": "Copenhagen Emergency Medical Services, Copenhagen, Denmark" + }, + { + "author_name": "Sisse R Ostrowski", + "author_inst": "Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Denmark" + }, + { + "author_name": "Thomas Benfield", + "author_inst": "Department of Infectious Diseases, Copenhagen University Hospital, Amager and Hvidovre, Hvidovre, Denmark" + }, + { + "author_name": "Kaare Moelbak", + "author_inst": "Statens Serum Institut, Copenhagen, Denmark" + }, + { + "author_name": "Steen Ethelberg", + "author_inst": "Statens Serum Institut, Copenhagen Denmark" + }, + { + "author_name": "Anders Koch", + "author_inst": "Department of Infectious Diseases, Copenhagen University Hospital, Rigshospitalet, Denmark and Statens Serum Institut, Copenhagen Denmark" + }, + { + "author_name": "Ute W Sonksen", + "author_inst": "Statens Serum Institut, Copenhagen Denmark" + }, + { + "author_name": "Anne-Marie Vangsted", + "author_inst": "Statens Serum Institut, Copenhagen Denmark" + }, + { + "author_name": "Tyra Grove Krause", + "author_inst": "Statens Serum Institut, Copenhagen Denmark" + }, + { + "author_name": "Anders Formsgaard", + "author_inst": "Statens Serum Institut, Copenhagen Denmark" + }, + { + "author_name": "Henrik Ullum", + "author_inst": "Statens Serum Institut, Copenhagen Denmark" + }, + { + "author_name": "Robert Skov", + "author_inst": "Statens Serum Institut, Copenhagen Denmark" + }, + { + "author_name": "Kasper Iversen", + "author_inst": "Department of Cardiology, Copenhagen University Hospital, Herlev and Gentofte, Denmark and Department of Emergency Medicine, Copenhagen University Hospital, Her" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.12.21261991", @@ -640267,51 +640502,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.12.21261970", - "rel_title": "A highly efficient T-cell immunoassay provides assessment of B cell help function of SARS-CoV-2 specific memory CD4+ T cells", + "rel_doi": "10.1101/2021.08.12.21261974", + "rel_title": "Data analysis of COVID-19 wave peaks in relation to latitude and temperature for multiple nations", "rel_date": "2021-08-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.12.21261970", - "rel_abs": "The B cell help function of CD4+ T cells may serve as an immunologic correlate of protective adaptive immunity. The quantitative assessment of the B cell help potential of CD4+ T cells is limited by the lack of suitable antigen-specific functional assays. Here, we describe a highly efficient antigen-specific T-B co-cultures for quantitative measurement of T-dependent B cell responses. Using Mycobacterium tuberculosis specific setup, we show that early priming and activation of CD4+ T cells is important for the mutualistic collaboration between antigen-specific T and B cells, which could be achieved by supplementing the co-cultures with autologous monocytes. We further show that monocyte-derived growth factors provide the impetus for productive T-B collaboration by conferring optimal survivability in the cultured cells. This study provides first evidence of C-type lectin domain family 11 member A (CLEC11A/SCGF) as an essential growth factor for B cell survival. Importantly, we demonstrate the successful translation of monocyte supplemented T-B co-cultures in qualitative assessment of SARS-CoV-2 specific memory CD4+ T cells by quantifying several correlates of productive T-B cross-talk like plasma cell output, secreted antibody, antibody secreting cells and IL21 secreting T cells. Thus, the method described here can provides qualitative assessment of SARS-CoV-2 spike CD4+ T cells after natural infection and can be applied to assess the B cell help function of memory CD4+ T cells generated in response to COVID-19 vaccine.\n\nOne sentence summaryQualitative assessment of antigen-specific CD4+ T cells for T-dependent B cell responses.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.12.21261974", + "rel_abs": "It was observed that the multiple peaks of coronavirus disease-19 (COVID-19) appeared in different seasons in different countries. There were countries where the COVID-19 peak occurred during extremely low temperatures, such as Norway, Canada and on the other hand there were countries with high-temperature ranges such as Brazil, India, UAE. Most of the high-latitude countries received their outbreak in winter and most of the countries near the equator mark the outbreak during the summer. Most of the biological organisms have their growth dependant on the temperature, and hence we explored that if there is any relation of temperature versus COVID-19 outbreak in the particular country. It was also seen that people are not behaving differently during the peak of the COVID-19 wave, hence it was important to know whether the COVID-19 virus has evolved or the global temperature variation caused these multiple peaks. This work focuses on finding the effect of temperature variation on the COVID-19 outbreak. We used Levenberg-Marquardt technique to find the correlation between the temperature at which COVID-19 outbreak peaks and the latitude of the particular country. We found that between the temperature range of 14 {degrees}C to 20 {degrees}C spread of the COVID-19 is minimal. Based on our results we can also say that the COVID-19 outbreak is seen in lower temperature (0 {degrees}C to 13 {degrees}C) ranges as well as in the higher temperature ranges (21 {degrees}C to 35 {degrees}C). The current data analysis will help the authorities to manage their resources in advance to prepare for any further outbreaks that might occur in the COVID-19 or even in the next pandemic.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Asgar Ansari", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" - }, - { - "author_name": "Shilpa Sachan", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" - }, - { - "author_name": "Bimal Prasad Jit", - "author_inst": "Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, 110029, India" - }, - { - "author_name": "Ashok Sharma", - "author_inst": "Department of Biochemistry, All India Institute of Medical Sciences, New Delhi, 110029, India" - }, - { - "author_name": "Poonam Coshic", - "author_inst": "Department of Transfusion Medicine, All India Institute of Medical Sciences, New Delhi, 110029, India" - }, - { - "author_name": "Alessandro Sette", - "author_inst": "La Jolla Institute for Immunology, La Jolla, CA, 92037, USA" + "author_name": "Mayuri Jain", + "author_inst": "APSIT" }, { - "author_name": "Daniela Weiskopf", - "author_inst": "La Jolla Institute For Allergy & Immunology" + "author_name": "Sukhada Aloni", + "author_inst": "APSIT" }, { - "author_name": "Nimesh Gupta", - "author_inst": "Vaccine Immunology Laboratory, National Institute of Immunology, New Delhi, 110067, India" + "author_name": "Pravin Adivarekar", + "author_inst": "APSIT" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "health informatics" }, { "rel_doi": "10.1101/2021.08.10.21261855", @@ -642629,61 +642844,41 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.08.10.455737", - "rel_title": "Molecular mimicry between Spike and human thrombopoietin may induce thrombocytopenia in COVID-19", + "rel_doi": "10.1101/2021.08.11.455903", + "rel_title": "Structural Differences In 3C-like protease (Mpro) From SARS-CoV and SARS-CoV-2: Molecular Insights For Drug Repurposing Against COVID-19 Revealed by Molecular Dynamics Simulations.", "rel_date": "2021-08-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.10.455737", - "rel_abs": "SARS-CoV-2 causes COVID-19, a disease curiously resulting in varied symptoms and outcomes, ranging from asymptomatic to fatal. Autoimmunity due to cross-reacting antibodies resulting from molecular mimicry between viral antigens and host proteins may provide an explanation. We computationally investigated molecular mimicry between SARS-CoV-2 Spike and known epitopes. We discovered molecular mimicry hotspots in Spike and highlight two examples with tentative autoimmune potential and implications for understanding COVID-19 complications. We show that a TQLPP motif in Spike and thrombopoietin shares similar antibody binding properties. Antibodies cross-reacting with thrombopoietin may induce thrombocytopenia, a condition observed in COVID-19 patients. Another motif, ELDKY, is shared in multiple human proteins such as PRKG1 and tropomyosin. Antibodies cross-reacting with PRKG1 and tropomyosin may cause known COVID-19 complications such as blood-clotting disorders and cardiac disease, respectively. Our findings illuminate COVID-19 pathogenesis and highlight the importance of considering autoimmune potential when developing therapeutic interventions to reduce adverse reactions.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.11.455903", + "rel_abs": "A recent fatal outbreak of novel coronavirus SARS-CoV-2, identified preliminary as a causative agent for series of unusual pneumonia cases in Wuhan city, China has infected more than 20 million individuals with more than 4 million mortalities. Since, the infection crossed geographical barriers, the WHO permanently named the causing disease as COVID-2019 by declaring it a pandemic situation. SARS-CoV-2 is an enveloped single-stranded RNA virus causing a wide range of pathological conditions from common cold symptoms to pneumonia and fatal severe respiratory syndrome. Genome sequencing of SARS-CoV-2 has revealed 96% identity to the bat coronavirus and 79.6% sequence identity to the previous SARS-CoV. The main protease (known as 3C-like proteinase/ Mpro) plays a vital role during the infection with the processing of replicase polyprotein thus offering an attractive target for therapeutic interventions. SARS-CoV and SARS-CoV-2 Mpro shares 97% sequence identity, with 12 variable residues but none of them present in the catalytic and substrate binding site. With the high level of sequence and structural similarity and absence of any drug/vaccine against SARS-CoV-2, drug repurposing against Mpro is an effective strategy to combat COVID-19. Here, we report a detailed comparison of SARS-CoV-2 Mpro with SARS-CoV Mpro using molecular dynamics simulations to assess the impact of 12 divergent residues on the molecular microenvironment of Mpro. A structural comparison and analysis is made on how these variable residues affects the intra-molecular interactions between key residues in the monomer and biologically active dimer form of Mpro. The present MD simulations study concluded the change in microenvironment of active-site residues at the entrance (T25, T26, M49 and Q189), near the catalytic region (F140, H163, H164, M165 and H172) and other residues in substrate binding site (V35T, N65S, K88R and N180K) due to 12 mutation incorporated in the SARS-CoV-2 Mpro. It is also evident that SARS-CoV-2 dimer is more stable and less flexible state compared to monomer which may be due to these variable residues, mainly F140, E166 and H172 which are involved in dimerization. This also warrants a need for inhibitor design considering the more stable dimer form. The mutation accumulated in SARS-CoV-2 Mpro indirectly reconfigures the key molecular networks around the active site conferring a potential change in SARS-CoV-2, thus posing a challenge in drug repurposing SARS drugs for COVID-19. The new networks and changes in microenvironment identified by our work might guide attempts needed for repurposing and identification of new Mpro inhibitors.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Janelle Nunez-Castilla", - "author_inst": "Florida International University" - }, - { - "author_name": "Vitalii Stebliankin", - "author_inst": "Florida International University" - }, - { - "author_name": "Prabin Baral", - "author_inst": "Florida International University" - }, - { - "author_name": "Christian A Balbin", - "author_inst": "Florida International University" - }, - { - "author_name": "Masrur Sobhan", - "author_inst": "Florida International University" + "author_name": "Dhaval Patel", + "author_inst": "Institute of Advanced Research" }, { - "author_name": "Trevor Cickovski", - "author_inst": "Florida International University" + "author_name": "Meet Parmar", + "author_inst": "Institute of Advanced Research" }, { - "author_name": "Ananda M Mondal", - "author_inst": "Florida International University" + "author_name": "Ritik Thumar", + "author_inst": "Institute of Advanced Research" }, { - "author_name": "Giri Narasimhan", - "author_inst": "Florida International University" + "author_name": "Bhumi Patel", + "author_inst": "NA" }, { - "author_name": "Prem Chapagain", - "author_inst": "Florida International University" + "author_name": "Mohd. Athar", + "author_inst": "Center for Chemical Biology and Therapeutics, InStem" }, { - "author_name": "Kalai Mathee", - "author_inst": "Florida International University" - }, - { - "author_name": "Jessica Siltberg-Liberles", - "author_inst": "Florida International University" + "author_name": "Prakash Jha", + "author_inst": "Central University of Gujarat, Gandhinagar" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", "category": "bioinformatics" }, @@ -644174,115 +644369,59 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2021.08.10.455627", - "rel_title": "An ultrapotent neutralizing bispecific antibody with broad spectrum against SARS-CoV-2 variants", - "rel_date": "2021-08-10", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.10.455627", - "rel_abs": "In spite of the successful development of effective countermeasures against Covid-19, variants have and will continue to emerge that could compromise the efficacy of currently approved neutralizing antibodies and vaccines. Consequently, novel and more efficacious agents are urgently needed. We have developed a bispecific antibody, 2022, consisting of two antibodies, 2F8 and VHH18. 2F8 was isolated from our proprietary fully synthetic human IDEAL (Intelligently Designed and Engineered Antibody Library)-VH/VL library and VHH18 is a single domain antibody isolated from IDEAL-nanobody library. 2022 was constructed by attaching VHH18 to the C-terminal of Fc of 2F8. 2022 binds two non-overlapping epitopes simultaneously on the RBD of the SARS-CoV-2 spike protein and blocks the binding of RBD to human angiotensin-converting enzyme 2 (ACE2). 2022 potently neutralizes SARS-CoV-2 and all of the variants tested in both pseudovirus and live virus assays, including variants carrying mutations known to resist neutralizing antibodies approved under EUA and that reduce the protection efficiency of current effective vaccines. The half-maximum inhibitory concentration (IC50) of 2022 is 270 pM, 30 pM, 20 pM, and 1 pM, for wild-type, alpha, beta, and delta pseudovirus, respectively. In the live virus assay, 2022 has an IC50 of 26.4 pM, 13.3 pM, and 88.6 pM, for wild-type, beta, and delta live virus, respectively. In a mouse model of SARS-CoV-2, 2022 showed strong prophylactic and therapeutic effects. A single administration of 2022 intranasal (i.n.) or intraperitoneal (i.p.) 24 hours before virus challenge completely protected all mice from bodyweight loss, as compared with up to 20% loss of bodyweight in placebo treated mice. In addition, the lung viral titers were undetectable (FRNT assay) in all mice treated with 2022 either prophylactically or therapeutically, as compared with around 1x105 pfu/g lung tissue in placebo treated mice. In summary, bispecific antibody 2022 showed potent binding and neutralizing activity across a variety of SARS-CoV-2 variants and could be an attractive weapon to combat the ongoing waves of the COVID-19 pandemic propagated mainly by variants, especially, the much more contagious delta variant.", - "rel_num_authors": 24, + "rel_doi": "10.1101/2021.08.08.21257737", + "rel_title": "Did Low Risk Perception Mediate the COVID-19 Second Wave in Bangladesh? A Cross-sectional Study on Risk Perception and Preventive Practice", + "rel_date": "2021-08-09", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.08.21257737", + "rel_abs": "ObjectiveThis study assessed the risk perception and preventive behavioral practice towards COVID-19 just prior to the second wave of corona, as well as the impact of perceived risk on preventive practices.\n\nDesign, setting, participants, and outcome measuresA cross-sectional study was conducted between December 2020 and January 2021, involving 1382 respondents aged 18 years and above from all eight divisions in Bangladesh. We used multiple linear regression to identify sociodemographic predictors of risk perception and multiple logistic regression to determine the relationship between risk perception and preventive practice.\n\nResultsLow risk perception regarding COVID-19 was present among one-fifth of the respondents (19.8%). Younger age, being male, low education, single marital status, and rural residence were significantly associated with a low perceived risk of COVID-19. Hand washing and wearing mask were practiced by 80% and 67% of respondents, respectively. A low prevalence was noticed for social distancing (31%), avoiding social gathering (31%), and covering face while coughing/sneezing (18%). Furthermore, respondents with a high risk perception were found to be more likely than those with a low risk perception to practice all recommended COVID-19 preventive behaviors-hand washing (OR=2.4, 95% CI=1.5, 3.7), mask use (OR=3.4, 95% CI=2.3, 5), social distancing (OR=3.7, 95% CI=2.4, 5.6), sanitizer use (OR=2.7, 95% CI=1.8, 4.1), avoiding gathering (OR=2.3, 95% CI=1.6, 3.5), avoid touching face and mouth (OR=2.8, 95% CI=1.5, 5.3), and covering mouth while coughing/sneezing (OR=7, 95% CI=3.6, 13.4).\n\nConclusionConsiderable number of Bangladeshi adults had low risk perception and low practice of some vital COVID-19 preventive behaviors before the onset of second wave of corona. All preventive practices were also influenced by respondents risk perception. This highlights the importance of strengthening and optimizing risk communication strategy even when the number of corona cases are low.\n\nSTRENGTHS AND LIMITATIONS OF THIS STUDYO_LIThe study explored the perceived risk and preventive practices for COVID-19 in Bangladesh right before the recent onset COVID-19 second wave in the South Asian region, and included a larger sample size than previous studies.\nC_LIO_LIUnlike most other studies on COVID-19 risk perception that used online surveys, this study administered a face-to-face data collection from both urban and rural settings across all the eight divisions of Bangladesh.\nC_LIO_LIThis is the first study in Bangladesh that investigated the effect of perceived risk of COVID-19 on the practice of a range of preventive behaviors, and used an analytical approach to quantify risk perception.\nC_LIO_LIRespondents self-reported information on COVID-19 preventive behavior practice is subject to be influenced by recall and desirability bias.\nC_LIO_LIThe study was unable to explore the respondents frequency and adherence to preventive practices, as well as the influence of psychological factors on preventive behaviors.\nC_LI", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Hui Zhang", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Haohui Huang", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Rong Li", - "author_inst": "Institute of Human Virology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China 510080" - }, - { - "author_name": "Lu Zhang", - "author_inst": "Guangzhou Customs District Technology Center, Guangzhou,Guangdong, China 510700" - }, - { - "author_name": "Zhiwei Wang", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Jiaping Li", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Junyou Chen", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Huafei Su", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Dandan Zheng", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" + "author_name": "Farah Naz Rahman", + "author_inst": "Centre for Injury Prevention and Research Bangladesh (CIPRB)" }, { - "author_name": "Ziqi Su", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" + "author_name": "AKM Fazlur Rahman", + "author_inst": "Centre for Injury Prevention and Research Bangladesh (CIPRB)" }, { - "author_name": "Li Wang", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" + "author_name": "Shah Monir Hossain", + "author_inst": "Divisional Public Health Advisory Committee, Directorate Generalof Health Services (DGHS)" }, { - "author_name": "Chunping Deng", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" + "author_name": "Mohammad Abul Faiz", + "author_inst": "Divisional Public Health Advisory Committee, Directorate Generalof Health Services (DGHS)" }, { - "author_name": "shujun Pei", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Shenghua Zhu", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Chan Li", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Yaochang Yuan", - "author_inst": "Institute of Human Virology, Zhongshan School of Medicine, Sun Yat-sen University, Guangzhou, Guangdong, China 510080" - }, - { - "author_name": "Haitao Yue", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" - }, - { - "author_name": "Yanqun Wang", - "author_inst": "Guangzhou Institute of Respiratory Health" - }, - { - "author_name": "Xiaobo Li", - "author_inst": "Guangzhou Customs District Technology Center, Guangzhou,Guangdong, China 510700" + "author_name": "Abu Jamil Faisel", + "author_inst": "Divisional Public Health Advisory Committee, Directorate Generalof Health Services (DGHS)" }, { - "author_name": "Cuihua Liu", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" + "author_name": "ATM Iqbal Anwar", + "author_inst": "Divisional Public Health Advisory Committee, Directorate Generalof Health Services (DGHS)" }, { - "author_name": "Jinchen Yu", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" + "author_name": "Moudud Hossain", + "author_inst": "Divisional Public Health Advisory Committee, Directorate Generalof Health Services (DGHS)" }, { - "author_name": "Hui Zhang", - "author_inst": "Sun Yat-sen University" + "author_name": "Tarek Mahmud Hussain", + "author_inst": "Divisional Public Health Advisory Committee, Directorate Generalof Health Services (DGHS)" }, { - "author_name": "Shengfeng Li", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" + "author_name": "Tania Mahbub", + "author_inst": "Divisional Public Health Advisory Committee, Directorate Generalof Health Services (DGHS)" }, { - "author_name": "Xianming Huang", - "author_inst": "Bio-Thera Solutions, Guangzhou, Guangdong, China 510530" + "author_name": "Liaquat Ali", + "author_inst": "Divisional Public Health Advisory Committee, Directorate Generalof Health Services (DGHS)" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2021.08.06.21261702", @@ -646288,75 +646427,291 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2021.08.06.455491", - "rel_title": "High genetic barrier to escape from human polyclonal SARS-CoV-2 neutralizing antibodies", + "rel_doi": "10.1101/2021.08.04.21261547", + "rel_title": "Deconvoluting complex correlates of COVID19 severity with local ancestry inference and viral phylodynamics: Results of a multiomic pandemic tracking strategy", "rel_date": "2021-08-08", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.08.06.455491", - "rel_abs": "The number and variability of the neutralizing epitopes targeted by polyclonal antibodies in SARS-CoV-2 convalescent and vaccinated individuals are key determinants of neutralization breadth and, consequently, the genetic barrier to viral escape. Using chimeric viruses and antibody-selected viral mutants, we show that multiple neutralizing epitopes, within and outside the viral receptor binding domain (RBD), are variably targeted by polyclonal plasma antibodies and coincide with sequences that are enriched for diversity in natural SARS-CoV-2 populations. By combining plasma-selected spike substitutions, we generated synthetic polymutant spike proteins that resisted polyclonal antibody neutralization to a similar degree as currently circulating variants of concern (VOC). Importantly, by aggregating VOC-associated and plasma-selected spike substitutions into a single polymutant spike protein, we show that 20 naturally occurring mutations in SARS-CoV-2 spike are sufficient to confer near-complete resistance to the polyclonal neutralizing antibodies generated by convalescents and mRNA vaccine recipients. Strikingly however, plasma from individuals who had been infected and subsequently received mRNA vaccination, neutralized this highly resistant SARS-CoV-2 polymutant, and also neutralized diverse sarbecoviruses. Thus, optimally elicited human polyclonal antibodies against SARS-CoV-2 should be resilient to substantial future SARS-CoV-2 variation and may confer protection against future sarbecovirus pandemics.", - "rel_num_authors": 14, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.04.21261547", + "rel_abs": "The SARS-CoV-2 pandemic has differentially impacted populations of varied race, ethnicity and socioeconomic status. Admixture mapping and local ancestry inference represent powerful tools to examine genetic risk within multi-ancestry genomes independent of these confounding social constructs. Here, we leverage a pandemic tracking strategy in which we sequence viral and host genomes and transcriptomes from 1,327 nasopharyngeal swab residuals and integrate them with digital phenotypes from electronic health records. We demonstrate over-representation of individuals possessing Oceanian and Indigenous American ancestry in SARS-CoV-2 positive populations. Genome-wide-association disaggregated by admixture mapping reveals regions of chromosomes 5 and 14 associated with COVID19 severity within African and Oceanic local ancestries, respectively, independent of overall ancestry fraction. Phylodynamic tracking of consensus viral genomes reveals no association with disease severity or inferred ancestry. We further present summary data from a multi-omic investigation of human-leukocyte-antigen (HLA) typing, nasopharyngeal microbiome and human transcriptomics that reveal metagenomic and HLA associations with severe COVID19 infection. This work demonstrates the power of multi-omic pandemic tracking and genomic analyses to reveal distinct epidemiologic, genetic and biological associations for those at the highest risk.", + "rel_num_authors": 68, "rel_authors": [ { - "author_name": "Fabian Schmidt", - "author_inst": "Rockefeller University" + "author_name": "V N Parikh", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine" }, { - "author_name": "Yiska Weisblum", - "author_inst": "Rockefeller University" + "author_name": "A G Ioannidis", + "author_inst": "Department of Biomedical Data Science and Institute for Computational and Mathematical Engineering, Stanford University" }, { - "author_name": "Magdalena Rutkowska", - "author_inst": "Rockefeller University" + "author_name": "D Jimenez-Morales", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" }, { - "author_name": "Daniel Poston", - "author_inst": "Rockefeller University" + "author_name": "J E Gorzynski", + "author_inst": "Department of Genetics and Department of Medicine, Stanford University School of Medicine" }, { - "author_name": "Justin Da Silva", - "author_inst": "Rockefeller University" + "author_name": "H N De Jong", + "author_inst": "Department of Genetics and Department of Medicine, Stanford University School of Medicine" }, { - "author_name": "Fengwen Zhang", - "author_inst": "Rockefeller University" + "author_name": "X Liu", + "author_inst": "Institute for Computational and Mathematical Engineering, Stanford University" }, { - "author_name": "Eva Bednarski", - "author_inst": "Rockefeller University" + "author_name": "J Roque", + "author_inst": "Department of Medicine, Stanford University School of Medicine" }, { - "author_name": "Alice Cho", - "author_inst": "Rockefeller University" + "author_name": "V P Cepeda-Espinoza", + "author_inst": "Department of Biomedical Data Science, Stanford University" }, { - "author_name": "Dennis Schaefer-Babajew", - "author_inst": "Rockefeller University" + "author_name": "K Osoegawa", + "author_inst": "Histocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Stanford Health Care" }, { - "author_name": "Christian Gaebler", - "author_inst": "Rockefeller University" + "author_name": "C Hughes", + "author_inst": "Department of Genetics, Stanford University School of Medicine" }, { - "author_name": "Marina Caskey", - "author_inst": "Rockefeller University" + "author_name": "S C Sutton", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine" }, { - "author_name": "Michel C. Nussenzweig", - "author_inst": "Rockefeller University" + "author_name": "N Youlton", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine" }, { - "author_name": "Theodora Hatziioannou", - "author_inst": "Rockefeller University" + "author_name": "R Joshi", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine" }, { - "author_name": "Paul D. Bieniasz", - "author_inst": "Rockefeller University" + "author_name": "D Amar", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine" + }, + { + "author_name": "Y Tanigawa", + "author_inst": "Department of Biomedical Data Science, Stanford University" + }, + { + "author_name": "D Russo", + "author_inst": "Department of Statistics, Stanford University" + }, + { + "author_name": "J Wong", + "author_inst": "Department of Statistics, Stanford University" + }, + { + "author_name": "J T Lauzon", + "author_inst": "Department of Aeronautics and Astronautics, Stanford University" + }, + { + "author_name": "J Edelson", + "author_inst": "Department of Biomedical Data Science, Stanford University" + }, + { + "author_name": "D M Montserrat", + "author_inst": "Department of Biomedical Data Science, Stanford University" + }, + { + "author_name": "Y Kwon", + "author_inst": "Department of Biomedical Data Science, Stanford University" + }, + { + "author_name": "S Rubinacci", + "author_inst": "Swiss Institute of Bioinformatics and Department of Computational Biology, University of Lausanne, Lausanne, Switzerland" + }, + { + "author_name": "O Delaneau", + "author_inst": "Swiss Institute of Bioinformatics and Department of Computational Biology, University of Lausanne, Lausanne, Switzerland" + }, + { + "author_name": "L Cappello", + "author_inst": "Department of Statistics, Stanford University" + }, + { + "author_name": "J Kim", + "author_inst": "Department of Biology, Stanford University" + }, + { + "author_name": "M J Shoura", + "author_inst": "Departments of Pathology & Genetics, Stanford University School of Medicine" + }, + { + "author_name": "A N Raja", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" + }, + { + "author_name": "N Watson", + "author_inst": "Department of Pathology, Stanford University School of Medicine" + }, + { + "author_name": "N Hammond", + "author_inst": "Department of Pathology, Stanford University School of Medicine" + }, + { + "author_name": "E Spiteri", + "author_inst": "Department of Pathology, Stanford University School of Medicine" + }, + { + "author_name": "K C Mallempati", + "author_inst": "Histocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Stanford Health Care" + }, + { + "author_name": "G Montero-Martin", + "author_inst": "Histocompatibility & Immunogenetics Laboratory, Stanford Blood Center, Stanford Health Care" + }, + { + "author_name": "J Christle", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" + }, + { + "author_name": "J Kim", + "author_inst": "Departments of Statistics and Biomedical Data Science, Stanford University" + }, + { + "author_name": "A Kirillova", + "author_inst": "Medical Scientist Training Program, University of Pittsburgh and Carnegie Mellon University" + }, + { + "author_name": "K Seo", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" + }, + { + "author_name": "Y Huang", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" + }, + { + "author_name": "C Zhao", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" + }, + { + "author_name": "S Moreno-Grau", + "author_inst": "Department of Biomedical Data Science, Stanford University" + }, + { + "author_name": "S Hershman", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" + }, + { + "author_name": "K P Dalton", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" + }, + { + "author_name": "J Zhen", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" + }, + { + "author_name": "J Kamm", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "K Bhatt", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "A Isakova", + "author_inst": "Department of Bioengineering, Stanford University" + }, + { + "author_name": "M Morri", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "T Ranganath", + "author_inst": "Department of Medicine, Stanford University School of Medicine" + }, + { + "author_name": "C A Blish", + "author_inst": "Department of Medicine, Stanford University School of Medicine" + }, + { + "author_name": "A J Rogers", + "author_inst": "Department of Medicine, Stanford University School of Medicine" + }, + { + "author_name": "K Nadeau", + "author_inst": "Department of Medicine and Sean N. Parker Center for Allergy and Asthma Research, Stanford University School of Medicine" + }, + { + "author_name": "S Yang", + "author_inst": "Department of Emergency Medicine, Stanford University School of Medicine" + }, + { + "author_name": "A Blomkalns", + "author_inst": "Department of Emergency Medicine, Stanford University School of Medicine, Stanford, CA, USA" + }, + { + "author_name": "R OHara", + "author_inst": "Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, CA, USA" + }, + { + "author_name": "N F Neff", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "C DeBoever", + "author_inst": "Takeda Development Center Americas, Inc" + }, + { + "author_name": "S Szalma", + "author_inst": "Takeda Development Center Americas, Inc" + }, + { + "author_name": "M T Wheeler", + "author_inst": "Department of Medicine, Division of Cardiovascular Medicine, Stanford University" + }, + { + "author_name": "K Farh", + "author_inst": "Illumina, Inc." + }, + { + "author_name": "G P Schroth", + "author_inst": "Illumina, Inc." + }, + { + "author_name": "P Febbo", + "author_inst": "Illumina, Inc." + }, + { + "author_name": "F deSouza", + "author_inst": "Illumina, Inc." + }, + { + "author_name": "M Fernandez-Vina", + "author_inst": "Department of Pathology, Stanford University School of Medicine" + }, + { + "author_name": "A Kistler", + "author_inst": "Chan Zuckerberg Biohub" + }, + { + "author_name": "J Palacios", + "author_inst": "Departments of Statistics and Biomedical Data Science, Stanford University" + }, + { + "author_name": "B A Pinsky", + "author_inst": "Departments of Pathology and Medicine, Stanford University School of Medicine" + }, + { + "author_name": "C D Bustamante", + "author_inst": "Department of Biomedical Data Science, Stanford University" + }, + { + "author_name": "M A Rivas", + "author_inst": "Department of Biomedical Data Science, Stanford University" + }, + { + "author_name": "E A Ashley", + "author_inst": "Department of Genetics and Dept of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine" } ], "version": "1", "license": "cc_no", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.08.06.21261713", @@ -647882,53 +648237,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.05.21261642", - "rel_title": "The unique evolutionary dynamics of the SARS-CoV-2 Delta variant", + "rel_doi": "10.1101/2021.08.05.21259465", + "rel_title": "Distinct age-specific SARS-CoV-2 IgG decay kinetics following natural infection", "rel_date": "2021-08-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.05.21261642", - "rel_abs": "The SARS-Coronavirus-2 (SARS-CoV-2) driven pandemic was first recognized in late 2019, and the first few months of its evolution were relatively clock-like, dominated mostly by neutral substitutions. In contrast, the second year of the pandemic was punctuated by the emergence of several variants that bore evidence of dramatic evolution. Here, we compare and contrast evolutionary patterns of various variants, with a focus on the recent Delta variant. Most variants are characterized by long branches leading to their emergence, with an excess of non-synonymous substitutions occurring particularly in the Spike and Nucleocapsid proteins. In contrast, the Delta variant that is now becoming globally dominant, lacks the signature long branch, and is characterized by a step-wise evolutionary process that is ongoing. Contrary to the \"star-like\" topologies of other variants, we note the formation of several distinct clades within Delta that we denote as clades A-E. We find that sequences from the Delta D clade are dramatically increasing in frequency across different regions of the globe. Delta D is characterized by an excess of non-synonymous mutations, mostly occurring in ORF1a/b, some of which occurred in parallel in other notable variants. We conclude that the Delta surge these days is composed almost exclusively of Delta D, and discuss whether selection or random genetic drift has driven the emergence of Delta D.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.05.21259465", + "rel_abs": "BackgroundAntibody responses to SARS-CoV-2 can be observed as early as 14 days post-infection, but little is known about the stability of antibody levels over time. Here we evaluate the long-term stability of anti-SARS-CoV-2 IgG antibodies following infection with SARS-CoV-2 in 402 adult donors.\n\nMethodsWe performed a multi-center study carried out at Plasma Donor Centers in the city of Heidelberg (Plasmazentrum Heidelberg, Germany) and Munich (Plasmazentrum Munchen, Germany). We present anti-S/N and anti-N IgG antibody levels in prospective serum samples collected up to 403 days post recovery from SARS-CoV-2 infected individuals.\n\nResultsThe cohort includes 402 adult donors (185 female, 217 male; 17 - 68 years of age) where anti-SARS-CoV-2 IgG levels were measured in plasma samples collected between 18- and 403-days post SARS-CoV-2 infection. A linear mixed effects model demonstrated IgG decay rates that decrease over time ({chi}2=176.8, p<0.00001) and an interaction of time*age {chi} ({chi}2=10.0, p<0.005)), with those over 60+ years showing the highest baseline IgG levels and the fastest rate of IgG decay. Baseline viral neutralization assays demonstrated that serum IgG levels correlated with in vitro neutralization capacity in 91% of our cohort.\n\nConclusionLong-term antibody levels and age-specific antibody decay rates suggest the potential need for age-specific vaccine booster guidelines to ensure long term vaccine protection against SARS-CoV-2 infection.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Adi Stern", - "author_inst": "Tel-Aviv University" + "author_name": "Calvin P Sjaarda", + "author_inst": "Queen's University" }, { - "author_name": "Shay Fleishon", - "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health and Sheba Medical Center" + "author_name": "Emily Moslinger", + "author_inst": "Queen's University" }, { - "author_name": "Talia Kustin", - "author_inst": "Tel Aviv University" + "author_name": "Kyla Tozer", + "author_inst": "Queen's University" }, { - "author_name": "Edo Dotan", - "author_inst": "Tel Aviv University" + "author_name": "Robert I Colautti", + "author_inst": "Queen's University" }, { - "author_name": "Michal Mandelboim", - "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health and Sheba Medical Center" + "author_name": "Samira Kheitan", + "author_inst": "Queen's University" }, { - "author_name": "Oran Erster", - "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health and Sheba Medical Center" + "author_name": "Robyn Meurant", + "author_inst": "NSF Health Sciences" }, { - "author_name": "- Israel Consortium of SARS-CoV-2 sequencing", - "author_inst": "" + "author_name": "Stefanie Van Cleaf", + "author_inst": "Biomex GmbH" }, { - "author_name": "Ella Mendelson", - "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health and Sheba Medical Center" + "author_name": "Ali Ardakani", + "author_inst": "Novateur Ventures Inc" }, { - "author_name": "Orna Mor", - "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health and Sheba Medical Center" + "author_name": "Oliver Bosnjak", + "author_inst": "Biomex GmbH" }, { - "author_name": "Neta Zuckerman", - "author_inst": "Central Virology Laboratory, Public Health Services, Ministry of Health and Sheba Medical Center" + "author_name": "Abdi Ghaffari", + "author_inst": "Queen's University" + }, + { + "author_name": "Prameet M Sheth", + "author_inst": "Queen's University" } ], "version": "1", @@ -649944,41 +650303,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.08.03.21261365", - "rel_title": "Population normalisation in wastewater-based epidemiology for improved understanding of SARS-CoV-2 prevalence: A multi-site study", + "rel_doi": "10.1101/2021.08.04.21261360", + "rel_title": "Quantifying the ongoing epidemic of disability after covid-19 in the UK population aged under 35 years; secondary analysis of the ONS Infection Survey", "rel_date": "2021-08-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.03.21261365", - "rel_abs": "This paper aims to determine whether population normalisation significantly alters the SARS-CoV-2 trends revealed by wastewater-based epidemiology, and whether it is beneficial and/or necessary to provide an understanding of prevalence from wastewater SARS-CoV-2 concentrations. It uses wastewater SARS-CoV-2 data collected from 394 sampling sites, and implements normalisation based on concentrations of a) ammoniacal nitrogen, and b) orthophosphate. Wastewater SARS-CoV-2 metrics are evaluated at a site and aggregated level against three indicators prevalence, based on positivity rates from the Office for National Statistics Coronavirus Infection Survey and test results reported by NHS Test and Trace. Normalisation is shown to have little impact on the overall trends in the wastewater SARS-CoV-2 data on average. However, significant variability between the impact of population normalisation at different sites, which is not evident from previous WBE studies focussed on a single site, is also revealed. Critically, it is demonstrated that while the impact of normalisation on SARS-CoV-2 trends is small on average, it is not reasonable to conclude that it is always insignificant. When averaged across many sites, normalisation strengthens the correlation between wastewater SARS-CoV-2 data and indicators of prevalence; however, confidence in the improvement is low. Lastly, it is noted that most data were collected during periods of national lockdown and/or local restrictions, and thus the impacts and benefits of population normalisation are expected to be higher when normal travel habits resume.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.04.21261360", + "rel_abs": "Web-based survey and anecdotal evidence suggest that many people infected with covid-19 go on to develop long covid (symptoms persisting for more than 12 weeks) despite mild initial disease. There is particular concern that this epidemic is unfolding in the younger population where vaccination rates are low. The Covid Infection Survey (CIS) has recently published estimates of the proportion of people with long covid whose daily activities are affected a little or a lot.\n\nThis paper focuses on the population aged under 35 years and uses the term disabling long covid to describe those with symptoms lasting more than 12 weeks and daily activities limited a lot. By applying the CIS estimates to confirmed infections, with age breakdown from mid-2020 population estimates, this paper reports a first estimate of the cases of disabling long covid seeded from confirmed covid-19 infections to July 31st 2021.\n\nResults suggest there will approximately 39,000 cases of disabling long covid in those aged under 35 seeded by Covid-19 infections confirmed to July 31st. There is a need for rapid action to prevent Covid-19 infection in the younger population and support those struggling with Long Covid-related disability.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Chris Sweetapple", - "author_inst": "University of Exeter" - }, - { - "author_name": "Matthew John Wade", - "author_inst": "Department of Health and Social Care" - }, - { - "author_name": "Jasmine M. S. Grimsley", - "author_inst": "Department of Health and Social Care" - }, - { - "author_name": "Joshua T. Bunce", - "author_inst": "Department of Health and Social Care" - }, - { - "author_name": "Peter Melville-Shreeve", - "author_inst": "University of Exeter" - }, - { - "author_name": "Albert Chen", - "author_inst": "University of Exeter" + "author_name": "Nicola Spiers", + "author_inst": "Royal Society of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -652278,51 +652617,75 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.08.03.21261438", - "rel_title": "COVID-19 impact on stroke admissions during France's first epidemic peak: an exhaustive, nationwide, observational study", + "rel_doi": "10.1101/2021.08.02.21261509", + "rel_title": "Sensitive and multiplexed RNA detection with Cas13 droplets and kinetic barcoding", "rel_date": "2021-08-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.03.21261438", - "rel_abs": "Background and PurposeThe COVID-19 pandemic continues to have great impacts on the care of non-COVID-19 patients. This was especially true during the first epidemic peak in France, which coincided with the national lockdown (17 March 2020 to 10 May 2020). Patients with serious and urgent disease like stroke may have experienced a degradation of care, or may have been hesitant to seek healthcare during this period. The aim of this study was to identify, on a national level, whether a decrease in stroke admissions occurred in spring 2020, by analyzing the evolution of all stroke admissions in France from January 2019 to June 2020.\n\nMethodsWe conducted a nationwide cohort study using the French national database of hospital admissions (PMSI) to extract exhaustive data on all hospitalizations in France with at least one stroke diagnosis between 1 January 2019 and 30 June 2020. The primary endpoint was the difference in the slope gradients of stroke hospitalizations between pre-epidemic, epidemic peak and post-epidemic periods. Modeling was carried out using Bayesian techniques.\n\nResultsStroke hospitalizations dropped from 10 March 2020 (slope gradient: -11.70), and began to rise again from 22 March (slope gradient: 2.090) to 7 May. In total, there were 23 873 stroke admissions during the period March-April 2020, compared to 29 263 at the same period in 2019, representing a decrease of 18.42%. The percentage change was -15.63%, - 25.19%, -18.62% for ischemic strokes, transient ischemic attacks, and hemorrhagic strokes, respectively. In spatial models of French departments, the incidence of COVID-19 explained the ratio of stroke hospitalizations.\n\nConclusionsStroke hospitalizations in France experienced a decline during the first lockdown period, which cannot be explained by a sudden change in stroke incidence. This decline is therefore likely to be a direct, or indirect, result of the COVID-19 pandemic.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.02.21261509", + "rel_abs": "Rapid and sensitive quantification of RNA is critical for detecting infectious diseases and identifying disease biomarkers. Recent direct detection assays based on CRISPR-Cas13a1-4 avoid reverse transcription and DNA amplification required of gold-standard PCR assays5, but these assays have not yet achieved the sensitivity of PCR and are not easily multiplexed to detect multiple viruses or variants. Here we show that Cas13a acting on single target RNAs loaded into droplets exhibits stochastic nuclease activity that can be used to enable sensitive, rapid, and multiplexed virus quantification. Using SARS-CoV-2 RNA as the target and combinations of CRISPR RNA (crRNA) that recognize different parts of the viral genome, we demonstrate that reactions confined to small volumes can rapidly achieve PCR-level sensitivity. By tracking nuclease activity within individual droplets over time, we find that Cas13a exhibits rich kinetic behavior that depends on both the target RNA and crRNA. We demonstrate that these kinetic signatures can be harnessed to differentiate between different human coronavirus species as well as SARS-CoV-2 variants within a single droplet. The combination of high sensitivity, short reaction times, and multiplexing makes this droplet-based Cas13a assay with kinetic barcoding a promising strategy for direct RNA identification and quantification.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Cl\u00e9mence Risser", - "author_inst": "H\u00f4pitaux Universitaires de Strasbourg" + "author_name": "Sungmin Son", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Pierre Tran Ba Loc", - "author_inst": "H\u00f4pitaux Universitaires de Strasbourg" + "author_name": "Amy Lyden", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Florence Binder-Foucard", - "author_inst": "H\u00f4pitaux Universitaires de Strasbourg" + "author_name": "Jeffrey Shu", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Thibaut Fabacher", - "author_inst": "H\u00f4pitaux Universitaires de Strasbourg" + "author_name": "Stephanie I Stephens", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Hassina Lefevre", - "author_inst": "H\u00f4pitaux Universitaires de Strasbourg" + "author_name": "Parinaz Fozouni", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Claire Sauvage", - "author_inst": "H\u00f4pitaux Universitaires de Strasbourg" + "author_name": "Gavin J Knott", + "author_inst": "Monash University" }, { - "author_name": "Erik Sauleau", - "author_inst": "H\u00f4pitaux Universitaires de Strasbourg" + "author_name": "Dylan C.J. Smock", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Val\u00e9rie Wolff", - "author_inst": "H\u00f4pitaux Universitaires de Strasbourg" + "author_name": "Tina Y Liu", + "author_inst": "University of California, Berkeley" + }, + { + "author_name": "Daniela Boehm", + "author_inst": "Gladstone Institutes" + }, + { + "author_name": "Camille Simoneau", + "author_inst": "Gladstone Institutes" + }, + { + "author_name": "Renuka Kumar", + "author_inst": "Gladstone Institutes" + }, + { + "author_name": "Jennifer A Doudna", + "author_inst": "UC Berkeley/HHMI" + }, + { + "author_name": "Melanie Ott", + "author_inst": "Gladstone Institutes" + }, + { + "author_name": "Daniel A Fletcher", + "author_inst": "UC Berkeley" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.08.03.21261496", @@ -654084,35 +654447,91 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.08.02.21260750", - "rel_title": "Hydroxychloroquine Prophylaxis against Coronavirus Disease-19: Practice Outcomes among Health-Care Workers", - "rel_date": "2021-08-04", + "rel_doi": "10.1101/2021.07.30.21261274", + "rel_title": "High parental vaccine motivation at a neighborhood-based vaccine and testing site serving a predominantly Latinx community", + "rel_date": "2021-08-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.08.02.21260750", - "rel_abs": "BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a rapidly emerging virus responsible for the ongoing Covid-19 pandemic with no known effective prophylaxis. We investigated whether hydroxychloroquine(HCQ) could prevent SARS CoV-2 in healthcare workers(HCW) at high-risk of exposure.\n\nMethodThis voluntary observational study for the prevention and treatment of COVID-19 was conducted at a tertiary care center, from 12th June to 12th October 2020(total 16 weeks). All consented asymptomatic HCWs of CIMS hospital were administered 400 mg HCQ twice a day on day one followed by 400 mg once weekly to be taken with meals up to 16 weeks. Data collected included OPD registration, risk assessment, medical and family history (related to COVID), physical examination and vitals, pulse oximetry, ECG (pre and post HCQ), drug adherence, side effects, adverse drug reactions.\n\nResultThe study enrolled 927 full-time, hospital-based HCWs ((including doctors, nurses, paramedical, lab technicians, sanitary workers and others), of whom 731(78.85%) initially started HCQ while 196 (21.14%) did not volunteer. The median age and weight of the study population was 27.5 years and 69.5 kg respectively. No major associated co-morbidities were present in these HCWs. There was an increased trend towards non adherence to HCQ with each proceeding week more so after week 11. Of the 731 HCWs taking HCQ a total of 167(22.8%) tested COVID positive at different intervals of time as against 30 HCW (15.3%) out of 196 not taking HCQ. The rate of COVID-19 positive was statistically significantly higher in the HCWs taking HCQ (p=0.0220; 95% CI: 1.14% to 12.94%), as compared to those not on HCQ. Thus HCQ was not prophylactically effective against COVID 19 infection. No participants in this study experienced grade 3 or 4 adverse events. No significant difference in the median of ECG changes in QTc between pre and post HCQ administration of 46 HCWs was observed.\n\nConclusionsThis clinical study did not detect a reduction in SARS CoV-2 transmission with prophylactic administration of 400 mg/HCQ in HCWs. All participants who did contract SARSCoV-2 were either asymptomatic or had mild disease courses with full recoveries. All adverse events were self-limiting and no serious cardiovascular events were reported with use of HCQ. In the absence of robust data, it seems premature to recommend HCQ as a prophylactic panacea for COVID-19.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.30.21261274", + "rel_abs": "PurposeTo understand vaccine attitudes of Latinx parents highly impacted by COVID-19. Methods. In April 2021, we surveyed parents about their attitudes for COVID-19 vaccination of their children at a community-based outdoor testing/vaccination site serving predominantly low-income, Latinx persons in San Francisco.\n\nResultsAmong 1,033 parents (75% Latinx), 92% would \"definitely\" or \"probably\" vaccinate their children. Vaccine hesitancy was higher for younger children; concerns included side effects and impacts on fertility. Doctors and community organizations were noted as trusted sources of information, including among vaccine-hesitant parents.\n\nConclusionLatinx parents accessing neighborhood-based COVID-19 testing/vaccination services are highly motivated to vaccinate their children for COVID-19.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Parloop Bhatt", - "author_inst": "Care Institute of Medical Sciences" + "author_name": "Jamie Naso", + "author_inst": "Unidos en Salud, San Francisco" }, { - "author_name": "Vishva Patel", - "author_inst": "Care Institute of Medical Sciences" + "author_name": "Susy Rojas", + "author_inst": "San Francisco Latino Task Force on COVID-19" }, { - "author_name": "Prachi Shah", - "author_inst": "Care Institute of Medical Sciences" + "author_name": "James Peng", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Keyur Parikh", - "author_inst": "Care Institute of Medical Sciences" + "author_name": "Carina Marquez", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Maria Contreras", + "author_inst": "Unidos en Salud, San Francisco" + }, + { + "author_name": "Edgar Castellanos", + "author_inst": "Unidos en Salud, San Francisco" + }, + { + "author_name": "Susana Rojas", + "author_inst": "San Francisco Latino Task Force on COVID-19" + }, + { + "author_name": "Luis Rubio", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Diane Jones", + "author_inst": "Unidos en Salud, San Francisco" + }, + { + "author_name": "Jon Jacobo", + "author_inst": "San Francisco Latino Task Force on COVID-19" + }, + { + "author_name": "Douglas Black", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Valerie Tulier-Laiwa", + "author_inst": "San Francisco Latino Task Force on COVID-19" + }, + { + "author_name": "Jacqueline Martinez", + "author_inst": "Unidos en Salud, San Francisco" + }, + { + "author_name": "Gabriel Chamie", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Genay Pilarowski", + "author_inst": "Unidos en Salud, San Francisco" + }, + { + "author_name": "Joseph Derisi", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Diane Havlir", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Maya Petersen", + "author_inst": "University of California, Berkeley" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.07.30.21261234", @@ -656086,43 +656505,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.29.21261314", - "rel_title": "Rapid comparative evaluation of SARS-CoV-2 rapid point-of-care antigen tests", + "rel_doi": "10.1101/2021.07.30.21261347", + "rel_title": "Wastewater based surveillance system to detect SARS-CoV-2 genetic material for countries with on-site sanitation facilities: an experience from Bangladesh", "rel_date": "2021-08-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.29.21261314", - "rel_abs": "BackgroundCurrently, more than 500 different AgPOCTs for SARS-CoV-2 diagnostics are on sale (July 2021), for many of which no data about sensitivity other than self-acclaimed values by the manufacturers are available. In many cases these do not reflect real-life diagnostic sensitivities. Therefore, manufacturer-independent quality checks of available AgPOCTs are needed, given the potential implications of false-negative results.\n\nObjectiveThe objective of this study was to develop a scalable approach for direct comparison of the analytical sensitivities of commercially available SARS-CoV-2 antigen point-of-care tests (AgPOCTs) in order to rapidly identify poor performing products.\n\nMethodsWe present a methodology for quick assessment of the sensitivity of SARS-CoV-2 lateral flow test stripes suitable for quality evaluation of many different products. We established reference samples with high, medium and low SARS-CoV-2 viral loads along with a SARS-CoV-2 negative control sample. Test samples were used to semi-quantitatively assess the analytical sensitivities of 32 different commercial AgPOCTs in a head-to-head comparison.\n\nResultsAmong 32 SARS-CoV-2 AgPOCTs tested, we observe sensitivity differences across a broad range of viral loads ([~]7.0*108 to [~]1.7*105 SARS-CoV-2 genome copies per ml). 23 AgPOCTs detected the Ct25 test sample ([~]1.4*106 copies/ ml), while only five tests detected the Ct28 test sample ([~]1.7*105 copies/ ml). In the low range of analytical sensitivity we found three saliva spit tests only delivering positive results for the Ct21 sample ([~]2.2*107 copies/ ml). Comparison with published data support our AgPOCT ranking. Importantly, we identified an AgPOCT offered in many local drugstores and supermarkets, which did not reliably recognize the sample with highest viral load (Ct16 test sample with [~]7.0*108 copies/ ml) leading to serious doubts in its usefulness in SARS-CoV-2 diagnostics.\n\nConclusionThe rapid sensitivity assessment procedure presented here provides useful estimations on the analytical sensitivities of 32 AgPOCTs and identified a widely-spread AgPOCT with concerningly low sensitivity.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.30.21261347", + "rel_abs": "The presence of SARS-CoV-2 genetic materials in wastewater has become a matter of grave for many countries of the world. Wastewater based epidemiology, in this context, emerged as an important tool in developed countries where proper sewage system is available. Due to the recent shift in the spread of the infection from urban to rural areas, it is now equally important to develop a similar mechanism for rural areas as well. Considering the urgency of the issue a study was conducted in 14 districts of Bangladesh and a total of 238 sewage samples were collected in two different periods from December 2020 to January 2021. We are the first to propose a surveillance system for both urban and rural areas where a proper sewage system is absent. Based on RT-PCR analysis of the water samples, in more than 92% of cases, we found the presence of the SARS-COV-2 gene (ORF1ab, N, and Internal Control-IC). The trend of Ct value varies for different study locations. The spread of genetic material for on-site ({Delta}m = 0.0749) sanitation system was found more prominent than that of off-site sewage system ({Delta}m = 0.0219); which indicated the shift of genetic material from urban to rural areas. Wastewater samples were also measured for physicochemical parameters, including pH (6.30 - 12.50) and temperature (22.10 - 32.60) {o}C. The highest viral titer of 1975 copy/mL in sewage sample was observed in a sample collected from the isolation ward of the SARS-COV-2 hospital. Additionally, a correlation was found between bacterial load and SARS-CoV-2 genetic materials. The results indicated the association of increased Ct values with decreasing number of patients and vice versa. The findings reported in this paper contributed to the field of wastewater-based epidemiology dealing with SARS-COV-2 surveillance for developing countries where proper sewage system is absent and highlighting some of the challenges associated with this approach in such settings.\n\nHighlightsO_LIDevelopment of wastewater-based surveillance system based on on-site sanitation system for developing countries.\nC_LIO_LIAssociation of different environmental parameters with the presence of SARS CoV-2 genetic material in wastewater.\nC_LIO_LIPrediction of the viral concentration of sewage system using viral load and copy number parameter.\nC_LI\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=122 SRC=\"FIGDIR/small/21261347v2_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (25K):\norg.highwire.dtl.DTLVardef@1f7847dorg.highwire.dtl.DTLVardef@11b2c93org.highwire.dtl.DTLVardef@10b9fe1org.highwire.dtl.DTLVardef@2d9e8d_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Anna Denzler", - "author_inst": "Center for Molecular Biology of Heidelberg University (ZMBH), Heidelberg, Germany" + "author_name": "Md. Jakariya", + "author_inst": "Department of Environmental Science and Management, North South University, Bashundhara, Dhaka-1229, Bangladesh" }, { - "author_name": "Max L. Jacobs", - "author_inst": "Center for Molecular Biology of Heidelberg University (ZMBH), Heidelberg, Germany" + "author_name": "Firoz Ahmed", + "author_inst": "Department of Microbiology, Noakhali Science and Technology University, Noakhali-3814, Bangladesh" }, { - "author_name": "Viktoria Witte", - "author_inst": "Center for Molecular Biology of Heidelberg University (ZMBH), Heidelberg, Germany" + "author_name": "Md. Aminul Islam", + "author_inst": "Department of Microbiology, Noakhali Science and Technology University, Noakhali-3814, Bangladesh" }, { - "author_name": "Paul Schnitzler", - "author_inst": "Department of Infectious Diseases, Virology, Heidelberg University Hospital, Heidelberg, Germany" + "author_name": "Tanvir Ahmed", + "author_inst": "Department of Civil Engineering, Bangladesh University of Engineering and Technology, Dhaka-1000" }, { - "author_name": "Claudia M. Denkinger", - "author_inst": "Department of Infectious Diseases, Division of Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany" + "author_name": "Abdullah Al Marzan", + "author_inst": "Department of Biochemistry and Molecular Biology, Shahjalal University of Science and Technology, Sylhet-3114, Bangladesh" }, { - "author_name": "Michael Knop", - "author_inst": "Center for Molecular Biology of Heidelberg University (ZMBH), Heidelberg, Germany; German Cancer Research Center (DKFZ), Heidelberg, Germany" + "author_name": "Maqsud Hossain", + "author_inst": "Department of Biochemistry and Microbiology, North South University, Bashundhara, Dhaka-1229, Bangladesh" + }, + { + "author_name": "Hasan Mahmud Reza", + "author_inst": "Department of Pharmaceutical Sciences, North South University, Bashundhara, Dhaka 1229, Bangladesh" + }, + { + "author_name": "Prosun Bhattacharya", + "author_inst": "COVID-19 Research@KTH, Department of Sustainable Development, Environmental Science and Engineering, KTH Royal Institute of Technology, Teknikringen 10B, SE-100" + }, + { + "author_name": "Ahmed Hossain", + "author_inst": "Department of Public Health, North South University, Bashundhara, Dhaka-1229, Bangladesh" + }, + { + "author_name": "Turasa Nahla", + "author_inst": "Department of Environmental Science and Management, North South University, Bashundhara, Dhaka-1229, Bangladesh" + }, + { + "author_name": "Newaz Mohammed Bahadur", + "author_inst": "Department of Applied Chemistry and Chemical Engineering, Noakhali Science and Technology University, Noakhali 3814, Bangladesh" + }, + { + "author_name": "Mohammad Nayeem Hasan", + "author_inst": "Department of Statistics, Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh" + }, + { + "author_name": "Md. Tahmidul Islam", + "author_inst": "WaterAid Bangladesh, Dhaka 1213, Bangladesh" + }, + { + "author_name": "Md. Foysal Hossen", + "author_inst": "Department of Microbiology, Noakhali Science and Technology University, Noakhali-3814, Bangladesh" + }, + { + "author_name": "Md. Didar ul Alam", + "author_inst": "Professor and Vice-Chancellor, Noakhali Science and Technology University, Noakhali 3814, Bangladesh" + }, + { + "author_name": "Nowrin Mou", + "author_inst": "WaterAid Bangladesh, Dhaka 1213, Bangladesh" + }, + { + "author_name": "Hasin Jahan", + "author_inst": "WaterAid Bangladesh, Dhaka 1213, Bangladesh" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.08.01.21261101", @@ -658232,79 +658695,79 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.29.21261156", - "rel_title": "Performance of Immunoglobulin G Serology on Finger Prick Capillary Dried Blood Spot Samples to Measure SARS-CoV-2 Humoral Immunogenicity", + "rel_doi": "10.1101/2021.07.29.21261196", + "rel_title": "Prospective examination of mental health in university students during the COVID-19 pandemic", "rel_date": "2021-07-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.29.21261156", - "rel_abs": "ImportanceMeasuring humoral immunogenicity of Severe Acute Respiratory Syndrome Coronavirus 2 vaccines and finding population-level correlates of protection against coronavirus disease presents an immediate challenge to public health practitioners.\n\nObjectiveTo study the diagnostic accuracy and predictive value of finger prick capillary dried blood spot samples tested using an anti-immunoglobulin G (IgG) serology assay to measure SARS-CoV-2 seropositivity and the humoral immunogenicity of COVID-19 vaccination.\n\nDesign, Setting and ParticipantsThis cross-sectional study enrolled participants (n= 644) who had paired DBS and serum samples collected by finger prick and venipuncture, respectively, in British Columbia, Canada between January 12th, 2020 and May 21st, 2021. Samples were tested by a multiplex electrochemiluminescence assay for SARS-CoV-2 anti-Spike (S), -Nucleocapsid (N) and -receptor binding domain (RBD) IgG reactivity using a Meso Scale Discovery (MSD) platform. Additionally, unpaired DBS samples (n= 6,706) that were collected in the province during the same time period were included for analysis of SARS-CoV-2 anti-N IgG reactivity.\n\nExposureCollection of a capillary dried blood spot by finger prick alone or paired with serum by venipuncture.\n\nOutcomeHumoral immune response to SARS-CoV-2 measured by detection of anti-S, -N or - RBD IgG.\n\nResultsIn comparison to a paired-serum reference, dried blood spot samples possess a sensitivity of 80% (95% CI: 61%-91%) and specificity of 97% (95% CI: 95%-98%). Receiver operator characteristic curve analysis (ROC) found that participant DBS samples tested for anti-SARS-CoV-2 IgG by MSD V-PLEX COVID-19 Coronavirus Panel 2 assay accurately classify SARS-CoV-2 seroconversion at an 88% percent rate, AUC= 88% (95% CI: 81%-96%). Modelling found that a dried blood spot-based testing approach has a high positive predictive value (98% [95% CI: 98%-99%]) in a theoretical population with seventy-five percent COVID-19 vaccine coverage. At lower vaccine coverages of fifteen and forty-five percent, the tests positive predictive value decreased, and the negative predictive value increased.\n\nConclusionWe demonstrate that dried blood spot collected samples, when tested using an electrochemiluminescence assay, provide a valid alternative to traditional venipuncture and should be considered to reliably detect SARS-CoV-2 seropositivity.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is the diagnostic accuracy and predictive value of immunoglobulin G serology on finger prick capillary dried blood spot samples to measure SARS-CoV-2 humoral immunogenicity?\n\nFindingsIn comparison to a paired-serum reference, dried blood spot samples tested for anti-SARS-CoV-2 IgG possess a sensitivity of 80% (95% CI: 61%-91%) and specificity of 97% (95% CI: 95%-98%). Dried blood spot testing has a positive predictive value of 98% (95% CI: 98%-99%) when modelled in a theoretical population with COVID-19 vaccine coverage of seventy-five percent.\n\nMeaningDried blood spot samples have equal diagnostic accuracy to serum collected by venipuncture when tested by electrochemiluminescence assay and should be considered to reliably detect SARS-CoV-2 seropositivity.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.29.21261196", + "rel_abs": "BackgroundThe impact of changing social restrictions on the mental health of students during the COVID-19 pandemic warrants exploration.\n\nAimsTo prospectively examine changes to university students mental health during the pandemic.\n\nMethodsStudents completed repeated online surveys at three time points (October 2020 (baseline), February 2021, March 2021) to explore relationships between demographic and psychological factors (loneliness and positive mood) and mental health outcomes (depression, anxiety, and stress).\n\nResultsA total of 893 students participated. Depression and anxiety levels were higher at all timepoints than pre-pandemic normative data (p<.001). Scores on all mental health measures were highest in February, with depression and anxiety remaining significantly higher in March than baseline. Female students and those with previous mental health disorders were at greatest risk of poor mental health outcomes. Lower positive mood and greater loneliness at baseline were associated with greater depression and anxiety at follow-ups. Baseline positive mood predicted improvement of depression and anxiety at follow-ups.\n\nConclusionDepression and anxiety were significantly higher than pre-pandemic norms, with female students and those with previous mental health difficulties being at greatest risk. Given these elevated rates, universities should ensure adequate support is available to meet potentially increased demand for services.", "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Aidan M Nikiforuk", - "author_inst": "The University of British Columbia" + "author_name": "Ru Jia", + "author_inst": "University of Nottingham" }, { - "author_name": "Brynn McMillan", - "author_inst": "The University of British Columbia" + "author_name": "Holly Knight", + "author_inst": "University of Nottingham" }, { - "author_name": "Sofia R Bartlett", - "author_inst": "The University of British Columbia" + "author_name": "Kieran Ayling", + "author_inst": "University of Nottingham" }, { - "author_name": "Ana Citlali Marquez", - "author_inst": "The University of British Columbia" + "author_name": "Carol Coupland", + "author_inst": "University of Nottingham" }, { - "author_name": "Tamara Pidduck", - "author_inst": "BCCDC" + "author_name": "Jessia Corner", + "author_inst": "University of Nottingham" }, { - "author_name": "Jesse Kustra", - "author_inst": "BCCDC" + "author_name": "Chris Denning", + "author_inst": "University of Nottingham" }, { - "author_name": "David M Goldfarb", - "author_inst": "Children's and Women's Health Centre of British Columbia" + "author_name": "Jonathan Ball", + "author_inst": "University of Nottingham" }, { - "author_name": "Vilte Barakauskas", - "author_inst": "The University of British Columbia" + "author_name": "Kirsty Bolton", + "author_inst": "University of Nottingham" }, { - "author_name": "Graham Sinclair", - "author_inst": "The University of British Columbia" + "author_name": "Joanne R Morling", + "author_inst": "University of Nottingham" }, { - "author_name": "David M Patrick", - "author_inst": "The University of British Columbia" + "author_name": "Grazziela Figueredo", + "author_inst": "University of Nottingham" }, { - "author_name": "Manish Sadarangani", - "author_inst": "The University of British Columbia" + "author_name": "David Ed Morris", + "author_inst": "University of Nottingham" }, { - "author_name": "Gina S Ogilvie", - "author_inst": "University of British Columbia" + "author_name": "Patrick Tighe", + "author_inst": "University of Nottingham" }, { - "author_name": "Muhammad Morshed", - "author_inst": "The University of British Columbia" + "author_name": "Armando Villalon", + "author_inst": "University of Nottingham" }, { - "author_name": "Inna Sekirov", - "author_inst": "The University of British Columbia" + "author_name": "Holly Blake", + "author_inst": "University of Nottingham" }, { - "author_name": "Agatha N Jassem", - "author_inst": "The Univeristy of British Columbia" + "author_name": "kavita vedhara", + "author_inst": "University of Nottingham" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.07.29.21261324", @@ -659814,63 +660277,43 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.07.26.21261162", - "rel_title": "Diagnostic performance of a novel digital immunoassay (RapidTesta SARS-CoV-2): a prospective observational study with 1,127 nasopharyngeal samples", + "rel_doi": "10.1101/2021.07.29.454385", + "rel_title": "3D printed cobalt-chromium-molybdenum porous superalloy with superior antiviral activity", "rel_date": "2021-07-30", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.26.21261162", - "rel_abs": "IntroductionDigital immunoassays are generally regarded as superior tests for the detection of infectious disease pathogens, but there have been insufficient data concerning SARS-CoV-2 immunoassays.\n\nMethodsWe prospectively evaluated a novel digital immunoassay (RapidTesta SARS-CoV-2). Two nasopharyngeal samples were simultaneously collected for antigen tests and RT-PCR. Real-time RT-PCR for SARS-CoV-2, using a method developed by the National Institute of Infectious Diseases, Japan, served as the reference RT-PCR method.\n\nResultsDuring the study period, 1,127 nasopharyngeal samples (symptomatic patients: 802, asymptomatic patients: 325) were evaluated. For digital immunoassay antigen tests, the sensitivity was 78.3% (95% CI: 67.3%-87.1%) and the specificity was 97.6% (95% CI: 96.5%-98.5%). When technicians visually analyzed the antigen test results, the sensitivity was 71.6% (95% CI: 59.9%-81.5%) and the specificity was 99.2% (95% CI: 98.5%-99.7%). Among symptomatic patients, the sensitivity was 89.4% (95% CI; 76.9%-96.5%) with digital immunoassay antigen tests, and 85.1% (95% CI; 71.7%-93.8%) with visually analyzed the antigen test, respectively.\n\nConclusionsThe findings indicated that RapidTesta SARS-CoV-2 analysis with the DIA device had sufficient analytical performance for the detection of SARS-CoV-2 in nasopharyngeal samples. When positive DIA results are recorded without a visually recognizable red line at the positive line location on the test cassette, additional RT-PCR evaluation should be performed.", - "rel_num_authors": 11, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.29.454385", + "rel_abs": "COVID-19 pandemic and associated supply-chain disruptions emphasise the requirement for antimicrobial materials for on-demand manufacturing. Besides aerosol transmission, SARS-CoV-2 is also propagated through contact with virus-contaminated surfaces. As such, the development of effective biofunctional materials that can inactivate SARS-CoV-2 are critical for pandemic preparedness. Such materials will enable the rational development of antiviral devices with prolonged serviceability reducing the environmental burden of disposable alternatives. This research reveals the novel use of Laser Powder Bed Fusion (LPBF) to 3D print porous Cobalt-Chromium-Molybdenum (Co-Cr-Mo) superalloy with potent antiviral activity (100% viral inactivation in 30 mins). The porous material was rationally conceived using a multi-objective surrogate model featuring track thickness (tt) and pore diameter ({phi}d) as responses. The regression analysis found the most significant parameters for Co-Cr-Mo track formation to be the interaction effects of scanning rate (Vs) and laser power (Pl) in the order PlVs > Vs > Pl. Contrastively, the pore diameter was found to be primarily driven by the hatch spacing (Sh). The study is the first to demonstrate the superior antiviral properties of 3D printed Co-Cr-Mo superalloy against an enveloped virus used as biosafe viral model of SARS-CoV-2. The material significantly outperforms the viral inactivation time of other broadly used antiviral metals such as copper and silver from 5 hours to 30 minutes. As such the study goes beyond the current state-of-the-art in antiviral alloys to provide extra-protection to combat the SARS-COV-2 viral spread. The evolving nature of the COVID-19 pandemic brings new and unpredictable challenges where on-demand 3D printing of antiviral materials can achieve rapid solutions while reducing the environmental impact of disposable devices.\n\nGraphical abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=148 SRC=\"FIGDIR/small/454385v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (47K):\norg.highwire.dtl.DTLVardef@992f2forg.highwire.dtl.DTLVardef@e8dbe5org.highwire.dtl.DTLVardef@1bcb8adorg.highwire.dtl.DTLVardef@100a345_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Hiromichi Suzuki", - "author_inst": "Department of Infectious Diseases, Faculty of Medicine, University of Tsukuba" - }, - { - "author_name": "Yusaku Akashi", - "author_inst": "Division of Infectious Diseases, Department of Medicine, Tsukuba Medical Center Hospital" - }, - { - "author_name": "Atsuo Ueda", - "author_inst": "Department of Clinical Laboratory, Tsukuba Medical Center Hospital" - }, - { - "author_name": "Yoshihiko Kiyasu", - "author_inst": "Department of Infectious Diseases, University of Tsukuba Hospital" - }, - { - "author_name": "Yuto Takeuchi", - "author_inst": "Department of Infectious Diseases, University of Tsukuba Hospital" - }, - { - "author_name": "Yuta Maehara", - "author_inst": "Sekisui Medical Co., Ltd. Research & Development Division" + "author_name": "Arun Arjunan", + "author_inst": "University of Wolverhampton" }, { - "author_name": "Yasushi Ochiai", - "author_inst": "Sekisui Medical Co., Ltd. Research & Development Division" + "author_name": "John Robinson", + "author_inst": "University of Wolverhampton" }, { - "author_name": "Shinya Okuyama", - "author_inst": "Sekisui Medical Co., Ltd. Research & Development Division" + "author_name": "Ahmad Baroutaji", + "author_inst": "University of Wolverhampton" }, { - "author_name": "Shigeyuki Notake", - "author_inst": "Department of Clinical Laboratory, Tsukuba Medical Center Hospital" + "author_name": "Miguel Marti", + "author_inst": "Universidad Catolica de Valencia San Vicente Martir" }, { - "author_name": "Koji Nakamura", - "author_inst": "Department of Clinical Laboratory, Tsukuba Medical Center Hospital" + "author_name": "Alberto Tunon-Molina", + "author_inst": "Universidad Catolica de Valencia San Vicente Martir" }, { - "author_name": "Hiroichi Ishikawa", - "author_inst": "Department of Respiratory Medicine, Tsukuba Medical Center Hospital" + "author_name": "Angel Serrano-Aroca", + "author_inst": "Universidad Catolica de Valencia San Vicente Martir" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by", + "type": "new results", + "category": "bioengineering" }, { "rel_doi": "10.1101/2021.07.30.454406", @@ -661988,51 +662431,139 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.26.21261130", - "rel_title": "Vaccine effectiveness when combining the ChAdOx1 vaccine as the first dose with an mRNA COVID-19 vaccine as the second dose", + "rel_doi": "10.1101/2021.07.22.21260837", + "rel_title": "Streptococcus pneumoniae colonisation associates with impaired adaptive immune responses against SARS-CoV-2", "rel_date": "2021-07-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.26.21261130", - "rel_abs": "BackgroundThe recommendations in several countries to stop using the ChAdOx1 vaccine has led to vaccine programs combining different vaccine types, which necessitates new knowledge on vaccine effectiveness (VE). In this study, we aimed to estimate the VE when combining the ChAdOx1 vaccine as the first dose and an mRNA vaccine as the second dose.\n\nMethodsThis nationwide population-based cohort study estimated VE against SARS-CoV-2 infection, all-cause and COVID-19 related hospitalization and death after receiving the ChAdOx1 vaccine as the first dose followed by an mRNA vaccine as the second dose. VE estimates were obtained using a Cox regression with calendar time as underlying time and adjusted for sex, age, comorbidity, heritage and hospital admission. Information on all individuals was extracted and linked from high-quality national registries.\n\nResultsA total of 5,542,079 individuals were included in the analyses (97.6% of the total Danish population). A total of 144,360 were vaccinated with the ChAdOx1 vaccine as the first dose and of these 136,551 individuals received an mRNA vaccine as the second dose. A total of 1,691,464 person-years and 83,034 cases of SARS-CoV-2 infection were included. The VE against SARS-CoV-2 infection when combining the ChAdOx1 and an mRNA vaccine was 88% (95% confidence interval (CI): 83; 92) 14 days after the second dose and onwards. There were no COVID-19 related hospitalizations and deaths among the individuals vaccinated with the combination of the ChAdOx1 and an mRNA vaccine during the study period.\n\nConclusionIn conclusion, this study found a reduction in the risk of SARS-CoV-2 infection when combining the ChAdOx1 and an mRNA vaccine, compared with unvaccinated individuals. This is similar to the VE of two doses of an mRNA vaccine. Longer follow-up time is needed to confirm vaccine induced protection against severe events, such as COVID-19 related hospitalization and death.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.22.21260837", + "rel_abs": "Although recent epidemiological data suggest that pneumococci may contribute to the risk of SARS-CoV-2 disease, secondary pneumococcal pneumonia has been reported as infrequent. This apparent contradiction may be explained by interactions of SARS-CoV-2 and pneumococcus in the upper airway, resulting in the escape of SARS-CoV-2 from protective host immune responses. Here, we investigated the relationship of these two respiratory pathogens in two distinct cohorts of a) healthcare workers with asymptomatic or mildly symptomatic SARS-CoV-2 infection identified by systematic screening and b) patients with moderate to severe disease who presented to hospital. We assessed the effect of co-infection on host antibody, cellular and inflammatory responses to the virus. In both cohorts, pneumococcal colonisation was associated with diminished anti-viral immune responses, which affected primarily mucosal IgA levels among individuals with mild or asymptomatic infection and cellular memory responses in infected patients. Our findings suggest that S. pneumoniae modulates host immunity to SARS-CoV-2 and raises the question if pneumococcal carriage also enables immune escape of other respiratory viruses through a similar mechanism and facilitates reinfection occurrence.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Mie Agermose Gram", - "author_inst": "Statens Serum Institut" + "author_name": "Elena Mitsi", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Hanne-Dorthe Emborg", - "author_inst": "Statens Serum Institut" + "author_name": "Jesus Reine", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Ida Rask Moustsen-Helms", - "author_inst": "Statens Serum Institut" + "author_name": "Britta C Urban", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Jens Nielsen", - "author_inst": "Statens Serum Institut" + "author_name": "Carla Solorzano", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Anne Katrine Bj\u00f8rkholt S\u00f8rensen", - "author_inst": "Statens Serum Institut" + "author_name": "Elissavet Nikolaou", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Palle Valentiner-Branth", - "author_inst": "Statens Serum Institut" + "author_name": "Angela D Hyder-Wright", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Astrid Blicher Schelde", - "author_inst": "Statens Serum Institut" + "author_name": "Sherin Pojar", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Katrine Finderup Nielsen", - "author_inst": "Statens Serum Institut" + "author_name": "Ashleigh Howard", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Lisa Hitchins", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Sharon Glynn", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Madlen Farrar", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Konstantinos Liatsikos", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Andrea M Collins", + "author_inst": "LSTM" + }, + { + "author_name": "Naomi F Walker", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Helen Hill", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Esther Lauryn German", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Katerina S Cheliotis", + "author_inst": "LSTM" + }, + { + "author_name": "Rachel Louise Byrne", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Christopher T Williams", + "author_inst": "LSTM" + }, + { + "author_name": "Ana I Cubas Atienzar", + "author_inst": "LSTM" + }, + { + "author_name": "Tom Fletcher", + "author_inst": "LSTM" + }, + { + "author_name": "Emily R Adams", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Simon J Draper", + "author_inst": "University of Oxford" + }, + { + "author_name": "David Pulido", + "author_inst": "University of Oxford" + }, + { + "author_name": "Rohini Beavon", + "author_inst": "Pfizer" + }, + { + "author_name": "Elizabeth Begier", + "author_inst": "Pfizer" + }, + { + "author_name": "Christian Theilacker", + "author_inst": "Pfizer" + }, + { + "author_name": "Luis Jodar", + "author_inst": "Pfizer" + }, + { + "author_name": "Bradford D Gessner", + "author_inst": "Pfizer" + }, + { + "author_name": "Daniela M Ferreira", + "author_inst": "Liverpool School of Tropical Medicine" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.07.26.21261028", @@ -663766,59 +664297,155 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.24.21261065", - "rel_title": "COVID-Q: validation of the first COVID-19 questionnaire based on patient-rated symptom gravity", + "rel_doi": "10.1101/2021.07.24.21261040", + "rel_title": "Novel risk factors for Coronavirus disease-associated mucormycosis (CAM): a case control study during the outbreak in India", "rel_date": "2021-07-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.24.21261065", - "rel_abs": "ObjectivesThe aim of the present study was to develop and validate the CoronaVirus Disease - 2019 (COVID-19) Questionnaire (COVID-Q), a novel symptom questionnaire specific for COVID-19 patients, to provide a comprehensive evaluation which may be helpful for physicians.. A secondary goal of the present study was to evaluate the performance of the COVID-Q in identifying subjects at higher risk of being tested positive for COVID-19.\n\nMaterial and methodsConsecutive non-hospitalized adults who underwent nasopharyngeal and throat swab for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection at Treviso Hospital in March 2020, were enrolled. Subjects were divided into positive (cases) and negative (controls) in equal number. All of them gave consent and answered the COVID-Q. Patients not able to answer the COVID-Q due to clinical conditions were excluded.\n\nParallel Analysis and Principal Component Analysis were used to identify clusters of items measuring the same dimension. The Item Response Theory (IRT)-based analyses evaluated the functioning of item categories, the presence of clusters of local dependence among items, item fit within the model and model fit to the data.\n\nResultsAnswers obtained from 230 COVID-19 cases (113 males, and 117 females; mean age 55 years, range 20-99 years) and 230 controls (61 males, and 169 females; mean age 46 years, range 21-89) were analyzed. Parallel analysis led to the extraction of six components, which corresponded to as many clinical presentation patterns: asthenia, influenza-like symptoms, ear and nose symptoms, breathing issues, throat symptoms, and anosmia/ageusia. The final IRT models retained 27 items as significant for symptom assessment. The total score on the questionnaire was significantly associated with positivity to the molecular SARS-CoV-2 test: subjects with multiple symptoms were significantly more likely to be affected by COVID-19 (p < .001). Older age and male gender also represented risk factors. Presence of breathing issues and anosmia/ageusia were significantly related to positivity to SARS-CoV-2 (p < 0.001). None of the examined comorbidities had a significant association with COVID-19 diagnosis.\n\nConclusionAccording to the analyses, COVID-Q could be validated since the aspects it evaluated were overall significantly related to SARS-CoV-2 infection. The application of the novel COVID-Q to everyday clinical practice may help identifying subjects who are likely to be affected by COVID-19 and address them to a nasopharyngeal swab in order to achieve an early diagnosis.\n\nWhat is already known about this topic?COVID-19 symptoms are widely known. Lots of studies have been published regarding self-administered questionnaires in order to characterize and know as much as possible regarding this disease. By the way, no specific questionnaires have been validated, yet, and there is no consensus regarding this topic.\n\nWhat does this article add?This paper shows the COVID-Q, a novel symptom questionnaire specific for COVID-19 patients. The aim is to provide a comprehensive evaluation that may be helpful to clinicians in order to suspect SARS-CoV-2 infection or not.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.24.21261040", + "rel_abs": "BackgroundThe epidemiology of the Coronavirus-disease associated mucormycosis (CAM) syndemic is poorly elucidated. We aimed to identify risk factors that may explain the burden of cases and help develop preventive strategies.\n\nMethodsWe performed a case-control study comparing cases diagnosed with CAM and those who had recovered from COVID-19 without developing mucormycosis (controls). Information on comorbidities, glycemic control, and practices related to COVID-19 prevention and treatment was recorded.\n\nResults352 patients (152 cases and 200 controls) diagnosed with COVID-19 during April-May 2021 were included. In the CAM group, symptoms of mucormycosis began a mean 18.9 (SD 9.1) days after onset of COVID-19, and predominantly rhino-sinus and orbital involvement was present. All, but one, CAM cases carried conventional risk factors of diabetes and steroid use. On multivariable regression, increased odds of CAM were associated with the presence of diabetes (adjusted OR 3.5, 95%CI 1.1-11), use of systemic steroids (aOR 7.7,95% CI 2.4-24.7), prolonged use of cloth and surgical masks (vs no mask, aOR 6.9, 95%CI 1.5-33.1), and repeated nasopharyngeal swab testing during the COVID-19 illness (aOR 1.6,95% CI 1.2-2.2). Zinc therapy, probably due to its utility in immune function, was found to be protective (aOR 0.05, 95%CI 0.01-0.19). Notably, the requirement of oxygen supplementation or hospitalization did not affect the risk of CAM.\n\nConclusionJudicious use of steroids and stringent glycemic control are vital to preventing mucormycosis. Use of clean masks, preference for N95 masks if available, and minimizing swab testing after the diagnosis of COVID-19 may further reduce the incidence of CAM.", + "rel_num_authors": 34, "rel_authors": [ { - "author_name": "Giacomo Spinato", - "author_inst": "Department of Neurosciences, University of Padova" + "author_name": "Umang Arora", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" }, { - "author_name": "Cristoforo Fabbris", - "author_inst": "University Hospital of Treviso" + "author_name": "Megha Priyadarshi", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" }, { - "author_name": "Federica Conte", - "author_inst": "Department of Psychology, University of Milano Bicocca" + "author_name": "Varidh Katiyar", + "author_inst": "Department of Neurosurgery, AIIMS, Delhi, India" }, { - "author_name": "Anna Menegaldo", - "author_inst": "University Hospital of Treviso, Treviso" + "author_name": "Manish Soneja", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" }, { - "author_name": "Leonardo Franz", - "author_inst": "Department of Neurosciences, University of Padova" + "author_name": "Prerna Garg", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" }, { - "author_name": "Piergiorgio Gaudioso", - "author_inst": "Department of Neurosciences, University of Padova" + "author_name": "Ishan Gupta", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" }, { - "author_name": "Francesco Cinetto", - "author_inst": "Department of Medicine, Clinical Immunology and Hematology, University of Padova" + "author_name": "Vishwesh Bharadiya", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" }, { - "author_name": "Carlo Agostini", - "author_inst": "Department of Medicine, Clinical Immunology and Hematology, University of Padova" + "author_name": "Parul Berry", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" }, { - "author_name": "Giulio Costantini", - "author_inst": "Department of Psychology, University of Milano Bicocca" + "author_name": "Tamoghna Ghosh", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" }, { - "author_name": "Paolo Boscolo Rizzo", - "author_inst": "University of Trieste" + "author_name": "Lajjaben Patel", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Radhika Sarda", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Shreya Garg", + "author_inst": "Department of Otolaryngology & Head-Neck Surgery, AIIMS, Delhi, India" + }, + { + "author_name": "Shubham Agarwal", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Veronica Arora", + "author_inst": "Department of Medical Genetics, Sir Ganga Ram Hospital, Delhi, India" + }, + { + "author_name": "Aishwarya Ramprasad", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Amit Kumar", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Rohit Kumar Garg", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Parul Kodan", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Neeraj Nischal", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Gagandeep Singh", + "author_inst": "Department of Microbiology, AIIMS, Delhi, India" + }, + { + "author_name": "Pankaj Jorwal", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Arvind Kumar", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Upendra Baitha", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Ved Prakash Meena", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Animesh Ray", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Prayas Sethi", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Immaculata Xess", + "author_inst": "Department of Microbiology, AIIMS, Delhi, India" + }, + { + "author_name": "Naval Kishore Vikram", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Sanjeev Sinha", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Ashutosh Biswas", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Alok Thakar", + "author_inst": "Department of Otolaryngology & Head-Neck Surgery, AIIMS, Delhi, India" + }, + { + "author_name": "Sushma Bhatnagar", + "author_inst": "Department of Onco-anaesthesia and Palliative Medicine, AIIMS, Delhi, India" + }, + { + "author_name": "Anjan Trikha", + "author_inst": "Department of Anaesthesiology, Pain Medicine and Critical Care, AIIMS, Delhi, India" + }, + { + "author_name": "Naveet Wig", + "author_inst": "Department of Medicine, AIIMS, Delhi, India" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.07.24.21261076", @@ -665860,49 +666487,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.24.21261007", - "rel_title": "Use of Indomethacin for mild and moderate Covid -19 patients. A Randomized Control Trial", + "rel_doi": "10.1101/2021.07.22.21260942", + "rel_title": "Safety and Immunogenicity of Nanocovax, a SARS-CoV-2 Recombinant Spike Protein Vaccine", "rel_date": "2021-07-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.24.21261007", - "rel_abs": "IntroductionIndomethacin, a non-steroidal anti-inflammatory drug (NSAID), has been presented as a broad-spectrum antiviral agent. This randomised clinical trial in a hospital setting evaluated the efficacy and safety of this drug in RT-PCR-positive coronavirus disease 2019 (COVID-19) patients.\n\nMaterials & MethodsA total of 210 RT-PCR-positive COVID-19 patients, who provided consent were allotted, to control or case arm, based on block randomisation. The control arm received standard of care comprising paracetamol, ivermectin, and other adjuvant therapies. The patients in the case arm received indomethacin instead of paracetamol, with other medications retained. The primary endpoint was the development of hypoxia/desaturation with SpO2 [≤] 93, while time to become afebrile and time for cough and myalgia resolution were the secondary endpoints.\n\nResultsThe results of 210 patients were available, with 103 and 107 patients in the indomethacin and paracetamol arms, respectively. We monitored patient profiles along with everyday clinical parameters. Blood chemistry at the time of admission and discharge was assessed.\n\nAs no one in either of the arms required high-flow oxygen, desaturation with SpO2 level of 93 and below was an important goal. In the indomethacin group, none of the 103 patients developed desaturation. On the other hand, 20 of the 107 patients in the paracetamol arm developed desaturation. Patients who received indomethacin also experienced more rapid symptomatic relief than those in the paracetamol arm, with most symptoms disappearing in half the time. 56 patients out of 107 in the paracetamol arm had fever on the seventh day, while no patient in the indomethacin group had fever. Neither arm reported any adverse event. The fourteenth-day follow-up revealed that the paracetamol arm patients had faced several discomforts, including myalgia, joint pain, and tiredness; indomethacin arm patients mostly complained only of tiredness.\n\nConclusionIndomethacin is a safe and effective drug for treating patients with mild and moderate covid-19.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.22.21260942", + "rel_abs": "BackgroundNanocovax is a recombinant severe acute respiratory syndrome coronavirus 2 subunit vaccine composed of full-length prefusion stabilized recombinant SARS-CoV-2 spike glycoproteins (S-2P) and aluminum hydroxide adjuvant.\n\nMethodsWe conducted a dose-escalation, open label trial (phase 1) and a randomized, double-blind, placebo-controlled trial (phase 2) to evaluate the safety and immunogenicity of the Nanocovax vaccine (in 25 microgram (mcg), 50 mcg, and 75 mcg doses, aluminum hydroxide adjuvanted). In phase 1, 60 participants received two intramuscular injection of the vaccine following dose-escalation procedure. The primary outcomes were reactogenicity and laboratory tests to evaluate the vaccine safety. In phase 2 which involved in 560 healthy adults, the primary outcomes are vaccine safety; and anti-S IgG antibody response. Secondary outcomes were surrogate virus neutralization, wild-type SARS-CoV-2 neutralization, and T-cell responses by intracellular staining (ICS) for interferon gamma (IFNg). We performed primary analyses at day 35 and day 42.\n\nResultsFor phase 1 study, no serious adverse events (SAE) were observed for all 60 participants. Most adverse events (AE) were grade 1 and disappeared shortly after injection. For phase 2 study, after randomization, 480 participants were assigned to receive the vaccine with adjuvant, and 80 participants were assigned to receive placebo. Reactogenicity was absent or mild in the majority of participants and of short duration (mean, [≤]3 days). Unsolicited adverse events were mild in most participants. There were no serious adverse events related to Nanocovax. Regarding the immunogenicity, Nanocovax induced robust anti-S antibody responses. There was no statistical difference in antibody responses among dose strengths on Day 42, in terms of anti S-IgG level and neutralizing antibody titer.\n\nConclusionsUp to 42 days, Nanocovax vaccine was safe, well tolerated and induced robust immune responses. We propose using Nanocovax 25 mcg for Phase 3 to evaluate the vaccine efficacy. (Research funded by Nanogen Pharmaceutical Biotechnology JSC., and the Ministry of Science and Technology of Vietnam; ClinicalTrials.gov number, NCT04683484.)", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "ravichandran rajan", - "author_inst": "miot hospitals, Chennai, India" - }, - { - "author_name": "Krishna Mohan Surapaneni", - "author_inst": "Panimalar Medical College Hospital & Research Institute" + "author_name": "Thuy P Nguyen", + "author_inst": "Nanogen Biopharmaceuticals JSC" }, { - "author_name": "Suresh Kumar Sukumaran", - "author_inst": "Panimalar Medical College Hospital & Research Institute, Chennai, India" - }, - { - "author_name": "Devakumar Kamaraj", - "author_inst": "Panimalar Medical College Hospital & Research Institute" + "author_name": "Quyet Do", + "author_inst": "Vietnam Military Medical University" }, { - "author_name": "Sumetha Suga Devisuga", - "author_inst": "Panimalar Medical College Hospital & Research Institute" + "author_name": "Lan T Lan", + "author_inst": "Pasteur Institute" }, { - "author_name": "Samson Oliver Ravi", - "author_inst": "Molbio Diagnostics, Chennai, India" + "author_name": "Duc V Dinh", + "author_inst": "Vietnam Military Medical University" }, { - "author_name": "Sivakumar Vijayaraghavalu", - "author_inst": "Narayana Translational Research Centre, Narayana Medical College, Nellore, Andhra Pradesh, India" + "author_name": "Hiep Khong", + "author_inst": "Nanogen Biopharmaceuticals JSC" }, { - "author_name": "Krishna Kumar Ramarathnam", - "author_inst": "Indian Institute of Technology Madras" + "author_name": "Si Minh Do", + "author_inst": "Nanogen Biopharmaceuticals JSC" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -668882,67 +669501,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.21.21260964", - "rel_title": "Phase 1 safety and pharmacokinetics studies of BRII-196 and BRII-198, SARS-CoV-2 spike-targeting monoclonal antibodies", + "rel_doi": "10.1101/2021.07.20.21260872", + "rel_title": "Excess mortality in India from June 2020 to June 2021 during the COVID pandemic: death registration, health facility deaths, and survey data", "rel_date": "2021-07-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.21.21260964", - "rel_abs": "BackgroundBRII-196 and BRII-198 are two anti-SARS-CoV-2 monoclonal neutralizing antibodies with modified Fc region that extends half-life and are being developed as cocktail therapy for the treatment of COVID-19. Safety, tolerability, pharmacokinetics, and immunogenicity of BRII-196 and BRII-198 were investigated in healthy adults.\n\nMethodsSingle ascending doses of BRII-196 and BRII-198 were evaluated in parallel in the first-in-human, placebo-controlled phase 1 studies. A total of 32 healthy adults were randomized and received a single intravenous infusion of 750, 1500, and 3000 mg of BRII-196 (n=12), BRII-198 (n=12), or placebo (n=8) and were followed for 180 days.\n\nResultsAll infusions were well tolerated at infusion rates between 0.5 mL/min to 4 mL/min with no dose-limiting adverse events, deaths, serious adverse events, or any systemic or local infusion reactions. Most treatment-emergent adverse events were isolated asymptomatic laboratory abnormalities of Grade 1-2 in severity. Each mAb displayed pharmacokinetics expected of Fc-engineered human IgG1 with mean terminal half-lives of approximately 46 days and 76 days, respectively, with no evidence of significant anti-drug antibody development.\n\nConclusionsBRII-196 and BRII-198 were well-tolerated. Clinical results support further development as therapeutic or prophylactic options for SARS-CoV-2 infection.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.20.21260872", + "rel_abs": "BackgroundIndias official death totals from the COVID pandemic are widely regarded as under-reports.\n\nMethodsWe quantified all-cause excess mortality in India, comparing deaths during the peak of the first and second COVID waves (Jul-Dec 2020 and April-June 2021) with month wise deaths in 2015-19 from three sources: Civil Registration System (CRS) mortality reports from 15 states or cities with 37% of Indias population; deaths in 0.2 million health facilities; and a representative survey of 0.14 million adults about COVID deaths.\n\nResultsDuring the first viral wave, the median excess mortality compared to CRS baseline was 22% and 41%, respectively, in included states and cities, rising to 46% and 85% during the second wave. In settings with 10 or more months of data across the two waves, the median excess mortality was 32% and 37% for states and cities, respectively. Deaths in health facilities showed a 27% excess mortality from July 2020-May 2021, reaching 120% during April-May 2021. The national survey found 3.5% of adults reported a COVID death in their household in April-June 2021, approximately doubling the 3.2% expected overall deaths. The national survey showed 29-32% excess deaths from June 1, 2020 to June 27, 2021, most of which were likely to be COVID. This translates to 3.1-3.4 million COVID deaths (including 2.5-2.8 million during April-June 2021). National extrapolations from health facility and CRS data suggest 2.7-3.3 million deaths during the year.\n\nConclusionsIndias COVID death rate may be about 7-8 times higher than the officially reported 290/million population.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Yao Zhang", - "author_inst": "TSB Therapeutics" - }, - { - "author_name": "Xiaohua Hao", - "author_inst": "Beijing Ditan Hospital, Capital Medical University" + "author_name": "Yashwant Deshmukh", + "author_inst": "Center for Voting Opinions and Trends in Election Research" }, { - "author_name": "Ji Ma", - "author_inst": "Brii Biosciences" + "author_name": "Wilson Suraweera", + "author_inst": "Centre for Global Health Research, Unity Health Toronto and Dalla Lana School of Public Health, University of Toronto" }, { - "author_name": "Mingming Wang", - "author_inst": "Brii Biosciences" + "author_name": "Chinmay Tumbe", + "author_inst": "Indian Institute of Management Ahmedabad" }, { - "author_name": "Yanyan Li", - "author_inst": "Brii Biosciences" + "author_name": "Aditi Bhowmick", + "author_inst": "Development Data Lab" }, { - "author_name": "Yang Liu", - "author_inst": "Brii Biosciences" + "author_name": "Sankalp Sharma", + "author_inst": "Development Data Lab" }, { - "author_name": "Dong Zhao", - "author_inst": "Beijing Ditan Hospital, Capital Medical University" + "author_name": "Paul Novosad", + "author_inst": "Department of Economics, Dartmouth College" }, { - "author_name": "Wen Zhang", - "author_inst": "Beijing Ditan Hospital, Capital Medical University" + "author_name": "Sze Hang Fu", + "author_inst": "Centre for Global Health Research, Unity Health Toronto and Dalla Lana School of Public Health, University of Toronto" }, { - "author_name": "Chunming Li", - "author_inst": "Brii Biosciences" + "author_name": "Leslie Newcombe", + "author_inst": "Centre for Global Health Research, Unity Health Toronto and Dalla Lana School of Public Health, University of Toronto" }, { - "author_name": "Li Yan", - "author_inst": "Brii Biosciences" + "author_name": "Hellen Gelband", + "author_inst": "Centre for Global Health Research, Unity Health Toronto and Dalla Lana School of Public Health, University of Toronto" }, { - "author_name": "Qing Zhu", - "author_inst": "TSB Therapeutics" + "author_name": "Patrick Brown", + "author_inst": "Centre for Global Health Research, Unity Health Toronto and Dalla Lana School of Public Health, University of Toronto" }, { - "author_name": "Fujie Zhang", - "author_inst": "Beijing Ditan Hospital, Capital Medical University" + "author_name": "Prabhat Jha", + "author_inst": "Centre for Global Health Research, Unity Health Toronto and Dalla Lana School of Public Health, University of Toronto" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.07.22.21260416", @@ -670776,77 +671391,57 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2021.07.18.21260718", - "rel_title": "Real-Time SARS-CoV-2 Genotyping by High-Throughput Multiplex PCR Reveals the Epidemiology of the Variants of Concern in Qatar", + "rel_doi": "10.1101/2021.07.16.21260464", + "rel_title": "K-12 School Teaching Posture Correlates with COVID-19 Disease Outcomes in Ohio", "rel_date": "2021-07-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.18.21260718", - "rel_abs": "Complementing whole genome sequencing strategies with high-throughput multiplex RT-qPCR genotyping allows for more comprehensive and real-time tracking of SARS-CoV-2 variants of concern. During the second and third waves of COVID-19 in Qatar, PCR genotyping, combined with Sanger sequencing of un-typeable samples, was employed to describe the epidemiology of the Alpha, Beta and Delta variants. A total of 9792 nasopharyngeal PCR-positive samples collected between April-June 2021 were successfully genotyped, revealing the importation and transmission dynamics of these three variants in Qatar.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.16.21260464", + "rel_abs": "At the start of the COVID-19 pandemic, most US K-12 schools shutdown and millions of students began remote learning. By September 2020, little guidance had been provided to school districts to inform fall teaching. This indecision led to a variety of teaching postures within a given state. In this report we examine Ohio school districts in-depth, to address whether on-premises teaching impacted COVID-19 disease outcomes in that community. We observed that counties with on-premises teaching had more cumulative deaths at the end of fall semester than counties with predominantly online teaching. To provide a measure of disease progression, we developed an observational disease model and examined multiple possible confounders, such as population size, mobility, and demographics. Examination of micropolitan counties revealed that the progression of COVID-19 disease was faster during the fall semester in counties with predominantly on-premises teaching. The relationship between increased disease prevalence in counties with on-premises teaching was not related to deaths at the start of the fall semester, population size, or the mobility within that county. This research addresses the critical question whether on-premises schooling can impact the spread of epidemic and pandemic viruses and will help inform future public policy decisions on school openings.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Mohammad R. Hasan", - "author_inst": "Sidra Medicine, Doha, Qatar" + "author_name": "Cheyenne Ehman", + "author_inst": "Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA, USA" }, { - "author_name": "Mahesh K. R. Kalikiri", - "author_inst": "Sidra Medicine, Doha, Qatar" - }, - { - "author_name": "Faheem Mirza", - "author_inst": "Sidra Medicine, Doha, Qatar" + "author_name": "Yixuan Luo", + "author_inst": "Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA, USA" }, { - "author_name": "Sathyavathi Sundararaju", - "author_inst": "Sidra Medicine, Doha, Qatar" - }, - { - "author_name": "Anju Sharma", - "author_inst": "Sidra Medicine, Doha, Qatar" - }, - { - "author_name": "Stephan Lorenz", - "author_inst": "Sidra Medicine, Doha, Qatar" - }, - { - "author_name": "Hiam Chemaitelly", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Zi Yang", + "author_inst": "Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA, USA" }, { - "author_name": "Reham A. El-Kahlout", - "author_inst": "Hamad Medical Corporation, Doha, Qatar" + "author_name": "Ziyan Zhu", + "author_inst": "Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA, USA" }, { - "author_name": "Kin Ming Tsui", - "author_inst": "Sidra Medicine, Doha, Qatar" + "author_name": "Sara Donovan", + "author_inst": "Global Center for Health Security, University of Nebraska Medical Center" }, { - "author_name": "Hadi M. Yassine", - "author_inst": "Qatar University, Doha, Qatar" - }, - { - "author_name": "Peter V. Coyle", - "author_inst": "Hamad Medical Corporation, Doha, Qatar" + "author_name": "Annika J. Avery", + "author_inst": "University of Pittsburgh School of Medicine" }, { - "author_name": "Abdullatif Al Khal", - "author_inst": "Hamad Medical Corporation, Doha, Qatar" + "author_name": "Jiayi Wang", + "author_inst": "Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA, USA" }, { - "author_name": "Roberto Bertollini", - "author_inst": "Ministry of Public Health, Doha, Qatar" + "author_name": "James Lawler", + "author_inst": "Global Center for Health Security, University of Nebraska Medical Center" }, { - "author_name": "Mohamed H. Al Thani", - "author_inst": "Ministry of Public Health, Doha, Qatar" + "author_name": "Rebecca Nugent", + "author_inst": "Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA, USA" }, { - "author_name": "Laith J. Abu-Raddad", - "author_inst": "Weill Cornell Medicine-Qatar" + "author_name": "Valerie Ventura", + "author_inst": "Department of Statistics & Data Science, Carnegie Mellon University, Pittsburgh, PA, USA" }, { - "author_name": "Patrick Tang", - "author_inst": "Sidra Medicine, Doha, Qatar" + "author_name": "Seema S Lakdawala", + "author_inst": "University of Pittsburgh School of Medicine" } ], "version": "1", @@ -672990,105 +673585,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.20.21260855", - "rel_title": "SARS-CoV-2 incidence, transmission and reinfection in a rural and an urban setting: results of the PHIRST-C cohort study, South Africa, 2020-2021", + "rel_doi": "10.1101/2021.07.19.21260707", + "rel_title": "Increased transmissibility of emerging SARS-CoV-2 variants is driven either by viral load or probability of infection rather than environmental stability", "rel_date": "2021-07-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.20.21260855", - "rel_abs": "BackgroundBy August 2021, South Africa experienced three SARS-CoV-2 waves; the second and third associated with emergence of Beta and Delta variants respectively.\n\nMethodsWe conducted a prospective cohort study during July 2020-August 2021 in one rural and one urban community. Mid-turbinate nasal swabs were collected twice-weekly from household members irrespective of symptoms and tested for SARS-CoV-2 using real-time reverse transcription polymerase chain reaction (rRT-PCR). Serum was collected every two months and tested for anti-SARS-CoV-2 antibodies.\n\nResultsAmong 115,759 nasal specimens from 1,200 members (follow-up rate 93%), 1976 (2%) were SARS-CoV-2-positive. By rRT-PCR and serology combined, 62% (749/1200) of individuals experienced [≥]1 SARS-CoV-2 infection episode, and 12% (87/749) experienced reinfection. Of 662 PCR-confirmed episodes with available data, 15% (n=97) were associated with [≥]1 symptom. Among 222 households, 200 (90%) had [≥]1 SARS-CoV-2-positive individual. Household cumulative infection risk (HCIR) was 25% (213/856). On multivariable analysis, accounting for age and sex, index case lower cycle threshold value (OR 3.9, 95%CI 1.7-8.8), urban community (OR 2.0,95%CI 1.1-3.9), Beta (OR 4.2, 95%CI 1.7-10.1) and Delta (OR 14.6, 95%CI 5.7-37.5) variant infection were associated with increased HCIR. HCIR was similar for symptomatic (21/110, 19%) and asymptomatic (195/775, 25%) index cases (p=0.165). Attack rates were highest in individuals aged 13-18 years and individuals in this age group were more likely to experience repeat infections and to acquire SARS-CoV-2 infection. People living with HIV who were not virally supressed were more likely to develop symptomatic illness, and shed SARS-CoV-2 for longer compared to HIV-uninfected individuals.\n\nConclusionsIn this study, 85% of SARS-CoV-2 infections were asymptomatic and index case symptom status did not affect HCIR, suggesting a limited role for control measures targeting symptomatic individuals. Increased household transmission of Beta and Delta variants, likely contributed to successive waves, with >60% of individuals infected by the end of follow-up.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSPrevious studies have generated wide-ranging estimates of the proportion of SARS-CoV-2 infections which are asymptomatic. A recent systematic review found that 20% (95% CI 3%-67%) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections remained asymptomatic throughout infection and that transmission from asymptomatic individuals was reduced. A systematic review and meta-analysis of 87 household transmission studies of SARS-CoV-2 found an estimated secondary attack rate of 19% (95% CI 16-22). The review also found that household secondary attack rates were increased from symptomatic index cases and that adults were more likely to acquire infection. As of December 2021, South Africa experienced three waves of SARS-CoV-2 infections; the second and third waves were associated with circulation of Beta and Delta variants respectively. SARS-CoV-2 vaccines became available in February 2021, but uptake was low in study sites reaching 5% fully vaccinated at the end of follow up. Studies to quantify the burden of asymptomatic infections, symptomatic fraction, reinfection frequency, duration of shedding and household transmission of SARS-CoV-2 from asymptomatically infected individuals have mostly been conducted as part of outbreak investigations or in specific settings. Comprehensive systematic community studies of SARS-CoV-2 burden and transmission including for the Beta and Delta variants are lacking, especially in low vaccination settings.\n\nAdded value of this studyWe conducted a unique detailed COVID-19 household cohort study over a 13 month period in South Africa, with real time reverse transcriptase polymerase chain reaction (rRT-PCR) testing twice a week irrespective of symptoms and bimonthly serology. By the end of the study in August 2021, 749 (62%) of 1200 individuals from 222 randomly sampled households in a rural and an urban community in South Africa had at least one confirmed SARS-CoV-2 infection, detected on rRT-PCR and/or serology, and 12% (87/749) experienced reinfection. Symptom data were analysed for 662 rRT-PCR-confirmed infection episodes that occurred >14 days after the start of follow-up (of a total of 718 rRT-PCR-confirmed episodes), of these, 15% (n=97) were associated with one or more symptoms. Among symptomatic indvidiausl, 9% (n=9) were hospitalised and 2% (n=2) died. Ninety percent (200/222) of included households, had one or more individual infected with SARS-CoV-2 on rRT-PCR and/or serology within the household. SARS-CoV-2 infected index cases transmitted the infection to 25% (213/856) of susceptible household contacts. Index case ribonucleic acid (RNA) viral load proxied by rRT-PCR cycle threshold value was strongly predictive of household transmission. Presence of symptoms in the index case was not associated with household transmission. Household transmission was four times greater from index cases infected with Beta variant and fifteen times greater from index cases infected with Delta variant compared to wild-type infection. Attack rates were highest in individuals aged 13-18 years and individuals in this age group were more likely to experience repeat infections and to acquire SARS-CoV-2 infection within households. People living with HIV (PLHIV) who were not virally supressed were more likely to develop symptomatic illness when infected with SARS-CoV-2, and shed SARS-CoV-2 for longer when compared to HIV-uninfected individuals.\n\nImplications of all the available evidenceWe found a high rate of SARS-CoV-2 infection in households in a rural community and an urban community in South Africa, with the majority of infections being asymptomatic in individuals of all ages. Asymptomatic individuals transmitted SARS-CoV-2 at similar levels to symptomatic individuals suggesting that interventions targeting symptomatic individuals such as symptom-based testing and contact tracing of individuals tested because they report symptoms may have a limited impact as control measures. Increased household transmission of Beta and Delta variants, likely contributed to recurrent waves of COVID-19, with >60% of individuals infected by the end of follow-up. Higher attack rates, reinfection and acquisition in adolescents and prolonged SARS-CoV-2 shedding in PLHIV who were not virally suppressed suggests that prioritised vaccination of individuals in these groups could impact community transmission.", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21260707", + "rel_abs": "Understanding the factors that increase the transmissibility of the recently emerging variants of SARS-CoV-2 (such as the Alpha, Epsilon, and Delta variants) can aid in mitigating their spread. The enhanced transmissibility could be attributed to one or more factors: higher stability on surfaces or within droplet nuclei suspended in air, increased maximal viral load or higher probability of infection. The relative importance of these factors on the transmission was examined using a validated stochastic-jump-continuous hybrid model. The transmissibility was quantified in terms of the household secondary attack rate (hSAR) which is the probability of transmission from an infected individual to a susceptible one in a household. We find that an increase in either the maximal viral load or the probability of infection is consistent with the observed hSAR of the variants. Specifically, in order to reach the relative increase in the hSAR of 40%, 55%, and 87% reported for the Epsilon, Alpha, and Delta variants (respectively), the maximal viral load should increase by 56%, 78%, and 125%, respectively. Alternatively, the probability of infection should increase by 34%, 53%, and 193%, respectively. Contrary to these results, even a dramatic increase in environmental stability increases hSAR by no more than 10%.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Cheryl Cohen", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Jackie Kleynhans", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Anne von Gottberg", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Meredith McMorrow", - "author_inst": "Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America" - }, - { - "author_name": "Nicole Wolter", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Jinal Bhiman", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Jocelyn Moyes", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Mignon du Plessis", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Maimuna Carrim", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Amelia Buys", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Neil A Martinson", - "author_inst": "Perinatal HIV Research Unit, Medical Research Council (MRC) Soweto Matlosana Collaborating Centre for HIV/AIDS and Tuberculosis, South Africa" - }, - { - "author_name": "Kathleen Kahn", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" - }, - { - "author_name": "Stephen Tollman", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" - }, - { - "author_name": "Limakatso Lebina", - "author_inst": "Perinatal HIV Research Unit, Medical Research Council (MRC) Soweto Matlosana Collaborating Centre for HIV/AIDS and Tuberculosis, South Africa" - }, - { - "author_name": "Floidy Wafawanaka", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" - }, - { - "author_name": "Jacques du Toit", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" - }, - { - "author_name": "Francesc Xavier Gomez-Olive", - "author_inst": "MRC/Wits Rural Public Health and Health Transitions Research Unit (Agincourt), School of Public Health, Faculty of Health Sciences, University of the Witwatersr" - }, - { - "author_name": "Fatima Dawood", - "author_inst": "Influenza Division, Centers for Disease Control and Prevention, Atlanta, Georgia, United States of America" - }, - { - "author_name": "Thulisa Mkhencele", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" - }, - { - "author_name": "Kaiyuan Sun", - "author_inst": "Fogarty International Center, National Institutes of Health" + "author_name": "Yehuda Arav", + "author_inst": "Israel Institute for Biological Reaserch" }, { - "author_name": "Cecile Viboud", - "author_inst": "Fogarty International Center, National Institutes of Health" + "author_name": "Eyal Fattal", + "author_inst": "Israeli Institute for Biological Research" }, { - "author_name": "Stefano Tempia", - "author_inst": "Centre for Respiratory Diseases and Meningitis, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Afri" + "author_name": "Ziv Klausner", + "author_inst": "Israel Institute for Biological Research" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -674640,29 +675159,33 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.07.18.21260567", - "rel_title": "Predicting Managers' Mental Health Across Countries Using Country-Level COVID-19 Statistics", + "rel_doi": "10.1101/2021.07.21.21260881", + "rel_title": "Understanding COVID-19 Vaccine Early Skepticism and Misinformation", "rel_date": "2021-07-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.18.21260567", - "rel_abs": "BackgroundThere is limited research focusing on publicly available statistics on the Coronavirus disease 2019 (COVID-19) pandemic as predictors of mental health across countries. Managers are at risk of suffering from mental disorders during the pandemic because they face particular hardship.\n\nObjectiveWe aim to predict mental disorder (anxiety and depression) symptoms of managers across countries using country-level COVID-19 statistics.\n\nMethodsA two-wave online survey of 406 managers from 26 countries was finished in May and July 2020. We used logistic panel regression models for our main analyses and performed robustness checks using ordinary least squares regressions. In the sample of 406 managers from 26 countries, 26.5% of managers reached the cut-off levels for anxiety (General Anxiety Disorder-7; GAD-7) and 43.5% did so for depression (Patient Health Questionnaire-9; PHQ-9) symptoms.\n\nFindingsWe found that cumulative COVID-19 statistics (e.g., cumulative cases, cumulative cases per million, cumulative deaths, and cumulative deaths per million) predicted managers anxiety and depression symptoms positively, whereas daily COVID-19 statistics (daily new cases, smoothed daily new cases, daily new deaths, smoothed daily new deaths, daily new cases per million, and smoothed daily new cases per million) predicted anxiety and depression symptoms negatively. In addition, the reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor. Individually, we found that the cumulative count of deaths is the best single predictor of both anxiety and depression symptoms.\n\nConclusionsCumulative COVID-19 statistics predicted managers anxiety and depression symptoms positively, while non-cumulative daily COVID-19 statistics predicted anxiety and depression symptoms negatively. Cumulative count of deaths is the best single predictor of both anxiety and depression symptoms. Reproduction rate was a positive predictor, while stringency of governmental lockdown measures was a negative predictor.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.21.21260881", + "rel_abs": "Recent polls report that approximately 18% of healthcare workers are still skeptical about getting vaccinated. These professionals play a key role as communicators to their patients and community members. Understanding their concerns and informational needs, as well as those of other essential workers, is important for building an effective communication strategy for the whole population. This study presents the results of a survey of 1,591 hesitant U.S. essential workers, conducted in December 2020, when they were the only group eligible for the vaccine, aiming to describe their concerns regarding the COVID-19 vaccine and related policies. Results show that freedom of choice, concerns about equal access to the vaccine and being able to live a life with no restrictions once vaccinated, were important issues since the early days of the distribution campaign. Vaccine communication campaigns and distribution policies should address both non-medical and medical concerns with the same relevance.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Lun Li", - "author_inst": "School of Economics and Management, Tsinghua University" + "author_name": "Elena Savoia", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Stephen X. Zhang", - "author_inst": "University of Adelaide" + "author_name": "Maxwell Su", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Lorenz Graf-Vlachy", - "author_inst": "TU Dortmund University, Dortmund, Germany & ESCP Business School, Berlin, Germany" + "author_name": "Rachael Piltch-Loeb", + "author_inst": "Harvard TH Chan School of Public Health" + }, + { + "author_name": "Marcia A Testa", + "author_inst": "Harvard T.H. Chan School of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -676522,191 +677045,71 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.07.16.452756", - "rel_title": "Comparison of heat-inactivated and infectious SARS-CoV-2 across indoor surface materials shows comparable RT-qPCR viral signal intensity and persistence", + "rel_doi": "10.1101/2021.07.16.21260627", + "rel_title": "High frequency, high throughput quantification of SARS-CoV-2 RNA in wastewater settled solids at eight publicly owned treatment works in Northern California shows strong association with COVID-19 incidence", "rel_date": "2021-07-20", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.16.452756", - "rel_abs": "Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with COVID-19 and inform appropriate infection mitigation responses. Research groups have reported detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2 positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative polymerase chain reaction (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over seven days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle (Cq)) can be correlated to surface viral load using only one linear regression model per material category. The same experiment was performed with infectious viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods.\n\nImportanceEnvironmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made towards containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) [1], a large-scale environmental monitoring effort in elementary school and child care settings, has processed > 13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT - qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.", - "rel_num_authors": 43, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.16.21260627", + "rel_abs": "A number of recent retrospective studies have demonstrated that SARS-CoV-2 RNA concentrations in wastewater are associated with COVID-19 cases in the corresponding sewersheds. Implementing high-resolution, prospective efforts across multiple plants depends on sensitive measurements that are representative of COVID-19 cases, scalable for high throughput analysis, and comparable across laboratories. We conducted a prospective study across eight publicly owned treatment works (POTWs). A focus on SARS-CoV-2 RNA in solids enabled us to scale-up our measurements with a commercial lab partner. Samples were collected daily and results were posted to a website within 24-hours. SARS-CoV-2 RNA in daily samples correlated to incidence COVID-19 cases in the sewersheds; a 1 log10 increase in SARS-CoV-2 RNA in settled solids corresponds to a 0.58 log10 (4X) increase in sewershed incidence rate. SARS-CoV-2 RNA signals measured with the commercial laboratory partner were comparable across plants and to measurements conducted in a university laboratory when normalized by pepper mild mottle virus PMMoV RNA. Results suggest that SARS-CoV-2 RNA should be detectable in settled solids for COVID-19 incidence rates > 1/100,000 (range 0.8 - 2.3 cases per 100,000). These sensitive, representative, scalable, and comparable methods will be valuable for future efforts to scale-up wastewater-based epidemiology.\n\nImportanceAccess to reliable, rapid monitoring data is critical to guide response to an infectious disease outbreak. For pathogens that are shed in feces or urine, monitoring wastewater can provide a cost-effective snapshot of transmission in an entire community via a single sample. In order for a method to be useful for ongoing COVID-19 monitoring, it should be sensitive for detection of low concentrations of SARS-CoV-2, representative of incidence rates in the community, scalable to generate data quickly, and comparable across laboratories. This paper presents a method utilizing wastewater solids to meet these goals, producing measurements of SARS-CoV-2 RNA strongly associated with COVID-19 cases in the sewershed of a publicly owned treatment work. Results, provided within 24 hrs, can be used to detect incidence rates as low as approximately 1/100,000 cases and can be normalized for comparison across locations generating data using different methods.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Rodolfo A. Salido", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Victor J. Cant\u00fa", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Alex E Clark", - "author_inst": "University of California San Diego" - }, - { - "author_name": "Sandra L. Leibel", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Anahid Foroughishafiei", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Anushka Saha", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Abbas Hakim", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Alhakam Nouri", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Alma L. Lastrella", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Anelizze Castro-Mart\u00ednez", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Ashley Plascencia", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Bhavika Kapadia", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Bing Xia", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Christopher Ruiz", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Clarisse (Lisa) Marotz", - "author_inst": "UC San Diego" - }, - { - "author_name": "Daniel Maunder", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Elijah S. Lawrence", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Elizabeth W. Smoot", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Emily Eisner", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Evelyn S. Crescini", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Laura Kohn", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Lizbeth Franco Vargas", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Marisol Chac\u00f3n", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Maryan Betty", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Michal Machnicki", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Min Yi Wu", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Nathan A. Baer", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Pedro Belda-Ferre", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Peter DeHoff", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Phoebe Saever", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "R. Tyler Ostrander", - "author_inst": "University of California, San Diego" + "author_name": "Marlene K Wolfe", + "author_inst": "Stanford University" }, { - "author_name": "Rebecca Tsai", - "author_inst": "University of California, San Diego" + "author_name": "Aaron Topol", + "author_inst": "Verily Life Sciences" }, { - "author_name": "Shashank Sathe", - "author_inst": "University of California, San Diego" + "author_name": "Alisha Knudson", + "author_inst": "Verily Life Sciences" }, { - "author_name": "Stefan Aigner", - "author_inst": "University of California, San Diego" + "author_name": "Adrian Simpson", + "author_inst": "Verily Life Sciences" }, { - "author_name": "Sydney C Morgan", - "author_inst": "University of California, San Diego" + "author_name": "Bradley J White", + "author_inst": "Verily Life Sciences" }, { - "author_name": "Toan T. Ngo", - "author_inst": "University of California, San Diego" + "author_name": "Duc J Vugia", + "author_inst": "California Department of Public Health" }, { - "author_name": "Tom Barber", - "author_inst": "University of California, San Diego" + "author_name": "Alexander T Yu", + "author_inst": "California Department of Public Health" }, { - "author_name": "Willi Cheung", - "author_inst": "University of California, San Diego" + "author_name": "Linlin Li", + "author_inst": "County of Santa Clara Public Health Department" }, { - "author_name": "Aaron F Carlin", - "author_inst": "University of California San Diego" + "author_name": "Michael Balliet", + "author_inst": "County of Santa Clara Department of Environmental Health" }, { - "author_name": "Gene W. Yeo", - "author_inst": "University of California, San Diego" + "author_name": "Pamela Stoddard", + "author_inst": "County of Santa Clara Public Health Department" }, { - "author_name": "Louise Laurent", - "author_inst": "University of California, San Diego" + "author_name": "George S Han", + "author_inst": "County of Santa Clara Public Health Department" }, { - "author_name": "Rebecca Fielding-Miller", - "author_inst": "University of California, San Diego" + "author_name": "Krista R Wigginton", + "author_inst": "University of Michigan" }, { - "author_name": "Rob Knight", - "author_inst": "UCSD School of Medicine" + "author_name": "Alexandria B Boehm", + "author_inst": "Stanford University" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2021.07.14.21260550", @@ -678340,73 +678743,125 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.15.21260561", - "rel_title": "Viral Load of SARS-CoV-2 in Respiratory Aerosols Emitted by COVID-19 Patients while Breathing, Talking, and Singing", + "rel_doi": "10.1101/2021.07.15.21260537", + "rel_title": "Characterising within-hospital SARS-CoV-2 transmission events: a retrospective analysis integrating epidemiological and viral genomic data from a UK tertiary care setting across two pandemic waves", "rel_date": "2021-07-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.15.21260561", - "rel_abs": "BackgroundMultiple SARS-CoV-2 superspreading events suggest that aerosols play an important role in driving the COVID-19 pandemic. However, the detailed roles of coarse (>5m) and fine ([≤]5m) respiratory aerosols produced when breathing, talking, and singing are not well-understood.\n\nMethodsUsing a G-II exhaled breath collector, we measured viral RNA in coarse and fine respiratory aerosols emitted by COVID-19 patients during 30 minutes of breathing, 15 minutes of talking, and 15 minutes of singing.\n\nResultsAmong the 22 study participants, 13 (59%) emitted detectable levels of SARS-CoV-2 RNA in respiratory aerosols, including 3 asymptomatic patients and 1 presymptomatic patient. Viral loads ranged from 63-5,821 N gene copies per expiratory activity per patient. Patients earlier in illness were more likely to emit detectable RNA, and loads differed significantly between breathing, talking, and singing. The largest proportion of SARS-CoV-2 RNA copies was emitted by singing (53%), followed by talking (41%) and breathing (6%). Overall, fine aerosols constituted 85% of the viral load detected in our study. Virus cultures were negative.\n\nConclusionsFine aerosols produced by talking and singing contain more SARS-CoV-2 copies than coarse aerosols and may play a significant role in the transmission of SARS-CoV-2. Exposure to fine aerosols should be mitigated, especially in indoor environments where airborne transmission of SARS-CoV-2 is likely to occur. Isolating viable SARS-CoV-2 from respiratory aerosol samples remains challenging, and whether this can be more easily accomplished for emerging SARS-CoV-2 variants is an important enquiry for future studies.\n\nKey PointsWe sampled respiratory aerosols emitted by COVID-19 patients and discovered that fine aerosols ([≤]5m) generated during talking and singing contain more SARS-CoV-2 copies than coarse aerosols (>5m) and may play a significant role in the transmission of SARS-CoV-2.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.15.21260537", + "rel_abs": "Structured abstractO_ST_ABSObjectivesC_ST_ABSTo characterise within-hospital SARS-CoV-2 transmission across two waves of the COVID-19 pandemic.\n\nDesignA retrospective Bayesian modelling study to reconstruct transmission chains amongst 2181 patients and healthcare workers using combined viral genomic and epidemiological data.\n\nSettingA large UK NHS Trust with over 1400 beds and employing approximately 17,000 staff.\n\nParticipants780 patients and 522 staff testing SARS-CoV-2 positive between 1st March 2020 and 25th July 2020 (Wave 1); and 580 patients and 299 staff testing SARS-CoV-2 positive between 30th November 2020 and 24th January 2021 (Wave 2).\n\nMain outcome measuresTransmission pairs including who-infected-whom; location of transmission events in hospital; number of secondary cases from each individual, including differences in onward transmission from community and hospital onset patient cases.\n\nResultsStaff-to-staff transmission was estimated to be the most frequent transmission type during Wave 1 (31.6% of observed hospital-acquired infections; 95% CI 26.9 to 35.8%), decreasing to 12.9% (95% CI 9.5 to 15.9%) in Wave 2. Patient-to-patient transmissions increased from 27.1% in Wave 1 (95% CI 23.3 to 31.4%) to 52.1% (95% CI 48.0 to 57.1%) in Wave 2, to become the predominant transmission type. Over 50% of hospital-acquired infections were concentrated in 8/120 locations in Wave 1 and 10/93 locations in Wave 2. Approximately 40% to 50% of hospital-onset patient cases resulted in onward transmission compared to less than 4% of definite community-acquired cases.\n\nConclusionsPrevention and control measures that evolved during the COVID-19 pandemic may have had a significant impact on reducing infections between healthcare workers, but were insufficient during the second wave to prevent a high number of patient-to-patient transmissions. As hospital-acquired cases appeared to drive most onward transmissions, more frequent and rapid identification and isolation of these cases will be required to break hospital transmission chains in subsequent pandemic waves.", + "rel_num_authors": 28, "rel_authors": [ { - "author_name": "Kristen K. Coleman", - "author_inst": "Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore" + "author_name": "Benjamin B Lindsey", + "author_inst": "University of Sheffield" }, { - "author_name": "Douglas Jie Wen Tay", - "author_inst": "Department of the Built Environment, National University of Singapore, Singapore" + "author_name": "Ch. Juli\u00e1n Villabona-Arenas", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Kai Sen Tan", - "author_inst": "Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore" + "author_name": "Finlay Campbell", + "author_inst": "World Health Organization" }, { - "author_name": "Sean Wei Xiang Ong", - "author_inst": "National Centre for Infectious Diseases, Singapore" + "author_name": "Alexander J Keeley", + "author_inst": "University of Sheffield" }, { - "author_name": "Than The Son", - "author_inst": "Programme in Emerging Infectious Diseases, Duke-NUS Medical School, Singapore" + "author_name": "Matthew D Parker", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Dhruv R Shah", + "author_inst": "University of Sheffield" }, { - "author_name": "Ming Hui Koh", - "author_inst": "Department of the Built Environment, National University of Singapore, Singapore" + "author_name": "Helena Parsons", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust" }, { - "author_name": "Yi Qing Chin", - "author_inst": "National Centre for Infectious Diseases, Singapore" + "author_name": "Peijun Zhang", + "author_inst": "University of Sheffield" }, { - "author_name": "Haziq Nasir", - "author_inst": "Division of Infectious Diseases, Department of Medicine, National University Health System, National University of Singapore, Singapore" + "author_name": "Nishchay Kakkar", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust" }, { - "author_name": "Tze Minn Mak", - "author_inst": "National Centre for Infectious Diseases, Singapore" + "author_name": "Marta Gallis", + "author_inst": "University of Sheffield" }, { - "author_name": "Justin Jang Hann Chu", - "author_inst": "Biosafety Level 3 Core Facility, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore" + "author_name": "Benjamin H Foulkes", + "author_inst": "University of Sheffield" }, { - "author_name": "Donald K. Milton", - "author_inst": "Maryland Institute for Applied Environmental Health, University of Maryland School of Public Health, USA" + "author_name": "Paige Wolverson", + "author_inst": "University of Sheffield" }, { - "author_name": "Vincent T.K. Chow", - "author_inst": "Infectious Diseases Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singap" + "author_name": "Stavroula F Louka", + "author_inst": "University of Sheffield" }, { - "author_name": "Paul Anantharajah Tambyah", - "author_inst": "Division of Infectious Diseases, Department of Medicine, National University Health System, National University of Singapore, Singapore" + "author_name": "Stella Christou", + "author_inst": "University of Sheffield" }, { - "author_name": "Mark Chen", - "author_inst": "National Centre for Infectious Diseases, Singapore" + "author_name": "Amy State", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust" + }, + { + "author_name": "Katie Johnson", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust" + }, + { + "author_name": "Mohammad Raza", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust" + }, + { + "author_name": "Sharon Hsu", + "author_inst": "University of Sheffield" + }, + { + "author_name": "Thibaut Jombart", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Anne Cori", + "author_inst": "Imperial College London" + }, + { + "author_name": "- Sheffield COVID-19 Genomics Group", + "author_inst": "" + }, + { + "author_name": "- The COVID-19 Genomics UK (COG-UK) consortium", + "author_inst": "" + }, + { + "author_name": "- CMMID COVID-19 working group", + "author_inst": "" + }, + { + "author_name": "Cariad M Evans", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust" + }, + { + "author_name": "David G Partridge", + "author_inst": "Sheffield Teaching Hospitals NHS Foundation Trust" + }, + { + "author_name": "Katherine E Atkins", + "author_inst": "University of Edinburgh" }, { - "author_name": "Tham Kwok Wai", - "author_inst": "Department of the Built Environment, National University of Singapore, Singapore" + "author_name": "St\u00e9phane Hu\u00e9", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Thushan I de Silva", + "author_inst": "University of Sheffield" } ], "version": "1", @@ -680254,51 +680709,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.07.16.452748", - "rel_title": "Key substitutions in the spike protein of SARS-CoV-2 variants can predict resistance to monoclonal antibodies, but other substitutions can modify the effects", + "rel_doi": "10.1101/2021.07.19.21258787", + "rel_title": "Dique Filipeia: A rehabilitation protocol for non-intubated COVID-19 in-hospital patients", "rel_date": "2021-07-19", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.16.452748", - "rel_abs": "Mutations in the spike protein of SARS-CoV-2 variants can compromise the effectiveness of therapeutic antibodies. Most clinical-stage therapeutic antibodies target the spike receptor binding domain (RBD), but variants often have multiple mutations in several spike regions. To help predict antibody potency against emerging variants, we evaluated 25 clinical-stage therapeutic antibodies for neutralization activity against 60 pseudoviruses bearing spikes with single or multiple substitutions in several spike domains, including the full set of substitutions in B.1.1.7 (Alpha), B.1.351 (Beta), P.1 (Gamma), B.1.429 (Epsilon), B.1.526 (Iota), A.23.1 and R.1 variants. We found that 14 of 15 single antibodies were vulnerable to at least one RBD substitution, but most combination and polyclonal therapeutic antibodies remained potent. Key substitutions in variants with multiple spike substitutions predicted resistance, but the degree of resistance could be modified in unpredictable ways by other spike substitutions that may reside outside of the RBD. These findings highlight the importance of assessing antibody potency in the context of all substitutions in a variant and show that epistatic interactions in spike can modify virus susceptibility to therapeutic antibodies.\n\nImportanceTherapeutic antibodies are effective in preventing severe disease from SARS-CoV-2 infection (COVID-19), but their effectiveness may be reduced by virus variants with mutations affecting the spike protein. To help predict resistance to therapeutic antibodies in emerging variants, we profiled resistance patterns of 25 antibody products in late stages of clinical development against a large panel of variants that include single and multiple substitutions found in the spike protein. We found that the presence of a key substitution in variants with multiple spike substitutions can predict resistance against a variant, but that other substitutions can affect the degree of resistance in unpredictable ways. These finding highlight complex interactions among substitutions in the spike protein affecting virus neutralization and potentially virus entry into cells.", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.19.21258787", + "rel_abs": "ObjectiveThe aim of this study was to evaluate the effectiveness of the \"Dique Filipeia\" rehabilitation protocol in patients with COVID-19 admitted to reference hospitals.\n\nMethodsThis is an experimental study with COVID-19 patients admitted to the hospitals wards being considered eligible. The study outcomes were assessed between patients undergoing the rehabilitation protocol (Dique Filipeia group) and patients who did not receive the protocol (control group). The rehabilitation protocol consisted in classifying patients daily into four levels of severity through peripheral oxygen saturation. Severity was classified by the oxygen flow needed to maintain a saturation greater than or equal to the cut-off point of 93%. A standardized ventilatory support and functional rehabilitation exercises were performed for each severity level patient, followed by an attempt to wean oxygen.\n\nResultsA total of 727 patients were analyzed in the study. The Dique Filipeia group presented a lower total (132.7 {+/-} 35.3 vs 307.0 {+/-} 114.3 m3/patient; effect size 1.73) and daily (2.9 {+/-} 1.0 vs 6.8 {+/-} 3.1 m3/day/patient; effect size 1.46) oxygen expenditure than the control group. The Dique Filipeia patients presented higher hospital discharge (64.9 {+/-} 9.3 vs 35.4 {+/-} 7.5%; effect size 3.46) and lower length of stay (15.8 {+/-} 4.2 vs 29.1 {+/-} 3.4 days; effect size 3.47) than the control group. The Dique Filipeia group patients, who were demanding oxygen therapy, were using 6.2 {+/-} 4.3 L/min of oxygen at day 1. There was a statistically significant reduction from day 2 (p = 0.0001) and oxygen flow was reduced below 1L/min after day 7.\n\nConclusionsThe implementation of a standardized rehabilitation protocol reduced oxygen expenditure, increased hospital discharge and reduced the length of hospital stay. Dique Filipeia is a practical, feasible and safe protocol.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sabrina Lusvarghi", - "author_inst": "US Food and Drug Administration" + "author_name": "Murillo Frazao", + "author_inst": "Municipal Health Department, Joao Pessoa, PB" }, { - "author_name": "Wei Wang", - "author_inst": "US Food and Drug Administration" + "author_name": "Kamila Marinho Paiva", + "author_inst": "Municipal Health Department, Joao Pessoa, PB" }, { - "author_name": "Rachel Herrup", - "author_inst": "US Food and Drug Administration" + "author_name": "Rossana Maria da Nova S", + "author_inst": "Municipal Health Department, Joao Pessoa, PB" }, { - "author_name": "Sabari Nath Neerukonda", - "author_inst": "US Food and Drug Administration" + "author_name": "Fabio dos Santos Menezes", + "author_inst": "Municipal Health Department, Joao Pessoa, PB" }, { - "author_name": "Russell Vassell", - "author_inst": "US Food and Drug Administration" + "author_name": "Lais Ailenny dos Santos Alves", + "author_inst": "Laboratory of Physical Training Studies Applied to Health, Federal University of Paraiba" }, { - "author_name": "Lisa Bentley", - "author_inst": "Office of the Assistance Secretary for Preparedness and Response, US Department of Human Health and Services" + "author_name": "Anderson Igor Silva de Souza Rocha", + "author_inst": "Laboratory of Physical Training Studies Applied to Health, Federal University of Paraiba" }, { - "author_name": "Ann E. Eakin", - "author_inst": "US National Institutes of Health" + "author_name": "Eduardo Eriko Tenorio Franca", + "author_inst": "Physiotherapy Laboratory in Cardiorespiratory Research, Federal University of Paraiba" }, { - "author_name": "Carol D. Weiss", - "author_inst": "US Food and Drug Administration" + "author_name": "Amilton da Cruz Santos", + "author_inst": "Laboratory of Physical Training Studies Applied to Health, Federal University of Paraiba" + }, + { + "author_name": "Maria do Socorro Brasileiro-Santos", + "author_inst": "Laboratory of Physical Training Studies Applied to Health, Federal University of Paraiba" } ], "version": "1", - "license": "cc0", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "rehabilitation medicine and physical therapy" }, { "rel_doi": "10.1101/2021.07.13.21260425", @@ -682236,41 +682695,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.13.21260442", - "rel_title": "Rapid and Quantitative Detection of Human Antibodies Against the 2019 Novel Coronavirus SARS CoV2 and its Variants as a Result of Vaccination and Infection", + "rel_doi": "10.1101/2021.07.13.21260426", + "rel_title": "Persistence of neutralizing antibodies a year after SARS-CoV-2 infection", "rel_date": "2021-07-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.13.21260442", - "rel_abs": "Measuring the antibody response to 2019 SARS CoV2 is critical for diagnostic purposes, monitoring the prevalence of infection, and for gauging the efficacy of the worldwide vaccination effort COVID-19. In this study, a microchip-based grating coupled fluorescent plasmonic (GC-FP) assay was used to measure antibody levels that resulted from COVID-19 infection and vaccination. In addition, we measured the relative antibody binding towards antigens from variants CoV2 virus variants, strains B.1.1.7 (UK) and B.1.351 (S. African). Antibody levels against multiple antigens within the SARS CoV2 spike protein were significantly elevated for both vaccinated and infected individuals, while those against the nucleocapsid (N) protein were only elevated for infected individuals. GC-FP was effective for monitoring the IgG-based serological response to vaccination throughout the vaccination sequence, and could also resolve acute (within hours) increases in antibody levels. A significant decrease in antibody binding to antigens from the B.1.351 variant, but not B.1.1.7, was observed for all vaccinated subjects when measured by GC-FP as compared to the 2019 SARS CoV2 antigens. These results were corroborated by competitive ELISA assay. Collectively, the findings suggest that GC-FP is a viable, rapid, and accurate method for measuring both overall antibody levels to CoV2 and relative antibody binding to viral variants during infection or vaccination.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.13.21260426", + "rel_abs": "Understanding for how long antibodies persist following Severe acute respiratory coronavirus 2 (SARS-CoV-2) infection provides important insight into estimating the duration of immunity induced by infection.\n\nWe assessed the persistence of serum antibodies following wild-type SARS-CoV-2 infection six and twelve months after diagnosis in 367 individuals of whom 13% had severe disease requiring hospitalization. We determined the SARS-CoV-2 spike (S-IgG) and nucleoprotein IgG concentrations and the proportion of subjects with neutralizing antibodies (NAb). We also measured the NAb titers among a smaller subset of participants (n=78) against a wild-type virus (B.1) and three variants of concern (VOCs): Alpha (B.1.1.7), Beta (B.1.351) and Delta (B.1.617.2).\n\nWe found that NAb against the wild-type virus and S-IgG persisted in 89% and 97% of subjects for at least twelve months after infection, respectively. IgG and NAb levels were higher after severe infection. NAb titers were significantly lower against variants compared to the wild-type virus.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Benjamin Taubner", - "author_inst": "SUNY Polytechnic Institute" + "author_name": "Anu Haveri", + "author_inst": "Finnish Institute for Health and Welfare" }, { - "author_name": "Ruben Peredo-Wende", - "author_inst": "Albany Medical Center" + "author_name": "Nina Ekstr\u00f6m", + "author_inst": "Finnish Institute for Health and Welfare" }, { - "author_name": "Ananthakrishnan Ramani", - "author_inst": "Albany Medical Center" + "author_name": "Anna Solastie", + "author_inst": "Finnish Institute for Health and Welfare" }, { - "author_name": "Gurpreet Singh", - "author_inst": "Albany Medical Center" + "author_name": "Camilla Virta", + "author_inst": "Finnish Institute for Health and Welfare" }, { - "author_name": "Klemen Strle", - "author_inst": "Wadsworth Center" + "author_name": "Pamela \u00d6sterlund", + "author_inst": "Finnish Institute for Health and Welfare" }, { - "author_name": "Nathaniel Cady", - "author_inst": "SUNY Polytechnic Institute" + "author_name": "Elina Isosaari", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Hanna Nohynek", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Arto A Palmu", + "author_inst": "Finnish Institute for Health and Welfare" + }, + { + "author_name": "Merit Melin", + "author_inst": "Finnish Institute for Health and Welfare" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -683754,159 +684225,119 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.07.12.21260360", - "rel_title": "The impact of hypoxia on B cells in COVID-19", + "rel_doi": "10.1101/2021.07.15.452246", + "rel_title": "Gut microbiome dysbiosis during COVID-19 is associated with increased risk for bacteremia and microbial translocation.", "rel_date": "2021-07-15", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.12.21260360", - "rel_abs": "Prominent early features of COVID-19 include severe, often clinically silent, hypoxia and a pronounced reduction in B cells, the latter important in defence against SARS-CoV-2. This brought to mind the phenotype of mice with VHL-deficient B cells, in which Hypoxia-Inducible Factors are constitutively active, suggesting hypoxia might drive B cell abnormalities in COVID-19. We demonstrated the breadth of early and persistent defects in B cell subsets in moderate/severe COVID-19, including reduced marginal zone-like, memory and transitional B cells, changes we also observed in B cell VHL-deficient mice. This was corroborated by hypoxia-related transcriptional changes in COVID-19 patients, and by similar B cell abnormalities in mice kept in hypoxic conditions, including reduced marginal zone and germinal center B cells. Thus hypoxia might contribute to B cell pathology in COVID-19, and in other hypoxic states. Through this mechanism it may impact on COVID-19 outcome, and be remediable through early oxygen therapy.", - "rel_num_authors": 35, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.15.452246", + "rel_abs": "The microbial populations in the gut microbiome have recently been associated with COVID-19 disease severity. However, a causal impact of the gut microbiome on COVID-19 patient health has not been established. Here we provide evidence that gut microbiome dysbiosis is associated with translocation of bacteria into the blood during COVID-19, causing life-threatening secondary infections. Antibiotics and other treatments during COVID-19 can potentially confound microbiome associations. We therefore first demonstrate in a mouse model that SARS-CoV-2 infection can induce gut microbiome dysbiosis, which correlated with alterations to Paneth cells and goblet cells, and markers of barrier permeability. Comparison with stool samples collected from 96 COVID-19 patients at two different clinical sites also revealed substantial gut microbiome dysbiosis, paralleling our observations in the animal model. Specifically, we observed blooms of opportunistic pathogenic bacterial genera known to include antimicrobial-resistant species in hospitalized COVID-19 patients. Analysis of blood culture results testing for secondary microbial bloodstream infections with paired microbiome data obtained from these patients indicates that bacteria may translocate from the gut into the systemic circulation of COVID-19 patients. These results are consistent with a direct role for gut microbiome dysbiosis in enabling dangerous secondary infections during COVID-19.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Prasanti Kotagiri", - "author_inst": "Cambridge University" - }, - { - "author_name": "Federica Mescia", - "author_inst": "Cambridge University" - }, - { - "author_name": "Aimee Hanson", - "author_inst": "Cambridge University" - }, - { - "author_name": "Lorinda Turner", - "author_inst": "Cambridge University" - }, - { - "author_name": "Laura Bergamaschi", - "author_inst": "Cambridge University" - }, - { - "author_name": "Ana Penalver", - "author_inst": "Cambridge University" - }, - { - "author_name": "Nathan Richoz", - "author_inst": "Cambridge University" - }, - { - "author_name": "Stephen Moore", - "author_inst": "Cambridge University" - }, - { - "author_name": "Brian Ortmann", - "author_inst": "Cambridge University" - }, - { - "author_name": "Benjamin Dunmore", - "author_inst": "Cambridge University" - }, - { - "author_name": "Helene Ruffieux", - "author_inst": "Cambridge University" + "author_name": "Mericien Venzon", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Michael Morgan", - "author_inst": "Cambridge University" + "author_name": "Lucie Bernard-Raichon", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Zewen Kelvin Tuong", - "author_inst": "Cambridge University" + "author_name": "Jon Klein", + "author_inst": "Yale University School of Medicine" }, { - "author_name": "Rachael Bashford Rogers", - "author_inst": "Oxford University" + "author_name": "Jordan E. Axelrad", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Myra Hosmillo", - "author_inst": "Cambridge University" + "author_name": "Chenzhen Zhang", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Stephen Baker", - "author_inst": "Cambridge University" + "author_name": "Grant A. Hussey", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Anne Elmer", - "author_inst": "Cambridge University" + "author_name": "Alexis P. Sullivan", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Ian Goodfellow", - "author_inst": "Cambridge University" + "author_name": "Arnau Cassanovas-Massana", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Ravindra Gupta", - "author_inst": "Cambridge University" + "author_name": "Maria G. Noval", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Nathalie Kingston", - "author_inst": "Cambridge University" + "author_name": "Ana M. Valero-Jimenez", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Paul Lehner", - "author_inst": "Cambridge University" + "author_name": "Juan Gago", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Nicholas Matheson", - "author_inst": "Cambridge University" + "author_name": "Gregory Putzel", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Sylvia Richardson", - "author_inst": "Cambridge University" + "author_name": "Alejandro Pironti", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Caroline Saunders", - "author_inst": "Cambridge University" + "author_name": "Evan Wilder", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Michael Weekes", - "author_inst": "Cambridge University" + "author_name": "- Yale IMPACT Research Team", + "author_inst": "-" }, { - "author_name": "Berthold Gottgens", - "author_inst": "Cambridge University" + "author_name": "Lorna E. Thorpe", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Mark Toshner", - "author_inst": "Cambridge University" + "author_name": "Dan R. Littman", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Christoph Hess", - "author_inst": "Cambridge University" + "author_name": "Meike Dittmann", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Patrick Maxwell", - "author_inst": "Cambridge University" + "author_name": "Kenneth A. Stapleford", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Menna Clatworthy", - "author_inst": "Cambridge University" + "author_name": "Bo Shopsin", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "James A Nathan", - "author_inst": "Cambridge University" + "author_name": "Victor J. Torres", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "John Bradley", - "author_inst": "Cambridge University" + "author_name": "Albert I. Ko", + "author_inst": "Yale University School of Public Health" }, { - "author_name": "Paul Lyons", - "author_inst": "Cambridge University" + "author_name": "Akiko Iwasaki", + "author_inst": "Yale University School of Medicine" }, { - "author_name": "Natalie Burrows", - "author_inst": "Cambridge University" + "author_name": "Ken Cadwell", + "author_inst": "NYU Grossman School of Medicine" }, { - "author_name": "Kenneth G C Smith", - "author_inst": "Cambridge University" + "author_name": "Jonas Schluter", + "author_inst": "NYU Grossman School of Medicine" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2021.07.15.452507", @@ -685707,47 +686138,115 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2021.07.13.452256", - "rel_title": "Tissue Specific Age Dependence of the Cell Receptors Involved in the SARS-CoV-2 Infection", + "rel_doi": "10.1101/2021.07.13.452160", + "rel_title": "Adaptation, spread and transmission of SARS-CoV-2 in farmed minks and related humans in the Netherlands", "rel_date": "2021-07-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.13.452256", - "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic has affected tens of millions of individuals and caused hundreds of thousands of deaths worldwide. Due to its rapid surge, there is a shortage of information on viral behavior and host response after SARS-CoV-2 infection. Here we present a comprehensive, multiscale network analysis of the transcriptional response to the virus. We particularly focus on key-regulators, cell-receptors, and host-processes that are hijacked by the virus for its advantage. ACE2-controlled processes involve a key-regulator CD300e (a TYROBP receptor) and the activation of IL-2 pro-inflammatory cytokine signaling. We further investigate the age-dependency of such receptors and identify the adipose and the brain as potentially contributing tissues for the diseases severity in old patients. In contrast, several other tissues in the young population are more susceptible to SARS-CoV-2 infection. In summary, this present study provides novel insights into the gene regulatory organization during the SARS-CoV-2 infection and the tissue-specific age dependence of the cell receptors involved in COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.13.452160", + "rel_abs": "In the first wave of the COVID-19 pandemic (April 2020), SARS-CoV-2 was detected in farmed minks and genomic sequencing was performed on mink farms and farm personnel. Here, we describe the outbreak and use sequence data with Bayesian phylodynamic methods to explore SARS-CoV-2 transmission in minks and related humans on farms. High number of farm infections (68/126) in minks and farm related personnel (>50% of farms) were detected, with limited spread to the general human population. Three of five initial introductions of SARS-CoV-2 lead to subsequent spread between mink farms until November 2020. The largest cluster acquired a mutation in the receptor binding domain of the Spike protein (position 486), evolved faster and spread more widely and longer. Movement of people and distance between farms were statistically significant predictors of virus dispersal between farms. Our study provides novel insights into SARS-CoV-2 transmission between mink farms and highlights the importance of combing genetic information with epidemiological information at the animal-human interface.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Christian V Forst", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Lu Lu", + "author_inst": "Usher Institute of Population Health Sciences & Informatics, Ashworth Laboratories, Kings Buildings, University of Edinburgh, United Kingdom" }, { - "author_name": "Lu Zeng", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Reina S. Sikkema", + "author_inst": "Erasmus MC, Department of Viroscience, WHO collaborating centre, Rotterdam, the Netherlands" }, { - "author_name": "Qian Wang", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Francisca C. Velkers", + "author_inst": "Department Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands" }, { - "author_name": "Xianxiao Zhou", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "David F. Nieuwenhuijse", + "author_inst": "Erasmus MC, Department of Viroscience, WHO collaborating centre, Rotterdam, the Netherlands" }, { - "author_name": "Sezen Vatansever", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Egil A.J. Fischer", + "author_inst": "Department Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands" }, { - "author_name": "Zhidong Tu", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Paola A. Meijer", + "author_inst": "Department Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands" }, { - "author_name": "Bin Zhang", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Noortje Bouwmeester-Vincken", + "author_inst": "Municipal Health Service GGD Limburg-Noord, Venlo, the Netherlands" + }, + { + "author_name": "Ariene Rietveld", + "author_inst": "Municipal Health Service GGD Hart voor Brabant, the Netherlands" + }, + { + "author_name": "Marjolijn C.A. Wegdam-Blans", + "author_inst": "Stichting PAMM, Veldhoven, the Netherlands" + }, + { + "author_name": "Paulien Tolsma", + "author_inst": "Municipal Health Service GGD Brabant-Zuidoost, Eindhoven, the Netherlands" + }, + { + "author_name": "Marco Koppelman", + "author_inst": "Sanquin Blood Supply Foundation, Amsterdam" + }, + { + "author_name": "Lidwien A.M. Smit", + "author_inst": "Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, the Netherlands" + }, + { + "author_name": "Renate W. Hakze-van der Honing", + "author_inst": "Wageningen Bioveterinary Research, Lelystad, the Netherlands" + }, + { + "author_name": "Wim H. M. van der Poel", + "author_inst": "Wageningen Bioveterinary Research, Lelystad, the Netherlands" + }, + { + "author_name": "Arco N. van der Spek", + "author_inst": "Netherlands Food and Consumer Product Safety Authority (NVWA), Utrecht, the Netherlands" + }, + { + "author_name": "Marcel A. H. Spierenburg", + "author_inst": "Netherlands Food and Consumer Product Safety Authority (NVWA), Utrecht, the Netherlands" + }, + { + "author_name": "Robert Jan Molenaar", + "author_inst": "GD Animal Health, Deventer, the Netherlands" + }, + { + "author_name": "Jan de Rond", + "author_inst": "GD Animal Health, Deventer, the Netherlands" + }, + { + "author_name": "Marieke Augustijn", + "author_inst": "GD Animal Health, Deventer, the Netherlands" + }, + { + "author_name": "Mark Woolhouse", + "author_inst": "Usher Institute of Population Health Sciences & Informatics, Ashworth Laboratories, Kings Buildings, University of Edinburgh, United Kingdom" + }, + { + "author_name": "Arjan J. Stegeman", + "author_inst": "Department Population Health Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands" + }, + { + "author_name": "Samantha Lycett", + "author_inst": "Roslin Institute, University of Edinburgh, United Kingdom" + }, + { + "author_name": "Bas B. Oude Munnink", + "author_inst": "Erasmus MC, Department of Viroscience, WHO collaborating centre, Rotterdam, the Netherlands" + }, + { + "author_name": "Marion P. G. Koppelman", + "author_inst": "Erasmus MC, Department of Viroscience, WHO collaborating centre, Rotterdam, the Netherlands" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "systems biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.07.13.452288", @@ -687525,27 +688024,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.07.21260167", - "rel_title": "Indications that Stockholm has reached herd immunity, given limited restrictions, against several variants of SARS-CoV-2", + "rel_doi": "10.1101/2021.07.12.452071", + "rel_title": "TNF-\u03b1 levels in respiratory samples are associated with SARS-CoV-2 infection.", "rel_date": "2021-07-13", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.07.21260167", - "rel_abs": "\"When COVID-19 cases go up, public compliance with restrictions is poor, when cases go down, public compliance is good.\" In this article, we question this explanation and show that relatively low levels of sero-prevalence helps to keep cases down. In other words, the herd-immunity threshold appears to be much lower than previously thought. We construct a mathematical model taking pre-immunity, antibody waning and more infectious variants of concern into consideration, thereby providing a theoretical framework in which the cases in Stockholm county can be fully predicted without relying on neither oscillations in restrictions (and public compliance thereof) nor vaccination roll-out. We also show that it is very difficult to match the data from Stockholm without including pre-immunity, or, which turns out to be equivalent, great variations in susceptibility.", - "rel_num_authors": 2, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.12.452071", + "rel_abs": "PurposeThe aim of this study was to measure levels of IL-6 and TNF- in respiratory samples from individuals with symptoms compatible with COVID-19 and analyze their association with SARS-CoV-2 presence.\n\nMethodsSARS-CoV-2 detection was performed using the CDC (USA) real-time RT-PCR primers, probes and protocols. Cytokine concentrations were measured using commercial reagents based on enzyme linked immunosorbent assay (ELISA).\n\nResultsTNF- median levels were greater in COVID19 (+) symptomatic group (5.88 (1.36 - 172.1) pg/ml) compared to COVID19 (-) symptomatic individuals (2.87 (1.45 - 69.9) pg/ml) (p=0.0003). No significant differences were shown in IL-6 median values between COVID-19 (+) and (-) symptomatic patients (5.40 (1.7 - 467) pg/ml and 6.07 (1.57 - 466.6) pg/ml respectively). In addition, increased TNF- levels (greater than 10 pg/ml), but not IL-6, were associated with SARS-CoV-2 presence (OR= 5.7; p=0.006; 95% CI= 1,551 to 19,11).\n\nConclusionsWe found a statistically significant association between the production of local TNF- and the presence of the virus in early stages of infection. IL-6 showed high levels in swabs from some symptomatic patients but independent from SARS-CoV-2 presence and viral load, individuals age and gender. On the contrary, TNF- evaluation confirmed the presence of inflammatory response but mostly related to COVID-19. More studies are required in order to characterize the cytokine profile expressed at the site of infection of SARS-CoV-2 and its implications in disease outcomes.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Marcus Carlsson", - "author_inst": "Lund University" + "author_name": "Matias Javier Pereson", + "author_inst": "IBAVIM - Facultad de Farmacia y Bioquimica" }, { - "author_name": "Cecilia Soderberg-Naucler", - "author_inst": "Department of Medicine, Karolinska Institute" + "author_name": "Maria Noel Badano Sr.", + "author_inst": "Academia Nacional de Medicina" + }, + { + "author_name": "Natalia Aloisi Sr.", + "author_inst": "Academia Nacional de Medicina" + }, + { + "author_name": "Roberto Chuit Sr.", + "author_inst": "Academia Nacional de Medicina" + }, + { + "author_name": "Maria Marta Braco Sr.", + "author_inst": "Academia Nacional de Medicina" + }, + { + "author_name": "Patricia Bare Sr.", + "author_inst": "Academia Nacional de Medicina" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.07.12.452027", @@ -689331,37 +689846,53 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.07.07.21260153", - "rel_title": "Transient infection with SARS-CoV-2 without induction of systemic immunity", + "rel_doi": "10.1101/2021.07.08.21260201", + "rel_title": "High prevalence of previous infection with SARS-CoV-2 and persistent symptoms at a large university", "rel_date": "2021-07-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.07.21260153", - "rel_abs": "SARS-CoV-2 testing using PCR is currently used as screening test to guide isolation and contact tracing. Among 1,700 players and staff of the German Bundesliga and Bundesliga 2 who were regularly tested twice weekly, 98 individuals had a positive PCR. Among those, 11 asymptomatic cases were identified who only had a transient single positive PCR of low viral load. As only one out of 11 individuals developed SARS-CoV-2 specific cellular and humoral immunity, this indicates that transient colonization with SARS-CoV-2 may frequently occur without systemic induction of specific adaptive immunity. This knowledge may have implications for management of isolation and contact tracing, which may not be justified in these cases.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.08.21260201", + "rel_abs": "ImportanceUniversities are unique settings with large populations, congregate housing, and frequent attendance of events in large groups. However, the prevalence of previous infection with SARS-CoV-2 in university students, including symptomatic and asymptomatic disease, is unknown.\n\nObjectiveTo determine the prevalence of previous infection, risk factors for infection, and the prevalence of persistent symptoms following infection among university students.\n\nDesignThis was a cross-sectional study that surveyed students about demographics, risk factors, and symptoms, and simultaneously tested their saliva for IgA antibodies to SARS-CoV-2. To estimate the prevalence of previous infection we adjusted our intentional sample of a diverse student population for year in school and age to resemble the composition of the entire student body, and adjusted for the imperfect sensitivity and specificity of the antibody test. Univariate and multivariate analysis was used to identify independent risk factors for infection.\n\nSettingA large public university in Athens, Georgia between January 22 and March 22, 2021.\n\nParticipantsUndergraduate and graduate students; 488 completed the survey, 432 had a valid antibody result. and 428 had both.\n\nExposurePrevious infection with SARS-CoV-2 based on measurement of IgA antibodies in saliva and adjustment for sample characteristics and test accuracy.\n\nMain Outcomes and MeasuresThe primary outcome was the estimated prevalence of previous infection with SARS-CoV-2. Secondary outcomes were independent risk factors for infection, and the prevalence of persistent symptoms among persons reporting a previous symptomatic infection.\n\nResultsThe estimated prevalence of previous infection for 432 participants with valid antibody results was between 41% and 42%. Independent risk factors for infection included male sex, having a roommate with a known symptomatic infection, and having 2 or fewer roommates. More frequent attendance of parties and bars was a univariate risk factor, but not in the multivariate analysis. Of 122 students reporting a previous symptomatic infection, 14 (11.4%) reported persistent symptoms a median of 132 days later.\n\nConclusions and RelevancePrevious infection with SARS-CoV-2, both symptomatic and asymptomatic, was common at a large university. Measures that could prevent resurgence of the infection when students return to campus include mandatory vaccination policies, mass surveillance testing, and testing of sewage for antigen to SARS-CoV-2.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is the prevalence of previous infection with SARS-CoV-2 and the prevalence of persistent symptoms in university students?\n\nFindingsIn this sample of 432 students who provided saliva for IgA antibodies, we estimate that 41% to 42% had evidence of previous infection. Of 122 reporting a previous symptomatic infection, 14 (11%) were still symptomatic a median of 132 days later.\n\nMeaningSymptomatic and asymptomatic infections with SARS-CoV-2 are common among university students, and a significant percentage had persistent symptoms over a long duration.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Barbara C Gaertner", - "author_inst": "Saarland University, Institute for Medical Microbiology and Hygiene" + "author_name": "Mark H. Ebell", + "author_inst": "University of Georgia" }, { - "author_name": "Verena Klemis", - "author_inst": "Saarland University, Department of Transplant and Infection Immunology" + "author_name": "David Forgacs", + "author_inst": "University of Georgia" }, { - "author_name": "Tina Schmidt", - "author_inst": "Saarland University, Department of Transplant and Infection Immunology" + "author_name": "Ye Shen", + "author_inst": "University of Georgia" }, { - "author_name": "Martina Sester", - "author_inst": "Saarland University, Department of Transplant and Infection Immunology" + "author_name": "Ted Ross", + "author_inst": "University System of Georgia" }, { - "author_name": "Tim Meyer", - "author_inst": "Saarland University, Institute of Sports and Preventive Medicine" + "author_name": "Cassie Hulme", + "author_inst": "University of Georgia" + }, + { + "author_name": "Michelle Bentivegna", + "author_inst": "University of Georgia" + }, + { + "author_name": "Hannah Hanley", + "author_inst": "University of Georgia" + }, + { + "author_name": "Alexandria Jefferson", + "author_inst": "University of Georgia" + }, + { + "author_name": "Lauren Haines", + "author_inst": "University of Georgia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -691293,23 +691824,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.07.08.451640", - "rel_title": "Insights into the mutation T1117I in the spike and the lineage B.1.1.389 of SARS-CoV-2 circulating in Costa Rica", + "rel_doi": "10.1101/2021.07.08.451649", + "rel_title": "Structure of a germline-like human antibody defines a neutralizing epitope on the SARS-CoV-2 spike NTD", "rel_date": "2021-07-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.08.451640", - "rel_abs": "Emerging mutations and genotypes of the SARS-CoV-2 virus, responsible for the COVID-19 pandemic, have been reported globally. In Costa Rica during the year 2020, a predominant genotype carrying the mutation T1117I in the spike (S:T1117I) was previously identified. To investigate the possible effects of this mutation on the function of the spike, i.e. the biology of the virus, different bioinformatic pipelines based on phylogeny, natural selection and co-evolutionary models, molecular docking and epitopes prediction were implemented.\n\nResults of the phylogeny of sequences carrying the S:T1117I worldwide showed a polyphyletic group, with the emergency of local lineages. In Costa Rica, the mutation is found in the lineage B.1.1.389 and it is suggested to be a product of positive/adaptive selection. Different changes in the function of the spike protein and more stable interaction with a ligand (nelfinavir drug) were found. Only one epitope out 742 in the spike was affected by the mutation, with some different properties, but suggesting scarce changes in the immune response and no influence on the vaccine effectiveness.\n\nJointly, these results suggest a partial benefit of the mutation for the spread of the virus with this genotype during the year 2020 in Costa Rica, although possibly not strong enough with the introduction of new lineages during early 2021 which became predominant later. In addition, the bioinformatics pipeline offers an integrative and exhaustive in silico strategy to eventually study other mutations of interest for the SARS-CoV-2 virus and other pathogens.\n\nHighlightsO_LIIn Costa Rica during the year 2020, a predominant SARS-CoV-2 genotype carrying the mutation T1117I in the spike (S:T1117I) was identified.\nC_LIO_LIThe S:T1117I was assessed for possible effects of this mutation on the function of the spike with a in silico approach.\nC_LIO_LIPhylogeny revealed that sequences carrying the S:T1117I worldwide define a polyphyletic group, with the emergency of local lineages, including the lineage B.1.1.389 in Costa Rica.\nC_LIO_LIA positive/adaptive selection was identified for S:T1117I, with different changes in the function of the spike protein, more stable interaction with ligands and scarce changes in the immune response.\nC_LIO_LIThe bioinformatics pipeline can be eventually used to study other mutations of the SARS-CoV-2 virus and other pathogens.\nC_LI", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.08.451649", + "rel_abs": "Structural characterization of infection- and vaccination-elicited antibodies in complex with antigen provides insight into the evolutionary arms race between the host and the pathogen and informs rational vaccine immunogen design. We isolated a germline-like monoclonal antibody (mAb) from plasmablasts activated upon mRNA vaccination against SARS-CoV-2 and determined its structure in complex with the spike glycoprotein by cryo-EM. We show that the mAb engages a previously uncharacterized neutralizing epitope on the spike N-terminal domain (NTD). The high-resolution structure reveals details of the intermolecular interactions and shows that the mAb inserts its HCDR3 loop into a hydrophobic NTD cavity previously shown to bind a heme metabolite, biliverdin. We demonstrate direct competition with biliverdin and that - because of the conserved nature of the epitope - the mAb maintains binding to viral variants B.1.1.7 and B.1.351. Our study illustrates the feasibility of targeting the NTD to achieve broad neutralization against SARS-CoV-2 variants.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jose Arturo Molina-Mora", - "author_inst": "Centro de Investigacion en Enfermedades Tropicales (CIET) & Facultad de Microbiologia, Universidad de Costa Rica, San Jose, Costa Rica" + "author_name": "Clara Gilda Altomare", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Daniel Cole Adelsberg", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Juan Manuel Carreno", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Iden Avery Sapse", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Fatima Amanat", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Ali Ellebedy", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Viviana Simon", + "author_inst": "Icahn School of Medicine" + }, + { + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Goran Bajic", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "immunology" }, { "rel_doi": "10.1101/2021.07.08.451555", @@ -693071,123 +693634,119 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.07.06.451119", - "rel_title": "Nonclinical Safety and Immunogenicity of an rVSV-\u0394G-SARS-CoV-2-S vaccine in mice, hamsters, rabbits and pigs", + "rel_doi": "10.1101/2021.07.06.451301", + "rel_title": "A Newcastle disease virus-vector expressing a prefusion-stabilized spike protein of SARS-CoV-2 induces protective immune responses against prototype virus and variants of concern in mice and hamsters", "rel_date": "2021-07-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.06.451119", - "rel_abs": "rVSV-{Delta}G-SARS-CoV-2-S is a clinical stage (Phase 2) replication competent recombinant vaccine against SARS-CoV-2. Nonclinical safety, immunogenicity and efficacy studies were conducted in 4 animal species, using multiple dose levels (up to 108 PFU/animal) and various dosing regimens. There were no treatment related mortalities in any study, or any noticeable clinical signs. Compared to unvaccinated controls, hematology and biochemistry parameters were unremarkable and no adverse histopathological findings gave cause for safety concern in any of the studies. There was no viral shedding in urine, nor viral RNA detected in whole blood or serum samples 7 days post vaccination. The rVSV-{Delta}G-SARS-CoV-2-S vaccine immune response gave rise to neutralizing antibodies, cellular immune response, and increased lymphocytic cellularity in the spleen germinal centers and regional lymph node. No evidence for neurovirulence was found in C57BL/6 immune competent mice or in highly sensitive IFNAR KO mice. Vaccine virus replication and distribution in K18 hACE2 transgenic mice showed a gradual clearance from the vaccination site with no vaccine virus recovered from the lungs. The rVSV-{Delta}G-SARS-CoV-2-S vaccine was well tolerated locally and systemically and elicited an effective immunogenic response up to the highest dose tested, supporting further clinical development.", - "rel_num_authors": 26, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.06.451301", + "rel_abs": "Rapid development of coronavirus disease 2019 (COVID-19) vaccines and expedited authorization for use and approval has been proven beneficial to mitigate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spread and given hope in this desperate situation. It is believed that sufficient supplies and equitable allocations of vaccines are necessary to limit the global impact of the COVID-19 pandemic and the emergence of additional variants of concern. We have developed a COVID-19 vaccine based on Newcastle disease virus (NDV) that can be manufactured at high yields in embryonated eggs. Here we provide evidence that the NDV vector expressing an optimized spike antigen (NDV-HXP-S), upgraded from our previous construct, is a versatile vaccine that can be used live or inactivated to induce strong antibody responses and to also cross-neutralize variants of concern. The immunity conferred by NDV-HXP-S effectively counteracts SARS-CoV-2 infection in mice and hamsters. It is noteworthy that vaccine lots produced by existing egg-based influenza virus vaccine manufacturers in Vietnam, Thailand and Brazil exhibited excellent immunogenicity and efficacy in hamsters, demonstrating that NDV-HXP-S vaccines can be quickly produced at large-scale to meet global demands.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Noa Madar-Balakirski", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Amir Rosner", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Weina Sun", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Sharon Melamed", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Yonghong Liu", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Boaz Politi", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Fatima Amanat", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Michal Steiner", - "author_inst": "GSAP" + "author_name": "Irene Gonzalez-Dominguez", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Hadas Tamir", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Stephen McCroskery", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Yfat Yahalom Ronen", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Stefan Slamanig", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Elad Bar-David", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Lynda Coughlan", + "author_inst": "University of Maryland" }, { - "author_name": "Amir Ben-Shmuel", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Victoria Rosado", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Assa Sittner", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Nicholas Lemus", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Itai Glinert", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Sonia Jangra", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Shay Weiss", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Raveen Rathnasinghe", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Erez Bar-Haim", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Michael Schotsaert", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Hila Cohen", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Jose Martinez", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Uri Elia", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Kaori Sano", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Hagit Achdout", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Ignacio Mena", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Noam Erez", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Bruce L. Innis", + "author_inst": "PATH" }, { - "author_name": "Shahar Rotem", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Ponthip Wirachwong", + "author_inst": "The Government Pharmaceutical Organization" }, { - "author_name": "Shlomi Lazar", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Duong Huu Thai", + "author_inst": "Institute of Vaccines and Medical Biologicals" }, { - "author_name": "Abraham Nyska", - "author_inst": "Tel Aviv University" + "author_name": "Ricardo Das Neves Oliveira", + "author_inst": "Instituto Butantan" }, { - "author_name": "Shmuel Yitzhaki", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Rami Scharf", + "author_inst": "PATH" }, { - "author_name": "Adi Beth-Din", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Richard Hjorth", + "author_inst": "PATH" }, { - "author_name": "Haim Levy", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Rama Raghunandan", + "author_inst": "PATH" }, { - "author_name": "Nir Paran", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Tomer Israely", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Adolfo Garcia-Sastre", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Hadar Marcus", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Peter Palese", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "pharmacology and toxicology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.07.06.451340", @@ -694881,39 +695440,51 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.07.05.21259790", - "rel_title": "What We Learned From COVID 19? Trying to find best approach from pathophysiology to treatment.", + "rel_doi": "10.1101/2021.07.06.21260058", + "rel_title": "Examining Medical Student Volunteering During The COVID-19 Pandemic As A Prosocial Behavior During An Emergency", "rel_date": "2021-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.05.21259790", - "rel_abs": "ObjectiveCOVID-19 may yield a variety of clinical pictures, differing from pneumonitis to Acute Respiratory Distress Syndrome (ARDS) along with vascular damage in the lung tissue, named as endotheliitis. To date, no specific treatment strategy was approved by any authority for the prevention or treatment of COVID-19 in terms of endotheliitis-related comorbidities. Here, we present our experience of COVID-19 by evaluating 11,190 COVID-19 patients with the manifestations of endotheliitis in skin, lung, and brain tissues according to the different phases of COVID-19.\n\nMethodsAfter a retrospective examination, patients were divided into three groups according to their repercussions of vascular distress, which were represented by radiological, histopathological, and clinical findings. (Group A: no or mild pulmonary involvement, Group B: moderate pulmonary involvement with clinical risk of deterioration, Group C: severe pulmonary involvement and respiratory failure). We presented the characteristics and disease course of seven representative and complicated cases which represents the different phases of the disease, and discussed the treatment strategies in each group. The current pathophysiological mechanisms responsible from SARS-CoV-2 infection, COVID-19 related respiratory failure and current treatment strategies were reviewed and discussed in detail.\n\nResultsAmong 11.190 patients, 9294 patients met the criteria for Group A, and 1376 patients were presented to our clinics with Group B characteristics. Among these patients, 1896 individuals(Group B and Group C) were hospitalized. While 1220 inpatients were hospitalized within the first 10 days after the diagnosis, 676 of them were worsened and hospitalized 10 days after their diagnosis. Among hospitalized patients, 520 of them did not respond to group A and B treatments and developed hypoxemic respiratory failure (Group C) and 146 individuals needed ventilator support and were followed in the intensive care unit, and 43 (2.2%) patients died.\n\nConclusionDistinctive manifestations in each COVID-19 patient, including non-respiratory conditions in the acute phase and the emerging risk of long-lasting complications, suggest that COVID-19 has an endotheliitis-centred thrombo-inflammatory pathophysiology. Endotheliitis can also explain the mechanism behind the respiratory failure in COVID-19, and the difference of COVID-19 related ARDS from ARDS seen in other critical conditions. In addition, use of early corticosteroid in patients with early symptoms and early tocilizumab in ICU helps to reduce mortality and progression of the disease. Endotheliitis-based pathophysiological mechanisms are known to be momentarily changing and difficut to manage due to their risk of sudden aggrevation. Hence, daily evaluation of clinical, laboratory and radiological findings of patients and deciding appropriate pathophysiological treatment would help to reduce the mortality rate of COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.06.21260058", + "rel_abs": "IntroductionCOVID-19 has caused major disruptions to healthcare, with voluntary opportunities offered to medical students to provide clinical support. We used the conceptual framework of prosocial behavior during an emergency - behaviors whose primary focus is benefiting others - to examine volunteering during COVID-19.\n\nMethodsWe conducted an in-depth, mixed-methods cross-sectional survey, from 2nd May to 15th June 2020, of medical students studying at UK medical schools. Data analysis was informed by Latane and Darleys theory of prosocial behavior during an emergency and aimed to understand students decision-making processes.\n\nResultsA total of 1145 medical students from 36 medical schools completed the survey. While 947 (82.7%) of students were willing to volunteer, only 391 (34.3%) had volunteered. The majority (92.7%) of students understood that they may be asked to volunteer; however, we found that deciding ones responsibility to volunteer was mitigated by a complex interaction between the interests of others and self-interest. Further, concerns revolving around professional role boundaries influenced students decisions over whether they had the required skills and knowledge to volunteer. Deciding to volunteer depended not only on possession of necessary skills, but also seniority and identification with the nature of volunteering roles offered.\n\nConclusionsWe propose two additional domains to Latane and Darleys theory of prosocial behavior during an emergency that students consider before making their final decision to volunteer. These are logistics - whether it is logistically feasible to volunteer - and safety - whether it is safe to volunteer. This study highlights a number of modifiable barriers to prosocial behavior that medical students encounter and provides suggestions regarding how Latane and Darleys theory of prosocial behavior can be operationalized within educational strategies to address these barriers. Optimizing the process of volunteering can aid healthcare provision and may facilitate a safer volunteering process for all.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Adem Dirican", - "author_inst": "VM Samsun Medicalpark Hospital, Department of Pulmonary Medicine, Samsun, Turkey" + "author_name": "Matthew H V Byrne", + "author_inst": "Nuffield Department of Surgical Sciences, University of Oxford" }, { - "author_name": "Selin Ildir", - "author_inst": "Bahcesehir University School of Medicine" + "author_name": "James Ashcroft", + "author_inst": "University of Cambridge, Department of Surgery. Cambridge University Hospitals Trust, UK" }, { - "author_name": "Tugce Uzar", - "author_inst": "Bahcesehir University School of Medicine, Istanbul, Turkey" + "author_name": "Jonathan C M Wan", + "author_inst": "Guy's and St Thomas' Hospital London, UK" }, { - "author_name": "Irem Karaman", - "author_inst": "Bahcesehir University School of Medicine, Istanbul, Turkey" + "author_name": "Laith Alexander", + "author_inst": "Guy's and St Thomas' Hospital London, UK" }, { - "author_name": "Sevket OZKAYA", - "author_inst": "Bahcesehir University Faculty of Medicine, Department of Pulmonary Medicine, Istanbul, Turkey" + "author_name": "Anna Harvey", + "author_inst": "King's College London, UK" + }, + { + "author_name": "Nicholas Schindler", + "author_inst": "University of Cambridge, Institute of Continuing Education, UK" + }, + { + "author_name": "Megan E L Brown", + "author_inst": "Hull York Medical School, Health Professions Education Unit, UK" + }, + { + "author_name": "Cecilia Brassett", + "author_inst": "University of Cambridge, Department of Physiology, Development and Neuroscience, UK" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "medical education" }, { "rel_doi": "10.1101/2021.07.05.21260037", @@ -696703,107 +697274,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.07.06.451353", - "rel_title": "Receptor-binding domain recombinant protein RBD219-N1C1 on alum-CpG induces broad protection against SARS-CoV-2 variants of concern", + "rel_doi": "10.1101/2021.07.07.451411", + "rel_title": "CAT, AGTR2, L-SIGN and DC-SIGN are potential receptors for the entry of SARS-CoV-2 into human cells", "rel_date": "2021-07-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.06.451353", - "rel_abs": "We conducted preclinical studies in mice using a yeast-produced SARS-CoV-2 RBD subunit vaccine candidate formulated with aluminum hydroxide (alum) and CpG deoxynucleotides. This formulation is equivalent to the Corbevax vaccine that recently received emergency use authorization by the Drugs Controller General of India. We compared the immune response of mice vaccinated with RBD/alum to mice vaccinated with RBD/alum+CpG. We also evaluated mice immunized with RBD/alum+CpG and boosted with RBD/alum. Mice were immunized twice intramuscularly at a 21-day interval. Compared to two doses of the /alum formulation, the RBD/alum+CpG vaccine induced a stronger and more balanced Th1/Th2 cellular immune response, with high levels of neutralizing antibodies against the original Wuhan isolate of SARS-CoV-2 as well as the B.1.1.7 (Alpha), B. 1.351 (Beta), B. 1.617.2 and (Delta) variants. Neutralizing antibody titers against the B.1.1.529 (BA.1, Omicron) variant exceeded those in human convalescent plasma after Wuhan infection but were lower than against the other variants. Interestingly, the second dose did not benefit from the addition of CpG, possibly allowing dose-sparing of the adjuvant in the future. The data reported here reinforces that the RBD/alum+CpG vaccine formulation is suitable for inducing broadly neutralizing antibodies against SARS-CoV-2 including variants of concern.", - "rel_num_authors": 22, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.07.451411", + "rel_abs": "Since December 2019, the COVID-19 caused by SARS-CoV-2 has been widely spread all over the world. It is reported that SARS-CoV-2 infection affects a series of human tissues, including lung, gastrointestinal tract, kidney, etc. ACE2 has been identified as the primary receptor of the SARS-CoV-2 Spike (S) protein. The relatively low expression level of this known receptor in the lungs, which is the predominantly infected organ in COVID-19, indicates that there may be some other co-receptors or alternative receptors of SARS-CoV-2 to work in coordination with ACE2. Here, we identified twenty-one candidate receptors of SARS-CoV-2, including ACE2-interactor proteins and SARS-CoV receptors. Then we investigated the protein expression levels of these twenty-one candidate receptors in different human tissues and found that five of which CAT, MME, L-SIGN, DC-SIGN, and AGTR2 were specifically expressed in SARS-CoV-2 affected tissues. Next, we performed molecular simulations of the above five candidate receptors with SARS-CoV-2 S protein, and found that the binding affinities of CAT, AGTR2, L-SIGN and DC-SIGN to S protein were even higher than ACE2. Interestingly, we also observed that CAT and AGTR2 bound to S protein in different regions with ACE2 conformationally, suggesting that these two proteins are likely capable of the co-receptors of ACE2. Conclusively, we considered that CAT, AGTR2, L-SIGN and DC-SIGN were the potential receptors of SARS-CoV-2. Moreover, AGTR2 and DC-SIGN tend to be highly expressed in the lungs of smokers, which is consistent with clinical phenomena of COVID-19, and further confirmed our conclusion. Besides, we also predicted the binding hot spots for these putative protein-protein interactions, which would help develop drugs against SARS-CoV-2.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jeroen Pollet", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Ulrich Strych", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Wen-Hsiang Chen", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Leroy Versteeg", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Brian Keegan", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Bin Zhan", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Junfei Wei", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Zhuyun Liu", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Jungsoon Lee", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Rakhi Kundu", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Rakesh Adhikari", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Cristina Poveda", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Maria Jose Villar", - "author_inst": "Baylor College of Medicine" + "author_name": "Dongjie Guo", + "author_inst": "College of Life and Health Sciences, Northeastern University" }, { - "author_name": "Syamala Rani Thimmiraju", - "author_inst": "Baylor College of Medicine" + "author_name": "Ruifang Guo", + "author_inst": "College of Life and Health Sciences, Northeastern University" }, { - "author_name": "Brianna Lopez", - "author_inst": "Baylor College of Medicine" + "author_name": "Zhaoyang Li", + "author_inst": "College of Life and Health Sciences, Northeastern University" }, { - "author_name": "Portia M. Gillespie", - "author_inst": "Baylor College of Medicine" + "author_name": "Yuyang Zhang", + "author_inst": "College of Life and Health Sciences, Northeastern University" }, { - "author_name": "Shannon Ronca", - "author_inst": "Baylor College of Medicine" - }, - { - "author_name": "Jason T. Kimata", - "author_inst": "Baylor College of Medicine" + "author_name": "Wei Zheng", + "author_inst": "University of Michigan" }, { - "author_name": "Martin Reers", - "author_inst": "Biological E. Limited" + "author_name": "Xiaoqiang Huang", + "author_inst": "University of Michigan" }, { - "author_name": "Vikram Paradkar", - "author_inst": "Biological E. Limited" + "author_name": "Tursunjan Aziz", + "author_inst": "College of Life and Health Sciences, Northeastern University" }, { - "author_name": "Peter Hotez", - "author_inst": "Baylor College of Medicine" + "author_name": "Yang Zhang", + "author_inst": "University of Michigan" }, { - "author_name": "Maria Elena Bottazzi", - "author_inst": "Baylor College of Medicine" + "author_name": "Lijun Liu", + "author_inst": "Northeastern University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "molecular biology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.07.07.451375", @@ -698565,57 +699084,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.04.21259992", - "rel_title": "Late surges in COVID-19 cases and varying transmission potential partially due to public health policy changes in 5 Western states, March 10, 2020-January 10, 2021", + "rel_doi": "10.1101/2021.07.04.21259980", + "rel_title": "The impact of demographic factors on the accumulated number of COVID-19 cases per capita in Europe and the regions of Ukraine in the summer of 2021", "rel_date": "2021-07-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.04.21259992", - "rel_abs": "ObjectiveThis study investigates how the SARS-CoV-2 transmission potential varied in North Dakota, South Dakota, Montana, Wyoming, and Idaho from March 2020 through January 2021.\n\nMethodsTime-varying reproduction numbers, Rt, of a 7-day-sliding-window and of non-overlapping-windows between policy changes were estimated utilizing the instantaneous reproduction number method. Linear regression was performed to evaluate if per-capita cumulative case-count varied across counties with different population size.\n\nResultsThe median 7-day-sliding-window Rt estimates across the studied region varied between 1 and 1.25 during September through November 2020. Between November 13 and 18, Rt was reduced by 14.71% (95% credible interval, CrI, [14.41%, 14.99%]) in North Dakota following a mask mandate; Idaho saw a 1.93% (95% CrI [1.87%, 1.99%]) reduction and Montana saw a 9.63% (95% CrI [9.26%, 9.98%]) reduction following the tightening of restrictions. High-population counties had higher per-capita cumulative case-count in North Dakota at four time points (June 30, August 31, October 31, and December 31, 2020). In Idaho, North Dakota, and South Dakota, there was a positive correlation between population size and per-capita weekly incident case-count, adjusted for calendar time and social vulnerability index variables.\n\nConclusionsRt decreased after mask mandate during the regions case-count spike suggested reduction in SARS-CoV-2 transmission.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.07.04.21259980", + "rel_abs": "The accumulated number of COVID-19 cases per capita is an important characteristic of the pandemic dynamics that may also indicate the effectiveness of quarantine, testing and vaccination. As this value increases monotonically over time, the end of June 2021 was chosen, when the growth rate in Ukraine and the vast majority of European countries was small. This allowed us to draw some intermediate conclusions about the influence of the volume of population, its density, and the level of urbanization on the accumulated number of laboratory-confirmed cases per capita in European countries and regions of Ukraine. A simple analysis showed that the number of cases per capita does not depend on these demographic factors, although it may differ by about 4 times for different regions of Ukraine and more than 9 times for different European countries. The number of COVID-19 per capita registered in Ukraine is comparable with the same characteristic in other European countries but much higher than in China, South Korea and Japan.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Xinyi Hua", - "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" - }, - { - "author_name": "Aubrey R. D. Kehoe", - "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" - }, - { - "author_name": "Joana Tome", - "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" - }, - { - "author_name": "Mina Motaghi", - "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" - }, - { - "author_name": "Sylvia K. Ofori", - "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" - }, - { - "author_name": "Po-Ying Lai", - "author_inst": "Boston University School of Public Health" - }, - { - "author_name": "Sheikh Taslim Ali", - "author_inst": "The University of Hong Kong School of Public Health" - }, - { - "author_name": "Gerardo Chowell", - "author_inst": "Georgia State University School of Public Health" - }, - { - "author_name": "Anne C. Spaulding", - "author_inst": "Emory University Rollins School of Public Health" + "author_name": "Igor Nesteruk", + "author_inst": "Institute of Hydromechanics National Academy of sciences of Ukraine" }, { - "author_name": "Isaac Chun-Hai Fung", - "author_inst": "Georgia Southern University Jiann-Ping Hsu College of Public Health" + "author_name": "Oleksii Rodionov", + "author_inst": "Private consulting office, Kyiv, Ukraine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -700371,55 +700858,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.30.21259491", - "rel_title": "Reduced COVID-19 Hospitalizations among New York City Residents Following Age-Based SARS-CoV-2 Vaccine Eligibility: Evidence from a Regression Discontinuity Design", + "rel_doi": "10.1101/2021.06.30.21259787", + "rel_title": "Low dose mRNA-1273 COVID-19 vaccine generates durable T cell memory and antibodies enhanced by pre-existing crossreactive T cell memory", "rel_date": "2021-07-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.30.21259491", - "rel_abs": "BackgroundIn clinical trials, several SARS-CoV-2 vaccines were shown to reduce risk of severe COVID-19 illness. Local, population-level, real-world evidence of vaccine effectiveness is accumulating. We assessed vaccine effectiveness for community-dwelling New York City (NYC) residents using a quasi-experimental, regression discontinuity design, leveraging a period (January 12-March 9, 2021) when [≥]65-year-olds were vaccine-eligible but younger persons, excluding essential workers, were not.\n\nMethodsWe constructed segmented, negative binomial regression models of age-specific COVID-19 hospitalization rates among 45-84-year-old NYC residents during a post-vaccination program implementation period (February 21-April 17, 2021), with a discontinuity at age 65 years. The relationship between age and hospitalization rates in an unvaccinated population was incorporated using a pre-implementation period (December 20, 2020-February 13, 2021). We calculated the rate ratio (RR) and 95% confidence interval (CI) for the interaction between implementation period (pre or post) and age-based eligibility (45-64 or 65-84 years). Analyses were stratified by race/ethnicity and borough of residence. Similar analyses were conducted for COVID-19 deaths.\n\nResultsHospitalization rates among 65-84-year-olds decreased from pre- to post-implementation periods (RR 0.85, 95% CI: 0.74-0.97), controlling for trends among 45-64-year-olds. Accordingly, an estimated 721 (95% CI: 126-1,241) hospitalizations were averted. Residents just above the eligibility threshold (65-66-year-olds) had lower hospitalization rates than those below (63-64-year-olds). Racial/ethnic groups and boroughs with higher vaccine coverage generally experienced greater reductions in RR point estimates. Uncertainty was greater for the decrease in COVID-19 death rates (RR 0.85, 95% CI: 0.66-1.10).\n\nConclusionThe vaccination program in NYC reduced COVID-19 hospitalizations among the initially age-eligible [≥]65-year-old population by approximately 15%. The real-world evidence of vaccine effectiveness makes it more imperative to improve vaccine access and uptake to reduce inequities in COVID-19 outcomes.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.30.21259787", + "rel_abs": "Understanding human immune responses to SARS-CoV-2 RNA vaccines is of interest for a panoply of reasons. Here we examined vaccine-specific CD4+ T cell, CD8+ T cell, binding antibody, and neutralizing antibody responses to the 25 g Moderna mRNA-1273 vaccine over 7 months post-immunization, including multiple age groups, with a particular interest in assessing whether pre-existing crossreactive T cell memory impacts vaccine-generated immunity. Low dose (25 g) mRNA-1273 elicited durable Spike binding antibodies comparable to that of convalescent COVID-19 cases. Vaccine-generated Spike memory CD4+ T cells 6 months post-boost were comparable in quantity and quality to COVID-19 cases, including the presence of TFH cells and IFN{gamma}-expressing cells. Spike CD8+ T cells were generated in 88% of subjects, with equivalent percentages of CD8+ T cell memory responders at 6 months post-boost compared to COVID-19 cases. Lastly, subjects with pre-existing crossreactive CD4+ T cell memory had increased CD4+ T cell and antibody responses to the vaccine, demonstrating a biological relevance of SARS-CoV-2 crossreactive CD4+ T cells.\n\nOne-Sentence SummaryThe mRNA-1273 vaccine induces a durable and functional T cell and antibody response comparable to natural infection.", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sharon K. Greene", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Jose Mateus", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Alison Levin-Rector", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Jennifer M Dan", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Emily McGibbon", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Zeli Zhang", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Jennifer Baumgartner", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Carolyn Rydyznski Moderbacher", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Katelynn Devinney", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Marshall Lammers", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Alexandra Ternier", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Benjamin Goodwin", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Jessica Sell", - "author_inst": "New York City Department of Health and Mental Hygiene" + "author_name": "Alessandro Sette", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Rebecca Kahn", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Shane Crotty", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Nishant Kishore", - "author_inst": "Harvard T.H. Chan School of Public Health" + "author_name": "Daniela Weiskopf", + "author_inst": "La Jolla Institute for Immunology" } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.30.21259796", @@ -702005,43 +702492,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.07.02.450964", - "rel_title": "SARS-CoV-2 Nsp14 mediates the effects of viral infection on the host cell transcriptome", + "rel_doi": "10.1101/2021.07.03.450989", + "rel_title": "Allotypic variation in antigen processing controls antigenic peptide generation from SARS-CoV-2 S1 Spike Glycoprotein", "rel_date": "2021-07-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.02.450964", - "rel_abs": "Viral infection involves complex set of events orchestrated by multiple viral proteins. To identify functions of SARS-CoV-2 proteins, we performed transcriptomic analyses of cells expressing individual viral proteins. Expression of Nsp14, a protein involved in viral RNA replication, provoked a dramatic remodeling of the transcriptome that strongly resembled that observed following SARS-CoV-2 infection. Moreover, Nsp14 expression altered the splicing of more than 1,000 genes and resulted in a dramatic increase in the number of circRNAs, which are linked to innate immunity. These effects were independent of the Nsp14 exonuclease activity and required the N7-guanine-methyltransferase domain of the protein. Activation of the NFkB pathway and increased expression of CXCL8 occurred early upon Nsp14 expression. We identified IMPDH2, which catalyzes the rate-limiting step of guanine nucleotides biosynthesis, as a key mediator of these effects. Nsp14 expression caused an increase in GTP cellular levels, and the effect of Nsp14 was strongly decreased in presence of IMPDH2 inhibitors. Together, our data demonstrate an unknown role for Nsp14 with implications for therapy.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.03.450989", + "rel_abs": "Population genetic variability in immune system genes can often underlie variability in immune responses to pathogens. Cytotoxic T-lymphocytes are emerging as critical determinants of both SARS-CoV-2 infection severity and long-term immunity, either after recovery or vaccination. A hallmark of COVID-19 is its highly variable severity and breadth of immune responses between individuals. To address the underlying mechanisms behind this phenomenon we analyzed the proteolytic processing of S1 spike glycoprotein precursor antigenic peptides by 10 common allotypes of ER aminopeptidase 1 (ERAP1), a polymorphic intracellular enzyme that can regulate cytotoxic T-lymphocyte responses by generating or destroying antigenic peptides. We utilized a systematic proteomic approach that allows the concurrent analysis of hundreds of trimming reactions in parallel, thus better emulating antigen processing in the cell. While all ERAP1 allotypes were capable of producing optimal ligands for MHC class I molecules, including known SARS-CoV-2 epitopes, they presented significant differences in peptide sequences produced, suggesting allotype-dependent sequence biases. Allotype 10, previously suggested to be enzymatically deficient, was rather found to be functionally distinct from other allotypes. Our findings suggest that common ERAP1 allotypes can be a major source of heterogeneity in antigen processing and through this mechanism contribute to variable immune responses to COVID-19.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Michela Zaffagni", - "author_inst": "Brandeis University" - }, - { - "author_name": "Jenna M Harris", - "author_inst": "Brandeis University" + "author_name": "George Stamatakis", + "author_inst": "Biomedical Sciences Research Center Alexander Fleming" }, { - "author_name": "Ines L Patop", - "author_inst": "Brandeis University" + "author_name": "Martina Samiotaki", + "author_inst": "Biomedical Sciences Research Center Alexander Fleming" }, { - "author_name": "Nagarjuna Reddy Pamudurti", - "author_inst": "Brandeis University" + "author_name": "Ioannis Temponeras", + "author_inst": "National Centre for Scientific Research Demokritos" }, { - "author_name": "Sinead Nguyen", - "author_inst": "Brandeis University" + "author_name": "George Panayotou", + "author_inst": "Biomedical Sciences Research Center Alexander Fleming" }, { - "author_name": "Sebastian Kadener", - "author_inst": "Brandeis University" + "author_name": "Efstratios Stratikos", + "author_inst": "National and Kapodistrian University of Athens" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "molecular biology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.07.03.451001", @@ -703899,87 +704382,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.23.21259414", - "rel_title": "The COVID-related mental health load of neonatal healthcare professionals: a multicentre study in Italy.", + "rel_doi": "10.1101/2021.06.28.21259570", + "rel_title": "Coping under stress: Prefrontal control predicts stress burden during the COVID-19 crisis", "rel_date": "2021-07-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.23.21259414", - "rel_abs": "BackgroundThe COVID-19 pandemic has dramatically affected healthcare professionals lives. We investigated the potential mental health risk faced by healthcare professionals working in neonatal units in a multicentre cross-sectional observational study.\n\nMethodsWe included all healthcare personnel of 7 level-3 and 6 level-2 neonatal units in Tuscany, Italy. We measured the level of physical exposure to COVID-19 risk, self-reported COVID-related stress, and mental health load outcomes (anxiety, depression, burnout, psychosomatic, and post-traumatic symptoms) via validated, self-administered, on-line questionnaires.\n\nResultsWe analysed 314 complete answers. Scores above the clinical cutoff were reported by 91% of participants for anxious symptoms, 29% for post-traumatic symptoms, 13% for burnout, and 3% for depressive symptoms. Moreover, 50% of the participants reported at least one psychosomatic symptom. COVID-related stress (but not actual physical exposure) was significantly associated with all the measured mental health load outcomes, with a Risk Ratio of 3.33 (95% Confidence interval: 1.89, 5.85) for clinically relevant anxiety, 2.39 (1.69, 3.38) for post-traumatic symptoms, 1.79 (1.16, 2.75) for emotional exhaustion, and 2.51 (0.98, 6.44) for depression.\n\nConclusionsDespite a low clinical impact of COVID-19 in neonatology, neonatal professionals are a specific population at risk for psychological consequences during the pandemic.\n\nKeynotesO_LIWe studied the mental health load (anxiety, post-traumatic, psychosomatic symptoms, burnout, depression) of healthcare professionals working in 13 neonatal units in Tuscany during the COVID-19 pandemic.\nC_LIO_LIWe found very high levels of anxiety and psychosomatic symptoms, and moderate-high post-traumatic and burnout symptoms.\nC_LIO_LIMental health load was higher in neonatal intensive (vs non-intensive) settings and in nurses (vs physicians). Mental health load outcomes were associated with COVID-related stress (rather than actual physical exposure to the virus).\nC_LI", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.28.21259570", + "rel_abs": "BackgroundThe coronavirus (COVID-19) pandemic has confronted millions of people around the world with an unprecedented stressor, affecting physical and mental health. Accumulating evidence suggests that emotional and cognitive self-regulation is particularly needed to effectively cope with stress. Therefore, we investigated the predictive value of affective and inhibitory prefrontal control for stress burden during the COVID-19 crisis.\n\nMethodPhysical and mental health burden were assessed using an online survey, which was administered to 104 participants of an ongoing German at-risk birth cohort during the first wave in April 2020. Two follow-ups were carried out during the pandemic, one capturing the relaxation during summer and the other the beginning of the second wave of the crisis. Prefrontal activity during emotion regulation and inhibitory control were assessed prior to the COVID-19 crisis.\n\nResultsIncreased inferior frontal gyrus activity during emotion regulation predicted lower stress burden at the beginning of the first and the second wave of the crisis. In contrast, inferior and medial frontal gyrus activity during inhibitory control predicted effective coping only during the summer, when infection rates decreased but stress burden remained unchanged. These findings remained significant when controlling for sociodemographic and clinical confounders such as stressful life events prior to the crisis or current psychopathology.\n\nConclusionsWe demonstrate that differential stress-buffering effects are predicted by the neural underpinnings of emotion regulation and cognitive regulation at different stages during the pandemic. These findings may inform future prevention strategies to foster stress coping in unforeseen situations.\n\nHighlightsO_LIHealth threatening stressors, such as the COVID-19 pandemic, significantly worsen well-being.\nC_LIO_LIResults reveal high levels of stress during the course of the pandemic with an increase of stress burden towards the second wave.\nC_LIO_LISelf-regulation is an important coping strategy to restore allostasis.\nC_LIO_LIHigher prefrontal activity during emotion regulation predicted less stress during the peaks of infection rates in the first and second wave\nC_LIO_LIHigher prefrontal inhibitory control predicted less stress burden between both waves when infection rates were low.\nC_LIO_LIOur findings highlight the importance of prefrontal regulation as effective coping mechanisms in the face of unprecedented stressors.\nC_LI", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Luigi Gagliardi", - "author_inst": "AUSL Toscana Nord Ovest" - }, - { - "author_name": "Serena Grumi", - "author_inst": "IRCCS Fondazione Mondino, Pavia, Italy" + "author_name": "Maximilian Monninger", + "author_inst": "Central Institute of Mental Health" }, { - "author_name": "Marzia Gentile", - "author_inst": "Division of Neonatology, Azienza Ospedaliero-Universitaria di Pisa, Italy" + "author_name": "Tania Maria Pollok", + "author_inst": "Central Institute of Mental Health" }, { - "author_name": "Roberta Cacciavellani", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale Versilia, Viareggio, AUSL Toscana Nord Ovest, Pisa, Italy" + "author_name": "Pascal M Aggensteiner", + "author_inst": "Central Institute of Mental Health" }, { - "author_name": "Giulia Placidi", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale Versilia, Viareggio, AUSL Toscana Nord Ovest, Pisa, Italy" + "author_name": "Anna Kaiser", + "author_inst": "Central Institute of Mental Health" }, { - "author_name": "Angelina Vaccaro", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale San Luca, Lucca, AUSL Toscana NordOvest, Pisa Italy" + "author_name": "Iris Reinhard", + "author_inst": "Central Institute of Mental Health" }, { - "author_name": "Claudia Maggi", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale Lotti, Pontedera, AUSL Toscana NordOvest, Pisa Italy" + "author_name": "Andrea Hermann", + "author_inst": "Justus Liebig University, Giessen" }, { - "author_name": "Beatrice Gambi", - "author_inst": "Division of Neonatology, Ospedale San Giovanni di Dio, AUSL Toscana Centro, Firenze, Italy" - }, - { - "author_name": "Letizia Magi", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale San Donato, Arezzo, AUSL Toscana Sud Est, Arezzo, Italy" - }, - { - "author_name": "Laura Crespin", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale di Barga, AUSL Toscana Nord Ovest, Pisa Italy" - }, - { - "author_name": "Graziano Memmini", - "author_inst": "Division of Neonatology and Pediatrics, Nuovo Ospedale Apuano, Massa, AUSL Toscana NordOvest, Pisa Italy" - }, - { - "author_name": "Marcello De Filippo", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale di Grosseto, AUSL Toscana Sud Est, Italy" - }, - { - "author_name": "Elena Verucci", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale di Livorno, AUSL Toscana Nord Ovest, Pisa, Italy" - }, - { - "author_name": "Liliana Malandra", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale di Cecina, AUSL Toscana Nord Ovest, Pisa Italy" + "author_name": "Andreas Meyer-Lindenberg", + "author_inst": "Central Institute of Mental Health" }, { - "author_name": "Laura Mele", - "author_inst": "Division of Neonatology and Pediatrics, Ospedale di Prato, AUSL Toscana Centro, Firenze, Italy" + "author_name": "Daniel Brandeis", + "author_inst": "Central Institute of Mental Health" }, { - "author_name": "Angelo Azzar\u00e0", - "author_inst": "Division of Neonatology, Azienda Ospedaliero-Universitaria Meyer, Firenze, Italy" + "author_name": "Tobias Banaschewski", + "author_inst": "Central Institute of Mental Health" }, { - "author_name": "Livio Provenzi", - "author_inst": "IRCCS Fondazione Mondino, Pavia, Italy" + "author_name": "Nathalie Elisabeth Holz", + "author_inst": "Central Institute of Mental Health" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2021.06.27.21259271", @@ -705917,90 +706372,34 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2021.07.02.450896", - "rel_title": "Implications of Spike-glycoprotein processing at S1/S2 by Furin, at S2' by Furin and/or TMPRSS2 and shedding of ACE2: cell-to-cell fusion, cell entry and infectivity of SARS-CoV-2", + "rel_doi": "10.1101/2021.07.01.450756", + "rel_title": "Flavonols and dihydroflavonols inhibit the main protease activity of SARS-CoV-2 and the replication of human coronavirus 229E", "rel_date": "2021-07-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.02.450896", - "rel_abs": "Disclaimer StatementThe author has withdrawn this manuscript due to a duplicate posting of manuscript number 423106. Therefore, the author does not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author (Nabil G. Seidah at seidahn@ircm.qc.ca.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.07.01.450756", + "rel_abs": "Since December 2019, the deadly novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the current COVID-19 pandemic. To date, vaccines are available in the developed countries to prevent the infection of this virus, however, medicines are necessary to help control COVID-19. Human coronavirus 229E (HCoV-229E) causes the common cold. The main protease (Mpro) is an essential enzyme required for the multiplication of these two viruses in the host cells, and thus is an appropriate candidate to screen potential medicinal compounds. Flavonols and dihydroflavonols are two groups of plant flavonoids. In this study, we report docking simulation with two Mpro enzymes and five flavonols and three dihydroflavonols, in vitro inhibition of the SARS-CoV-2 Mpro, and in vitro inhibition of the HCoV 229E replication. The docking simulation results predicted that (+)-dihydrokaempferol, (+)-dihydroquercetin, (+)-dihydromyricetin, kaempferol, quercetin, myricentin, isoquercetin, and rutin could bind to at least two subsites (S1, S1, S2, and S4) in the binding pocket and inhibit the activity of SARS-CoV-2 Mpro. Their affinity scores ranged from -8.8 to -7.4. Likewise, these compounds were predicted to bind and inhibit the HCoV-229E Mpro activity with affinity scores ranging from -7.1 to -7.8. In vitro inhibition assays showed that seven available compounds effectively inhibited the SARS-CoV-2 Mpro activity and their IC50 values ranged from 0.125 to 12.9 {micro}M. Five compounds inhibited the replication of HCoV-229E in Huh-7 cells. These findings indicate that these antioxidative flavonols and dihydroflavonols are promising candidates for curbing the two viruses.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Rachid Essalmani", - "author_inst": "Montreal Clinical Research Institute" - }, - { - "author_name": "Jaspreet Jain", - "author_inst": "Montreal Clinical Research Institute" - }, - { - "author_name": "Delia Susan-Resiga", - "author_inst": "Montreal Clinical Research Institute" - }, - { - "author_name": "Ursula Andreo", - "author_inst": "Montreal Clinical Research Institute" - }, - { - "author_name": "Alexandra Evagelidis", - "author_inst": "Montreal Clinical Research Institute" - }, - { - "author_name": "Mouna Derbali", - "author_inst": "Montreal Clinical Research Institute" - }, - { - "author_name": "David Huynh", - "author_inst": "Montreal Clinical Research Institute" - }, - { - "author_name": "Frederic Dallaire", - "author_inst": "Montreal Clinical Research Institute" - }, - { - "author_name": "Melanie Laporte", - "author_inst": "Montreal Clinical Research Institute" - }, - { - "author_name": "Adrien Delpal", - "author_inst": "Universite de Marseille" - }, - { - "author_name": "Priscila Sutto-Ortiz", - "author_inst": "Universite de Marseille" - }, - { - "author_name": "Bruno Coutard", - "author_inst": "Aix Marseille Universite" - }, - { - "author_name": "Claudine Mapa", - "author_inst": "Boston Pharmaceuticals" - }, - { - "author_name": "Keith Wilcoxen", - "author_inst": "Boston Pharmaceuticals" - }, - { - "author_name": "Etienne Decroly", - "author_inst": "Universite de Marseille" + "author_name": "Yue Zhu", + "author_inst": "North Carolina State University" }, { - "author_name": "Tram NQ Pham", - "author_inst": "Montreal Clinical Research Institute" + "author_name": "Frank Scholle", + "author_inst": "North Carolina State University" }, { - "author_name": "Eric A. Cohen", - "author_inst": "Montreal Clinical Research Institute" + "author_name": "Samantha C. Kisthardt", + "author_inst": "North Carolina State University" }, { - "author_name": "Nabil G Seidah", - "author_inst": "Montreal Clinical Research Institute" + "author_name": "Deyu Xie", + "author_inst": "North Carolina State University" } ], "version": "1", - "license": "cc_no", - "type": "new results", + "license": "cc_by_nc_nd", + "type": "confirmatory results", "category": "biochemistry" }, { @@ -708323,53 +708722,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.21.21258023", - "rel_title": "ASSESSMENT OF POTENTIAL SARS-CoV-2 VIRUS N GENE INTEGRATION INTO HUMAN GENOME REVEALS NO SIGNIFICANT IMPACT ON RT-qPCR COVID-19 DIAGNOSTIC TESTING", + "rel_doi": "10.1101/2021.06.25.21259565", + "rel_title": "Comparative evaluation of the transmissibility of SARS-CoV-2 variants of concern", "rel_date": "2021-06-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.21.21258023", - "rel_abs": "The SARS Coronavirus 2 (SARS-CoV-2) pandemic presents new scientific and scale-up challenges for diagnostic capabilities worldwide. The gold standard diagnostic for SARS-CoV-2 infection is a reverse transcription/quantitative PCR (RT-qPCR) which targets the viral genome, an assay that has now been performed on millions of patient specimens worldwide regardless of symptomatic status. Recently Zhang et al. suggested the possibility that the SARS-CoV-2 N gene could integrate into host cell DNA through the action of the LINE-1 retrotransposon, a mobile element that is potentially active in human somatic cells, thereby calling into question the veracity of N-gene based RT-qPCR for detection of SARS-CoV-2 infection. Accordingly, we assessed the potential impact of these purported integration events on nasal swab specimens tested at our clinical laboratory. Using an N-gene based RT-qPCR assay, we tested 768 arbitrarily selected specimens and identified 2 samples which resulted in a positive detection of viral sequence in the absence of reverse transcriptase, a necessary but not sufficient signal consistent with possible integration of the SARS-CoV-2 N gene into the host genome. Regardless of possible viral N gene integration into the genome, in this small subset of samples, all patients were still positive for SARS-CoV-2 infection, as indicated by a much lower Ct value for reactions performed in the presence of reverse transcriptase (RT) versus reactions performed without RT. Moreover, one of the two positives observed in the absence of RT also tested positive when using primers targeting ORF1ab, a gene closer to the 5 end of the genome. These data are inconsistent with the N gene integration hypothesis suggested by the studies by Zhang et al., and importantly, our results suggest little to no practical impact of possible SARS-CoV-2 genome integration events on RT-qPCR testing.\n\nCOMPETING INTEREST STATEMENTThe authors of this study are employees of the Pandemic Response Lab (PRL)/ReOpen Diagnostics, a private company performing SARS-CoV-2 RT-qPCR based testing, an area of interest of this study.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.25.21259565", + "rel_abs": "Since the start of the SARS-CoV-2 pandemic in late 2019, several variants of concern (VOC) have been reported, such as B.1.1.7, B.1.351, P.1, and B.1.617.2. The exact reproduction number Rt for these VOCs is important to determine appropriate control measures. Here, we estimated the transmissibility for VOCs and lineages of SAR-CoV-2 based on genomic data and Bayesian inference under an epidemiological model to infer the reproduction number (Rt). We analyzed data for multiple VOCs from the same time period and countries, in order to compare their transmissibility while controlling for geographical and temporal factors. The lineage B had a significantly higher transmissibility than lineage A, and contributed to the global pandemic to a large extent. In addition, all VOCs had increased transmissibility when compared with other lineages in each country, indicating they are harder to control and present a high risk to public health. All countries should formulate specific prevention and control policies for these VOCs when they are detected to curve their potential for large-scale spread.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Erica Briggs", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA" - }, - { - "author_name": "William Ward", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA" - }, - { - "author_name": "Sol Rey", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA" - }, - { - "author_name": "Dylan Law", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA" - }, - { - "author_name": "Katherine Nelson", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA" - }, - { - "author_name": "Michael Bois", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA" - }, - { - "author_name": "Nili Ostrov", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA; Department of Genetics, Harvard Medi" + "author_name": "Liang Wang", + "author_inst": "Institute of Microbiology, Chinese Academy of Science" }, { - "author_name": "Henry H. Lee", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA; Department of Genetics, Harvard Medi" + "author_name": "Xavier Didelot", + "author_inst": "University of Warwick" }, { - "author_name": "Jon M. Laurent", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA" + "author_name": "Yuhai Bi", + "author_inst": "Institute of Microbiology, Chinese Academy of Sciences" }, { - "author_name": "Paolo Mita", - "author_inst": "Pandemic Response Lab (PRL) Research and Development Department, 30-02 48th Avenue, Long Island City, New York, 11101, USA" + "author_name": "George Fu Gao", + "author_inst": "Institute of Microbiology Chinese Academy of Sciences" } ], "version": "1", @@ -710077,123 +710452,91 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.06.28.450244", - "rel_title": "Systematic genome-scale identification of host factors for SARS-CoV-2 infection across models yields a core single gene dependency; ACE2", + "rel_doi": "10.1101/2021.06.29.450293", + "rel_title": "Rapid determination of the wide dynamic range of SARS-CoV-2 Spike T cell responses in whole blood of vaccinated and naturally infected", "rel_date": "2021-06-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.28.450244", - "rel_abs": "SARS-CoV-2, depends on host cell components for replication, therefore the identification of virus-host dependencies offers an effective way to elucidate mechanisms involved in viral infection. Such host factors may be necessary for infection and replication of SARS-CoV-2 and, if druggable, presents an attractive strategy for anti-viral therapy. We performed genome wide CRISPR knockout screens in Vero E6 cells and 4 human cell lines including Calu-3, Caco-2, Hek293 and Huh7 to identify genetic regulators of SARS-CoV-2 infection. Our findings identified only ACE2, the cognate SARS-CoV-2 entry receptor, as a common host dependency factor across all cell lines, while all other host genes identified were cell line specific including known factors TMPRSS2 and CTSL. Several of the discovered host-dependency factors converged on pathways involved in cell signalling, lipid metabolism, immune pathways and chromatin modulation. Notably, chromatin modulator genes KMT2C and KDM6A in Calu-3 cells had the strongest impact in preventing SARS-CoV-2 infection when perturbed. Overall, the network of host factors that have been identified will be broadly applicable to understanding the impact of SARS-CoV-2 on human cells and facilitate the development of host-directed therapies.\n\nIN BRIEFSARS-CoV-2, depends on host cell components for infection and replication. Genome-wide CRISPR screens were performed in multiple human cell lines to elucidate common host dependencies required for SARS-CoV-2 infection. Only ACE2, the cognate SARS-CoV-2 entry receptor, was common amongst cell lines, while all other host genes identified were cell line specific, several of which converged on pathways involved in cell signalling, lipid metabolism, immune pathways, and chromatin modulation. Overall, a network of host factors was identified that will be broadly applicable to understanding the impact of SARS-CoV-2 on human cells and facilitate productive targeting of host genes and pathways.\n\nHIGHLIGHTS- Genome-wide CRISPR screens for SARS-CoV-2 in multiple human cell lines\n- Identification of wide-ranging cell-type dependent genetic dependencies for SARS-CoV-2 infection\n- ACE2 is the only common host factor identified across different cell types", - "rel_num_authors": 26, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.29.450293", + "rel_abs": "BackgroundAntibodies and T cells cooperate to control virus infections. The definition of the correlates of protection necessary to manage the COVID-19 pandemic, require both immune parameters but the complexity of traditional tests limits virus-specific T cell measurements.\n\nMethodsWe test the sensitivity and performance of a simple and rapid SARS-CoV-2 Spike-specific T cell test based on stimulation of whole blood with peptides covering the SARS-CoV-2 Spike protein followed by cytokine (IFN-{gamma}, IL-2) measurement in different cohorts including BNT162b2 vaccinated (n=112; 201 samples), convalescent asymptomatic (n=62; 62 samples) and symptomatic (n=68; 115 samples) COVID-19 patients and SARS-CoV-1 convalescent individuals (n=12; 12 samples).\n\nResultsThe sensitivity of the rapid cytokine whole blood test equates traditional methods of T cell analysis (ELISPOT, Activation Induced Markers). Utilizing this test we observed that Spike-specific T cells in vaccinated preferentially target the S2 region of Spike and that their mean magnitude is similar between them and SARS-CoV-2 convalescents at 3 months after vaccine or virus priming respectively. However, a wide heterogeneity of Spike-specific T cell magnitude characterizes the individual responses irrespective of the time of analysis. No correlation between neutralizing antibody levels and Spike-specific T cell magnitude were found.\n\nConclusionsRapid measurement of cytokine production in whole blood after peptide activation revealed a wide dynamic range of Spike-specific T cell response after vaccination that cannot be predicted from neutralizing antibody quantities. Both Spike-specific humoral and cellular immunity should be tested after vaccination to define the correlates of protection necessary to evaluate current vaccine strategies.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Katherine Chan", - "author_inst": "University of Toronto" - }, - { - "author_name": "Adrian Granda Farias", - "author_inst": "University of Toronto" - }, - { - "author_name": "Hunsang Lee", - "author_inst": "University of Toronto" - }, - { - "author_name": "Furkan Guvenc", - "author_inst": "University of Toronto" - }, - { - "author_name": "Patricia Mero", - "author_inst": "University of Toronto" - }, - { - "author_name": "Kamaldeep Aulakh", - "author_inst": "University of Toronto" - }, - { - "author_name": "Kevin R Brown", - "author_inst": "University of Toronto" - }, - { - "author_name": "Shahan Haider", - "author_inst": "University of Toronto" - }, - { - "author_name": "Edyta Marcon", - "author_inst": "University of Toronto" + "author_name": "Anthony T Tan", + "author_inst": "DUKE-NUS Medical School" }, { - "author_name": "Ulrich Braunschweig", - "author_inst": "University of Toronto" + "author_name": "Joey ME Lim", + "author_inst": "DUKE-NUS Medical School" }, { - "author_name": "Amy Hin Yan Tong", - "author_inst": "University of Toronto" + "author_name": "Nina Le Bert", + "author_inst": "DUKE-NUS Medical School" }, { - "author_name": "Shuye Pu", - "author_inst": "University of Toronto" + "author_name": "Kamini Kunasegaran", + "author_inst": "DUKE-NUS Medical School" }, { - "author_name": "Andrea Habsid", - "author_inst": "University of Toronto" + "author_name": "Adeline Chia", + "author_inst": "DUKE-NUS Medical School" }, { - "author_name": "Natasha Christie-Holmes", - "author_inst": "University of Toronto" + "author_name": "Martin Qui", + "author_inst": "DUKE-NUS Medical School" }, { - "author_name": "Patrick Budylowski", - "author_inst": "University of Toronto" + "author_name": "Nicole Tan", + "author_inst": "DUKE-NUS Medical School" }, { - "author_name": "Audrey Astori", - "author_inst": "Princess Margaret Cancer Centre" + "author_name": "Wan Ni Chia", + "author_inst": "DUKE-NUS Medical School" }, { - "author_name": "Ayoob Ghalami", - "author_inst": "University of Toronto" + "author_name": "Ruklanthi Alwis", + "author_inst": "Viral Research and Experimental Medicine Centre @ Singhealth Duke-NUS" }, { - "author_name": "Samira Mubareka", - "author_inst": "Sunnybrook Research Institute" + "author_name": "Ying Ding", + "author_inst": "National Centre for Infectious Diseases" }, { - "author_name": "Arinjay Banerjee", - "author_inst": "University of Saskatchewan" + "author_name": "Eng Eong Ooi", + "author_inst": "DUKE-NUS Medical School" }, { - "author_name": "Karen L Mossman", - "author_inst": "McMaster University" + "author_name": "Lin-Fa Wang", + "author_inst": "Duke-NUS Medical School" }, { - "author_name": "Jack Greenblatt", - "author_inst": "University of Toronto" + "author_name": "Mark IC Chen", + "author_inst": "National Centre for Infectious Diseases" }, { - "author_name": "Scott D Gray-Owen", - "author_inst": "University of Toronto" + "author_name": "Barnaby Young", + "author_inst": "National Centre for Infectious Diseases" }, { - "author_name": "Brian Raught", - "author_inst": "Princess Margaret Cancer Centre" + "author_name": "Li Yang Hsu", + "author_inst": "National University of Singapore and National University Health System" }, { - "author_name": "Benjamin Blencowe", - "author_inst": "University of Toronto" + "author_name": "Jenny Low", + "author_inst": "Singapore General Hospital" }, { - "author_name": "Mikko Taiplale", - "author_inst": "University of Toronto" + "author_name": "David Lye", + "author_inst": "National Centre for Infectious Diseases" }, { - "author_name": "Jason Moffat", - "author_inst": "University of Toronto" + "author_name": "Antonio Bertoletti", + "author_inst": "DUKE-NUS Medical School" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "systems biology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.06.29.450397", @@ -712615,35 +712958,47 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.06.25.449831", - "rel_title": "Solar simulated ultraviolet radiation inactivates HCoV-NL63 and SARS-CoV-2 coronaviruses at environmentally relevant doses", + "rel_doi": "10.1101/2021.06.28.450163", + "rel_title": "N4-hydroxycytidine and inhibitors of dihydroorotate dehydrogenase synergistically suppress SARS-CoV-2 replication", "rel_date": "2021-06-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.25.449831", - "rel_abs": "The germicidal properties of short wavelength ultraviolet C (UVC) light are well established and used to inactivate many viruses and other microbes. However, much less is known about germicidal effects of terrestrial solar UV light, confined exclusively to wavelengths in the UVA and UVB regions. Here, we have explored the sensitivity of the human coronaviruses HCoV-NL63 and SARS-CoV-2 to solar-simulated full spectrum ultraviolet light (sUV) delivered at environmentally relevant doses. First, HCoV-NL63 coronavirus inactivation by sUV-exposure was confirmed employing (i) viral plaque assays, (ii) RT-qPCR detection of viral genome replication, and (iii) infection-induced stress response gene expression array analysis. Next, a detailed dose-response relationship of SARS-CoV-2 coronavirus inactivation by sUV was elucidated, suggesting a half maximal suppression of viral infectivity at low sUV doses. Likewise, extended sUV exposure of SARS-CoV-2 blocked cellular infection as revealed by plaque assay and stress response gene expression array analysis. Moreover, comparative (HCoV-NL63 versus SARS-CoV-2) single gene expression analysis by RT-qPCR confirmed that sUV exposure blocks coronavirus-induced redox, inflammatory, and proteotoxic stress responses. Based on our findings, we estimate that solar ground level full spectrum UV light impairs coronavirus infectivity at environmentally relevant doses. Given the urgency and global scale of the unfolding SARS-CoV-2 pandemic, these prototype data suggest feasibility of solar UV-induced viral inactivation, an observation deserving further molecular exploration in more relevant exposure models.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.28.450163", + "rel_abs": "Effective therapeutics to inhibit the replication of SARS-CoV-2 in infected individuals are still under development. The nucleoside analogue N4-hydroxycytidine (NHC), also known as EIDD-1931, interferes with SARS-CoV-2 replication in cell culture. It is the active metabolite of the prodrug Molnupiravir (MK-4482), which is currently being evaluated for the treatment of COVID-19 in advanced clinical studies. Meanwhile, inhibitors of dihydroorotate dehydrogenase (DHODH), by reducing the cellular synthesis of pyrimidines, counteract virus replication and are also being clinically evaluated for COVID-19 therapy. Here we show that the combination of NHC and DHODH inhibitors such as teriflunomide, IMU-838/vidofludimus, and BAY2402234, strongly synergizes to inhibit SARS-CoV-2 replication. While single drug treatment only mildly impaired virus replication, combination treatments reduced virus yields by at least two orders of magnitude. We determined this by RT-PCR, TCID50, immunoblot and immunofluorescence assays in Vero E6 and Calu-3 cells infected with wildtype and the Alpha and Beta variants of SARS-CoV-2. We propose that the lack of available pyrimidine nucleotides upon DHODH inhibition increases the incorporation of NHC in nascent viral RNA, thus precluding the correct synthesis of the viral genome in subsequent rounds of replication, thereby inhibiting the production of replication competent virus particles. This concept was further supported by the rescue of replicating virus after addition of pyrimidine nucleosides to the media. Based on our results, we suggest combining these drug candidates, which are currently both tested in clinical studies, to counteract the replication of SARS-CoV-2, the progression of COVID-19, and the transmission of the disease within the population.\n\nSIGNIFICANCEO_LIThe strong synergy displayed by DHODH inhibitors and the active compound of Molnupiravir might enable lower concentrations of each drug to antagonize virus replication, with less toxicity.\nC_LIO_LIBoth Molnupiravir and DHODH inhibitors are currently being tested in advanced clinical trials or are FDA-approved for different purposes, raising the perspective of rapidly testing their combinatory efficacy in clinical studies.\nC_LIO_LIMolnupiravir is currently a promising candidate for treating early stages of COVID-19, under phase II/III clinical evaluation. However, like Remdesivir, it appears only moderately useful in treating severe COVID-19. Since the combination inhibits virus replication far more strongly, and since DHODH inhibitors may also suppress excessive immune responses, the combined clinical application bears the potential of alleviating the disease burden even at later stages.\nC_LI", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Georg T. Wondrak", - "author_inst": "Department of Pharmacology and Toxicology, College of Pharmacy and UA Cancer Center, University of Arizona, Tucson, Arizona" + "author_name": "Kim M Stegmann", + "author_inst": "University Medical Center Goettingen" }, { - "author_name": "Jana Jandova", - "author_inst": "Department of Pharmacology and Toxicology, College of Pharmacy and UA Cancer Center, University of Arizona, Tucson, Arizona" + "author_name": "Antje Dickmanns", + "author_inst": "University Medical Center Goettingen" }, { - "author_name": "Spencer J. Williams", - "author_inst": "Department of Immunobiology, College of Medicine, University of Arizona, Tucson, Arizona" + "author_name": "Natalie Heinen", + "author_inst": "Ruhr University Bochum" }, { - "author_name": "Dominik Schenten", - "author_inst": "Department of Immunobiology, College of Medicine, University of Arizona, Tucson, Arizona" + "author_name": "Uwe Gross", + "author_inst": "University Medical Center Goettingen" + }, + { + "author_name": "Dirk Goerlich", + "author_inst": "Max Planck Institute for Biophysical Chemistry" + }, + { + "author_name": "Stephanie Pfaender", + "author_inst": "Department for Molecular and Medical Virology, Ruhr University Bochum, Germany" + }, + { + "author_name": "Matthias Dobbelstein", + "author_inst": "University Medical Center Goettingen" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.06.24.21259130", @@ -714821,49 +715176,45 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.06.22.21259345", - "rel_title": "Multi-centre post-implementation evaluation of SARS-CoV-2 antigen-based point of care tests used for asymptomatic screening of continuing care healthcare workers", + "rel_doi": "10.1101/2021.06.22.21259349", + "rel_title": "Inflection in prevalence of SARS-CoV-2 infections missing the N501Y mutation as a marker of rapid Delta (B.1.617.2) lineage expansion in Ontario, Canada", "rel_date": "2021-06-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.22.21259345", - "rel_abs": "OBJECTIVESFrequent screening of SARS-CoV-2 among asymptomatic populations using antigen-based point of care tests (APOCT) is occurring globally with limited clinical performance data. The positive predictive value (PPV) of two APOCT used in the asymptomatic screening of SARS-CoV-2 among healthcare workers (HCW) at continuing care (CC) sites across Alberta, Canada was evaluated.\n\nMETHODSBetween February 22 and May 2, 2021, CC sites implemented SARS-CoV-2 voluntary screening of their asymptomatic HCW. Onsite testing with Abbott Panbio or BD Veritor occurred on a weekly or twice weekly basis. Positive APOCT were confirmed with a real-time reverse-transcriptase polymerase chain reaction (rRT-PCR) reference method.\n\nRESULTSA total of 71,847 APOCT (17,689 Veritor and 54,158 Panbio) were performed among 369 CC sites. Eighty-seven (0.12%) APOCT were positive, of which 39 (0.05%) confirmed as true positives using rRT-PCR. Use of the Veritor and Panbio resulted in a 76.6% and 30.0% false positive detection, respectively (p<0.001). This corresponded to a 23.4% and 70.0% PPV for the Veritor and Panbio, respectively.\n\nCONCLUSIONSFrequent screening of SARS-CoV-2 among asymptomatic HCW in CC, using APOCT, resulted in a very low detection rate and a high detection of false positives. Careful assessment between the risks vs benefits of APOCT programs in this population needs to be thoroughly considered before implementation.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.22.21259349", + "rel_abs": "BackgroundThe severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Delta lineage (B.1.617.2) was implicated in the SARS-CoV-2 surge in India. We sought to describe the rapid expansion of the Delta lineage in Ontario, Canada (population 15 million) using mutation profile information and confirmatory whole genome sequencing.\n\nMethodsAll laboratory-confirmed SARS-CoV-2 cases reported to Public Health Ontario between April 1st and June 12th 2021, with cycle threshold values [≤]35, were eligible for screening for the N501Y and the E484K mutations. We classified cases via mutation screening as: (1) N501Y-/E484K- (wild-type/Delta), (2) Alpha (N501Y+/E484K-), (3) Beta/Gamma (N501Y+/E484K+), or (4) N501Y-/E484K+ (predominantly B.1.525, and B.1.1.318).\n\nResultsThe N501Y-/E484K- mutation profile went from having a 29% transmission deficit relative to Alpha (relative Re = 0.71, 95%CI: 0.64, 0.77) on April 1st to having a 50% transmission advantage on June 12th (relative Re = 1.50, 95%CI: 1.31, 1.71). Whole genome sequencing of N501Y-/E484K-cases (N=583) confirmed that the pattern of increasing relative reproduction number coincided with the replacement of wild-type with Delta variant (from 2.2% in early April, to 83% in late May).\n\nDiscussionDelta is rapidly overtaking other SARS-CoV-2 variants in Ontario, and has a substantial transmission advantage. An inflection in the proportion of cases missing the N501Y mutation from rapidly decreasing to rapidly increasing,3 may be an early warning signal for Delta lineage expansion.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Jamil N Kanji", - "author_inst": "University of Calgary; Alberta Precision Laboratories" - }, - { - "author_name": "Dustin Proctor", - "author_inst": "University of Calgary" + "author_name": "Kevin Antoine Brown", + "author_inst": "Public Health Ontario" }, { - "author_name": "William Stokes", - "author_inst": "University of Alberta; Alberta Precision Laboratories" + "author_name": "Jonathan Gubbay", + "author_inst": "Public Health Ontario" }, { - "author_name": "Byron M Berenger", - "author_inst": "University of Calgary; Alberta Precision Laboratories" + "author_name": "Sarah A Buchan", + "author_inst": "Public Health Ontario" }, { - "author_name": "James Silvius", - "author_inst": "University of Calgary" + "author_name": "Nick Daneman", + "author_inst": "Sunnybrook Hospital" }, { - "author_name": "Graham Tipples", - "author_inst": "University of Alberta; Li Ka Shing Institute for Virology; Alberta Precision Laboratories" + "author_name": "Sharmistha Mishra", + "author_inst": "University of Toronto" }, { - "author_name": "A Mark Joffe", - "author_inst": "University of Alberta; Alberta Health Services" + "author_name": "Samir Patel", + "author_inst": "Public Health Ontario" }, { - "author_name": "Allison A Venner", - "author_inst": "University of Calgary; Alberta Precision Laboratories" + "author_name": "Troy Day", + "author_inst": "Queens University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -716551,43 +716902,67 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.06.25.449750", - "rel_title": "A random priming amplification method for whole genome sequencing of SARS-CoV-2 and H1N1 influenza A virus.", + "rel_doi": "10.1101/2021.06.25.449871", + "rel_title": "Engineered chimeric T cell receptor fusion construct (TRuC)-expressing T cells prevent translational shutdown in SARS-CoV-2-infected cells", "rel_date": "2021-06-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.25.449750", - "rel_abs": "BackgroundNon-targeted whole genome sequencing is a powerful tool to comprehensively identify constituents of microbial communities in a sample. There is no need to direct the analysis to any identification before sequencing which can decrease the introduction of bias and false negatives results. It also allows the assessment of genetic aberrations in the genome (e.g., single nucleotide variants, deletions, insertions and copy number variants) including in noncoding protein regions.\n\nMethodsThe performance of four different random priming amplification methods to recover RNA viral genetic material of SARS-CoV-2 were compared in this study. In method 1 (H-P) the reverse transcriptase (RT) step was performed with random hexamers whereas in methods 2-4 RT incorporating an octamer primer with a known tag. In methods 1 and 2 (K-P) sequencing was applied on material derived from the RT-PCR step, whereas in methods 3 (SISPA) and 4 (S-P) an additional amplification was incorporated before sequencing.\n\nResultsThe SISPA method was the most effective and efficient method for non-targeted/random priming whole genome sequencing of COVID that we tested. The SISPA method described in this study allowed for whole genome assembly of SARS-CoV-2 and influenza A(H1N1)pdm09 in mixed samples. We determined the limit of detection and characterization of SARS-CoV-2 virus which was 103 pfu/ml (Ct, 22.4) for whole genome assembly and 101 pfu/ml (Ct, 30) for metagenomics detection.\n\nConclusionsThe SISPA method is predominantly useful for obtaining genome sequences from RNA viruses or investigating complex clinical samples as no prior sequence information is needed. It might be applied to monitor genomic virus changes, virus evolution and can be used for fast metagenomics detection or to assess the general picture of different pathogens within the sample.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.25.449871", + "rel_abs": "SARS-CoV-2, the causative agent of Covid-19, is known to evade the immune system by several mechanisms. This includes the shutdown of the host cellular protein synthesis, which abrogates the induction of antiviral interferon responses. The virus initiates the infection of susceptible cells by binding with its spike protein (S) to the host angiotensin-converting enzyme 2 (ACE2). Here we applied the T cell receptor fusion construct (TRuC) technology to engineer T cells against such infected cells. In our TRuCs an S-binding domain is fused to the CD3{varepsilon} component of the T cell receptor (TCR) complex, enabling recognition of S-containing cells in an HLA independent manner. This domain either consists of the S-binding part of ACE2 or a single-chain variable fragment of an anti-S antibody. We show that the TRuC T cells are activated by and kill cells that express S of SARS-CoV-2 and its alpha (B.1.1.7) and beta (B.1.351) variants at the cell surface. Treatment of SARS-CoV-2 infected cells with our engineered T cells did not lead to massive cytotoxicity towards the infected cells, but resulted in a complete rescue of the translational shutdown despite ongoing viral replication. Our data show that engineered TRuC T cell products might be used against SARS-CoV-2 by exposing infected cells to the host innate immune system.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Klaudia Chrzastek", - "author_inst": "The Pirbright Institute" + "author_name": "Ira Godbole", + "author_inst": "Signaling Research Centers BIOSS and CIBSS, Department of Immunology, Faculty of Biology, University of Freiburg" }, { - "author_name": "Chandana Tennakoon", - "author_inst": "The Pirbright Institute" + "author_name": "Kevin Ciminski", + "author_inst": "Institute of Virology, Medical Center University of Freiburg" }, { - "author_name": "Dagmara Bialy", - "author_inst": "The Pirbright Institute" + "author_name": "O. Sascha Yousefi", + "author_inst": "Signaling Research Centers BIOSS and CIBSS, Department of Immunology, Faculty of Biology, University of Freiburg" }, { - "author_name": "Graham L Freimanis", - "author_inst": "The Pirbright Institute" + "author_name": "Salma Pathan-Chhatbar", + "author_inst": "Signaling Research Centers BIOSS and CIBSS, Department of Immunology, Faculty of Biology, University of Freiburg" }, { - "author_name": "John Flannery", - "author_inst": "The Pirbright Institute" + "author_name": "Deniz Saltukoglu", + "author_inst": "Signaling Research Centers BIOSS and CIBSS, Department of molecular Immunology, Faculty of Biology, University of Freiburg" }, { - "author_name": "Holly Shelton", - "author_inst": "The Pirbright institute" + "author_name": "Niklas Vesper", + "author_inst": "Signaling Research Centers BIOSS and CIBSS, Department of Molecular Immunology, Faculty of Biology, University of Freiburg" + }, + { + "author_name": "Pavel Salavei", + "author_inst": "Core Facility Signalling Factory, BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany" + }, + { + "author_name": "Juliane Strietz", + "author_inst": "Signaling Research Centers BIOSS and CIBSS, Department of Immunology, Faculty of Biology, University of Freiburg" + }, + { + "author_name": "Nicole Gensch", + "author_inst": "Core Facility Signalling Factory, BIOSS Centre for Biological Signalling Studies, University of Freiburg, Germany" + }, + { + "author_name": "Michael Reth", + "author_inst": "Signaling Research Centers BIOSS and CIBSS, Department of Molecular Immunology, Faculty of Biology, University of Freiburg" + }, + { + "author_name": "Martin Schwemmle", + "author_inst": "Institute of Virology, Medical Center University of Freiburg" + }, + { + "author_name": "Wolfgang W. Schamel", + "author_inst": "Signaling Research Centers BIOSS and CIBSS, Department of Immunology, Faculty of Biology, University of Freiburg" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "bioengineering" }, { "rel_doi": "10.1101/2021.06.25.449882", @@ -718257,39 +718632,39 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.06.14.21258907", - "rel_title": "Hybrid-Quantum approach for the optimal lockdown to stop the SARS-CoV-2 community spread subject to maximizing nation economy globally", + "rel_doi": "10.1101/2021.06.18.21259062", + "rel_title": "Temporal changes in mental response and prevention patterns, and their impact from uncertainty stress during the transition in China from the COVID-19 epidemic to sporadic infection", "rel_date": "2021-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.14.21258907", - "rel_abs": "Owing to the SARS-CoV-2 epidemic (severe acute respiratory coronavirus 2 syndromes), the global situation has changed drastically. Several countries, including India, Europe, U.S.A., introduced a full state/nation lockdown to minimize the disease transmission through human interaction after the virus entered the population and to minimize the loss of human life. Millions of people have gone unemployed due to lockdown implementation, resulting in business and industry closure and leading to a national economic slowdown. Therefore, preventing the spread of the COVID-19 virus in the world while also preserving the global economy is an essential problem requiring an effective and immediate solution. Using the compartmental epidemiology S, E, I, R or D (Susceptible, Exposed, Infectious, Recovery or Death) model extended to multiple population regions we predict the evolution of the SARS-CoV-2 disease and construct an optimally scheduled lockdown calendar to execute lockdown over phases, using the well-known Knapsack problem. A comparative analysis of both classical and quantum models shows that our model decreases SARS-CoV-2 active cases while retaining the average global economic factor, GDP, in contrast to the scenario with no lockdown.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.18.21259062", + "rel_abs": "ObjectiveThis prospective observational study examined changing trends of mental responses and prevention patterns, and their impact from uncertainty stress during the transition in China from the COVID-19 epidemic to sporadic infection.\n\nSettingA prospective longitudinal observation design was utilized in this study.\n\nParticipantsWe recruited participants for an online panel survey from chat groups on Chinese social media platforms.\n\nData collectionThere were 7 waves of interviews. Data were obtained by an online survey. A special administrative WeChat group was established to manage the follow-up data collection.\n\nMeasuresSeveral mental responses and prevention patterns were each measured by single questionnaire items. Uncertainty stress was measured by 5-point scale. An irrational beliefs about prevention variable was comprised 5 common misconceptions, which manifested during the COVID-19 epidemic in China.\n\nAnalysisSixty-two participants completed all observation points and were included in the study. The Mann-Kendall Test was used to assess changing trends across the seven observation points. The nonparametric linear mixed effects model was used to examine the association between uncertainty stress and mental and behavioral responses.\n\nResultsThe mean uncertainty stress did not change significantly over the observation period (T:-0.911, P>0.05). This trend was also true for perceived risk (T: -0.141, P>0.05), perceived severity (T: 1.010, P>0.05), self-efficacy for prevention (T: 0.129, P>0.05), and prevention behavior (T: 0.728, P>0.05). There was a statistically significant downwards trend in irrational beliefs about prevention (T: -4.993, p < 0.01), sleep (T: -2.499, p < 0.05), emotions (T: -5.650, p < 0.01), and lifestyle (T:-5.978, p < 0.01). The results showed that uncertainty stress was positively associated with irrational beliefs ({beta}: 0.16298, p<0.01). The more uncertainty stress, the worse was their sleep ({beta}: 0.02070, p<0.05), emotions ({beta}: 0.03462, p<0.01), and lifestyle({beta}: 0.02056, p<0.05). High levels of uncertainty stress was negatively associated with self-efficacy for prevention and prevention behavior, {beta}value was =-1.33210 (p<0.01) and -0.82742 (p<0.01), respectively.\n\nConclusionAs the COVID-19 virus spreads around the globe, it is currently in epidemic status in some countries, in sporadic status in another countries, and it will eventually transition to a sporadic infection status. This study provides new information on changing trends of mental responses and prevention patterns from the COVID-19 epidemic as the transition to a sporadic infection period takes place. These results may have important policy and disease prevention in post-epidemic times.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Sahil Zaman", - "author_inst": "Acharya Prafulla Chandra College, New Barrackpur" + "author_name": "Sihui Peng", + "author_inst": "Jinan University" }, { - "author_name": "Alex Khan", - "author_inst": "Aligned IT, LLC, USA" + "author_name": "Xiaozhao Yousef Yang", + "author_inst": "Sun Yat-sen University" }, { - "author_name": "Arindam Sadhu", - "author_inst": "Narula Institute of Technology, India" + "author_name": "Tingzhong Yang", + "author_inst": "Zhejiang university" }, { - "author_name": "Dr Kunal Das Sr.", - "author_inst": "Acharya Prafulla Chandra College" + "author_name": "Weifang Zhang", + "author_inst": "The Affiliated Hospital of Stomatology, School of Stomatology, Zhejiang University School of Medicine" }, { - "author_name": "Faisal Shah Khan", - "author_inst": "Khalifa University, UAE" + "author_name": "Randall R Cottrell", + "author_inst": "University of North Carolina Wilmington" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.17.21259027", @@ -720087,33 +720462,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.18.21259156", - "rel_title": "Factors affecting the transmission of SARS-CoV-2 in school settings", + "rel_doi": "10.1101/2021.06.14.21258886", + "rel_title": "The majority of the variation in COVID-19 rates between nations is explained by median age, obesity rate, and island status", "rel_date": "2021-06-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.18.21259156", - "rel_abs": "BackgroundSeveral studies have reported SARS-CoV-2 outbreaks in schools, with a wide range of secondary attack rate (SAR; range: 0-100%). We aimed to examine key risk factors to better understand SARS-CoV-2 transmission in schools.\n\nMethodsWe collected records of 39 SARS-CoV-2 school outbreaks globally published through July 2021 and compiled information on hypothesized risk factors. We utilized the directed acyclic graph (DAG) to conceptualize risk mechanisms, used logistic regression to examine each risk-factor group, and further built multi-risk models.\n\nResultsThe best-fit model showed that the intensity of concurrent community transmission (adjusted odds ratio [aOR]: 1.2, 95% CI: 1.17 - 1.24, for each increase of 1 case per 10,000 persons per week), individualism (aOR: 1.72, 95% CI: 1.19 - 2.5, above vs. below the median) were associated higher risk, whereas preventive measures (aOR: 0.22, 95% CI: 0.17 - 0.29, distancing and masking vs. none) and higher population immunity (aOR: 0.28, 95% CI: 0.22 - 0.35) were associated with lower risk of SARS-CoV-2 transmission in schools. Compared to students in pre-schools, the aOR was 0.35 (95% CI: 0.23 - 0.54) for students in primary schools and 1.3 (95% CI: 0.9 - 1.88) for students in high schools.\n\nConclusionsPreventive measures in schools (e.g. social distancing and mask-wearing) and communal efforts to lower transmission and increase vaccination uptake (i.e. vaccine-induced population immunity) in the community should be taken to collectively reduce transmission and protect children in schools. Flexible reopening policies may be considered for different levels of schools given their risk differences.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.14.21258886", + "rel_abs": "Since the World Health Organization declared SARS-CoV-2 to be a global pandemic on March 11, 2020, nearly every nation on earth has reported infections. Incidence and prevalence of COVID-19 case rates have demonstrated extreme geospatial and temporal variability across the globe. The outbreaks in some countries are extreme and devastating, while other countries face outbreaks that are relatively minor. The causes of these differences between nations remain poorly understood, and identifying the factors that underlie this variation is critical to understand the dynamics of this disease in order to better respond to this and future pandemics.\n\nHere, we examine four factors that we anticipated would explain much of the variation in COVID-19 rates between nations: median age, obesity rate, island status, and strength of border closure measures. Clinical evidence suggests that age and obesity increase both the likelihood of infection and transmission in individual patients, which make them plausible demographic factors. The third factor, whether or not each country is an island nation, was selected because the geographical isolation of islands is expected to influence COVID-19 transmission. The fourth factor of border closure was selected because of its anticipated interaction with island nation status.\n\nTogether, these four variables are able to explain a majority of the international variance in COVID-19 case rates. Using a dataset of 190 countries, simple modeling based on these four factors and their interactions explains more than 70% of the total variance between countries. With additional covariates, more complex modeling and higher-order interactions explains more than 80% of the variance. These novel findings offer a solution to explain the unusual global variation of COVID-19 that has remained largely elusive throughout the pandemic.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Haokun Yuan", - "author_inst": "Columbia University" - }, - { - "author_name": "Connor Reynolds", - "author_inst": "Columbia University" + "author_name": "Joseph B Fraiman", + "author_inst": "Louisiana State University" }, { - "author_name": "Sydney Ng", - "author_inst": "Columbia University" + "author_name": "Ethan Ludwin-Peery", + "author_inst": "New York University" }, { - "author_name": "Wan Yang", - "author_inst": "Columbia University" + "author_name": "Sarah Ludwin-Peery", + "author_inst": "Independent Researcher" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -721269,53 +721640,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.18.21259072", - "rel_title": "Evaluation of the effectiveness of remdesivir in treating severe COVID-19 using data from the ISARIC WHO Clinical Characterisation Protocol UK: a prospective, national cohort study.", + "rel_doi": "10.1101/2021.06.15.21258966", + "rel_title": "Tocilizumab in COVID-19 - A Bayesian reanalysis of RECOVERY", "rel_date": "2021-06-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.18.21259072", - "rel_abs": "BackgroundRemdesivir has been evaluated in clinical trial populations, but there is a sparsity of evidence evaluating effectiveness in general populations.\n\nMethodsAdults eligible to be treated with remdesivir, requiring oxygen but not ventilated, were identified from UK patients hospitalised with COVID-19. Patients treated with remdesivir within 24h of hospitalisation were compared with propensity-score matched controls; estimates of effectiveness were calculated for short-term outcomes (14-day mortality, 28-day mortality, time-to-recovery among others) using multivariable modelling.\n\nResults9,278 out of 39,330 patients satisfied eligibility criteria. 1,549 patients were identified as treated and matched with 4,964 controls. Patients were 62% male, mean (SD) age 63.1 (15.6) years, 80% White ethnicity, and symptomatic for a median of 6 days prior to baseline. There was no statistically significant benefit of remdesivir at 14 days in terms of mortality or clinical status; there were signals of effectiveness in time-to-recovery after day 9, and a reduction in 28-day mortality.\n\nConclusionIn a real-world setting, initiation of remdesivir within 24h of hospitalisation in conjunction with standard of care was not associated with a benefit at 14 days but supports clinical trial evidence of a potential reduction in 28-day mortality.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.15.21258966", + "rel_abs": "BackgroundRandomised Evaluation of COVID-19 Therapy (RECOVERY) demonstrated that tocilizumab reduces mortality in hospitalized COVID-19 patients. However, substantial uncertainty remains whether tocilizumabs effect is similar across clinically relevant subgroups. Whether this uncertainty can be resolved with Bayesian methods is unknown.\n\nDesign, Setting, Participants, and InterventionsRECOVERY was a controlled, open-label, platform UK trial that randomized (1:1) 4116 adults with oxygen saturation <92% on room air or receiving oxygen therapy with C-reactive protein [≥]75 mg/L to either usual care or tocilizumab plus usual care.\n\nMain outcome measuresMortality and hospital discharge within 28 days.\n\nMethodsUsing Bayesian methods, we combined RECOVERY with evidence-based priors in-corporating previous COVID-19 tocilizumab RCTs. The probability of tocilizumabs benefit for respiratory support and corticosteroid subgroups and sensitivity analyses were performed with different prior distributions and baseline risks.\n\nResultsFor all-cause mortality, the posterior probabilities of decreased deaths with tocilizumab were >99% and 19% in patients using and not using corticosteroids, respectively. In patients on simple oxygen only, non-invasive ventilation and invasive mechanical ventilation, the probabilities of decreased mortality were 96%, >99% and 77%, respectively. The probabilities for a clinically significant mortality reduction, as assessed by an absolute risk difference > 3% (number needed to treat [≤] 33), were 77%, 96%, 56%, respectively. Sensitivity analyses highlighted the uncertainty and lack of conclusive evidence for tocilizumabs effect in patients on invasive mechanical ventilation and those without concurrent corticosteroids. Posterior probabilities of benefit for hospital discharge outcome were high and consistent across most subgroups.\n\nConclusionsIn this Bayesian reanalysis, COVID-19 hospitalized patients exposed to corticosteroids or on non-invasive ventilation have a high probability of a clinically meaningful mortality benefit from tocilizumab. Tocilizumab also likely improves discharge from hospital in most subgroups. Future research should further address if patients on invasive mechanical ventilation can also benefit from tocilizumab.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Barbara N Arch", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Dorottya Kovacs", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Janet T Scott", - "author_inst": "MRC-University of Glasgow Center for Virus research" - }, - { - "author_name": "Ashley P Jones", - "author_inst": "University of Liverpool" + "author_name": "Arthur M. Albuquerque", + "author_inst": "School of Medicine, Universidade Federal do Rio de Janeiro, Brazil" }, { - "author_name": "Ewen M Harrison", - "author_inst": "University of Edinburgh" + "author_name": "Lucas Tramujas", + "author_inst": "HCor Research Institute, Brazil" }, { - "author_name": "Anna Rosala-Hallas", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Carrol G Gamble", - "author_inst": "University of Liverpool" - }, - { - "author_name": "Peter JM Openshaw", - "author_inst": "Imperial College London" - }, - { - "author_name": "J Kenneth Baillie", - "author_inst": "Roslin Institute, University of Edinburgh" + "author_name": "Lorenzo R. Sewanan", + "author_inst": "Department of Internal Medicine, Columbia University, U.S.A." }, { - "author_name": "Malcolm Gracie Semple", - "author_inst": "University of Liverpool" + "author_name": "James M. Brophy", + "author_inst": "McGill University Health Center, Canada" } ], "version": "1", @@ -723171,59 +723518,87 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.20.21258949", - "rel_title": "Role of physiotherapy team in critically ill COVID-19 patients pronation: can a multidisciplinary management reduce the complications rate?", + "rel_doi": "10.1101/2021.06.21.449284", + "rel_title": "SARS-CoV-2 activates ER stress and Unfolded protein response", "rel_date": "2021-06-21", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.20.21258949", - "rel_abs": "ObjectivesDuring the pandemic, critically ill COVID-19 patients management presented an increased workload for Intensive Care Unit (ICU) nursing staff, particularly during pronation maneuvers, with high risk of complications. In this scenario, a support during pronation by the ICU Physiotherapy Team was introduced.\n\nResearch methodologyRetrospective analysis. Consecutive critically ill COVID-19 patients.\n\nSettingA COVID-19 Center in southern Switzerland, between March 16th and April 30th, 2020.\n\nMain Outcome MeasuresRates and characteristics of pronation-related complications.\n\nResultsForty-two patients on mechanical ventilation (MV) were treated; 296 standard prone/supine positioning were performed, with 3.52 cycles/patient. One (0.3%) major complication was observed, while fourteen (33.3%) patients developed minor complications, e.g. pressure injuries. The incidence of pressure sores was related to ICU length-of-stay (LOS) (p = 0.029) and MV days (p = 0.015), while their number (n = 27) further correlated with ICU LOS (p = 0.001) and MV days (p = 0.001). The propensity matching score analysis did not show any protective factor of pronation regarding pressure injuries (p = 0.448). No other significant correlation was found.\n\nConclusionThe specific pronation team determined a low rate of major complications in critically ill COVID19 patients. The high rate of minor complications appeared to be related to disease severity, rather than from pronation.", - "rel_num_authors": 10, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.21.449284", + "rel_abs": "Coronavirus disease-2019 (COVID-19) pandemic caused by the SARS-CoV-2 coronavirus infection is a major global public health concern affecting millions of people worldwide. The scientific community has joint efforts to provide effective and rapid solutions to this disease. Knowing the molecular, transmission and clinical features of this disease is of paramount importance to develop effective therapeutic and diagnostic tools. Here, we provide evidence that SARS-CoV-2 hijacks the glycosylation biosynthetic, ER-stress and UPR machineries for viral replication using a time-resolved (0-48 hours post infection, hpi) total, membrane as well as glycoproteome mapping and orthogonal validation. We found that SARS-CoV-2 induces ER stress and UPR is observed in Vero and Calu-3 cell lines with activation of the PERK-eIF2-ATF4-CHOP signaling pathway. ER-associated protein upregulation was detected in lung biopsies of COVID-19 patients and associated with survival. At later time points, cell death mechanisms are triggered. The data show that ER stress and UPR pathways are required for SARS-CoV-2 infection, therefore representing a potential target to develop/implement anti-CoVID-19 drugs.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Andrea Glotta", - "author_inst": "Clinica Luganese Moncucco" + "author_name": "Livia Rosa-Fernandes", + "author_inst": "GlycoProteomics Laboratory, Department of Parasitology, ICB, University of Sao Paulo, Brazil" }, { - "author_name": "Nicola Faldarini", - "author_inst": "Clinica Luganese Moncucco" + "author_name": "Lucas C Lazari", + "author_inst": "GlycoProteomics Laboratory, Department of Parasitology, ICB, University of Sao Paulo, Brazil" }, { - "author_name": "Maira Biggiogero", - "author_inst": "Clinica Luganese Moncucco" + "author_name": "Janaina Macedo-da-Silvia", + "author_inst": "GlycoProteomics Laboratory, Department of Parasitology, ICB, University of Sao Paulo, Brazil" }, { - "author_name": "Andrea Saporito", - "author_inst": "Ospedale Regionale di Bellinzona e Valli" + "author_name": "Vinicius de Morais Gomes", + "author_inst": "GlycoProteomics Laboratory, Department of Parasitology, ICB, University of Sao Paulo, Brazil" }, { - "author_name": "Diana Olivieri", - "author_inst": "Clinica Luganese Moncucco" + "author_name": "Rafael Rahal Guaragna Machado", + "author_inst": "Laboratory of Clinical and Molecular Virology, Department of Microbiology, ICB, University of Sao Paulo, Brazil" }, { - "author_name": "Claudia Molteni", - "author_inst": "Clinica Luganese Moncucco" + "author_name": "Ancely Ferreira dos Santos", + "author_inst": "Department of Biochemistry, Institute of Chemistry, University of Sao Paulo, Brazil" }, { - "author_name": "Stefano Petazzi", - "author_inst": "Clinica Luganese Moncucco" + "author_name": "Danielle Bastos Araujo", + "author_inst": "Laboratory of Clinical and Molecular Virology, Department of Microbiology, ICB, University of Sao Paulo, Brazil" }, { - "author_name": "Romano Mauri", - "author_inst": "Clinica Luganese Moncucco" + "author_name": "Joao Vitor Paccini Coutinho", + "author_inst": "GlycoProteomics Laboratory, Department of Parasitology, ICB, University of Sao Paulo, Brazil" }, { - "author_name": "Xavier Capdevila", - "author_inst": "University of Montpellier" + "author_name": "Gabriel Santos Arini", + "author_inst": "Department of Biochemistry, Institute of Chemistry, University of Sao Paulo, Brazil" }, { - "author_name": "Samuele Ceruti", - "author_inst": "Clinica Luganese Moncucco" + "author_name": "Claudia Blanes Angeli", + "author_inst": "GlycoProteomics Laboratory, Department of Parasitology, ICB, University of Sao Paulo, Brazil" + }, + { + "author_name": "Edmarcia E de Souza", + "author_inst": "Unit for Drug Discovery, Department of Parasitology, ICB, University of Sao Paulo, Brazil" + }, + { + "author_name": "Carsten Wrenger", + "author_inst": "Unit for Drug Discovery, Department of Parasitology, ICB, University of Sao Paulo, Brazil" + }, + { + "author_name": "Claudio R. F. Marinho", + "author_inst": "Laboratory of Experimental Immunoparasitology, Department of Parasitology, ICB, University of Sao Paulo, Brazil" + }, + { + "author_name": "Danielle B. L. Oliveira", + "author_inst": "Laboratory of Clinical and Molecular Virology, Department of Microbiology, ICB, University of Sao Paulo, Brazil" + }, + { + "author_name": "Edison L. Durigon", + "author_inst": "Laboratory of Clinical and Molecular Virology, Department of Microbiology, ICB, University of Sao Paulo, Brazil" + }, + { + "author_name": "Leticia Labriola", + "author_inst": "Department of Biochemistry, Institute of Chemistry, University of Sao Paulo, Brazil" + }, + { + "author_name": "Giuseppe Palmisano", + "author_inst": "GlycoProteomics Laboratory, Department of Parasitology, ICB, University of Sao Paulo, Brazil" } ], "version": "1", "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.06.21.449182", @@ -725252,43 +725627,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.14.21258855", - "rel_title": "The Clinical Utility of Serial Procalcitonin and Procalcitonin Clearance in Predicting the Outcome of COVID-19 Patients", + "rel_doi": "10.1101/2021.06.14.21258919", + "rel_title": "Age-Based Disparities in Hospitalizations and Mortality for Coronavirus Disease 2019 (COVID-19)", "rel_date": "2021-06-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.14.21258855", - "rel_abs": "BackgroundThe pandemic of coronavirus disease 2019 (COVID-19) represents a significant threat to global health. Sensitive tests that effectively predict the disease outcome are essentially required to guide proper intervention.\n\nObjectivesTo evaluate the predictive ability of serial procalcitonin (PCT) measurement to predict the outcome of COVID-19 patients, using PCT clearance (PCT-c) as a tool to reflect its dynamic changes.\n\nMethodsA prospective observational study of inpatients diagnosed with COVID-19 at the Quarantine Hospitals of Ain-Shams University, Cairo, Egypt. During the first five days of hospitalization, serial PCT and PCT-c values were obtained and compared between survivors and non-survivors. Patients were followed up to hospital discharge or in-hospital mortality.\n\nResultsCompared to survivors, serial PCT levels of non-survivors were significantly higher (p [≤] 0.001) and progressively increased during follow-up. In contrast, PCT-c values were significantly lower (p < 0.01) and progressively decreased. Receiver operating characteristic (ROC) curve analysis showed that using the initial PCT value alone, at a cut-off value of 0.80 ng/ml, the area under the curve for predicting in-hospital mortality was 0.81 with 61.1% sensitivity and 87.3% accuracy. Serial measurements showed better predictive performance, and the combined prediction value was better than the single prediction by the initial PCT alone.\n\nConclusionsSerial PCT measurement could be a helpful laboratory tool to predict the prognosis and outcome of COVID-19 patients. Moreover, PCT-c could be a reliable tool to assess PCT progressive kinetics.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.14.21258919", + "rel_abs": "PurposeEvidence suggests that older adults, racial/ethnic minorities, and those with comorbidities all face elevated risk for morbidity and mortality from COVID-19; but there are limited reports describing the potential for interactions between these factors.\n\nMethodsWe sought to evaluate age-based heterogeneity in observed disparities in hospitalization, ICU admission, and mortality related to COVID-19 using CDC public use surveillance data on 3,662,325 COVID-19 cases reported from January 1 to August 30, 2020.\n\nResultsRacial/ethnic and comorbidity disparities in hospitalization were most pronounced during ages 20-29 and ages 10-19, with similar elevation seen for disparities in ICU risk.\n\nRacial/ethnic disparities in mortality were most pronounced during ages 20-29 while risk from comorbidity peaks among ages 10-39.\n\nConclusionsAs COVID-19 continues to affect younger populations, special attention to the implications for the most vulnerable subgroups are clearly warranted.\n\nImplications and ContributionAdolescents and young adults appear to have experienced the greatest inequities in COVID-19 outcomes by race/ethnicity and comorbidity. Careful monitoring of trends in this population is warranted as they re-enter school, work, and social settings while being the last group to receive priority for vaccination.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sara I. Taha", - "author_inst": "Department of Clinical Pathology, Faculty of Medicine, Ain Shams University, Cairo, Egypt." - }, - { - "author_name": "Aalaa K. Shata", - "author_inst": "Department of Pulmonary Medicine, Faculty of Medicine, Ain Shams university, Cairo, Egypt." - }, - { - "author_name": "Shereen A. Baioumy", - "author_inst": "Department of Microbiology and Immunology, Faculty of Medicine, Zagazig University, Zagazig, Egypt" - }, - { - "author_name": "Shaimaa H. Fouad", - "author_inst": "Department of Internal Medicine / Allergy and Clinical Immunology, Ain Shams University, Cairo, Egypt." + "author_name": "Lauren E Wisk", + "author_inst": "David Geffen School of Medicine at UCLA" }, { - "author_name": "Aya H. Moussa", - "author_inst": "Department of Anesthesia, Intensive Care and Pain Management, Faculty of Medicine, Ain Shams University, Cairo, Egypt." + "author_name": "Santi K.M. Bhagat", + "author_inst": "Physician-Parent Caregivers, Washington DC" }, { - "author_name": "Mariam K. Youssef", - "author_inst": "Department of Clinical Pathology, Faculty of Medicine, Ain Shams University, Cairo, Egypt." + "author_name": "Niraj Sharma", + "author_inst": "Harvard Medical School" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.06.17.21259021", @@ -726970,139 +727333,171 @@ "category": "synthetic biology" }, { - "rel_doi": "10.1101/2021.06.17.448459", - "rel_title": "Memory B cells control SARS-CoV-2 variants upon mRNA vaccination of naive and COVID-19 recovered individuals.", + "rel_doi": "10.1101/2021.06.17.448820", + "rel_title": "SARS-CoV-2 spike P681R mutation enhances and accelerates viral fusion", "rel_date": "2021-06-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.17.448459", - "rel_abs": "How a previous SARS-CoV-2 infection may amplify and model the memory B cell (MBC) response elicited by mRNA vaccines was addressed by a comparative longitudinal study of two cohorts, naive individuals and disease-recovered patients, up to 2 months after vaccination. The quality of the memory response was assessed by analysis of the VDJ repertoire, affinity and neutralization against variants of concerns (VOC), using unbiased cultures of 2452 MBCs. Upon boost, the MBC pool of recovered patients selectively expanded, further matured and harbored potent neutralizers against VOC. Maturation of the MBC response in naive individuals was much less pronounced. Nevertheless, and as opposed to their weaker neutralizing serum response, half of their RBD-specific MBCs displayed high affinity towards multiple VOC and one-third retained neutralizing potency against B.1.351. Thus, repeated vaccine challenges could reduce these differences by recall of affinity-matured MBCs and allow naive vaccinees to cope efficiently with VOC.", - "rel_num_authors": 30, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.17.448820", + "rel_abs": "During the current SARS-CoV-2 pandemic, a variety of mutations have been accumulated in the viral genome, and currently, four variants of concerns (VOCs) are considered as the hazardous SARS-CoV-2 variants to the human society1. The newly emerging VOC, the B.1.617.2/Delta variant, closely associates with a huge COVID-19 surge in India in Spring 20212. However, its virological property remains unclear. Here, we show that the B.1.617.2/Delta variant is highly fusogenic, and notably, more pathogenic than prototypic SARS-CoV-2 in infected hamsters. The P681R mutation in the spike protein, which is highly conserved in this lineage, facilitates the spike protein cleavage and enhances viral fusogenicity. Moreover, we demonstrate that the P681R-bearing virus exhibits higher pathogenicity than the parental virus. Our data suggest that the P681R mutation is a hallmark that characterizes the virological phenotype of the B.1.617.2/Delta variant and is closely associated with enhanced pathogenicity.", + "rel_num_authors": 38, "rel_authors": [ { - "author_name": "Aurelien Sokal", - "author_inst": "Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Universite de Paris, Paris, France." + "author_name": "Akatsuki Saito", + "author_inst": "University of Miyazaki" }, { - "author_name": "Giovanna Barba-Spaeth", - "author_inst": "Institut Pasteur, Unite de Virologie Structurale, Paris, France." + "author_name": "Rigel Suzuki", + "author_inst": "Hokkaido University" }, { - "author_name": "Ignacio Fernandez", - "author_inst": "Institut Pasteur, Unite de Virologie Structurale, Paris, France." + "author_name": "Tadashi Maemura", + "author_inst": "University of Tokyo" }, { - "author_name": "Matteo Broketa", - "author_inst": "Institut Pasteur, Anticorps en therapie et en pathologie, UMR 1222 INSERM, France" + "author_name": "Hesham Nasser", + "author_inst": "Kumamoto University" }, { - "author_name": "Imane Azzaoui", - "author_inst": "INSERM U955, equipe 2. Institut Mondor de Recherche Biomedicale (IMRB), Universite Paris-Est Creteil (UPEC), Creteil, France." + "author_name": "Keiya Uriu", + "author_inst": "The University of Tokyo" }, { - "author_name": "Andrea de La Selle", - "author_inst": "Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Universite de Paris, Paris, France." + "author_name": "Yusuke Kosugi", + "author_inst": "The University of Tokyo" }, { - "author_name": "Alexis Vandenberghe", - "author_inst": "INSERM U955, equipe 2. Institut Mondor de Recherche Biomedicale (IMRB), Universite Paris-Est Creteil (UPEC), Creteil, France." + "author_name": "Kotaro Shirakawa", + "author_inst": "Kyoto University" }, { - "author_name": "Slim Fourati", - "author_inst": "Departement de Virologie, Bacteriologie, Hygiene et Mycologie-Parasitologie, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hopitaux de Pari" + "author_name": "Kenji Sadamasu", + "author_inst": "Tokyo Metropolitan Institute of Public Health" }, { - "author_name": "Anais Roeser", - "author_inst": "Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Universite de Paris, Paris, France." + "author_name": "Izumi Kimura", + "author_inst": "The University of Tokyo" }, { - "author_name": "Annalisa Meola", - "author_inst": "Institut Pasteur, Unite de Virologie Structurale, Paris, France." + "author_name": "Jumpei Ito", + "author_inst": "The Institute of Medical Science, The University of Tokyo" }, { - "author_name": "Magali Bouvier-Alias", - "author_inst": "Departement de Virologie, Bacteriologie, Hygiene et Mycologie-Parasitologie, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hopitaux de Pari" + "author_name": "Jiaqi Wu", + "author_inst": "Tokai University" }, { - "author_name": "Etienne Crickx", - "author_inst": "Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Universite de Paris, Paris, France." + "author_name": "Kiyoko Iwatsuki-Horimoto", + "author_inst": "Institute of Medical Science, University of Tokyo" }, { - "author_name": "Laetitia Languille", - "author_inst": "Service de Medecine Interne, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hopitaux de Paris (AP-HP), Universite Paris-Est Creteil (UPEC), " + "author_name": "Mutsumi Ito", + "author_inst": "Institute of Medical Science, University of Tokyo" }, { - "author_name": "Marc Michel", - "author_inst": "Service de Medecine Interne, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hopitaux de Paris (AP-HP), Universite Paris-Est Creteil (UPEC), " + "author_name": "Seiya Yamayoshi", + "author_inst": "University of Tokyo" }, { - "author_name": "Bertrand Godeau", - "author_inst": "Service de Medecine Interne, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hopitaux de Paris (AP-HP), Universite Paris-Est Creteil (UPEC), " + "author_name": "Seiya Ozono", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Sebastien Gallien", - "author_inst": "Service des Maladies infectieuses, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hopitaux de Paris (AP-HP), Universite Paris-Est Creteil (U" + "author_name": "Erika P Butlertanaka", + "author_inst": "University of Miyazaki" }, { - "author_name": "Giovanna Melica", - "author_inst": "Service des Maladies infectieuses, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hopitaux de Paris (AP-HP), Universite Paris-Est Creteil (U" + "author_name": "Yuri L Tanaka", + "author_inst": "University of Miyazaki" }, { - "author_name": "Yann Nguyen", - "author_inst": "Service de Medecine Interne, Hopital Beaujon, Assistance Publique des Hopitaux de Paris, Universite de Paris, Clichy, France" + "author_name": "Ryo Shimizu", + "author_inst": "Kumamoto University" }, { - "author_name": "Virginie Zarrouk", - "author_inst": "Service de Medecine Interne, Hopital Beaujon, Assistance Publique des Hopitaux de Paris, Universite de Paris, Clichy, France" + "author_name": "Kenta Shimizu", + "author_inst": "Hokkaido University" }, { - "author_name": "Florence Canoui-Poitrine", - "author_inst": "Departement de Sante Publique, Unite de Recherche Clinique (URC), CEpiA (Clinical Epidemiology and Ageing), EA 7376- Institut Mondor de Recherche Biomedicale (I" + "author_name": "Kumiko Yoshimatsu", + "author_inst": "Hokkaido University" }, { - "author_name": "France Noizat-Pirenne", - "author_inst": "Etablissement Francais du Sang, INSERM U955, Universite Paris-Est Creteil (UPEC), Creteil, France" + "author_name": "Ryoko Kawabata", + "author_inst": "Hiroshima University" }, { - "author_name": "Jerome Megret", - "author_inst": "Plateforme de Cytometrie en Flux, Structure Federative de Recherche Necker, INSERM US24-CNRS UMS3633, Paris, France." + "author_name": "Takemasa Sakaguchi", + "author_inst": "Hiroshima University" }, { - "author_name": "Jean-Michel Pawlotsky", - "author_inst": "Departement de Virologie, Bacteriologie, Hygiene et Mycologie-Parasitologie, Centre Hospitalier Universitaire Henri-Mondor, Assistance Publique-Hopitaux de Pari" + "author_name": "Kenzo Tokunaga", + "author_inst": "National Institute of Infectious Diseases" }, { - "author_name": "Simon Fillatreau", - "author_inst": "Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Universite de Paris, Paris, France." + "author_name": "Isao Yoshida", + "author_inst": "Tokyo Metropolitan Institute of Public Health" }, { - "author_name": "Pierre Brunhs", - "author_inst": "Institut Pasteur, Anticorps en therapie et en pathologie, UMR 1222 INSERM, France" + "author_name": "Hiroyuki Asakura", + "author_inst": "Tokyo Metropolitan Institute of Public Health" }, { - "author_name": "Felix A. Rey", - "author_inst": "Institut Pasteur, Unite de Virologie Structurale, Paris, France." + "author_name": "Mami Nagashima", + "author_inst": "Tokyo Metropolitan Institute of Public Health" }, { - "author_name": "Jean-Claude Weill", - "author_inst": "Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Universite de Paris, Paris, France." + "author_name": "Yasuhiro Kazuma", + "author_inst": "Kyoto University, Graduate School of Medicine" }, { - "author_name": "Claude-Agnes Reynaud", - "author_inst": "Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Universite de Paris, Paris, France." + "author_name": "Ryosuke Nomura", + "author_inst": "Kyoto University" }, { - "author_name": "Pascal Chappert", - "author_inst": "Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Universite de Paris, Paris, France." + "author_name": "Yasuhito Horisawa", + "author_inst": "Kyoto University, Graduate School of Medicine" }, { - "author_name": "Matthieu Mahevas", - "author_inst": "Institut Necker Enfants Malades (INEM), INSERM U1151/CNRS UMS 8253, Universite de Paris, Paris, France." + "author_name": "Kazuhisa Yoshimura", + "author_inst": "Tokyo Metropolitan Institute of Public Health" + }, + { + "author_name": "Akifumi Takaori-Kondo", + "author_inst": "Graduate School of Medicine, Kyoto University" + }, + { + "author_name": "Masaki Imai", + "author_inst": "Institute of Medical Science, University of Tokyo" + }, + { + "author_name": "- The Genotype to Phenotype Japan (G2P-Japan) Consortium", + "author_inst": "-" + }, + { + "author_name": "So Nakagawa", + "author_inst": "Tokai University" + }, + { + "author_name": "Terumasa Ikeda", + "author_inst": "Kumamoto University" + }, + { + "author_name": "Takasuke Fukuhara", + "author_inst": "Hokkaido University" + }, + { + "author_name": "Yoshihiro Kawaoka", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Kei Sato", + "author_inst": "Institute of Medical Science, The University of Tokyo" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.06.17.21258639", @@ -729620,77 +730015,77 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.06.14.448461", - "rel_title": "Protective efficacy of rhesus adenovirus COVID-19 vaccines against mouse-adapted SARS-CoV-2", + "rel_doi": "10.1101/2021.06.15.448497", + "rel_title": "The SARS-CoV-2 nucleocapsid protein associates with the replication organelles before viral assembly at the Golgi/ERGIC and lysosome-mediated egress", "rel_date": "2021-06-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.14.448461", - "rel_abs": "The global COVID-19 pandemic has sparked intense interest in the rapid development of vaccines as well as animal models to evaluate vaccine candidates and to define immune correlates of protection. We recently reported a mouse-adapted SARS-CoV-2 virus strain (MA10) with the potential to infect wild-type laboratory mice, driving high levels of viral replication in respiratory tract tissues as well as severe clinical and respiratory symptoms, aspects of COVID-19 disease in humans that are important to capture in model systems. We evaluated the immunogenicity and protective efficacy of novel rhesus adenovirus serotype 52 (RhAd52) vaccines against MA10 challenge in mice. Baseline seroprevalence is lower for rhesus adenovirus vectors than for human or chimpanzee adenovirus vectors, making these vectors attractive candidates for vaccine development. We observed that RhAd52 vaccines elicited robust binding and neutralizing antibody titers, which inversely correlated with viral replication after challenge. These data support the development of RhAd52 vaccines and the use of the MA10 challenge virus to screen novel vaccine candidates and to study the immunologic mechanisms that underscore protection from SARS-CoV-2 challenge in wild-type mice.\n\nImportanceWe have developed a series of SARS-CoV-2 vaccines using rhesus adenovirus serotype 52 (RhAd52) vectors, which exhibits a lower seroprevalence than human and chimpanzee vectors, supporting their development as novel vaccine vectors or as an alternative Ad vector for boosting. We sought to test these vaccines using a recently reported mouse-adapted SARS-CoV-2 (MA10) virus to i) evaluate the protective efficacy of RhAd52 vaccines and ii) further characterize this mouse-adapted challenge model and probe immune correlates of protection. We demonstrate RhAd52 vaccines elicit robust SARS-CoV-2-specific antibody responses and protect against clinical disease and viral replication in the lungs. Further, binding and neutralizing antibody titers correlated with protective efficacy. These data validate the MA10 mouse model as a useful tool to screen and study novel vaccine candidates, as well as the development of RhAd52 vaccines for COVID-19.", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.15.448497", + "rel_abs": "Despite being the target of extensive research efforts due to the COVID-19 pandemic, relatively little is known about the dynamics of SARS-CoV-2 replication within cells. We investigate and characterise the tightly orchestrated sequence of events during different stages of the infection cycle by visualising the spatiotemporal dynamics of the four structural proteins of SARS-CoV-2 at high resolution. The nucleoprotein is expressed first and accumulates around folded ER membranes in convoluted layers that connect to viral RNA replication foci. We find that of the three transmembrane proteins, the membrane protein appears at the Golgi apparatus/ERGIC before the spike and envelope proteins. Relocation of the lysosome marker LAMP1 towards the assembly compartment and its detection in transport vesicles of viral proteins confirm an important role of lysosomes in SARS-CoV-2 egress. These data provide new insights into the spatiotemporal regulation of SARS-CoV-2 assembly, and refine current understanding of SARS-CoV-2 replication.", "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Lisa Tostanoski", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Katharina M Scherer", + "author_inst": "University of Cambridge" }, { - "author_name": "Lisa Gralinski", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Luca Mascheroni", + "author_inst": "University of Cambridge" }, { - "author_name": "David Martinez", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "George W Carnell", + "author_inst": "University of Cambridge" }, { - "author_name": "Alexandra Schaefer", - "author_inst": "UNC-CH, School of Public Health" + "author_name": "Lucia C S Wunderlich", + "author_inst": "University of Cambridge" }, { - "author_name": "Shant Mahrokhian", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Stanislaw Makarchuk", + "author_inst": "UK Dementia Research Institute, Cambridge" }, { - "author_name": "Zhenfeng Li", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Marius Brockhoff", + "author_inst": "University of Cambridge" }, { - "author_name": "Felix Nampanya", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Ioanna Mela", + "author_inst": "University of Cambridge" }, { - "author_name": "Huahua Wan", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Ana Fernandez-Villegas", + "author_inst": "University of Cambridge" }, { - "author_name": "Jingyou Yu", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Max Barysevich", + "author_inst": "University of Cambridge" }, { - "author_name": "Aiquan Chang", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Hazel Stewart", + "author_inst": "University of Cambridge" }, { - "author_name": "Jinyan Liu", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Maria Suau Sans", + "author_inst": "University of Cambridge" }, { - "author_name": "Katherine McMahan", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Charlotte L George", + "author_inst": "University of Cambridge" }, { - "author_name": "Kenneth Dinnon III", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Jacob R Lamb", + "author_inst": "University of Cambridge" }, { - "author_name": "Sarah R. Leist", - "author_inst": "University of North Carolina" + "author_name": "Gabriele S Kaminski Schierle", + "author_inst": "University of Cambridge" }, { - "author_name": "Ralph S. Baric", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Jonathan L Heeney", + "author_inst": "University of Cambridge" }, { - "author_name": "Dan H. Barouch", - "author_inst": "Beth Israel Deaconess Medical Center" + "author_name": "Clemens F Kaminski", + "author_inst": "University of Cambridge" } ], "version": "1", @@ -731017,37 +731412,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.14.21258236", - "rel_title": "Survey of COVID-19 associated symptoms and reported deaths in an urban community in Kano, Nigeria.", + "rel_doi": "10.1101/2021.06.10.21258685", + "rel_title": "A Meta-Analysis of Influenza Vaccination Following Correspondence: Considerations for COVID-19", "rel_date": "2021-06-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.14.21258236", - "rel_abs": "BackgroundNigeria reported the first case of COVID-19 on February 27, 2020. By June of 2020, many people reported experiencing mild COVID-19 associated symptoms, yet did not get tested due to inaccessible testing and insufficient knowledge of the disease. There were media stories quoting grave diggers in Kano who reported high burial rates during this time.\n\nMethodsIn order to draw more data on COVID-19 cases during this time period, we conducted a cross-sectional symptom survey in Kano, surveying 291 adults. Participants were asked to report demographic characteristics, past COVID-19 testing and symptoms, and community deaths. To assess associations between COVID-19 associated symptoms and socio-demographic characteristics, bivariate analyses using Chi-square tests were performed. A logistic regression assessing the association between any reported symptoms and the kind of work (indoor/outdoor) was done while adjusting for age, gender and education level.\n\nResultsHalf of the respondents reported at least one symptom associated with COVID-19; the three most common symptoms were loss of appetite, cough, and fever. There was a statistically significant relationship between age group of the respondent and presence of COVID-19 associated symptoms. Gender or level of education did not have statistically significant association with COVID-19 associated symptoms among the respondents. People with outdoor occupations such as trading and hawking were more than twice as likely to report COVID-19 associated symptoms compared to those who were unemployed. Just under half of the respondents reported knowing someone who died in their community, with unexplained causes attributed to two-thirds of these cases. Our study found evidence of COVID-19 associated symptoms especially among the older population and unexplained deaths in Kano. Lack of confirmatory laboratory tests and absence of baseline vital statistics precluded us from finding definitive evidence for or against COVID-19 infection and associated mortality.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.10.21258685", + "rel_abs": "BackgroundHigh vaccination rates are needed to protect against influenza and to end the COVID-19 pandemic. Health authorities need to know if supplementing mass communications with direct correspondence to the community would increase uptake.\n\nObjectivesThe primary objective is to determine if sending a single written message directly to individuals increases influenza vaccine uptake, and a secondary objective is to identify any identified content shown to increase influenza vaccine uptake.\n\nMethodsPubMed, PsycInfo and Web of Science were searched for English language RCTs testing a single correspondence for members of the community in OECD countries to obtain influenza vaccination. A meta-analysis with inverse-variance, random-effects modelling was used to estimate a mean, weighted risk ratio effect size measure of vaccine uptake. Studies were quality assessed and analysis was undertaken to account for potential publication bias.\n\nResultsTwenty-two randomized controlled trials were included covering 37 interventions. Of the 37 interventions, 32 (86%) report an increase in influenza vaccination rates. A formal meta-analysis shows that sending a single written message increases influenza vaccine uptake by 18% (RR = 1.18, 95%CI [1.13-1.22], Z = 8.56, p < .001) relative to the no contact comparator group. Analysis shows that the intervention is effective across correspondence type, age group, time, and location, and after allowing for risk of publication bias.\n\nLimitationsThe review was restricted to English language publications, and the generalizability of results across the OECD may be questioned.\n\nConclusions and implicationsThe implication for public health authorities organizing vaccination programs for influenza, and arguably also for COVID-19, is that sending written vaccination correspondence to members of the community is likely to increase uptake.\n\nThe review was not registered nor was a protocol prepared due to time sensitivity.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Disha Shahani", - "author_inst": "eHealth Africa" + "author_name": "Robert P Murphy", + "author_inst": "Department of Health, Ireland" }, { - "author_name": "Zayyad Sani Farouq", - "author_inst": "EHA Clinics" + "author_name": "Carol Taaffe", + "author_inst": "Department of Health, Ireland" }, { - "author_name": "Hadiza Galadima", - "author_inst": "Old Dominion University" + "author_name": "Elayne Ahern", + "author_inst": "Dublin City University" }, { - "author_name": "Ashna Khare", - "author_inst": "eHealth Africa" + "author_name": "Grace McMahon", + "author_inst": "University of Limerick" }, { - "author_name": "Nirmal Ravi", - "author_inst": "eHealth Africa" + "author_name": "Orla Muldoon", + "author_inst": "University of Limerick" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -732432,235 +732827,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.06.14.448343", - "rel_title": "COVID-eVax, an electroporated plasmid DNA vaccine candidate encoding the SARS-CoV-2 Receptor Binding Domain, elicits protective immune responses in animal models of COVID-19", + "rel_doi": "10.1101/2021.06.12.448149", + "rel_title": "Regulatory dissection of the severe COVID-19 risk locus introgressed by Neanderthals", "rel_date": "2021-06-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.14.448343", - "rel_abs": "The COVID-19 pandemic caused by the {beta}-coronavirus SARS-CoV-2 has made the development of safe and effective vaccines a critical global priority. To date, four vaccines have already been approved by European and American authorities for preventing COVID-19 but the development of additional vaccine platforms with improved supply and logistics profiles remains a pressing need. Here we report the preclinical evaluation of a novel COVID-19 vaccine candidate based on the electroporation of engineered, synthetic cDNA encoding a viral antigen in the skeletal muscle, a technology previously utilized for cancer vaccines. We constructed a set of prototype DNA vaccines expressing various forms of the SARS-CoV-2 Spike (S) protein and assessed their immunogenicity in animal models. Among them, COVID-eVax - a DNA plasmid encoding a secreted monomeric form of SARS-CoV-2 S protein RBD - induced the most potent anti-SARS-CoV-2 neutralizing antibody responses (including against the current most common variants of concern) and a robust T cell response. Upon challenge with SARS-CoV-2, immunized K18-hACE2 transgenic mice showed reduced weight loss, improved pulmonary function and significantly lower viral replication in the lungs and brain. COVID-eVax conferred significant protection to ferrets upon SARS-CoV-2 challenge. In summary, this study identifies COVID-eVax as an ideal COVID-19 vaccine candidate suitable for clinical development. Accordingly, a combined phase I-II trial has recently started in Italy.", - "rel_num_authors": 54, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.12.448149", + "rel_abs": "Individuals infected with the SARS-CoV-2 virus present with a wide variety of phenotypes ranging from asymptomatic to severe and even lethal outcomes. Past research has revealed a genetic haplotype on chromosome 3 that entered the human population via introgression from Neanderthals as the strongest genetic risk factor for the severe COVID-19 phenotype. However, the specific variants along this introgressed haplotype that contribute to this risk and the biological mechanisms that are involved remain unclear. Here, we assess the variants present on the risk haplotype for their likelihood of driving the severe COVID-19 phenotype. We do this by first exploring their impact on the regulation of genes involved in COVID-19 infection using a variety of population genetics and functional genomics tools. We then perform an locus-specific massively parallel reporter assay to individually assess the regulatory potential of each allele on the haplotype in a multipotent immune-related cell line. We ultimately reduce the set of over 600 linked genetic variants to identify 4 introgressed alleles that are strong functional candidates for driving the association between this locus and severe COVID-19. These variants likely drive the locus impact on severity by putatively modulating the regulation of two critical chemokine receptor genes: CCR1 and CCR5. These alleles are ideal targets for future functional investigations into the interaction between host genomics and COVID-19 outcomes.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Antonella Conforti", - "author_inst": "Evvivax" - }, - { - "author_name": "Emanuele Marra", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Fabio Palombo", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Giuseppe Roscilli", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Micol Rava", - "author_inst": "San Raffaele Scientific Institute" - }, - { - "author_name": "Valeria Fumagalli", - "author_inst": "San Raffaele Scientific Institute" - }, - { - "author_name": "Alessia Muzi", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Mariano Maffei", - "author_inst": "San Raffaele Scientific Institute" - }, - { - "author_name": "Laura Luberto", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Lucia Lione", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Erika Salvatori", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Mirco Compagnone", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Eleonora Pinto", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Emiliano Pavoni", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Federica Bucci", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Grazia Vitagliano", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Daniela Stoppoloni", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Maria Lucrezia Pacello", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Manuela Cappelletti", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Fabiana Fosca Ferrara", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Valerio Chiarini", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Roberto Arriga", - "author_inst": "Takis Biotech" - }, - { - "author_name": "Abraham Nyska", - "author_inst": "Tel Aviv University" - }, - { - "author_name": "Pietro Di Lucia", - "author_inst": "San Raffaele Scientific Institute" - }, - { - "author_name": "Davide Marotta", - "author_inst": "San Raffaele Scientific Institute" - }, - { - "author_name": "Elisa Bono", - "author_inst": "San Raffaele Scientific Institute" - }, - { - "author_name": "Leonardo Giustini", - "author_inst": "San Raffaele Scientific Institute" - }, - { - "author_name": "Eleonora Sala", - "author_inst": "San Raffaele Scientific Institute" - }, - { - "author_name": "Chiara Perucchini", - "author_inst": "San Raffaele Scientific Institute" - }, - { - "author_name": "Jemma Paterson", - "author_inst": "PHE" - }, - { - "author_name": "Kathryn A Ryan", - "author_inst": "Public Health England" - }, - { - "author_name": "Amy Challis", - "author_inst": "PHE" - }, - { - "author_name": "Giulia Matusali", - "author_inst": "Inmi" - }, - { - "author_name": "Francesca Colavita", - "author_inst": "INMI" - }, - { - "author_name": "Gianfranco Caselli", - "author_inst": "Rottapharm" - }, - { - "author_name": "Elena Criscuolo", - "author_inst": "HSR" - }, - { - "author_name": "Nicola A Clementi", - "author_inst": "Vita-Salute San Raffaele University" - }, - { - "author_name": "Nicasio Mancini", - "author_inst": "Universita Vita-Salute San Raffaele" - }, - { - "author_name": "Rudiger Gross", - "author_inst": "Ulm university" - }, - { - "author_name": "Alina Siedel", - "author_inst": "Ulm University" - }, - { - "author_name": "Lukas Wettstein", - "author_inst": "Ulm University" - }, - { - "author_name": "Jan Munch", - "author_inst": "Ulm University" - }, - { - "author_name": "Lorena Donnici", - "author_inst": "INGM" - }, - { - "author_name": "Matteo Conti", - "author_inst": "INGM" - }, - { - "author_name": "Raffaele De Francesco", - "author_inst": "INGM" - }, - { - "author_name": "Mirela Kuka", - "author_inst": "HSR" - }, - { - "author_name": "Gennaro Ciliberto", - "author_inst": "IFO" - }, - { - "author_name": "Concetta Castilletti", - "author_inst": "INMI" - }, - { - "author_name": "Maria R. Capobianchi", - "author_inst": "National Institute for Infectious Diseases" + "author_name": "Evelyn Jagoda", + "author_inst": "Harvard University" }, { - "author_name": "Giuseppe Ippolito", - "author_inst": "National Institute Infectious Diseaseas" + "author_name": "Davide Marnetto", + "author_inst": "University of Tartu" }, { - "author_name": "Luca Guidotti", - "author_inst": "HSR" + "author_name": "Francesco Montinaro", + "author_inst": "University of Bari" }, { - "author_name": "Lucio Rovati", - "author_inst": "Rottapharm" + "author_name": "Daniel Richard", + "author_inst": "Harvard University" }, { - "author_name": "Matteo Iannacone", - "author_inst": "San Raffaele Scientific Institute" + "author_name": "Luca Pagani", + "author_inst": "University of Padova" }, { - "author_name": "Luigi Aurisicchio", - "author_inst": "Takis Biotech" + "author_name": "Terence D Capellini", + "author_inst": "Harvard University" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "genetics" }, { "rel_doi": "10.1101/2021.06.13.448258", @@ -734234,31 +734437,39 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.06.08.21258525", - "rel_title": "COVID19, Consumption and Inequality: A Systematic Analysis of Rural Population of India", + "rel_doi": "10.1101/2021.06.08.21258561", + "rel_title": "The impact of Covid-19 vaccination on the Italian healthcare system: a scenario analysis", "rel_date": "2021-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.08.21258525", - "rel_abs": "BackgroundCOVID19 pandemic has had major impact on consumption levels and inequality within India. Government policy interventions have targeted poor households for cash and food transfers. It is important, however, to study the impact of the pandemic on consumption levels of non-poor in India, and in particular the middle class. In this paper, we aim to quantify the changes in consumption levels and inequality over time, across all groups of rural households in India.\n\nMethodsWe analyze three rounds of COVID 19-related shock surveys between May and September 2020. These surveys cover rural households of six large states in India and are representative of more than 442 million (52% of Indias rural population).\n\nFindingsIn the early phase of the pandemic, it was the bottom 40% of households that experienced the most severe decline in consumption. But as the pandemic deepened, consumption declined across all classes of households. Besides the poorest, it was particularly severe for the middle class (defined as 40%-80%). We also measure consumption inequality over time and find that the Gini coefficient of consumption distribution increased significantly.\n\nInterpretationIn addition to focusing on poor households, policy responses to alleviate peoples sufferings would have to consider a more comprehensive boost to consumption and compensate for the reduced consumption among middle class families as well.\n\nFundingNone.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.08.21258561", + "rel_abs": "IntroductionThe objective of this study is to estimate the effects of the national immunisation strategy for Covid-19 in Italy on the national healthcare system.\n\nMethodsAn epidemiological scenario analysis was developed in order to simulate the impact of the Covid-19 pandemic on the Italian national healthcare system in 2021. Hospitalisations, ICU admissions and death rates were modelled based on 2020 data. We forecast the impact of the introduction of a primary prevention strategy on the national healthcare system by considering vaccine efficacy, availability of doses and potential population coverage over time.\n\nResultsIn the absence of immunisation, between 57,000 and 63,000 additional deaths are forecast in 2021. Based on the assumptions underlying the two epidemiological scenarios from the 2020 data, our model predicts that cumulative hospital admissions in 2021 will range from 3.4 to 3.9 million. The deployment of vaccine immunisation has the potential to control the evolution of 2021 infections and avoid from 60 to 67 percent of deaths compared to not vaccinating.\n\nConclusionsIn order to inform Italian policymakers on delivering a mass vaccination programme, this study highlights and detects some key factors that must be controlled to ensure that immunisation targets will be met in reasonable time.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Mudit Kapoor", - "author_inst": "Indian Statistical Institution, Delhi" + "author_name": "Andrea Marcellusi", + "author_inst": "University of Rome \"Tor Vergata\"" }, { - "author_name": "Shamika Ravi", - "author_inst": "Brookings Institution" + "author_name": "Gianluca Fabiano", + "author_inst": "Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK" }, { - "author_name": "A.K.Shiva Kumar", - "author_inst": "Development Economist and Policy Advisor" + "author_name": "Paolo Sciattella", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Massimo Andreoni", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Francesco Saverio Mennini", + "author_inst": "University of Rome Tor Vergata" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health policy" }, { "rel_doi": "10.1101/2021.06.08.21258545", @@ -736208,43 +736419,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.08.21258434", - "rel_title": "The impact of COVID-19 pandemic on influenza transmission: molecular and epidemiological evidence", + "rel_doi": "10.1101/2021.06.07.21258476", + "rel_title": "Possible future waves of SARS-CoV-2 infection generated by variants of concern with a range of characteristics", "rel_date": "2021-06-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.08.21258434", - "rel_abs": "To quantify the impact of COVID-19-related control measures on the spread of human influenza virus, we analyzed case numbers, viral molecular sequences, personal behavior data, and policy stringency data from various countries, and found consistent evidence of decrease in influenza incidence after the emergence of COVID-19.\n\nArticle SummaryWe quantify a noticeable decrease in H1N1 and H3N2 cases and genetic diversity in selected countries since the onset of the COVID-19 pandemic.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.07.21258476", + "rel_abs": "Viral reproduction of SARS-CoV-2 provides opportunities for the acquisition of advantageous mutations, altering viral transmissibility, disease severity, and/or allowing escape from natural or vaccine-derived immunity. We use three mathematical models: a parsimonious deterministic model with homogeneous mixing; an age-structured model; and a stochastic importation model to investigate the effect of potential variants of concern (VOCs). Calibrating to the situation in England in May 2021, we find epidemiological trajectories for putative VOCs are wide-ranging and dependent on their transmissibility, immune escape capability, and the introduction timing of a postulated VOC-targeted vaccine. We demonstrate that a VOC with a substantial transmission advantage over resident variants, or with immune escape properties, can generate a wave of infections and hospitalisations comparable to the winter 2020-2021 wave. Moreover, a variant that is less transmissible, but shows partial immune-escape could provoke a wave of infection that would not be revealed until control measures are further relaxed.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Leon K Tran", - "author_inst": "Department of Statistics, Stanford University, CA, USA" + "author_name": "Louise Dyson", + "author_inst": "The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C" }, { - "author_name": "Dai-Wei Huang", - "author_inst": "College of Life Science, National Tsing Hua University, Hsinchu, Taiwan" + "author_name": "Edward M Hill", + "author_inst": "The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C" }, { - "author_name": "Nien-Kung Li", - "author_inst": "College of Life Science, National Tsing Hua University, Hsinchu, Taiwan" + "author_name": "Sam Moore", + "author_inst": "The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C" }, { - "author_name": "Julia Palacios", - "author_inst": "Department of Statistics, Stanford University, CA, USA" + "author_name": "Jacob Curran-Sebastian", + "author_inst": "Department of Mathematics, University of Manchester, Manchester, United Kingdom" }, { - "author_name": "Hsiao-Han Chang", - "author_inst": "Department of Life Science & Institute of Bioinformatics and Structural Biology, National Tsing Hua University, Hsinchu, Taiwan" + "author_name": "Michael J Tildesley", + "author_inst": "The Zeeman Institute for Systems Biology & Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, C" }, { - "author_name": "Lucy M Li", - "author_inst": "The Public Health Company, Goleta, CA, USA" + "author_name": "Katrina A Lythgoe", + "author_inst": "Big Data Institute, Old Road Campus, University of Oxford, United Kingdom." + }, + { + "author_name": "Thomas House", + "author_inst": "Department of Mathematics, University of Manchester, Manchester, United Kingdom." + }, + { + "author_name": "Lorenzo Pellis", + "author_inst": "Department of Mathematics, University of Manchester, Manchester, United Kingdom." + }, + { + "author_name": "Matt J Keeling", + "author_inst": "The Zeeman Institute for Systems Biology \\& Infectious Disease Epidemiology Research, School of Life Sciences and Mathematics Institute, University of Warwick, " } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.06.07.21258461", @@ -738166,159 +738389,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.08.21258284", - "rel_title": "Highly-specific memory B cells generation after the 2nd dose of BNT162b2 vaccine compensate for the decline of serum antibodies and absence of mucosal IgA", + "rel_doi": "10.1101/2021.06.08.21258558", + "rel_title": "Response of Unvaccinated US Adults to Official Information About the Pause in Use of the Johnson & Johnson-Janssen COVID-19 Vaccine", "rel_date": "2021-06-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.08.21258284", - "rel_abs": "Specific memory B cells and antibodies are reliable read-out of vaccine efficacy. We analyzed these biomarkers after one and two doses of BNT162b2 vaccine. The second dose significantly increases the level of highly-specific memory B cells and antibodies. Two months after the second dose, specific antibody levels decline, but highly specific memory B cells continue to increase thus predicting a sustained protection from COVID-19.\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC=\"FIGDIR/small/21258284v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (28K):\norg.highwire.dtl.DTLVardef@1700325org.highwire.dtl.DTLVardef@deb172org.highwire.dtl.DTLVardef@53f056org.highwire.dtl.DTLVardef@c7a98d_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract\n\nC_FIG", - "rel_num_authors": 35, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.08.21258558", + "rel_abs": "On April 13, 2021 the Centers for Disease Control and Prevention (CDC) and Food and Drug Administration (FDA) recommended in a pause in use of the Johnson & Johnson (J&J)-Janssen COVID-19 vaccine due to reports of cerebral venous sinus thrombosis (CVST) in recently vaccinated individuals. The announcement of the pause required development of a coordinated communication strategy under extreme time pressure and careful messaging by stakeholders to mitigate reduced public confidence in COVID-19 vaccines, as was observed following the temporary suspension of the Oxford-AstraZeneca vaccine in many countries. In this survey study, we evaluated understanding and impressions of the CDCs public online information about the J&J-Janssen pause among unvaccinated US adults.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Eva Piano Mortari", - "author_inst": "Ospedale Pediatrico Bambino Gesu" - }, - { - "author_name": "Cristina Russo", - "author_inst": "Bambino Gesu Children Hospital" - }, - { - "author_name": "Maria Rosaria Vinci", - "author_inst": "Bambino Gesu Children Hospital" - }, - { - "author_name": "Sara Terreri", - "author_inst": "Bambino Gesu Children Hospital" - }, - { - "author_name": "Ane Fernandez Salinas", - "author_inst": "Bambino Gesu Children Hospital" - }, - { - "author_name": "Livia Piccioni", - "author_inst": "Bambino Gesu Children Hospital" - }, - { - "author_name": "Claudia Alteri", - "author_inst": "University of Milano" - }, - { - "author_name": "luna Colagrossi", - "author_inst": "Bambino Gesu Children Hospital" - }, - { - "author_name": "Luana Coltella", - "author_inst": "Bambino gesu Children Hospital" - }, - { - "author_name": "Stefania Ranno", - "author_inst": "Bambino Gesu Children Hospital" - }, - { - "author_name": "Giulia Linardos", - "author_inst": "Bambino Gesu Children hospital" - }, - { - "author_name": "Marilena Agosta", - "author_inst": "Bambino Gesu children hospital" - }, - { - "author_name": "Christian Albano", - "author_inst": "bambino gesu children hospita" - }, - { - "author_name": "Chiara Agrati", - "author_inst": "Spallanzani Roma" - }, - { - "author_name": "Concetta Castilletti", - "author_inst": "Spallanzani Roma" - }, - { - "author_name": "Silvia Meschi", - "author_inst": "National institute of infectious diseases l spallanzani" - }, - { - "author_name": "Paolo Romania", - "author_inst": "La Sapienza Roma" - }, - { - "author_name": "Giuseppe Roscilli", - "author_inst": "Takis" - }, - { - "author_name": "Emiliano Pavoni", - "author_inst": "Takis" - }, - { - "author_name": "Vincenzo Camisa", - "author_inst": "Bambino Gesu Children Hospital" - }, - { - "author_name": "Annapaola Santoro", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "Rita Brugaletta", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "Nicola Magnavita", - "author_inst": "Policlinico Gemelli Roma" - }, - { - "author_name": "Alessandra Ruggiero", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "Nicola Cotugno", - "author_inst": "Bambino Gesu children hospital" - }, - { - "author_name": "Donato Amodio", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "Marta Luisa Cioffi Degli Atti", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "Daniela Giorgio", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "Nicoletta Russo", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "Guglielmo Salvatori", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "tiziana corsetti", - "author_inst": "bambino gesu children hospital" - }, - { - "author_name": "Franco Locatelli", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "Carlo Federico Perno", - "author_inst": "Bambino gesu children hospital" - }, - { - "author_name": "Salvatore Zaffina", - "author_inst": "Bambino gesu children hospital" + "author_name": "Vishala Mishra", + "author_inst": "Madras Medical College" }, { - "author_name": "Rita Carsetti", - "author_inst": "Bambino Gesu Children Hospital" + "author_name": "Joseph P. Dexter", + "author_inst": "Harvard University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.06.06.21258253", @@ -740240,35 +740331,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.07.446560", - "rel_title": "Mapping Potential Antigenic Drift Sites (PADS) on SARS-CoV-2 Spike in Continuous Epitope-Paratope Space", + "rel_doi": "10.1101/2021.06.07.447437", + "rel_title": "FXa cleaves the SARS-CoV-2 spike protein and blocks cell entry to protect against infection with inferior effects in B.1.1.7 variant", "rel_date": "2021-06-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.07.446560", - "rel_abs": "SARS-CoV-2 mutations with antigenic effects pose a risk to immunity developed through vaccination and natural infection. While vaccine updates for current variants of concern (VOCs) are underway, it is likewise important to prepare for further antigenic mutations as the virus navigates the heterogeneous global landscape of host immunity. Toward this end, a wealth of data and tools exist that can augment existing genetic surveillance of VOC evolution. In this study, we integrate published datasets describing genetic, structural, and functional constraints on mutation along with computational analyses of antibody-spike co-crystal structures to identify a set of potential antigenic drift sites (PADS) within the receptor binding domain (RBD) and N-terminal domain (NTD) of SARS-CoV-2 spike protein. Further, we project the PADS set into a continuous epitope-paratope space to facilitate interpretation of the degree to which newly observed mutations might be antigenically synergistic with existing VOC mutations, and this representation suggests that functionally convergent and synergistic antigenic mutations are accruing across VOC NTDs. The PADS set and synergy visualization serve as a reference as new mutations are detected on VOCs, enable proactive investigation of potentially synergistic mutations, and offer guidance to antibody and vaccine design efforts.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=129 SRC=\"FIGDIR/small/446560v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (27K):\norg.highwire.dtl.DTLVardef@13b884forg.highwire.dtl.DTLVardef@171fe3eorg.highwire.dtl.DTLVardef@eac445org.highwire.dtl.DTLVardef@fba613_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.07.447437", + "rel_abs": "The ongoing coronavirus disease 2019 (COVID-19) pandemic is caused by infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human natural defense mechanisms against SARS-CoV-2 are largely unknown. Serine proteases (SPs) including furin and TMPRSS2 cleave SARS-CoV-2 spike protein, facilitating viral entry. Here, we show that FXa, a SP for blood coagulation, is upregulated in COVID-19 patients compared to non-COVID-19 donors and exerts anti-viral activity. Mechanistically, FXa cleaves the SARS-CoV-2 spike protein, which prevents its binding to ACE2, and thus blocks viral entry. Furthermore, the variant B.1.1.7 with several mutations is dramatically resistant to the anti-viral effect of FXa compared to wild-type SARA-CoV-2 in vivo and in vitro. The anti-coagulant rivaroxaban directly inhibits FXa and facilitates viral entry, whereas the indirect inhibitor fondaparinux does not. In a lethal humanized hACE2 mouse model of SARS-CoV-2, FXa prolonged survival while combination with rivaroxaban but not fondaparinux abrogated this protection. These preclinical results identify a previously unknown SP function and associated anti-viral host defense mechanism and suggest caution in considering direct inhibitors for prevention or treatment of thrombotic complications in COVID-19 patients.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Nathaniel Loren Miller", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Jianhua Yu", + "author_inst": "Department of Hematology & Hematopoietic Cell Transplantation, City of Hope National Medical Center" }, { - "author_name": "Thomas Clark", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Wenjuan Dong", + "author_inst": "Department of Hematology & Hematopoietic Cell Transplantation, City of Hope National Medical Center" }, { - "author_name": "Rahul Raman", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Jing Wang", + "author_inst": "Department of Hematology & Hematopoietic Cell Transplantation, City of Hope National Medical Center" }, { - "author_name": "Ram Sasisekharan", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Lei Tian", + "author_inst": "Department of Hematology & Hematopoietic Cell Transplantation, City of Hope National Medical Center" + }, + { + "author_name": "Jianying Zhang", + "author_inst": "Department of Computational and Quantitative Medicine, City of Hope National Medical Center" + }, + { + "author_name": "Heather L. Mead", + "author_inst": "Northern Arizona University" + }, + { + "author_name": "Sierra Jaramillo", + "author_inst": "Pathogen and Microbiome Institute, Northern Arizona University" + }, + { + "author_name": "Aimin Li", + "author_inst": "Pathology Core of Shared Resources Core, Beckman Research Institute, City of Hope National Medical Center" + }, + { + "author_name": "Ross Zumwalt", + "author_inst": "Department of Pathology, University of New Mexico" + }, + { + "author_name": "Sean P. J. Whelan", + "author_inst": "Department of Molecular Microbiology, Washington University School of Medicine" + }, + { + "author_name": "Erik Settles", + "author_inst": "Pathogen and Microbiome Institute, Northern Arizona University" + }, + { + "author_name": "Paul Keim", + "author_inst": "Northern Arizona University" + }, + { + "author_name": "Bridget M. Barker", + "author_inst": "Northern Arizona University" + }, + { + "author_name": "Michael Caligiuri", + "author_inst": "Department of Hematology & Hematopoietic Cell Transplantation, City of Hope National Medical Center" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.06.08.447477", @@ -742050,23 +742181,71 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2021.06.07.447287", - "rel_title": "A Web Portal and Workbench for Biological Dissection of Single Cell COVID-19 Host Responses", + "rel_doi": "10.1101/2021.06.05.447177", + "rel_title": "Neutralization against B.1.351 and B.1.617.2 with sera of COVID-19 recovered cases and vaccinees of BBV152", "rel_date": "2021-06-07", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.07.447287", - "rel_abs": "Numerous studies have provided single-cell transcriptome profiles of host responses to SARS-CoV-2 infection. Critically lacking however is a datamine that allows users to compare and explore cell profiles to gain insights and develop new hypotheses. To accomplish this, we harmonized datasets from COVID-19 and other control condition blood, bronchoalveolar lavage, and tissue samples, and derived a compendium of gene signature modules per cell type, subtype, clinical condition, and compartment. We demonstrate approaches to probe these via a new interactive web portal (http://toppcell.cchmc.org/ COVID-19). As examples, we develop three hypotheses: (1) a multicellular signaling cascade among alternatively differentiated monocyte-derived macrophages whose tasks include T cell recruitment and activation; (2) novel platelet subtypes with drastically modulated expression of genes responsible for adhesion, coagulation and thrombosis; and (3) a multilineage cell activator network able to drive extrafollicular B maturation via an ensemble of genes strongly associated with risk for developing post-viral autoimmunity.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.06.05.447177", + "rel_abs": "Recently, multiple SARS-CoV-2 variants have been detected across the globe. The recent emergence of B.1.617 lineage has created serious public health problem in India. The high transmissibility was observed with this lineage which has led to daily increase in the number of SARS-CoV-2 infections. Apparently, the sub-lineage B.1.617.2 has slowly dominated the other variants including B1617.1, B.617.3 and B.1.1.7. With this, World Health Organization has described B.1.617.2 as variant of concern. Besides this, variant of concern B.1.351 has been also reported from India, known to showreducedefficacyfor many approved vaccines. With the increasing threat of the SARS-CoV-2 variants, it is imperative to assess the efficacy of the currently available vaccines against these variants. Here, we have evaluated the neutralization potential of sera collected from COVID-19 recovered cases (n=20) and vaccinees with two doses of BBV152 (n=17) against B.1.351 and B.1.617.2 compared to the prototype B.1 (D614G) variant.The finding of the study demonstrated a reduction in neutralization titers with sera of COVID-19 recovered cases(3.3-fold and 4.6-fold) and BBV152 vaccinees (3. 0 and 2.7 fold) against B.1.351 and B.1.617.2 respectively.Although, there is reduction in neutralization titer, the whole-virion inactivated SARS-CoV-2 vaccine (BBV152) demonstrates protective response against VOC B.1351 and B.1.617.2.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Daniel P Krummel", - "author_inst": "University of Cincinnati" + "author_name": "Pragya D Yadav", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, IndiaPin-411021" + }, + { + "author_name": "Gajanan Sapkal", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, IndiaPin-411021" + }, + { + "author_name": "Raches Ella", + "author_inst": "Bharat Biotech International Limited, Genome Valley, Hyderabad, Telangana, India Pin-500 078" + }, + { + "author_name": "Rima R Sahay", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, IndiaPin-411021" + }, + { + "author_name": "Dimpal A Nyayanit", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, IndiaPin-411021" + }, + { + "author_name": "Deepak Y Patil", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, IndiaPin-411021" + }, + { + "author_name": "Gururaj Deshpande", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, IndiaPin-411021" + }, + { + "author_name": "Anita M Shete", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, IndiaPin-411021" + }, + { + "author_name": "Nivedita Gupta", + "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" + }, + { + "author_name": "V Krishna Mohan", + "author_inst": "Bharat Biotech International Limited, Genome Valley, Hyderabad, Telangana, India Pin-500 078" + }, + { + "author_name": "Priya Abraham", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, IndiaPin-411021" + }, + { + "author_name": "Samiran Panda", + "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" + }, + { + "author_name": "Balram Bhargava", + "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India Pin-110029" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.06.06.446781", @@ -743760,55 +743939,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.06.02.21258257", - "rel_title": "Efficacy of clarithromycin on COVID-19 pneumonia without oxygen administration; protocol for multicenter, open-label, randomized-controlled, 3-armed parallel group comparison, exploratory trial (CAME COVID study)", + "rel_doi": "10.1101/2021.06.02.21258243", + "rel_title": "A Cluster-based Model of COVID-19 Transmission Dynamics", "rel_date": "2021-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.02.21258257", - "rel_abs": "IntroductionThe coronavirus disease 2019 (COVID-19) epidemic has been emerged worldwide. Although several medications have been approved for treating moderate-to-severe COVID-19, no treatment strategy has been established for mild COVID-19 patients who do not require oxygen administration. The spread of SARS -CoV-2 has been mostly through patients with mild COVID-19; therefore, treating patients with mild COVID-19 is critical in society. Clarithromycin is a macrolide antimicrobial agent that has been widely used for bacterial respiratory infectious diseases. Clarithromycin also acts an immunomodulating drug and suppresses cytokine storms in viral respiratory diseases, including influenza infection. In this study, we aimed to evaluate the efficacy of clarithromycin in patients with mild COVID-19.\n\nMethods and analysisThis is a multicenter, open-label, randomized controlled, 3-armed parallel group comparison, exploratory trial. Subjects with mild COVID-19 pneumonia who did not require oxygen administration were enrolled and randomly assigned in a 1:1:1 ratio to Group A (administration of clarithromycin 800 mg/day), Group B (administration of clarithromycin 400 mg/day), or Group C (standard treatment without clarithromycin). The primary endpoint was the number of days required to improve clinical symptoms as measured by the severity score. Secondary endpoints included days to recover the body temperature, proportion of subjects with oxygen administration, inflammatory cytokines, viral load, serum immunoglobulins, peripheral blood lymphocytes, blood biomarkers, and pneumonia infiltrations.\n\nEthics and disseminationThe study protocol was approved by the Clinical Research Review Board of Nagasaki University in accordance with the Clinical Trials Act in Japan. The study will be conducted in accordance with the Declaration of Helsinki, the Clinical Trials Act, and other current legal regulations in Japan. Written informed consent will be obtained from all participants. The results of this study will be reported as journal publications.\n\nRegistrationThis study was registered at the Japan Registry of Clinical Trials (registration number: jRCTs071210011).\n\nStrengths and limitations of this studyO_LIThis is the first randomized controlled trial to evaluate the efficacy of clarithromycin against COVID-19 pneumonia, especially in patients with mild COVID-19 pneumonia who do not require oxygen administration.\nC_LIO_LITo date, no treatment strategy has been established for mild COVID-19 pneumonia.\nC_LIO_LIThe major limitations of this study are its exploratory nature and relatively small sample size.\nC_LIO_LIAnother limitation is the open-label study design and generalizability because this study was conducted only in Japan with Japanese patients.\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.02.21258243", + "rel_abs": "Many countries have manifested COVID-19 trajectories where extended periods of constant and low daily case rate suddenly transition to epidemic waves of considerable severity with no correspondingly drastic relaxation in preventive measures. Such solutions are outside the scope of classical epidemiological models. Here we construct a deterministic, discrete-time, discrete-population mathematical model which can explain these non-classical phenomena. Our key hypothesis is that with partial preventive measures in place, viral transmission occurs primarily within small, closed groups of family members and friends, which we call clusters. Inter-cluster transmission is infrequent compared to intra-cluster transmission but it is the key to determining the course of the epidemic. If inter-cluster transmission is low enough, we see stable plateau solutions. Above a cutoff level however, such transmission can destabilize a plateau into a huge wave even though its contribution to the population-averaged spreading rate still remains small. We call this the cryptogenic instability. We also find that stochastic effects when case counts are very low may result in a temporary and artificial suppression of an instability; we call this the critical mass effect. Both these phenomena are absent from conventional infectious disease models and militate against the successful management of the epidemic.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Kazuko Yamamoto", - "author_inst": "Nagasaki University Hospital" - }, - { - "author_name": "Naoki Hosogaya", - "author_inst": "Nagasaki University Hospital" - }, - { - "author_name": "Noriho Sakamoto", - "author_inst": "Nagasaki University Hospital" - }, - { - "author_name": "Haruo Yoshida", - "author_inst": "Nagasaki University Graduate School of Biomedical Sciences" - }, - { - "author_name": "Hiroshi Ishii", - "author_inst": "Fukuoka University Hospital" - }, - { - "author_name": "Kazuhiro Yatera", - "author_inst": "University of Occupational and Environmental Health" - }, - { - "author_name": "Koichi Izumikawa", - "author_inst": "Nagasaki University Hospital" - }, - { - "author_name": "Katsunori Yanagihara", - "author_inst": "Nagasaki University Hospital" + "author_name": "B Shayak", + "author_inst": "Cornell University" }, { - "author_name": "Hiroshi Mukae", - "author_inst": "Nagasaki University Hospital" + "author_name": "Mohit Manoj Sharma", + "author_inst": "Weill Cornell Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.02.21258211", @@ -745322,31 +745473,43 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2021.06.03.21258240", - "rel_title": "Aggregating probabilistic predictions of the safety, efficacy, and timing of a COVID-19 vaccine", + "rel_doi": "10.1101/2021.06.01.21258187", + "rel_title": "The Impact of COVID-19 Vaccination on California's Return to Normalcy", "rel_date": "2021-06-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.03.21258240", - "rel_abs": "Safe, efficacious vaccines were developed to reduce the transmission of SARS-CoV-2 during the COVID-19 pandemic. But in the middle of 2020, vaccine effectiveness, safety, and the timeline for when a vaccine would be approved and distributed to the public was uncertain. To support public health decision making, we solicited trained forecasters and experts in vaccinology and infectious disease to provide monthly probabilistic predictions from July to September of 2020 of the efficacy, safety, timing, and delivery of a COVID-19 vaccine. We found, that despite sparse historical data, a consensus--a combination of human judgment probabilistic predictions--can quantify the uncertainty in clinical significance and timing of a potential vaccine. The consensus underestimated how fast a therapy would show a survival benefit and the high efficacy of approved COVID-19 vaccines. However, the consensus did make an accurate prediction for when a vaccine would be approved by the FDA. Compared to individual forecasters, the consensus was consistently above the 50th percentile of the most accurate forecasts. A consensus is a fast and versatile method to build probabilistic predictions of a developing vaccine that is robust to poor individual predictions. Though experts and trained forecasters did underestimate the speed of development and the high efficacy of a SARS-CoV-2 vaccine, consensus predictions can improve situational awareness for public health officials and for the public make clearer the risks, rewards, and timing of a vaccine.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.01.21258187", + "rel_abs": "SARS-CoV-2 has infected nearly 3.7 million and killed 61,722 Californians, as of May 22, 2021. Non-pharmaceutical interventions have been instrumental in mitigating the spread of the coronavirus. How- ever, as we ease restrictions, widespread implementation of COVID- 19 vaccines is essential to prevent its resurgence. In this work, we addressed the adequacy and deficiency of vaccine uptake within California and the possibility and severity of resurgence of COVID-19 as restrictions are lifted given the current vaccination rates. We implemented a real-time Bayesian data assimilation approach to provide projections of incident cases and deaths in California following the reopening of its economy on June 15, 2021. We implemented scenarios that vary vaccine uptake prior to reopening, and transmission rates and effective population sizes following the reopening. For comparison purposes, we adopted a baseline scenario using the current vaccination rates, which projects a total 11,429 cases and 429 deaths in a 15-day period after reopening. We used posterior estimates based on CA historical data to provide realistic model parameters after reopening. When the transmission rate is increased after reopening, we projected an increase in cases by 21.8% and deaths by 4.4% above the baseline after reopening. When the effective population is increased after reopening, we observed an increase in cases by 51.8% and deaths by 12.3% above baseline. A 30% reduction in vaccine uptake alone has the potential to increase cases and deaths by 35% and 21.6%, respectively. Conversely, increasing vaccine uptake by 30% could decrease cases and deaths by 26.1% and 17.9%, respectively. As California unfolds its plan to reopen its economy on June 15, 2021, it is critical that social distancing and public behavior changes continue to be promoted, particularly in communities with low vaccine uptake. The Centers of Disease Controls (CDC) recommendation to ease mask- wearing for fully vaccinated individuals despite major inequities in vaccine uptake in counties across the state highlights some of the logistical challenges that society faces as we enthusiastically phase out of this pandemic.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Thomas Charles McAndrew", - "author_inst": "Lehigh University" + "author_name": "Maria L Daza-Torres", + "author_inst": "University of California, Davis" }, { - "author_name": "Juan Cambeiro", - "author_inst": "Metaculus" + "author_name": "Yury Elena Garcia Puerta", + "author_inst": "University of California, Davis" }, { - "author_name": "Tamay Besiroglu", - "author_inst": "Metaculus" + "author_name": "Alec J Schmidt", + "author_inst": "University of California Davis" + }, + { + "author_name": "James L Sharpnack", + "author_inst": "University of California, Davis" + }, + { + "author_name": "Bradley H Pollock", + "author_inst": "University of California, Davis" + }, + { + "author_name": "Miriam A Nuno", + "author_inst": "University of California, Davis" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.06.01.21258176", @@ -747360,35 +747523,75 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.06.01.21258147", - "rel_title": "Minimum manufacturing costs, national prices and estimated global availability of new repurposed therapies for COVID-19.", + "rel_doi": "10.1101/2021.05.30.21258086", + "rel_title": "Virologic features of SARS-CoV-2 infection in children", "rel_date": "2021-06-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.01.21258147", - "rel_abs": "BackgroundCurrently, only dexamethasone, tocilizumab and sarilumab have conclusively been shown to reduce mortality of COVID-19. Safe and effective treatments will need to be both affordable and widely available globally to be used alongside vaccination programmes. This analysis will estimate and compare potential generic minimum costs of a selection of approved COVID-19 drug candidates with available international list prices.\n\nMethodsWe searched for repurposed drugs that have been approved by at least one of the WHO, FDA or NICE, or at least given emergency use authorisation or recommended for off-label prescription. Drug prices were searched for, for dexamethasone, budesonide, baricitinib, tocilizumab, casirivimab and imdevimab, and sarilumab using active pharmaceutical ingredients (API) data extracted from global shipping records. This was compared with national pricing data from a range of low, medium, and high-income countries. Annual API export volumes from India were used to estimate the current availability of each drug.\n\nResultsRepurposed therapies can be generically manufactured for some treatments at very low per-course costs, ranging from $2.58 for IV dexamethasone (or $0.19 orally) and $4.34 for inhaled budesonide. No export price data was available for baricitinib, tocilizumab, casirivimab and imdevimab or sarilumab, but courses of these treatments are priced highly, ranging from $6.67 for baricitinib to $875.5 for sarilumab. When comparing international list prices, we found wide variations between countries.\n\nConclusionsSuccessful management of COVID-19 will require equitable access to treatment for all populations, not just those able to pay high prices. Dexamethasone and budesonide are widely available and affordable, whilst monoclonal antibodies and IV treatment courses are more expensive.\n\nKey PointsO_LIRe-purposed drugs must be affordable worldwide to compliment COVID-19 vaccine programmes.\nC_LIO_LIEstimated costs/course were: dexamethasone (Oral $0.22, IV $2.58), budesonide ($4.34), baricitnib ($6.67), tocilizumab ($410.59), sarilumab ($875.70). Casirivimab and imdevimab = no data available.\nC_LIO_LIHigh drug prices will limit access.\nC_LI", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.30.21258086", + "rel_abs": "BackgroundData on pediatric COVID-19 has lagged behind adults throughout the pandemic. An understanding of SARS-CoV-2 viral dynamics in children would enable data-driven public health guidance.\n\nMethodsRespiratory swabs were collected from children with COVID-19. Viral load was quantified by RT-PCR; viral culture was assessed by direct observation of cytopathic effects and semiquantitative viral titers. Correlations with age, symptom duration, and disease severity were analyzed. SARS-CoV-2 whole genome sequences were compared with contemporaneous sequences.\n\nResults110 children with COVID-19 (median age 10 years, range 2 weeks-21 years) were included in this study. Age did not impact SARS-CoV-2 viral load. Children were most infectious within the first five days of illness, and severe disease did not correlate with increased viral loads. Pediatric SARS-CoV-2 sequences were representative of those in the community and novel variants were identified.\n\nConclusionsSymptomatic and asymptomatic children can carry high quantities of live, replicating SARS-CoV-2, creating a potential reservoir for transmission and evolution of genetic variants. As guidance around social distancing and masking evolves following vaccine uptake in older populations, a clear understanding of SARS-CoV-2 infection dynamics in children is critical for rational development of public health policies and vaccination strategies to mitigate the impact of COVID-19.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Junzheng Wang", - "author_inst": "Imperial College London" + "author_name": "Lael M. Yonker", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Jacob Levi", - "author_inst": "University College London Hospitals NHS Foundation Trust" + "author_name": "Julie Boucau", + "author_inst": "Ragon Institute of MGH, MIT and Harvard" }, { - "author_name": "Leah Ellis", - "author_inst": "Imperial College London" + "author_name": "James Regan", + "author_inst": "Brigham and Women's Hospital" }, { - "author_name": "Andrew Hill", - "author_inst": "University of Liverpool" + "author_name": "Manish Chandra Choudhary", + "author_inst": "Brigham & Women's Hospital" + }, + { + "author_name": "Madeleine D. Burns", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Nicola Young", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Eva J. Farkas", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Jameson P. Davis", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Peter P. Moschovis", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "T. Bernard Kinane", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Alessio Fasano", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Anne M Neilan", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Jonathan Z. M Li", + "author_inst": "Brigham and Women's Hospital, Harvard Medical School" + }, + { + "author_name": "Amy K. Barczak", + "author_inst": "Ragon Institute of MGH, MIT and Harvard" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.06.03.21255116", @@ -749390,81 +749593,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.06.01.21258124", - "rel_title": "Regular testing of asymptomatic healthcare workers identifies cost-efficient SARS-CoV-2 preventive measures", + "rel_doi": "10.1101/2021.05.29.21257950", + "rel_title": "Performance evaluation of virus concentration methods for implementing SARS-CoV-2 Wastewater-based epidemiology emphasizing quick data turnaround.", "rel_date": "2021-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.06.01.21258124", - "rel_abs": "Protecting healthcare professionals is crucial in maintaining a functioning health-care system. The risk of infection and optimal preventive strategies for health-care workers during the COVID-19 pandemic remain poorly understood. Here we report the results of a weekly testing regime that has been performed since the beginning of the COVID-19 pandemic to identify pre- and asymptomatic healthcare workers. Based on these observations we have developed a mathematical model of SARS-CoV-2 transmission that integrates the sources of infection from inside and outside the hospital. The data were used to study how regular testing and a desynchronisation protocol are effective in preventing transmission of COVID-19 infection at work, and compared both strategies in terms of workforce availability and cost-effectiveness. We showed that case incidence among healthcare workers is higher than would be explained solely by community infection. Furthermore, while testing and desynchronisation protocols are both effective in preventing nosocomial transmission, regular testing maintains work productivity with implementation costs.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.29.21257950", + "rel_abs": "Wastewater based epidemiology (WBE) has drawn significant attention as an early warning tool to detect and predict the trajectory of COVID-19 cases in a community, in conjunction with public health data. This means of monitoring for outbreaks has been used at municipal wastewater treatment centers to analyze COVID-19 trends in entire communities, as well as by universities and other community living environments to monitor COVID-19 spread in buildings. Sample concentration is crucial, especially when viral abundance in raw wastewater is below the threshold of detection by RT-qPCR analysis. We evaluated the performance of a rapid ultrafiltration-based virus concentration method using InnovaPrep Concentrating Pipette (CP) Select and compared this to the established electronegative membrane filtration (EMF) method. We evaluated sensitivity of SARS-CoV-2 quantification, surrogate virus recovery rate, and sample processing time. Results suggest that the CP Select concentrator is more efficient at concentrating SARS-CoV-2 from wastewater compared to the EMF method. About 25% of samples that tested negative when concentrated with the EMF method produced a positive signal with the CP Select protocol. Increased recovery of the surrogate virus control using the CP Select confirms this observation. We optimized the CP Select protocol by adding AVL lysis buffer and sonication, to increase the recovery of virus. Sonication increased Bovine Coronavirus (BCoV) recovery by 19%, which seems to compensate for viral loss during centrifugation. Filtration time decreases by approximately 30% when using the CP Select protocol, making this an optimal choice for building surveillance applications where quick turnaround time is necessary.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "DANIEL SANCHEZ-TALTAVULL", - "author_inst": "UNIVERSITY OF BERN" - }, - { - "author_name": "Violeta Castelo-Szekely", - "author_inst": "University of Bern" - }, - { - "author_name": "Shaira Murugan", - "author_inst": "University of Bern" - }, - { - "author_name": "Tim Rollenske", - "author_inst": "University of Bern" - }, - { - "author_name": "Stephanie C. Ganal-Vonarburg", - "author_inst": "University of Bern" - }, - { - "author_name": "Isabel Buchi", - "author_inst": "University of Bern" - }, - { - "author_name": "Adrian Keogh", - "author_inst": "University of Bern" - }, - { - "author_name": "Hai Li", - "author_inst": "University of Bern" - }, - { - "author_name": "Lilian Salm", - "author_inst": "University of Bern" + "author_name": "Md Ariful Islam Juel", + "author_inst": "Department of Civil and Environmental Engineering, University of North Carolina Charlotte" }, { - "author_name": "Daniel Spari", - "author_inst": "University of Bern" + "author_name": "Nicholas Stark", + "author_inst": "Department of Bioinformatics and Genomics, University of North Carolina Charlotte" }, { - "author_name": "Bahtiyar Yilmaz", - "author_inst": "University of Bern" + "author_name": "Bridgette Nicolosi", + "author_inst": "Department of Bioinformatics and Genomics, University of North Carolina Charlotte" }, { - "author_name": "Jakob Zimmermann", - "author_inst": "University of Bern" + "author_name": "Jordan Lontai", + "author_inst": "Department of Bioinformatics and Genomics, University of North Carolina Charlotte" }, { - "author_name": "- UVCM-COVID researchers", - "author_inst": "" + "author_name": "Kevin Lambirth", + "author_inst": "Department of Bioinformatics and Genomics, University of North Carolina Charlotte" }, { - "author_name": "Michael Gerfin", - "author_inst": "University of Bern" + "author_name": "Jessica Schlueter", + "author_inst": "Department of Bioinformatics and Genomics, University of North Carolina Charlotte" }, { - "author_name": "Edgar Roldan", - "author_inst": "ICTP - The Abdus Salam International Centre for Theoretical Physics" + "author_name": "Cynthia Gibas", + "author_inst": "Department of Bioinformatics and Genomics, University of North Carolina at Charlotte" }, { - "author_name": "Guido Beldi", - "author_inst": "University of Bern" + "author_name": "Mariya Munir", + "author_inst": "Department of Civil and Environmental Engineering, University Of North Carolina Charlotte" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -751064,95 +751235,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.31.21255594", - "rel_title": "Signatures of mast cell activation are associated with severe COVID-19", + "rel_doi": "10.1101/2021.05.30.21258040", + "rel_title": "Effect of 2021 Assembly Election in India on Covid-19 Transmission", "rel_date": "2021-06-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.31.21255594", - "rel_abs": "Lung inflammation is a hallmark of Coronavirus disease 2019 (COVID-19) in severely ill patients and the pathophysiology of disease is thought to be immune-mediated. Mast cells (MCs) are polyfunctional immune cells present in the airways, where they respond to certain viruses and allergens, often promoting inflammation. We observed widespread degranulation of MCs during acute and unresolved airway inflammation in SARS-CoV-2-infected mice and non-human primates. In humans, transcriptional changes in patients requiring oxygen supplementation also implicated cells with a MC phenotype. MC activation in humans was confirmed, through detection of the MC-specific protease, chymase, levels of which were significantly correlated with disease severity. These results support the association of MC activation with severe COVID-19, suggesting potential strategies for intervention.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.30.21258040", + "rel_abs": "India is one of the countries in the world which is badly affected by the Covid-19 second wave. Assembly election in four states and a union territory of India was taken place during March-May 2021 when the Covid-19 second wave was close to its peak and affected a huge number of people. We studied the impact of assembly election on the effective contact rate and the effective reproduction number of Covid-19 using different epidemiological models like SIR, SIRD, and SEIR. We also modeled the effective reproduction number for all election-bound states using different mathematical functions. We separately studied the case of all election-bound states and found all the states shown a distinct increase in the effective contact rate and the effective reproduction number during the election-bound time and just after that compared to pre-election time. States, where elections were conducted in single-phase, showed less increase in the effective contact rate and the reproduction number. The election commission imposed extra measures from the first week of April 2021 to restrict big campaign rallies, meetings, and different political activities. The effective contact rate and the reproduction number showed a trend to decrease for few states due to the imposition of the restrictions. We also compared the effective contact rate, and the effective reproduction number of all election-bound states and the rest of India and found all the parameters related to the spread of virus for election-bound states are distinctly high compared to the rest of India.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Janessa Tan", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Danielle Anderson", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Abhay P.S. Rathore", - "author_inst": "Duke University" - }, - { - "author_name": "Aled O'Neill", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Chinmay Kumar Mantri", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Wilfried A.A. Saron", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Cheryl Lee", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Wern Chui Chu", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Adrian Kang", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Randy Foo", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Shirin Kalimuddin", - "author_inst": "Singapore General Hospital" - }, - { - "author_name": "Jenny Low", - "author_inst": "Singapore General Hospital" - }, - { - "author_name": "Lena Ho", - "author_inst": "Duke-NUS Medical School" - }, - { - "author_name": "Paul Tambyah", - "author_inst": "National University of Singapore" - }, - { - "author_name": "Thomas W. Burke", - "author_inst": "Duke University" - }, - { - "author_name": "Christopher W. Woods", - "author_inst": "Duke University School of Medicine" + "author_name": "Souvik Manik", + "author_inst": "Midnapore City College" }, { - "author_name": "Kuan Rong Chan", - "author_inst": "Duke-NUS Medical School" + "author_name": "Sabyasachi Pal", + "author_inst": "Midnapore City College" }, { - "author_name": "Joern Karhausen", - "author_inst": "Duke University" + "author_name": "Manoj Mandal", + "author_inst": "Midnapore City College" }, { - "author_name": "Ashley L. St John", - "author_inst": "Duke-NUS Medical School" + "author_name": "Mangal Hazra", + "author_inst": "Midnapore City College" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.05.31.21258118", @@ -752510,75 +752621,87 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.05.31.446421", - "rel_title": "Accelerated Antibody Discovery Targeting the SARS-CoV-2 Spike Protein for COVID-19 Therapeutic Potential", + "rel_doi": "10.1101/2021.05.31.446386", + "rel_title": "Spike mutation T403R allows bat coronavirus RaTG13 to use human ACE2", "rel_date": "2021-05-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.31.446421", - "rel_abs": "Rapid deployment of technologies capable of high-throughput and high-resolution screening is imperative for timely response to viral outbreaks. Risk mitigation in the form of leveraging multiple advanced technologies further increases the likelihood of identifying efficacious treatments in an aggressive timeline. In this study, we describe two parallel, yet distinct, in vivo approaches for accelerated discovery of antibodies targeting the SARS-CoV-2 spike protein. Working with human transgenic Alloy-GK mice, we detail a single B-cell discovery workflow to directly interrogate antibodies secreted from plasma cells for binding specificity and ACE2 receptor blocking activity. Additionally, we describe a concurrent accelerated hybridoma-based workflow utilizing a DiversimAb mouse model for increased diversity. The panel of antibodies isolated from both workflows revealed binding to distinct epitopes with both blocking and non-blocking profiles. Sequence analysis of the resulting lead candidates uncovered additional diversity with the opportunity for straightforward engineering and affinity maturation. By combining in vivo models with advanced integration of screening and selection platforms, lead antibody candidates can be sequenced and fully characterized within one to three months.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.31.446386", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the COVID-19 pandemic, most likely emerged from bats1. A prerequisite for this devastating zoonosis was the ability of the SARS-CoV-2 Spike (S) glycoprotein to use human angiotensin-converting enzyme 2 (ACE2) for viral entry. Although the S protein of the closest related bat virus, RaTG13, shows high similarity to the SARS-CoV-2 S protein it does not efficiently interact with the human ACE2 receptor2. Here, we show that a single T403R mutation allows the RaTG13 S to utilize the human ACE2 receptor for infection of human cells and intestinal organoids. Conversely, mutation of R403T in the SARS-CoV-2 S significantly reduced ACE2-mediated virus infection. The S protein of SARS-CoV-1 that also uses human ACE2 also contains a positive residue (K) at this position, while the S proteins of CoVs utilizing other receptors vary at this location. Our results indicate that the presence of a positively charged amino acid at position 403 in the S protein is critical for efficient utilization of human ACE2. This finding could help to predict the zoonotic potential of animal coronaviruses.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Tracey E Mullen", - "author_inst": "Abveris Inc." + "author_name": "Fabian Zech", + "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" + }, + { + "author_name": "Daniel Schniertshauer", + "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" }, { - "author_name": "Rashed Abdullah", - "author_inst": "Abveris Inc." + "author_name": "Christoph Jung", + "author_inst": "Institute of Electrochemistry, Ulm University, 89081 Ulm, Germany" }, { - "author_name": "Jacqueline Boucher", - "author_inst": "Abveris Inc." + "author_name": "Alexandra Herrmann", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universitaet Erlangen-Nuernberg, 91054 Erlangen, Germany." }, { - "author_name": "Anna Susi Brousseau", - "author_inst": "Abveris Inc." + "author_name": "Qinya Xie", + "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" }, { - "author_name": "Narayan K Dasuri", - "author_inst": "Abveris Inc." + "author_name": "Rayhane Nchioua", + "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" }, { - "author_name": "Noah T Ditto", - "author_inst": "Carterra" + "author_name": "Caterina Prelli Bozzo", + "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" }, { - "author_name": "Andrew M Doucette", - "author_inst": "Abveris Inc." + "author_name": "Meta Volcic", + "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" }, { - "author_name": "Chloe Emery", - "author_inst": "Abveris Inc." + "author_name": "Lennart Koepke", + "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" }, { - "author_name": "Justin Gabriel", - "author_inst": "Abveris Inc." + "author_name": "Jana Krueger", + "author_inst": "Department of Internal Medicine I, Ulm University Medical Center, 89081 Ulm, Germany" }, { - "author_name": "Brendan Greamo", - "author_inst": "Abveris Inc." + "author_name": "Sandra Heller", + "author_inst": "Department of Internal Medicine I, Ulm University Medical Center, 89081 Ulm, Germany" + }, + { + "author_name": "Alexander Kleger", + "author_inst": "Department of Internal Medicine I, Ulm University Medical Center, 89081 Ulm, Germany" + }, + { + "author_name": "Timo Jacob", + "author_inst": "Institute of Electrochemistry, Ulm University, 89081 Ulm, Germany" }, { - "author_name": "Ketan S Patil", - "author_inst": "Abveris Inc." + "author_name": "Karl-Klaus Conzelmann", + "author_inst": "Max von Pettenkofer-Institute of Virology, Medical Faculty, and Gene Center, Ludwig-Maximilians-Universitaet Muenchen, 81377 Munich, Germany" }, { - "author_name": "Kelly Rothenberger", - "author_inst": "Abveris Inc." + "author_name": "Armin Ensser", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander Universitaet Erlangen-Nuernberg, 91054 Erlangen, Germany." }, { - "author_name": "Justin Stolte", - "author_inst": "Abveris Inc." + "author_name": "Konstantin Maria Johannes Sparrer", + "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" }, { - "author_name": "Colby A Souders", - "author_inst": "Abveris Inc." + "author_name": "Frank Kirchhoff", + "author_inst": "Institute of Molecular Virology, Ulm University Medical Center, 89081 Ulm, Germany" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.05.31.446374", @@ -754107,103 +754230,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.26.21257834", - "rel_title": "Development and external validation of a diagnostic multivariable prediction model for a prompt identification of cases at high risk for SARS-COV-2 infection among patients admitted to the emergency department", + "rel_doi": "10.1101/2021.05.26.21257835", + "rel_title": "Inferring SARS-CoV-2 variant within-host kinetics", "rel_date": "2021-05-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.26.21257834", - "rel_abs": "BackgroundAn urgent need exists for an early detection of cases with a high-risk of SARS-CoV-2 infection, particularly in high-flow and -risk settings, such as emergency departments (EDs). The aim of this work is to develop and validate a predictive model for the evaluation of SARS-CoV-2 infection risk, with the rationale of using this tool to manage ED patients.\n\nMethodsA retrospective study was performed by cross-sectionally reviewing the electronical case records of patients admitted to Niguarda Hospital or referred to its ED in the period 15 March to 24 April 2020.\n\nDerivation sample was composed of non-random inpatients hospitalized on 24 April and admitted before 22 April 2020. Validation sample was composed of consecutive patients who visited the ED between 15 and 25 March 2020. The association between the dichotomic outcome and each predictor was explored by univariate analysis with logistic regression models.\n\nResultsA total of 113 patients in the derivation sample and 419 in the validation sample were analyzed. History of fever, elder age and low oxygen saturation showed to be significant predictors of SARS-CoV-2 infection. The neutrophil count improves the discriminative ability of the model, even if its calibration and usefulness in terms of diagnosis is unclear.\n\nConclusionThe discriminatory ability of the identified models makes the overall performance suboptimal; their implementation to calculate the individual risk of infection should not be used without additional investigations. However, they could be useful to evaluate the spatial allocation of patients while awaiting the result of the nasopharyngeal swab.\n\nKey Messages boxO_ST_ABSWhat is already known on this topicC_ST_ABS1 year after the onset of the coronavirus disease 2019 (COVID-19) pandemic, the trend of its spread has not shown a substantial global reduction. An urgent need exists for efficient early detection of cases with a high risk of SARS-CoV-2 infection and a number of diagnostic prediction models have been developed, but a few models were externally validated in high-flow and -risk settings, such as emergency departments (EDs).\n\nWhat this study addsThis study develops and validate predictive models for the evaluation of SARS-CoV-2 infection risk, with the rationale of using these tools to promptly manage patients who are afferent to the ED, allocating them accordingly to the risk of infection while awaiting swab result. History of fever, older age and low oxygen saturation showed to be significant predictors of the presence of SARS-CoV-2 infection. The use of laboratory findings, such as neutrophil count, showed to improve the discriminative ability of the model, even if its calibration and usefulness in terms of diagnosis is unclear.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.26.21257835", + "rel_abs": "Since early 2021, SARS-CoV-2 variants of concern (VOCs) have been causing epidemic rebounds in many countries. Their properties are well characterised at the epidemiological level but the potential underlying within-host determinants remain poorly understood. We analyse a longitudinal cohort of 6,944 individuals with 14,304 cycle threshold (Ct) values of qPCR VOC screening tests performed in the general population and hospitals in France between February 6 and August 21, 2021. To convert Ct values into numbers of virus copies, we performed an additional analysis using droplet digital PCR (ddPCR). We find that the number of viral genome copies reaches a higher peak value and has a slower decay rate in infections caused by Alpha variant compared to that caused by historical lineages. Following the evidence that viral genome copies in upper respiratory tract swabs are informative on contagiousness, we show that the kinetics of the Alpha variant translate into significantly higher transmission potentials, especially in older populations. Finally, comparing infections caused by the Alpha and Delta variants, we find no significant difference in the peak viral copy number. These results highlight that some of the differences between variants may be detected in virus load variations.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Nicola Ughi", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Antonella ADINOLFI", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Michel CHEVALLARD", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Laura BELLOLI", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Michele SENATORE", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Alessandro TOSCANO", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Andrea BELLONE", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Cristina GIANNATTASIO", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Paolo TARSIA", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Massimo Puoti", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Francesco SCAGLIONE", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Fabrizio COLOMBO", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Michaela BERTUZZI", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" - }, - { - "author_name": "Giuseppe BETTONI", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" + "author_name": "Baptiste Elie", + "author_inst": "MIVEGEC, CNRS, IRD, Universite de Montpellier, Montpellier, France" }, { - "author_name": "Davide FERRAZZI", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" + "author_name": "Benedicte Roquebert", + "author_inst": "Cerba Laboratory, Saint Ouen L Aumone, France" }, { - "author_name": "Alessandro MALOBERTI", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" + "author_name": "Mircea T. Sofonea", + "author_inst": "MIVEGEC, CNRS, IRD, Universite de Montpellier, Montpellier, France" }, { - "author_name": "Armanda DICUONZO", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" + "author_name": "Sabine Trombert", + "author_inst": "Cerba Laboratory, Saint Ouen L Aumone, France" }, { - "author_name": "Francesca DEL GAUDIO", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" + "author_name": "Vincent Foulogne", + "author_inst": "Laboratoire de Virologie, CHU de Montpellier, France" }, { - "author_name": "Claudio ROSSETTI", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" + "author_name": "Jeremie Guedj", + "author_inst": "Universite de Paris, INSERM, IAME, F-75018 Paris, France" }, { - "author_name": "Oscar Massimiliano EPIS", - "author_inst": "ASST Grande Ospedale Metropolitano Niguarda" + "author_name": "Stephanie Haim-Boukobza", + "author_inst": "Cerba Laboratory, Saint Ouen L Aumone, France" }, { - "author_name": "- Niguarda COVID group", - "author_inst": "" + "author_name": "Samuel Alizon", + "author_inst": "MIVEGEC, CNRS, IRD, Universite de Montpellier, Montpellier, France" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.05.28.21257774", @@ -755788,49 +755859,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.28.21258006", - "rel_title": "Fear, Anxiety, Stress, and Depression of novel coronavirus (COVID-19) pandemic among patients and their healthcare workers", + "rel_doi": "10.1101/2021.05.28.21257954", + "rel_title": "Age- and gender-dependent differences in attitudes towards COVID-19 vaccination and underlying psychological processes", "rel_date": "2021-05-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.28.21258006", - "rel_abs": "BackgroundDisease pandemics are known to cause psychological distress. The ensuing mental health issues are not only restricted to the patients and their relatives/friends but affect the healthcare workers (HCWs) as well. Our study aims to assess these psychological trends during the COVID-19 pandemic between the two most affected population groups, that is, patients and frontline healthcare workers.\n\nMethodsA survey questionnaire including scales to assess fear, anxiety, stress, depression - PSS 10, and DASS 21 was distributed and sent to all COVID-19 suspected/confirmed individuals and healthcare workers at a tertiary care center along with a second visit after 14 days of answering the first questionnaire and this continued as follow up. Data were analyzed with the SPSS Version 23 using various tests of significance.\n\nResultsIn the community, COVID-19 patients in the age group 41-50 with respiratory tract symptoms and those who were home isolated/quarantined experienced a greater tendency of mental health problems. Healthcare workers posted in COVID-19 designated areas of the hospital displayed higher levels of stress, anxiety, and depression.\n\nConclusionThe high degree of uncertainty associated with novel pathogens has a profound effect on the psychological state of suspected/confirmed cases as well as healthcare workers. Within the community, individuals suspected of having COVID-19 display a significant mental health burden, while HCWs also experience an unprecedented amount of stress during such enduring situations.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSWhat is the psychological impact among patients and their healthcare workers during the COVID-19 pandemic?\n\nFindingsIn this observational study based on PSS 10 and DASS 21 questionnaire that included 156 patients and 226 health care workers, the patients in the age group 41-50 with respiratory tract symptoms and those who were home isolated/quarantined experienced a greater tendency of mental health problems. Similar burden was observed among health care workers.\n\nMeaningIn a COVID-19 pandemic both population groups displayed higher levels of fear, anxiety, stress, and depression.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.28.21257954", + "rel_abs": "The most promising way to prevent the explosive spread of COVID-19 infection is to achieve herd immunity through vaccination. It is therefore important to motivate those who are less willing to be vaccinated. To address this issue, we conducted an online survey of 6232 Japanese people to investigate age- and gender-dependent differences in attitudes towards COVID-19 vaccination and the underlying psychological processes. We asked participants to read one of nine different messages about COVID-19 vaccination and rate their willingness to be vaccinated. We also collected their 17 social personality trait scores and demographic information. We found that males 10-20 years old showed the minimum willingness to be vaccinated. We also found that prosocial traits are the driving force for young people, but the motivation in older people also depends on risk aversion and self-interest. Furthermore, an analysis of 9 different messages demonstrated that for young people (particularly males), the message emphasizing the majoritys intention to vaccinate and scientific evidence for the safety of the vaccination had the strongest positive effect on the willingness to be vaccinated, suggesting that the herding effect arising from the \"majority + scientific evidence\" message nudges young people to show their prosocial nature in action.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ashwin Parchani", - "author_inst": "AIIMS Rishikesh" - }, - { - "author_name": "K Vidhya", - "author_inst": "AIIMS Rishikesh" - }, - { - "author_name": "Prasan Kumar Panda", - "author_inst": "AIIMS Rishikesh" - }, - { - "author_name": "Vikram Singh Rawat", - "author_inst": "AIIMS Rishikesh" - }, - { - "author_name": "Yogesh Arvind Bahurupi", - "author_inst": "AIIMS Rishikesh" + "author_name": "Toshiko Tanaka", + "author_inst": "National Institute of Information and Communications Technology" }, { - "author_name": "Deepjyoti Kalita", - "author_inst": "AIIMS Rishikesh" + "author_name": "Tsuyoshi Nihonsugi", + "author_inst": "Osaka University of Economics" }, { - "author_name": "Harsh Kumar", - "author_inst": "AIIMS Rishikesh" + "author_name": "Fumio Ohtake", + "author_inst": "Osaka University" }, { - "author_name": "Naveen Dr", - "author_inst": "AIIMS Rishikesh" + "author_name": "Masahiko Haruno", + "author_inst": "National Institute of Information and Communications Technology" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -757750,93 +757805,137 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.24.21257703", - "rel_title": "COVID-19 mass testing: harnessing the power of wastewater epidemiology", + "rel_doi": "10.1101/2021.05.24.21257738", + "rel_title": "Post-vaccination SARS-CoV-2 infection: risk factors and illness profile in a prospective, observational community-based case-control study", "rel_date": "2021-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.24.21257703", - "rel_abs": "BackgroundCOVID-19 patients shed SARS-CoV-2 RNA in their faeces. We hypothesised that detection of SARS-CoV-2 RNA in wastewater treatment plant (WWTP) influent could be a valuable tool to assist in public health decision making. We aimed to rapidly develop and validate a scalable methodology for the detection of SARS-CoV-2 RNA in wastewater that could be implemented at a national level and to determine the relationship between the wastewater signal and COVID-19 cases in the community.\n\nMethodsWe developed a filtration-based methodology for the concentration of SARS-CoV-2 from WWTP influent and subsequent detection and quantification by RT-qPCR. This methodology was used to monitor 28 WWTPs across Scotland, serving 50% of the population. For each WWTP catchment area, we collected data describing COVID-19 cases and deaths. We quantified spatial and temporal relationships between SARS-CoV-2 RNA in wastewater and COVID-19 cases.\n\nFindingsDaily WWTP SARS-CoV-2 influent viral RNA load, calculated using daily influent flow rates, had the strongest correlation ({rho}>0.9) with COVID-19 cases within a catchment. As the incidence of COVID-19 cases within a community increased, a linear relationship emerged between cases and influent viral RNA load. There were significant differences between WWTPs in their capacity to predict case numbers based on influent viral RNA load, with the limit of detection ranging from twenty-five cases for larger plants to a single case in smaller plants.\n\nInterpretationThe levels of SARS-CoV-2 RNA in WWTP influent provide a cost-effective and unbiased measure of COVID-19 incidence within a community, indicating that national scale wastewater-based epidemiology can play a role in COVID-19 surveillance. In Scotland, wastewater testing has been expanded to cover 75% of the population, with sub-catchment sampling being used to focus surge testing. SARS-CoV-2 variant detection, assessment of vaccination on community transmission and surveillance for other infectious diseases represent promising future applications.\n\nFundingThis study was funded by project grants from the Scottish Government via the Centre of Expertise for Waters (CD2019/06) and The Natural Environment Research Councils COVID-19 Rapid Response grants (NE/V010441/1). The Roslin Institute receives strategic funding from the Biotechnology and Biological Sciences Research Council (BB/P013740/1, BBS/E/D/20002173). Sample collection and supplementary analysis was funded and undertaken by Scottish Water and the majority of the sample analysis was funded and undertaken by the Scottish Environment Protection Agency.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.24.21257738", + "rel_abs": "BackgroundCOVID-19 vaccines show excellent efficacy in clinical trials and real-world data, but some people still contract SARS-CoV-2 despite vaccination. This study sought to identify risk factors associated with SARS-CoV-2 infection post-vaccination and describe characteristics of post-vaccination illness.\n\nMethodsAmongst 1,102,192 vaccinated UK adults from the COVID Symptom Study, 2394 (0.2%) cases of post-vaccination SARS-CoV-2 infection were identified between 8th December 2020 and 1st May 2021. Using a control group of vaccinated individuals testing negative, we assessed the associations of age, frailty, comorbidity, area-level deprivation and lifestyle factors with infection. Illness profile post-vaccination was assessed using a second control group of unvaccinated cases.\n\nFindingsOlder adults with frailty (OR=2.78, 95% CI=[1.98-3.89], p-value<0.0001) and individuals living in most deprived areas (OR=1.22 vs. intermediate group, CI[1.04-1.43], p-value=0.01) had increased odds of post-vaccination infection. Risk was lower in individuals without obesity (OR=0.6, CI[0.44-0.82], p-value=0.001) and those reporting healthier diet (OR=0.73, CI[0.62-0.86], p-value<0.0001). Vaccination was associated with reduced odds of hospitalisation (OR=0.36, CI[0.28-0.46], p-value<0.0001), and high acute-symptom burden (OR=0.51, CI[0.42-0.61], p-value<0.0001). In older adults, risk of [≥]28 days illness was lower following vaccination (OR=0.72, CI[0.51-1.00], p-value=0.05). Symptoms were reported less in positive-vaccinated vs. positive-unvaccinated individuals, except sneezing, which was more common post-vaccination (OR=1.24, CI[1.05-1.46], p-value=0.01).\n\nInterpretationOur findings suggest that older individuals with frailty and those living in most deprived areas are at increased risk of infection post-vaccination. We also showed reduced symptom burden and duration in those infected post-vaccination. Efforts to boost vaccine effectiveness in at-risk populations, and to targeted infection control measures, may still be appropriate to minimise SARS-CoV-2 infection.\n\nFundingThis work is supported by UK Department of Health via the National Institute for Health Research (NIHR) comprehensive Biomedical Research Centre (BRC) award to Guys & St Thomas NHS Foundation Trust in partnership with Kings College London and Kings College Hospital NHS Foundation Trust and via a grant to ZOE Global; the Wellcome Engineering and Physical Sciences Research Council (EPSRC) Centre for Medical Engineering at Kings College London (WT 203148/Z/16/Z). Investigators also received support from the Chronic Disease Research Foundation, the Medical Research Council (MRC), British Heart Foundation, the UK Research and Innovation London Medical Imaging & Artificial Intelligence Centre for Value Based Healthcare, the Wellcome Flagship Programme (WT213038/Z/18/Z and Alzheimers Society (AS-JF-17-011), and the Massachusetts Consortium on Pathogen Readiness (MassCPR).\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSTo identify existing evidence for risk factors and characteristics of SARS-CoV-2 infection post-vaccination, we searched PubMed for peer-reviewed articles published between December 1, 2020 and May 18, 2021 using keywords (\"COVID-19\" OR \"SARS-CoV-2\") AND (\"Vaccine\" OR \"vaccination\") AND (\"infection\") AND (\"risk factor*\" OR \"characteristic*\"). We did not restrict our search by language or type of publication. Of 202 articles identified, we found no original studies on individual risk and protective factors for COVID-19 infection following vaccination nor on nature and duration of symptoms in vaccinated, community-based individuals. Previous studies in unvaccinated populations have shown that social and occupational factors influence risk of SARS-CoV-2infection, and that personal factors (age, male sex, multiple morbidities and frailty) increased risk for adverse outcomes in COVID-19. Phase III clinical trials have demonstrated good efficacy of BNT162b2 and ChAdOx1 vaccines against SARS-CoV-2 infection, confirmed in published real-world data, which additionally showed reduced risk of adverse outcomes including hospitalisation and death.\n\nAdded value of this studyThis is the first observational study investigating characteristics of and factors associated with SARS-CoV-2 infection after COVID-19 vaccination. We found that vaccinated individuals with frailty had higher rates of infection after vaccination than those without. Adverse determinants of health such as increased social deprivation, obesity, or a less healthy diet were associated with higher likelihood of infection after vaccination. In comparison with unvaccinated individuals, those with post-vaccination infection had fewer symptoms of COVID-19, and more were entirely asymptomatic. Fewer vaccinated individuals experienced five or more symptoms, required hospitalisation, and, in the older adult group, fewer had prolonged illness duration (symptoms lasting longer than 28 days).\n\nImplications of all the available evidenceSome individuals still contract COVID-19 after vaccination and our data suggest that frail older adults and those living in more deprived areas are at higher risk. However, in most individuals illness appears less severe, with reduced need for hospitalisation and lower risk of prolonged illness duration. Our results are relevant for health policy post-vaccination and highlight the need to prioritise those most at risk, whilst also emphasising the balance between the importance of personal protective measures versus adverse effects from ongoing social restrictions. Strategies such as timely prioritisation of booster vaccination and optimised infection control could be considered for at-risk groups. Research is also needed on how to enhance the immune response to vaccination in those at higher risk.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Stephen F Fitzgerald", - "author_inst": "The Roslin Institute, UNiversity of Edinburgh" + "author_name": "Michela Antonelli", + "author_inst": "King's College London" }, { - "author_name": "Gianluigi Rossi", - "author_inst": "The Roslin Institute, University of Edinburgh" + "author_name": "Rose S Penfold", + "author_inst": "King's College London" }, { - "author_name": "Alison S Low", - "author_inst": "The Roslin Institute, University of Edinburgh" + "author_name": "Jordi Merino", + "author_inst": "Department of Medicine, Harvard Medical School, Boston, MA, USA" }, { - "author_name": "Sean P MacAteer", - "author_inst": "The Roslin, Institute, University of Edinburgh" + "author_name": "Carole H Sudre", + "author_inst": "Centre for Medical Image Computing, University College London, London, UK" }, { - "author_name": "Brian O'Keefe", - "author_inst": "Scottish Environment Protection Agency" + "author_name": "Erika Molteni", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" }, { - "author_name": "David Findlay", - "author_inst": "Scottish Environment Protection Agency" + "author_name": "Sarah Berry", + "author_inst": "Department of Twin Research and Genetic Epidemiology, King's College London, UK" }, { - "author_name": "Greame J Cameron", - "author_inst": "Scottish Environment Protection Agency" + "author_name": "Liane S Canas", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" }, { - "author_name": "Peter Pollard", - "author_inst": "Scottish Environment Protection Agency" + "author_name": "Mark S Graham", + "author_inst": "King's College London" }, { - "author_name": "Peter T. R. Singleton", - "author_inst": "Scottish Environment Protection Agency" + "author_name": "Kerstin Klaser", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" }, { - "author_name": "George Ponton", - "author_inst": "Scottish Water" + "author_name": "Marc Modat", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" }, { - "author_name": "Andrew C Singer", - "author_inst": "UK Centre for Ecology & Hydrology" + "author_name": "Benjamin Murray", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" }, { - "author_name": "Kata Farkas", - "author_inst": "School of Natural Sciences, Bangor University" + "author_name": "Eric Kerfoot", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" }, { - "author_name": "David L Jones", - "author_inst": "School of Natural Sciences, Bangor University" + "author_name": "Liyuan Chen", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" }, { - "author_name": "Davd W. Graham", - "author_inst": "School of Engineering, Newcastle University" + "author_name": "Jie Deng", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" }, { - "author_name": "Marcos Quintela-Baluja", - "author_inst": "School of Engineering, Newcastle University" + "author_name": "Marc F \u00d6sterdahl", + "author_inst": "Department of Twin Research and Genetic Epidemiology, King's College London, UK" }, { - "author_name": "Christine Tait-Burkard", - "author_inst": "The Roslin, Institute, University of Edinburgh" + "author_name": "Nathan J Cheetham", + "author_inst": "Department of Twin Research and Genetic Epidemiology, King's College London, UK" }, { - "author_name": "David L Gally", - "author_inst": "The Roslin, Institute, University of Edinburgh" + "author_name": "David Alden Drew", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Rowland Raymond Kao", - "author_inst": "The Roslin, Institute, University of Edinburgh" + "author_name": "Long Alden Nguyen", + "author_inst": "Massachusetts General Hospital and Harvard Medical School" }, { - "author_name": "Alexander Corbishley", - "author_inst": "The Roslin, Institute, University of Edinburgh" + "author_name": "Joan Capdeila", + "author_inst": "Zoe Global, London, UK" + }, + { + "author_name": "Christina Hu", + "author_inst": "Zoe Global, London, UK" + }, + { + "author_name": "Somesh Selvachandran", + "author_inst": "Zoe Global, London, UK" + }, + { + "author_name": "Lorenzo Polidori", + "author_inst": "Lorenzo Polidori" + }, + { + "author_name": "Anna May", + "author_inst": "Zoe Global, London, UK" + }, + { + "author_name": "Jonathan Wolf", + "author_inst": "Zoe Global, London, UK" + }, + { + "author_name": "Andrew T Chan", + "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA" + }, + { + "author_name": "Alexander Hammers", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" + }, + { + "author_name": "Emma Duncan", + "author_inst": "Department of Twin Research and Genetic Epidemiology, King's College London, UK" + }, + { + "author_name": "Timothy Spector", + "author_inst": "King's College London" + }, + { + "author_name": "Sebastien Ourselin", + "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, UK" + }, + { + "author_name": "Claire J Steves", + "author_inst": "Department of Twin Research and Genetic Epidemiology, King's College London, UK" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -759468,39 +759567,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.21.21257631", - "rel_title": "Detecting COVID-19 Related Pneumonia on CT Scans using Hyperdimensional Computing", + "rel_doi": "10.1101/2021.05.23.21257692", + "rel_title": "COVID-19 gender difference pattern in Iranian population, compared to the global pattern; a systematic review and meta-analysis", "rel_date": "2021-05-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.21.21257631", - "rel_abs": "Pneumonia is a common complication associated with COVID-19 infections. Unlike common versions of pneumonia spread quickly through large lung regions, COVID-19 related pneumonia starts in small localized pockets before spreading over the course of several days. This makes the infection more resilient and with a high probability of developing acute respiratory distress syndrome. Because of the peculiar spread pattern, the use of pulmonary computerized tomography (CT) scans was key in identifying COVID-19 infections. Identifying uncommon pulmonary diseases could be a strong line of defense in early detection of new respiratory infection-causing viruses. In this paper we describe a classification algorithm based on hyperdimensional computing for the detection of COVID-19 pneumonia in CT scans. We test our algorithm using three different datasets. The highest reported accuracy is 95.2% with an F1 score of 0.90, and all three models had a precision of 1 (0 false positives).", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.23.21257692", + "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic has highlighted Sex-related immune responses. In this review, gender differences in seroprevalence, severity, mortality, and recovery in the Iranian population were systematically compared to the COVID-19 global pattern. This compressive meta-analysis was conducted on studies published up to April 1, 2021, examining seroprevalence in the general population as well as disease outcomes in hospitalized patients. Data were analyzed based on gender to determine differences between men and women in COVID-19. The PubMed, Scopus, Google Scholar, WOS, medRxiv, and bioRxiv were searched. The odds ratio (OR) was calculated based on the random-effects model, with a corresponding 95% confidence interval (CI), according to the number of participants reported in papers. Subgroup analyses were performed according to the age, antibody isotype, and detection assay. Overall, 61 studies with 225799 males and 237017 females were eligible for meta-analysis. Seroprevalence was 1.13 times higher (95% CI: 1.03, 1.24), mortality was 1.45 times higher (95% CI: 1.19, 1.77), and severity was up to 1.37 times higher (95% CI: 1.13, 1.67) in males than those of females in the general population across the globe. Mortality was higher in Iranian patients up to 26% in men (95% CI: 1.20, 1.33), but no significant difference was observed between disease severity and serum prevalence between men and women. Besides, the rate of recovery was 29% (global pattern) and 21% (Iran pattern) lower in males than in females. The results of subgroup analyses for seroprevalence were not significant for the age, antibody isotype, and detection methods. The results of our meta-analyses showed that the patient mortality and recovery patterns are similar in Iran and other countries in the context of gender differences, and the disease is more fatal in men.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Neftali D Watkinson", - "author_inst": "University of California, Irvine" - }, - { - "author_name": "Victor Joe", - "author_inst": "UCI Medical Center" + "author_name": "misagh rajabinejad", + "author_inst": "Mazandaran University of Medical Science" }, { - "author_name": "Tony Givargis", - "author_inst": "University of California, Irvine" - }, - { - "author_name": "Alexandru Nicolau", - "author_inst": "University of California, Irvine" - }, - { - "author_name": "Alexander Veidenbaum", - "author_inst": "University of California, Irvine" + "author_name": "Hossein Asgarian-Omran", + "author_inst": "Mazandaran University of Medical Science" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.23.21257673", @@ -761350,47 +761437,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.22.21257649", - "rel_title": "The COVID in the Context of Pregnancy, Infancy and Parenting (CoCoPIP) Study: protocol for a longitudinal study of parental mental health, social interactions, physical growth, and cognitive development of infants during the pandemic.", + "rel_doi": "10.1101/2021.05.23.445371", + "rel_title": "Unsupervised explainable AI for the collective analysis of a massive number of genome sequences: various examples from the small genome of pandemic SARS-CoV-2 to the human genome", "rel_date": "2021-05-24", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.22.21257649", - "rel_abs": "IntroductionWhile the secondary impact of the COVID pandemic on the psychological wellbeing of pregnant women and parents has become apparent over the past year, the impact of these changes on early social interactions, physical growth and cognitive development of their infants is unknown, as is the way in which a range of COVID related changes have mediated this impact. This study (CoCoPIP) will investigate: i) how parents experiences of the social, medical, and financial changes during the pandemic have impacted pre and postnatal parental mental health and parent-infant social interaction; and (ii) the extent to which these COVID-related changes in parental pre and postnatal mental health and social interaction are associated with fetal and infant development.\n\nMethods and analysisThe CoCoPIP study is a national online survey initiated in July 2020. This ongoing study (n = 1700 families currently enrolled as of 6th May 2021) involves both quantitative and qualitative data being collected across pregnancy and infancy. It is designed to identify the longitudinal impact of the pandemic from pregnancy to two years of age, with the aim of identifying if stress-associated moderators (i.e., loss of income, COVID-19 illness, access to ante/postnatal support) impact parental mental health, and in turn, infant development. In addition, we aim to document individual differences in social and cognitive development in toddlers who were born during restrictions intended to mitigate COVID-19 spread (e.g., social distancing, national lockdowns).\n\nEthics and disseminationEthical approval was given by the University of Cambridge, Psychology Research Ethics Committee (PREC) (PRE.2020.077). Findings will be made available via community engagement, public forums (e.g., social media,) and to national (e.g., NHS England) and local (Cambridge Universities Hospitals NHS Foundation Trust) healthcare partners. Results will be submitted for publication in peer-reviews journals.\n\nStrengths and Limitations of this study- This is a new cohort of families being followed from prenatal to postnatal (up to 18 months) during the COVID-19 pandemic.\n- The study involves the collection of quantifiable data to identify the short- and long-term influences of the pandemic on key aspects of infant development.\n- The study also has a range of open-ended questions for qualitative analysis aimed at exploring familial experiences in more detail.\n- The data is being collected online and is therefore limited to self- and parent-report measures, with no direct assessment of child development and parental mental health.\n- Although the sample of families being recruited are diverse in their indices of multiple deprivation (IMD) and geographic location, they may not be fully representative of the wider population.", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.23.445371", + "rel_abs": "In genetics and related fields, huge amounts of data, such as genome sequences, are accumulating, and the use of artificial intelligence (AI) suitable for big data analysis has become increasingly important. Unsupervised AI that can reveal novel knowledge from big data without prior knowledge or particular models is highly desirable for analyses of genome sequences, particularly for obtaining unexpected insights. We have developed a batch-learning self-organizing map (BLSOM) for oligonucleotide compositions that can reveal various novel genome characteristics. Here, we explain the data mining by the BLSOM: unsupervised and explainable AI. As a specific target, we first selected SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) because a large number of the viral genome sequences have been accumulated via worldwide efforts. We analyzed more than 0.6 million sequences collected primarily in the first year of the pandemic. BLSOMs for short oligonucleotides (e.g., 4~6-mers) allowed separation into known clades, but longer oligonucleotides further increased the separation ability and revealed subgrouping within known clades. In the case of 15-mers, there is mostly one copy in the genome; thus, 15-mers appeared after the epidemic start could be connected to mutations. Because BLSOM is an explainable AI, BLSOM for 15-mers revealed the mutations that contributed to separation into known clades and their subgroups. After introducing the detailed methodological strategies, we explained BLSOMs for various topics. The tetranucleotide BLSOM for over 5 million 5-kb fragment sequences derived from almost all microorganisms currently available and its use in metagenome studies. We also explained BLSOMs for various eukaryotes, such as fishes, frogs and Drosophila species, and found a high separation ability among closely related species. When analyzing the human genome, we found evident enrichments in transcription factor-binding sequences (TFBSs) in centromeric and pericentromeric heterochromatin regions. The tDNAs (tRNA genes) were separated by the corresponding amino acid.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ezra Aydin", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Staci M Weiss", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Kevin A Glasgow", - "author_inst": "University of Cambridge" + "author_name": "Toshimichi Ikemura", + "author_inst": "Nagahama Institute of Bio-Science and Technology" }, { - "author_name": "Jane Barlow", - "author_inst": "University of Oxford" + "author_name": "Yuki Iwasaki", + "author_inst": "Nagahama Institute of Bio-Science and Technology" }, { - "author_name": "Topun Austin", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" + "author_name": "Kennosuke Wada", + "author_inst": "Nagahama Institute of Bio-Science and Technology" }, { - "author_name": "Mark H Johnson", - "author_inst": "University of Cambridge" + "author_name": "Yoshiko Wada", + "author_inst": "Nagahama Institute of Bio-Science and Technology" }, { - "author_name": "Sarah Lloyd-Fox", - "author_inst": "University of Cambridge" + "author_name": "Takashi Abe", + "author_inst": "Niigata University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "license": "cc_by", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.05.23.445348", @@ -763328,101 +763407,133 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.05.17.21257134", - "rel_title": "Heterologous vaccination strategy for containing COVID-19 pandemic", + "rel_doi": "10.1101/2021.05.21.21257572", + "rel_title": "Towards Internationally standardised humoral Immune Correlates of Protection from SARS CoV 2 infection and COVID-19 disease", "rel_date": "2021-05-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.17.21257134", - "rel_abs": "An unequitable vaccine allocation and continuously emerging SARS-CoV-2 variants pose challenges to contain the pandemic, which underscores the need for licensing more vaccine candidates, increasing manufacturing capacity and implementing better immunization strategy. Here, we report data from a proof-of-concept investigation in two healthy individuals who received two doses of inactivated whole-virus COVID-19 vaccines, followed by a single heterologous boost vaccination after 7 months with an mRNA vaccine candidate (LPP-Spike-mRNA) developed by Stemirna Therapeutics. Following the boost, Spike-specific antibody (Ab), memory B cell and T cell responses were significantly increased. These findings indicate that a heterologous immunization strategy combining inactivated and mRNA vaccines can generate robust vaccine responses and therefore provide a rational and effective vaccination regimen.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.21.21257572", + "rel_abs": "Precision monitoring of antibody responses during the COVID-19 pandemic is increasingly important during large scale vaccine rollout and rise in prevalence of Severe Acute Respiratory Syndrome-related Coronavirus-2 (SARS-CoV-2) variants of concern (VOC). Equally important is defining Correlates of Protection (CoP) for SARS-CoV-2 infection and COVID-19 disease. Data from epidemiological studies and vaccine trials identified virus neutralising antibodies (Nab) and SARS-CoV-2 antigen-specific (notably RBD, and S) binding antibodies as candidate CoP. In this study, we used the World Health Organisation (WHO) international standard to benchmark neutralising antibody responses and a large panel of binding antibody assays to compare convalescent sera obtained from: a) COVID-19 patients; b) SARS-CoV-2 seropositive healthcare workers (HCW) and c) seronegative HCW. The ultimate aim of this study, was to identify biomarkers of humoral immunity that could be used as candidate CoP in internationally accepted unitage. Whenever suitable, the antibody levels of the samples studied were expressed in International Units (INU) for virus neutralisation assays or International Binding Antibody Units (BAU) for ELISA tests. In this work we used commercial and non-commercial antibody binding assays; a lateral flow test for detection of SARS-CoV-2-specific IgG / IgM; a high throughput multiplexed particle flow cytometry assay for SARS-CoV-2 Spike (S), Nucleocapsid (N) and Receptor Binding Domain (RBD) proteins); a multiplex antigen semi-automated immuno-blotting assay measuring IgM, IgA and IgG; a pseudotyped microneutralisation test (pMN) and electroporation-dependent neutralisation assay (EDNA). Our results indicate that overall, severe COVID-19 patients showed statistically significantly higher levels of SARS-CoV-2-specific neutralising antibodies (average 1029 IU/ml) than those observed in seropositive HCW with mild or asymptomatic infections (379 IU/ml) and that clinical severity scoring, based on WHO guidelines was tightly correlated with neutralisation and RBD / S binding assays. In addition, there was a positive correlation between severity, N-antibody assays and intracellular virus neutralisation.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Ang Lin", - "author_inst": "Stemirna Therapeutics" + "author_name": "Javier Castillo-Olivares", + "author_inst": "University of Cambridge" }, { - "author_name": "Jingjing Liu", - "author_inst": "National Institutes for Food and Drug Control (NIFDC), Beijing, China." + "author_name": "David Wells", + "author_inst": "University of Cambridge; DIOSynVax" }, { - "author_name": "Xiaopin Ma", - "author_inst": "Stemirna Therapeutics" + "author_name": "Matteo Ferrari", + "author_inst": "University of Cambridge; DioSynvax" }, { - "author_name": "Fanfan Zhao", - "author_inst": "Stemirna Therapeutics" + "author_name": "Andrew Chan", + "author_inst": "University of Cambridge" }, { - "author_name": "Bo Yu", - "author_inst": "Stemirna Therapeutics" + "author_name": "Peter Smith", + "author_inst": "University of Cambridge" }, { - "author_name": "Jiaxin He", - "author_inst": "Stemirna Therapeutics" + "author_name": "Angalee Nadesalingam", + "author_inst": "University of Cambridge" }, { - "author_name": "Mingyun Shen", - "author_inst": "Stemirna Therapeutics" + "author_name": "Minna Paloniemi", + "author_inst": "University of Cambridge; Fimlab Laboratories, Tampere, Finland" }, { - "author_name": "Lei Huang", - "author_inst": "Stemirna Therapeutics" + "author_name": "George Carnell", + "author_inst": "University of Cambridge" }, { - "author_name": "Hongming Tang", - "author_inst": "Shanghai East Hospital, Tongji University" + "author_name": "Luis Ohlendorf", + "author_inst": "University of Cambridge" }, { - "author_name": "Erpeng Jiang", - "author_inst": "Shanghai East Hospital, Tongji University" + "author_name": "Diego Cantoni", + "author_inst": "University of Kent" }, { - "author_name": "Yue Wang", - "author_inst": "Shanghai East Hospital, Tongji University" + "author_name": "Martin Mayora-Neto", + "author_inst": "University of Kent" }, { - "author_name": "Pingfang Cui", - "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences" + "author_name": "Phillip Palmer", + "author_inst": "University of Cambridge" }, { - "author_name": "Yujiang Zhang", - "author_inst": "Stemirna Therapeutics" + "author_name": "Paul Tonks", + "author_inst": "University of Cambridge" }, { - "author_name": "Weiguo Yao", - "author_inst": "Stemirna Therapeutics" + "author_name": "Nigel Temperton", + "author_inst": "University of Kent" }, { - "author_name": "Aihua Zhang", - "author_inst": "Stemirna Therapeutics" + "author_name": "Patrick Neckermann", + "author_inst": "University of Regensburg" }, { - "author_name": "Youchun Wang", - "author_inst": "Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC)" + "author_name": "David Peterhoff", + "author_inst": "University of Regensburg, Germany" }, { - "author_name": "Yuhua Li", - "author_inst": "National Institutes for Food and Drug Control (NIFDC), Beijing, China." + "author_name": "Ralf James Wagner", + "author_inst": "Institute of Medical Microbiology and Hygiene" }, { - "author_name": "Weijin Huang", - "author_inst": "Division of HIV/AIDS and Sex-transmitted Virus Vaccines, Institute for Biological Product Control, National Institutes for Food and Drug Control (NIFDC)" + "author_name": "Rainer Doffinger", + "author_inst": "Addenbrooke's Hospital, Cambridge, UK" }, { - "author_name": "Qihan Li", - "author_inst": "Institute of Medical Biology, Chinese Academy of Medical Sciences" + "author_name": "Sarah Kempster", + "author_inst": "National Institute for Biological Standards and Control, UK" }, { - "author_name": "Zhongmin Liu", - "author_inst": "Shanghai East Hospital, Tongji University" + "author_name": "Ashley Otter", + "author_inst": "National Infection Service, Public Health England, Porton Down, UK" + }, + { + "author_name": "Amanda Semper", + "author_inst": "National Infection Service, Public Health England, Porton Down, UK" + }, + { + "author_name": "Tim Brooks", + "author_inst": "National Infection Service, Public Health England, Porton Down, UK" + }, + { + "author_name": "Mark Page", + "author_inst": "National Institute for Biological Standards and Control" + }, + { + "author_name": "Anna Albecka", + "author_inst": "MRC Laboratory of Molecular Biology, Cambridge, UK" + }, + { + "author_name": "John Briggs", + "author_inst": "MRC Laboratory of Molecular Biology, Cambridge, UK" + }, + { + "author_name": "Leo James", + "author_inst": "MRC Laboratory of Molecular Biology, Cambridge, UK" }, { - "author_name": "Hangwen Li", - "author_inst": "Stemirna Therapeutics; Shanghai East Hospital, Tongji University" + "author_name": "Wilhelm Schwabble", + "author_inst": "Complement Laboratory, Department of Veterinary Medicine, University of Cambridge, UK" + }, + { + "author_name": "Dr HE Baxendale", + "author_inst": "Royal Papworth Hospital NHS Foundation Trust" + }, + { + "author_name": "Jonathan Heeney", + "author_inst": "University of Cambridge, UK" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -765346,49 +765457,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.19.21257470", - "rel_title": "RT-qPCR half reaction optimization for the detection of SARS-CoV-2", + "rel_doi": "10.1101/2021.05.19.21257485", + "rel_title": "Dysbiosis and structural disruption of the respiratory microbiota in COVID-19 patients with severe and fatal outcomes", "rel_date": "2021-05-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.19.21257470", - "rel_abs": "BACKGROUNDThe main laboratory test for the diagnosis of COVID-19 is the reverse transcription real-time polymerase chain reaction (RT-qPCR). However, the RT-qPCR is an expensive method due to the number of tests required.\n\nOBJECTIVESTo evaluate an alternative RT-qPCR approach for the detection of SARS-CoV-2 sing half of the total volume currently recommended by the US Centers for Disease Control and Prevention.\n\nMETHODSThe analytical limit of detection (LoD) and the reaction efficiency using half volumes of RT-qPCR assay were evaluated for both the N1 and N2 regions by using a synthetic control RNA. A panel of 76 SARS-CoV-2-positive and 26 SARS-CoV-2-negative clinical samples were evaluated to establish the clinical sensitivity and specificity.\n\nFINDINGSThe RT-qPCR assay efficiency was 105% for both the half and standard reactions considering the N2 target and 84% (standard) and 101% (half) for N1. The RT-qPCR half reaction LoD for N1 and N2 were 20 and 80 copies/{micro}L, respectively. Clinical sensitivity and specificity were 100%. The half reaction presented a decrease of up to 5.5 cycle thresholds when compared with the standard RT-qPCR.\n\nCONCLUSIONSThe use of RT-qPCR half reaction proved to be a feasible and economic strategy for detection of SARS-CoV-2 RNA.\n\nSponsorshipThis work was supported by FAPERGS (20/2551-0000265-9) and by Fundo de Incentivo a Pesquisa e Eventos do Hospital de Clinicas de Porto Alegre (FIPE/HCPA) (Project no. 2020-0163).", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.19.21257485", + "rel_abs": "COVID-19 outbreak has caused over 3 million deaths worldwide. Understanding disease pathology and the factors that drive severe and fatal clinical outcomes is of special relevance. Studying the role of the respiratory microbiota in COVID-19 is particularly important since its known that the respiratory microbiota interacts with the host immune system, contributing to clinical outcomes in chronic and acute respiratory diseases. Here, we characterized the microbiota in the respiratory tract of patients with mild, severe, or fatal COVID-19, and compared with healthy controls and patients with non-COVID-19-pneumonia. We comparatively studied the microbial composition, diversity, and microbiota structure across study groups and correlated the results with clinical data. We found differences in diversity and abundance of bacteria between groups, higher levels of dysbiosis in the respiratory microbiota of COVID-19 patients (regardless of severity level), differences in diversity structure among mild, severe, and fatal COVID-19, and the presence of specific bacteria that correlated with clinical variables associated with increased mortality risk. Our data suggest that host-related and environmental factors could be affecting the respiratory microbiota before SARS-CoV-2 infection, potentially compromising the immunological response of the host against disease and promoting secondary bacterial infections. For instance, the high levels of dysbiosis coupled with low microbial structural complexity in the respiratory microbiota of COVID-19 patients, possibly resulted from antibiotic uptake and comorbidities, could have consequences for the host and microbial community level. Altogether, our findings identify the respiratory microbiota as a potential factor associated with COVID-19 severity.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Priscila Lamb Wink", - "author_inst": "Hospital de Clinicas de Porto Alegre" + "author_name": "Alejandra Hernandez-Teran Jr.", + "author_inst": "Departamento de Investigacion en Tabaquismo y EPOC. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." }, { - "author_name": "Fabiana Volpato", - "author_inst": "Hospital de Clinicas de Porto Alegre" + "author_name": "Fidencio Mejia-Nepomuceno", + "author_inst": "Departamento de Investigacion en Tabaquismo y EPOC. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." }, { - "author_name": "Daiana Lima-Morales", - "author_inst": "Hospital de Clinicas de Porto Alegre" + "author_name": "Maria Teresa Herrera", + "author_inst": "Departamento de Investigacion en Microbiologia. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." }, { - "author_name": "Rodrigo Minuto Paiva", - "author_inst": "Hospital de Clinicas de Porto Alegre" + "author_name": "Omar Barreto", + "author_inst": "Coordinacion de Atencion Medica. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." }, { - "author_name": "Julia Biz Willig", - "author_inst": "Hospital de Clinicas de Porto Alegre" + "author_name": "Emma Garcia", + "author_inst": "Coordinacion de Atencion Medica. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." }, { - "author_name": "Hugo Bock", - "author_inst": "Hospital de Clinicas de Porto Alegre" + "author_name": "Manuel Castillejos", + "author_inst": "Departamento de Unidad de Epidemiologia Hospitalaria e Infectologia. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." }, { - "author_name": "Fernanda de-Paris", - "author_inst": "Hospital de Clinicas de Porto Alegre" + "author_name": "Celia Boukadida Jr.", + "author_inst": "Centro de Investigacion en Enfermedades Infecciosas, CIENI. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." }, { - "author_name": "Afonso Luis Barth", - "author_inst": "Hospital de Clinicas de Porto Alegre" + "author_name": "Santiago Avila-Rios", + "author_inst": "Centro de Investigacion en Enfermedades Infecciosas, CIENI. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Margarita Matias-Florentino", + "author_inst": "Centro de Investigacion en Enfermedades Infecciosas, CIENI. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Alma Rincon-Rubio", + "author_inst": "Centro de Investigacion en Enfermedades Infecciosas, CIENI. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Mario Mujica-Sanchez", + "author_inst": "Laboratorio de Microbiologia. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Ricardo Serna-Munoz", + "author_inst": "Departamento de Investigacion en Tabaquismo y EPOC. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Eduardo Becerril-Vargas", + "author_inst": "Laboratorio de Microbiologia. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Cristobal Guadarrama-Perez", + "author_inst": "Servicio de Urgencias Medicas. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Victor Ahumada-Topete", + "author_inst": "Departamento de Unidad de Epidemiologia Hospitalaria e Infectologia. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Sebastian Rodriguez", + "author_inst": "Departamento de Investigacion en Tabaquismo y EPOC. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Jose A. Martinez-Orozco", + "author_inst": "Laboratorio de Microbiologia. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Jorge Salas-Hernandez", + "author_inst": "Direccion General INER. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Rogelio Perez-Padilla", + "author_inst": "Departamento de Investigacion en Tabaquismo y EPOC. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." + }, + { + "author_name": "Joel A. Vazquez-Perez", + "author_inst": "Departamento de Investigacion en Tabaquismo y EPOC. Instituto Nacional de Enfermedades Respiratorias Ismael Cosio Villegas, INER." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -766924,37 +767083,29 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.05.18.21257426", - "rel_title": "Modeling waning and boosting of COVID-19 in Canada with vaccination", + "rel_doi": "10.1101/2021.05.18.21257386", + "rel_title": "FOCUS: Forecasting COVID-19 in the United States", "rel_date": "2021-05-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.18.21257426", - "rel_abs": "SARS-CoV-2, the causative agent of COVID-19, has caused devastating health and economic impacts around the globe since its appearance in late 2019. The advent of effective vaccines leads to open questions on how best to vaccinate the population. To address such questions, we developed a model of COVID-19 infection by age that includes the waning and boosting of immunity against SARS-CoV-2 in the context of infection and vaccination. The model also accounts for changes to infectivity of the virus, such as public health mitigation protocols over time, increases in the transmissibility of variants of concern, changes in compliance to mask wearing and social distancing, and changes in testing rates. The model is employed to study public health mitigation and vaccination of the COVID-19 epidemic in Canada, including different vaccination programs (rollout by age), and delays between doses in a two-dose vaccine. We find that the decision to delay the second dose of vaccine is appropriate in the Canadian context. We also find that the benefits of a COVID-19 vaccination program in terms of reductions in infections is increased if vaccination of 15-19 year olds are included in the vaccine rollout.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.18.21257386", + "rel_abs": "Infectious disease forecasting has been a useful tool for public health planning and messaging during the COVID-19 pandemic. In partnership with the CDC, the organizers of the COVID-19 Forecast Hub have created a mechanism for forecasters from academia, industry, and government organizations to submit weekly near-term predictions of COVID-19 targets in the United States. Here we describe our efforts to participate in the COVID-19 Forecast Hub through the Forecasting COVID-19 in the United States (FOCUS) project. The effort led to more than three months of weekly submissions and development of an automated pipeline to generate forecasts. The models used in FOCUS yielded forecasts that ranked relatively well in terms of precision and accuracy.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Lauren Childs", - "author_inst": "Virginia Tech" - }, - { - "author_name": "David W Dick", - "author_inst": "York University" - }, - { - "author_name": "Zhilan Feng", - "author_inst": "Purdue University" + "author_name": "VP Nagraj", + "author_inst": "Signature Science, LLC" }, { - "author_name": "Jane M Heffernan", - "author_inst": "York University" + "author_name": "Stephanie L Guertin", + "author_inst": "Signature Science, LLC" }, { - "author_name": "Jing Li", - "author_inst": "California State University" + "author_name": "Chris Hulme-Lowe", + "author_inst": "Signature Science, LLC" }, { - "author_name": "Gergely R\u00f6st", - "author_inst": "University of Szeged" + "author_name": "Stephen D Turner", + "author_inst": "Signature Science, LLC" } ], "version": "1", @@ -768994,61 +769145,45 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.05.19.444569", - "rel_title": "Spatially distributed infection increases viral load in a computational model of SARS-CoV-2 lung infection", + "rel_doi": "10.1101/2021.05.19.444825", + "rel_title": "Adaptive immune determinants of viral clearance and protection in mouse models of SARS-CoV-2", "rel_date": "2021-05-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.19.444569", - "rel_abs": "A key question in SARS-CoV-2 infection is why viral loads and patient outcomes vary dramatically across individuals. Because spatial-temporal dynamics of viral spread and immune response are challenging to study in vivo, we developed Spatial Immune Model of Coronavirus (SIMCoV), a scalable computational model that simulates hundreds of millions of lung cells, including respiratory epithelial cells and T cells. SIMCoV replicates viral growth dynamics observed in patients and shows how spatially dispersed infections can lead to increased viral loads. The model also shows how the timing and strength of the T cell response can affect viral persistence, oscillations, and control. By incorporating spatial interactions, SIMCoV provides a parsimonious explanation for the dramatically different viral load trajectories among patients by varying only the number of initial sites of infection, and the magnitude and timing of the T cell immune response. When the branching airway structure of the lung is explicitly represented, we find that virus spreads faster than in a 2D layer of epithelial cells, but much more slowly than in an undifferentiated 3D grid or in a well-mixed ODE model. These results illustrate how realistic spatially explicit computational models can improve understanding of within-host dynamics of SARS-CoV-2 infection.\n\nSummaryA key question in SARS-CoV-2 infection is why viral loads and patient outcomes are so different across individuals. Because its difficult to see how the virus spreads in the lungs of infected people, we developed Spatial Immune Model of Coronavirus (SIMCoV), a computational model that simulates hundreds of millions of cells, including lung cells and immune cells. SIMCoV simulates how virus grows and then declines, and the simulations match data observed in patients. SIMCoV shows that when there are more initial infection sites, the virus grows to a higher peak. The model also shows how the timing of the immune response, particularly the T cell response, can affect how long the virus persists and whether it is ultimately cleared from the lungs. SIMCoV shows that the different viral loads in different patients can be explained by how many different places the virus is initially seeded inside their lungs. We explicitly add the branching airway structure of the lung into the model and show that virus spreads slightly faster than it would in a two-dimensional layer of lung cells, but much slower than traditional mathematical models based on differential equations. These results illustrate how realistic spatial computational models can improve understanding of how SARS-CoV-2 infection spreads in the lung.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.19.444825", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused more than 160 million infections and more than 3 million deaths worldwide. While effective vaccines are currently being deployed, the adaptive immune determinants which promote viral clearance and confer protection remain poorly defined. Using mouse models of SARS-CoV-2, we demonstrate that both humoral and cellular adaptive immunity contributes to viral clearance in the setting of primary infection. Furthermore, we find that either convalescent mice, or mice that receive mRNA vaccination are protected from both homologous infection and infection with a variant of concern, B.1.351. Additionally, we find this protection to be largely mediated by antibody response and not cellular immunity. These results highlight the in vivo protective capacity of antibodies generated to both vaccine and natural infection.\n\nOne-Sentence SummaryDefining the roles of humoral and cellular adaptive immunity in viral clearance and protection from SARS-CoV-2 and a variant of concern.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Melanie E. Moses", - "author_inst": "University of New Mexico" - }, - { - "author_name": "Steve Hofmeyr", - "author_inst": "Lawrence Berkeley National Laboratory" - }, - { - "author_name": "Judy L Cannon", - "author_inst": "University of New Mexico" - }, - { - "author_name": "Akil Andrews", - "author_inst": "University of New Mexico" - }, - { - "author_name": "Rebekah Gridley", - "author_inst": "University of New Mexico" + "author_name": "Benjamin Israelow", + "author_inst": "Yale University, Yale School of Medicine" }, { - "author_name": "Monica Hinga", - "author_inst": "University of New Mexico" + "author_name": "Tianyang Mao", + "author_inst": "Yale University, Yale School of Medicine" }, { - "author_name": "Kirtus Leyba", - "author_inst": "Arizona State University" + "author_name": "Jon Klein", + "author_inst": "Yale University, Yale School of Medicine" }, { - "author_name": "Abigail Pribisova", - "author_inst": "University of New Mexico" + "author_name": "Eric Song", + "author_inst": "Yale University" }, { - "author_name": "Vanessa Surjadidjaja", - "author_inst": "University of New Mexico" + "author_name": "Bridget Menasche", + "author_inst": "Yale University, Yale School of Medicine" }, { - "author_name": "Humayra Tasnim", - "author_inst": "University of New Mexico" + "author_name": "Saad B Omer", + "author_inst": "Yale University, Yale School of Medicine" }, { - "author_name": "Stephanie Forrest", - "author_inst": "Arizona State University" + "author_name": "Akiko Iwasaki", + "author_inst": "Yale University School of Medicine" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -772308,105 +772443,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.15.21257254", - "rel_title": "Inhibitor screening of Spike variants reveals the heterogeneity of neutralizing antibodies to COVID-19 infection and vaccination", + "rel_doi": "10.1101/2021.05.14.21257231", + "rel_title": "Patient Characteristics in Cases of Reinfection or Prolonged viral shedding in SARS-CoV-2", "rel_date": "2021-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.15.21257254", - "rel_abs": "Mutations of the coronavirus responsible for coronavirus disease 2019 (COVID-19) could impede drug development and reduce the efficacy of COVID-19 vaccines. Here, we developed a multiplexed Spike-ACE2 Inhibitor Screening (mSAIS) assay that can measure the neutralizing effect of antibodies across numerous variants of the coronaviruss Spike (S) protein simultaneously. By screening purified antibodies and serum from convalescent COVID-19 patients and vaccinees against 72 S variants with the mSAIS assay, we identified new S mutations that are sensitive and resistant to neutralization. Serum from both infected and vaccinated groups with a high titer of neutralizing antibodies (NAbs) displayed a broader capacity to neutralize S variants than serum with low titer NAbs. These data were validated using serum from a large vaccinated cohort (n=104) with a tiled S peptide microarray. In addition, similar results were obtained using a SARS-CoV-2 pseudovirus neutralization assay specific for wild-type S and four prevalent S variants (D614G, B.1.1.7, B.1.351, P.1), thus demonstrating that high antibody diversity is associated with high NAb titers. Our results demonstrate the utility of the mSAIS platform in screening NAbs. Moreover, we show that heterogeneous antibody populations provide a more protective effect against S variants, which may help direct COVID-19 vaccine and drug development.\n\nHighlightsO_LIDeveloped a high throughput assay to screen the neutralizing effect of antibodies across multiple SARS-CoV-2 Spike variants simultaneously.\nC_LIO_LICharacterized the heterogeneity of neutralizing antibodies produced in response to COVID-19 infection and vaccination.\nC_LIO_LIDemonstrated the capacity of Spike variants neutralization is associated with the diversity of anti-Spike antibodies.\nC_LI", - "rel_num_authors": 22, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.14.21257231", + "rel_abs": "ImportanceAs testing options increase for COVID-19, their interpretability is challenged by the increasing variety of clinical contexts in which results are obtained. In particular, positive COVID-19 diagnostic (RT-PCR) tests that occur after a patient has seroconverted may be indicative of reinfection. However, in the absence of SARS-CoV-2 sequence data, the possibility of prolonged viral shedding may not be excluded. We highlight a testing pattern that identifies such cases and study its statistical power in identifying potential reinfection. We also study the medical records of patients that matched the pattern.\n\nObjectiveTo describe the frequency and demographic information of people with a testing pattern indicative of SARS-CoV-2 reinfection.\n\nDesignWe examined 4.2 million test results from a large national health insurer in the United States. Specifically, we identified the pattern of a positive RT-PCR test followed by a positive IgG test, again followed by a positive RT-PCR.\n\nSettingData from outpatient laboratories across the United States was joined with claims data from a single large commercial insurers administrative claims database.\n\nParticipantsStudy participants are those whose insurance, either commercial or Medicare, is provided by a single US based insurer.\n\nExposuresPeople who received at least two positive diagnostic tests via RT-PCR for SARS-Cov-2 separated by 42 or more days with at least one serological test (IgG) indicating the presence of antibodies between diagnostic tests.\n\nMain Outcomes and MeasuresCount and characteristics of people with the timeline of three tests as described in Exposures.\n\nResultsWe identified 79 patients who had two positive RT-PCR tests separated by more than six weeks, with a positive IgG test in between. These patients tended to be older than those COVID-19 patients without this pattern (median age 56 vs. 42), and they exhibited comorbidities typically attributed to a compromised immune system and heart disease.\n\nConclusions and RelevanceWhile the testing pattern alone was not sufficient to distinguish potential reinfection from prolonged viral shedding, we were able to identify common traits of the patients identified through the pattern.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Xiaomei Zhang", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" - }, - { - "author_name": "Mei Zheng", - "author_inst": "Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing, China." - }, - { - "author_name": "Te Liang", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" - }, - { - "author_name": "Haijian Zhou", - "author_inst": "State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Diseas" - }, - { - "author_name": "Hongye Wang", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" - }, - { - "author_name": "Jiahui Zhang", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" - }, - { - "author_name": "Jing Ren", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" - }, - { - "author_name": "Huoying Peng", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" - }, - { - "author_name": "Siping Li", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" - }, - { - "author_name": "Haodong Bian", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" - }, - { - "author_name": "Chundi Wei", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" - }, - { - "author_name": "Shangqi Yin", - "author_inst": "Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing, China." - }, - { - "author_name": "Chaonan He", - "author_inst": "Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing, China" - }, - { - "author_name": "Ying Han", - "author_inst": "Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing, China." - }, - { - "author_name": "Minghui Li", - "author_inst": "State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Diseas" - }, - { - "author_name": "Xuexin Hou", - "author_inst": "State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Diseas" - }, - { - "author_name": "Jie Zhang", - "author_inst": "Beijing Key Laboratory of Monoclonal Antibody Research and Development, Sino Biological, Inc., Beijing, 100176, China" + "author_name": "Richard M. Yoo", + "author_inst": "Harvard Medical School" }, { - "author_name": "Liangzhi Xie", - "author_inst": "Beijing Key Laboratory of Monoclonal Antibody Research and Development, Sino Biological, Inc., Beijing, 100176, China" + "author_name": "Roland A. Romero", + "author_inst": "OptumLabs at UnitedHealth Group" }, { - "author_name": "Jing Lv", - "author_inst": "Gobond Testing Technology (Beijing) Co., Ltd., Beijing, 102629, China." + "author_name": "Joseph Mabajen", + "author_inst": "OptumLabs at UnitedHealth Group" }, { - "author_name": "Biao Kan", - "author_inst": "State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Diseas" + "author_name": "Suchit Mehrotra", + "author_inst": "OptumLabs at UnitedHealth Group" }, { - "author_name": "Yajie Wang", - "author_inst": "Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing, China." + "author_name": "Isaac S. Kohane", + "author_inst": "Harvard Medical School" }, { - "author_name": "xiaobo yu", - "author_inst": "State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeom" + "author_name": "Natalie E. Sheils", + "author_inst": "OptumLabs at UnitedHealth Group" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -774178,43 +774249,35 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2021.05.18.21257259", - "rel_title": "SARS-CoV-2 Vaccine-Induced Antibody Response and Reinfection in Persons with Past Natural Infection", + "rel_doi": "10.1101/2021.05.16.21257155", + "rel_title": "Evaluation of High Flow Local Extraction on control of the aerosol plume in an operating theatre", "rel_date": "2021-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.18.21257259", - "rel_abs": "Several studies have shown that subjects with a history of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection had significantly higher antibody titers than previously uninfected vaccinees after vaccination with mRNA vaccine. Yet no information is available for other vaccines.\n\nIn the current observational cohort study, 105 health care workers who had received Covishield an Adeno associated viral vector-based DNA vaccine were enrolled at Sarojini Nadu Medical College Agra, India. The study included 40 (23 men and 17 women) subjects with a previous history of SARS-CoV-2 infection and 65 participants (39 men and 26 women) who were not infected previously. Both the groups received the adenovirus vector vaccine ChAdOx1-S recombinant vaccines (Covishield, Astra Zeneca). The levels of SARS-CoV-2-anti-spike-IgG-antibodies titer were measured using Electrochemiluminescence immunoassay on Roche platform as arbitrary units per milliliter (AU/ml).\n\nAfter 28 days of the second dose, subjects with no previous SARSCoV-2 infection showed a significantly lower level of circulating anti-spike-IgG-antibody titers compared to previously infected participants. After the second dose, we also observed a significant increase in SARS-CoV-2 infection in subjects with no prior history of SARS-CoV-2 infection compared to subjects with a previous history of natural infection.\n\nThe most important observation of the study is a low percentage of infection in previously infected subjects. The finding of the study also indicates the presence of robust humoral memory response in previously infected patients.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.16.21257155", + "rel_abs": "BackgroundEngineering controls are a necessity for minimising aerosol transmission of SARS-CoV-2, yet so far, little attention has been given to such interventions. High flow local extraction (HFLE) is a standard in other industries that deal with airborne contaminants.\n\nObjectiveThis study aims to provide a quantitative evaluation of an HFLE concept feasible to implement in most real clinical settings.\n\nDesignA unique combined experimental model of Laser sheet illumination videography paired with continuous nanoparticle counts was used to quantitatively assess the impact of HFLE in an operating theatre. Propylene Glycol was aerosolised via a customised physiological lung simulator and dispersion was measured in 3 dimensions. Cumulative probability heat maps were generated to describe aerosol behaviour. Continuous particle counts were made at 15 locations throughout the room to validate laser assessments.\n\nResultsHigh flow local extraction reduced dispersion of simulated exhaled aerosols to undetectable levels. With the HFLE in operation and optimally positioned, the aerosol plume was tightly controlled. Particle counts remained at baseline when HFLE was active. HFLE becomes less effective when positioned at increasing distance from the mouth.\n\nAerosol plume behaviour in the absence of HFLE was highly variable and unpredictable.\n\nConclusionsThis analysis demonstrates great potential for HFLE to have a significant impact in reducing aerosol transmission. Simple HFLE devices can be easily engineered and could be widely deployed without impacting on the safe delivery of care.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Nitu Chauhan", - "author_inst": "Department of Transfusion Medicine, Sarojini Naidu Medical College Agra, Uttar Pradesh, India" - }, - { - "author_name": "Ajeet Singh Chahar", - "author_inst": "Department of Transfusion Medicine, Sarojini Naidu Medical College Agra, Uttar Pradesh, India" - }, - { - "author_name": "Prem Singh", - "author_inst": "Department of Transfusion Medicine, Sarojini Naidu Medical College Agra, Uttar Pradesh, India" + "author_name": "Logan Marriott", + "author_inst": "Fiona Stanley Hospital" }, { - "author_name": "Neel Sarovar Bhavesh", - "author_inst": "International Centre for Genetic Engineering and Biotechnology, New Delhi, India" + "author_name": "Matthew Harper", + "author_inst": "Fiona Stanley Hospital" }, { - "author_name": "Ravi Tandon", - "author_inst": "School of Biotechnology and Special Center for Systems Medicine, Jawaharlal Nehru University, New Delhi, India" + "author_name": "Tongming Zhou", + "author_inst": "University Western Australia" }, { - "author_name": "Rupesh Chaturvedi", - "author_inst": "School of Biotechnology and Special Center for Systems Medicine, Jawaharlal Nehru University, New Delhi, India" + "author_name": "Chenlin Sun", + "author_inst": "University of Western Australia" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2021.05.18.21257324", @@ -775908,57 +775971,53 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.05.13.21257146", - "rel_title": "Sociodemographic inequality in COVID-19 vaccination coverage amongst elderly adults in England: a national linked data study", + "rel_doi": "10.1101/2021.05.17.21257012", + "rel_title": "Pre-Exposure Prophylaxis with Various Doses of Hdroxychloroquine among high-risk COVID 19 Healthcare Personnel: CHEER randomized controlled trial", "rel_date": "2021-05-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.13.21257146", - "rel_abs": "ObjectiveTo examine inequalities in COVID-19 vaccination rates amongst elderly adults in England\n\nDesignCohort study\n\nSettingPeople living in private households and communal establishments in England\n\nParticipants6,829,643 adults aged [≥] 70 years (mean 78.7 years, 55.2% female) who were alive on 15 March 2021.\n\nMain outcome measuresHaving received the first dose of a vaccine against COVID-19 by 15 March 2021. We calculated vaccination rates and estimated unadjusted and adjusted odds ratios using logistic regression models.\n\nResultsBy 15 March 2021, 93.2% of people living in England aged 70 years and over had received at least one dose of a COVID-19 vaccine. While vaccination rates differed across all factors considered apart from sex, the greatest disparities were seen between ethnic and religious groups. The lowest rates were in people of Black African and Black Caribbean ethnic backgrounds, where only 67.2% and 73.9% had received a vaccine, with adjusted odds of not being vaccinated at 5.01 (95% CI 4.86 - 5.16) and 4.85 (4.75 - 4.96) times greater than the White British group. The proportion of individuals self-identifying as Muslim and Buddhist who had received a vaccine was 79.1% and 84.1%, respectively. Older age, greater area deprivation, less advantaged socio-economic position (proxied by living in a rented home), being disabled and living either alone or in a multi-generational household were also associated with higher odds of not having received the vaccine.\n\nConclusionPeople disproportionately affected seem most hesitant to COVID-19 vaccinations. Policy Interventions to improve these disparities are urgently needed.\n\nSummary BoxO_ST_ABSWhat is already known on this subject?C_ST_ABSThe UK began an ambitious vaccination programme to combat the COVID-19 pandemic on 8th December 2020. Existing evidence suggests that COVID-19 vaccination rates differ by level of area deprivation, ethnicity and certain underlying health conditions, such as learning disability and mental health problems.\n\nWhat does this study add?Our study shows that first dose vaccination rates in adults aged 70 or over differed markedly by ethnic group and self-reported religious affiliation, even after adjusting for geography, socio-demographic factors and underlying health conditions. Our study also highlights differences in vaccination rates by deprivation, household composition, and disability status, factors disproportionately associated with SARS-CoV-2 infection. Public health policy and community engagement aimed at promoting vaccination uptake is these groups are urgently needed.\n\nStrengths and limitations of this studyO_LIUsing nationwide linked population-level data from clinical records and the 2011 Census, we examined a wide range of socio-demographic characteristics not available n electronic health records\nC_LIO_LIMost demographic and socio-economic characteristics are derived from the 2011 Census and therefore are 10 years old. However, we focus primarily on characteristics that are unlikely to change over time, such as ethnicity or religion, or likely to be stable for our population\nC_LIO_LIBecause the data are based on the 2011 Census, it excluded people living in England in 2011 but not taking part in the 2011 Census; respondents who could not be linked to the 2011-2013 NHS patients register; recent migrants. Consequently, we excluded 5.4% of vaccinated people who could not be linked\nC_LI", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.17.21257012", + "rel_abs": "BackgroundPre-exposure prophylaxis (PrEP) is a promising strategy to break the chain of transmission of novel coronavirus (2019-nCoV).\n\nAimsThis trial aimed to evaluate the safety and efficacy of PrEP with various doses of HCQ against a placebo among high-risk healthcare providers (HCPs).\n\nMethodsA phase II, randomized, placebo-controlled trial was conducted at a tertiary care hospital. A total of 228 HCPs were screened, we included 200 subjects with no active or past SARS-CoV-2 infection. Subjects of experimental groups 1-3 received HCQ in various doses and those in the control group received placebo. The study outcomes in terms of safety and efficacy were monitored. Participants exhibiting COVID-19 symptoms were tested for SARS-CoV-2 during the study and also by the end of the 12th week, with PCR or IgM and IgG serology.\n\nResultsOverall, 146 of 200 participants reported exposure to a confirmed COVID-19 case in the first month, 189 in the 2nd month and 192 were exposed by the 12th week of the study. Moreover, the precautionary practices, i.e. use of personal protective equipment (PPE), significantly varied; initially more than 80% of the exposed HCPs werent ensuring the PPE used by the patients treated by them. However, it gradually developed with the increasing knowledge of the virus. As far as safety is concerned, mild treatment-related side effects were observed among the interventional and placebo arm patients. While none of the participants were critical, and a few had mild illness by the end of the 12th week, requiring only outpatient observation with no hospitalization. There was no significant clinical benefit of PrEP with HCQ as compared to placebo (p>0.05).\n\nConclusionIt is concluded from the study findings that the PrEP HCQ does not significantly prevent illness compatible with COVID-19 or confirmed infection among high-risk HCPs.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Vahe Nafilyan", - "author_inst": "Office for National Statistics" + "author_name": "Fibhaa Syed", + "author_inst": "Department of Medicine, Shaheed Zulfiqar Ali Bhutto Medical University" }, { - "author_name": "Ted Dolby", - "author_inst": "Office for National Statistics" + "author_name": "Mohammad Ali Arif", + "author_inst": "Department of Medicine, Shaheed Zulfiqar Ali Bhutto Medical University" }, { - "author_name": "Cameron Razieh", - "author_inst": "Diabetes Research Centre, University of Leicester" - }, - { - "author_name": "Charlotte Gaughan", - "author_inst": "Office for National Statistics" + "author_name": "Rauf Niazi", + "author_inst": "Department of Medicine, Shaheed Zulfiqar Ali Bhutto Medical University" }, { - "author_name": "Jasper Morgan", - "author_inst": "Office for National Statistics" + "author_name": "Jaffer Bin Baqar", + "author_inst": "Department of Statistics, University of Karachi" }, { - "author_name": "Daniel Ayoubkhani", - "author_inst": "Office for National Statistics" + "author_name": "Ume Laila Hashmi", + "author_inst": "Internal Medicine Shaheed Zulfiqar Ali Bhutto Medical University" }, { - "author_name": "Ann Sarah Walker", - "author_inst": "University of Oxford" + "author_name": "Sadia Batool", + "author_inst": "Internal Medicine Shaheed Zulfiqar Ali Bhutto Medical University" }, { - "author_name": "Kamlesh Khunti", - "author_inst": "Diabetes Research Centre, University of Leicester" + "author_name": "Sadia Ashraf", + "author_inst": "Internal Medicine Shaheed Zulfiqar Ali Bhutto Medical University" }, { - "author_name": "Myer Glickman", - "author_inst": "Office for National Statistics" + "author_name": "Junaid Arshad", + "author_inst": "Internal Medicine Shaheed Zulfiqar Ali Bhutto Medical University" }, { - "author_name": "Thomas Yates", - "author_inst": "Diabetes Research Centre, University of Leicester" + "author_name": "Saira Musarrat", + "author_inst": "Internal Medicine Shaheed Zulfiqar Ali Bhutto Medical University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -778181,67 +778240,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.12.21257117", - "rel_title": "Seven-day COVID-19 quarantine may be too short: assessing post-quarantine transmission risk in four university cohorts", + "rel_doi": "10.1101/2021.05.13.21257141", + "rel_title": "Risk of COVID-19 variant importation - How useful are travel control measures?", "rel_date": "2021-05-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.12.21257117", - "rel_abs": "BackgroundDespite rising rates of vaccination, quarantine remains critical to control SARS-CoV-2 transmission. COVID-19 quarantine length around the world varies in part due to the limited amount of empirical data.\n\nObjectiveTo assess post-quarantine transmission risk for various quarantine lengths.\n\nDesignCohort study.\n\nSettingFour US universities, September 2020 to February 2021.\n\nParticipants3,641 students and staff were identified as close contacts to SARS-CoV-2-positive individuals. They entered strict or non-strict quarantine and were tested on average twice per week for SARS-CoV-2. Strict quarantine included designated housing with a private room, private bathroom and meal delivery. Non-strict quarantine potentially included interactions with household members.\n\nMeasurementsDates of exposure and last negative and first positive tests during quarantine.\n\nResultsOf the 418 quarantined individuals who eventually converted to positive, 11%, 4.2%, and 1.2% were negative and asymptomatic on days 7, 10 and 14, respectively. The US CDC recently shortened its quarantine guidance from 14 to 7 days based on estimates of 2.3-8.6% post-quarantine transmission risk at day 7, significantly below the 11% risk we report here. Notably, 6% of individuals tested positive after day 7 in strict quarantine, versus 14% in non-strict quarantine. Ongoing exposure during quarantine likely explains the higher rate of COVID-19 in non-strict quarantine.\n\nLimitationsQuarantine should be longer for individuals using antigen testing, given antigen testings lower sensitivity than qPCR. Results apply in settings in which SAR-CoV-2 variants do not affect latent period.\n\nConclusionsTo maintain the 5% transmission risk that the CDC used in its guidance, our data suggest that quarantine with qPCR testing 1 day before intended release should extend to 10 days for non-strict quarantine.\n\nFunding SourceNone.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.13.21257141", + "rel_abs": "We consider models for the importation of a new variant COVID-19 strain in a location already seeing propagation of a resident variant. By distinguishing contaminations generated by imported cases from those originating in the community, we are able to evaluate the contribution of importations to the dynamics of the disease in a community. We find that after an initial seeding, the role of importations becomes marginal compared to that of community-based propagation. We also evaluate the role of two travel control measures, quarantine and travel interruptions. We conclude that quarantine is an efficacious way of lowering importation rates, while travel interruptions have the potential to delay the consequences of importations but need to be applied within a very tight time window following the initial emergence of the variant.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Andrew Bo Liu", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Dan Davidi", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Hannah Emily Landsberg", - "author_inst": "Boston University" - }, - { - "author_name": "Maria Francesconi", - "author_inst": "Harvard University Health Services" - }, - { - "author_name": "Judy T Platt", - "author_inst": "Boston University" - }, - { - "author_name": "Giang T Nguyen", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Sehyo Yune", - "author_inst": "Northeastern University" - }, - { - "author_name": "Anastasia Deckard", - "author_inst": "Duke University" - }, - { - "author_name": "Jamie Puglin", - "author_inst": "Duke University" + "author_name": "Julien Arino", + "author_inst": "University of Manitoba" }, { - "author_name": "Steven B Haase", - "author_inst": "Duke University School of Medicine" + "author_name": "Pierre-Yves Boelle", + "author_inst": "IPLESP, Sorbonne Universite" }, { - "author_name": "Davidson H Hamer", - "author_inst": "Boston University School of Public Health" + "author_name": "Evan M Milliken", + "author_inst": "University ofLouisville" }, { - "author_name": "Michael Springer", - "author_inst": "Harvard Medical School" + "author_name": "Stephanie Portet", + "author_inst": "University of Manitoba" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.12.21257131", @@ -780175,123 +780202,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.07.21256823", - "rel_title": "Evolution of human antibody responses up to one year after SARS-CoV-2 infection", + "rel_doi": "10.1101/2021.05.08.21256885", + "rel_title": "In hospital cardiac arrest in Intensive Care Unit versus non Intensive Care Unit patients with COVID 19. A systematic review and meta analysis", "rel_date": "2021-05-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.07.21256823", - "rel_abs": "Assessment of the kinetics of SARS-CoV-2 antibodies is essential to predict protection against reinfection and durability of vaccine protection. Here, we longitudinally measured Spike (S) and Nucleocapsid (N)-specific antibodies in 1,309 healthcare workers (HCW) including 393 convalescent COVID-19 and 916 COVID-19 negative HCW up to 405 days. From M1 to M7-9 after infection, SARS-CoV-2 antibodies decreased moderately in convalescent HCW in a biphasic model, with men showing a slower decay of anti-N (p=0.02), and a faster decay of anti-S (p=0.0008) than women. At M11-13, anti-N antibodies dramatically decreased (half-life: 210 days) while anti-S stabilized (half-life: 630 days) at a median of 2.41 log Arbitrary Units (AU)/mL (Interquartile Range (IQR): 2.11 -2.75). One case of reinfection was recorded in convalescent HCW (0.47 per 100 person-years) versus 50 in COVID-19 negative HCW (10.11 per 100 person-years). Correlation with live-virus neutralization assay revealed that variants D614G and B.1.1.7, but not B.1.351, were sensitive to anti-S antibodies at 2.3 log AU/mL, while IgG [≥] 3 log AU/mL neutralized all three variants. After SARS-CoV-2 vaccination, anti-S levels reached 4 logs regardless of pre-vaccination IgG levels, type of vaccine, and number of doses. Our study demonstrates a long-term persistence of anti-S IgG antibodies that may protect against reinfection. By significantly increasing cross-neutralizing antibody titers, a single-dose vaccination strengthens protection against escape mutants.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256885", + "rel_abs": "AimTo estimate the incidence of in-hospital cardiac arrest (IHCA) and return of spontaneous circulation (ROSC) in COVID-19 patients, as well as to compare the incidence and outcomes of IHCA in Intensive Care Unit (ICU) versus non-ICU patients with COVID-19.\n\nMethodsWe systematically reviewed the PubMed, Scopus and clinicaltrials.gov databases to identify relevant studies.\n\nResultsEleven studies were included in our study. The pooled prevalence/incidence, pooled odds ratios (OR) and 95% Confidence Intervals (95% CI) were calculated, as appropriate. The quality of the included studies was assessed using appropriate tools. The pooled incidence of IHCA in COVID-19 patients was 7% [95% CI: 4 - 11%; P < 0.0001] and 44% [95% CI: 30 - 58%; P < 0.0001] achieved ROSC. Of those that survived, 58% [95% CI: 42 - 74%; P < 0.0001] had a good neurological outcome (Cerebral Performance Category 1 or 2) and the mortality at the last follow-up was 59% [95% CI: 37 - 81%; P < 0.0001]. A statistically significant higher percentage of ROSC [OR (95% CI): 5.088 (2.852, 9.079); P < 0.0001] was found among ICU patients versus those in the general wards.\n\nConclusionThe incidence of IHCA amongst hospitalized COVID-19 patients is 7%, with 44% of them achieving ROSC. Patients in the ICU were more likely to achieve ROSC than those in the general wards, however the mortality did not differ.\n\nWhat this paper addsSection 1: What is already known on this subject\n\nO_LIMortality in COVID-19 patients ranges between 20% and 40%.\nC_LIO_LIit has been reported that patients with COVID-19 have a high incidence of IHCA and higher mortality.\nC_LIO_LIThis paper aimed to calculate the proportion of COVID-19 patients who experience IHCA and their outcome, as well as compare the outcome of IHCA between ICU and non-ICU patients.\nC_LI\n\nSection 2: What this study adds\n\nO_LIApproximately 7% of hospitalized COVID-19 patients suffer from IHCA and 44% of those achieve ROSC.\nC_LIO_LIThe rate of ROSC was higher in ICU patients, but the rate of mortality did not differe between ICU and non-ICU patients.\nC_LI", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Floriane Gallais", - "author_inst": "Virology Laboratory, Strasbourg University Hospital, Strasbourg, France; Strasbourg University, INSERM, IRM UMR-S 1109, F-67000 Strasbourg, France" - }, - { - "author_name": "Pierre Gantner", - "author_inst": "Virology Laboratory, Strasbourg University Hospital, Strasbourg, France; Strasbourg University, INSERM, IRM UMR-S 1109, F-67000 Strasbourg, France" - }, - { - "author_name": "Timothee Bruel", - "author_inst": "Virus & Immunity Unit, Department of Virology, Institut Pasteur, Paris, France. CNRS UMR 3569, Paris, France. 5Vaccine Research Institute, Creteil, France." - }, - { - "author_name": "Aurelie Velay", - "author_inst": "Virology Laboratory, Strasbourg University Hospital, Strasbourg, France; Strasbourg University, INSERM, IRM UMR-S 1109, F-67000 Strasbourg, France" - }, - { - "author_name": "Delphine Planas", - "author_inst": "Virus & Immunity Unit, Department of Virology, Institut Pasteur, Paris, France. CNRS UMR 3569, Paris, France. 5Vaccine Research Institute, Creteil, France." - }, - { - "author_name": "Marie-Josee Wendling", - "author_inst": "Virology Laboratory, Strasbourg University Hospital, Strasbourg, France;" - }, - { - "author_name": "Sophie Bayer", - "author_inst": "CHU de Strasbourg, Laboratoire de Biochimie Clinique et Biologie Moleculaire, F-67091 Strasbourg, France" - }, - { - "author_name": "Morgane Solis", - "author_inst": "Virology Laboratory, Strasbourg University Hospital, Strasbourg, France; Strasbourg University, INSERM, IRM UMR-S 1109, F-67000 Strasbourg, France;" - }, - { - "author_name": "Elodie Laugel", - "author_inst": "Virology Laboratory, Strasbourg University Hospital, Strasbourg, France; Strasbourg University, INSERM, IRM UMR-S 1109, F-67000 Strasbourg, France" - }, - { - "author_name": "Nathalie Reix", - "author_inst": "CHU de Strasbourg, Laboratoire de Biochimie Clinique et Biologie Moleculaire, F-67091 Strasbourg, France" - }, - { - "author_name": "Anne Schneider", - "author_inst": "CHU de Strasbourg, Departement de Genetique Moleculaire du cancer, F-67091 Strasbourg, France." - }, - { - "author_name": "Ludovic Glady", - "author_inst": "CHU de Strasbourg, Laboratoire de Biochimie Clinique et Biologie Moleculaire, F-67091 Strasbourg, France" - }, - { - "author_name": "Baptiste Panaget", - "author_inst": "Virology Laboratory, Strasbourg University Hospital, Strasbourg, France; Strasbourg University, INSERM, IRM UMR-S 1109, F-67000 Strasbourg, France" - }, - { - "author_name": "Nicolas Collongues", - "author_inst": "Centre d'investigation Clinique INSERM 1434, CHU Strasbourg, France." - }, - { - "author_name": "Marialuisa Partisani", - "author_inst": "CHU de Strasbourg, Trait d Union, F-67091 Strasbourg, France." - }, - { - "author_name": "Jean-Marc Lessinger", - "author_inst": "CHU de Strasbourg, Laboratoire de Biochimie Clinique et Biologie Moleculaire, F-67091 Strasbourg, France" - }, - { - "author_name": "Arnaud Fontanet", - "author_inst": "Emerging Diseases Epidemiology Unit, Department of Global Health, Institut Pasteur, Paris, France" - }, - { - "author_name": "David Rey", - "author_inst": "CHU de Strasbourg, Trait d Union, F-67091 Strasbourg, France." - }, - { - "author_name": "Yves Hansmann", - "author_inst": "CHU de Strasbourg, Service des infectieuses et tropicales, F-67091 Strasbourg, France." - }, - { - "author_name": "Laurence Kling-Pillitteri", - "author_inst": "CHU de Strasbourg, Service de Pathologies Professionnelles, F-67091 Strasbourg, France." + "author_name": "Georgios Mavrovounis", + "author_inst": "Department of Emergency Medicine, University of Thessaly, Faculty of Medicine" }, { - "author_name": "Olivier Schwartz", - "author_inst": "Virus & Immunity Unit, Department of Virology, Institut Pasteur, Paris, France. CNRS UMR 3569, Paris, France. 5Vaccine Research Institute, Creteil, France." + "author_name": "Maria Mermiri", + "author_inst": "Department of Anesthesiology, University of Thessaly, Faculty of Medicine" }, { - "author_name": "Jerome De Seze", - "author_inst": "Centre d'investigation Clinique INSERM 1434, CHU Strasbourg, France." + "author_name": "Athanasios Chalkias", + "author_inst": "Department of Anesthesiology, University of Thessaly, Faculty of Medicine" }, { - "author_name": "Nicolas Meyer", - "author_inst": "CHU de Strasbourg, Service de sante Publique, GMRC, F-67091 Strasbourg, France." + "author_name": "Vishad Sheth", + "author_inst": "Department of Pulmonary & Critical Care Medicine Mount Sinai Morningside, Mount Sinai West, Mount Sinai Beth Israel, Icahn School of Medicine" }, { - "author_name": "Maria Gonzalez", - "author_inst": "CHU de Strasbourg, Service de Pathologies Professionnelles, F-67091 Strasbourg, France." + "author_name": "Vasiliki Tsolaki", + "author_inst": "Department of Intensive Care Medicine, University of Thessaly, Faculty of Medicine" }, { - "author_name": "Catherine Schmidt-Mutter", - "author_inst": "Centre d'investigation Clinique INSERM 1434, CHU Strasbourg, France." + "author_name": "Konstantinos Gourgoulianis", + "author_inst": "Department of Respiratory Medicine, University of Thessaly, Faculty of Medicine" }, { - "author_name": "Samira Fafi-Kremer", - "author_inst": "Virology Laboratory, Strasbourg University Hospital, Strasbourg, France; Strasbourg University, INSERM, IRM UMR-S 1109, F-67000 Strasbourg, France" + "author_name": "Ioannis Pantazopoulos", + "author_inst": "Department of Emergency Medicine, University of Thessaly, Faculty of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2021.05.10.21256942", @@ -782885,31 +782836,39 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.02.09.21250610", - "rel_title": "Pooling of samples for SARS-CoV-2 detection using rapid antigen tests", - "rel_date": "2021-05-13", + "rel_doi": "10.1101/2021.05.08.21256892", + "rel_title": "Impact of vaccination on the COVID-19 pandemic: Evidence from U.S. states", + "rel_date": "2021-05-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21250610", - "rel_abs": "While molecular assays, such as RT-PCR, have been widely used throughout the COVID-19 pandemic, the technique is costly and resource intensive. As a means to reduce costs and increase diagnostic efficiency, pooled testing for RT-PCR has been implemented. However, pooling samples for antigen testing has not been evaluated. We propose a pooling strategy for antigen testing that would significantly expand SARS-CoV-2 surveillance, especially for low-to-middle income countries, schools, and workplaces. Our data demonstrate that combining of up to 20 nasal swab specimens per pool can expand surveillance with antigen tests, even if a pool contains only one positive sample.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256892", + "rel_abs": "Governments worldwide are implementing mass vaccination programs in an effort to end the novel coronavirus (COVID-19) pandemic. Although the approved vaccines exhibited high efficacies in randomized controlled trials1,2, their population effectiveness in the real world remains less clear, thus casting uncertainty over the prospects for herd immunity. In this study, we evaluated the effectiveness of the COVID-19 vaccination program and predicted the path to herd immunity in the U.S. Using data from 12 October 2020 to 7 March 2021, we estimated that vaccination reduced the total number of new cases by 4.4 million (from 33.0 to 28.6 million), prevented approximately 0.12 million hospitalizations (from 0.89 to 0.78 million), and decreased the population infection rate by 1.34 percentage points (from 10.10% to 8.76%). We then built a Susceptible-Infected-Recovered (SIR) model with vaccination to predict herd immunity. Our model predicts that if the average vaccination pace between January and early March 2021 (2.08 doses per 100 people per week) is maintained, the U.S. can achieve herd immunity by the last week of July 2021, with a cumulative vaccination coverage of 60.2%. Herd immunity could be achieved earlier with a faster vaccination pace, lower vaccine hesitancy, or higher vaccine effectiveness. These findings improve our understanding of the impact of COVID-19 vaccines and can inform future public health policies regarding vaccination, especially in countries with ongoing vaccination programs.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Nol Salcedo", - "author_inst": "E25Bio, Inc." + "author_name": "Xiao Chen", + "author_inst": "University of International Business and Economics" }, { - "author_name": "Alexander Harmon", - "author_inst": "E25Bio, Inc." + "author_name": "Hanwei Huang", + "author_inst": "City University of Hong Kong" }, { - "author_name": "Bobby Brooke Herrera", - "author_inst": "E25Bio, Inc." + "author_name": "Jiandong Ju", + "author_inst": "Tsinghua University" + }, + { + "author_name": "Ruoyan Sun", + "author_inst": "University of Alabama at Birmingham" + }, + { + "author_name": "Jialiang Zhang", + "author_inst": "Tsinghua University" } ], - "version": "2", - "license": "cc_by_nc_nd", + "version": "1", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.05.08.21256881", @@ -784739,113 +784698,65 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.05.12.443228", - "rel_title": "Interferon-armed RBD dimer enhances the immunogenicity of RBD for sterilizing immunity against SARS-CoV-2", + "rel_doi": "10.1101/2021.05.12.443645", + "rel_title": "Neutralization potential of Covishield vaccinated individuals against B.1.617.1", "rel_date": "2021-05-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.12.443228", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global crisis, urgently necessitating the development of safe, efficacious, convenient-to-store, and low-cost vaccine options. A major challenge is that the receptor-binding domain (RBD)-only vaccine fails to trigger long-lasting protective immunity if used solely for vaccination. To enhance antigen processing and cross-presentation in draining lymph nodes (DLNs), we developed an interferon (IFN)-armed RBD dimerized by immunoglobulin fragment (I-R-F). I-R-F efficiently directs immunity against RBD to DLN. A low dose of I-R-F induces not only high titer long-lasting neutralizing antibodies but also comprehensive T cell responses than RBD, and even provides comprehensive protection in one dose without adjuvant. This study shows that the I-R-F vaccine provides rapid and complete protection throughout upper and lower respiratory tracts against high dose SARS-CoV-2 challenge in rhesus macaques. Due to its potency and safety, this engineered vaccine may become one of the next-generation vaccine candidates in the global race to defeat COVID-19.", - "rel_num_authors": 24, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.12.443645", + "rel_abs": "Covishield comprises the larger proportion in the vaccination program in India. Hence, it is of utmost importance to understand neutralizing capability of vaccine against the B.1.617.1 variant which is considered to responsible for surge of the cases in India. The neutralizing-antibody (NAb) titer against B.1.167.1 and prototype B.1 variant (D614G) was determined of the vaccine sera (4 weeks after second dose) of COVID-19 naive subjects (n=43) and COVID-19 recovered subjects (n=18). The results demonstrated that sera of COVID-19 recovered subjects (n=18) who received two doses of Covishield have higher NAb response compared to the COVID-19 naive with a significant difference (p<0.0001) in NAb titer against B.1 and B.1.617.1 In-spite of reduction in the neutralizing titer against B.1.617.1 variant; Covishield vaccine-induced antibodies are likely to be protective to limit the severity and mortality of the disease in the vaccinated individuals.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Shiyu Sun", - "author_inst": "Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China University of Chinese Academy of Science" - }, - { - "author_name": "Yueqi Cai", - "author_inst": "Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China University of Chinese Academy of Science" - }, - { - "author_name": "Tian-Zhang Song", - "author_inst": "Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunm" - }, - { - "author_name": "Yang Pu", - "author_inst": "Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, Beijing, 100005, China" - }, - { - "author_name": "Lin Cheng", - "author_inst": "Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen, 518112, Guangdong Province, China" - }, - { - "author_name": "Hairong Xu", - "author_inst": "Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China" - }, - { - "author_name": "Chaoyang Meng", - "author_inst": "Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China" - }, - { - "author_name": "Yifan Lin", - "author_inst": "Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China University of Chinese Academy of Science" - }, - { - "author_name": "Jin Sun", - "author_inst": "State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou" - }, - { - "author_name": "Silin Zhang", - "author_inst": "School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China." - }, - { - "author_name": "Yu Gao", - "author_inst": "Key Laboratory of Protein and Peptide Pharmaceuticals, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Bei" - }, - { - "author_name": "Jian-Bao Han", - "author_inst": "Kunming National High-level Biosafety Research Center for Non-human Primates, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy o" - }, - { - "author_name": "Xiao-Li Feng", - "author_inst": "Kunming National High-level Biosafety Research Center for Non-human Primates, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy o" + "author_name": "Pragya Yadav", + "author_inst": "ICMR-National Institute of Virology" }, { - "author_name": "Dan-Dan Yu", - "author_inst": "Kunming National High-level Biosafety Research Center for Non-human Primates, Center for Biosafety Mega-Science, Kunming Institute of Zoology, Chinese Academy o" + "author_name": "Gajanan N Sapkal", + "author_inst": "ICMR-National Institute of Virology" }, { - "author_name": "Yalan Zhu", - "author_inst": "Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China" + "author_name": "Priya Abraham", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India" }, { - "author_name": "Pu Gao", - "author_inst": "Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China" + "author_name": "Gururaj Deshpande", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India" }, { - "author_name": "Haidong Tang", - "author_inst": "School of Pharmaceutical Sciences, Tsinghua University, Beijing 100084, China." + "author_name": "Dimpal Nyayanit", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India" }, { - "author_name": "Jincun Zhao", - "author_inst": "State Key Laboratory of Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou" + "author_name": "Deepak Y Patil", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India" }, { - "author_name": "Jiaming Yang", - "author_inst": "Livzon Mabpharm Inc., Zhuhai, Guangdong 519045, China" + "author_name": "Nivedita Gupta", + "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India" }, { - "author_name": "Zenxiang Hu", - "author_inst": "Livzon Mabpharm Inc., Zhuhai, Guangdong 519045, China" + "author_name": "Rima R Sahay", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India" }, { - "author_name": "Zheng Zhang", - "author_inst": "Institute for Hepatology, National Clinical Research Center for Infectious Disease, Shenzhen Third Peoples Hospital, Shenzhen, 518112, Guangdong Province, China" + "author_name": "Anita Shete", + "author_inst": "Indian Council of Medical Research-National Institute of Virology, Pune, India" }, { - "author_name": "Yang-Xin Fu", - "author_inst": "UT southwestern medical center" + "author_name": "Sanjay Kumar", + "author_inst": "Department of Neurosurgery, Command Hospital (Southern Command), Armed Forces Medical College (AFMC), Pune, Maharashtra, India" }, { - "author_name": "Yong-Tang Zheng", - "author_inst": "Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunm" + "author_name": "Samiran Panda", + "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India" }, { - "author_name": "Hua Peng", - "author_inst": "Key Laboratory of Infection and Immunity, Institute of Biophysics, Chinese Academy of Sciences, Beijing 100101, China" + "author_name": "Balram Bhargava", + "author_inst": "Indian Council of Medical Research, V. Ramalingaswami Bhawan, Ansari Nagar, New Delhi, India" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -787469,49 +787380,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.10.21256995", - "rel_title": "Magnetofluidic platform for rapid multiplexed screening of SARS-CoV-2 variants and respiratory pathogens", + "rel_doi": "10.1101/2021.05.11.21257011", + "rel_title": "COVID-19 in patients hospitalized and healthcare workers: what have changed after the first wave in a university hospital", "rel_date": "2021-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.10.21256995", - "rel_abs": "The rise of highly transmissible SARS-CoV-2 variants brings new challenges and concerns with vaccine efficacy, diagnostic sensitivity, and public health responses in the fight to end the pandemic. Widespread detection of variant strains will be critical to inform policy decisions to mitigate further spread, and post-pandemic multiplexed screening of respiratory viruses will be necessary to properly manage patients presenting with similar respiratory symptoms. In this work, we have developed a portable, magnetofluidic cartridge platform for automated PCR testing in <30 min. Cartridges were designed for multiplexed detection of SARS-CoV-2 with either distinctive variant mutations or with Influenza A and B. The platform demonstrated a limit of detection down to 2 copies/{micro}L SARS-CoV-2 RNA with successful identification of B.1.1.7 and B.1.351 variants. The multiplexed SARS-CoV-2/Flu assay was validated using archived clinical nasopharyngeal swab eluates (n = 116) with an overall sensitivity/specificity of 98.1%/95.2%, 85.7%/100%, 100%/98.2%, respectively, for SARS-CoV-2, Influenza A, and Influenza B. Further testing with saliva (n = 14) demonstrated successful detection of all SARS-CoV-2 positive samples with no false-positives.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.11.21257011", + "rel_abs": "ObjectiveTo assess the COVID-19 frequency rates in hospitalized patients (HP) and healthcare workers (HCW), viral load inference, and the impact of vaccination and variants of concern (VOC) during the first pandemic wave.\n\nMethodsWe evaluated the COVID-19 diagnostics at Hospital Sao Paulo, Brazil, from March 2020 to April 2021, in 10,202 samples (6,502 HP and 3,700 HCW) tested by RT-qPCR, inferring viral load by cycle threshold (Ct) values, and frequency rates.\n\nResultsSARS-CoV-2 was detected in 31.27% of individuals (32.23% HP and 29.80% HCW). The mean age of HP positives was 57.26 {+/-} 18.29 years (median = 59), with a mean Ct value of 25.55 {+/-} 6.07. Neither age nor Ct values in both groups have significantly differed during the first and second waves or even since the predominance of VOC P.1 on March 2021.\n\nConclusionsThe COVID-19 epidemic curves of HP and HCW accompanied the variations reported in Sao Paulo city, as well as the variation of hospitalization and occupancy of ICU beds. The VOC P.1 has no impact on the viral load, since its predominance in March 2021. The vaccination of HCW may have contributed to a decrease in the positivity rates, although more studies will provide a better understanding of the impact of immunization on the COVID-19 pandemic.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Alexander Y Trick", - "author_inst": "Johns Hopkins University" + "author_name": "Luiz Vinicius Leao Moreira Sr.", + "author_inst": "Federal University of Sao Paulo" }, { - "author_name": "Fan-En Chen", - "author_inst": "Johns Hopkins University" + "author_name": "Gabriela Barbosa", + "author_inst": "Federal University of Sao Paulo" }, { - "author_name": "Liben Chen", - "author_inst": "Johns Hopkins University" + "author_name": "Luciano Kleber de Souza Luna", + "author_inst": "Universidade Federal de Sao Paulo" }, { - "author_name": "Pei-Wei Lee", - "author_inst": "Johns Hopkins University" + "author_name": "Alberto Fernando Oliveira Justo", + "author_inst": "Federal University of Sao Paulo" }, { - "author_name": "Alexander C Hasnain", - "author_inst": "Johns Hopkins University" + "author_name": "Ana Paula Cunha Chaves", + "author_inst": "Federal University of Sao Paulo" }, { - "author_name": "Heba H Mostafa", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Danielle Dias Conte", + "author_inst": "Federal University of Sao Paulo" }, { - "author_name": "Karen C Carroll", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Joseane Mayara Almeida Carvalho", + "author_inst": "Federal University of Sao Paulo" }, { - "author_name": "Tza-Huei Wang", - "author_inst": "Johns Hopkins University" + "author_name": "Ana Helena Perosa", + "author_inst": "Federal University of Sao Paulo" + }, + { + "author_name": "Klinger Soares Faico-Filho", + "author_inst": "Federal University of Sao Paulo" + }, + { + "author_name": "Clarice Neves Camargo", + "author_inst": "Federal University of Sao Paulo" + }, + { + "author_name": "Nancy cristina junqueira Bellei", + "author_inst": "Federal University of Sao Paulo" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -789519,73 +789442,101 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2021.05.08.21256775", - "rel_title": "Intra-host evolution provides for continuous emergence of SARS-CoV-2 variants", + "rel_doi": "10.1101/2021.05.08.21256619", + "rel_title": "Characterization of the emerging B.1.621 variant of interest of SARS-CoV-2", "rel_date": "2021-05-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256775", - "rel_abs": "Variants of concern (VOC) in SARS-CoV-2 refer to viral genomes that differ significantly from the ancestor virus and that show the potential for higher transmissibility and/or worse clinical progression. VOC have the potential to disrupt ongoing public health measures and vaccine efforts. Yet, little is known regarding how frequently different viral variants emerge and under what circumstances. We report a longitudinal study to determine the degree of SARS-CoV-2 sequence evolution in 94 COVID-19 cases and to estimate the frequency at which highly diverse variants emerge. 2 cases accumulated [≥]9 single-nucleotide variants (SNVs) over a two-week period and 1 case accumulated 23 SNVs over a three-week period, including three non-synonymous mutations in the Spike protein (D138H, E554D, D614G). We estimate that in 2% of COVID cases, viral variants with multiple mutations, including in the Spike glycoprotein, can become the dominant strains in as little as one month of persistent in patient virus replication. This suggests the continued local emergence of VOC independent of travel patterns. Surveillance by sequencing for (i) viremic COVID-19 patients, (ii) patients suspected of re-infection, and (iii) patients with diminished immune function may offer broad public health benefits.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.08.21256619", + "rel_abs": "The genetic diversity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has the potential to impact the virus transmissibility and the escape from natural infection- or vaccine-elicited neutralizing antibodies. Here, representative samples from circulating SARS-CoV-2 in Colombia between January and April 2021, were processed for genome sequencing and lineage determination following the nanopore amplicon ARTIC network protocol and PANGOLIN pipeline. This strategy allowed us to identify the emergence of the B.1.621 lineage, considered a variant of interest (VOI) with the accumulation of several substitutions affecting the Spike protein, including the amino acid changes T95I, Y144T, Y145S and the insertion 146N in the N-terminal domain, R346K, E484K and N501Y in the Receptor-binding Domain (RBD) and P681H1 in the S1/S2 cleavage site of the Spike protein. The rapid increase in frequency and fixation in a relatively short time in Magdalena, Atlantico, Bolivar, Bogota D.C, and Santander that were near the theoretical herd immunity suggests an epidemiologic impact. Further studies will be required to assess the biological and epidemiologic roles of the substitution pattern found in the B.1.621 lineage.\n\nHighlightsO_LIMonitoring the emergence of new variants of SARS-CoV-2 in real time is a worldwide priority.\nC_LIO_LIEmerging variants of SARS-CoV-2 may have high impact biological implications for public health\nC_LIO_LIThe SARS-CoV-2 B.1.621 variant of interest was characterized by several substitutions: T95I, Y144T, Y145S, ins146N, R346K, E484K, N501Y and P681H in spike protein.\nC_LI", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Justin Landis", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Katherine Laiton-Donato", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Razia Moorad", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Carlos Franco-Munoz", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Linda J. Pluta", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Diego Alejandro Alvarez-Diaz", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Carolina Caro-Vegas", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Hector Ruiz-Moreno", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Ryan P. McNamara", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Jose Usme-Ciro", + "author_inst": "Universidad Cooperativa de Colombia, Santa Marta, Colombia - Instituto Nacional de Salud" }, { - "author_name": "Anthony B Eason", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Diego Prada", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Aubrey Bailey", - "author_inst": "Kuopio Center for Gene and Cell Therapy" + "author_name": "Jhonnatan Reales", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Femi Cleola S. Villamor", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Sheryll Corchuelo", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Angelic Juarez", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Maria Herrera-sepulveda", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Jason P Wong", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Julian Naizaque", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Brian Yang", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Gerardo Santamaria", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Grant S. Broussard", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Jorge Rivera", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Blossom Damania", - "author_inst": "Department of Microbiology and Immunology, The University of North Carolina at Chapel Hill School of Medicine" + "author_name": "Paola Rojas", + "author_inst": "Instituto Nacional de Salud" }, { - "author_name": "Dirk Dittmer", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Andres Cardona Rios", + "author_inst": "Laboratorio genomico One Health - Universidad Nacional de Colombia" + }, + { + "author_name": "Juan Hernandez-Ortiz", + "author_inst": "Laboratorio genomico One Health Universidad Nacional de Colombia" + }, + { + "author_name": "Diana Malo", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Franklin Prieto", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Fernando Ruiz-Gomez", + "author_inst": "Ministerio de Salud y Proteccion Social de Colombia. Bogota Colombia." + }, + { + "author_name": "Magdalena Wiesner", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Martha Lucia Ospina-Martinez", + "author_inst": "Instituto Nacional de Salud" + }, + { + "author_name": "Marcela Mercado-Reyes", + "author_inst": "Instituto Nacional de Salud" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -791969,41 +791920,81 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.05.08.443275", - "rel_title": "In-vivo Protection from SARS-CoV-2 infection by ATN-161 in k18-hACE2 transgenic mice", + "rel_doi": "10.1101/2021.05.07.442971", + "rel_title": "Expansion of tissue-resident CD8+ T cells and CD4+ Th17 cells in the nasal mucosa following mRNA COVID-19 vaccination", "rel_date": "2021-05-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.08.443275", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an infectious disease that has spread worldwide. Current treatments are limited in both availability and efficacy, such that improving our understanding of the factors that facilitate infection is urgently needed to more effectively treat infected individuals and to curb the pandemic. We and others have previously demonstrated the significance of interactions between the SARS-CoV-2 spike protein, integrin 5{beta}1, and human ACE2 to facilitate viral entry into host cells in vitro. We previously found that inhibition of integrin 5{beta}1 by the clinically validated small peptide ATN-161 inhibits these spike protein interactions and cell infection in vitro. In continuation with our previous findings, here we have further evaluated the therapeutic potential of ATN-161 on SARS-CoV-2 infection in k18-hACE2 transgenic (SARS-CoV-2 susceptible) mice in vivo. We discovered that treatment with single- or repeated intravenous doses of ATN-161 (1 mg/kg) within 48 hours after intranasal inoculation with SARS-CoV-2 lead to a reduction of lung viral load, viral immunofluorescence and improved lung histology in a majority of mice 72 hours post-infection. Furthermore, ATN-161 reduced SARS-CoV-2-induced increased expression of lung integrin 5 and v (an 5-related integrin that has also been implicated in SARS-CoV-2 interactions) as well as the C-X-C motif chemokine ligand 10 (Cxcl10), further supporting the potential involvement of these integrins, and the anti-inflammatory potential of ATN-161, respectively, in SARS-CoV-2 infection. To the best of our knowledge, this is the first study demonstrating the potential therapeutic efficacy of targeting integrin 5{beta}1 in SARS-CoV-2 infection in vivo and supports the development of ATN-161 as a novel SARS-CoV-2 therapy.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.05.07.442971", + "rel_abs": "Vaccines against SARS-CoV-2 have shown high efficacy in clinical trials, yet a full immunologic characterization of these vaccines, particularly within the upper respiratory tract, remains lacking. We enumerated and phenotyped T cells in nasal mucosa and blood before and after vaccination with the Pfizer-BioNTech COVID-19 vaccine (n =21). Tissue-resident memory (Trm) CD8+ T cells expressing CD69+CD103+ expanded [~]12 days following the first and second doses, by 0.31 and 0.43 log10 cells per swab respectively (p=0.058 and p=0.009 in adjusted linear mixed models). CD69+CD103+CD8+ T cells in the blood decreased post-vaccination. Similar increases in nasal CD8+CD69+CD103-T cells were observed, particularly following the second dose. CD4+ Th17 cells were also increased in abundance following both doses. Following stimulation with SARS-CoV-2 spike peptides, CD8+ T cells increased expression of CD107a and CD154. These data suggest that nasal T cells may be induced and contribute to the protective immunity afforded by this vaccine.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Amruta Narayanappa", - "author_inst": "Tulane School of Medicine" + "author_name": "Aloysious Ssemaganda", + "author_inst": "University of Manitoba" }, { - "author_name": "Elizabeth B Engler-Chiurazzi", - "author_inst": "Tulane University" + "author_name": "Huong Mai Nguyen", + "author_inst": "University of Manitoba" }, { - "author_name": "Isabel C Murray-Brown", - "author_inst": "Tulane University" + "author_name": "Faisal Nuhu", + "author_inst": "University of Manitoba" }, { - "author_name": "Timothy E Gressett", - "author_inst": "Tulane University" + "author_name": "Naima Jahan", + "author_inst": "University of Manitoba" }, { - "author_name": "Ifechukwude J Biose", - "author_inst": "Tulane University" + "author_name": "Catherine M Card", + "author_inst": "Public Health Agency of Canada" }, { - "author_name": "Wesley H Chastain", - "author_inst": "Tulane University" + "author_name": "Sandra Kiazyk", + "author_inst": "Public Health Agency of Canada" }, { - "author_name": "Gregory Bix", - "author_inst": "Tulane University" + "author_name": "Giulia Severini", + "author_inst": "University of Manitoba" + }, + { + "author_name": "Yoav Keynan", + "author_inst": "University of Manitoba" + }, + { + "author_name": "Ruey-Chyi Su", + "author_inst": "Public Health Agency of Canada" + }, + { + "author_name": "Hezhao Ji", + "author_inst": "Public Health Agency of Canada" + }, + { + "author_name": "Bernard Abrenica", + "author_inst": "Public Health Agency of Canada" + }, + { + "author_name": "Paul J McLaren", + "author_inst": "Public Health Agency of Canada" + }, + { + "author_name": "Blake Ball", + "author_inst": "Public Health Agency of Canada" + }, + { + "author_name": "Jared Bullard", + "author_inst": "Cadham Provincial Laboratory, Manitoba" + }, + { + "author_name": "Paul Van Caeseele", + "author_inst": "Cadham Provincial Laboratory, Manitoba" + }, + { + "author_name": "Derek Stein", + "author_inst": "Cadham Provincial Laboratory, Manitoba" + }, + { + "author_name": "Lyle McKinnon", + "author_inst": "University of Manitoba" } ], "version": "1", @@ -793563,83 +793554,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.05.05.21256475", - "rel_title": "Extracorporeal membrane oxygenation in COVID-19 patients and in-hospital mortality: results from the Brazilian Registry using a propensity score matched analysis", + "rel_doi": "10.1101/2021.05.06.21253948", + "rel_title": "The first GAEN-based COVID-19 contact tracing app in Norway identifies 80% of close contacts in \"real life\" scenarios.", "rel_date": "2021-05-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.05.21256475", - "rel_abs": "Around 5% of coronavirus disease 2019 (COVID-19) patients develop critical disease, with severe pneumonia and acute respiratory distress syndrome (ARDS). In these cases, extracorporeal membrane oxygenation (ECMO) may be considered when conventional therapy fails. This study aimed to assess the clinical characteristics and in-hospital outcomes of COVID-19 patients with ARDS refractory to standard lung-protective ventilation and pronation treated with ECMO support and to compare them to patients who did not receive ECMO. Patients were selected from the Brazilian COVID-19 Registry. At the moment of the analysis, 7,646 patients were introduced in the registry, eight of those received ECMO support (0.1%). The convenience sample of patients submitted to ECMO was compared to control patients selected by genetic matching for gender, age, comorbidities, pronation, ARDS and hospital, in a 5:1 ratio. From the 48 patients included in the study, eight received ECMO and 40 were matched controls. There were no significant differences in demographic, clinical and laboratory characteristics. Mortality was higher in the ECMO group (n = 7; 87.5%) when compared with controls (n = 17; 42.5%), (p=0.048). In conclusion, COVID 19 patients with ARDS refractory to conventional therapy who received ECMO support had worse outcomes to patients who did not receive ECMO. Our findings are not different from previous studies including a small number of patients, however there is a huge difference from Extracorporeal Life Support Organization results, which encourages us to keep looking for our best excellence.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.06.21253948", + "rel_abs": "The COVID-19 response in most countries depends on testing, isolation, contact tracing, and quarantine, which is labor- and time consuming. Therefore, several countries worldwide launched Bluetooth based apps as supplemental tools. We evaluated the new Norwegian GAEN (Google Apple Exposure Notification) based contact tracing app \"Smittestopp\" under two relevant simulated scenarios, namely standing in a queue and riding public transport.\n\nWe compared two configurations (C1: 58/63 dBm; C2: 58/68 dBm) with multiple weights (1.0-2.5) and time thresholds (10-15 min), by calculating notification rates among close contacts ([≤]2 meters, [≥]15 min) and other non-close contacts. In addition, we estimated the effect of using different operating systems and locations of phone (hand/pocket) using {chi}2.\n\nC2 resulted in significantly higher notification rates than C1 (p-value 0.05 - 0.005). The optimal setting resulted in notifications among 80% of close contacts and 34% of other contacts, using C2 with weights of 2.0 for the low and 1.5 for the middle bucket with a 13-minutes time threshold. Among other contacts, the notification rate was 67% among those [≤]2 meters for <15 minutes compared to 19% among those >2 meters (p=0.004). Significantly (p-values 0.046 - 0.001) lower notification rates were observed when using the iOS operating systems or carrying the phone in the pocket instead of in the hand.\n\nThis study highlights the importance of testing and optimizing the performance of contact tracing apps under \"real life\" conditions to optimized configuration for identifying close contacts.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Daniela Ponce", - "author_inst": "Faculdade de Medicina de Botucatu. Universidade Estadual Paulista Julio de Mesquita Filho" - }, - { - "author_name": "Milena Soriano Marcolino", - "author_inst": "Hospital Universitario, Universidade Federal de Minas Gerais" - }, - { - "author_name": "Magda Carvalho Pires", - "author_inst": "Departamento de Estatistica, Universidade Federal de Minas Gerais." - }, - { - "author_name": "Rafael Lima Rodrigues de Carvalho", - "author_inst": "Instituto de Avaliacaoo de Tecnologia em Saude" - }, - { - "author_name": "Heloisa Reniers Vianna", - "author_inst": "Hospital Universitario Ciencias Medicas" - }, - { - "author_name": "Matheus Carvalho Alves Nogueira", - "author_inst": "Hospitais da Rede Mater Dei" - }, - { - "author_name": "Fernando Antonio Botoni", - "author_inst": "Hospital Julia Kubitschek" + "author_name": "Hinta Meijerink", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Fernando Graca Aranha", - "author_inst": "Hospital SOS Cardio" + "author_name": "Elisabeth H. Madslien", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Andre Soares de Moura Costa", - "author_inst": "Hospitais da Rede Mater Dei" + "author_name": "Camilla Mauroy", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Giovanna Grunewald Vietta", - "author_inst": "Hospital SOS Cardio" + "author_name": "Mia Karoline Johansen", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Felipe Ferraz Martins Graca Aranha", - "author_inst": "Hospital SOS Cardio" + "author_name": "Sindre Mogster Braaten", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Maria Clara Pontello Barbosa Lima", - "author_inst": "Universidade Federal de Ouro Preto. Hospitais da Rede Mater Dei." + "author_name": "Christine Ursin Steen Lunde", + "author_inst": "Norsk Helsenett SF" }, { - "author_name": "Ana Paula Beck da Silva Etges", - "author_inst": "Universidade Federal do Rio Grande do Sul, Instituto de Avaliacao de Tecnologia em Saude" - }, - { - "author_name": "Antonio Tolentino Nogueira de Sa", - "author_inst": "Faculty of Medicine, Universidade Federal de Minas Gerais" + "author_name": "Trude Margrete Arnesen", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Luana Martins Oliveira", - "author_inst": "CEPEAD, Universidade Federal de Minas Gerais" + "author_name": "Siri Laura Feruglio", + "author_inst": "Norwegian Institute of Public Health" }, { - "author_name": "Carisi Anne Polanczyk", - "author_inst": "Universidade Federal do Rio Grande do Sul, Instituto de Avaliacao de Tecnologia em Saude" + "author_name": "Karin Maria Nygard", + "author_inst": "Norwegian Institute of Public Health" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.05.06.21256282", @@ -795929,91 +795892,119 @@ "category": "emergency medicine" }, { - "rel_doi": "10.1101/2021.05.04.21256609", - "rel_title": "SARS-CoV-2 infection and reinfection in a seroepidemiological workplace cohort in the United States", + "rel_doi": "10.1101/2021.05.04.21256597", + "rel_title": "SARS-CoV-2 seroprevalence in Germany - a population based sequential study in five regions", "rel_date": "2021-05-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21256609", - "rel_abs": "Identifying the extent of SARS-CoV-2 reinfection is crucial for understanding possible long-term epidemic dynamics. We analysed longitudinal PCR and serological testing data from a prospective cohort of 4411 US employees in four states between April 2020 and February 2021. We conducted a multivariable logistic regression investigating the association between baseline serological status and subsequent PCR test result in order to calculate an odds ratio for reinfection. We estimated an adjusted odds ratio of 0.09 (95% CI: 0.005 - 0.48) for reinfection, implying that the presence of SARS-CoV-2 antibodies at baseline is associated with around 91% reduced odds of a subsequent PCR positive test. This suggests that primary infection with SARS-CoV-2 provides protection against reinfection in the majority of individuals, at least over a sixth month time period. We also highlight two major sources of bias and uncertainty to be considered when estimating reinfection risk, confounders and the choice of baseline time point, and show how to account for both in our analysis.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.04.21256597", + "rel_abs": "Prevalence of SARS-CoV-2 antibodies is an essential indicator to guide measures. Few population-based estimates are available in Germany. We determine seroprevalence allowing comparison between regions, time points, socio-demographic and health-related factors.\n\nMuSPAD is a sequential multi-local seroprevalence study. We randomly recruited adults in five counties with differing cumulative SARS-CoV-2 incidence July 2020 -February 2021. Serostatus was determined using Spike S1-specific IgG ELISA. We determined county-wise proportions of seropositivity. We assessed underestimation of infections, county and age specific infection fatality risks, and association of seropositivity with demographic, socioeconomic and health factors.\n\nWe found seroprevalence of 2.4 % (95%CI: 1.8-3.1%) for Reutlingen in June 2020 (stage 1) which increased to 2.9% (95%CI: 2.1-3.8%) in October (stage 2), Freiburg stage 1 1.5% (95% CI: 1.1-2.1%) vs. 2.5% (95%CI: 1.8-3.4%), Aachen stage 1 2.3% (95% CI: 1.7-3.1%) vs. 5.4% (95%CI: 4.4-6.6%), Osnabruck 1.3% (95% CI: 1.0-1.9%) and Magdeburg in Nov/Dec 2020. 2.4% (95%CI 1.9-3.1%). Number needed to quarantine to prevent one infection was 8.2. The surveillance detection ratio (SDR) between number of infections based on our results and number reported to health authorities ranged from 2.5-4.5. Participants aged 80+ had lower SDR. Infection fatality estimates ranged from 0.2-2.4%. Lower education was associated with higher, smoking with lower seropositivity.\n\nSeroprevalence remained low until December 2020 with high underdetection. The second wave from November 2020 to February 2021 resulted in additional 2-5% of the population being infected. Detected age specific differences of SDR should be taken into account in modelling and forecasting COVID-19 morbidity.\n\nFundingThe Helmholtz Association, European Unions Horizon 2020 research and innovation programme [grant number 101003480] and intramural funds of the Helmholtz Centre for infection (HZI).\n\nHighlightsO_ST_ABSEvidence before this studyC_ST_ABSSeroepidemiological surveys on SARS-CoV-2 are a useful tool to track the transmission during the epidemic. We searched PubMed/the pre-print server medRxiv and included web-based reports from German health organizations using the keywords \"seroprevalence\", \"SARS-CoV-2\", \"Germany\" and similar other English and German terms in the period from January 1st, 2020 until March 2021. We identified 30 published studies in Germany which mostly report low SARS-CoV-2 seroprevalence (<5%). Most of these surveys were so-called hotspot studies which assessed seroprevalence after localized outbreaks or examined seroprevalence of specific population groups such as e.g. medical staff. Few studies are either population-based or blood donor-based, but do not allow comparisons between regions. To date, we only consider the Corona sub-study of the Rhineland study similar to MuSPAD. It reports a low SARS-CoV-2 seroprevalence (46/4755; 0.97%; 95% CI: 0.72-1.30). Based on this, almost the entire German population remained susceptible to a SARS-CoV-2 infection by the end of 2020.\n\nAdded value of this studyWe provide the first comprehensive, high-precision multi-region population-based SARS-CoV-2 seroprevalence study with representative sampling following the WHO protocol in Germany. By measuring SARS-CoV-2 IgG, we explore immunity at regional and national level over time. We also assess risk factors and sample each region twice, which permits to monitor seroprevalence progression throughout the epidemic in different exemplary German regions.\n\nImplications of all the available evidenceOur results show low seroprevalence (<3%) until Mid-December 2020 in all regions. While estimates in Reutlingen, Aachen, Freiburg and Osnabruck reflect low seroprevalence mostly after the first wave, the survey in Magdeburg cumulatively already represents the beginning of the second wave. The number needed to quarantine to prevent one infection was 8.2 in our study. We also show that for the first wave reported infections reflected overall around 25% of those actually infected rising to 40-50% in the second wave. A slightly raised infection risk could be shown for persons with lower education.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Emilie Finch", - "author_inst": "Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" + "author_name": "Daniela Gornyk", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Rachel Lowe", - "author_inst": "Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" + "author_name": "Manuela Harries", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Stephanie Fischinger", - "author_inst": "Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA and Institut fur HIV Forschung, Universitat Duisburg-Essen, Duisburg, Germany" + "author_name": "Stephan Gloeckner", + "author_inst": "Helmholtz Center for Infection Research" }, { - "author_name": "Michael de St Aubin", - "author_inst": "Harvard Humanitarian Initiative, Cambridge, MA, USA" + "author_name": "Monika Strengert", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Sameed M. Siddiqui", - "author_inst": "Computational and Systems Biology Program, Massachusetts Institute of Technology and Broad Institute of MIT and Harvard, Cambridge, MA, USA" + "author_name": "Tobias Kerrinnes", + "author_inst": "Helmholtz-Institute for RNA-based Infection Research, Department: RNA-Biology of Bacterial Infections" }, { - "author_name": "Diana Dayal", - "author_inst": "Space Exploration Technologies Corp" + "author_name": "Gerhard Bojara", + "author_inst": "Health service for the district and city of Osnabrueck" }, { - "author_name": "Michael A. Loesche", - "author_inst": "Space Exploration Technologies Corp and Brigham and Women's Hospital, Boston" + "author_name": "Stefanie Castell", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Justin Rhee", - "author_inst": "Space Exploration Technologies Corp" + "author_name": "Kerstin Frank", + "author_inst": "Institute of Transfusion Medicine and Immunohematology, German Red Cross, Plauen" }, { - "author_name": "Samuel Berger", - "author_inst": "Space Exploration Technologies Corp" + "author_name": "Knut Gubbe", + "author_inst": "Institute of Transfusion Medicine and Immunohematology, German Red Cross, Plauen, Germany" }, { - "author_name": "Yiyuan Hu", - "author_inst": "Space Exploration Technologies Corp" + "author_name": "Jana-Kristin Heise", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Matthew J. Gluck", - "author_inst": "Space Exploration Technologies Corp" + "author_name": "Pilar Hernandez", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Benjamin Mormann", - "author_inst": "Space Exploration Technologies Corp" + "author_name": "Oliver Kappert", + "author_inst": "Department of Health and Supply Landratsamt Breisgau-Hochschwarzwald" }, { - "author_name": "Mohammad A. Hasdianda", - "author_inst": "Brigham and Women's Hospital, Boston" + "author_name": "Winfried Kern", + "author_inst": "Infectious Diseases and Travel Medicine, Department of Medicine II, University Hospital Freiburg" }, { - "author_name": "Elon R. Musk", - "author_inst": "Space Exploration Technologies Corp" + "author_name": "Thomas Illig", + "author_inst": "Hannover Unified Biobank (HUB), Medizinische Hochschule Hannover (MHH)" }, { - "author_name": "Galit Alter", - "author_inst": "Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA and Broad Institute of MIT and Harvard, Cambridge, MA, USA" + "author_name": "Norman Klopp", + "author_inst": "Hannover Unified Biobank (HUB), Medizinische Hochschule Hannover (MHH)" }, { - "author_name": "Anil S. Menon", - "author_inst": "Space Exploration Technologies Corp" + "author_name": "Henrike Maass", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Eric J. Nilles", - "author_inst": "Harvard Humanitarian Initiative, Cambridge, MA, USA and Brigham and Women's Hospital, Boston" + "author_name": "Julia Ortmann", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Adam J. Kucharski", - "author_inst": "Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" + "author_name": "Barbora Kessel", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Gottfried Roller", + "author_inst": "Baden-Wuerttemberg State Health Office" + }, + { + "author_name": "Monike Schlueter", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Torsten Tonn", + "author_inst": "Institute of Transfusion Medicine and Immunohematology" + }, + { + "author_name": "Micheal Ziemons", + "author_inst": "Department of Social Affairs, Health and Digitalization StaedteRegion Aachen" + }, + { + "author_name": "Yvonne Kemmling", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Berit Lange", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Gerard Krause", + "author_inst": "Helmholtz Centre for Infection Research" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.06.442911", @@ -797662,35 +797653,71 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.05.01.21256442", - "rel_title": "Prevalence of anxiety, depression, and stress among teachers during the COVID-19 pandemic: Systematic review", + "rel_doi": "10.1101/2021.05.01.21256470", + "rel_title": "LENZILUMAB EFFICACY AND SAFETY IN NEWLY HOSPITALIZED COVID-19 SUBJECTS: RESULTS FROM THE LIVE-AIR PHASE 3 RANDOMIZED DOUBLE-BLIND PLACEBO-CONTROLLED TRIAL", "rel_date": "2021-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.01.21256442", - "rel_abs": "ObjectiveIdentifying the prevalence of anxiety, depression, and stress among teachers during the COVID-19 pandemic.\n\nMethodsSystematic review of original studies published in any language. Protocol published in PROSPERO under number CRD42021240543. The search was carried out in the Web of Science, PsycINFO, Pubmed, Embase, LILACS, and SciELO databases, using the descriptors: anxiety, depression, stress, teacher, faculty, COVID-19, and their synonyms. Narrative synthesis was carried out in line with the synthesis without meta-analysis (SWiM) in systematic reviews.\n\nResultsOf the 1,372 records identified, six studies, all cross-sectional, were included in the review. The studies were carried out in China, Brazil, the United States of America, India, and Spain. Five studies included more women than men. The participants were aged from 24 to 60 years. Three studies included only school teachers, two included schools and universities teachers, and one only university teachers. Of the five studies, all dealt with remote activities and only one included teachers who returned to face-to-face classes one to two weeks ago. The prevalence of anxiety ranged from 10% to 49.4%, and depression from 15.9% to 28.9%, being considerably higher in studies with teachers who worked in schools. The prevalence of stress ranged from 12.6% to 50.6%.\n\nConclusionsThe prevalence of anxiety, depression, and stress was high among teachers during the pandemic, with great variation between studies. Anxiety and stress were more prevalent in the Spanish study. The results show the need for measures for the care of teachers mental health, especially when returning to face-to-face classes.\n\nWhat is already known about this subject?[tpltrtarr] With remote classes during the COVID-19 pandemic, there were changes in the professional practice of teachers.\n[tpltrtarr]Sudden changes in professional practice can result in increased levels of anxiety, depression, and stress.\n[tpltrtarr]Returning to face-to-face classes can also result in increased levels of anxiety, depression, and stress.\n\n\nWhat are the new findings?[tpltrtarr] The prevalence of anxiety ranged from 10% to 49.4%, with higher rates recorded in female teachers, with comorbidities and working in schools.\n[tpltrtarr]The prevalence of depression ranged from 15.9% to 28.9%, with higher rates identified in school teachers.\n[tpltrtarr]The prevalence of stress varied from 12.6% to 50.6%, with higher rates observed among female teachers and those with chronic diseases.\n[tpltrtarr]The only study that performed data collection during the return to face-to-face classes registered a higher prevalence of anxiety and stress than the other studies, in which the research was carried out during remote classes.\n\n\nHow might this impact policy or clinical practice in the foreseeable future?[tpltrtarr] Better training of teachers to handle the remote education model can contribute to preventing work overload and mental problems. Further, pedagogical and psychological support, especially for those who work in schools, can also prove effective.\n[tpltrtarr]The return to face-to-face classes can increase stress and anxiety. Ensuring bio-safety protocols for safe return to face-to-face activities, can contribute to mitigating anxiety and stress about the risk of contracting the disease.\n[tpltrtarr]There is insufficient evidence to determine a cause and effect relationship of the COVID-19 pandemic with anxiety, depression, and stress among teachers. Prospective cohort studies with control of confounding factors are necessary to infer that the pandemic has increased mental health problems in these professionals.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.01.21256470", + "rel_abs": "BACKGROUNDSevere COVID-19 pneumonia results from a hyperinflammatory immune response (cytokine storm, CS), characterized by GM-CSF mediated activation and trafficking of myeloid cells, leading to elevation of downstream inflammatory chemokines (MCP-1, IL-8, IP-10), cytokines (IL-6, IL-1), and other markers of systemic inflammation (CRP, D-dimer, ferritin). CS leads to fever, hypotension, coagulopathy, respiratory failure, ARDS, and death. Lenzilumab is a novel Humaneered(R) anti-human GM-CSF monoclonal antibody that directly binds GM-CSF and prevents signaling through its receptor. The LIVE-AIR Phase 3 randomized, double-blind, placebo-controlled trial investigated the efficacy and safety of lenzilumab to assess the potential for lenzilumab to improve the likelihood of ventilator-free survival (referred to herein as survival without ventilation, SWOV), beyond standard supportive care, in hospitalized subjects with severe COVID-19.\n\nMETHODSSubjects with COVID-19 (n=520), [≥]18 years, and [≤]94% oxygen saturation on room air and/or requiring supplemental oxygen, but not invasive mechanical ventilation, were randomized to receive lenzilumab (600 mg, n=261) or placebo (n=259) via three intravenous infusions administered 8 hours apart. Subjects were followed through Day 28 following treatment.\n\nRESULTSBaseline demographics were comparable between the two treatment groups: male, 64.7%; mean age, 60.5 years; mean BMI, 32.5 kg/m2; mean CRP, 98.36 mg/L; CRP was <150 mg/L in 77.9% of subjects. The most common comorbidities were obesity (55.1%), diabetes (53.4%), chronic kidney disease (14.0%), and coronary artery disease (13.6%). Subjects received steroids (93.7%), remdesivir (72.4%), or both (69.1%). Lenzilumab improved the likelihood of SWOV by 54% in the mITT population (HR: 1.54; 95%CI: 1.02-2.31, p=0.041) and by 90% in the ITT population (HR: 1.90; 1.02-3.52, nominal p=0.043) compared to placebo. SWOV also relatively improved by 92% in subjects who received both corticosteroids and remdesivir (1.92; 1.20-3.07, nominal p=0.0067); by 2.96-fold in subjects with CRP<150 mg/L and age <85 years (2.96; 1.63-5.37, nominal p=0.0003); and by 88% in subjects hospitalized [≤]2 days prior to randomization (1.88; 1.13-3.12, nominal p=0.015). Survival was improved by 2.17-fold in subjects with CRP<150 mg/L and age <85 years (2.17; 1.04-4.54, nominal p=0.040).\n\nCONCLUSIONLenzilumab significantly improved SWOV in hospitalized, hypoxic subjects with COVID-19 pneumonia over and above treatment with remdesivir and/or corticosteroids. Subjects with CRP<150 mg/L and age <85 years demonstrated an improvement in survival and had the greatest benefit from lenzilumab. NCT04351152", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "David Franciole de Oliveira Silva", - "author_inst": "Federal University of Rio Grande do Norte" + "author_name": "Zelalem Temesgen", + "author_inst": "Mayo Clinic, Rochester, MN" }, { - "author_name": "Ricardo Ney Oliveira Cobucci", - "author_inst": "Potiguar University" + "author_name": "Charles D. Burger", + "author_inst": "Mayo Clinic, Jacksonville, FL" }, { - "author_name": "Severina Carla Vieira Cunh Lima", - "author_inst": "Federal University of Rio Grande do Norte" + "author_name": "Jason Baker", + "author_inst": "Hennepin Healthcare Research Institute, Minneapolis, MN" }, { - "author_name": "Fabia Barbosa de Andrade", - "author_inst": "Federal University of Rio Grande do Norte" + "author_name": "Christopher Polk", + "author_inst": "Atrium Health, Charlotte, NC" + }, + { + "author_name": "Claudia Libertin", + "author_inst": "Mayo Clinic, Jacksonville, FL" + }, + { + "author_name": "Colleen Kelley", + "author_inst": "Emory University, Grady Memorial Hospital, Atlanta, GA" + }, + { + "author_name": "Vincent C Marconi", + "author_inst": "Emory University" + }, + { + "author_name": "Robert Orenstein", + "author_inst": "Mayo Clinic, Scottsdale, AZ" + }, + { + "author_name": "Cameron Durrant", + "author_inst": "Humanigen, Inc." + }, + { + "author_name": "Dale Chappell", + "author_inst": "Humanigen, Inc." + }, + { + "author_name": "Omar Ahmed", + "author_inst": "Humanigen, Inc." + }, + { + "author_name": "Gabrielle Chappell", + "author_inst": "Humanigen, Inc." + }, + { + "author_name": "Andrew Badley", + "author_inst": "Mayo Clinic, Rochester, MN" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.05.04.21256355", @@ -799628,61 +799655,65 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2021.05.01.21256452", - "rel_title": "A hemagglutination-based, semi-quantitative test for point-of-care determination of SARS-CoV-2 antibody levels", + "rel_doi": "10.1101/2021.04.30.21256415", + "rel_title": "A Meta-analysis of Mortality, Need for ICU admission, Use of Mechanical Ventilation and Adverse Effects with Ivermectin Use in COVID-19 Patients", "rel_date": "2021-05-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.05.01.21256452", - "rel_abs": "Serologic, point-of-care tests to detect antibodies against SARS-CoV-2 are an important tool in the COVID-19 pandemic. The majority of current point-of-care antibody tests developed for SARS-CoV-2 rely on lateral flow assays, but these do not offer quantitative information. To address this, we developed a new method of COVID-19 antibody testing employing hemagglutination tested on a dry card, similar to that which is already available for rapid typing of ABO blood groups. A fusion protein linking red blood cells (RBCs) to the receptor-binding domain (RBD) of SARS-CoV-2 spike protein was placed on the card. 200 COVID-19 patient and 200 control plasma samples were reconstituted with O-negative RBCs to form whole blood and added to the dried protein, followed by a stirring step and a tilting step, 3-minute incubation, and a second tilting step. The sensitivity for the hemagglutination test, Euroimmun IgG ELISA test and RBD-based CoronaChek lateral flow assay was 87.0%, 86.5%, and 84.5%, respectively, using samples obtained from recovered COVID-19 individuals. Testing pre-pandemic samples, the hemagglutination test had a specificity of 95.5%, compared to 97.3% and 98.9% for the ELISA and CoronaChek, respectively. A distribution of agglutination strengths was observed in COVID-19 convalescent plasma samples, with the highest agglutination score (4) exhibiting significantly higher neutralizing antibody titers than weak positives (2) (p<0.0001). Strong agglutinations were observed within 1 minute of testing, and this shorter assay time also increased specificity to 98.5%. In conclusion, we developed a novel rapid, point-of-care RBC agglutination test for the detection of SARS-CoV-2 antibodies that can yield semi-quantitative information on neutralizing antibody titer in patients. The five-minute test may find use in determination of serostatus prior to vaccination, post-vaccination surveillance and travel screening.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.30.21256415", + "rel_abs": "ImportanceRepurposing Ivermectin, a known anti-parasitic agent, for treating COVID-19 has demonstrated positive results in several studies. We aim to evaluate the benefit and risk of Ivermectin in COVID-19.\n\nMethodsWe conducted a systematic search for full-text manuscripts published from February 1, 2020, to August 15th, 2021 focusing on Ivermectin therapy against COVID-19. The primary outcomes were mortality, need for intensive care unit (ICU) admission; secondary outcomes were - adverse effects, need for mechanical ventilation, viral clearance, time to viral clearance, need for hospitalization, and length of hospital stay. Random-effects models were used for all analyses.\n\nResultsWe included a total of 52 studies (n=17561) in the qualitative analysis, out of these, 44 studies (n=14019) were included in the meta-analysis. In the mortality meta-analysis (N=29), odds of death were lower in the Ivermectin-arm compared to control (OR 0.54, p=0.009). Although lower odds of mortality were observed in various subgroup analyses of RCTs, they did not reach statistical significance: therapeutic RCTs: mild-moderate COVID-19 (OR 0.31, p=0.06), therapeutic RCTs: severe/critical COVID-19 (OR 0.86, p=0.56), inpatient RCTs: mild-moderate COVID-19 (OR 0.18, p=0.08), inpatient RCTs: severe/critical COVID-19 (OR 0.86, p=0.56). Ivermectin, mostly as adjuvant therapy, was associated with higher odds of viral clearance (N=22) (OR 3.52, p=0.0002), shorter duration to achieve viral clearance (N=8) (MD - 4.12, p=0.02), reduced need for hospitalization (N=6) (OR 0.34, p=008).\n\nConclusionOur meta-analysis suggests that the mortality benefit of Ivermectin in COVID-19 is uncertain. But as adjuvant therapy, Ivermectin may improve viral clearance and reduce the need for hospitalization.\n\nHighlightsO_ST_ABSWhat We Already Know about This TopicC_ST_ABSO_LICOVID-19 is an ongoing global pandemic, for which Ivermectin has been tried on a therapeutic and prophylactic basis.\nC_LIO_LIResults from several clinical trials and observational studies suggest that Ivermectin may improve survival and clinical outcomes with a good safety profile when compared with other treatments; however, the current evidence is limited..\nC_LI\n\nWhat This Article Tells Us That Is NewO_LIThis systematic review and meta-analysis provide a summary of the latest literature on the efficacy and safety of Ivermectin use for COVID-19.\nC_LIO_LIBased on our analysis of the latest evidence, we found that Ivermectins benefit in reducing mortality cannot be concluded with confidence. However, as an adjuvant therapy it may help reduce the need for hospitalization, duration for viral clearance while increasing the likelihood of achieving viral clearance.\nC_LIO_LIWe need more high-quality data for conclusive evidence regarding the benefit of Ivermectin in reducing the need for ICU admissions, mechanical ventilation and duration of hospital stay in COVID-19 patients.\nC_LI", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Robert Kruse", - "author_inst": "Department of Pathology, Johns Hopkins University School of Medicine" + "author_name": "Smruti Karale", + "author_inst": "Government Medical College Kolhapur, Kolhapur, India" }, { - "author_name": "Yuting Huang", - "author_inst": "Department of Medicine, University of Maryland Medical Center Midtown Campus" + "author_name": "Vikas Bansal", + "author_inst": "Mayo Clinic, Rochester, MN, USA" }, { - "author_name": "Alyssa Lee", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Janaki Makadia", + "author_inst": "GMERS Medical College Gotri, Vadodara, Gujarat, India" }, { - "author_name": "Xianming Zhu", - "author_inst": "Department of Pathology, Johns Hopkins University School of Medicine" + "author_name": "Muhammad Tayyeb", + "author_inst": "Monmouth Medical Center, Long Branch, NJ, USA" }, { - "author_name": "Ruchee Shrestha", - "author_inst": "Department of Medicine, Johns Hopkins University School of Medicine" + "author_name": "Hira Khan", + "author_inst": "Allegheny General Hospital, Pittsburgh, PA, USA" }, { - "author_name": "Oliver Laeyendecker", - "author_inst": "Department of Medicine, Johns Hopkins University School of Medicine" + "author_name": "Shree Spandana Ghanta", + "author_inst": "St. Elizabeth's Medical Center, Boston, MA, USA" }, { - "author_name": "Kirsten Littlefield", - "author_inst": "Department of Molecular Microbiology and Immunology, The Johns Hopkins Bloomberg School of Public Health" + "author_name": "Romil Singh", + "author_inst": "Allegheny General Hospital, Pittsburgh, PA, USA" + }, + { + "author_name": "Aysun Tekin", + "author_inst": "Mayo Clinic, Rochester, MN, USA" }, { - "author_name": "Andy Pekosz", - "author_inst": "Department of Molecular Microbiology and Immunology, The Johns Hopkins Bloomberg School of Public Health" + "author_name": "Abhishek Bhurwal", + "author_inst": "Rutgers Robert Wood Johnson School of Medicine, New Brunswick, NJ, USA" }, { - "author_name": "Evan M Bloch", - "author_inst": "Department of Pathology, Johns Hopkins University School of Medicine" + "author_name": "Hemant Mutneja", + "author_inst": "Cook County Hospital, Chicago, Illinois, USA" }, { - "author_name": "Aaron A.R. Tobian", - "author_inst": "Department of Pathology, Johns Hopkins University School of Medicine" + "author_name": "Ishita Mehra", + "author_inst": "North Alabama Medical Center, Florence, AL, USA" }, { - "author_name": "Zack Z Wang", - "author_inst": "Department of Medicine, Johns Hopkins University School of Medicine" + "author_name": "Rahul Kashyap", + "author_inst": "Mayo Clinic, Rochester, MN, USA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -800996,35 +801027,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.04.30.21256385", - "rel_title": "The immediate and longer-term impact of the COVID-19 pandemic on the mental health and wellbeing of older adults in England", + "rel_doi": "10.1101/2021.04.30.21256372", + "rel_title": "Rehabilitation needs and mortality associated with the Covid-19 pandemic: a population-based study of all hospitalised and home-healthcare individuals in a Swedish healthcare region", "rel_date": "2021-05-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.30.21256385", - "rel_abs": "ObjectiveTo evaluate changes in mental health and wellbeing before and during the initial and later phases of the COVID-19 pandemic and investigate whether patterns varied with age, sex, and socioeconomic status.\n\nDesignProspective cohort study.\n\nParticipantsEnglish Longitudinal Study of Ageing cohort of 5146 community dwelling adults aged 52 years and older (53% women, average age 66.74 years, standard deviation 10.62) who provided data before the pandemic (2018-19) and at two occasions in 2020 (June-July and November-December).\n\nMain outcome measureDepression, poor quality of life, loneliness and anxiety.\n\nResultsThe prevalence of clinically significant depressive symptoms increased from 12.5% pre-pandemic to 22.6% in June-July 2020, with a further rise to 28.5% in November-December. This was accompanied by increased loneliness and deterioration in quality of life. The prevalence of anxiety rose from 9.4% to 10.9% between June-July and November-December 2022. Women and non-partnered people experienced worse changes in mental health and wellbeing. Participants with less wealth had lowest levels of mental health before and during the pandemic. Higher socioeconomic groups had better mental health overall, but responded to the pandemic with more negative changes. Patterns of changes were similar across age groups, the only exception was for depression which showed a smaller increase in the 75+ age group than in the youngest age group (50-59 years).\n\nConclusionsThese data showed that mental health and wellbeing continued to worsen as lockdown continued, and that socioeconomic inequalities persisted. Women and non-partnered people experienced greater deterioration in all mental health outcomes. The immediate provision of diagnosis of mental health problems and targeted psychological interventions should target and support sociodemographic groups of older people at higher risk of psychological distress.\n\nWhat is already known on this topic- The COVID-19 pandemic and mitigation measures have upended the economic and social lives of many, leading to widespread psychological distress.\n- During the early months of the pandemic, levels of depression, anxiety and loneliness were high and lower levels of wellbeing were reported across the adult population, with certain higher risk groups identified.\n- However, evidence from longitudinal studies of representative samples of older adults that include pre-pandemic data is scarce, and little is known about mental health beyond the initial period of the pandemic. Repeated assessments are needed in order to understand whether mental health and wellbeing levels recovered or continued to deteriorate throughout 2020.\n\n\nWhat this study adds- These data suggest that mental health and wellbeing deteriorated significantly during June-July 2020 compared with pre-pandemic levels and continued to deteriorate during the second national lockdown in November-December 2020, showing that older individuals did not adapt to circumstances.\n- Inequalities in experiences of mental ill-health and poor wellbeing during 2020 were evident, with women, individuals living alone and those with less wealth being particularly vulnerable. Furthermore, socioeconomic inequalities in mental health have persisted during the pandemic.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.30.21256372", + "rel_abs": "BackgroundThis first report of the Linkoping Covid-19 Study (LinCoS) aimed at determination of Covid-19-associated mortality, impairments, activity and participation limitations denoting rehabilitation needs four months after discharge from hospital.\n\nMethodsAn ambidirectional population-based cohort study including all confirmed Covid-19 cases admitted to hospital during 1/03-31/05 and those living in home healthcare settings identified through a regional registry and evaluated through medical records, including WHO Clinical Progression Scale (CPS). All patients discharged from hospital were followed-up by structured telephone interview at 4 months post-discharge. Respondents indicated any new or aggravated persisting problems in any of 25 body functions and 12 activity/participation items and rated them for impact on daily life.\n\nFindingsOut of 734 hospitalised patients, 149 were excluded, 125 died, and 460 were alive at 4-month follow-up of whom 433 (94.1%) were interviewed. In total, 40% reported impairments and activity/participation limitations affecting daily life and warranted further multi-professional rehabilitation assessment, predominantly those with severe disease and a considerable proportion of those with moderate disease. Cognitive and affective impairments were equally common in all groups and were reported by 20-40% of cases. Limb weakness was reported by 31%, with CPS 7-9 being four times more likely to report this problem as compared to CPS 4-5. 26% of those working or studying reported difficulties returning to these activities, this being 3.5 times more likely in CPS 7-9 as compared to CPS 4-5. 25% reported problems walking >1 km, with CPS 7-9 over three times more likely to report this as compared to the other two sub-groups. 90-day mortality rate of Covid-19 associated deaths was 15.1%.\n\nInterpretationMost rehabilitation needs after Covid-19 involved higher cerebral dysfunction both in patients with moderate and severe disease. This should be considered when designing services aiming at minimizing long-term disability.\n\nFundingALF grant and Region Ostergotland.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Paola Zaninotto", - "author_inst": "UCL" + "author_name": "Anestis Divanoglou", + "author_inst": "Link\u00f6ping University Hospital" }, { - "author_name": "Eleonora Iob", - "author_inst": "University College London" + "author_name": "Kersti Samuelsson", + "author_inst": "Link\u00f6ping University Hospital" }, { - "author_name": "Panayotes Demakakos", - "author_inst": "University College London" + "author_name": "Rune Sj\u00f6dahl", + "author_inst": "Link\u00f6ping University Hospital" }, { - "author_name": "Andrew Steptoe", - "author_inst": "University College London" + "author_name": "Christer Andersson", + "author_inst": "Link\u00f6ping University Hospital" + }, + { + "author_name": "Richard Levi", + "author_inst": "Link\u00f6ping University Hospital" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "rehabilitation medicine and physical therapy" }, { "rel_doi": "10.1101/2021.04.29.21256335", @@ -802878,135 +802913,119 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.27.21256207", - "rel_title": "SARS-CoV-2 antibodies remain detectable 12 months after infection and antibody magnitude is associated with age and COVID-19 severity", + "rel_doi": "10.1101/2021.04.28.21256261", + "rel_title": "Aspirin and NSAID use and the risk of COVID-19", "rel_date": "2021-05-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.27.21256207", - "rel_abs": "ImportanceThe persistence of SARS-CoV-2 antibodies may be a predictive correlate of protection for both natural infections and vaccinations. Identifying predictors of robust antibody responses is important to evaluate the risk of re-infection / vaccine failure and may be translatable to vaccine effectiveness.\n\nObjectiveTo 1) determine the durability of anti-SARS-CoV-2 IgG and neutralizing antibodies in subjects who experienced mild and moderate to severe COVID-19, and 2) to evaluate the correlation of age and IgG responses to both endemic human seasonal coronaviruses (HCoVs) and SARS-CoV-2 according to infection outcome.\n\nDesignLongitudinal serum samples were collected from PCR-confirmed SARS-CoV-2 positive participants (U.S. active duty service members, dependents and military retirees, including a range of ages and demographics) who sought medical treatment at seven U.S. military hospitals from March 2020 to March 2021 and enrolled in a prospective observational cohort study.\n\nResultsWe observed SARS-CoV-2 seropositivity in 100% of inpatients followed for six months (58/58) to one year (8/8), while we observed seroreversion in 5% (9/192) of outpatients six to ten months after symptom onset, and 18% (2/11) of outpatients followed for one year. Both outpatient and inpatient anti-SARS-CoV-2 binding-IgG responses had a half-life (T1/2) of >1000 days post-symptom onset. The magnitude of neutralizing antibodies (geometric mean titer, inpatients: 378 [246-580, 95% CI] versus outpatients: 83 [59-116, 95% CI]) and durability (inpatients: 65 [43-98, 95% CI] versus outpatients: 33 [26-40, 95% CI]) were associated with COVID-19 severity. Older age was a positive correlate with both higher IgG binding and neutralizing antibody levels when controlling for COVID-19 hospitalization status. We found no significant relationships between HCoV antibody responses and COVID-19 clinical outcomes, or the development of SARS-CoV-2 neutralizing antibodies.\n\nConclusions and RelevanceThis study demonstrates that humoral responses to SARS-CoV-2 infection are robust on longer time-scales, including those arising from milder infections.\n\nHowever, the magnitude and durability of the antibody response after natural infection was lower and more variable in younger participants who did not require hospitalization for COVID-19. These findings support vaccination against SARS-CoV-2 in all suitable populations including those individuals that have recovered from natural infection.", - "rel_num_authors": 29, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.28.21256261", + "rel_abs": "Early reports raised concern that use of non-steroidal anti-inflammatory drugs (NSAIDs) may increase risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease (COVID-19). Users of the COVID Symptom Study smartphone application reported use of aspirin and other NSAIDs between March 24 and May 8, 2020. Users were queried daily about symptoms, COVID-19 testing, and healthcare seeking behavior. Cox proportional hazards regression was used to determine the risk of COVID-19 among according to aspirin or non-aspirin NSAID users. Among 2,736,091 individuals in the U.S., U.K., and Sweden, we documented 8,966 incident reports of a positive COVID-19 test over 60,817,043 person-days of follow-up. Compared to non-users and after stratifying by age, sex, country, day of study entry, and race/ethnicity, non-aspirin NSAID use was associated with a modest risk for testing COVID-19 positive (HR 1.23 [1.09, 1.32]), but no significant association was observed among aspirin users (HR 1.13 [0.92, 1.38]). After adjustment for lifestyle factors, comorbidities and baseline symptoms, any NSAID use was not associated with risk (HR 1.02 [0.94, 1.10]). Results were similar for those seeking healthcare for COVID-19 and were not substantially different according to lifestyle and sociodemographic factors or after accounting for propensity to receive testing. Our results do not support an association of NSAID use, including aspirin, with COVID-19 infection. Previous reports of a potential association may be due to higher rates of comorbidities or use of NSAIDs to treat symptoms associated with COVID-19.\n\nOne Sentence SummaryNSAID use is not associated with COVID-19 risk.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Eric Laing", - "author_inst": "Uniformed Services University" - }, - { - "author_name": "Nusrat J Epsi", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation" - }, - { - "author_name": "Stephanie A Richard", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation" - }, - { - "author_name": "Emily C Samuels", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation" - }, - { - "author_name": "Wei Wang", - "author_inst": "US Food and Drug Admininstration" + "author_name": "David Alden Drew", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Russell Vassell", - "author_inst": "US Food and Drug Administration" + "author_name": "Chuan-Guo Guo", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Daniel F Ewing", - "author_inst": "Naval Medical Research Center-Fort Detrick" + "author_name": "Karla Lee", + "author_inst": "Department of Twin Research and Genetic Epidemiology" }, { - "author_name": "Rachel Herrup", - "author_inst": "US Food and Drug Administration" + "author_name": "Long Nguyen", + "author_inst": "Massachusetts General Hospital and Harvard Medical School" }, { - "author_name": "Spencer L. Sterling", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation" + "author_name": "Amit D Joshi", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "David A Lindholm", - "author_inst": "Brooke Army Medical Center" + "author_name": "Chun-Han Lo", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Eugene V Millar", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation" + "author_name": "Wenjie Ma", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Ryan C Maves", - "author_inst": "Naval Medical Center San Diego" + "author_name": "Raaj S Mehta", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Derek T Larson", - "author_inst": "Fort Belvoir Community Hospital" + "author_name": "Sohee Kwon", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Rhonda E Colombo", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation, Madigan Army Medical Center" + "author_name": "Christina M Astley", + "author_inst": "Boston Children's Hospital" }, { - "author_name": "Sharon Chi", - "author_inst": "Tripler Army Medical Center" + "author_name": "Mingyang Song", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Cristian S Madar", - "author_inst": "Tripler Army Medical Center" + "author_name": "Richard Davies", + "author_inst": "Zoe Global Ltd." }, { - "author_name": "Tahaniyat Lalani", - "author_inst": "Naval Medical Center Portsmouth" + "author_name": "Joan Capdevila", + "author_inst": "Zoe Global Ltd" }, { - "author_name": "Anuradha Ganesan", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation, Walter Reed National Military Medical Center" + "author_name": "Mary M Ni Lochlainn", + "author_inst": "King's College London" }, { - "author_name": "Anthony Fries", - "author_inst": "U.S. Air Force School of Aerospace Medicine" + "author_name": "Carole Sudre", + "author_inst": "Kings College London" }, { - "author_name": "Christopher J Colombo", - "author_inst": "Madigan Army Medical Center" + "author_name": "Mark S Graham", + "author_inst": "King's College London" }, { - "author_name": "Katrin Mende", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation, Brooke Army Medical Center" + "author_name": "Thomas Varsavsky", + "author_inst": "Kings College London" }, { - "author_name": "Mark P Simons", - "author_inst": "Uniformed Services University" + "author_name": "Maria F. Gomez", + "author_inst": "Lund University" }, { - "author_name": "Kevin L Schully", - "author_inst": "Naval Medical Research Center-Fort Detrick" + "author_name": "Beatrice Kennedy", + "author_inst": "Uppsala University" }, { - "author_name": "Carol D Weiss", - "author_inst": "US Food and Drug Administration" + "author_name": "Hugo Fitipaldi", + "author_inst": "Lund University" }, { - "author_name": "David R Tribble", - "author_inst": "Uniformed Services University" + "author_name": "Jonathan Wolf", + "author_inst": "Zoe Global Ltd." }, { - "author_name": "Brian K Agan", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation" + "author_name": "Timothy Spector", + "author_inst": "King's College London" }, { - "author_name": "Simon D Pollett", - "author_inst": "Uniformed Services University, Henry M. Jackson Foundation" + "author_name": "Sebastien Ourselin", + "author_inst": "King's College London" }, { - "author_name": "Christopher C Broder", - "author_inst": "Uniformed Services University" + "author_name": "Claire Steves", + "author_inst": "King's College London" }, { - "author_name": "Timothy H Burgess", - "author_inst": "Uniformed Services University" + "author_name": "Andrew T. Chan", + "author_inst": "Massachusetts General Hospital" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.04.29.21256360", @@ -804552,27 +804571,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.29.21256255", - "rel_title": "Objective and Subjective COVID-19 Vaccine Reactogenicity by Age and Vaccine Manufacturer", + "rel_doi": "10.1101/2021.04.27.21256214", + "rel_title": "SARS-CoV-2 serological findings and exposure risk among employees in school and retail after first and second wave COVID-19 pandemic in Oslo, Norway: a cohort study", "rel_date": "2021-04-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.29.21256255", - "rel_abs": "Several vaccines against SARS-CoV-2 have been granted emergency use authorization from the United States Food and Drug Administration and similar regulatory bodies abroad to combat the COVID-19 pandemic. While these vaccines have been shown to be extremely safe, transient side-effects lasting 24-48 hours post-vaccination have been reported. Here we conducted a retrospective analysis of 50977 subscribers to the WHOOP platform (33119 males, 17858 females; total of 65686 unique responses) who received either the AstraZeneca (AZ, n=2093), Janssen/Johnson & Johnson (J&J&J, n=3888), Moderna (n=23776; M1, 14553 first dose; M2, 9223 second dose), or Pfizer/BioNTech (n=35929; P&B1, 22387 first dose; P&B2, 13542 second dose) vaccines using data collected through April 14, 2021. Subjective reactogenicity was assessed using self-reported surveys. Results from these surveys indicated that the odds of self-reporting an adverse event after vaccination depend on gender, age, and manufacturer. Objectively measured cardiovascular (resting heart rate, RHR; heart rate variability, HRV) and sleep (total sleep duration, % light sleep, and % restorative sleep [a combination of REM and slow wave sleep]) metrics were assessed using a wrist-worn biometric device (Whoop Inc, Boston, MA, USA) and compared to the same day of the week, one week prior. Data are presented as a percent change from baseline {+/-} 95% confidence intervals. On the night after vaccination, RHR was higher (AZ: 13.5{+/-}0.76%; J&J&J: 16.5{+/-}0.64%; M1: 2.86{+/-}0.19%; M2: 9.3{+/-}0.53%; P&B1: 1.18{+/-}0.14%; P&B2: 13.5{+/-}0.36%) and HRV (AZ: -21.8{+/-}1.47%; J&J&J: - 25.6{+/-}1.15%; M1: -4.8{+/-}055%; M2: -19.9{+/-}1.33%; P&B1: -1.7{+/-}0.45%; P&B2: 8.60{+/-}1.10%) was lower than baseline levels. As for sleep metrics, total sleep was lower after the AZ and J&J&J vaccines (AZ: -3.7{+/-}0.98%; J&J&J: -3.8{+/-}0.80%; M1: 0.94{+/-}0.32%; M2: 0.14{+/-}0.80%; P&B1: 1.10{+/-}0.25%; P&B2: 0.35{+/-}0.63%); for AZ, J&J&J and the second dose of Moderna and P&B, a greater percentage of sleep post-vaccination came from light sleep (AZ: 9.24{+/-}1.22%; J&J&J: 13.8{+/-}1.02%; M1: 1.73{+/-}0.40%; M2: 8.02{+/-}0.99%; P&B1: 0.44{+/-}0.31%; P&B2: 2.54{+/-}0.74%) and a lower percentage from restorative sleep (AZ: -9.21{+/-}1.27%; J&J&J: -12.6{+/-}1.00%; M1: 0.16{+/-}0.43%; M2: -8.31{+/-}1.05%; P&B1: 1.27{+/-}0.34%; P&B2: -1.36{+/-}0.83%) than the week prior. Across all objective metrics measured, there were general trends that indicated an attenuated response in older populations and a larger response after the second dose for the Pfizer/BioNTech and Moderna vaccines (AstraZeneca second dose not analyzed). Importantly, the effects of the vaccines on cardiovascular and sleep measures were transient and returned to baseline by the second night following vaccination (P > 0.05 or absolute Cohens d < 0.25). In summary, these results confirm the previously observed subjective symptomatology trends, and for the first time show that objectively measured cardiovascular and sleep parameters are altered the night after vaccination. Moreover, these results suggest that the response may be different between vaccine manufacturers and may be modified by age and larger after the second dose. This information can be used to inform policy makers and employers considering offering paid time off for vaccination, as well as individuals planning their commitments post-vaccination.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.27.21256214", + "rel_abs": "BackgroundDuring initial phases of the coronavirus disease 2019 (COVID-19) pandemic, many workplaces were affected by closures and various preventive measures intended to limit infections. Here, we characterize and compare in an ambidirectional cohort study SARS-CoV-2 serology among Norwegian school employees and retail employees at baseline following the first epidemiological wave, and at follow-up after a second wave.\n\nMethodsWe enrolled a cohort of 238 school and retail employees after the first COVID-19 pandemic wave. Self-reported exposure history and serum samples were collected at 10 schools and 15 retail stores in Oslo, Norway, sampled at two time-points, baseline (May 18. to July 2. 2020) and follow-up (Jan 7. to Mar 17. 2021). SARS-CoV-2 antibodies targeting both spike and nucleocapsid were characterized by multiplex microsphere-based serological methods.\n\nResultsAt baseline, 6 enrolled workers presented with positive SARS-CoV-2 serology (3%; CI [1, 6]; P=0.019), which was significantly higher than the expected 1% prevalence in the general Oslo-population at this time-point. Five of the positive cases were retail employees. However, school and retail groups distributions at baseline were not significantly different as the number of seropositive observations were limited. Due to a school closure effectuated during the first wave, half of the school employees reported [≤]2 days of physical workplace presence per week, while 65% of the retail employees reported [≥]5 days per week. Eight months later, after passing a second epidemiological wave, school and retail groups presented 11 new seropositive cases altogether, but there was still no significant differences between the groups. Physical attendance at the workplace was similar between the groups during the second wave, but some preventive measures against viral transmission at workplaces were different. Self-reported virus diagnostics (RNA) for the same period were compared to the serological data obtained in this study, showing that all but one positive SARS-CoV-2 serological findings arising between baseline and follow-up had been diagnosed with virus testing.\n\nConclusionsAfter the first wave, distribution of SARS-CoV-2 positive serology was slightly higher than expected in a cohort of school and retail employees. Distribution of infection was not significantly different between the groups at baseline nor at follow-up, even though physical workplace attendance had been different. Nearly all new seropositive cases discovered in this study between baseline and follow-up, had already been diagnosed due to widespread virus testing during the second wave. This highlights the importance of extensive viral testing among workers.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "David Presby", - "author_inst": "WHOOP Inc" + "author_name": "Anne-Mari Gjestvang Moe", + "author_inst": "National Institute of Occupational Health STAMI, Oslo, Norway" }, { - "author_name": "Emily Capodilupo", - "author_inst": "WHOOP Inc." + "author_name": "Mina Eriksen", + "author_inst": "National Institute of Occupational Health STAMI, Oslo, Norway" + }, + { + "author_name": "Tiril Schj\u00f8lberg", + "author_inst": "National Institute of Occupational Health STAMI, Oslo, Norway" + }, + { + "author_name": "Fred Haugen", + "author_inst": "1National Institute of Occupational Health STAMI, Oslo, Norway" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.04.27.21256199", @@ -806252,157 +806279,73 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.04.29.441258", - "rel_title": "Allelic variation in Class I HLA determines pre-existing memory responses to SARS-CoV-2 that shape the CD8+ T cell repertoire upon viral exposure", + "rel_doi": "10.1101/2021.04.28.441880", + "rel_title": "Protracted yet coordinated differentiation of long-lived SARS-CoV-2-specific CD8+ T cells during COVID-19 convalescence", "rel_date": "2021-04-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.29.441258", - "rel_abs": "Effective presentation of antigens by HLA class I molecules to CD8+ T cells is required for viral elimination and generation of long-term immunological memory. In this study, we applied a single-cell, multi-omic technology to generate the first unified ex vivo characterization of the CD8+ T cell response to SARS-CoV-2 across 4 major HLA class I alleles. We found that HLA genotype conditions key features of epitope specificity, TCR /{beta} sequence diversity, and the utilization of pre-existing SARS-CoV-2 reactive memory T cell pools. Single-cell transcriptomics revealed functionally diverse T cell phenotypes of SARS-CoV-2-reactive T cells, associated with both disease stage and epitope specificity. Our results show that HLA variations influence pre-existing immunity to SARS-CoV-2 and shape the immune repertoire upon subsequent viral exposure.\n\nOne-Sentence SummaryWe perform a unified, multi-omic characterization of the CD8+ T cell response to SARS-CoV-2, revealing pre-existing immunity conditioned by HLA genotype.", - "rel_num_authors": 35, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.28.441880", + "rel_abs": "CD8+ T cells are important antiviral effectors that can potentiate long-lived immunity against COVID-19, but a detailed characterization of these cells has been hampered by technical challenges. We screened 21 well-characterized, longitudinally-sampled convalescent donors that recovered from mild COVID-19 against a collection of SARS-CoV-2 tetramers, and identified one participant with an immunodominant response against Nuc322-331, a peptide that is conserved in all the SARS-CoV-2 variants-of-concern reported to date. We conducted 38- parameter CyTOF phenotyping on tetramer-identified Nuc322-331-specific CD8+ T cells, and on CD4+ and CD8+ T cells recognizing the entire nucleocapsid and spike proteins from SARS- CoV-2, and took 32 serological measurements on longitudinal specimens from this participant. We discovered a coordination of the Nuc322-331-specific CD8+ T response with both the CD4+ T cell and antibody pillars of adaptive immunity. Nuc322-331-specific CD8+ T cells were predominantly central memory T cells, but continually evolved over a [~]6-month period of convalescence. We observed a slow and progressive decrease in the activation state and polyfunctionality of the Nuc322-331-specific CD8+ T cells, accompanied by an increase in their lymph-node homing and homeostatic proliferation potential. These results suggest that following a typical case of mild COVID-19, SARS-CoV-2-specific CD8+ T cells not only persist but continuously differentiate in a coordinated fashion well into convalescence, into a state characteristic of long-lived, self-renewing memory.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Joshua M Francis", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Del Leistritz-Edwards", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Augustine Dunn", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Christina Tarr", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Jesse Lehman", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Conor Dempsey", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Andrew Hamel", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Violeta Rayon", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Gang Liu", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Yuntong Wang", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Marcos Wille", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Melissa Durkin", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Kane Hadley", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Aswathy Sheen", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Benjamin Roscoe", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Mark Ng", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Graham Rockwell", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Margaret Manto", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Elizabeth Gienger", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "Joshua Nickerson", - "author_inst": "Repertoire Immune Medicines" - }, - { - "author_name": "- MGH COVID-19 Collection and Processing Team", - "author_inst": "-" - }, - { - "author_name": "Amir Moarefi", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Tongcui Ma", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Michael Noble", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Heeju Ryu", + "author_inst": "Fred Hutchison Cancer Research Center" }, { - "author_name": "Thomas Malia", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Matthew McGregor", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Philip D Bardwell", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Benjamin Babcock", + "author_inst": "Emory" }, { - "author_name": "William Gordon", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Jason Neidleman", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Joanna Swain", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Guorui Xie", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Mojca Skoberne", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Ashley F. George", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Karsten Sauer", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Julie Frouard", + "author_inst": "Gladstone Institutes" }, { - "author_name": "Tim Harris", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Victoria Murray", + "author_inst": "UCSF" }, { - "author_name": "Ananda W Goldrath", - "author_inst": "University of California, San Diego" + "author_name": "Gurjot Gill", + "author_inst": "UCSF" }, { - "author_name": "Alex K Shalek", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Eliver Ghosn", + "author_inst": "Emory" }, { - "author_name": "Anthony J Coyle", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Evan Newell", + "author_inst": "Fred Hutchison Cancer Research Center" }, { - "author_name": "Christophe Benoist", - "author_inst": "Harvard Medical School" + "author_name": "Sulggi Lee", + "author_inst": "UCSF" }, { - "author_name": "Daniel C Pregibon", - "author_inst": "Repertoire Immune Medicines" + "author_name": "Nadia Roan", + "author_inst": "University of California, San Francisco; and Gladstone Institutes" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "new results", "category": "immunology" }, @@ -808110,53 +808053,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.26.21256154", - "rel_title": "Optimal use of COVID19 Ag-RDT screening at border crossings to prevent community transmission: a modeling analysis", + "rel_doi": "10.1101/2021.04.26.21256136", + "rel_title": "Detecting in-school transmission of SARS-CoV-2 from case ratios and documented clusters", "rel_date": "2021-04-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.26.21256154", - "rel_abs": "BackgroundCountries around the world have implemented restrictions on mobility, especially cross-border travel to reduce or prevent SARS-CoV-2 community transmission. Rapid antigen testing (Ag-RDT), with on-site administration and rapid turnaround time may provide a valuable screening measure to ease cross-border travel while minimizing risk of local transmission. To maximize impact, we developed an optimal Ag-RDT screening algorithm for cross-border entry.\n\nMethodsUsing a previously developed mathematical model, we determined the daily number of imported COVID-19 cases that would generate no more than a relative 1% increase in cases over one month for different effective reproductive numbers (Rt) of the recipient country. We then developed an algorithm- for differing levels of Rt, arrivals per day, mode of travel, and SARS-CoV-2 prevalence amongst travelers-to determine the minimum proportion of people that would need Ag-RDT testing at border crossings to ensure no greater than the relative 1% community spread increase.\n\nFindingsWhen daily international arrivals and/or COVID-19 prevalence amongst arrivals increases, the proportion of arrivals required to test using Ag-RDT increases. At very high numbers of international arrivals/COVID-19 prevalence, Ag-RDT testing is not sufficient to prevent increased community spread, especially for lower levels of Rt. In these cases, Ag-RDT screening would need to be supplemented with other measures to prevent an increase in community transmission.\n\nInterpretationAn efficient Ag-RDT algorithm for SARS-CoV-2 testing depends strongly on Rt, volume of travel, proportion of land and air arrivals, test sensitivity, and COVID-19 prevalence among travelers.\n\nFundingUSAID, Government of the Netherlands", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.26.21256136", + "rel_abs": "Claims that in-person schooling has not amplified SARS-CoV-2 transmission are based on similar infection rates in schools and their surrounding communities and limited numbers of documented in-school transmission events. Simulations assuming high in-school transmission suggest that these metrics cannot exclude the possibility that transmission in schools exacerbated overall pandemic risks.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Joshua M Chevalier", - "author_inst": "Department of Global Health, Boston University School of Public Health, Boston, MA, USA" - }, - { - "author_name": "Karla Therese L. Sy", - "author_inst": "Department of Epidemiology, Boston University School of Public Health; Department of Global Health, Boston University School of Public Health" - }, - { - "author_name": "Sarah J Girdwood", - "author_inst": "Health Economics and Epidemiology Research Office, Department of Internal Medicine, School of Clinical Medicine, Faculty of Health Sciences, University of the W" + "author_name": "Kaitlyn Johnson", + "author_inst": "The University of Texas at Austin" }, { - "author_name": "Shaukat Khan", - "author_inst": "Clinton Health Access Initiative, Boston, MA, USA" + "author_name": "Michael Lachmann", + "author_inst": "Santa Fe Institute, Santa Fe, NM, USA" }, { - "author_name": "Heidi Albert", - "author_inst": "FIND, Cape Town, South Africa" + "author_name": "Madison Stoddard", + "author_inst": "Fractal Therapeutics" }, { - "author_name": "Amy Toporowski", - "author_inst": "FIND, Geneva, Switzerland" + "author_name": "Remy Pasco", + "author_inst": "The University of Texas at Austin" }, { - "author_name": "Emma Hannay", - "author_inst": "FIND, Geneva, Switzerland" + "author_name": "Spencer J Fox", + "author_inst": "The University of Texas at Austin" }, { - "author_name": "Sergio Carmona", - "author_inst": "FIND, Geneva, Switzerland" + "author_name": "Lauren Ancel Meyers", + "author_inst": "The University of Texas at Austin" }, { - "author_name": "Brooke E Nichols", - "author_inst": "Department of Global Health, Boston University School of Public Health; Health Economics and Epidemiology Research Office, Department of Internal Medicine, Scho" + "author_name": "Arijit Chakravarty", + "author_inst": "Fractal Therapeutics" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -810008,25 +809943,101 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.21.21255782", - "rel_title": "Mathematical modeling suggests pre-existing immunity to SARS-CoV-2", + "rel_doi": "10.1101/2021.04.21.21255898", + "rel_title": "Indicators for Risk of Airborne Transmission in Shared Indoor Environments and their application to COVID-19 Outbreaks", "rel_date": "2021-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.21.21255782", - "rel_abs": "Mathematical models have largely failed to predict the unfolding of the COVID-19 pandemic. We revisit several variants of the SEIR-model and investigate various adjustments to the model in order to achieve output consistent with measured data in Manaus, India and Stockholm. In particular, Stockholm is interesting due to the almost constant NPIs, which substantially simplifies the mathematical modeling. Analyzing mobility data for Stockholm, we argue that neither behavioral changes, age and activity stratification nor NPIs alone are sufficient to explain the observed pandemic progression. We find that the most plausible hypothesis is that a large portion of the population, between 40 to 60 percent, have some protection against infection with the original variant of SARS-CoV-2.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.21.21255898", + "rel_abs": "Some infectious diseases, including COVID-19, can be transmitted via aerosols that are emitted by an infectious person and inhaled by susceptible individuals. Most airborne transmission occurs at close proximity and is effectively reduced by physical distancing, but as time indoors increases, infections occur in those sharing room air despite maintaining distancing. There have been calls for quantified models to estimate the absolute and relative contribution of these different factors to infection risk. We propose two indicators of infection risk for this situation, i.e., relative risk parameter (Hr) and risk parameter (H). They combine the key factors that control airborne disease transmission indoors: virus-containing aerosol generation rate, breathing flow rate, masking and its quality, ventilation and particulate air cleaning rates, number of occupants, and duration of exposure. COVID-19 outbreaks show a clear trend in relation to these factors that is consistent with airborne infection The observed trends of outbreak size (attack rate) vs. H (Hr) allow us to recommend values of these parameters to minimize COVID-19 indoor infection risk. Transmission in typical pre-pandemic indoor spaces is highly sensitive to mitigation efforts. Previous outbreaks of measles, flu, and tuberculosis were assessed along with recently reported COVID-19 outbreaks. Measles outbreaks occur at much lower risk parameter values than COVID-19, while tuberculosis outbreaks are observed at much higher risk parameter values. Since both diseases are accepted as airborne, the fact that COVID-19 is less contagious than measles does not rule out airborne transmission. It is important that future outbreak reports include information on the nature and type of masking, ventilation and particulate-air cleaning rates, number of occupants, and duration of exposure, to allow us to understand the circumstances conducive to airborne transmission of different diseases.\n\nSynopsisWe propose two infection risk indicators for indoor spaces and apply them to COVID-19 outbreaks analysis and mitigation.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Marcus Carlsson", - "author_inst": "Lund University" + "author_name": "Zhe Peng", + "author_inst": "University of Colorado Boulder" }, { - "author_name": "Gad Hatem", - "author_inst": "Department of clinical sciences" + "author_name": "Andrea Pineda Rojas", + "author_inst": "CIMA, UMI-IFAECI/CNRS" }, { - "author_name": "Cecilia Soderberg-Naucler", - "author_inst": "Department of Medicine, Karolinska Institute" + "author_name": "Emilio Kropff", + "author_inst": "Leloir Institute - IIBBA/CONICET" + }, + { + "author_name": "William Bahnfleth", + "author_inst": "Pennsylvania State University" + }, + { + "author_name": "Giorgio Buonanno", + "author_inst": "University of Cassino and Southern Lazio" + }, + { + "author_name": "Stephanie J Dancer", + "author_inst": "NHS Lanarkshire" + }, + { + "author_name": "Jarek Kurnitski", + "author_inst": "Tallinn University of Technology" + }, + { + "author_name": "Yuguo Li", + "author_inst": "University of Hong Kong" + }, + { + "author_name": "Marcel G.L.C. Loomans", + "author_inst": "Eindhoven University of Technology" + }, + { + "author_name": "Linsey C. Marr", + "author_inst": "Virginia Tech" + }, + { + "author_name": "Lidia Morawska", + "author_inst": "Queensland University of Technology" + }, + { + "author_name": "William Nazaroff", + "author_inst": "University of California, Berkeley" + }, + { + "author_name": "Catherine Noakes", + "author_inst": "University of Leeds" + }, + { + "author_name": "Xavier Querol", + "author_inst": "IDAEA, Spanish Research Council" + }, + { + "author_name": "Chandra Sekhar", + "author_inst": "National University of Singapore" + }, + { + "author_name": "Raymond Tellier", + "author_inst": "McGill University" + }, + { + "author_name": "Trisha Greenhalgh", + "author_inst": "University of Oxford" + }, + { + "author_name": "Lydia Bourouiba", + "author_inst": "Massachusetts Institute of Technology" + }, + { + "author_name": "Atze Boerstra", + "author_inst": "BBA Binnenmilieu" + }, + { + "author_name": "Julian Tang", + "author_inst": "University of Leicester" + }, + { + "author_name": "Shelly Miller", + "author_inst": "University of Colorado Boulder" + }, + { + "author_name": "Jose L Jimenez", + "author_inst": "University of Colorado Boulder" } ], "version": "1", @@ -811609,61 +811620,49 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2021.04.26.21256081", - "rel_title": "Clinical validation of RCSMS: a rapid and sensitive CRISPR-Cas12a test for the molecular detection of SARS-CoV-2 from saliva", + "rel_doi": "10.1101/2021.04.24.21256040", + "rel_title": "The dark side of SARS-CoV-2 rapid antigen testing: screening asymptomatic patients.", "rel_date": "2021-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.26.21256081", - "rel_abs": "Early detection of SARS-CoV-2 using molecular techniques is paramount to the fight against COVID-19. Due to its high sensitivity and specificity, RT-qPCR is the \"gold standard\" method for this purpose. However, its technical requirements, processing time and elevated costs hamper its use towards massive and timely molecular testing for COVID-19 in rural and socioeconomically deprived areas of Latin America. The advent and rapid evolution of CRISPR-Cas technology has boosted the development of new pathogen detection methodologies. Recently, DETECTR -a combination of isothermal RT-LAMP amplification and Cas12a-mediated enzymatic detection-has been successfully validated in the Netherlands and the USA as a rapid and low-cost alternative to RT-qPCR for the detection of SARS-CoV-2 from nasopharyngeal swabs. Here, we evaluated the performance of RCSMS, a locally adapted variant of DETECTR, to ascertain the presence of SARS-CoV-2 in saliva samples from 276 patients in two hospitals in Lima, Peru (current status over a total of 350 samples). We show that a low-cost thermochemical treatment with TCEP/EDTA is sufficient to inactivate viral particles and cellular nucleases in saliva, eliminating the need to extract viral RNA with commercial kits, as well as the cumbersome nasopharyngeal swab procedure and the requirement of biosafety level 2 laboratories for molecular analyses. Our clinical validation shows that RCSMS detects up to 5 viral copies per reaction in 40 min, with sensitivity and specificity of 93.8% and 99.0% in the field, respectively, relative to RT-qPCR. Since CRISPR-Cas biosensors can be easily reprogrammed by using different guide RNA molecules, RCSMS has the potential to be quickly adapted for the detection of new SARS-CoV-2 variants. Notably, estimation of its negative and positive predictive values suggests that RCSMS can be confidently deployed in both high and low prevalence settings. Furthermore, our field study validates the use of lateral flow strips to easily visualize the presence of SARS-CoV-2, which paves the way to deploy RCSMS as a \"point of care\" test in environments with limited access to state-of-the-art diagnostic laboratories. In sum, RCSMS is a fast, efficient and inexpensive alternative to RT-qPCR for expanding COVID-19 testing capacity in low- and middle-income countries.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.24.21256040", + "rel_abs": "Most of the reports describing SARS-CoV-2 rapid antigen tests (RATs) performances derive from COVID-19 symptomatic subjects in outpatient settings during periods of highest incidence of infections and high rates of hospital admissions. Here we investigated the role of RATs in an Emergency Department, as a screening tool before admission for COVID-19 asymptomatic patients. Each patient was screened with two simultaneous nasopharyngeal swabs: one immediately analyzed at the bedside using RAT and the other sent to the laboratory for RT-PCR analysis. A total of 116 patients were screened at hospital admission in a 250-bed community hospital in Morges (EHC), Switzerland. With a disease prevalence of 6% based on RT-PCR results, RAT detected only two out of seven RT-PCR positive patients (sensitivity 28.6%) and delivered two false positive results (specificity 98.2%), thus resulting not fiable enough to be used as a screening method in this clinical scenario.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Joaqu\u00edn Abugatt\u00e1s N\u00fa\u00f1ez del Prado", - "author_inst": "Facultad de Ciencias y Filosof\u00eda, Universidad Peruana Cayetano Heredia, Lima, Per\u00fa" - }, - { - "author_name": "Ang\u00e9lica Quintana Reyes", - "author_inst": "Facultad de Ciencias y Filosof\u00eda, Universidad Peruana Cayetano Heredia, Lima, Per\u00fa" - }, - { - "author_name": "Juan Blume La Torre", - "author_inst": "Facultad de Ciencias y Filosof\u00eda, Universidad Peruana Cayetano Heredia, Lima, Per\u00fa" - }, - { - "author_name": "Renzo Guti\u00e9rrez-Loli", - "author_inst": "Facultad de Ciencias y Filosof\u00eda, Universidad Peruana Cayetano Heredia, Lima, Per\u00fa" + "author_name": "Giorgia Caruana", + "author_inst": "University of Lausanne" }, { - "author_name": "Alejandro Pinz\u00f3n Olejua", - "author_inst": "Department of Computer Science, Christian-Albrecht University of Kiel, Germany" + "author_name": "Laure-Line Lebrun", + "author_inst": "Ensemble Hospitalier de la Cote (EHC), Morges" }, { - "author_name": "Elena Chamorro Chirinos", - "author_inst": "Hospital Nacional Guillermo Almenara Yrigoyen, EsSalud, Lima, Per\u00fa" + "author_name": "Oriane Aebischer", + "author_inst": "Ensemble Hospitalier de la Cote (EHC), Morges" }, { - "author_name": "F\u00e9lix Antonio Loza Mauricio", - "author_inst": "Hospital Nacional Edgardo Rebagliati Martins, EsSalud, Lima, Per\u00fa" + "author_name": "Onya Opota", + "author_inst": "Institute of Microbiology, University of Lausanne and Lausanne University Hospital" }, { - "author_name": "Jorge L Magui\u00f1a", - "author_inst": "Instituto de Evaluaci\u00f3n de Tecnolog\u00edas en Salud e Investigaci\u00f3n (IETSI), EsSalud, Lima, Per\u00fa" + "author_name": "Luis Urbano", + "author_inst": "Ensemble Hospitalier de la Cote (EHC), Morges" }, { - "author_name": "Julio Leon", - "author_inst": "IMS RIKEN Center for Integrative Medical Sciences, Japan" + "author_name": "Mikael DeRham", + "author_inst": "Ensemble Hospitalier de la Cote (EHC), Morges" }, { - "author_name": "Piere Rodriguez-Aliaga", - "author_inst": "Department of Biology, Stanford University, California, USA" + "author_name": "Oscar Marchetti", + "author_inst": "Ensemble Hospitalier de la Cote (EHC), Morges" }, { - "author_name": "Edward M\u00e1laga-Trillo", - "author_inst": "Facultad de Ciencias y Filosof\u00eda, Universidad Peruana Cayetano Heredia, Lima, Per\u00fa" + "author_name": "Gilbert Greub", + "author_inst": "University of Lausanne" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -813459,39 +813458,35 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.04.25.441372", - "rel_title": "Control-theoretic immune tradeoffs explain SARS-CoV-2 virulence and transmission variation", + "rel_doi": "10.1101/2021.04.26.440920", + "rel_title": "A SARS CoV-2 nucleocapsid vaccine protects against distal viral dissemination", "rel_date": "2021-04-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.25.441372", - "rel_abs": "Dramatic variation in SARS-CoV-2 virulence and transmission between hosts has driven the COVID-19 pandemic. The complexity and dynamics of the immune response present a challenge to understanding variation in SARS-CoV-2 infections. To address this challenge, we apply control theory, a framework used to study complex feedback systems, to establish rigorous mathematical bounds on immune responses. Two mechanisms of SARS-CoV-2 biology are sufficient to create extreme variation between hosts: (1) a sparsely expressed host receptor and (2) potent, but not unique, suppression of interferon. The resulting model unifies disparate and unexplained features of the SARS-CoV-2 pandemic, predicts features of future viruses that threaten to cause pandemics, and identifies potential interventions.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.26.440920", + "rel_abs": "The SARS CoV-2 pandemic has killed millions of people. This viral infection can also result in substantial morbidity, including respiratory insufficiency and neurological manifestations, such as loss of smell and psychiatric diseases. Most SARS CoV-2 vaccines are based on the spike antigen, and although they have shown extraordinary efficacy at preventing severe lung disease and death, they do not always confer sterilizing immune protection. We performed studies in K18-hACE2 mice to evaluate whether the efficacy of SARS CoV-2 vaccines could be augmented by incorporating nucleocapsid as a vaccine antigen. We vaccinated mice with adenovirus-based vaccines encoding spike antigen alone, nucleocapsid antigen alone, or combined spike and nucleocapsid antigens. Mice were then challenged intranasally with SARS CoV-2, and acute viral loads were quantified at a proximal site of infection (lung) and a distal site of infection (brain). Interestingly, the spike-based vaccine conferred acute protection in the lung, but not in the brain. The spike-based vaccine conferred acute protection in the brain only if combined with the nucleocapsid-based vaccine. These findings suggest that nucleocapsid-specific immunity is important for the distal control of SARS CoV-2, warranting the inclusion of nucleocapsid in next-generation COVID-19 vaccines.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Anish A Sarma", - "author_inst": "California Institute of Technology" - }, - { - "author_name": "Aartik Sarma", - "author_inst": "University of California-San Francisco" + "author_name": "Jacob Class", + "author_inst": "Department of Microbiology & Immunology, University of Illinois Chicago College of Medicine, Chicago, IL 60612" }, { - "author_name": "Marie Csete", - "author_inst": "-" + "author_name": "Tanushree Dangi", + "author_inst": "Department of Microbiology and Immunology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611" }, { - "author_name": "Peter P Lee", - "author_inst": "City of Hope Cancer Center" + "author_name": "Justin Richner", + "author_inst": "Department of Microbiology & Immunology, University of Illinois Chicago College of Medicine, Chicago, IL 60612" }, { - "author_name": "John C Doyle", - "author_inst": "California Institute of Technology" + "author_name": "Pablo Penaloza-MacMaster", + "author_inst": "Department of Microbiology and Immunology, Northwestern University Feinberg School of Medicine, Chicago, IL 60611" } ], "version": "1", "license": "cc_by_nd", "type": "new results", - "category": "systems biology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.04.26.441501", @@ -815013,57 +815008,49 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.04.21.21255880", - "rel_title": "Efficacy of universal masking for source control and personal protection from simulated cough and exhaled aerosols in a room", + "rel_doi": "10.1101/2021.04.22.21255908", + "rel_title": "Learning from the resilience of hospitals and their staff to the COVID-19 pandemic: a scoping review.", "rel_date": "2021-04-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.21.21255880", - "rel_abs": "Face masks reduce the spread of infectious respiratory diseases such as COVID-19 by blocking aerosols produced during coughs and exhalations (\"source control\"). Masks also slow and deflect cough and exhalation airflows, which changes the dispersion of aerosols. Factors such as the directions in which people are facing (orientation) and separation distance also affect aerosol dispersion. However, it is not clear how masking, orientation, and distance interact. We placed a respiratory aerosol simulator (\"source\") and a breathing simulator (\"recipient\") in a 3 m x 3 m chamber and measured aerosol concentrations for different combinations of masking, orientation, and separation distance. When the simulators were front-to-front during coughing, masks reduced the 15-minute mean aerosol concentration at the recipient by 92% at 0.9 and 1.8 m separation. When the simulators were side-by-side, masks reduced the concentration by 81% at 0.9 m and 78% at 1.8 m. During breathing, masks reduced the aerosol concentration by 66% when front-to-front and 76% when side-by-side at 0.9 m. Similar results were seen at 1.8 m. When the simulators were unmasked, changing the orientations from front-to-front to side-by-side reduced the cough aerosol concentration by 59% at 0.9 m and 60% at 1.8 m. When both simulators were masked, changing the orientations did not significantly change the concentration at either distance during coughing or breathing. Increasing the distance between the simulators from 0.9 m to 1.8 m during coughing reduced the aerosol concentration by 25% when no masks were worn but had little effect when both simulators were masked. During breathing, when neither simulator was masked, increasing the separation reduced the concentration by 13%, which approached significance, while the change was not significant when both source and recipient were masked. Our results show that universal masking reduces exposure to respiratory aerosol particles regardless of the orientation and separation distance between the source and recipient.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.22.21255908", + "rel_abs": "BackgroundThe COVID-19 pandemic has brought huge strain on hospitals worldwide. It is crucial that we gain a deeper understanding of hospital resilience in this unprecedented moment. This paper aims to report the key strategies and recommendations in terms of hospitals and professionals resilience to the COVID-19 pandemic, as well as the quality and limitations of research in this field at present.\n\nMethodsWe conducted a scoping review of evidence on the resilience of hospitals and their staff during the COVID-19 crisis in the first half of 2020. The Stephen B. Thacker CDC Library website was used to identify papers meeting the eligibility criteria, from which we selected 65 publications. After having extracted data, we presented the results synthesis using an \"effects-strategies-impacts\" resilience framework.\n\nResultsWe found a wealth of research rapidly produced in the first half of 2020, describing different strategies used to improve hospitals resilience, particularly in terms of 1) planning, management, and security, and 2) human resources. Research focuses mainly on interventions related to healthcare workers well-being and mental health, protection protocols, space reorganization, personal protective equipment and resources management, work organization, training, e-health and the use of technologies. Hospital financing, information and communication, and governance were less represented in the literature.\n\nConclusionThe selected literature was dominated by quantitative descriptive case studies, sometimes lacking consideration of methodological limitations. The review revealed a lack of holistic research attempting to unite the topics within a resilience framework. Research on hospitals resilience would benefit from a greater range of analysis to draw more nuanced and contextualized lessons from the multiple specific responses to the crisis. We identified key strategies on how hospitals maintained their resilience when confronted with the COVID-19 pandemic and a range of recommendations for practice.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "William G Lindsley", - "author_inst": "National Institute for Occupational Safety and Health" - }, - { - "author_name": "Donald H Beezhold", - "author_inst": "National Institute for Occupational Safety and Health" - }, - { - "author_name": "Raymond C Derk", - "author_inst": "National Institute for Occupational Safety and Health" + "author_name": "Lola Traverson", + "author_inst": "CEPED, Institute for Research on Sustainable Development, IRD-Universite de Paris, ERL INSERM SAGESU, Paris, France" }, { - "author_name": "Jayme Coyle", - "author_inst": "National Institute for Occupational Safety and Health" + "author_name": "Jack Stennett", + "author_inst": "CEPED, Institute for Research on Sustainable Development, IRD-Universite de Paris, ERL INSERM SAGESUD, Paris, France" }, { - "author_name": "Francoise M Blachere", - "author_inst": "National Institute for Occupational Safety and Health" + "author_name": "Isadora Mathevet", + "author_inst": "CEPED, Institute for Research on Sustainable Development, IRD-Universite de Paris, ERL INSERM SAGESUD, Paris, France" }, { - "author_name": "Theresa Boots", - "author_inst": "National Institute for Occupational Safety and Health" + "author_name": "Amanda Correia Paes Zacarias", + "author_inst": "Department of Public Health, Institute Aggeu Magalhaes (IAM), Fondation Oswaldo Cruz (Fiocruz), Recife, Brazil" }, { - "author_name": "Jeffrey S Reynolds", - "author_inst": "National Institute for Occupational Safety and Health" + "author_name": "Karla Paz de Sousa", + "author_inst": "Department of Public Health, Institute Aggeu Magalhaes (IAM), Fondation Oswaldo Cruz (Fiocruz), Recife, Brazil" }, { - "author_name": "Walter G McKinney", - "author_inst": "National Institute for Occupational Safety and Health" + "author_name": "Andrea Andrade", + "author_inst": "Department of Public Health, Institute Aggeu Magalhaes (IAM), Fondation Oswaldo Cruz (Fiocruz), Recife, Brazil" }, { - "author_name": "Erik Sinsel", - "author_inst": "National Institute for Occupational Safety and Health" + "author_name": "Kate Zinszer", + "author_inst": "University of Montreal, Montreal, Canada" }, { - "author_name": "John D Noti", - "author_inst": "National Institute for Occupational Safety and Health" + "author_name": "Valery Ridde", + "author_inst": "CEPED, Institute for Research on Sustainable Development, IRD-Universite de Paris, ERL INSERM SAGESUD, Paris, France" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -816719,139 +816706,35 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.04.20.440658", - "rel_title": "Gut microbiota diversity and C-Reactive Protein are predictors of disease severity in COVID-19 patients", + "rel_doi": "10.1101/2021.04.23.441125", + "rel_title": "Computational investigation reveals that the mutant strains of SARS-CoV2 are highly infectious than wildtype", "rel_date": "2021-04-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.20.440658", - "rel_abs": "Risk factors for COVID-19 disease severity are still poorly understood. Considering the pivotal role of gut microbiota on host immune and inflammatory functions, we investigated the association between changes in gut microbiota composition and the clinical severity of COVID-19. We conducted a multicentre cross-sectional study prospectively enrolling 115 COVID-19 patients categorized according to: 1) WHO Clinical Progression Scale - mild 19 (16.5%), moderate 37 (32.2%) or severe 59 (51.3%); and 2) location of recovery from COVID-19 - ambulatory 14 (household isolation; 12.2%), hospitalized in ward 40 (34.8%) or intensive care unit 61 (53.0%). Gut microbiota analysis was performed through 16S rRNA gene sequencing and data obtained was further related with clinical parameters of COVID-19 patients. Risk factors for COVID-19 severity were identified by univariate and multivariable logistic regression models.\n\nIn comparison with mild COVID-19 patients, the gut microbiota of moderate and severe patients has: a) lower Firmicutes/Bacteroidetes ratio, b) higher abundance of Proteobacteria; and c) lower abundance of beneficial butyrate-producing bacteria such as Roseburia and Lachnospira genera. Multivariable regression analysis showed that Shannon index diversity (odds ratio [OR] 2.85 [95% CI 1.09-7.41]; p=0.032) and C-Reactive Protein (OR 3.45 [95% CI 1.33-8.91]; p=0.011) were risk factors for COVID-19 severe disease (a score of 6 or higher in WHO clinical progression scale).\n\nIn conclusion, our results demonstrated that hospitalised moderate and severe COVID-19 patients have microbial signatures of gut dysbiosis and for the first time, the gut microbiota diversity is pointed out as a prognostic biomarker for COVID-19 disease severity.", - "rel_num_authors": 30, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.23.441125", + "rel_abs": "Remarkable infectivity of severe acute respiratory syndrome-coronavirus 2 (SARS-CoV2) is due to the rapid emergence of various strains, thus enable the virus to rule the world. Over the course of SARS-CoV2 pandemic, the scientific communities worldwide are responding to newly emerging genetic variants. However, the mechanism behind the persistent infection of these variants is still not known due to the paucity of study of these variants at molecular level. In this scenario, computational methods have immense utility in understanding the molecular and functional properties of different variants. Therefore, in this study various mutants (MTs) of SpikeS1 receptor binding domain (RBD) of highly infectious SARS-CoV2 strains were carried and elucidated the protein structure and dynamics using molecular dynamics (MD) approach. MD simulation study showed that all MTs exhibited stable structures with altered functional properties. Furthermore, the binding strength of different MTs along with WT (wildtype) was revealed through protein-protein docking and observed that MTs showed high binding affinities than WT. Hence, this study shed light on the molecular basis of infection caused by different variants of SARS-CoV2, which might play an important role in to cease the transmission and pathogenesis of virus and also implicate in rational designing of a specific drug.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Andre Moreira-Rosario", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Claudia Marques", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Helder Pinheiro", - "author_inst": "Infectious Diseases Department Hospital Curry Cabral, Centro Hospitalar Universitario Lisboa Central" - }, - { - "author_name": "Joao Ricardo Araujo", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Pedro Ribeiro", - "author_inst": "Centro de Medicina Laboratorial Germano de Sousa, Lisboa, Portugal" - }, - { - "author_name": "Rita Rocha", - "author_inst": "i3S - Instituto de Investigacao e Inovacao em Saude, Universidade do Porto, Portugal" - }, - { - "author_name": "Ines Mota", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Diogo Pestana", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Rita Ribeiro", - "author_inst": "Centro de Medicina Laboratorial Germano de Sousa, Lisboa, Portugal" - }, - { - "author_name": "Ana Pereira", - "author_inst": "Centro de Medicina Laboratorial Germano de Sousa, Lisboa, Portugal" - }, - { - "author_name": "Maria Jose de Sousa", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Jose Pereira-Leal", - "author_inst": "Ophiomics Precision Medicine, Lisboa, Portugal" - }, - { - "author_name": "Jose de Sousa", - "author_inst": "Centro de Medicina Laboratorial Germano de Sousa, Lisboa, Portugal" - }, - { - "author_name": "Juliana Morais", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Diana Teixeira", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Julio Cesar Rocha", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Marta Silvestre", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" - }, - { - "author_name": "Nuno Principe", - "author_inst": "Department of Emergency and Intensive Care Medicine, Sao Joao University Hospital Center - Porto" - }, - { - "author_name": "Nuno Gatta", - "author_inst": "Department of Emergency and Intensive Care Medicine, Sao Joao University Hospital Center - Porto" - }, - { - "author_name": "Jose Amado", - "author_inst": "Department of Emergency and Intensive Care Medicine, Sao Joao University Hospital Center - Porto" - }, - { - "author_name": "Lurdes Santos", - "author_inst": "Infectious Diseases Service - ID Intensive Care Unit, Sao Joao University Hospital Center - Faculty of Medicine, Porto" - }, - { - "author_name": "Fernando Maltez", - "author_inst": "Infectious Diseases Department Hospital Curry Cabral, Centro Hospitalar Universitario Lisboa Central, Lisboa" - }, - { - "author_name": "Ana Boquinhas", - "author_inst": "Emergency Department, CUF Infante Santo Hospital, Lisboa, Portugal" - }, - { - "author_name": "Germano de Sousa", - "author_inst": "Centro de Medicina Laboratorial Germano de Sousa, Lisboa, Portugal" - }, - { - "author_name": "Nuno Germano", - "author_inst": "Polyvalent Intensive Care Unit, Hospital Curry Cabral, Centro Hospitalar Universitario Lisboa Central, Lisboa, Portugal" - }, - { - "author_name": "Goncalo Sarmento", - "author_inst": "Internal Medicine Department, Centro Hospitalar Entre Douro e Vouga, Santa Maria da Feira, Portugal" - }, - { - "author_name": "Cristina Granja", - "author_inst": "Anesthesiology Department, Centro Hospital Universitario Sao Joao, Porto, Portugal" + "author_name": "Rakesh Kumar", + "author_inst": "All India Institute of Medical Sciences" }, { - "author_name": "Pedro Povoa", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" + "author_name": "Rahul Kumar", + "author_inst": "All India Institute of Medical Sciences" }, { - "author_name": "Ana Faria", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" + "author_name": "Harsh Goel", + "author_inst": "All India Institute of Medical Sciences" }, { - "author_name": "Conceicao Calhau", - "author_inst": "Faculdade de Ciencias Medicas|NOVA Medical School, Universidade NOVA de Lisboa" + "author_name": "Pranay Tanwar", + "author_inst": "All India Institute of Medical Sciences" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.04.23.441024", @@ -818637,61 +818520,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.14.21255443", - "rel_title": "Association of in-hospital use of ACE-I/ARB and COVID-19 outcomes in African American population", + "rel_doi": "10.1101/2021.04.19.21252978", + "rel_title": "Mid-Regional pro-Adrenomedullin (MR-proADM), C-Reactive Protein (CRP) and Other Biomarkers in the Early Identification of Disease Progression in COVID-19 Patients in the Acute NHS Setting", "rel_date": "2021-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.14.21255443", - "rel_abs": "ImportanceThe ACE D allele is more prevalent among African Americans (AA) compared to other races/ethnicities and has previously been associated with severe COVID-19 pathogenesis through excessive ACE1 activity. ACE-I/ARBs may counteract this mechanism, but their association with COVID-19 outcomes has not been specifically tested in the AA population.\n\nObjectivesTo determine whether the use of ACE-I/ARBs is associated with COVID-19 in-hospital mortality in AA compared with non-AA population.\n\nDesign, Setting, and ParticipantsIn this observational, retrospective study, patient-level data were extracted from the Mount Sinai Health Systems (MSHS) electronic medical record (EMR) database, and 6,218 patients with a laboratory-confirmed COVID-19 diagnosis from February 24 to May 31, 2020 were identified as ACE-I/ARB users.\n\nExposuresPatients with an active prescription from January 1, 2019 up to the date of admission for ACE-I/ARB (outpatient use) and patients administered ACE-I/ARB during hospitalization (in-hospital use) were identified.\n\nMain Outcomes and MeasuresThe primary outcome was in-hospital mortality, assessed in the entire, AA, and non-AA population.\n\nResultsOf the 6,218 COVID-19 patients, 1,138 (18.3%) were ACE-I/ARB users. In a multivariate logistic regression model, ACE-I/ARB use was independently associated with reduced risk of in-hospital mortality in the entire population (OR, 0.655; 95% CI, 0.505-0.850; P=0.001), AA population (OR, 0.44; 95% CI, 0.249-0.779; P=0.005), and non-AA population (OR, 0.748, 95% CI, 0.553-1.012, P=0.06). In the AA population, in-hospital use of ACE-I/ARBs was associated with improved mortality (OR, 0.378; 95% CI, 0.188-0.766; P=0.006) while outpatient use was not (OR, 0.889; 95% CI, 0.375-2.158; P=0.812). When analyzing each medication class separately, ARB in-hospital use was significantly associated with reduced in-hospital mortality in the AA population (OR, 0.196; 95% CI, 0.074-0.516; P=0.001), while ACE-I use was not associated with impact on mortality in any population.\n\nConclusion and RelevanceIn-hospital use of ARBs was associated with a significant reduction in in-hospital mortality among COVID-19-positive AA patients. These results support further investigation of ARBs to improve outcomes in AA patients at high risk for COVID-19-related mortality.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.19.21252978", + "rel_abs": "AimsThere is a lack of biomarkers validated for assessing clinical deterioration in COVID-19 patients upon presentation to secondary or tertiary care. This evaluation looked at the potential clinical application of C-Reactive Protein, Procalcitonin, Mid-Regional pro-adrenomedullin (MR-proADM) and White Cell Count to support prediction of clinical outcomes.\n\nMethods135 patients presenting to Hampshire Hospitals NHS Foundation Trust between April and June 2020 confirmed to have COVID-19 via RT-qPCR were included. Biomarkers from within 24 hours of admission were used to predict disease progression by Cox regression and area under the receiver operating characteristic (AUROC) curves. The endpoints assessed were 30-day all-cause mortality, intubation and ventilation, critical care admission and non-invasive ventilation (NIV) use.\n\nResultsElevated MR-proADM was shown to have the greatest ability to predict 30-day mortality adjusting for age, cardiovascular, renal and neurological disease. A significant association was also noted between raised MR-proADM and CRP concentrations and the requirement for critical care admission and non-invasive ventilation.\n\nConclusionsThe measurement of MR-proADM and CRP in patients with confirmed COVID-19 infection upon admission shows significant potential to support clinicians in identifying those at increased risk of disease progression and need for higher level care, subsequently enabling prompt escalation in clinical interventions.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Shilong Li", - "author_inst": "Sema4, Stamford, CT, USA" + "author_name": "Nathan A. Moore", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Rangaprasad Sarangarajan", - "author_inst": "BERG, 500 Old Connecticut Path, Bldg B 3rd Floor, Framingham, MA, USA." + "author_name": "Rebecca Williams", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Tomi Jun", - "author_inst": "Division of Hematology & Medical Oncology, Icahn School of Medicine at Mount Sinai, New York, NY, USA." + "author_name": "Matilde Mori", + "author_inst": "University of Southampton, School of Medicine" }, { - "author_name": "Yu-Han Kao", - "author_inst": "Sema4, Stamford, CT, USA" + "author_name": "Beatrice Bertolusso", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Zichen Wang", - "author_inst": "Sema4, Stamford, CT, USA" + "author_name": "Gabrielle Vernet", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Emilio Schadt", - "author_inst": "Sema4, Stamford, CT, USA" + "author_name": "Jessica Lynch", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Michael A. Kiebish", - "author_inst": "BERG, 500 Old Connecticut Path, Bldg B 3rd Floor, Framingham, MA, USA." + "author_name": "Peter Philipson", + "author_inst": "University of Newcastle, School of Mathematics, Statistics and Physics" }, { - "author_name": "Elder Granger", - "author_inst": "BERG, 500 Old Connecticut Path, Bldg B 3rd Floor, Framingham, MA, USA." + "author_name": "Thomas Ledgerwood", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Niven R. Narain", - "author_inst": "BERG, 500 Old Connecticut Path, Bldg B 3rd Floor, Framingham, MA, USA." + "author_name": "Stephen P. Kidd", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Rong Chen", - "author_inst": "Sema4, Stamford, CT, USA" + "author_name": "Claire Thomas", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Eric E. Schadt", - "author_inst": "Sema4, Stamford, CT, USA" + "author_name": "Veronica Garcia-Arias", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" }, { - "author_name": "Li Li", - "author_inst": "Sema4, Stamford, CT, USA" + "author_name": "Michelle Young", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Kordo Saeed", + "author_inst": "University of Southampton, School of Medicine. University Hospital Southampton NHS Foundation Trust" + }, + { + "author_name": "Kirsty Gordon", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Nicholas Cortes", + "author_inst": "Basingstoke and North Hampshire Hospital, Hampshire Hospitals NHS Foundation Trust. University Hospital Southampton NHS Foundation Trust. Gibraltar Health Autho" } ], "version": "1", @@ -820538,87 +820433,43 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.20.440676", - "rel_title": "Eicosanoid signaling as a therapeutic target in middle-aged mice with severe COVID-19", + "rel_doi": "10.1101/2021.04.21.440680", + "rel_title": "Human Taste Cells Express ACE2: A Portal for SARS-CoV-2 Infection", "rel_date": "2021-04-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.20.440676", - "rel_abs": "Coronavirus disease 2019 (COVID-19) is especially severe in aged populations1. Resolution of the COVID-19 pandemic has been advanced by the recent development of SARS-CoV-2 vaccines, but vaccine efficacy is partly compromised by the recent emergence of SARS-CoV-2 variants with enhanced transmissibility2. The emergence of these variants emphasizes the need for further development of anti-SARS-CoV-2 therapies, especially in aged populations. Here, we describe the isolation of a new set of highly virulent mouse-adapted viruses and use them to test a novel therapeutic drug useful in infections of aged animals. Initially, we show that many of the mutations observed in SARS-CoV-2 during mouse adaptation (at positions 417, 484, 501 of the spike protein) also arise in humans in variants of concern (VOC)2. Their appearance during mouse adaptation indicates that immune pressure is not required for their selection. Similar to the human infection, aged mice infected with mouse-adapted SARS-CoV-2 develop more severe disease than young mice. In murine SARS, in which severity is also age-dependent, we showed that elevated levels of an eicosanoid, prostaglandin D2 (PGD2) and of a phospholipase, PLA2G2D, contributed to poor outcomes in aged mice3,4. Using our virulent mouse-adapted SARS-CoV-2, we show that infection of middle-aged mice lacking expression of DP1, a PGD2 receptor, or PLA2G2D are protected from severe disease. Further, treatment with a DP1 antagonist, asapiprant, protected aged mice from a lethal infection. DP1 antagonism is one of the first interventions in SARS-CoV-2-infected animals that specifically protects aged animals, and demonstrates that the PLA2G2D-PGD2/DP1 pathway is a useful target for therapeutic interventions. (Words: 254)", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.21.440680", + "rel_abs": "Loss and changes in taste and smell are well-reported symptoms of SARS-CoV-2 infection. The virus targets cells for entry by high affinity binding of its spike protein to cell-surface angiotensin-converting enzyme-2 (ACE2). It was not known whether ACE2 is expressed on taste receptor cells (TRCs) nor if TRCs are infected directly. Using an in-situ hybridization (ISH) probe and an antibody specific to ACE2, it seems evident that ACE2 is present on a subpopulation of specialized TRCs, namely, PLC{beta}2 positive, Type II cells in taste buds in taste papillae. Fungiform papillae (FP) of a SARS-CoV-2+ patient exhibiting symptoms of COVID-19, including taste changes, were biopsied. Based on ISH, replicating SARS-CoV-2 was present in Type II cells of this patient. Therefore, taste Type II cells provide a portal for viral entry that predicts vulnerabilities to SARS-CoV-2 in the oral cavity. The continuity and cell turnover of the FP taste stem cell layer of the patient were disrupted during infection and had not fully recovered 6 weeks post symptom onset. Another patient suffering post-COVID-19 taste disturbances also had disrupted stem cells. These results indicate that a COVID-19 patient who experienced taste changes had replicating virus in their taste buds and that SARS-CoV-2 infection results in deficient stem cell turnover needed for differentiation into TRCs.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Stanley Perlman", - "author_inst": "University of Iowa" - }, - { - "author_name": "Lok Yin Roy Wong", - "author_inst": "University of Iowa" - }, - { - "author_name": "Jian Zheng", - "author_inst": "University of Iowa" - }, - { - "author_name": "Kevin Wilhelmsen", - "author_inst": "BIOAGE Labs" - }, - { - "author_name": "Kun Li", - "author_inst": "University of Iowa" - }, - { - "author_name": "Miguel E Ortiz Bezara", - "author_inst": "University of Iowa" - }, - { - "author_name": "Nicholas J Schnicker", - "author_inst": "University of Iowa" - }, - { - "author_name": "Alejandro A A Pezzulo", - "author_inst": "University of Iowa Roy J. and Lucille A. Carver College of Medicine" - }, - { - "author_name": "Peter J Szachowicz", - "author_inst": "University of Iowa" - }, - { - "author_name": "Klaus Klumpp", - "author_inst": "BIOAGE Labs" + "author_name": "Maire Doyle", + "author_inst": "NIA/NIH" }, { - "author_name": "Fred Aswad", - "author_inst": "BIOAGE Labs" + "author_name": "Ashley Appleton", + "author_inst": "NIA/NIH" }, { - "author_name": "Justin Rebo", - "author_inst": "BIOAGE Labs" + "author_name": "Qing-Rong Liu", + "author_inst": "NIA/NIH" }, { - "author_name": "Shut Narumiya", - "author_inst": "Kyoto University" - }, - { - "author_name": "Makoto Murakami", - "author_inst": "The University of Tokyo" - }, - { - "author_name": "David Meyerholz", - "author_inst": "University of Iowa" + "author_name": "Qin Yao", + "author_inst": "NIA/NIH" }, { - "author_name": "Kristen Fortney", - "author_inst": "BIOAGE Labs" + "author_name": "Caio Henrique Mazucanti", + "author_inst": "NIA/NIH" }, { - "author_name": "Paul B McCray", - "author_inst": "University of Iowa" + "author_name": "Josephine M Egan", + "author_inst": "NIA/NIH" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "new results", - "category": "microbiology" + "category": "pathology" }, { "rel_doi": "10.1101/2021.04.21.440833", @@ -822312,41 +822163,89 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.04.15.21255533", - "rel_title": "Evaluation of seven different rapid methods for nucleic acid detection of SARS-COV-2 virus", + "rel_doi": "10.1101/2021.04.17.21255663", + "rel_title": "Asymptomatic or mild symptomatic SARS-CoV-2 infection elicits durable neutralizing antibody responses in children and adolescents", "rel_date": "2021-04-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.15.21255533", - "rel_abs": "BackgroundIn the current COVID-19 pandemic there is mass screening of SARS-CoV-2 happening round the world due to the extensive spread of the infections. There is a high demand for rapid diagnostic tests to expedite identification of cases and to facilitate early isolation and control spread. Hence this study evaluates seven different rapid nucleic acid detection assays that are commercially available for SARS-CoV-2 virus detection.\n\nMethodsNasopharyngeal samples were collected from 4859 participants and were tested for SARS-CoV-2 virus by the gold standard RT-PCR method along with one of these seven rapid methods of detection. Evaluation of the rapid nucleic acid detection assays was done by comparing the results of these rapid methods with the gold standard RT-qPCR results for SARS-COV-2 detection.\n\nResultsAQ-TOP had the highest sensitivity (98%) and strong kappa value of 0.943 followed by Genechecker and Abbot ID NOW. The POCKIT (ii RT-PCR) assay had the highest test accuracy of 99.29% followed by Genechecker and Cobas Liat. Atila iAMP showed the highest percentage of invalid reports (35.5%) followed by AQ-TOP with 6% and POCKIT with 3.7% of invalid reports.\n\nConclusionGenechecker system, Abbott ID NOW and Cobas Liat, were found to have best performance and agreement when compared to the standard RT-PCR for COVID-19 detection. With further research, these rapid tests have the potential to be employed in large scale screening of COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.17.21255663", + "rel_abs": "As SARS-CoV-2 continues to spread globally, questions have emerged regarding the strength and durability of immune responses in specific populations. In this study, we evaluated humoral immune responses in 69 children and adolescents with asymptomatic or mild symptomatic SARS-CoV-2 infection. We detected robust IgM, IgG, and IgA antibody responses to a broad array of SARS-CoV-2 antigens at the time of acute infection and 2 and 4 months after acute infection in all participants. Notably, these antibody responses were associated with virus neutralizing activity that was still detectable 4 months after acute infection in 94% of children. Moreover, antibody responses and neutralizing activity in sera from children and adolescents were comparable or superior to those observed in sera from 24 adults with mild symptomatic infection. Taken together, these findings indicate children and adolescents with mild or asymptomatic SARS-CoV-2 infection generate robust and durable humoral immune responses that are likely to protect from reinfection.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Sally Mahmoud", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" + "author_name": "Carolina Garrido", + "author_inst": "Duke University School of Medicine" }, { - "author_name": "Esra Ibrahim", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" + "author_name": "Jillian H Hurst", + "author_inst": "Duke University School of Medicine" }, { - "author_name": "Subhashini Ganesan", - "author_inst": "G42 Healthcare" + "author_name": "Cynthia G. Lorang", + "author_inst": "Duke University School of Medicine" }, { - "author_name": "Bhagyashree Thakre", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" + "author_name": "Jhoanna N. Aquino", + "author_inst": "Duke University School of Medicine" }, { - "author_name": "Juliet Teddy", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" + "author_name": "Javier Rodriguez", + "author_inst": "Duke University School of Medicine" }, { - "author_name": "Preety Raheja", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" + "author_name": "Trevor S. Pfeiffer", + "author_inst": "Duke University School of Medicine" }, { - "author_name": "Walid Zaher", - "author_inst": "G42 Healthcare Abu Dhabi, UAE" + "author_name": "Tulika Singh", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Eleanor C. Semmes", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Debra J. Lugo", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Alexandre T. Rotta", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Nicholas A. Turner", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Thomas W. Burke", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Micah T McClain", + "author_inst": "Duke University Medical Center" + }, + { + "author_name": "Elizabeth A. Petzold", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Sallie R. Permar", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "M. Anthony Moody", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Christopher W. Woods", + "author_inst": "Duke University School of Medicine" + }, + { + "author_name": "Matthew S Kelly", + "author_inst": "Duke University" + }, + { + "author_name": "Genevieve G. Fouda", + "author_inst": "Duke University School of Medicine" } ], "version": "1", @@ -824138,95 +824037,35 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.04.20.440651", - "rel_title": "Comparison of Mucosal and Intramuscular Immunization against SARS-CoV-2 with Replication-Defective and Replicating Single-cycle Adenovirus Vaccines", + "rel_doi": "10.1101/2021.04.19.440446", + "rel_title": "Inactivation of SARS-CoV-2 in chlorinated swimming pool water", "rel_date": "2021-04-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.20.440651", - "rel_abs": "SARS-CoV-2 enters the body at mucosal surfaces, such as the nose and lungs. These events involve a small number of virions at these mucosal barriers and are therefore a strategic point to stop a COVID-19 infection before it starts. Despite this, most vaccines against COVID-19 are being injected into the muscle where they will not generate the highest levels of mucosal protection. The vaccines that are approved for use in humans are all replication-defective (RD) mRNA, DNA, or adenovirus (Ad) vaccines that do not amplify antigen transgenes. We developed single cycle adenovirus (SC-Ad) vectors that replicate antigen genes up to 10,000-fold in human cells, but that are disabled from producing infectious Ad particles. We show here that SC-Ad expressing the full-length SARS-CoV-2 spike protein produces 100-fold more spike protein than a matched RD-Ad-Spike vector. When Ad-permissive hamsters were immunized with these vaccines by intranasal (IN) or intramuscular (IM) routes, SC-Ad produced significantly stronger antibody responses as compared to RD-Ad against the spike protein that rose over 14 weeks after one immunization. Single IN or IM immunizations generated significant antibody responses in serum and in bronchoalveolar lavages (BALs). IN priming, but not IM priming, generated HLA-restricted CD8 T cell responses in BALs. SC-Ad-Spike generated antibodies that retain binding to spike receptor binding domains (RBDs) with mutations from new viral variants. These data suggest empowering the genomes of gene-based vaccines with the ability to amplify antigen genes can increase potency. This may be particularly advantageous when applying mucosal vaccines to combat mucosal pathogens like SARS-CoV-2.\n\nOne Sentence SummaryArming adenovirus vaccines with the ability to replicate vaccine antigen genes may increase potency for systemic, or more importantly, mucosal immunization against mucosal pathogens.", - "rel_num_authors": 19, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.19.440446", + "rel_abs": "SARS-CoV-2 transmission remains a global problem which exerts a significant direct cost to public health. Additionally, other aspects of physical and mental health can be affected by limited access to social and exercise venues as a result of lockdowns in the community or personal reluctance due to safety concerns. Swimming pools have reopened in the UK as of April 12th, but the effect of swimming pool water on inactivation of SARS-CoV-2 has not yet been directly demonstrated. Here we demonstrate that water which adheres to UK swimming pool guidelines is sufficient to reduce SARS-CoV-2 infectious titre by at least 3 orders of magnitude.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Michael A Barry", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Haley Mudrick", - "author_inst": "Mayo" - }, - { - "author_name": "Erin McGlinch", - "author_inst": "Mayo" - }, - { - "author_name": "Brian Parrett", - "author_inst": "Mayo" - }, - { - "author_name": "Jack Hemsath", - "author_inst": "Mayo" - }, - { - "author_name": "Mary Barry", - "author_inst": "Mayo" - }, - { - "author_name": "Jeffrey Rubin", - "author_inst": "Mayo" - }, - { - "author_name": "Chisom Uzendu", - "author_inst": "Mayo" - }, - { - "author_name": "Michael Hansen", - "author_inst": "Mayo" - }, - { - "author_name": "Courtney Erskine", - "author_inst": "Mayo" - }, - { - "author_name": "Virginia VanKeulen", - "author_inst": "Mayo" - }, - { - "author_name": "Aleksandra Drelich", - "author_inst": "UTMB" - }, - { - "author_name": "Chien-Te Kent Tseng", - "author_inst": "UTMB" - }, - { - "author_name": "Christopher Shane Massey", - "author_inst": "UTMB" - }, - { - "author_name": "Madiha Fida", - "author_inst": "Mayo" - }, - { - "author_name": "Gina A Suh", - "author_inst": "Mayo Clinic" + "author_name": "Jonathan C Brown", + "author_inst": "Imperial College London" }, { - "author_name": "Tobias Peikert", - "author_inst": "Mayo" + "author_name": "Alex Blackwell", + "author_inst": "Water Babies Ltd" }, { - "author_name": "Matthew Block", - "author_inst": "Mayo" + "author_name": "Maya Moshe", + "author_inst": "Imperial College London" }, { - "author_name": "Gloria Olivier", - "author_inst": "Mayo" + "author_name": "Wendy S Barclay", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.04.14.21255429", @@ -826368,81 +826207,89 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.04.18.440366", - "rel_title": "An Immune Cell Atlas Reveals Dynamic COVID-19 Specific Neutrophil Programming Amendable to Dexamethasone Therapy", + "rel_doi": "10.1101/2021.04.17.440278", + "rel_title": "Differential plasmacytoid dendritic cell phenotype and type I Interferon response in asymptomatic and severe COVID-19 infection", "rel_date": "2021-04-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.18.440366", - "rel_abs": "SARS-CoV-2 is a novel coronavirus that causes acute respiratory distress syndrome (ARDS), death and long-term sequelae. Innate immune cells are critical for host defense but are also the primary drivers of ARDS. The relationships between innate cellular responses in ARDS resulting from COVID-19 compared to other causes of ARDS, such as bacterial sepsis is unclear. Moreover, the beneficial effects of dexamethasone therapy during severe COVID-19 remain speculative, but understanding the mechanistic effects could improve evidence-based therapeutic interventions. To interrogate these relationships, we developed an scRNA-Seq and plasma proteomics atlas (biernaskielab.ca/COVID_neutrophil). We discovered that compared to bacterial ARDS, COVID-19 was associated with distinct neutrophil polarization characterized by either interferon (IFN) or prostaglandin (PG) active states. Neutrophils from bacterial ARDS had higher expression of antibacterial molecules such as PLAC8 and CD83. Dexamethasone therapy in COVID patients rapidly altered the IFNactive state, downregulated interferon responsive genes, and activated IL1R2+ve neutrophils. Dexamethasone also induced the emergence of immature neutrophils expressing immunosuppressive molecules ARG1 and ANXA1, which were not present in healthy controls. Moreover, dexamethasone remodeled global cellular interactions by changing neutrophils from information receivers into information providers. Importantly, male patients had higher proportions of IFNactive neutrophils, a greater degree of steroid-induced immature neutrophil expansion, and increased mortality benefit compared to females in the dexamethasone era. Indeed, the highest proportion of IFNactive neutrophils was associated with mortality. These results define neutrophil states unique to COVID-19 when contextualized to other life-threatening infections, thereby enhancing the relevance of our findings at the bedside. Furthermore, the molecular benefits of dexamethasone therapy are also defined, and the identified pathways and plasma proteins can now be targeted to develop improved therapeutics.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.17.440278", + "rel_abs": "SARS-CoV-2 fine-tunes the interferon (IFN)-induced antiviral responses, which play a key role in preventing coronavirus disease 2019 (COVID-19) progression. Indeed, critically ill patients show an impaired type I IFN response accompanied by elevated inflammatory cytokine and chemokine levels, responsible for cell and tissue damage and associated multi-organ failure.\n\nHere, the early interaction between SARS-CoV-2 and immune cells was investigated by interrogating an in vitro human peripheral blood mononuclear cell (PBMC)-based experimental model. We found that, even in absence of a productive viral replication, the virus mediates a vigorous TLR7/8-dependent production of both type I and III IFNs and inflammatory cytokines and chemokines, known to contribute to the cytokine storm observed in COVID-19. Interestingly, we observed how virus-induced type I IFN secreted by PBMC enhances anti-viral response in infected lung epithelial cells, thus, inhibiting viral replication. This type I IFN was released by plasmacytoid dendritic cells (pDC) via an ACE-2-indipendent mechanism. Viral sensing regulates pDC phenotype by inducing cell surface expression of PD-L1 marker, a feature of type I IFN producing cells. Coherently to what observed in vitro, asymptomatic SARS-CoV-2 infected subjects displayed a similar pDC phenotype associated to a very high serum type I IFN level and induction of anti-viral IFN-stimulated genes in PBMC. Conversely, hospitalized patients with severe COVID-19 display very low frequency of circulating pDC with an inflammatory phenotype and high levels of chemokines and pro-inflammatory cytokines in serum.\n\nThis study further shed light on the early events resulting from the interaction between SARS-CoV-2 and immune cells occurring in vitro and confirmed ex vivo. These observations can improve our understanding on the contribution of pDC/type I IFN axis in the regulation of the anti-viral state in asymptomatic and severe COVID-19 patients.\n\nAuthor summarySARS-CoV-2 pandemic has resulted in millions of infections and deaths worldwide, yet the role of host innate immune responses in COVID-19 pathogenesis remains only partially characterized. Innate immunity represents the first line of host defense against viruses. Upon viral recognition, the secretion of type I and III interferons (IFN) establishes the cellular state of viral resistance, and contributes to induce the specific adaptive immune responses. Moving from in vitro evidences on the protective role played by plasmacytoid dendritic cells (pDC)-released type I IFN in the early phase of SARS-CoV-2 infection, here we characterized ex vivo the pDC phenotype and the balance between anti-viral and pro-inflammatory cytokines of COVID-19 patients stratified according to disease severity. Our study confirms in COVID-19 the crucial and protective role of pDC/type I IFN axis, whose deeper understanding may contribute to the development of novel pharmacological strategies and/or host-directed therapies aimed at boosting pDC response since the early phases of SARS-CoV-2 infection.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Sarthak Sinha", - "author_inst": "University of Calgary" + "author_name": "Martina Severa", + "author_inst": "Istituto Superiore di Sanit\u00e0" }, { - "author_name": "Nicole Rosin", - "author_inst": "University of Calgary" + "author_name": "Roberta Antonina Diotti", + "author_inst": "Vita-Salute San Raffaele University" }, { - "author_name": "Rohit Arora", - "author_inst": "University of Calgary" + "author_name": "Marilena Paola Etna", + "author_inst": "Istituto Superiore di Sanit\u00e0" }, { - "author_name": "Elodie Labit", - "author_inst": "University of Calgary" + "author_name": "Fabiana Rizzo", + "author_inst": "Istituto Superiore di Sanit\u00e0" }, { - "author_name": "Arzina Jaffer", - "author_inst": "University of Calgary" + "author_name": "Stefano Fiore", + "author_inst": "Istituto Superiore di Sanit\u00e0" }, { - "author_name": "Leslie Cao", - "author_inst": "University of Calgary" + "author_name": "Daniela Ricci", + "author_inst": "Istituto Superiore di Sanit\u00e0" }, { - "author_name": "Raquel Farias", - "author_inst": "University of Calgary" + "author_name": "Marco Iannetta", + "author_inst": "Policlinico Tor Vergata" }, { - "author_name": "Angela P Nguyen", - "author_inst": "University of Calgary" + "author_name": "Alessandro Sinigaglia", + "author_inst": "Padua University" }, { - "author_name": "Luiz G. N. de Almeida", - "author_inst": "University of Calgary" + "author_name": "Alessandra Lodi", + "author_inst": "Policlinico Tor Vergata" }, { - "author_name": "Antoine Dufour", - "author_inst": "University of Calgary" + "author_name": "Nicasio Mancini", + "author_inst": "Universit\u00e0 Vita-Salute San Raffaele" }, { - "author_name": "Amy Bromley", - "author_inst": "University of Calgary" + "author_name": "Elena Criscuolo", + "author_inst": "Vita-Salute San Raffaele University" }, { - "author_name": "Braedon McDonald", - "author_inst": "University of Calgary" + "author_name": "Massimo Clementi", + "author_inst": "Vita-Salute San Raffaele University" }, { - "author_name": "Mark Gillrie", - "author_inst": "University of Calgary" + "author_name": "Massimo Andreoni", + "author_inst": "Policlinico Tor Vergata" }, { - "author_name": "Marvin J Fritzler", - "author_inst": "University of Calgary" + "author_name": "Stefano Balducci", + "author_inst": "Metabolic Fitness association" }, { - "author_name": "Bryan Yipp", - "author_inst": "University of Calgary" + "author_name": "Luisa Barzon", + "author_inst": "Padua University" }, { - "author_name": "Jeff Biernaskie", - "author_inst": "University of Calgary" + "author_name": "Paola Stefanelli", + "author_inst": "Istituto Superiore di Sanit\u00e0" + }, + { + "author_name": "Nicola Clementi", + "author_inst": "Vita-Salute San Raffaele University" + }, + { + "author_name": "Eliana Coccia", + "author_inst": "Istituto Superiore di Sanit\u00e0" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -828114,63 +827961,39 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2021.04.16.21255616", - "rel_title": "Prevalence and Transmission of SARS-CoV-2 in Childcare Facilities: A Longitudinal Study", + "rel_doi": "10.1101/2021.04.16.21255543", + "rel_title": "Will the Large-scale Vaccination Succeed in Containing the COVID-19 Epidemic and How Soon?", "rel_date": "2021-04-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.16.21255616", - "rel_abs": "ObjectivesPrevious data indicate that children might play a less crucial role in SARS-CoV-2 transmission than initially assumed. We conducted a study to gain further knowledge on prevalence, transmission and spread of SARS-CoV-2 among preschool children, their parents and caretakers.\n\nMethodsChildren, their parents and care givers in 14 childcare facilities in Dresden, Saxony/ Germany were invited to participate in the KiTaCoviDD19-study between July 2020 and January 2021. Seroprevalence of SARS-CoV-2 antibodies was assessed up to 4 times during the study period in all participating adults and personal characteristics as well as epidemiological information of personal SARS-CoV-2 history were obtained. Stool viral shedding of SARS-CoV-2 was analyzed every 2-4 weeks in all participating children.\n\nResultsIn total, 318 children, 299 parents and 233 childcare workers were enrolled. The percentage of seropositive adults and SARS-CoV-2 positive detected children rose considerably by January 2021. However, the rate of SARS-CoV-2 positive children was considerably lower than the rate of seropositive adults. Overall, we detected a maximum of three connected cases in children. About 50% of SARS-CoV-2 infections in children could not be connected to a secondary case within our study population.\n\nConclusionThe study could not provide evidence for a relevant asymptomatic (\"silent\") spread of SARS-CoV-2 in childcare facilities, neither in a low nor a high prevalence setting. This finding adds to the evidence that childcare and educational settings do not play a crucial role in driving the SARS-CoV-2 pandemic.\n\nTable of Contents SummaryThis longitudinal study among children, parents and childcare workers provides further insight on SARS-CoV-2 prevalence and transmission within childcare facilities.\n\nWhats Known on This SubjectBased on age distribution of SARS-CoV-2 infections and previous data of very limited spread of COVID-19 among primary and secondary schools there is reason to believe that children play a less crucial role in SARS-CoV-2 transmission than initially assumed.\n\nWhat This Study AddsPreviously published studies focus mainly on SARS-CoV-2 transmission in schools. This longitudinal study provides information on prevalence, transmission and spread of SARS-CoV-2 within childcare facilities during low- and high-prevalence settings.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.16.21255543", + "rel_abs": "The availability of vaccines provides a promising solution to containing the COVID-19 pandemic. Here, we develop an epidemiological model to quantitatively analyze and predict the epidemic dynamics of COVID-19 under vaccination. The model is applied to the daily released numbers of confirmed cases of Israel and United States of America to explore and predict the trend under vaccination based on their current epidemic status and intervention measures.\n\nFor Israel, of which 53.83% of the population was fully vaccinated, under the current intensity of NPIs and vaccination scheme, the pandemic is predicted to end between May 14, 2021 to May 16, 2021 depending on an immunity duration between 180 days and 365 days; Assuming no NPIs after March 24, 2021, the pandemic will ends later, between July 4, 2021 to August 26, 2021. For USA, if we assume the current vaccination rate (0.268% per day) and intensity of NPIs, the pandemic will end between February 3, 2022 and August 17, 2029 depending on an immunity duration between 180 days and 365 days. However, assuming an immunity duration of 180 days and with no NPIs, the pandemic will not end, and instead reach an equilibrium state with a proportion of the population remaining actively infected.\n\nOverall the daily vaccination rate should be chosen according to the vaccine efficacy and the immunity duration to achieve herd immunity. In some situations, vaccination alone cannot stop the pandemic, and NPIs are necessary both to supplement vaccination and accelerate the end of the pandemic. Considering that vaccine efficacy and duration of immunity may be reduced for new mutant strains, it is necessary to remain cautiously optimistic about the prospect of the pandemic under vaccination.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Luise Haag", - "author_inst": "Department of Pediatrics, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" - }, - { - "author_name": "Judith Blankenburg", - "author_inst": "Department of Pediatrics, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" - }, - { - "author_name": "Manja Unrath", - "author_inst": "Department of Pediatrics, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" - }, - { - "author_name": "Johanna Grabietz", - "author_inst": "Department of Pediatrics, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" - }, - { - "author_name": "Elisabeth Kahre", - "author_inst": "Department of Pediatrics, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" - }, - { - "author_name": "Lukas Galow", - "author_inst": "Department of Pediatrics, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" - }, - { - "author_name": "Josephine Schneider", - "author_inst": "Department of Pediatrics, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" + "author_name": "Shilei Zhao", + "author_inst": "China National Center for Bioinformation" }, { - "author_name": "Alexander Dalpke", - "author_inst": "Institute for Medical Microbiology and Virology, Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" + "author_name": "Tong Sha", + "author_inst": "China National Center for Bioinformation" }, { - "author_name": "Christian Lueck", - "author_inst": "Institute for Medical Microbiology and Virology, Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" + "author_name": "Yongbiao Xue", + "author_inst": "China National Center for Bioinformation" }, { - "author_name": "Leo Buettner", - "author_inst": "Institute for Medical Microbiology and Virology, Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" + "author_name": "Chung-I Wu", + "author_inst": "Sun Yet-sen University" }, { - "author_name": "Jakob Peter Armann", - "author_inst": "Department of Pediatrics, University Hospital and Medical Faculty Carl Gustav Carus, Technische Universitaet Dresden" + "author_name": "Hua Chen", + "author_inst": "Beijing Institute of Genomics (China National Center for Bioinformation)" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.04.14.21255475", @@ -829864,75 +829687,151 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.04.16.440173", - "rel_title": "Viral neuroinvasion and neurotropism without neuronal damage in the hACE2 mouse model of COVID-19", + "rel_doi": "10.1101/2021.04.16.440101", + "rel_title": "A pair of non-competing neutralizing human monoclonal antibodies protecting from disease in a SARS-CoV-2 infection model", "rel_date": "2021-04-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.16.440173", - "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) not only affects the respiratory tract but also causes neurological symptoms such as loss of smell and taste, headache, fatigue or severe cerebrovascular complications. Using transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) we investigated the spatiotemporal distribution and pathomorphological features in the CNS following intranasal infection with SARS-CoV-2 variants, also after prior influenza A virus infection. Apart from Omicron, we found all variants to frequently spread to and within the CNS. Infection was restricted to neurons and appeared to spread from the olfactory bulb mainly in basally orientated regions in the brain and into the spinal cord, independent of ACE2 expression and without evidence of neuronal cell death, axonal damage or demyelination. However, microglial activation, microgliosis and a mild macrophage and T cell dominated inflammatory response was consistently observed, accompanied by apoptotic death of endothelial, microglial and immune cells, without their apparent infection. Microgliosis and immune cell apoptosis indicate a potential role of microglia for pathogenesis and viral effect in COVID-19 and possible impairment of neurological functions, especially in long COVID. These data may also be informative for the selection of therapeutic candidates, and broadly support investigation of agents with adequate penetration into relevant regions of the CNS.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.16.440101", + "rel_abs": "TRIANNI mice carry an entire set of human immunoglobulin V region gene segments and are a powerful tool to rapidly generate human monoclonal antibodies. After immunizing these mice against the spike protein of SARS-CoV-2, we identified 29 hybridoma antibodies that reacted with the SARS-CoV-2 spike protein. Nine antibodies neutralized SARS-CoV-2 infection at IC50 values in the subnanomolar range. ELISA-binding studies and DNA sequence analyses revealed one cluster of clonally related neutralizing antibodies that target the receptor-binding domain and compete with the cellular receptor hACE2. A second cluster of neutralizing antibodies binds to the N-terminal domain of the spike protein without competing with the binding of hACE2 or cluster 1 antibodies. SARS-CoV-2 mutants selected for resistance to an antibody from one cluster are still neutralized by an antibody from the other cluster. Antibodies from both clusters markedly reduced viral spread in mice transgenic for human ACE2 and protected the animals from SARS-CoV-2 induced weight loss. Thus, we report two clusters of potent non-competing SARS-CoV-2 neutralizing antibodies providing potential candidates for therapy and prophylaxis of COVID-19. The study further supports the use of transgenic animals with human immunoglobulin gene repertoires in pandemic preparedness initiatives.", + "rel_num_authors": 33, "rel_authors": [ { - "author_name": "Frauke Seehusen", - "author_inst": "University of Zurich" + "author_name": "Antonia Sophia Peter", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Jordan J. Clark", - "author_inst": "University of Liverpool" + "author_name": "Edith Roth", + "author_inst": "Division of Molecular Immunology, Internal Medicine III, Nikolaus-Fiebiger-Center of Molecular Medicine, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Parul Sharma", - "author_inst": "University of Liverpool" + "author_name": "Sebastian R. Schulz", + "author_inst": "Division of Molecular Immunology, Internal Medicine III, Nikolaus-Fiebiger-Center of Molecular Medicine, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Eleanor Bentley", - "author_inst": "University of Liverpool" + "author_name": "Kirsten Fraedrich", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Adam Kirby", - "author_inst": "University of Liverpool" + "author_name": "Tobit Steinmetz", + "author_inst": "Division of Molecular Immunology, Internal Medicine III, Nikolaus-Fiebiger-Center of Molecular Medicine, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Krishanthi Subramaniam", - "author_inst": "University of Liverpool" + "author_name": "Dominik Damm", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Sabina Wunderlin Giuliani", - "author_inst": "University of Zurich" + "author_name": "Manuela Hauke", + "author_inst": "Division of Molecular Immunology, Internal Medicine III, Nikolaus-Fiebiger-Center of Molecular Medicine, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Grant Hughes", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Elie Richel", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Edward I Patterson", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Sandra Mueller-Schmucker", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Benedict D Michael", - "author_inst": "University of Liverpool" + "author_name": "Katharina Habenicht", + "author_inst": "Division of Genetics, Department Biology, Nikolaus-Fiebiger-Center of Molecular Medicine, Friedrich-Alexander University Erlangen-Nuremberg" }, { - "author_name": "Andrew Owen", - "author_inst": "University of Liverpool" + "author_name": "Valentina Eberlein", + "author_inst": "Department of Immunology, Fraunhofer Institute for Cell Therapy and Immunology IZI" }, { - "author_name": "Julian Alexander Hiscox", - "author_inst": "University of Liverpool" + "author_name": "Leila Issmail", + "author_inst": "Department of Immunology, Fraunhofer Institute for Cell Therapy and Immunology IZI" }, { - "author_name": "James P Stewart", - "author_inst": "University of Liverpool" + "author_name": "Nadja Uhlig", + "author_inst": "Department of Immunology, Fraunhofer Institute for Cell Therapy and Immunology IZI" }, { - "author_name": "Anja Kipar", - "author_inst": "University of Zurich" + "author_name": "Simon Dolles", + "author_inst": "Department of Chemistry & Pharmacy, Friedrich-Alexander University Erlangen-Nuremberg" + }, + { + "author_name": "Eva Gruner", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg" + }, + { + "author_name": "David Peterhoff", + "author_inst": "Institute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg" + }, + { + "author_name": "Sandra Ciesek", + "author_inst": "Goethe Universtiy Frankfurt" + }, + { + "author_name": "Markus Hoffmann", + "author_inst": "Deutsches Primatenzentrum GmbH - Leibniz-Institut fur Primatenforschung" + }, + { + "author_name": "Stefan Pohlmann", + "author_inst": "Deutsches Primatenzentrum GmbH - Leibniz-Institut fur Primatenforschung" + }, + { + "author_name": "Paul F. McKay", + "author_inst": "Department of Infectious Diseases, Imperial College London" + }, + { + "author_name": "Robin J Shattock", + "author_inst": "Department of Infectious Diseases, Imperial College London" + }, + { + "author_name": "Roman Wolfel", + "author_inst": "Bundeswehr Institute of Microbiology, Munich" + }, + { + "author_name": "Ralf Wagner", + "author_inst": "Institute of Medical Microbiology and Hygiene, Molecular Microbiology (Virology), University of Regensburg" + }, + { + "author_name": "Jutta Eichler", + "author_inst": "Department of Chemistry & Pharmacy, Friedrich-Alexander University Erlangen-Nuremberg" + }, + { + "author_name": "Wolfgang Schuh", + "author_inst": "Division of Molecular Immunology, Internal Medicine III, Nikolaus-Fiebiger-Center of Molecular Medicine, Friedrich-Alexander University Erlangen-Nuremberg" + }, + { + "author_name": "Frank Neipel", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg" + }, + { + "author_name": "Armin Ensser", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg" + }, + { + "author_name": "Dirk Mielenz", + "author_inst": "Division of Molecular Immunology, Internal Medicine III, Nikolaus-Fiebiger-Center of Molecular Medicine, Friedrich-Alexander University Erlangen-Nuremberg" + }, + { + "author_name": "Matthias Tenbusch", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg" + }, + { + "author_name": "Thomas H. Winkler", + "author_inst": "Division of Genetics, Department Biology, Nikolaus-Fiebiger-Center of Molecular Medicine, Friedrich-Alexander University Erlangen-Nuremberg" + }, + { + "author_name": "Thomas Grunwald", + "author_inst": "Department of Immunology, Fraunhofer Institute for Cell Therapy and Immunology IZI" + }, + { + "author_name": "Klaus Uberla", + "author_inst": "Institute of Clinical and Molecular Virology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Erlangen" + }, + { + "author_name": "Hans-Martin Jack", + "author_inst": "Division of Molecular Immunology, Internal Medicine III, Nikolaus-Fiebiger-Center of Molecular Medicine, Friedrich-Alexander University Erlangen-Nuremberg" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "pathology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.04.15.440067", @@ -831430,31 +831329,75 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.04.13.21255336", - "rel_title": "Trajectories of compliance with COVID-19 related guidelines: longitudinal analyses of 50,000 UK adults", + "rel_doi": "10.1101/2021.04.12.21255344", + "rel_title": "Seroepidemiology among Employees of New York City Health and Hospitals during the First Wave of the SARS-CoV-2 Epidemic", "rel_date": "2021-04-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255336", - "rel_abs": "BackgroundGovernments have implemented a range of measure to tackle COVID-19, primarily focusing on changing citizens behaviours in order to lower transmission of the virus. Some policymakers have expressed concern that citizens would not maintain high levels of compliance with these behaviours over the pandemic and would instead exhibit so-called \"behavioural fatigue\". While the concept has been criticized, there have been few tests of behavioural fatigue using data from the COVID-19 pandemic, and none that have tracked individuals compliance trajectories.\n\nMethodsWe used longitudinal data on self-reported compliance from 50,851 adults in the COVID-19 Social Study collected across two waves of the pandemic in the UK (01 April 2020 - 22 February 2021). We modelled typical compliance trajectories using latent growth curve analysis (LGCA) and tested for behavioural fatigue by attempting to identify a set of participants whose compliance decreased substantially over the study period.\n\nResultsWe selected a four-class LGCA solution. Most individuals maintained high levels of compliance over the pandemic and reported similar levels of compliance across the first and second waves. Approximately one in seven participants had decreasing levels of compliance across the pandemic, reporting noticeably lower levels of compliance in the second wave, a pattern compatible with behavioural fatigue. Individuals with declining compliance levels differed from those with consistently high compliance on multiple characteristics, including (young) age, better physical health, lower empathy and conscientiousness and greater general willingness to take risks.\n\nConclusionWhile a minority, not all individuals have maintained high compliance across the pandemic. Decreasing compliance is related to several psychological traits. The results suggest that targeting of behaviour change messages later in the pandemic may be needed to increase compliance.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.12.21255344", + "rel_abs": "ObjectiveEstimate the seroprevalence of SARS-CoV-2 antibodies among New York City Health + Hospitals healthcare workers, and identify demographic and occupational factors associated with SARS-CoV-2 antibodies among healthcare workers.\n\nMethodsThis was an observational, cross-sectional study using data from SARS-CoV-2 serological tests accompanied by a demographic and occupational survey administered to healthcare workers. Participants were employed by New York City Health + Hospitals (NYC H+H) and either completed serologic testing at NYC H+H between April 30 and June 30, 2020, or completed SARS-CoV-2 antibody testing outside of NYC H+H and were able to self-report results.\n\nResultsSeven hundred twenty-seven survey respondents were included in analysis. Participants had a mean age of 46 years (SD= 12.19) and 543 (75%) were women. Two hundred fourteen (29%) participants tested positive or reported testing positive for the presence of SARS-CoV-2 antibodies (IgG+). Characteristics associated with positive SARS-CoV-2 serostatus were Black race (25% IgG+ vs. 15% IgG-, p=0.001), having someone in the household with COVID symptoms (49% IgG+ vs. 21% IgG-, p<0.001), or having a confirmed COVID-19 case in the household (25% IgG+ vs 5% IgG-, p<0.001). Characteristics associated with negative SARS-CoV-2 serostatus included working on a COVID patient floor (27% IgG+ vs. 36% IgG-, p=0.02), working in the ICU (20% IgG+ vs. 28% IgG-, p=0.03), or having close contact with a patient with COVID-19 (51% IgG+ vs. 62% IgG-, p=0.03).\n\nConclusionsResults underscore the significance of community factors and inequities might have on SARS-CoV-2 exposure for healthcare workers.\n\nWhat is already known about this subject?Healthcare workers are at risk of occupational transmission of SARS-CoV-2, and the risk of infection varies by demographic characteristics and work location.\n\nWhat are the new findings?Healthcare worker race and household contacts were significantly associated with SARS-CoV-2 seropositivity, while working on a COVID patient floor or ICU was associated with seronegativity.\n\nHow might this impact on policy or clinical practice in the foreseeable future?Results underscore the significance of community factors and inequities on healthcare worker exposure to SARS-CoV-2, and the need to address these inequities at the community level where healthcare workers live.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Liam Wright", - "author_inst": "University College London" + "author_name": "Alexander D Bryan", + "author_inst": "New York City Health + Hospitals" }, { - "author_name": "Andrew Steptoe", - "author_inst": "University College London" + "author_name": "Kathleen Tatem", + "author_inst": "New York City Health + Hospitals" }, { - "author_name": "Daisy Fancourt", - "author_inst": "University College London" + "author_name": "Jillian Diuguid-Gerber", + "author_inst": "New York City Health + Hospitals" + }, + { + "author_name": "Caroline Cooke", + "author_inst": "New York City Health + Hospitals" + }, + { + "author_name": "Anya Romanoff", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Nandini Choudhury", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Michael Scanlon", + "author_inst": "Indiana University" + }, + { + "author_name": "Preeti Kishore", + "author_inst": "New York City Health + Hospitals" + }, + { + "author_name": "Elana Sydney", + "author_inst": "New York City Health + Hospitals" + }, + { + "author_name": "Joseph Masci", + "author_inst": "New York City Health + Hospitals" + }, + { + "author_name": "Parampreet Bakshi", + "author_inst": "New York City Health + Hospitals" + }, + { + "author_name": "Sahithi Pemmasani", + "author_inst": "New York City Health + Hospitals" + }, + { + "author_name": "Nichola J Davis", + "author_inst": "New York City Health + Hospitals" + }, + { + "author_name": "Duncan Maru", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.04.13.21255401", @@ -833376,81 +833319,53 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2021.04.10.21255111", - "rel_title": "Rapid spread and high impact of the Variant of Concern P.1 in the largest city of Brazil", + "rel_doi": "10.1101/2021.04.13.21255142", + "rel_title": "Effect of COVID-19 on Lipid Profile and its Correlation with Acute Phase Reactants", "rel_date": "2021-04-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.10.21255111", - "rel_abs": "First in Manaus in the Brazilian Northern region, the Variant of Concern P.1 traveled 3800 kilometers southeast to endanger Sao Paulo contributing to the collapse of the health system. Here, we show evidence of how fast the VOC P.1 has spread in the most populated city in South America.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.13.21255142", + "rel_abs": "Background and ObjectiveCoronavirus disease 2019 (COVID-19) manifests as multiple clinical and pathological organ dysfunctions. It also disrupts metabolic profile due to the release of pro-inflammatory cytokines causing a systemic inflammation reaction. However, the development and correlation of dyslipidemia with acute phase reactants is unknown. This investigation was performed to assess the pathological alterations of low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein (HDL), triglycerides, and total cholesterol levels in COVID-19 patients.\n\nMethodsThis was a prospective study performed on real-world patients to assess serum levels of LDL-C, HDL, TG, TC on COVID-19 patients (mild: 319; moderate: 391; critical: 357) hospitalized at our center between April 2020 through January 2021. Age- and gender-matched controls who had their lipid profiles in the same period were included as the control group.\n\nResultsLDL-C, HDL, TG, and TC levels were significantly lower in COVID-19 patients when compared with the control group (P < 0.001, 0.047, 0.045, < 0.001, respectively). All parameters decreased gradually with COVID-19 disease severity (LDL-C: median (IQR), mild: 98 (91,134); moderate: 97 (81,113); critical: 68 (68,83); HDL: mild: 45 (37,50); moderate: 46 (41,50); critical: 40 (37,46); TG: mild: 186 (150,245); moderate: 156 (109,198); critical: 111 (98,154); TC: mild: 224 (212,238); moderate: 212 (203,213); critical: 154 (125,187)). LDL-C, TC, and TG were inversely correlated with acute phase reactants (interleukin-6 (IL-6), Procalcitonin, C-reactive protein (CRP), and D-dimers). Logistic regression demonstrated lipid profile, thyroid profile, and acute phase reactants as predictors of severity of COVID-19 disease.\n\nConclusionHypolipidemia develops in increasing frequency with severe COVID-19 disease. It inversely correlates with levels of acute-phase reactants, indicating SARS-COV-2 as the causative agent for alteration in lipid and thyroid levels.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Gabriela Barbosa", - "author_inst": "UNIFESP" - }, - { - "author_name": "Luiz Vinicius Leao Moreira", - "author_inst": "Federal University of Sao Paulo (UNIFESP)" - }, - { - "author_name": "Alberto Fernando Oliveira Justo", - "author_inst": "Federal University of Sao Paulo (UNIFESP)" - }, - { - "author_name": "Ana Helena Perosa", - "author_inst": "Federal University of Sao Paulo (UNIFESP)" - }, - { - "author_name": "Ana Paula Chaves", - "author_inst": "UNIFESP" - }, - { - "author_name": "Mariana Sardinha Bueno", - "author_inst": "UNIFESP" - }, - { - "author_name": "Luciano Kleber de Souza Luna", - "author_inst": "Universidade Federal de Sao Paulo" - }, - { - "author_name": "Danielle Dias Conte", - "author_inst": "UNIFESP" + "author_name": "Jahanzeb Malik", + "author_inst": "Rawalpindi Institute of Cardiology" }, { - "author_name": "Joseane Mayara Carvalho", - "author_inst": "UNIFESP" + "author_name": "Uzma Ishaq", + "author_inst": "Foundation University Medical College" }, { - "author_name": "Janesly Prates", - "author_inst": "UNIFESP" + "author_name": "Talha Laique", + "author_inst": "Allama Iqbal Medical College" }, { - "author_name": "Patricia Sousa Dantas", - "author_inst": "UNIFESP" + "author_name": "Amna Ashraf", + "author_inst": "Military Hospital, Rawalpindi" }, { - "author_name": "Klinger Faico", - "author_inst": "UNIFESP" + "author_name": "Asmara Malik", + "author_inst": "National University of Medical Sciences" }, { - "author_name": "Clarice Camargo", - "author_inst": "UNIFESP" + "author_name": "Mommana Ali Rathore", + "author_inst": "National University of Medical Sciences" }, { - "author_name": "Paola Cristina Resende", - "author_inst": "Oswaldo Cruz Institute" + "author_name": "Syed Muhammad Jawad Zaidi", + "author_inst": "Rawalpindi Medical University" }, { - "author_name": "Marilda Siqueira", - "author_inst": "Oswald Cruz Intitute" + "author_name": "Muhammad Javaid", + "author_inst": "Rawalpindi Institute of Cardiology" }, { - "author_name": "Nancy cristina junqueira Bellei", - "author_inst": "Federal University of Sao Paulo" + "author_name": "Asad Mehmood", + "author_inst": "Rawalpindi Institute of Cardiology" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -834998,83 +834913,51 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.04.09.21255195", - "rel_title": "Ovarian follicular function is not altered by SARS-Cov-2 infection or BNT162b2 mRNA Covid-19 vaccination.", + "rel_doi": "10.1101/2021.04.12.21255304", + "rel_title": "Survey of Behaviour Attitudes Towards Preventive Measures Following COVID-19 Vaccination", "rel_date": "2021-04-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.09.21255195", - "rel_abs": "ImportanceThis is the first study to examine the impact of SARS-Cov-2 infection and COVID-19 vaccination on ovarian function.\n\nObjectiveTo characterize anti-COVID-19 antibodies in follicular fluid and compare ovarian follicle function in women following confirmed SARS-CoV-2 infection, COVID-19 vaccination, and non-infected, unvaccinated controls.\n\nDesignThis is a cohort study conducted between February 1 and March 10, 2021.\n\nSettingA single university hospital-based IVF clinic.\n\nParticipantsConsecutive sample of female patients undergoing oocyte retrieval.\n\nInterventionsConsenting patients were recruited and assigned to one of three study groups: recovering from confirmed COVID 19 (n=9); vaccinated (n=9); and uninfected, non-vaccinated controls (n=14). Serum and follicular fluid samples were taken and analyzed for anti-COVID IgG as well as estrogen, progesterone and HSPG2 concentration, as well as the number and maturity of aspirated oocytes and previous estrogen and progesterone measurements.\n\nMain outcome measuresFollicular function, including steroidogenesis, follicular response to the LH/hCG trigger, and oocyte quality biomarkers.\n\nResultsBoth natural and vaccine elicited anti-COVID IgG antibodies were detected in the follicular fluid in levels proportional to the IgG serum concentration. No differences were detected in any of the surrogate ovarian follicle quality reporting parameters.\n\nConclusions and relevanceBoth SARS-COV-2 infection and vaccination with the BNT162b2 mRNA vaccine mediate IgG immunity that crosses into the follicular fluid. No detrimental effect on follicular function was detected.\n\nTrial RegistrationCinicalTrials.gov registry number NCT04822012\n\nKey PointCOVID 19 disease and BNT162b2 mRNA vaccine induce anti-COVID IgG in follicular fluid; neither recent infection nor vaccination appear to negatively effect follicular function.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.12.21255304", + "rel_abs": "Following the widespread vaccination program for COVID-19 carried out in Israel, a survey was conducted to preliminarily assess behavior changes in the vaccinated population, prior to the expected upcoming policy change as to mask wearing and social distancing regulation in Israel. 200 people answered at least one question pertaining to preventive behaviour. Among the respondents, 21.1% reported a decrease in mask wearing compared to 47.3% who reported a decrease in social distancing. There was no difference in these measures between the sexes. However, people under the age of 50 were more likely to decrease mask wearing (28.1%) and decrease social distancing (56.1%), as compared with people over the age of 50 (17.2% and 41.8%, respectively). Among health care workers, there was a minimal decrease in mask wearing (1/23 people) compared to a more widespread decrease in social distancing (10/23). These data suggest that preventive attitudes change following COVID-19 vaccination, with less adherence to social distancing as compared to mask wearing, and should be taken into account when planning public policy in the future.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Yaakov Bentov", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" - }, - { - "author_name": "Ofer Beharier", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" - }, - { - "author_name": "Arbel Moav-Zafrir", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" - }, - { - "author_name": "Maor Kabessa", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" - }, - { - "author_name": "Miri Godin", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" - }, - { - "author_name": "Caryn Greenfield", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" - }, - { - "author_name": "Mali Ketzinel-Gilad", - "author_inst": "MALCA@hadassah.org.ilDepartment of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" - }, - { - "author_name": "Efrat Esh Broder", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" - }, - { - "author_name": "Hananel Holzer", - "author_inst": "Hadassah University medical center, Jerusalem, Israel" + "author_name": "Daniella Rahamim-Cohen", + "author_inst": "Maccabi Healthcare Services" }, { - "author_name": "Dana Wolf", - "author_inst": "Clinical Virology Unit, Hadassah Hebrew University Medical Center, Jerusalem, Israel" + "author_name": "Sivan Gazit", + "author_inst": "KSM Research & Innovation Center" }, { - "author_name": "Esther Oiknine-Djian", - "author_inst": "Clinical Virology Unit, Hadassah Hebrew University Medical Center, Jerusalem, Israel" + "author_name": "Galit Perez", + "author_inst": "KSM Research & Innovation Center" }, { - "author_name": "Iyad Barghouti", - "author_inst": "Biochemistry Laboratory, Hadassah University Hospital, Mt. Scopus, Jerusalem" + "author_name": "Barak Nada", + "author_inst": "KSM Research & Innovation Center" }, { - "author_name": "Debra Goldman-Wohl", - "author_inst": "Division of Obstetrics and Gynecology, Hadassah-Hebrew University Medical Center, Jerusalem" + "author_name": "Shay Ben Moshe", + "author_inst": "KSM Research & Innovation Center" }, { - "author_name": "Simcha Yagel", - "author_inst": "Division of Obstetrics and Gynecology, Hadassah-Hebrew University Medical Center, Jerusalem" + "author_name": "Miri Mizrahi-Reuveni", + "author_inst": "Maccabi Healthcare Services" }, { - "author_name": "Asnat Walfisch", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" + "author_name": "Joseph Azuri", + "author_inst": "Maccabi Healthcare Services" }, { - "author_name": "Anat Hershko Klement", - "author_inst": "Department of Obstetrics and Gynecology, Hadassah Mount Scopus-Hebrew University medical center, Jerusalem, Israel" + "author_name": "Tal Patalon", + "author_inst": "KSM Research & Innovation Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "category": "health policy" }, { "rel_doi": "10.1101/2021.04.09.21255159", @@ -837016,35 +836899,27 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2021.04.12.439473", - "rel_title": "Revealing the threat of emerging SARS-CoV-2 mutations to antibody therapies", + "rel_doi": "10.1101/2021.04.11.439322", + "rel_title": "Prediction and evolution of the molecular fitness of SARS-CoV-2 variants: Introducing SpikePro", "rel_date": "2021-04-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.12.439473", - "rel_abs": "The ongoing massive vaccination and the development of effective intervention offer the long-awaited hope to end the global rage of the COVID-19 pandemic. However, the rapidly growing SARS-CoV-2 variants might compromise existing vaccines and monoclonal antibody (mAb) therapies. Although there are valuable experimental studies about the potential threats from emerging variants, the results are limited to a handful of mutations and Eli Lilly and Regeneron mAbs. The potential threats from frequently occurring mutations on the SARS-CoV-2 spike (S) protein receptor-binding domain (RBD) to many mAbs in clinical trials are largely unknown. We fill the gap by developing a topology-based deep learning strategy that is validated with tens of thousands of experimental data points. We analyze 261,348 genome isolates from patients to identify 514 non-degenerate RBD mutations and investigate their impacts on 16 mAbs in clinical trials. Our findings, which are highly consistent with existing experimental results about variants from the UK, South Africa, Brazil, US-California, and Mexico shed light on potential threats of 95 high-frequency mutations to mAbs not only from Eli Lilly and Regeneron but also from Celltrion and Rockefeller University that are in clinical trials. We unveil, for the first time, that high-frequency mutations R346K/S, N439K, G446V, L455F, V483F/A, E484Q/V/A/G/D, F486L, F490L/V/S, Q493L, and S494P/L might compromise some of mAbs in clinical trials. Our study gives rise to a general perspective about how mutations will affect current vaccines.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.11.439322", + "rel_abs": "The understanding of the molecular mechanisms driving the fitness of the SARS-CoV-2 virus and its mutational evolution is still a critical issue. We built a simplified computational model, called SpikePro, to predict the SARS-CoV-2 fitness from the amino acid sequence and structure of the spike protein. It contains three contributions: the viral transmissibility predicted from the stability of the spike protein, the infectivity computed in terms of the affinity of the spike protein for the ACE2 receptor, and the ability of the virus to escape from the human immune response based on the binding affinity of the spike protein for a set of neutralizing antibodies. Our model reproduces well the available experimental, epidemiological and clinical data on the impact of variants on the biophysical characteristics of the virus. For example, it is able to identify circulating viral strains that, by increasing their fitness, recently became dominant at the population level. SpikePro is a useful instrument for the genomic surveillance of the SARS-CoV-2 virus, since it predicts in a fast and accurate way the emergence of new viral strains and their dangerousness. It is freely available in the GitHub repository github.com/3BioCompBio/SpikeProSARS-CoV-2.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Jiahui Chen", - "author_inst": "Michigan State University" - }, - { - "author_name": "Kaifu Gao", - "author_inst": "Michigan State University" - }, - { - "author_name": "Rui Wang", - "author_inst": "Michigan State University" + "author_name": "Fabrizio Pucci", + "author_inst": "Universit\u00e9 Libre de Bruxelles" }, { - "author_name": "Guo-Wei Wei", - "author_inst": "Michigan State University" + "author_name": "Marianne Rooman", + "author_inst": "Universit\u00e9 Libre de Bruxelles" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.04.11.439398", @@ -838766,21 +838641,89 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.09.439203", - "rel_title": "A trimeric hydrophobic zipper mediates the intramembrane assembly of SARS-CoV-2 spike", + "rel_doi": "10.1101/2021.04.08.438911", + "rel_title": "Nanobody Repertoires for Exposing Vulnerabilities of SARS-CoV-2", "rel_date": "2021-04-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.09.439203", - "rel_abs": "The S protein of the SARS-CoV-2 is a Type I membrane protein that mediates membrane fusion and viral entry. A vast amount of structural information is available for the ectodomain of S, a primary target by the host immune system, but much less is known regarding its transmembrane domain (TMD) and its membrane-proximal regions. Here, we determined the nuclear magnetic resonance (NMR) structure of the S protein TMD in bicelles that closely mimic a lipid bilayer. The TMD structure is a transmembrane -helix (TMH) trimer that assembles spontaneously in membrane. The trimer structure shows an extensive hydrophobic core along the 3-fold axis that resembles that of a trimeric leucine/isoleucine zipper, but with tetrad, not heptad, repeat. The trimeric core is strong in bicelles, resisting hydrogen-deuterium exchange for weeks. Although highly stable, structural guided mutagenesis identified single mutations that can completely dissociate the TMD trimer. Multiple studies have shown that the membrane anchor of viral fusion protein can form highly specific oligomers, but the exact function of these oligomers remain unclear. Our findings should guide future experiments to address the above question for SARS coronaviruses.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.08.438911", + "rel_abs": "Despite the great promise of vaccines, the COVID-19 pandemic is ongoing and future serious outbreaks are highly likely, so that multi-pronged containment strategies will be required for many years. Nanobodies are the smallest naturally occurring single domain antigen binding proteins identified to date, possessing numerous properties advantageous to their production and use. We present a large repertoire of high affinity nanobodies against SARS-CoV-2 Spike protein with excellent kinetic and viral neutralization properties, which can be strongly enhanced with oligomerization. This repertoire samples the epitope landscape of the Spike ectodomain inside and outside the receptor binding domain, recognizing a multitude of distinct epitopes and revealing multiple neutralization targets of pseudoviruses and authentic SARS-CoV-2, including in primary human airway epithelial cells. Combinatorial nanobody mixtures show highly synergistic activities, and are resistant to mutational escape and emerging viral variants of concern. These nanobodies establish an exceptional resource for superior COVID-19 prophylactics and therapeutics.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Qingshan Fu", - "author_inst": "Harvard Medical School" + "author_name": "Peter C Fridy", + "author_inst": "The Rockefeller University" }, { - "author_name": "James J Chou", - "author_inst": "Harvard Medical School" + "author_name": "Natalia E Ketaren", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Junjie Wang", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Erica Y Jacobs", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Tanmoy Sanyal", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Kelly R Molloy", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Fabian Schmidt", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Magda Rutkowska", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Yiska Weisblum", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Sarah Keegan", + "author_inst": "New York University" + }, + { + "author_name": "Jacob B Jiler", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Milana E Stein", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Paul Dominic B Olinares", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Theodora Hatziioannou", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "David Feny\u00f6", + "author_inst": "New York University" + }, + { + "author_name": "Andej Sali", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Paul D Bieniasz", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Brian T Chait", + "author_inst": "The Rockefeller University" + }, + { + "author_name": "Michael P Rout", + "author_inst": "The Rockefeller University" } ], "version": "1", @@ -840512,39 +840455,75 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.04.07.21255071", - "rel_title": "Results Availability and Timeliness of Registered COVID-19 Clinical Trials: A Cross-Sectional Study", + "rel_doi": "10.1101/2021.04.06.21254740", + "rel_title": "Detecting Pathogen-Associated RNA via Piecewise Isothermal Testing achieving Sample-to-Result Integration", "rel_date": "2021-04-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.07.21255071", - "rel_abs": "ObjectiveTo examine how and when the results of COVID-19 clinical trials are disseminated.\n\nDesignCross-sectional bibliographic study\n\nSettingThe COVID-19 clinical trial landscape\n\nParticipants285 registered interventional clinical trials for the treatment and prevention of COVID-19 completed by 30 June 2020\n\nMain outcome measuresOverall reporting and reporting by dissemination route (i.e., by journal article, preprint, or results on a registry); time to reporting by dissemination route.\n\nResultsFollowing automated and manual searches of the COVID-19 literature, we located 41 trials (14%) with results spread across 47 individual results publications published by 15 August 2020. The most common dissemination route was preprints (n = 25) followed by journal articles (n = 18), and results on a registry (n = 2). Of these, four trials were available as both a preprint and journal publication. The cumulative incidence of any reporting surpassed 20% at 119 days from completion. Sensitivity analyses using alternate dates available and definitions of results did not appreciably change the reporting percentage. Expanding minimum follow-up time to 3 months increased the overall reporting percentage to 19%.\n\nConclusionCOVID-19 trials completed during the first six months of the pandemic did not consistently yield rapid results in the literature or on clinical trial registries. Our findings suggest that the COVID-19 response may be seeing quicker results disclosure compared to non-emergency conditions. Issues with the reliability and timeliness of trial registration data may impact our estimates. Ensuring registry data is accurate should be a priority for the research community during a pandemic. Data collection is underway for Phase 2 of the DIRECCT study expanding our trial population to those completed anytime in 2020.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.06.21254740", + "rel_abs": "We report a novel piece-wise isothermal nucleic acid test (PINAT) for diagnosing pathogen-associated RNA that embeds an exclusive DNA-mediated specific probing reaction with the backbone of an isothermal reverse-transcription cum amplification protocol as a unified single-step procedure. This single step sample-to-result test method has been seamlessly integrated in an inexpensive, scalable, pre-programmable and portable instrument, resulting in a generic platform technology for detecting nucleic acid from a wide variety of pathogens. The test exhibited high sensitivity and specificity of detection when assessed using 200 double-blind patient samples for detecting SARS-CoV-2 infection conducted by the Indian Council of Medical Research (ICMR), reporting a positive and negative percent agreement of 94.6% and 98% respectively. We also established its efficacy in detecting influenza-A infection, performing the diagnosis at the point of collection with uncompromised detection rigor. The envisaged trade-off between advanced laboratory-based procedures with the elegance of common rapid tests renders the innovation to be ideal for deployment in resource-limited settings towards catering the needs of the underserved.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Maia Salholz-Hillel", - "author_inst": "Charit\u00e9 Universit\u00e4tsmedizin Berlin" + "author_name": "Saptarshi Banerjee", + "author_inst": "School of Bioscience, Indian Institute of Technology Kharagpur, India-721302" }, { - "author_name": "Peter Grabitz", - "author_inst": "Charit\u00e9 Universit\u00e4tsmedizin Berlin" + "author_name": "Sujay Kumar Biswas", + "author_inst": "School of Medical Science and Technology, Indian Institute of Technology Kharagpur, India-721302" }, { - "author_name": "Molly Pugh-Jones", - "author_inst": "Charit\u00e9 Universit\u00e4tsmedizin Berlin" + "author_name": "Nandita Kedia", + "author_inst": "School of Bioscience, Indian Institute of Technology Kharagpur, India-721302" }, { - "author_name": "Daniel Strech", - "author_inst": "Charit\u00e9 Universit\u00e4tsmedizin Berlin" + "author_name": "Rakesh Sarkar", + "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases, India-700010" }, { - "author_name": "Nicholas J DeVito", - "author_inst": "University of Oxford" + "author_name": "Aratrika De", + "author_inst": "School of Bioscience, Indian Institute of Technology Kharagpur, India-721302" + }, + { + "author_name": "Suvrotoa Mitra", + "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases, India-700010" + }, + { + "author_name": "Subhanita Roy", + "author_inst": "Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, India-721302" + }, + { + "author_name": "Aditya Bandopadhyay", + "author_inst": "Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, India-721302" + }, + { + "author_name": "Indranath Banerjee", + "author_inst": "B.C. Roy Technology Hospital, Indian Institute of Technology Kharagpur, India-721302" + }, + { + "author_name": "Ritobrata Goswami", + "author_inst": "School of Bioscience, Indian Institute of Technology Kharagpur, India-721302" + }, + { + "author_name": "Shanta Dutta", + "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases, India-700010" + }, + { + "author_name": "Mamta Chawla-Sarkar", + "author_inst": "ICMR-National Institute of Cholera and Enteric Diseases, India-700010" + }, + { + "author_name": "Suman Chakraborty", + "author_inst": "Department of Mechanical Engineering, Indian Institute of Technology Kharagpur, India-721302" + }, + { + "author_name": "Arindam Mondal", + "author_inst": "School of Bioscience, Indian Institute of Technology Kharagpur, India-721302" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "medical ethics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.04.07.21255063", @@ -842570,203 +842549,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.04.07.438818", - "rel_title": "Structural basis for broad sarbecovirus neutralization by a human monoclonal antibody", + "rel_doi": "10.1101/2021.04.06.21254996", + "rel_title": "Examining changes in sleep duration associated with the onset of the COVID-19 pandemic: Who is sleeping and who is not?", "rel_date": "2021-04-08", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.07.438818", - "rel_abs": "The recent emergence of SARS-CoV-2 variants of concern (VOC) and the recurrent spillovers of coronaviruses in the human population highlight the need for broadly neutralizing antibodies that are not affected by the ongoing antigenic drift and that can prevent or treat future zoonotic infections. Here, we describe a human monoclonal antibody (mAb), designated S2x259, recognizing a highly conserved cryptic receptor-binding domain (RBD) epitope and cross-reacting with spikes from all sarbecovirus clades. S2x259 broadly neutralizes spike-mediated entry of SARS-CoV-2 including the B.1.1.7, B.1.351, P.1 and B.1.427/B.1.429 VOC, as well as a wide spectrum of human and zoonotic sarbecoviruses through inhibition of ACE2 binding to the RBD. Furthermore, deep-mutational scanning and in vitro escape selection experiments demonstrate that S2x259 possesses a remarkably high barrier to the emergence of resistance mutants. We show that prophylactic administration of S2x259 protects Syrian hamsters against challenges with the prototypic SARS-CoV-2 and the B.1.351 variant, suggesting this mAb is a promising candidate for the prevention and treatment of emergent VOC and zoonotic infections. Our data unveil a key antigenic site targeted by broadly-neutralizing antibodies and will guide the design of pan-sarbecovirus vaccines.", - "rel_num_authors": 46, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.06.21254996", + "rel_abs": "IntroductionThe COVID-19 pandemic has resulted in social isolation and reports of insomnia. However, reports of changes in sleep duration and associated factors are few.\n\nMethodsData were from an online survey of adults recruited via social media that included a question asking whether the respondent slept less or more after the onset of the pandemic. Analyses determined the association between changes in sleep duration and self reported sociodemographic and occupational information; beliefs about COVID-19; changes in sleep patterns; and responses pertaining to loneliness, anxiety, and depression.\n\nResultsThere were 5,175 respondents; 53.9% had a change in sleep duration. 17.1% slept less and 36.7% slept more. Sleeping more was related to greater education, being single/divorced/separated, unemployed or a student. Being retired, divorced/separated or a homemaker, and living in the Mountain or Central time zones were associated with less sleep. Beliefs that COVID-19 would result in personal adverse consequences was associated with both more and less sleep. However, the strongest associations with both more and less sleep were seen with depression, anxiety, and loneliness with adjusted odds ratios ranging from 1.92 (95% CI 1.67-2.21) for sleeping more and loneliness to 5.29 (95% CI 4.1-6.7) for sleeping less and anxiety.\n\nConclusionsChanges in sleep duration since the start of the COVID-19 pandemic were highly prevalent among social media users and were associated with several sociodemographic factors and beliefs that COVID-19 would have adverse personal impacts. However, the strongest associations occurred with worse mental health suggesting that improvements may occur with better sleep.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "M. Alejandra Tortorici", - "author_inst": "University of Washington" - }, - { - "author_name": "Nadine Czudnochowski", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Tyler N Starr", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Roberta Marzi", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Alexandra C. Walls", - "author_inst": "University of Washington" - }, - { - "author_name": "Fabrizia Zatta", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "John E. Bowen", - "author_inst": "University of Washington" - }, - { - "author_name": "Stefano Jaconi", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Julia di Iulio", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Zhaoqian Wang", - "author_inst": "University of Washington" - }, - { - "author_name": "Anna De Marco", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Samantha Zepeda", - "author_inst": "University of Washington" - }, - { - "author_name": "Dora Pinto", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Zhuoming Liu", - "author_inst": "Washington University School of Medicine" - }, - { - "author_name": "Martina Beltramello", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Istvan Bartha", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Michael P. Housley", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Florian A Lempp", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Laura E. Rosen", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Exequiel Dellota Jr.", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Hanna Kaiser", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Martin Montiel-Ruiz", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Jiayi Zhou", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Amin Addetia", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Barbara Guarino", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Katja Culap", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Nicole Sprugasci", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Christian Saliba", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Eneida Vetti", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Isabella Giacchetto-Sasselli", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Chiara Silacci Fregni", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Rana Abdelnabi", - "author_inst": "Rega Institute, KU Leuven" - }, - { - "author_name": "Caroline Shi-Yan Foo", - "author_inst": "Katholieke Universiteit Leuven" - }, - { - "author_name": "Colin Havenar-Daughton", - "author_inst": "Vir Biotechnology" + "author_name": "Salma Batool-Anwar", + "author_inst": "Brigham and Women's Hospital" }, { - "author_name": "Michael A Schmid", - "author_inst": "Vir Biotechnology" + "author_name": "Rebecca Robbins", + "author_inst": "Brigham & Women's Hospital" }, { - "author_name": "Fabio Benigni", - "author_inst": "Vir Biotechnology" + "author_name": "Shahmir H Ali", + "author_inst": "Department of Social and Behavioral Sciences, School of Global Public Health, New York University" }, { - "author_name": "Elisabetta Cameroni", - "author_inst": "Vir Biotechnology" + "author_name": "Ariadna Capasso", + "author_inst": "Department of Social and Behavioral Sciences, School of Global Public Health, New York University" }, { - "author_name": "Johan Neyts", - "author_inst": "Rega Institute" + "author_name": "Joshua Foreman", + "author_inst": "Department of Social and Behavioral Sciences, School of Global Public Health, New York University" }, { - "author_name": "Amalio Telenti", - "author_inst": "Vir Biotechnology" - }, - { - "author_name": "Gyorgy Snell", - "author_inst": "Vir Biotechnology Inc" + "author_name": "Abbey M Jones", + "author_inst": "Department of Epidemiology, School of Global Public Health, New York University" }, { - "author_name": "Herbert W Virgin", - "author_inst": "Vir Biotechnology" + "author_name": "Yesim Tozan", + "author_inst": "Global Health Program, School of Global Public Health, New York University" }, { - "author_name": "Sean P. J. Whelan", - "author_inst": "Washington University in Saint Louis" + "author_name": "Ralph J DiClemente", + "author_inst": "Department of Social and Behavioral Sciences, School of Global Public Health, New York University" }, { - "author_name": "Jesse D Bloom", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Davide Corti", - "author_inst": "Humabs Biomed SA, subsidiary of Vir Biotechnology" - }, - { - "author_name": "David Veesler", - "author_inst": "University of Washington" - }, - { - "author_name": "Matteo Samuele Pizzuto", - "author_inst": "Vir Biotechnology" + "author_name": "Stuart Quan", + "author_inst": "Brigham and Women's Hospital" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2021.04.06.21255009", @@ -844548,31 +844379,67 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.04.05.21254722", - "rel_title": "Outcomes of COVID-19 Vaccination Efforts in Florida from December 14, 2020 to March 15, 2021 on Older Individuals", + "rel_doi": "10.1101/2021.04.06.438552", + "rel_title": "The SARS-CoV-2 Nsp3 macrodomain reverses PARP9/DTX3L-dependent ADP-ribosylation induced by interferon signalling", "rel_date": "2021-04-07", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.05.21254722", - "rel_abs": "Per-capita, Florida ranks second in those 65 years of age and older (20.5%) with more than 4,500,000 individuals in this category. COVID-19 vaccine was allocated in a phased roll-out beginning December 14, 2020. Phase 1A included health care personnel with direct patient contact, and residents and staff of nursing homes (NHs) and assisted living facilities (ALFs). Following this initial phase, individuals 65 years of age and older became eligible for vaccination, along with individuals determined by hospital providers to be extremely medically vulnerable to COVID-19. This strategy was based on the desire to most immediately reduce morbidity and mortality, as COVID-19 morbidity and mortality is age-related. Through March 15, 2021, 4,338,099 individuals received COVID-19 vaccine, including 2,431,540 individuals who completed their vaccination series. Of all those vaccinated, 70% were 65 years of age and older, and 63% of those 65 years of age and older. Beginning February 1, 2021, the decline in the number of new cases per week became greater in those 65 years of age and older than those younger. By March 15, 2021, the number of new cases, hospitalizations, and deaths per day for those 65 years of age and older relative to mid-January, were 82%, 80%, and 92% lower respectively. In comparison, the number of new cases, hospitalizations, and deaths per day for those younger than 65 years of age were 70%, 60%, and 87% lower respectively. Reductions in rates in those 65 year of age and older, were thus greater than in those who were younger (p <0.01; Wilcoxon test). These data show that vaccination efforts directed at those 65 years of age and older results in accelerated rates of overall declines in COVID-19 hospitalizations and mortality.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.06.438552", + "rel_abs": "SARS-CoV-2 non-structural protein 3 (Nsp3) contains a macrodomain that is essential for virus replication and is thus an attractive target for drug development. This macrodomain is thought to counteract the host interferon (IFN) response, an important antiviral signalling cascade, via the removal of ADP-ribose modifications catalysed by host poly(ADP-ribose) polymerases (PARPs). Here, we show that activation of the IFN response induces ADP-ribosylation of host proteins and that ectopic expression of the SARS-CoV-2 Nsp3 macrodomain reverses this modification in human cells. We further demonstrate that this can be used to screen for cell-active macrodomain inhibitors without the requirement for BSL-3 facilities. This IFN-induced ADP-ribosylation is dependent on the PARP9/DTX3L heterodimer, but surprisingly the expression of Nsp3 macrodomain or PARP9/DTX3L deletion do not impair STAT1 phosphorylation or the induction of IFN-responsive genes. Our results suggest that PARP9/DTX3L-dependent ADP-ribosylation is a downstream effector of the host IFN response and that the cellular function of the SARS-CoV-2 Nsp3 macrodomain is to hydrolyse this end product of IFN signalling, and not to suppress the IFN response itself.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Scott Rivkees", - "author_inst": "Florida Department of Health" + "author_name": "Lilian Cristina Russo", + "author_inst": "University of Sao Paulo" }, { - "author_name": "Shamarial Roberson", - "author_inst": "Florida Department of Health" + "author_name": "Rebeka Tomasin", + "author_inst": "University of Sao Paulo" }, { - "author_name": "Carina Blackmore", - "author_inst": "Florida Department of Health" + "author_name": "Isaac Ara\u00fajo Matos", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Antonio Carlos Manucci", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Sven T Sowa", + "author_inst": "University of Oulu" + }, + { + "author_name": "Katie Dale", + "author_inst": "University of Sussex" + }, + { + "author_name": "Keith W Caldecott", + "author_inst": "University of Sussex" + }, + { + "author_name": "Lari Lehti\u00f6", + "author_inst": "University of Oulu" + }, + { + "author_name": "Deborah Schechtman", + "author_inst": "Instituto de Qu\u00edmica, Departamento de Bioqu\u00edmica, Universidade de S\u00e3o Paulo" + }, + { + "author_name": "Fl\u00e1via Carla Meotti", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Alexandre Bruni-Cardoso", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Nicolas Carlos Hoch", + "author_inst": "University of Sao Paulo" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.04.05.21254938", @@ -846422,99 +846289,135 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2021.04.05.21254952", - "rel_title": "mRNA vaccination compared to infection elicits an IgG-predominant response with greater SARS-CoV-2 specificity and similar decrease in variant spike recognition", + "rel_doi": "10.1101/2021.04.05.21254940", + "rel_title": "Single Prime hAd5 Spike (S) + Nucleocapsid (N) Dual Antigen Vaccination of Healthy Volunteers Induces a Ten-Fold Increase in Mean S- and N- T-Cell Responses Equivalent to T-Cell Responses from Patients Previously Infected with SARS-CoV-2", "rel_date": "2021-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.05.21254952", - "rel_abs": "During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic, new vaccine strategies including lipid nanoparticle delivery of antigen encoding RNA have been deployed globally. The BioNTech/Pfizer mRNA vaccine BNT162b2 encoding SARS-CoV-2 spike protein shows 95% efficacy in preventing disease, but it is unclear how the antibody responses to vaccination differ from those generated by infection. Here we compare the magnitude and breadth of antibodies targeting SARS-CoV-2, SARS-CoV-2 variants of concern, and endemic coronaviruses, in vaccinees and infected patients. We find that vaccination differs from infection in the dominance of IgG over IgM and IgA responses, with IgG reaching levels similar to those of severely ill COVID-19 patients and shows decreased breadth of the antibody response targeting endemic coronaviruses. Viral variants of concern from B.1.1.7 to P.1 to B.1.351 form a remarkably consistent hierarchy of progressively decreasing antibody recognition by both vaccinees and infected patients exposed to Wuhan-Hu-1 antigens.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.05.21254940", + "rel_abs": "In response to the need for a safe, efficacious vaccine that elicits vigorous T cell as well as humoral protection against SARS-CoV-2 infection, we have developed a dual-antigen COVID-19 vaccine comprising both the viral spike (S) protein modified to increase cell-surface expression (S-Fusion) and nucleocapsid (N) protein with an Enhanced T-cell Stimulation Domain (N-ETSD) to enhance MHC class I and II presentation and T-cell responses. The antigens are delivered using a human adenovirus serotype 5 (hAd5) platform with E1, E2b, and E3 regions deleted that has been shown previously in cancer vaccine studies to be safe and effective in the presence of pre-existing hAd5 immunity. The findings reported here are focused on human T-cell responses due to the likelihood that such responses will sustain efficacy against emerging variants, a hypothesis supported by our in silico prediction of T-cell epitope HLA binding for both the first-wave SARS-CoV-2 A strain and the B.1.351 strain K417N, E484K, and N501Y spike and T201I N variants. We demonstrate the hAd5 S-Fusion + N-ETSD vaccine antigens expressed by previously SARS-CoV-2-infected patient dendritic cells elicit Th1 dominant activation of autologous patient T cells, indicating the vaccine antigens have the potential to elicit immune responses in previously infected patients. For participants in our open-label Phase 1b study of the vaccine (NCT04591717; https://clinicaltrials.gov/ct2/show/NCT04591717), the magnitude of Th-1 dominant S- and N-specific T-cell responses after a single prime subcutaneous injection were comparable to T-cell responses from previously infected patients. Furthermore, vaccinated participant T-cell responses to S were similar for A strain S and a series of spike variant peptides, including S variants in the B.1.1.7 and B.1.351 strains. The findings that this dual-antigen vaccine elicits SARS-CoV-2-relevant T-cell responses and that such cell-mediated protection is likely to be sustained against emerging variants supports the testing of this vaccine as a universal booster that would enhance and broaden existing immune protection conferred by currently approved S-based vaccines.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Katharina Roeltgen", - "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" + "author_name": "Pete Sieling", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Sandra C.A. Nielsen", - "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" + "author_name": "Thomas King", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Prabhu S Arunachalam", - "author_inst": "Stanford University, Stanford, CA, USA" + "author_name": "Raymond Wong", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Fan Yang", - "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" + "author_name": "Andy Nguyen", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Ramona A. Hoh", - "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" + "author_name": "Kamil Wnuk", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Oliver F. Wirz", - "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" + "author_name": "Elizabeth R Gabitzsch", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Alexandra S Lee", - "author_inst": "Sean N. Parker Center for Allergy & Asthma Research, Stanford, CA, USA" + "author_name": "Adrian Rice", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Fei Gao", - "author_inst": "Stanford University, Stanford, CA, USA" + "author_name": "Helty Adisetiyo", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Vamsee Mallajosyula", - "author_inst": "Stanford University, Stanford, CA, USA" + "author_name": "Melanie Hermreck", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Chunfeng Li", - "author_inst": "Stanford University, Stanford, CA, USA" + "author_name": "Mohit Verma", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Emily Haraguchi", - "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" + "author_name": "Lise Zakin", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Massa J Shoura", - "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" + "author_name": "Annie Shin", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "James L Wilbur", - "author_inst": "Meso Scale Diagnostics LLC, Rockville, Maryland, USA." + "author_name": "Brett Morimoto", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Jacob N. Wohlstadter", - "author_inst": "Meso Scale Diagnostics LLC, Rockville, Maryland, USA." + "author_name": "Wendy Higashide", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Mark M. Davis", - "author_inst": "Stanford University, Stanford, CA, USA" + "author_name": "Kyle Dinkins", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Benjamin A. Pinsky", - "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" + "author_name": "Joseph Balint", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "George B. Sigal", - "author_inst": "Meso Scale Diagnostics LLC, Rockville, Maryland, USA." + "author_name": "Victor Peykov", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Bali Pulendran", - "author_inst": "Stanford University, Stanford, CA, USA" + "author_name": "Justin Taft", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Kari C. Nadeau", - "author_inst": "Sean N. Parker Center for Allergy & Asthma Research, Stanford, CA, USA." + "author_name": "Roosheel Patel", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Scott D. Boyd", - "author_inst": "Stanford University School of Medicine, Stanford, CA, USA" + "author_name": "Sofija Buta", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Marta Martin-Fernandez", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Dusan Bogunovic", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Patricia Spilman", + "author_inst": "ImmunityBio, Inc." + }, + { + "author_name": "Lennie Sender", + "author_inst": "NantKwest" + }, + { + "author_name": "Sandeep Reddy", + "author_inst": "ImmunityBio, Inc." + }, + { + "author_name": "Philip Robinson", + "author_inst": "Hoag Hospital, Orange County (Irvine, Newport Beach)" + }, + { + "author_name": "Shahrooz Rabizadeh", + "author_inst": "ImmunityBio, Inc." + }, + { + "author_name": "Kayvan Niazi", + "author_inst": "ImmunityBio, Inc." + }, + { + "author_name": "Patrick Soon-Shiong", + "author_inst": "ImmunityBio, Inc." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2021.04.05.21254941", @@ -848152,115 +848055,55 @@ "category": "rheumatology" }, { - "rel_doi": "10.1101/2021.03.31.21254674", - "rel_title": "Efficient Maternal to Neonatal transfer of SARS-CoV-2 and BNT162b2 antibodies", + "rel_doi": "10.1101/2021.03.31.21254723", + "rel_title": "Quantifying Face Mask Comfort", "rel_date": "2021-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.31.21254674", - "rel_abs": "BackgroundThe significant risks posed to mothers and fetuses by COVID-19 in pregnancy have sparked a worldwide debate surrounding the pros and cons of antenatal SARS-CoV-2 inoculation, as we lack sufficient evidence regarding vaccine effectiveness in pregnant women and their offspring. We aimed to provide substantial evidence for the effect of BNT162b2 mRNA vaccine versus native infection on maternal humoral, as well as transplacentally acquired fetal immune response, potentially providing newborn protection.\n\nMethodsA multicenter study where parturients presenting for delivery were recruited at 8 medical centers across Israel and assigned to three study groups: vaccinated (n=86); PCR confirmed SARS-CoV-2 infected during pregnancy (n=65), and unvaccinated non-infected controls (n=62). Maternal and fetal blood samples were collected from parturients prior to delivery and from the umbilical cord following delivery, respectively. Sera IgG and IgM titers were measured using Milliplex MAP SARS-CoV-2 Antigen Panel (for S1, S2, RBD and N).\n\nResultsBNT162b2 mRNA vaccine elicits strong maternal humoral IgG response (Anti-S and RBD) that crosses the placenta barrier and approaches maternal titers in the fetus within 15 days following the first dose. Maternal to neonatal anti-COVID-19 antibodies ratio did not differ when comparing sensitization (vaccine vs. infection). IgG transfer rate was significantly lower for third-trimester as compared to second trimester infection. Lastly, fetal IgM response was detected in 5 neonates, all in the infected group.\n\nConclusionsAntenatal BNT162b2 mRNA vaccination induces a robust maternal humoral response that effectively transfers to the fetus, supporting the role of vaccination during pregnancy.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.31.21254723", + "rel_abs": "Face mask usage is one of the most effective ways to limit SARS-CoV-2 transmission, but a mask is only useful if user compliance is high. Through anonymous surveys, we show that mask discomfort is the primary source of noncompliance in mask wearing. Further, through these surveys, we identify three critical parameters that dictate mask comfort: air resistance, water vapor permeability, and face temperature change. To validate these parameters in a physiological context, we performed experiments to measure the respiratory rate and change in face temperature while wearing different types of commonly used masks. Finally, using values of these parameters from experiments and the literature, and surveys asking users to rate the comfort of various masks, three machine learning algorithms were trained and tested to generate overall comfort scores for those masks. Although all three models tested performed with an accuracy of approximately 70%, the multiple linear regression model also provides a simple analytical expression to predict the comfort scores for any face mask provided the input parameters. As face mask usage is crucial during the COVID-19 pandemic, the ability of this quantitative framework to predict mask comfort is likely to improve user experience and prevent discomfort-induced noncompliance.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Ofer Beharier", - "author_inst": "Hadassah Hebrew University Medical Center" - }, - { - "author_name": "Romina Plitman Mayo", - "author_inst": "Weizmann Institute of Science" - }, - { - "author_name": "Tal Raz", - "author_inst": "Hebrew University" - }, - { - "author_name": "Kira Nahum Sacks", - "author_inst": "Wolfson Medical Center" - }, - { - "author_name": "Letizia Schreiber", - "author_inst": "Wolfson Medical Center" - }, - { - "author_name": "Yael Suissa-Cohen", - "author_inst": "Hadassah Hebrew University Medical Center" - }, - { - "author_name": "Rony Chen", - "author_inst": "Rabin Medical Center" - }, - { - "author_name": "Rachel Gomez-Tolub", - "author_inst": "Rabin Medical Center" - }, - { - "author_name": "Eran Hadar", - "author_inst": "Rabin Medical Center" - }, - { - "author_name": "Rinat Gabbay-Benziv", - "author_inst": "Hillel Yaffe Medical Center" - }, - { - "author_name": "Yuval Jaffe Moshkovich", - "author_inst": "Hillel Yaffe Medical Center" - }, - { - "author_name": "Tal Biron-Shental", - "author_inst": "Meir Medical Center" - }, - { - "author_name": "Gil Shechter-Maor", - "author_inst": "Meir Medical Center" - }, - { - "author_name": "Sivan Farladansky-Gershnabel", - "author_inst": "Meir Medical Center" - }, - { - "author_name": "Hen Yitzhak Sela", - "author_inst": "Shaare Zedek Medical Center" - }, - { - "author_name": "Hedi Benyamini-Raischer", - "author_inst": "Emek Medical Center" + "author_name": "Esther Koh", + "author_inst": "Harvard University" }, { - "author_name": "Nitzan D Sela", - "author_inst": "Emek Medical Center" + "author_name": "Mythri Ambatipudi", + "author_inst": "Harvard University" }, { - "author_name": "Debra Goldman-Wohl", - "author_inst": "Hadassah Hebrew University Medical Center" + "author_name": "DaLoria L. Boone", + "author_inst": "Harvard University" }, { - "author_name": "Ziv Shulman", - "author_inst": "Weizmann Institute of Science" + "author_name": "Julia B.W. Luehr", + "author_inst": "Harvard University" }, { - "author_name": "Ariel Many", - "author_inst": "Sourasky Medical Center" + "author_name": "Alena Blaise", + "author_inst": "Harvard University" }, { - "author_name": "Haim Barr", - "author_inst": "Weizmann Institute of Science" + "author_name": "Jose Gonzalez", + "author_inst": "Harvard University" }, { - "author_name": "Simcha Yagel", - "author_inst": "Hadassah Hebrew University Medical Center" + "author_name": "Nishant Sule", + "author_inst": "Harvard University" }, { - "author_name": "Michal Neeman", - "author_inst": "Weizmann Institute of Science" + "author_name": "David J. Mooney", + "author_inst": "Harvard University" }, { - "author_name": "Michal Kovo", - "author_inst": "Wolfson Medical Center" + "author_name": "Emily M. He", + "author_inst": "Harvard University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.03.31.21254708", @@ -850014,37 +849857,169 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.04.01.21254679", - "rel_title": "Is convalescent plasma futile in COVID-19? A Bayesian re-analysis of the RECOVERY randomised controlled trial", + "rel_doi": "10.1101/2021.03.31.21254685", + "rel_title": "Genomic epidemiology of SARS-CoV-2 transmission lineages in Ecuador", "rel_date": "2021-04-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.04.01.21254679", - "rel_abs": "IntroductionRandomised trials are generally performed from a frequentist perspective reporting point estimates and 95% confidence intervals. This approach can confuse \"evidence of no effect\" with \"no evidence of an effect\" and does not allow for contextual knowledge. The RECOVERY trial evaluated convalescent plasma for patients hospitalised with COVID-19, the interaction test for the primary outcome was not statistically significant, and the trial concluded no evidence of an effect. From the clinical immunology perspective, there is strong justification to expect differential responses to convalescent plasma in patients who already have their own antibodies to SARS-CoV2 (seropositive) versus those who do not (seronegative).\n\nMethodsOutcome data was extracted from the RECOVERY trial both overall and for seronegative participants. A Bayesian re-analysis with a wide variety of priors (vague, optimistic, skeptical and pessimistic) was performed calculating the posterior probability for both any benefit or a modest benefit (number needed to treat of 100).\n\nResultsAcross all patients, when analysed with a vague prior the likelihood of any benefit or a modest benefit was estimated to be 64% and 18% respectively. In contrast, in the seronegative subgroup, the likelihood of any benefit or a modest benefit was estimated to be 90% and 74%. Results were broadly consistent across all prior distributions.\n\nConclusionPerforming clinical trials during a pandemic is challenging, and RECOVERY has provided high quality evidence for numerous therapies. However, the use of frequentist hypothesis testing in this trial has led to the trialists and governing bodies to conclude a strong evidence of no effect. Based on this trial, and other prior knowledge there remains a strong probability that convalescent plasma provides at least a modest benefit in seronegative patients.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.31.21254685", + "rel_abs": "Characterisation of SARS-CoV-2 genetic diversity through space and time can reveal trends in virus importation and domestic circulation, and permit the exploration of questions regarding the early transmission dynamics. Here we present a detailed description of SARS-CoV-2 genomic epidemiology in Ecuador, one of the hardest hit countries during the early stages of the COVID-19 pandemic. We generate and analyse 160 whole genome sequences sampled from all provinces of Ecuador in 2020. Molecular clock and phylgeographic analysis of these sequences in the context of global SARS-CoV-2 diversity enable us to identify and characterise individual transmission lineages within Ecuador, explore their spatiotemporal distributions, and consider their introduction and domestic circulation. Our results reveal a pattern of multiple international importations across the country, with apparent differences between key provinces. Transmission lineages were mostly introduced before the implementation of non-pharmaceutical interventions (NPIs), with differential degrees of persistence and national dissemination.", + "rel_num_authors": 38, "rel_authors": [ { - "author_name": "Fergus W Hamilton", - "author_inst": "University of Bristol" + "author_name": "Bernardo Gutierrez", + "author_inst": "University of Oxford; Universidad San Francisco de Quito" }, { - "author_name": "Todd Campbell Lee", - "author_inst": "McGill University" + "author_name": "Sully Marquez", + "author_inst": "Universidad San Francisco de Quito" }, { - "author_name": "David T Arnold", - "author_inst": "University of Bristol" + "author_name": "Belen Prado-Vivar", + "author_inst": "Universidad San Francisco de Quito" }, { - "author_name": "Richard J Lilford", - "author_inst": "University of Birmingham" + "author_name": "Monica Becerra-Wong", + "author_inst": "Universidad San Francisco de Quito" }, { - "author_name": "Karla Hemming", - "author_inst": "University of Birmingham" + "author_name": "Juan Jose Guadalupe", + "author_inst": "Universidad San Francisco de Quito" + }, + { + "author_name": "Darlan da Silva Candido", + "author_inst": "University of Oxford" + }, + { + "author_name": "Juan Carlos Fernandez-Cadena", + "author_inst": "Universidad de Especialidades Espiritu Santo" + }, + { + "author_name": "Gabriel Morey-Leon", + "author_inst": "Universidad de Guayaquil" + }, + { + "author_name": "Ruben Armas-Gonzalez", + "author_inst": "Universidad de Especialidades Espiritu Santo" + }, + { + "author_name": "Derly Madeleiny Andrade-Molina", + "author_inst": "Universidad de Especialidades Espiritu Santo" + }, + { + "author_name": "Alfredo Bruno", + "author_inst": "Instituto Nacional de Investigacion en Salud Publica de Ecuador; Universidad Agraria del Ecuador" + }, + { + "author_name": "Domenica de Mora", + "author_inst": "Instituto Nacional de Investigacion en Salud Publica de Ecuador" + }, + { + "author_name": "Maritza Olmedo", + "author_inst": "Instituto Nacional de Investigacion en Salud Publica de Ecuador" + }, + { + "author_name": "Denisse Portugal", + "author_inst": "Instituto Nacional de Investigacion en Salud Publica de Ecuador" + }, + { + "author_name": "Manuel Gonzalez", + "author_inst": "Instituto Nacional de Investigacion en Salud Publica de Ecuador" + }, + { + "author_name": "Alberto Orlando", + "author_inst": "Instituto Nacional de Investigacion en Salud Publica de Ecuador" + }, + { + "author_name": "Jan Felix Drexler", + "author_inst": "Charite-Universitatsmedizin Berlin" + }, + { + "author_name": "Andres Moreira-Soto", + "author_inst": "Charite-Universitatsmedizin Berlin" + }, + { + "author_name": "Anna-Lena Sander", + "author_inst": "Charite-Universitatsmedizin Berlin" + }, + { + "author_name": "Sebastian Brunink", + "author_inst": "Charite-Universitatsmedizin Berlin" + }, + { + "author_name": "Arne Kuhne", + "author_inst": "Charite-Universitatsmedizin Berlin" + }, + { + "author_name": "Leandro Patino", + "author_inst": "Instituto Nacional de Investigacion en Salud Publica de Ecuador" + }, + { + "author_name": "Andres Carrazco-Montalvo", + "author_inst": "Instituto Nacional de Investigacion en Salud Publica de Ecuador" + }, + { + "author_name": "Orson Mestanza", + "author_inst": "Instituto Nacional de Investigacion en Salud Publica de Ecuador" + }, + { + "author_name": "Jeannete Zurita", + "author_inst": "Pontificia Universidad Catolica del Ecuador; Zurita & Zurita Laboratorios" + }, + { + "author_name": "Gabriela Sevillano", + "author_inst": "Zurita & Zurita Laboratorios" + }, + { + "author_name": "Louis du Plessis", + "author_inst": "University of Oxford" + }, + { + "author_name": "John T. McCrone", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Josefina Coloma", + "author_inst": "University of California, Berkeley" + }, + { + "author_name": "Gabriel Trueba", + "author_inst": "Universidad San Francisco de Quito" + }, + { + "author_name": "Veronica Barragan", + "author_inst": "Universidad San Francisco de Quito" + }, + { + "author_name": "Patricio Rojas-Silva", + "author_inst": "Universidad San Francisco de Quito" + }, + { + "author_name": "Michelle Grunauer", + "author_inst": "Universidad San Francisco de Quito" + }, + { + "author_name": "Moritz U.G. Kraemer", + "author_inst": "University of Oxford" + }, + { + "author_name": "Nuno R. Faria", + "author_inst": "University of Oxford; Imperial College London" + }, + { + "author_name": "Marina Escalera-Zamudio", + "author_inst": "University of Oxford" + }, + { + "author_name": "Oliver G. Pybus", + "author_inst": "University of Oxford" + }, + { + "author_name": "Paul Cardenas", + "author_inst": "Universidad San Francisco de Quito" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -851852,55 +851827,115 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.04.02.438274", - "rel_title": "Structure and dynamics of SARS-CoV-2 proofreading exoribonuclease ExoN", + "rel_doi": "10.1101/2021.04.02.438262", + "rel_title": "Recovery from acute SARS-CoV-2 infection and development of anamnestic immune responses in T cell-depleted rhesus macaques", "rel_date": "2021-04-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.02.438274", - "rel_abs": "High-fidelity replication of the large RNA genome of coronaviruses (CoVs) is mediated by a 3'-to-5' exoribonuclease (ExoN) in non-structural protein 14 (nsp14), which excises nucleotides including antiviral drugs mis-incorporated by the low-fidelity viral RNA-dependent RNA polymerase (RdRp) and has also been implicated in viral RNA recombination and resistance to innate immunity. Here we determined a 1.6-[A] resolution crystal structure of SARS-CoV-2 ExoN in complex with its essential co-factor, nsp10. The structure shows a highly basic and concave surface flanking the active site, comprising several Lys residues of nsp14 and the N-terminal amino group of nsp10. Modeling suggests that this basic patch binds to the template strand of double-stranded RNA substrates to position the 3' end of the nascent strand in the ExoN active site, which is corroborated by mutational and computational analyses. Molecular dynamics simulations further show remarkable flexibility of multi-domain nsp14 and suggest that nsp10 stabilizes ExoN for substrate RNA-binding to support its exoribonuclease activity. Our high-resolution structure of the SARS-CoV-2 ExoN-nsp10 complex serves as a platform for future development of anti-coronaviral drugs or strategies to attenuate the viral virulence.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.02.438262", + "rel_abs": "Severe COVID-19 has been associated with T cell lymphopenia 1,2, but no causal effect of T cell deficiency on disease severity has been established. To investigate the specific role of T cells in recovery from SARS-CoV-2 infections we studied rhesus macaques that were depleted of either CD4+, CD8+ or both T cell subsets prior to infection. Peak virus loads were similar in all groups, but the resolution of virus in the T cell-depleted animals was slightly delayed compared to controls. The T cell-depleted groups developed virus-neutralizing antibody responses and also class-switched to IgG. When re-infected six weeks later, the T cell-depleted animals showed anamnestic immune responses characterized by rapid induction of high-titer virus-neutralizing antibodies, faster control of virus loads and reduced clinical signs. These results indicate that while T cells play a role in the recovery of rhesus macaques from acute SARS-CoV-2 infections, their depletion does not induce severe disease, and T cells do not account for the natural resistance of rhesus macaques to severe COVID-19. Neither primed CD4+ or CD8+ T cells appeared critical for immunoglobulin class switching, the development of immunological memory or protection from a second infection.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Nicholas H Moeller", - "author_inst": "University of Minnesota" + "author_name": "Kim J Hasenkrug", + "author_inst": "Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hami" }, { - "author_name": "Ke Shi", - "author_inst": "University of Minnesota" + "author_name": "Friederike Feldmann", + "author_inst": "Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton" }, { - "author_name": "\u00d6zlem Demir", - "author_inst": "University of California, San Diego" + "author_name": "Lara Myers", + "author_inst": "Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hami" }, { - "author_name": "Surajit Banerjee", - "author_inst": "Cornell University" + "author_name": "Mario L Santiago", + "author_inst": "University of Colorado School of Medicine, Aurora, CO" }, { - "author_name": "Lulu Yin", - "author_inst": "University of Minnesota" + "author_name": "Kejun Guo", + "author_inst": "University of Colorado School of Medicine, Aurora, CO" }, { - "author_name": "Christopher Belica", - "author_inst": "University of Minnesota" + "author_name": "Bradley S Barrett", + "author_inst": "University of Colorado School of Medicine, Aurora, CO" }, { - "author_name": "Cameron Durfee", - "author_inst": "University of Minnesota" + "author_name": "Kaylee L Mickens", + "author_inst": "University of Colorado School of Medicine, Aurora, CO" }, { - "author_name": "Rommie E Amaro", - "author_inst": "University of California, San Diego" + "author_name": "Aaron Carmody", + "author_inst": "Research Technologies Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, U" }, { - "author_name": "Hideki Aihara", - "author_inst": "University of Minnesota" + "author_name": "Atsushi Okumura", + "author_inst": "Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "Deepashri Rao", + "author_inst": "Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hami" + }, + { + "author_name": "Madison M Collins", + "author_inst": "Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hami" + }, + { + "author_name": "Ronald J Messer", + "author_inst": "Laboratory of Persistent Viral Diseases, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hami" + }, + { + "author_name": "Jamie Lovaglio", + "author_inst": "Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton" + }, + { + "author_name": "Carl Shaia", + "author_inst": "Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton" + }, + { + "author_name": "Rebecca Rosenke", + "author_inst": "Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton" + }, + { + "author_name": "Neeltje van Doremalen", + "author_inst": "Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "Chad Clancy", + "author_inst": "Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton" + }, + { + "author_name": "Greg Saturday", + "author_inst": "Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton" + }, + { + "author_name": "Patrick Hanley", + "author_inst": "Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton" + }, + { + "author_name": "Brian Smith", + "author_inst": "Rocky Mountain Veterinary Branch, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton" + }, + { + "author_name": "Kimberly Meade-White", + "author_inst": "Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "W. Lesley Shupert", + "author_inst": "Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "David W. Hawman", + "author_inst": "Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + }, + { + "author_name": "Heinz Feldmann", + "author_inst": "Laboratory of Virology, Rocky Mountain Laboratories, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "new results", - "category": "biochemistry" + "category": "immunology" }, { "rel_doi": "10.1101/2021.04.03.438258", @@ -853822,125 +853857,37 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.04.01.438035", - "rel_title": "The neutralization potency of anti-SARS-CoV-2 therapeutic human monoclonal antibodies is retained against novel viral variants", + "rel_doi": "10.1101/2021.03.31.437931", + "rel_title": "Limiting the priming dose of a SARS CoV-2 vaccine improves virus-specific immunity", "rel_date": "2021-04-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.04.01.438035", - "rel_abs": "A wide range of SARS-CoV-2 neutralizing monoclonal antibodies (mAbs) were reported to date, most of which target the spike glycoprotein and in particular its receptor binding domain (RBD) and N-terminal domain (NTD) of the S1 subunit. The therapeutic implementation of these antibodies has been recently challenged by emerging SARS-CoV-2 variants that harbor extensively mutated spike versions. Consequently, the re-assessment of mAbs, previously reported to neutralize the original early-version of the virus, is of high priority.\n\nFour previously selected mAbs targeting non-overlapping epitopes, were evaluated for their binding potency to RBD versions harboring individual mutations at spike positions 417, 439, 453, 477, 484 and 501. Mutations at these positions represent the prevailing worldwide distributed modifications of the RBD, previously reported to mediate escape from antibody neutralization. Additionally, the in vitro neutralization potencies of the four RBD-specific mAbs, as well as two NTD-specific mAbs, were evaluated against two frequent SARS-CoV-2 variants of concern (VOCs): (i) the B.1.1.7 variant, emerged in the UK and (ii) the B.1.351 variant, emerged in South Africa. Variant B.1.351 was previously suggested to escape many therapeutic mAbs, including those authorized for clinical use. The possible impact of RBD mutations on recognition by mAbs is addressed by comparative structural modelling. Finally, we demonstrate the therapeutic potential of three selected mAbs by treatment of K18-hACE2 transgenic mice two days post infection with each of the virus strains.\n\nOur results clearly indicate that despite the accumulation of spike mutations, some neutralizing mAbs preserve their potency against SARS-CoV-2. In particular, the highly potent MD65 and BL6 mAbs are shown to retain their ability to bind the prevalent novel viral mutations and to effectively protect against B.1.1.7 and B.1.351 variants of high clinical concern.", - "rel_num_authors": 27, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.31.437931", + "rel_abs": "Since late 2019, SARS-CoV-2 has caused a global pandemic that has infected 128 million people worldwide. Although several vaccine candidates have received emergency use authorization (EUA), there are still a limited number of vaccine doses available. To increase the number of vaccinated individuals, there are ongoing discussions about administering partial vaccine doses, but there is still a paucity of data on how vaccine fractionation affects vaccine-elicited immunity. We performed studies in mice to understand how the priming dose of a SARS CoV-2 vaccine affects long-term immunity to SARS CoV-2. We first primed C57BL/6 mice with an adenovirus-based vaccine encoding SARS CoV-2 spike protein (Ad5-SARS-2 spike), similar to that used in the CanSino and Sputnik V vaccines. This prime was administered either at a low dose (LD) of 106 PFU or at a standard dose (SD) of 109 PFU, followed by a SD boost in all mice four weeks later. As expected, the LD prime induced lower immune responses relative to the SD prime. However, the LD prime elicited immune responses that were qualitatively superior, and upon boosting, mice that were initially primed with a LD exhibited significantly more potent immune responses. Overall, these data demonstrate that limiting the priming dose of a SARS CoV-2 vaccine may confer unexpected benefits. These findings may be useful for improving vaccine availability and for rational vaccine design.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Efi Makdasi", - "author_inst": "IIBR" - }, - { - "author_name": "Anat Zvi", - "author_inst": "IIBR" - }, - { - "author_name": "Ron Alcalay", - "author_inst": "IIBR" - }, - { - "author_name": "Tal Noy-Porat", - "author_inst": "IIBR" - }, - { - "author_name": "Eldar Peretz", - "author_inst": "IIBR" - }, - { - "author_name": "Adva Mechaly", - "author_inst": "IIBR" - }, - { - "author_name": "Yinon Levy", - "author_inst": "IIBR" - }, - { - "author_name": "Eyal Epstein", - "author_inst": "IIBR" - }, - { - "author_name": "Theodor Chitlaru", - "author_inst": "IIBR" - }, - { - "author_name": "Ariel Tennenhouse", - "author_inst": "Weizmann Institute of Science" - }, - { - "author_name": "Moshe Aftalion", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "David Gur", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Nir Paran", - "author_inst": "Israel Institute for Biological Research" - }, - { - "author_name": "Hadas Tamir", - "author_inst": "IIBR" - }, - { - "author_name": "Oren Zimhony", - "author_inst": "Kaplan Medical Center" - }, - { - "author_name": "Shay Weiss", - "author_inst": "IIBR" - }, - { - "author_name": "Michal Mandelboim", - "author_inst": "Israel Ministry of Health" - }, - { - "author_name": "Ella Mendelson", - "author_inst": "Israel Ministry of Health" - }, - { - "author_name": "Neta Zuckerman", - "author_inst": "Israel Ministry of Health" - }, - { - "author_name": "Ital Nemet", - "author_inst": "Israel Ministry of Health" - }, - { - "author_name": "Limor Kliker", - "author_inst": "Israel Ministry of Health" - }, - { - "author_name": "Shmuel Yitzhaki", - "author_inst": "IIBR" - }, - { - "author_name": "Shmuel C Shapira", - "author_inst": "IIBR" + "author_name": "Sarah Sanchez", + "author_inst": "Northwestern University" }, { - "author_name": "Tomer Israely", - "author_inst": "IBR" + "author_name": "Nicole Palacio", + "author_inst": "Northwestern University" }, { - "author_name": "Sarel J. Fleishman", - "author_inst": "Weizmann Institute of Science" + "author_name": "Tanushree Dangi", + "author_inst": "Northwestern University" }, { - "author_name": "Ohad Mazor", - "author_inst": "Israel Institute for Biological Research" + "author_name": "Thomas Ciucci", + "author_inst": "University of Rochester" }, { - "author_name": "Ronit Rosenfeld", - "author_inst": "IIBR" + "author_name": "Pablo Penaloza-MacMaster", + "author_inst": "Northwestern University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", "category": "immunology" }, @@ -855872,49 +855819,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.29.21254334", - "rel_title": "Estimating the asymptomatic proportion of SARS-CoV-2 infection in the general population: Analysis of a nationwide serosurvey in the Netherlands", + "rel_doi": "10.1101/2021.03.30.21254631", + "rel_title": "Performance of early warning signals for disease emergence: a case study on COVID-19 data", "rel_date": "2021-03-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.29.21254334", - "rel_abs": "BackgroundThe proportion of SARS-CoV-2 positive persons who are asymptomatic - and whether this proportion is age-dependent - are still open research questions. Because an unknown proportion of reported symptoms among SARS-CoV-2 positives will be attributable to another infection or affliction, the observed, or crude proportion without symptoms may underestimate the proportion of persons without symptoms that are caused by SARS-CoV-2 infection.\n\nMethodsBased on a large population-based serological study comprising test results on seropositivity and self-reported symptom history conducted in April/May 2020 in the Netherlands (n=3147), we estimated the proportion of reported symptoms among those persons infected with SARS-CoV-2 that is attributable to this infection, where the set of relevant symptoms fulfills the ECDC case definition of COVID-19, using inferential methods for the attributable risk (AR). Generalised additive regression modelling was used to estimate the age-dependent relative risk (RR) of reported symptoms, and the AR and asymptomatic proportion (AP) were calculated from the fitted RR.\n\nResultsUsing age-aggregated data, the estimated AP was 70% (95% CI: 65-77%). The estimated AP decreased with age, from 80% (95% CI: 67-100%) for the <20 years age-group, to 55% (95% CI: 48-68%) for the 70+ years age-group.\n\nConclusionWhereas the crude AP represents a lower bound for the proportion of persons infected with SARS-CoV-2 without COVID-19 symptoms, the AP as estimated via an attributable risk approach represents an upper bound. Age-specific AP estimates can inform the implementation of public health actions such as targetted virological testing and therefore enhance containment strategies.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.30.21254631", + "rel_abs": "Developing tools for rapid and early detection of disease re-emergence is important to perform science-based risk assessment of epidemic threats. In the past few years, several early warning signals (EWS) from complex systems theory have been introduced to detect impending critical transitions and extend the set of indicators. However, it is still debated whether they are generically applicable or potentially sensitive to some dynamical characteristics such as system noise and rates of approach to critical parameter values. Moreover, testing on empirical data has, so far, been limited. Hence, verifying EWS performance remains a challenge. In this study, we tackle this question by analyzing the performance of common EWS, such as increasing variance and autocorrelation, in detecting the emergence of COVID-19 outbreaks in various countries. We illustrate that EWS are successful in detecting disease emergence if some basic assumptions are satisfied: a slow forcing through the transitions and not-fat-tailed noise. In uncertain cases, noise properties or commensurable time scales may obscure the expected early warning signals. Overall, our results suggest that EWS can be useful for active monitoring of epidemic dynamics, but that their performance is sensitive to certain features of the underlying dynamics. Our findings thus pave a connection between theoretical and empirical studies, constituting a further step towards the application of EWS indicators for informing public health policies.\n\nAuthor summaryTo extend the toolkit of alerting indicators against the emergence of infectious diseases, recent studies have suggested the use of generic early warning signals (EWS) from the theory of dynamical systems. Although extensively investigated theoretically, their empirical performance has still not been fully assessed. We contribute to it by considering the emergence of subsequent waves of COVID-19 in several countries. We show that, if some basic assumptions are met, EWS could be useful against new outbreaks, but they fail to detect rapid or noisy shifts in epidemic dynamics. Hence, we discuss the potentials and limitations of such indicators, depending on country-specific dynamical characteristics and on data collection strategies.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Scott A. McDonald", - "author_inst": "Netherlands National Institute for Public Health and the Environment" - }, - { - "author_name": "Fuminari Miura", - "author_inst": "Netherlands National Institute for Public Health and the Environment" - }, - { - "author_name": "Eric R.A. Vos", - "author_inst": "Netherlands National Institute for Public Health and the Environment" - }, - { - "author_name": "Michiel van Boven", - "author_inst": "Netherlands National Institute for Public Health and the Environment" - }, - { - "author_name": "Hester E. de Melker", - "author_inst": "Netherlands National Institute for Public Health and the Environment" - }, - { - "author_name": "Fiona R. M. van der Klis", - "author_inst": "Netherlands National Institute for Public Health and the Environment" + "author_name": "Daniele Proverbio", + "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg" }, { - "author_name": "Rob S. van Binnendijk", - "author_inst": "Netherlands National Institute for Public Health and the Environment" + "author_name": "Francoise Kemp", + "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg" }, { - "author_name": "Gerco den Hartog", - "author_inst": "Netherlands National Institute for Public Health and the Environment" + "author_name": "Stefano Magni", + "author_inst": "Luxembourg Centre for Systems Biomedicine, University of Luxembourg" }, { - "author_name": "Jacco Wallinga", - "author_inst": "Netherlands National Institute for Public Health and the Environmen" + "author_name": "Jorge Goncalves", + "author_inst": "University of Luxembourg" } ], "version": "1", @@ -857362,23 +857289,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.29.21254581", - "rel_title": "A new Reproduction Index Ri and its Usefulness for Germany's Covid19-Data", - "rel_date": "2021-03-31", + "rel_doi": "10.1101/2021.03.26.21254398", + "rel_title": "A RANDOMIZED TRIAL - INTENSIVE TREATMENT BASED IN IVERMECTIN AND IOTA-CARRAGEENAN AS PRE-EXPOSURE PROPHYLAXIS FOR COVID- 19 IN HEALTHCARE AGENTS", + "rel_date": "2021-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.29.21254581", - "rel_abs": "In the course of a large-scale infectious disease a time-dependent Reproduction rate is an important parameter for political, economic and social decisions. In this paper we focus on that parameter and introduce a mathematical implementation in addition to the mostly used definition of Robert-Koch-Institute (RKI) in Germany.\n\nSuch value is of particular interest in order to serve as a criterion for possible Lock-Downs and \"LockUps\" in society and can provide deep insights into a pandemic event.\n\nBoth the definition of the new Reproduction index and the RKIs Reproduction number are compared analytically, applied to simple model calculations and finally on real Covid19 data. Clear advantages of the new Reproduction index become apparent and some weaknesses of the RKIs Reproduction number become clearly visible.\n\nIn addition we propose two additional ways of displaying pandemic data to have the pandemic behaviour at a glance. We find that some signatures of the pandemic appear now very well expressed - especially in conjunction with the new Reproduction index Ri.\n\nThis all could be very helpful for future political, social and economic decisions.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.26.21254398", + "rel_abs": "Key PointO_ST_ABSIMPORTANCEC_ST_ABSThe emergency of COVID-19 requires the implementation of urgent strategies to prevent the spread of the disease, mainly in health personnel, who are the most exposed and has the highest risk of becoming infected with the SARS-COV-2. Drug repurposing is a pragmatic strategy, a faster and cheaper option, compared to the new drug development that has proven successful for many drugs and can be a key tool in emergency situations such as the current one that requires quick action. In addition, considering the limited access to vaccines for developing countries, preventive use of ivermectin can be a palliative that minimizes the risks of infection.\n\nOBJECTIVETo evaluate the protective effect of the combination Ivermectin / Iota-Carrageenan (IVER/IOTACRC), intensive treatment with repeated administration in oral- and nasal-spray, respectively, as a prophylaxis treatment prior to exposure to SARS-CoV-2, in health personnel at Public Healthcare Centers.\n\nPARTICIPANTS, DESIGN AND SETTINGRandomized controlled 1-1 clinical trial in Personal Health, n = 234. The subjects were divided into experimental (EG: n=117; 39.6 {+/-} 9.4 years old, 65F) and control groups (CG: n=117; 38.4 {+/-} 7.4 years old, 61F). The EG received Ivermectin orally 2 tablets of 6 mg = 12 mg every 7 days, and Iota-Carrageenan 6 sprays per day for 4 weeks. All participants were evaluated by physical examination COVID-19 diagnosed with negative RT-PCR at the beginning, final, and follow-up of the protocol. Differences between the variables were determined using the Chi-square test. The proportion test almost contagious subject and the contagion risk (Odds Ratio) were calculated using software STATA. The level of statistical significance was reached when p-Value < 0.05.\n\nRESULTThe number of subjects who were diagnosed with COVID-19 in EG was lower, only 4 of 117 (3.4%) than subjects in CG: 25 of 117 (21.4%) (P-Value = 1.10-5). Nineteen patients had mild symptoms, 4 were in EG whereas, 15 were in CG (p-Value = 0.001). Seven subjects were moderate, and 3 with severe diagnostics, all them in CG. The probability (Odds Ratio) of becoming ill with COVID-19 was significantly lower in EG with values of 0.13, 95% 0.03 to 0.40; p-Value = 1.10-4, this value (<1) indicates a protective effect of the IVER/IOTACRC in the EG. Logistic regression test demonstrated that treatment was effective to prevent COVID-19 (Odds Ratio 0.11, 95% 0.03 to 0.33; p-Value = 1.10-4). We also found that when increase the age, decrease contagious risk (Odds Ratio 0, 93, 95% 0.88 to 0.98, p-Value= 0, 02). On the other hand, the probability of contracting COVID-19 was dependent on the patients preexisting comorbidity (Odds Ratio 5.58, 95% 2.20 to 14.16, p-Value = 1.10-5). The other variables sex and designation were independent.\n\nCONCLUSIONThe intensive preventive treatment (short-term) with IVER/IOTACRC was able to reduce the number of health workers infected with COVID-19. This treatment had also effect in preventing the severity of the disease, since all patients treated were mild. We propose a new therapeutic alternative for prevention and short-term intervention scheme (intensive) that is of benefit of the health worker in this pandemic accelerated time. This intervention did not produce lack of adherence to treatment or adverse effects.\n\nTrial RegistrationClinicalTrials.gov Identifier: NCT04701710", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Robert N.J. Conradt", - "author_inst": "CONRADT Mess- und Regeltechnik" + "author_name": "Rossana Elena Chahla", + "author_inst": "SI.PRO.SA (Province Health System), Tucuman Argentina" + }, + { + "author_name": "Luis Medina Ruiz", + "author_inst": "SI.PRO.SA (Province Health System), Tucuman, Argentina" + }, + { + "author_name": "Eugenia Silvana Ortega", + "author_inst": "Health Research Institute, Ministry of Health, SI.PRO.SA" + }, + { + "author_name": "Marcelo Fabio Morales", + "author_inst": "Clinical Hospital Angel C. Padilla, Tucuman" + }, + { + "author_name": "Francisco Barreiro", + "author_inst": "Medical Center Emergence, Tucuman, Argentina" + }, + { + "author_name": "Alexia George", + "author_inst": "Medical Center Emergence, Tucuman, Argentina" + }, + { + "author_name": "Cesar Mansilla", + "author_inst": "Clinical Hospital Angel C. Padilla, Tucuman, Argentina" + }, + { + "author_name": "Sylvia Paola D'Amato", + "author_inst": "Clinical Hospital Angel C. Padilla, Tucuman, Argentina" + }, + { + "author_name": "Guillermo Barrenechea", + "author_inst": "Health Research Institute, Ministry of Health, SI.PRO.SA, Tucuman, Argentina" + }, + { + "author_name": "Gustavo Daniel Goroso", + "author_inst": "Research and Technology Center, Mogi das Cruzes University, Brazil. Human Motor Skill Analysis Laboratory, National University of Tucuman" + }, + { + "author_name": "Maria de los Angeles Peral de Bruno", + "author_inst": "Health Research Institute, Ministry of Health, SI.PRO.SA" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.03.25.21254322", @@ -859336,43 +859303,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.26.21254422", - "rel_title": "Targeting the Microbiome With KB109 in Outpatients with Mild to Moderate COVID-19 Reduced Medically Attended Acute Care Visits and Improved Symptom Duration in Patients With Comorbidities", + "rel_doi": "10.1101/2021.03.28.21254477", + "rel_title": "Changes in utilization and outcomes of mechanical ventilation of COVID-19 during the course of the pandemic in Germany in 2020: an observational study of 7,490 patients", "rel_date": "2021-03-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.26.21254422", - "rel_abs": "IntroductionIn 2020, the world experienced the beginning of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), also known as the coronavirus disease 2019 (COVID-19) pandemic. Mounting evidence indicates that the gut microbiome plays a role in host immune response to infections and, in turn, may have an impact on the disease trajectory of SARS-CoV2 infection. However, it remains to be established whether modulation of the microbiome can impact COVID-19-related symptomatology and patient outcomes. Therefore, we conducted a study designed to modulate the microbiome evaluating the safety and physiologic effects of KB109 combined with self-supportive care (SSC) vs SSC alone in non-hospitalized patients with mild to moderate COVID-19. KB109 is a novel synthetic glycan developed to increase the production of gut microbial metabolites that support immune system homeostasis through gut microbiome modulation. Our goal was to gain a better understanding of the safety of KB109, the natural course of COVID-19 symptomatology, and the possible role of the gut microbiome in patients with mild to moderate COVID-19.\n\nMethodsAdult patients who tested positive for COVID-19 were randomized 1:1 to receive KB109 combined with SSC or SSC alone for 14 days and were then followed for an additional 21 days (35 days in total). Patients self-assessed their COVID-19-related symptoms (8 cardinal symptoms plus 5 additional symptoms) and self-reported comorbidities. The primary and secondary objectives were to evaluate the safety of KB109 plus SSC compared with that of SSC alone and to evaluate selected measures of health, respectively.\n\nResultsBetween July 2, 2020 and December 23, 2020, 350 patients were randomized to receive KB109 and SSC (n=174) or SSC alone (n=176). Overall, the most common comorbidities reported were hypertension (18.0% [63/350 patients]) followed by chronic lung disease (8.6% 30/350 patients). KB109 was well tolerated with most treatment-emergent adverse events being mild to moderate in severity. The administration of KB109 plus SSC reduced medically-attended visits (ie, hospitalization, emergency room visits, or urgent care visits) by 50.0% in the overall population and by 61.7% in patients with [≥]1 comorbidity; in patients aged [≥]45 years or with [≥]1 comorbidity, medically-attended visits were reduced by 52.8%, In the SSC group, patients reporting [≥]1 comorbidity had a longer median time to resolution of symptoms than those who reported no comorbidities at baseline (13 overall symptoms: 30 vs 21 days, respectively; hazard ratio [HR]=1.163 [95% CI, 0.723-1.872]; 8 cardinal symptoms: 21 vs 15 days, respectively; HR=1.283 [95% CI, 0.809-2.035]). In patients reporting [≥]1 comorbidity, median time to resolution of symptoms was shorter in the KB109 plus SSC group compared with the SSC alone group (13 overall symptoms: 30 vs 21 days, respectively; HR=1.422 [95% CI, 0.898-2.250]; 8 cardinal symptoms: 17 vs 21 days, respectively; HR=1.574 [95% CI, 0.997-2.485]). In the KB109 plus SSC group, patients aged [≥]45 years or with [≥]1 comorbidity had a shorter median time to resolution of symptoms compared with SSC alone (overall 13 symptoms: 21 vs 31 days; HR=1.597 [95% CI, 1.064-2.398]).\n\nConclusionsResults from our study show that KB109 is well tolerated among patients with mild to moderate COVID-19. Patients with [≥]1 comorbidity had a longer duration of COVID-19 symptoms than those without comorbidities. Moreover, in patients reporting [≥]1 comorbidity or aged [≥]45 years (at-risk population), administration of KB109 plus SSC improved median time to resolution of COVID-19-related symptoms and reduced the rate of medically-attended visits compared with SSC alone.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.28.21254477", + "rel_abs": "RationaleThe role of non-invasive ventilation (NIV) in severe COVID-19 remains a matter of debate.\n\nObjectivesTo determine the utilization and outcome of NIV in COVID-19 in an unbiased cohort.\n\nMethodsObservational study of confirmed COVID-19 cases of claims data of the Local Health Care Funds comparing patients with non-invasive and invasive mechanical ventilation (IMV) between spring versus autumn period 2020.\n\nMeasurements and Main ResultsNationwide cohort of 7490 cases (median/IQR age 70/60-79 years, 66% male) 3851 (51%) patients primarily received IMV without NIV, 1614 (22%) patients received NIV without subsequent intubation, and 1247 (17%) patients had NIV failure (NIV-F), defined by subsequent endotracheal intubation. The proportion of patients who received invasive MV decreased from 74% to 39% during the second period. Accordingly, the proportion of patients with NIV exclusively increased from 10% to 28%, and those failing NIV increased from 9% to 21%. Median length of hospital stay decreased from 26 to 22 days, and duration of MV decreased from 11.6 to 7.6 days. The NIV failure rate decreased from 49% to 42%. Overall mortality remained unchanged (51% versus 53%). Mortality was 39% with NIV-only, 52% with IMV and 66% with NIV-F with mortality rates steadily increasing from 58% in early NIV-F (day 1) to 75% in late NIV-F (>4 days).\n\nConclusionUtilization of NIV rapidly increased during the autumn period, which was associated with a reduced duration of MV, but not with overall mortality. High NIV-F rates are associated with increased mortality, particularly in late NIV-F.\n\nFundingInstitutional support and physical resources were provided by the University Witten/Herdecke and Kliniken der Stadt Koln and the Federal Association of the Local Health Care Funds.\n\nAt a Glance CommentaryO_ST_ABSScientific Knowledge on the SubjectC_ST_ABSCurrent management of ventilatory support in COVID-19 patients with respiratory failure is heterogeneous. Despite increasing use of non-invasive ventilation (NIV), defining intubation criteria still remains a matter of uncertainty and discussion, especially with regard to the balance between the NIV benefits and the risk of NIV failure. In addition, robust data concerning the influence of the duration and failure of NIV on intubation and mortality rates are still missing, although the time span between initiation of NIV and subsequent intubation in case of respiratory failure progression is suggested to influence patient outcome.\n\nWhat This Study Adds to the FieldThis is the first large observational study describing differences of ventilatory strategies between the spring and autumn period of the SARS-CoV-2 pandemic in Germany and provides the in-hospital mortality rate of 7,490 patients who received mechanical ventilation. The increased utilization of NIV from 10% (first period) to 29% (second period) was associated with overall reduced durations of mechanical ventilation and length of hospital stay, but overall mortality remained comparably high and reached 51%, 53% respectively. Patients succeeding with NIV had lower mortality rates than those getting intubated without preceding NIV attempts, but those failing NIV had higher mortality rates, respectively, and this became even more predominant in late NIV failure. The present observational study shows the increasing role of NIV in the concert of ICU medicine related to COVID-19, but also clearly addresses its risks in addition to its benefits, both impacting on mortality.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "John P Haran", - "author_inst": "University of Massachusetts Medical School" + "author_name": "Christian Karagiannidis", + "author_inst": "ARDS and ECMO centre Cologne-Merheim, University Witten/ Herdecke" }, { - "author_name": "Yan Zheng", - "author_inst": "Kaleido Biosciences, Inc, Lexington, MA" + "author_name": "Corinna Hentschker", + "author_inst": "Research Institute of the Local Health Care Funds, Berlin, Germany" + }, + { + "author_name": "Michael Westhoff", + "author_inst": "Department of Pneumology, Sleep and Critical Care Medicine, Lungenklinik Hemer, Hemer, Germany, and University Witten/Herdecke, Witten, Germany" + }, + { + "author_name": "Steffen Weber-Carstens", + "author_inst": "Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charite - Universitaetsmedizin Berlin, Berlin, Germany." }, { - "author_name": "Katharine Knobil", - "author_inst": "Kaleido Biosciences, Inc, Lexington, MA" + "author_name": "Uwe Janssens", + "author_inst": "Medical Clinic and Medical Intensive Care Medicine, St.-Antonius Hospital, Eschweiler, Germany" }, { - "author_name": "Norma Alonzo-Palma", - "author_inst": "Kaleido Biosciences, Inc, Lexington, MA" + "author_name": "Stefan Kluge", + "author_inst": "University Medical Center Hamburg-Eppendorf, Hamburg, Germany" }, { - "author_name": "Jonathan Lawrence", - "author_inst": "Kaleido Biosciences, Inc, Lexington, MA" + "author_name": "Michael Pfeifer", + "author_inst": "Department of Internal Medicine II, University Hospital Regensburg, Regensburg, Germany; Department of Pneumology, Donaustauf Hospital, Donaustauf, Germany" }, { - "author_name": "Mark Wingertzahn", - "author_inst": "Kaleido Biosciences, Inc, Lexington, MA" + "author_name": "Claudia Spies", + "author_inst": "Department of Anesthesiology and Operative Intensive Care Medicine (CCM, CVK), Charite - Universitaetsmedizin Berlin, Berlin, Germany." + }, + { + "author_name": "Tobias Welte", + "author_inst": "Department of Respiratory Medicine and German Centre of Lung Research (DZL), Hannover Medical School, Hannover, Germany" + }, + { + "author_name": "Rolf Rossaint", + "author_inst": "Department of Anesthesiology, University Hospital Aachen, RWTH Aachen, Aachen, Germany" + }, + { + "author_name": "Carina Mostert", + "author_inst": "Research Institute of the Local Health Care Funds, Berlin, Germany" + }, + { + "author_name": "Wolfram Windisch", + "author_inst": "Department of Pneumology and Critical Care Medicine, Cologne-Merheim Hospital, ARDS and ECMO center, Kliniken der Stadt Koeln, Witten/Herdecke University Hospit" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2021.03.25.21254215", @@ -860922,123 +860913,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.25.21254335", - "rel_title": "Infliximab is associated with attenuated immunogenicity to BNT162b2 and ChAdOx1 nCoV-19 SARS-CoV-2 vaccines", - "rel_date": "2021-03-28", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.25.21254335", - "rel_abs": "BackgroundDelayed second-dose SARS-CoV-2 vaccination trades maximal effectiveness for a lower level of immunity across more of the population. We investigated whether patients with inflammatory bowel disease treated with infliximab have attenuated serological responses to a single-dose of a SARS-CoV-2 vaccine.\n\nMethodsAntibody responses and seroconversion rates in infliximab-treated patients (n=865) were compared to a cohort treated with vedolizumab (n=428), a gut-selective anti-integrin 4{beta}7 monoclonal antibody. Our primary outcome was anti-SARS-CoV-2 spike (S) antibody concentrations 3-10 weeks after vaccination in patients without evidence of prior infection. Secondary outcomes were seroconversion rates, and antibody responses following past infection or a second dose of the BNT162b2 vaccine.\n\nFindingsGeometric mean [SD] anti-SARS-CoV-2 antibody concentrations were lower in patients treated with infliximab than vedolizumab, following BNT162b2 (6.0 U/mL [5.9] vs 28.8 U/mL [5.4] P<0.0001) and ChAdOx1 nCoV-19 (4.7 U/mL [4.9]) vs 13.8 U/mL [5.9] P<0.0001) vaccines. In our multivariable models, antibody concentrations were lower in infliximab-compared to vedolizumab-treated patients who received the BNT162b2 (fold change [FC] 0.29 [95% CI 0.21, 0.40], p<0.0001) and ChAdOx1 nCoV-19 (FC 0.39 [95% CI 0.30, 0.51], p<0.0001) vaccines. In both models, age [≥] 60 years, immunomodulator use, Crohns disease, and smoking were associated with lower, whilst non-white ethnicity was associated with higher, anti-SARS-CoV-2 antibody concentrations. Seroconversion rates after a single-dose of either vaccine were higher in patients with prior SARS-CoV-2 infection and after two doses of BNT162b2 vaccine.\n\nInterpretationInfliximab is associated with attenuated immunogenicity to a single-dose of the BNT162b2 and ChAdOx1 nCoV-19 SARS-CoV-2 vaccines. Vaccination after SARS-CoV-2 infection, or a second dose of vaccine, led to seroconversion in most patients. Delayed second dosing should be avoided in patients treated with infliximab.\n\nFundingRoyal Devon and Exeter and Hull University Hospital Foundation NHS Trusts. Unrestricted educational grants: F. Hoffmann-La Roche AG (Switzerland), Biogen GmbH (Switzerland), Celltrion Healthcare (South Korea) and Galapagos NV (Belgium).\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSFaced with further surges of SARS-CoV-2 infection, a growing number of countries, including the UK, have opted to delay second vaccine doses for all people. This strategy trades maximal effectiveness against a lower level of protective immunity across more of the at-risk population.\n\nWe have previously shown that seroprevalence, seroconversion in PCR-confirmed cases, and the magnitude of anti-SARS-CoV-2 antibodies following SARS-CoV-2 infection are reduced in infliximab-compared with vedolizumab-treated patients. Whether single-doses of vaccines are effective in patients treated with anti-TNF therapies is unknown.\n\nWe searched PubMed from 25 November 2019 to 23 March 2021 with the terms \"anti-tumour necrosis factor\" or \"anti-integrin\" or \"infliximab\" or \"adalimumab\" or \"vedolizumab\" or \"biological therapy\" or \"biologic therapy\" AND \"SARS-CoV-2\" or \"coronavirus\" or \"COVID-19\" or AND \"seroprevalence\" or \"seroconversion\" or \"antibody\" or \"antibody response\" or \"magnitude\" or \"immunogenicity\" AND \"vaccine\" or \"vaccination\" or \"immunisation\" or \"immunization\" or \"ChAdOx1 nCoV-19\" or \"BNT162b2\" or \"mRNA-1273\", without restriction on language.\n\nSerological responses to SARS-CoV-2 vaccines have been reported in registration trials and small observational cohorts of healthy volunteers. Two small studies, including one unpublished preprint, found that COVID-19 vaccine immunogenicity rates were lower in transplant recipients and patients with malignancy receiving immunosuppressive therapy, and fewer patients treated with potent immunosuppressants seroconverted than healthy controls. No studies have assessed the effect of anti-TNF therapy on immunogenicity following SARS-CoV-2 vaccination.\n\nAdded value of this studyTo test if anti-TNF drugs attenuate serological responses to primary SARS-CoV-2 vaccines, we analysed anti-SARS-CoV-2 spike (S) antibody concentrations and seroconversion rates in 1293 patients with inflammatory bowel disease who received primary vaccinations with either the ChAdOx1 nCoV-19 or BNT162b2 vaccines. 865 were treated with the anti-TNF drug infliximab and outcomes were compared to a reference cohort of 428 patients treated with vedolizumab, a gut selective anti-integrin 4{beta}7 monoclonal antibody that is not associated with impaired systemic immune responses.\n\nAnti-SARS-CoV-2 antibody levels and rates of seroconversion were lower following primary vaccination with both the BNT162b2 and ChAdOx1 nCoV-19 vaccines in patients with IBD treated with infliximab compared to vedolizumab. Older age, immunomodulator use, Crohns disease (versus ulcerative colitis or inflammatory bowel disease unclassified), and current smoking were associated with lower anti-SARS-CoV-2 antibody concentrations, irrespective of vaccine type. Non-white ethnicity was associated with higher anti-SARS-CoV-2 (S) antibody concentrations following primary vaccination with both vaccines. Antibody concentrations and seroconversion rates were higher in patients with past SARS-CoV-2 infection prior to a single-dose of either vaccine, and after 2 doses of the BNT162b2 vaccine.\n\nImplications of the available evidenceOur findings have important implications for patients treated with anti-TNF therapy, particularly for those also treated with an immunomodulator. Poor antibody responses to a single-dose of vaccine exposes these patients to a potential increased risk of SARS-CoV-2 infection. However, higher rates of seroconversion in patients with two exposures to SARS-CoV-2 antigen, even in the presence of TNF blockade, suggest that all patients receiving these drugs should be prioritized for optimally timed second doses. Until patients receive a second vaccine dose, they should consider that they are not protected from SARS-CoV-2 infection and continue to practice enhanced physical distancing and shielding if appropriate. Even after two antigen exposures, a small subset of patients failed to mount an antibody response. Antibody testing and adapted vaccine schedules should be considered to protect these at-risk patients.", - "rel_num_authors": 26, + "rel_doi": "10.1101/2021.03.26.437274", + "rel_title": "Mechanism of a COVID-19 nanoparticle vaccine candidate that elicits a broadly neutralizing antibody response to SARS-CoV-2 variants", + "rel_date": "2021-03-27", + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.26.437274", + "rel_abs": "Vaccines that induce potent neutralizing antibody (NAb) responses against emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are essential for combating the coronavirus disease 2019 (COVID-19) pandemic. We demonstrated that mouse plasma induced by self-assembling protein nanoparticles (SApNPs) that present 20 rationally designed S2G{Delta}HR2 spikes of the ancestral Wuhan-Hu-1 strain can neutralize the B.1.1.7, B.1.351, P.1, and B.1.617 variants with the same potency. The adjuvant effect on vaccine-induced immunity was investigated by testing 16 formulations for the multilayered I3-01v9 SApNP. Using single-cell sorting, monoclonal antibodies (mAbs) with diverse neutralization breadth and potency were isolated from mice immunized with the receptor binding domain (RBD), S2G{Delta}HR2 spike, and SApNP vaccines. The mechanism of vaccine-induced immunity was examined in mice. Compared with the soluble spike, the I3-01v9 SApNP showed 6-fold longer retention, 4-fold greater presentation on follicular dendritic cell dendrites, and 5-fold stronger germinal center reactions in lymph node follicles.\n\nONE-SENTENCE SUMMARYWith a well-defined mechanism, spike nanoparticle vaccines can effectively counter SARS-CoV-2 variants.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Nicholas A Kennedy", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" - }, - { - "author_name": "Simeng Lin", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" - }, - { - "author_name": "James R Goodhand", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" - }, - { - "author_name": "Neil Chanchlani", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" - }, - { - "author_name": "Benjamin Hamilton", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" - }, - { - "author_name": "Claire Bewshea", - "author_inst": "Exeter IBD and Pharmacogenetics Research Group" - }, - { - "author_name": "Rachel Nice", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" - }, - { - "author_name": "Desmond Chee", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" - }, - { - "author_name": "JR Fraser Cummings", - "author_inst": "University Hospital Southampton NHS Foundation Trust" - }, - { - "author_name": "Aileen Fraser", - "author_inst": "University Hospitals Bristol NHS Foundation Trust" - }, - { - "author_name": "Peter M Irving", - "author_inst": "Guy's and St Thomas' NHS Foundation Trust" - }, - { - "author_name": "Nikolaos Kamperidis", - "author_inst": "St Marks Hospital and Academic Institute" - }, - { - "author_name": "Klaartje B Kok", - "author_inst": "Barts Health NHS Trust" - }, - { - "author_name": "Christropher A Lamb", - "author_inst": "Newcastle upon Tyne Hospitals NHS Foundation Trust" - }, - { - "author_name": "Jonathan MacDonald", - "author_inst": "Queen Elizabeth University Hospital" - }, - { - "author_name": "Shameer J Mehta", - "author_inst": "University College London Hospitals NHS Foundation Trust" - }, - { - "author_name": "Richard CG Pollok", - "author_inst": "St George's University Hospital NHS Foundation Trust" + "author_name": "Yi-Nan Zhang", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Tim Raine", - "author_inst": "Cambridge University Hospitals NHS Foundation Trust" + "author_name": "Jennifer Paynter", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Philip J Smith", - "author_inst": "Liverpool University Hospitals NHS Foundation Trust" + "author_name": "Cindy Sou", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Ajay M Verma", - "author_inst": "Kettering General Hospital" + "author_name": "Tatiana Fourfouris", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Timothy J Mcdonald", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" + "author_name": "Ying Wang", + "author_inst": "Temple University" }, { - "author_name": "Shaji Sebastian", - "author_inst": "Hull University Teaching Hospitals NHS Trust" + "author_name": "Ciril Abraham", + "author_inst": "Temple University" }, { - "author_name": "Charlie Lees", - "author_inst": "Western General Hospital" + "author_name": "Timothy Ngo", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Nick Powell", - "author_inst": "Imperial College Healthcare NHS Trust" + "author_name": "Yi Zhang", + "author_inst": "Temple University" }, { - "author_name": "Tariq Ahmad", - "author_inst": "Royal Devon and Exeter NHS Foundation Trust" + "author_name": "Linling He", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "- CLARITY IBD Contributors", - "author_inst": "" + "author_name": "Jiang Zhu", + "author_inst": "The Scripps Research Institute" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" + "license": "cc_by_nc", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.03.26.437180", @@ -863144,51 +863071,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.22.21254139", - "rel_title": "Acute Brain Ischemia, Infarction and Hemorrhage in Subjects Dying with or Without Autopsy-Proven Acute Pneumonia", + "rel_doi": "10.1101/2021.03.22.21254081", + "rel_title": "COVID-19 reinfection: A Rapid Systematic Review of Case Reports and Case Series", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.22.21254139", - "rel_abs": "Stroke is one of the most serious complications of Covid-19 disease but it is still unclear whether stroke is more common with Covid-19 pneumonia as compared to non-Covid-19 pneumonia. We investigated the concurrence rate of autopsy-confirmed acute brain ischemia, acute brain infarction and acute brain hemorrhage with autopsy-proven acute non-Covid pneumonia in consecutive autopsies in the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND), a longitudinal clinicopathological study of normal aging and neurodegenerative diseases. Of 691 subjects with a mean age of 83.4 years, acute pneumonia was histopathologically diagnosed in 343 (49.6%); the concurrence rates for histopathologically-confirmed acute ischemia, acute infarction or subacute infarction was 14% and did not differ between pneumonia and non-pneumonia groups while the rates of acute brain hemorrhage were 1.4% and 2.0% of those with or without acute pneumonia, respectively. In comparison, in reviews of Covid-19 publications, reported clinically-determined rates of acute brain infarction range from 0.5% to 20% while rates of acute brain hemorrhage range from 0.13% to 2%. In reviews of Covid-19 autopsy studies, concurrence rates for both acute brain infarction and acute brain hemorrhage average about 10%. Covid-19 pneumonia and non-Covid-19 pneumonia may have similar risks tor concurrent acute brain infarction and acute brain hemorrhage when pneumonia is severe enough to cause death. Additionally, acute brain ischemia, infarction or hemorrhage may not be more common in subjects dying of acute pneumonia than in subjects dying without acute pneumonia.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.22.21254081", + "rel_abs": "The COVID-19 pandemic has infected millions of people worldwide and many countries have been suffering from a large number of deaths. Acknowledging the ability of SARS-CoV-2 to mutate into distinct strains as an RNA virus and investigating its potential to cause reinfection is important for future health policy guidelines. It was thought that individuals who recovered from COVID-19 generate a robust immune response and develop protective immunity, however, since the first case of documented reinfection of COVID-19 in August 2020, there have been a number of cases with reinfection. Many cases are lacking genomic data of the two infections and it remains unclear whether they were caused by different strains. In the present study, we undertook a rapid systematic review to identify cases infected with different genetic strains of SARS-CoV-2 confirmed by polymerase-chain reaction and viral genome sequencing. A total of 17 cases of genetically confirmed COVID-19 reinfection were found. One immunocompromised patient had mild symptoms with the first infection, but developed severe symptoms resulting in death with the second infection. Overall, 68.8% (11/16) had similar severity, 18.8% (3/16) had worse symptoms, and 12.5% (2/16) had milder symptoms with the second episode. Our case series shows that reinfection with different strains is possible and some cases may experience more severe infections with the second episode. The findings also suggest that COVID-19 may continue to circulate even after achieving herd immunity through natural infection or vaccination suggesting the need for longer term transmission mitigation efforts.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Thomas G Beach", - "author_inst": "Banner Sun Health Research Institute" - }, - { - "author_name": "Lucia I Sue", - "author_inst": "Banner Sun Health Research Institute" - }, - { - "author_name": "Anthony J Intorcia", - "author_inst": "Banner Sun Health Research Institute" - }, - { - "author_name": "Michael J Glass", - "author_inst": "Banner Sun Health Research Institute" - }, - { - "author_name": "Jessica E Walker", - "author_inst": "Banner Sun Health Research Institute" + "author_name": "Jingzhou Wang", + "author_inst": "Univ of Chicago" }, { - "author_name": "Richard Arce", - "author_inst": "Banner Sun Health Research Institute" + "author_name": "Christopher Kaperak", + "author_inst": "Univ of Chicago" }, { - "author_name": "Courtney M Nelson", - "author_inst": "Banner Sun Health Research Institute" + "author_name": "Toshiro Sato", + "author_inst": "Keio Univ" }, { - "author_name": "Geidy E Serrano", - "author_inst": "Banner Sun Health Research Institute" + "author_name": "Atsushi Sakuraba", + "author_inst": "Univ of Chicago" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.03.23.21254171", @@ -864978,35 +864889,27 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2021.03.23.21254214", - "rel_title": "Mouth-rinses and SARS-CoV-2 viral load in saliva: A living systematic review", + "rel_doi": "10.1101/2021.03.25.21254362", + "rel_title": "Estimation of the Reproduction Number for COVID-19 Based on Latest Vaccination Results and the Timing for Herd-Immunity: Prospect for 2021", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.23.21254214", - "rel_abs": "ObjectiveTo conduct a living systematic review of the clinical evidence regarding the effect of different mouth-rinses on the viral load of SARS-CoV-2 in the saliva of infected patients. The viral load in aerosols, the duration of the reduction in viral load, viral clearance, SARS-CoV-2 cellular infectivity, and salivary cytokine profiles were also evaluated.\n\nMaterials and methodsThis study was reported using the PRISMA guidelines. An electronic search was conducted in seven databases and in preprint repositories. We included human clinical trials that evaluated the effect of mouth-rinses with antiseptic substances on the viral load of SARS-CoV-2 in the saliva of children or adults that tested positive for SARS-CoV-2 using reverse transcriptase polymerase chain reaction (RT-PCR). Risk of bias was assessed using the ROBINS-I tool. PROSPERO registration number CRD42021240561.\n\nResultsFour studies matching eligibility criteria were selected for evaluation (n=32 participants). Study participants underwent oral rinses with hydrogen peroxide (H2O2) at 1 %, povidone-iodine (PI) at 0.5% or 1%, chlorhexidine gluconate (CHX) at 0.2% or 0.12% or cetylpyridinium chloride (CPC) at 0.075%. Only one study included a control group with sterile water. Three of the studies identified a significant reduction in viral load up to 3, 4, and 6 hours after the use of mouthwashes with PI, CHX, and CPC or PI vs. sterile water, respectively, while one study did not identify a significant reduction in viral load after the use of H2O2 rinses.\n\nConclusionsAccording to the present systematic review, the effect of the use of mouth-rinses on SARS-CoV-2 viral load in the saliva of COVID-19 patients remains uncertain. This is mainly due to the limited number of patients included and a high risk of bias present in the studies analyzed. Evidence from well-designed randomized clinical trials is required for further and more objective evaluation of this effect.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.25.21254362", + "rel_abs": "This study examined four countries Israel, United States, United Kingdom, and Serbia and present their possible vaccination trajectories into 2021. We found that populations in all the four countries are relaxing and taking the advantage of the benefit of an increasingly immunized community hence, experiencing a rising phase of [R] c(t). The United States is of particular concern, due to its fast rising [R]c(t) in comparison to other countries, potentially generating another wave of infection. Due to aggressive vaccination program, continued implementation of restrictive measures, or both, in all countries we analyzed, present a cautiously optimistic outlook at controlling the pandemic toward the latter part of 2021. We also found that despite a significant fraction of the population in selected countries being immunized, no countries other than Israel has its [R]c(t) reached its intrinsic [R]0 value. Based on our proposed methodology for deriving [R]0, our prediction shows that Israels indigenous COVID-19 daily [R]0 is approximately 2.2 based on its latest data.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Akram Hern\u00e1ndez V\u00e1squez", - "author_inst": "Universidad San Ignacio de Loyola, Lima, Peru" - }, - { - "author_name": "Antonio Barrenechea Pulache", - "author_inst": "Universidad Cient\u00edfica del Sur, Lima, Peru" + "author_name": "Steven Suan Zhu", + "author_inst": "Washington University in St.Louis" }, { - "author_name": "Daniel Comand\u00e9", - "author_inst": "Instituto de Efectividad Cl\u00ednica y Sanitaria (IECS). Buenos Aires, Argentina" - }, - { - "author_name": "Diego Aza\u00f1edo", - "author_inst": "Independent Researcher. Lima, Peru" + "author_name": "Enahoro Iboi", + "author_inst": "Spelman College" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "dentistry and oral medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.03.25.21254307", @@ -866504,21 +866407,145 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.24.21253923", - "rel_title": "Pattern of COVID-19 epidemics in Japan influenced by the control measures", + "rel_doi": "10.1101/2021.03.24.21253992", + "rel_title": "Longitudinal immune profiling of a SARS-CoV-2 reinfection in a solid organ transplant recipient", "rel_date": "2021-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.24.21253923", - "rel_abs": "BackgroundCOVID-19 has spread worldwide since its emergence in 2019. In contrast to many other countries with epidemics, Japan differed in that it avoided lockdowns and instead asked people for self-control. A travel campaign was conducted with a sizable budget, but the number of PCR tests was severely limited. These choices may have influenced the course of the epidemic.\n\nMethodsThe increase or decrease in the classes of SARS-CoV-2 variants was estimated by analyzing the published sequences with an objective multivariate analysis. This approach observes the samples in multiple directions, digesting complex differences into simpler forms. The results were compared over time with the number of confirmed cases, PCR tests, and overseas visitors. The kinetics of infection were analyzed using the logarithmic growth rate.\n\nResultsThe declared states of emergency failed to alter the movement of the growth rate. Three epidemic peaks were caused by domestically mutated variants. In other countries, there are few cases in which multiple variants have peaked. However, due to the relaxation of immigration restrictions, several infective variants have been imported from abroad and are currently competing for expansion, creating the fourth peak. By April 2021, these foreign variants exceeded 80%. The chaotic situation in Japan will continue for some time, in part because no effort has been made to identify asymptomatic carriers, and details of the vaccination program are undecided.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.24.21253992", + "rel_abs": "Prior to the emergence of antigenically distinct SARS-CoV-2 variants, reinfections were reported infrequently - presumably due to the generation of durable and protective immune responses. However, case reports also suggested that rare, repeated infections may occur as soon as 48 days following initial disease onset. The underlying immunologic deficiencies enabling SARS-CoV-2 reinfections are currently unknown. Here we describe a renal transplant recipient who developed recurrent, symptomatic SARS-CoV-2 infection - confirmed by whole virus genome sequencing - 7 months after primary infection. To elucidate the immunological mechanisms responsible for SARS-CoV-2 reinfection, we performed longitudinal profiling of cellular and humoral responses during both primary and recurrent SARS-CoV-2 infection. We found that the patient responded to the primary infection with transient, poor-quality adaptive immune responses. The patients immune system was further compromised by intervening treatment for acute rejection of the renal allograft prior to reinfection. Importantly, we also identified the development of neutralizing antibodies and the formation of humoral memory responses prior to SARS-CoV-2 reinfection. However, these neutralizing antibodies failed to confer protection against reinfection, suggesting that additional factors are required for efficient prevention of SARS-CoV-2 reinfection. Further, we found no evidence supporting viral evasion of primary adaptive immune responses, suggesting that susceptibility to reinfection may be determined by host factors rather than pathogen adaptation in this patient. In summary, our study suggests that a low neutralizing antibody presence alone is not sufficient to confer resistance against reinfection. Thus, patients with solid organ transplantation, or patients who are otherwise immunosuppressed, who recover from infection with SARS-CoV-2 may not develop sufficient protective immunity and are at risk of reinfection.", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Tomokazu Konishi", - "author_inst": "Akita Prefectural University" + "author_name": "Jonathan Klein", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Anderson F. Brito", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Paul Trubin", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Peiwen Lu", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Patrick Wong", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Tara Alpert", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Mario A. Pena-Hernandez", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Winston Haynes", + "author_inst": "SerImmune Inc." + }, + { + "author_name": "Kathy Kamath", + "author_inst": "SerImmune Inc." + }, + { + "author_name": "Feimei Liu", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Chantal B.F. Vogels", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Joseph R. Fauver", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Carolina Lucas", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Jieun Oh", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Tianyang Mao", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Julio Silva", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Anne L. Wyllie", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Catherine Muenker", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Arnau Casanovas-Massana", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Adam J. Moore", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Mary E. Petrone", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Chaney C. Kalinich", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "- IMPACT Research Team", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Charles Dela Cruz", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Shelli Farhadian", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Aaron Ring", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "John Shon", + "author_inst": "SerImmune Inc." + }, + { + "author_name": "Albert I. Ko", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Nathan D. Grubaugh", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Benjamin Israelow", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Akiko Iwasaki", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Marwan M. Azar", + "author_inst": "Yale School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -868138,71 +868165,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.26.437014", - "rel_title": "Aberrant glycosylation of anti-SARS-CoV-2 IgG is a pro-thrombotic stimulus for platelets", + "rel_doi": "10.1101/2021.03.26.436314", + "rel_title": "Immunoinformatic approach to design a vaccine against SARS-COV-2 membrane glycoprotein", "rel_date": "2021-03-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.26.437014", - "rel_abs": "A subset of patients with COVID-19 become critically ill, suffering from severe respiratory problems and also increased rates of thrombosis. The causes of thrombosis in severely ill COVID-19 patients are still emerging, but the coincidence of critical illness with the timing of the onset of adaptive immunity could implicate an excessive immune response. We hypothesised that platelets might be susceptible to activation by anti-SARS-CoV-2 antibodies and contribute to thrombosis. We found that immune complexes containing recombinant SARS-CoV-2 spike protein and anti-spike IgG enhanced platelet-mediated thrombosis on von Willebrand Factor in vitro, but only when the glycosylation state of the Fc domain was modified to correspond with the aberrant glycosylation previously identified in patients with severe COVID-19. Furthermore, we found that activation was dependent on FcyRIIA and we provide in vitro evidence that this pathogenic platelet activation can be counteracted by therapeutic small molecules R406 (fostamatinib) and ibrutinib that inhibit tyrosine kinases syk and btk respectively or by the P2Y12 antagonist cangrelor.", - "rel_num_authors": 13, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.26.436314", + "rel_abs": "SARS-COV-2 is a pandemic virus causing COVID-19 disease which affects lungs and upper respiratory tract leading to progressive increase in the death rate worldwide. Currently, there are more than 123 million cases and over 2.71 million confirmed death caused by this virus. In this study, by utilizing an immunoinformatic approach, multiepitope-based vaccine is designed from the membrane protein which plays a vital role in the virion assembly of the novel-CoV. A total of 19 MHC class- I binders with HLA-A and HLA-B alleles have been selected with NetMHC pan EL 4.0 method from IEDB MHC-I prediction server. Four epitopes candidates from M-protein were selected based on the antigenicity, stability, immunogenicity, Ramachandran plot and scores with 100 % was taken for docking analysis with alleles HLA-A (PDB ID: 1B0R) and HLA-B (PDB ID: 3C9N) using ClusPro server. Among the four epitopes, the epitope FVLAAVYRI has the least binding energy and forms electrostatic, hydrogen and hydrophobic interactions with HLA-A (-932.8 Kcal/mol) and HLA-B (-860.7 Kcal/mol) which induce the T-cell response. Each HLA-A and HLA-B complex in the system environment achieves stable backbone configuration between 45-100 ns of MD simulation. This study reports a potent antigenic and immunogenic profile of FVLAAVYRI epitope from M-protein and further in vitro and in vivo validation is needed for its adaptive use as vaccine against COVID-19.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Alexander P Bye", - "author_inst": "University of Reading" - }, - { - "author_name": "Willianne Hoepel", - "author_inst": "Amsterdam UMC" - }, - { - "author_name": "Joanne L Mitchell", - "author_inst": "University of Birmingham" - }, - { - "author_name": "Sophie Jegouic", - "author_inst": "University of Reading" - }, - { - "author_name": "Silvia Loureiro", - "author_inst": "University of Reading" - }, - { - "author_name": "Tanya Sage", - "author_inst": "University of Reading" - }, - { - "author_name": "Steven de Taeye", - "author_inst": "Amsterdam UMC" - }, - { - "author_name": "Marit van Gils", - "author_inst": "Amsterdam UMC" - }, - { - "author_name": "Neline Kriek", - "author_inst": "University of Reading" - }, - { - "author_name": "Nichola Cooper", - "author_inst": "Imperial College London" - }, - { - "author_name": "Ian Jones", - "author_inst": "University of Reading" - }, - { - "author_name": "Jeroen den Dunnen", - "author_inst": "Amsterdam UMC" - }, - { - "author_name": "Jonathan M Gibbins", - "author_inst": "University of Reading" + "author_name": "Radhika Ravindran", + "author_inst": "Indian Institute of Technology, Madras" } ], "version": "1", - "license": "cc_no", + "license": "cc0_ng", "type": "new results", - "category": "immunology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2021.03.26.437194", @@ -870183,41 +870162,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.15.21253567", - "rel_title": "Evaluation of pooling of samples for testing SARS-COV- 2 for mass screening of COVID-19", + "rel_doi": "10.1101/2021.03.19.21253924", + "rel_title": "VIRAL AND ANTIBODY TESTING FOR CORONAVIRUS DISEASE 2019 (COVID-19): FACTORS ASSOCIATED WITH POSITIVITY IN ELECTRONIC HEALTH RECORDS FROM THE UNITED STATES", "rel_date": "2021-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253567", - "rel_abs": "BackgroundThe current pandemic of SARS- COV- 2 virus, widely known as COVID-19 has affected millions of people around the world. The World Health Organization (WHO) has recommended vigorous testing to differentiate SARS-CoV-2 from other respiratory infections to aid in guiding appropriate care and management. Situations like this have demanded robust testing strategies and pooled testing of samples for SARS- COV- 2 virus has provided the solution to mass screening of people. The pooled testing strategy can be very effective in testing with limited resources, yet it comes with its own limitations. These limitations need critical consideration when it comes to testing of highly infectious disease like COVID -19.\n\nMethodsThe study evaluated the pooled testing of nasopharyngeal swabs for SARS- COV- 2 by comparing sensitivity of individual sample testing with 4 and 8 pool sample testing. Median cycle threshold (Ct) values were compared. The precision of pooled testing was assessed by doing an inter and intra assay of pooled samples. Coefficient of variance was calculated for inter and intra assay variability.\n\nResultsThe sensitivity becomes considerably low when the samples are pooled, there is a higher percentage of false negatives with higher pool size and when the patient viral load is low or weak positive samples. High variability was seen in the intra and inter assay, especially in weak positive samples and larger pool size.\n\nConclusionAs COVID - 19 numbers are still high and testing capacity needs to be high, we have to meticulously evaluate the testing strategy for each country depending on its testing capacity, infrastructure, economic strength, and need to make a serious call on cost effective strategy of resource saving and risk/ cost of missing positive patients.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253924", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSInsufficient information on SARS-CoV-2 testing results exists in clinical practice from the United States.\n\nMethodsWe conducted an observational retrospective cohort study using Optum(R) de-identified COVID-19 electronic health records from the United States to characterize patients who received a SARS-CoV-2 viral or antibody test between February 20, 2020 and July 10, 2020. We assessed temporal trends in testing and positivity by demographic and clinical characteristics; evaluated concordance between viral and antibody tests; and identified factors associated with positivity via multivariable logistic regression.\n\nResultsOur study population included 891,754 patients. Overall positivity rate for SARS-CoV-2 was 9% and 12% for viral and antibody tests, respectively. Positivity rate was inversely associated with the number of individuals tested and decreased over time across regions and race/ethnicities. Among patients who received a viral test followed by an antibody test, concordance ranged from 90%-93% depending on the duration between the two tests which is notable given uncertainties related to specific viral and antibody test characteristics. The following factors increased the odds of viral and antibody positivity in multivariable models: male, Hispanic or non-Hispanic Black and Asian, uninsured or Medicaid insurance, Northeast residence, dementia, diabetes, and obesity. Charlson Comorbidity Index was negatively associated with test positivity. We identified symptoms that were positively associated with test positivity, as well as, commonly co-occurring symptoms / conditions. Pediatric patients had reduced odds of a positive viral test, but conversely had increased odds of a positive antibody test.\n\nConclusionsThis study identified sociodemographic and clinical factors associated with SARS-CoV-2 testing and positivity within routine clinical practice from the United States.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Dr. Sally Mahmoud", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" - }, - { - "author_name": "Ms.Esra Ibrahim", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" + "author_name": "Lisa Lindsay", + "author_inst": "Genentech Inc." }, { - "author_name": "Dr. Bhagyashree Thakre", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" + "author_name": "Matthew H Secrest", + "author_inst": "Genentech Inc." }, { - "author_name": "Dr.Juliet George Teddy", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" + "author_name": "Shemra Rizzo", + "author_inst": "Genentech Inc." }, { - "author_name": "Mrs.Preeti Raheja", - "author_inst": "Biogenix Lab G42, Abu Dhabi, UAE" + "author_name": "Daniel Keebler", + "author_inst": "Genentech Inc." }, { - "author_name": "Dr. Subhashini Ganesan", - "author_inst": "G42 Healthcare, UAE" + "author_name": "Fei Yang", + "author_inst": "Roche Diagnostics" }, { - "author_name": "Dr.Walid Zaher", - "author_inst": "G42 Healthcare, UAE" + "author_name": "Larry W Tsai", + "author_inst": "Genentech Inc." } ], "version": "1", @@ -871825,39 +871800,47 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.03.24.436822", - "rel_title": "Arginine Methylation Regulates SARS-CoV-2 Nucleocapsid Protein Function and Viral Replication", + "rel_doi": "10.1101/2021.03.16.21253753", + "rel_title": "Rapid, widespread, and preferential increase of SARS-CoV-2 B.1.1.7 variant in Houston, TX, revealed by 8,857 genome sequences", "rel_date": "2021-03-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.24.436822", - "rel_abs": "Viral proteins are known to be methylated by host protein arginine methyltransferases (PRMTs) playing critical roles during viral infections. Herein, we show that PRMT1 methylates SARS-CoV-2 nucleocapsid (N) protein at residues R95 and R177 within RGG/RG sequences. Arginine methylation of N protein was confirmed by immunoblotting viral proteins extracted from SARS-CoV-2 virions isolated by cell culture. We demonstrate that arginine methylation of N protein is required for its RNA binding capacity, since treatment with a type I PRMT inhibitor (MS023) or substitution of R95K or R177K inhibited interaction with the 5-UTR of the SARS-CoV-2 genomic RNA. We defined the N interactome in HEK293 cells with or without MS023 treatment and identified PRMT1 and many of its RGG/RG substrates including the known interactor, G3BP1, and other components of stress granules (SG). Methylation of N protein at R95 regulates another function namely its property to suppress the formation of SGs. MS023 treatment or R95K substitution blocked N-mediated suppression of SGs. Also, the co-expression of methylarginine reader TDRD3 quenched N-mediated suppression of SGs in a dose-dependent manner. Finally, pre-treatment of VeroE6 cells with MS023 significantly reduced SARS-CoV-2 replication. With type I PRMT inhibitors being in clinical trials for cancer treatment, inhibiting arginine methylation to target the later stages of the viral life cycle such as viral genome packaging and assembly of virions may be an additional therapeutic application of these drugs.", - "rel_num_authors": 5, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.16.21253753", + "rel_abs": "Genetic variants of the SARS-CoV-2 virus have become of great interest worldwide because they have the potential to detrimentally alter the course of the SARS-CoV-2 pandemic, and disease in individual patients. We recently sequenced 20,453 SARS- CoV-2 genomes from patients with COVID-19 disease in metropolitan Houston (population 7 million), dating from March 2020 to early February 2021. We discovered that all major variants of concern or interest are circulating in the region. To follow up on this discovery, we analyzed 8,857 genome sequences from patients in eight Houston Methodist hospitals dispersed throughout the metroplex diagnosed from January 1, 2021 to March 7, 2021. This sample represents 94% of Houston Methodist cases and 4.8% of all reported cases in metropolitan Houston during this period. We discovered rapid, widespread, and preferential increase of the SARS-CoV-2 UK B.1.1.7 throughout the region. The estimated case doubling time in the Houston area is 6.9 days. None of the 648 UK B.1.1.7 samples identified had the E484K change in spike protein that can cause decreased recognition by antibodies.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Ting Cai", - "author_inst": "McGill University/Lady Davis Institute for Medical Research" + "author_name": "James M. Musser", + "author_inst": "Houston Methodist Hospital" }, { - "author_name": "Zhenbao Yu", - "author_inst": "McGill University/Lady Davis Institute for Medical Research" + "author_name": "Randall J. Olsen", + "author_inst": "Houston Methodist Hospital" }, { - "author_name": "Zhen Wang", - "author_inst": "McGill University/Lady Davis Institute for Medical Research" + "author_name": "Paul A. Christensen", + "author_inst": "Houston Methodist Hospital" }, { - "author_name": "Chen Liang", - "author_inst": "McGill University/Lady Davis Institute for Medical Research" + "author_name": "S. Wesley Long", + "author_inst": "Houston Methodist Hospital" + }, + { + "author_name": "Sishir Subedi", + "author_inst": "Houston Methodist Hospital" + }, + { + "author_name": "James J. Davis", + "author_inst": "Argonne National Laboratory" }, { - "author_name": "Stephane Richard", - "author_inst": "McGill University/Lady Davis Institute for Medical Research" + "author_name": "Jimmy Gollihar", + "author_inst": "CCDC Army Research Laboratory-South" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "molecular biology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "pathology" }, { "rel_doi": "10.1101/2021.03.20.21253624", @@ -873393,33 +873376,33 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2021.03.19.21253756", - "rel_title": "Characterizing Post-Acute Sequelae of SARS-CoV-2 Infection across Claims and Electronic Health Record Databases", + "rel_doi": "10.1101/2021.03.17.21253760", + "rel_title": "Chronic diseases: Perceptions about Covid-19 risk and vaccination", "rel_date": "2021-03-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253756", - "rel_abs": "Structured AbstractO_ST_ABSImportanceC_ST_ABSPost-acute sequelae of SARS-CoV-2 infection (PASC) is emerging as a major public health issue.\n\nObjectiveWe characterized the incidence of PASC, or related symptoms and diagnoses, for COVID-19 and influenza patients.\n\nDesignRetrospective cohort study.\n\nSettingOur data sources were the IBM MarketScan Commercial Claims and Encounters (CCAE), Optum Electronic Health Record (EHR) and Columbia University Irving Medical Center (CUIMC) databases that were transformed to the Observational Medical Outcome Partnership (OMOP) Common Data Model (CDM) and were part of the Observational Health Sciences and Informatics (OHDSI) network.\n\nParticipantsThe COVID-19 cohort consisted of patients with a diagnosis of COVID-19 or positive lab test of SARS-CoV-2 after January 1st 2020 with a follow up period of at least 30 days. The influenza cohort consisted of patients with a diagnosis of influenza between October 1, 2018 and May 1, 2019 with a follow up period of at least 30 days.\n\nInterventionInfection with COVID-19 or influenza.\n\nMain Outcomes and MeasuresPost-acute sequelae of SARS-CoV-2 infection (PASC), or related diagnoses, for COVID-19 and influenza patients.\n\nResultsIn aggregate, we characterized the post-acute experience for over 440,000 patients who were diagnosed with COVID-19 or tested positive for SARS-COV-2. The long term sequelae that had a higher incidence in the COVID-19 compared to Influenza cohorts were altered smell or taste, myocarditis, acute kidney injury, dyspnea and alopecia. Additionally, the long term incidences of respiratory illness, musculoskeletal disease, and psychiatric disorders for the COVID-19 population were higher than expected.\n\nConclusions and RelevanceThe long term sequelae of COVID-19 and influenza may be different. Further characterization of PASC on large scale observational healthcare databases is warranted.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.17.21253760", + "rel_abs": "BackgroundCOVID-19 disproportionately affects those with preexisting conditions, but little research has determined whether those with chronic diseases view the pandemic itself differently - and whether there are differences between chronic diseases. We theorized that while individuals with respiratory disease or autoimmune disorders would perceive greater threat from COVID-19 and be more supportive of non-pharmaceutical interventions (NPIs), those with autoimmune disorders would be less likely to support vaccination-based interventions.\n\nMethodsWe conducted a two-wave online survey conducted in February and November 2021 asking respondents their beliefs about COVID-19 risk perception, adoption and support of interventions, willingness to be vaccinated against COVID-19, and reasons for vaccination. Regression analysis was conducted to assess the relationship of respondents reporting a chronic disease and COVID-19 behaviors and attitudes, compared to healthy respondents adjusting for demographic and political factors.\n\nResultsIn the initial survey, individuals reporting a chronic disease had stronger both stronger feelings of risk from COVID-19 as well as preferences for NPIs than healthy controls. The only NPI that was still practiced significantly more compared to healthy controls in the resample was limiting trips outside of the home. Support for community-level NPIs was higher among individuals reporting a chronic disease than healthy controls and remained high among those with respiratory diseases in sample 2. Vaccine acceptance produced more divergent results: those reporting chronic respiratory diseases were 6% more willing to be vaccinated than healthy controls, while we found no significant difference between individuals with autoimmune diseases and healthy controls. Respondents with chronic respiratory disease and those with autoimmune diseases were more likely to want to be vaccinated to protect themselves from COVID-19, and those with an autoimmune disease were more likely to report fear of a bad vaccine reaction as the reason for vaccine hesitancy. In the resample, neither those with respiratory diseases nor autoimmune diseases reported being more willing to receive a booster vaccine than healthy controls.\n\nConclusionsIt is not enough to recognize the importance of health in determining attitudes: nuanced differences between conditions must also be recognized.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Matthew E Spotnitz", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Brianna A Smith", + "author_inst": "United States Naval Academy" }, { - "author_name": "George Hripcsak", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Emily E Ricotta", + "author_inst": "National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Patrick B Ryan", - "author_inst": "Janssen Research and Development" + "author_name": "Jennifer L Kwan", + "author_inst": "National Institute of Allergy and Infectious Diseases, National Institutes of Health" }, { - "author_name": "Karthik Natarajan", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Nicholas G Evans", + "author_inst": "University of Massachusetts Lowell" } ], "version": "1", - "license": "cc_by", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -875587,119 +875570,107 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.23.436564", - "rel_title": "Protein-primed RNA synthesis in SARS-CoVs and structural basis for inhibition by AT-527", + "rel_doi": "10.1101/2021.03.22.436476", + "rel_title": "The Dual-Antigen Ad5 COVID-19 Vaccine Delivered as an Intranasal Plus Subcutaneous Prime Elicits Th1 Dominant T-Cell and Humoral Responses in CD-1 Mice", "rel_date": "2021-03-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.23.436564", - "rel_abs": "How viruses from the Coronaviridae family initiate viral RNA synthesis is unknown. Here we show that the SARS-CoV-1 and -2 Nidovirus RdRp-Associated Nucleotidyltransferase (NiRAN) domain on nsp12 uridylates the viral cofactor nsp8, forming a UMP-Nsp8 covalent intermediate that subsequently primes RNA synthesis from a poly(A) template; a protein-priming mechanism reminiscent of Picornaviridae enzymes. In parallel, the RdRp active site of nsp12 synthesizes a pppGpU primer, which primes (-)ssRNA synthesis at the precise genome-poly(A) junction. The guanosine analogue 5-triphosphate AT-9010 (prodrug: AT-527) tightly binds to the NiRAN and inhibits both nsp8-labeling and the initiation of RNA synthesis. A 2.98 [A] resolution Cryo-EM structure of the SARS-CoV-2 nsp12-nsp7-(nsp8)2 /RNA/NTP quaternary complex shows AT-9010 simultaneously binds to both NiRAN and RdRp active site of nsp12, blocking their respective activities. AT-527 is currently in phase II clinical trials, and is a potent inhibitor of SARS-CoV-1 and -2, representing a promising drug for COVID-19 treatment.", - "rel_num_authors": 25, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.22.436476", + "rel_abs": "In response to the need for an efficacious, thermally-stable COVID-19 vaccine that can elicit both humoral and cell-mediated T-cell responses, we have developed a dual-antigen human adenovirus serotype 5 (hAd5) COVID-19 vaccine in formulations suitable for subcutaneous (SC), intranasal (IN), or oral delivery. The vaccine expresses both the SARS-CoV-2 spike (S) and nucleocapsid (N) proteins using an hAd5 platform with E1, E2b, and E3 sequences deleted (hAd5[E1-, E2b-, E3-]) that is effective even in the presence of hAd5 immunity. In the vaccine, S is modified (S-Fusion) for enhanced cell-surface display to elicit humoral responses and N is modified with an Enhanced T-cell Stimulation Domain (N-ETSD) to direct N to the endosomal/lysosomal pathway to increase MHC I and II presentation. Initial studies using subcutaneous (SC) prime and SC boost vaccination of CD-1 mice demonstrated that the hAd5 S-Fusion + N-ETSD vaccine elicits T-helper cell 1 (Th1) dominant T-cell and humoral responses to both S and N. We then compared SC to IN prime vaccination with either an SC or IN boost post-SC prime and an IN boost after IN prime. These studies reveal that IN prime/IN boost is as effective at generating Th1 dominant humoral responses to both S and N as the other combinations, but that the SC prime with either an IN or SC boost elicits greater T cell responses. In a third study to assess the power of the two routes of delivery when used together, we used a combined SC plus IN prime with or without a boost and found the combined prime alone to be as effective as the combined prime with either an SC or IN boost in generating both humoral and T-cell responses. The findings here in CD-1 mice demonstrate that combined SC and IN prime-only delivery has the potential to provide broad immunity - including mucosal immunity - against SARS-CoV-2 and supports further testing of this delivery approach in additional animal models and clinical trials.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Ashleigh Shannon", - "author_inst": "AFMB-CNRS-AMU" - }, - { - "author_name": "Veronique Fattorini", - "author_inst": "AFMB-CNRS-AMU" - }, - { - "author_name": "Bhawna Sama", - "author_inst": "AFMB-CNRS-AMU" - }, - { - "author_name": "Barbara Selisko", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Adrian Rice", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Mikael Feracci", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Mohit Verma", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Camille Falcou", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Annie Shin", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Pierre Gauffre", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Lise Zakin", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Priscila El Kazzi", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Peter Sieling", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Etienne Decroly", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Shiho Tanaka", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Nadia Rabah", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Joseph Balint", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Karine Toulon", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Kyle Dinkins", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Cecilia Eydoux", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Helty Adisetiyo", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Jean-Claude Guillemot", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Brett Morimoto", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Mathieu Noel", - "author_inst": "CNRS" + "author_name": "Wendy Higashide", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Francoise Debart", - "author_inst": "CNRS" + "author_name": "Justin Taft", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Jean-Jacques Vasseur", - "author_inst": "CNRS" + "author_name": "Roosheel Sandeep Patel", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Adel Moussa", - "author_inst": "ATEA Pharmaceuticals" + "author_name": "Sofija Buta", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Steven Good", - "author_inst": "ATEA Pharmaceuticals" + "author_name": "Marta Martin-Fernandez", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Kai Lin", - "author_inst": "ATEA Pharmaceuticals" + "author_name": "Dusan Bogunovic", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Jean-Pierre Sommadossi", - "author_inst": "ATEA Pharmaceuticals" + "author_name": "Patricia R Spilman", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Yingxiao Zhu", - "author_inst": "WuxiBiortus" + "author_name": "Elizabeth R Gabitzsch", + "author_inst": "ImmunityBio, Inc" }, { - "author_name": "Xiaodong Yan", - "author_inst": "WuxiBiortus" + "author_name": "Jeffrey T Safrit", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Hui Shi", - "author_inst": "WuxiBiortus" + "author_name": "Shahrooz Rabizadeh", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Francois Ferron", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Kayvan Niazi", + "author_inst": "ImmunityBio, Inc." }, { - "author_name": "Bruno Canard", - "author_inst": "AFMB-CNRS-AMU" + "author_name": "Patrick Soon-Shiong", + "author_inst": "ImmunityBio, Inc." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "biochemistry" + "category": "immunology" }, { "rel_doi": "10.1101/2021.03.23.436611", @@ -877457,43 +877428,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.21.21253754", - "rel_title": "Role of Combining Anticoagulant and Antiplatelet Agents in COVID-19 Treatment: A Rapid Review", + "rel_doi": "10.1101/2021.03.15.435423", + "rel_title": "Network medicine links SARS-CoV-2/COVID-19 infection to brain microvascular injury and neuroinflammation in dementia-like cognitive impairment", "rel_date": "2021-03-22", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.21.21253754", - "rel_abs": "Although primarily affecting the respiratory system, COVID-19 causes multiple organ damage. One of its grave consequences is a prothrombotic state that manifests as thrombotic, microthrombotic, and thromboembolic events.Therefore, understanding the effect of antiplatelet and anticoagulation therapy in the context of COVID-19 treatment is important. The aim of this rapid review is to highlight the role of thrombosis in COVID-19 and provide new insights on the use of antithrombotic therapy in its management. A rapid systematic review was performed using preferred reporting items for systematic reviews. Papers published in English on antithrombotic agent use and COVID-19 complications were eligible. Results showed that the use of anticoagulants increased survival and reduced thromboembolic events in patients. However, despite the use of anticoagulants, patients still suffered thrombotic events likely due to heparin resistance. Data on antiplatelet use in combination with anticoagulants in the setting of COVID-19 is quite scarce. Current side effects of anticoagulation therapy emphasize the need to update treatment guidelines. In this rapid review, we address a possible modulatory role of antiplatelet and anticoagulant combination against COVID{square}19 pathogenesis. This combination may be an effective form of adjuvant therapy against COVID{square}19 infection. However, further studies are needed to elucidate potential risks and benefits associated with this combination.\n\nIt was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.15.435423", + "rel_abs": "BackgroundDementia-like cognitive impairment is an increasingly reported complication of SARS-CoV-2 infection. However, the underlying mechanisms responsible for this complication remain unclear. A better understanding of causative processes by which COVID-19 may lead to cognitive impairment is essential for developing preventive interventions.\n\nMethodsIn this study, we conducted a network-based, multimodal genomics comparison of COVID-19 and neurologic complications. We constructed the SARS-CoV-2 virus-host interactome from protein-protein interaction assay and CRISPR-Cas9 based genetic assay results, and compared network-based relationships therein with those of known neurological manifestations using network proximity measures. We also investigated the transcriptomic profiles (including single-cell/nuclei RNA-sequencing) of Alzheimers disease (AD) marker genes from patients infected with COVID-19, as well as the prevalence of SARS-CoV-2 entry factors in the brains of AD patients not infected with SARS-CoV-2.\n\nResultsWe found significant network-based relationships between COVID-19 and neuroinflammation and brain microvascular injury pathways and processes which are implicated in AD. We also detected aberrant expression of AD biomarkers in the cerebrospinal fluid and blood of patients with COVID-19. While transcriptomic analyses showed relatively low expression of SARS-CoV-2 entry factors in human brain, neuroinflammatory changes were pronounced. In addition, single-nucleus transcriptomic analyses showed that expression of SARS-CoV-2 host factors (BSG and FURIN) and antiviral defense genes (LY6E, IFITM2, IFITM3, and IFNAR1) was significantly elevated in brain endothelial cells of AD patients and healthy controls relative to neurons and other cell types, suggesting a possible role for brain microvascular injury in COVID-19-mediated cognitive impairment. Notably, individuals with the AD risk allele APOE E4/E4 displayed reduced levels of antiviral defense genes compared to APOE E3/E3 individuals.\n\nConclusionOur results suggest significant mechanistic overlap between AD and COVID-19, strongly centered on neuroinflammation and microvascular injury. These results help improve our understanding of COVID-19-associated neurological manifestations and provide guidance for future development of preventive or treatment interventions.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Kamal Matli", - "author_inst": "LAUMCRH" + "author_name": "Yadi Zhou", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Raymond Farah", - "author_inst": "Lebanese University" + "author_name": "Jielin Xu", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Mario Maalouf", - "author_inst": "LAU" + "author_name": "Yuan Hou", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Christy Costanian", - "author_inst": "LAU" + "author_name": "James B. Leverenz", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Nibal Chamoun", - "author_inst": "LAU" + "author_name": "Asha Kallianpur", + "author_inst": "Cleveland Clinic" }, { - "author_name": "Georges Ghanem", - "author_inst": "LAUMCRH" + "author_name": "Reena Mehra", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Yunlong Liu", + "author_inst": "Indiana University" + }, + { + "author_name": "Haiyuan Yu", + "author_inst": "Cornell University" + }, + { + "author_name": "Andrew A. Pieper", + "author_inst": "Case Western Reserve University" + }, + { + "author_name": "Lara Jehi", + "author_inst": "Cleveland Clinic" + }, + { + "author_name": "Feixiong Cheng", + "author_inst": "Cleveland Clinic" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "cardiovascular medicine" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "systems biology" }, { "rel_doi": "10.1101/2021.03.22.435957", @@ -879543,43 +879534,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.18.21253887", - "rel_title": "Effect of Increased Alcohol Consumption During COVID-19 Pandemic on Alcohol-related Liver Disease: A Modelling Study", + "rel_doi": "10.1101/2021.03.18.21253902", + "rel_title": "Smoking and Vaping Among a National Sample of U.S. Adults During the COVID-19 Pandemic", "rel_date": "2021-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.18.21253887", - "rel_abs": "ObjectivesThe burden of alcohol-related liver disease (ALD) is surging in the US. There is evidence that alcohol consumption increased during the early periods of the coronavirus disease-2019 (COVID-19) pandemic. We describe the impact of increased alcohol consumption on alcohol-related liver disease.\n\nDesignMicrosimulation model\n\nSettingModel parameters estimated from publicly available data sources, including national surveys on drug and alcohol use and published studies informing the impact of alcohol consumption on ALD severity.\n\nParticipantsUS residents\n\nMethodsWe extended a previously validated microsimulation model that estimated the short- and long-term effect of increased drinking during the COVID-19 pandemic in individuals in the US born between 1950-2012. We modelled short- and long-term outcomes of current drinking patterns during COVID-19 (status quo) using survey data of changes in alcohol consumption in a nationally representative sample between February and April 2020. We compared these outcomes with a counter-factual scenario wherein no COVID-19 occurs, and drinking patterns do not change. Reported outcomes are for individuals aged 18-65.\n\nMain outcome measuresALD-related deaths inclusive of HCC mortality, the prevalence and incidence of decompensated cirrhosis and hepatocellular carcinoma, and disability-adjusted life-years (DALYs)\n\nResultsIncreases in alcohol consumption during 2020 due to the COVID-19 pandemic are estimated to result in to 8,200 [95% UI 7,700 - 8,700] additional ALD-related deaths (1% increase compared with the counter-factual scenario), 17,100 [95% UI 16,100 - 18,200] cases of decompensated cirrhosis (2% increase) and 1,100 [95% UI 1,100 - 1,200] cases of HCC (1% increase) between 2020 and 2040. Between 2020 and 2023, alcohol consumption changes due to COVID-19 will lead to 100 [100-200] additional deaths and 2,200 [2,200-2,300] additional decompensations in patients suffering from alcohol-related liver disease.\n\nConclusionsA short-term increase in alcohol consumption during the COVID-19 pandemic can substantially increase long-term ALD-related morbidity and mortality. Our findings highlight the need for individuals and policymakers to make informed decisions to mitigate the impact of high-risk alcohol drinking in the US.\n\nSummary Box\"O_ST_ABSWhat is already known on this topicC_ST_ABSO_LIThe impact of an increase in alcohol consumption during coronavirus disease 2019 (COVID-19) on drinking trajectory changes and alcohol-related liver diseases is not known.\nC_LIO_LIStudies have reported increases in hospital admissions for alcohol-related liver disease or pancreatitis potentially related to COVID-19, increases in alcohol consumption, and exacerbation of pre-existing liver injury, though limited evidence exists for the long-term effect of increased drinking on alcohol-related liver cirrhosis and liver cancer in the USA.\nC_LI\n\nAdded value of this studyO_LIOur study provides new data on liver disease morbidity and mortality associated with increased consumption of alcohol during the COVID-19 pandemic.\nC_LIO_LIOur study suggests that drinking changes associated with the COVID-19 pandemic it is expected to lead to increases in both mortality and morbidity in the long term. to 8,200 additional ALD-related deaths, 17,100 cases of decompensated cirrhosis, and 1,100 cases of HCC between 2020 and 2040 2\nC_LI", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.18.21253902", + "rel_abs": "IntroductionWith concerns about cigarette smoking being a risk factor for severe disease from COVID-19, understanding nicotine and tobacco use patterns is important for preventive efforts. We aimed to understand changes in product use behaviors among U.S. adult combustible cigarette smokers and electronic cigarette (e-cigarette) users.\n\nMethodsIn August 2020, we conducted a cross-sectional survey of a nationally-representative sample of adults age >18 in NORCs AmeriSpeak Panel who reported past 6-month use of combustible cigarettes or e-cigarettes. Multivariable logistic regression assessed factors associated with increased product use and quit attempts since hearing about COVID-19.\n\nResults1024 past 6-month cigarette smokers and/or e-cigarette users were surveyed. Among cigarette smokers, 45% reported no change in cigarette smoking and 33% increased cigarette smoking since hearing about COVID-19. Higher stress was associated with increased cigarette smoking. Among e-cigarette users, 41% reported no change in and 23% reported increasing e-cigarette use. 26% of cigarette smokers and 41% of e-cigarette users tried to quit because of COVID-19. Higher perceived risk of COVID-19 was associated with attempts to quit combustible cigarettes (AOR 2.37, 95% CI 1.59-3.55) and e-cigarettes (AOR 3.14, 1.73-5.70).\n\nConclusionsCigarette and e-cigarette use patterns varied in response to the COVID-19 pandemic. Most cigarette smokers and e-cigarette users perceived product use as increasing COVID-19-related health risks, and this was associated with attempts to quit. Others, especially those reporting higher stress, increased product use. Proactive provision of cessation support to smokers and e-cigarette users may help mitigate stress-related increases in product use during the COVID-19 pandemic.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jovan Julien", - "author_inst": "Georgia Institute of Technology, Massachusetts General Hospital" - }, - { - "author_name": "Turgay Ayer", - "author_inst": "Department of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA" - }, - { - "author_name": "Elliot Tapper", - "author_inst": "Division of Gastroenterology and Hepatology, University of Michigan, Ann Arbor, MI" + "author_name": "Sara Kalkhoran", + "author_inst": "Tobacco Research and Treatment Center, Massachusetts General Hospital and Harvard Medical School" }, { - "author_name": "Carolina Barbosa", - "author_inst": "RTI International, Research Triangle Park, NC" + "author_name": "Douglas E Levy", + "author_inst": "Tobacco Research and Treatment Center and Mongan Institute, Massachusetts General Hospital and Harvard Medical School" }, { - "author_name": "William Dowd", - "author_inst": "RTI International, Research Triangle Park, NC" - }, - { - "author_name": "Jagpreet Chhatwal", - "author_inst": "Harvard Medical School, Massachusetts General Hospital" + "author_name": "Nancy A Rigotti", + "author_inst": "Tobacco Research and Treatment Center, Massachusetts General Hospital and Harvard Medical School" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "gastroenterology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.03.18.21253891", @@ -881953,81 +881932,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.19.21253889", - "rel_title": "Risk of reinfection after seroconversion to SARS-CoV-2: A population-based propensity-score matched cohort study", + "rel_doi": "10.1101/2021.03.17.21253853", + "rel_title": "Modelling the impact of rapid tests, tracing and distancing in lower-income countries suggest optimal policies varies with rural-urban settings", "rel_date": "2021-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.19.21253889", - "rel_abs": "ImportanceSerological assays detecting specific IgG antibodies generated against the Spike protein following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection are being widely deployed in research studies and clinical practice. However, the duration and the effectiveness of the protection conferred by the immune response against future infection remains to be assessed in a large population.\n\nObjectiveTo estimate the incidence of newly acquired SARS-CoV-2 infections in seropositive individuals from a population-based sample as compared to seronegative controls.\n\nDesignRetrospective longitudinal propensity-score matched cohort study.\n\nSettingA seroprevalence survey including a population-based representative sample of the population from the canton of Geneva (Switzerland) was conducted between April and June 2020, immediately after the first pandemic wave. Each individual included in the seroprevalence survey was linked to a state centralized registry compiling virologically confirmed SARS-CoV-2 infections since the beginning of the pandemic.\n\nParticipantsParticipants aged twelve years old and over, who developed anti-spike IgG antibodies were matched one-to-two to seronegative controls, using a propensity-score including age, gender, immunodeficiency, body mass index, smoking status and education level.\n\nExposureSARS-CoV-2 seropositivity.\n\nMain outcomes and measuresOur primary outcome was virologically confirmed SARS-CoV-2 infections which occurred from serological status assessment in April-June 2020 to the end of the second pandemic wave (January 2021). Additionally, incidence of infections, rate of testing and proportion of positive tests were analysed.\n\nResultsAmong 8344 serosurvey participants, 498 seropositive individuals were selected and matched with 996 seronegative controls. After a mean follow-up of 35.6 (Standard Deviation, SD: 3.2) weeks, 7 out of 498 (1.4%) seropositive subjects had a positive SARS-CoV-2 test, of which 5 (1.0%) were considered as reinfections. By contrast, infection rate was significantly higher in seronegative individuals (15.5%, 154/996) during a similar mean follow-up of 34.7 (SD 3.2) weeks, corresponding to a 94% (95%CI 86% to 98%, P<0.001) reduction in the hazard of having a positive SARS-CoV-2 test for seropositive subjects.\n\nConclusions and relevanceSeroconversion after SARS-CoV-2 infection confers protection to successive viral contamination lasting at least 8 months. These findings could help global health authorities establishing priority for vaccine allocation.\n\nKey points\n\nQuestionDo SARS-CoV-2 antibodies confer protection against future infection?\n\nFindingsIn this retrospective matched cohort study nested in a representative sample of the general population of Geneva, Switzerland, we observed a 94% reduction in the hazard of being infected among participants with antibodies against SARS-CoV-2, when compared to seronegative controls, >8 months after initial serology assessment.\n\nMeaningSeroconversion to SARS-CoV-2 is associated with a large and sustained protection against reinfection.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.17.21253853", + "rel_abs": "Low- and middle-income countries (LMICs) remain of high potential for hotspots for COVID-19 deaths and emerging variants given the inequality of vaccine distribution and their vulnerable healthcare systems. We aim to evaluate containment strategies that are sustainable and effective for LMICs. We constructed synthetic populations with varying contact and household structures to capture LMIC demographic characteristics that vary across communities. Using an agent- based model, we explored the optimal containment strategies for rural and urban communities by designing and simulating setting-specific strategies that deploy rapid diagnostic tests, symptom screening, contact tracing and physical distancing. In low-density rural communities, we found implementing either high quality (sensitivity > 50%) antigen rapid diagnostic tests or moderate physical distancing could contain the transmission. In urban communities, we demonstrated that both physical distancing and case finding are essential for containing COVID-19 (average infection rate < 10%). In high density communities that resemble slums and squatter settlements, physical distancing is less effective compared to rural and urban communities. Lastly, we demonstrated contact tracing is essential for effective containment. Our findings suggested that rapid diagnostic tests could be prioritised for control and monitor COVID-19 transmission and highlighted that contact survey data could guide strategy design to save resources for LMICs. An accompanying open source R package is available for simulating COVID-19 transmission based on contact network models.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Antonio Leidi", - "author_inst": "Geneva University Hospitals" - }, - { - "author_name": "Flora Koegler", - "author_inst": "Geneva University Hospitals" - }, - { - "author_name": "Roxane Dumont", - "author_inst": "Geneva University Hospitals" - }, - { - "author_name": "Richard Dubos", - "author_inst": "Geneva University Hospitals" - }, - { - "author_name": "Maria-Eugenia Zaballa", - "author_inst": "Geneva University Hospitals" - }, - { - "author_name": "Giovanni Piumatti", - "author_inst": "Geneva University Hospitals" - }, - { - "author_name": "Matteo Coen", - "author_inst": "Geneva University Hospitals" - }, - { - "author_name": "Amandine Berner", - "author_inst": "Geneva University Hospitals" - }, - { - "author_name": "Pauline Darbellay Farhoumand", - "author_inst": "Geneva University Hospitals" - }, - { - "author_name": "Pauline Vetter", - "author_inst": "Geneva University Hospitals" + "author_name": "Xilin Jiang", + "author_inst": "University of Oxford" }, { - "author_name": "Nicolas Vuilleumier", - "author_inst": "Geneva University Hospitals" + "author_name": "Wenfeng Gong", + "author_inst": "Bill & Melinda Gates Foundation" }, { - "author_name": "Laurent Kaiser", - "author_inst": "University of Geneva Hospitals" + "author_name": "Zlatina Dobreva", + "author_inst": "Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK" }, { - "author_name": "Delphine Courvoisier", - "author_inst": "General Directorate of Health, Geneva, Switzerland" + "author_name": "Ya Gao", + "author_inst": "Department of International Health, Johns Hopkins University" }, { - "author_name": "Andrew Azman", - "author_inst": "Geneva University Hospitals" + "author_name": "Matthew Quaife", + "author_inst": "Faculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK" }, { - "author_name": "Idris Guessous", - "author_inst": "Geneva University Hospitals" + "author_name": "Christophe Fraser", + "author_inst": "University of Oxford" }, { - "author_name": "Silvia Stringhini", - "author_inst": "Geneva University Hospitals" + "author_name": "Chris Holmes", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -883551,59 +883494,39 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.03.19.435740", - "rel_title": "The inhibitory effects of toothpaste and mouthwash ingredients on the interaction between the SARS-CoV-2 spike protein and ACE2, and the protease activity of TMPRSS2, in vitro", + "rel_doi": "10.1101/2021.03.19.435959", + "rel_title": "Common dandelion (Taraxacum officinale) efficiently blocks the interaction between ACE2 cell surface receptor and SARS-CoV-2 spike protein D614, mutants D614G, N501Y, K417N and E484K in vitro", "rel_date": "2021-03-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.19.435740", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters host cells when the viral spike protein is cleaved by transmembrane protease serine 2 (TMPRSS2) after binding to the host angiotensin-converting enzyme 2 (ACE2). Since ACE2 and TMPRSS2 are expressed in the mucosa of the tongue and gingiva, the oral cavity seems like it is an entry point for SARS-CoV-2. Daily oral care using mouthwash seems to play an important role in preventing SARS-CoV-2 infection. However, the relationship between daily oral care and the mechanisms of virus entry into host cells is unclear. In this study, we evaluated the inhibitory effects of ingredients that are generally contained in toothpaste and mouthwash on the interaction between the spike protein and ACE2 and on the serine protease activity of TMPRSS2 using an enzyme-linked immunosorbent assay and in vitro enzyme assay, respectively. Both assays detected inhibitory effects of sodium tetradecene sulfonate, sodium N-lauroyl-N-methyltaurate, sodium N-lauroylsarcosinate, sodium dodecyl sulfate, and copper gluconate. Molecular docking simulations suggested that these ingredients could bind to the inhibitor-binding site of ACE2. In addition, tranexamic acid and 6-aminohexanoic acid, which act as serine protease inhibitors, exerted inhibitory effects on TMPRSS2 protease activity. Further experimental and clinical studies are needed to further elucidate these mechanisms. Our findings support the possibility that toothpaste and mouthwash contain ingredients that inhibit SARS-CoV-2 infection.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.19.435959", + "rel_abs": "On 11th March 2020, coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, was declared as a global pandemic by the World Health Organization (WHO). To date, there are rapidly spreading new \"variants of concern\" of SARS-CoV-2, the United Kingdom (B.1.1.7), the South African (B.1.351) or Brasilian (P.1) variant. All of them contain multiple mutations in the ACE2 receptor recognition site of the spike protein, compared to the original Wuhan sequence, which is of great concern, because of their potential for immune escape. Here we report on the efficacy of common dandelion (Taraxacum officinale) to block protein-protein interaction of spike S1 to the human ACE2 cell surface receptor. This could be shown for the original spike D614, but also for its mutant forms (D614G, N501Y, and mix of K417N, E484K, N501Y) in human HEK293-hACE2 kidney and A549-hACE2-TMPRSS2 lung cells. High molecular weight compounds in the water-based extract account for this effect. Infection of the lung cells using SARS-CoV-2 spike pseudotyped lentivirus particles was efficiently prevented by the extract and so was virus-triggered pro-inflammatory interleukin 6 secretion. Modern herbal monographs consider the usage of this medicinal plant as safe. Thus, the in vitro results reported here should encourage further research on the clinical relevance and applicability of the extract as prevention strategy for SARS-CoV-2 infection.\n\nSignificance statementSARS-CoV-2 is steadily mutating during continuous transmission among humans. This might eventually lead the virus into evading existing therapeutic and prophylactic approaches aimed at the viral spike. We found effective inhibition of protein-protein interaction between the human virus cell entry receptor ACE2 and SARS-CoV-2 spike, including five relevant mutations, by water-based common dandelion (Taraxacum officinale) extracts. This was shown in vitro using human kidney (HEK293) and lung (A549) cells, overexpressing the ACE2 and ACE2/TMPRSS2 protein, respectively. Infection of the lung cells using SARS-CoV-2 pseudotyped lentivirus was efficiently prevented by the extract. The results deserve more in-depth analysis of dandelions effectiveness in SARS-CoV-2 prevention and now require confirmatory clinical evidence.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Riho Tateyama-Makino", - "author_inst": "Research & Development Headquarters, Lion Corporation, Tokyo, Japan" - }, - { - "author_name": "Mari Abe-Yutori", - "author_inst": "Research & Development Headquarters, Lion Corporation, Tokyo, Japan" - }, - { - "author_name": "Taku Iwamoto", - "author_inst": "Research & Development Headquarters, Lion Corporation, Tokyo, Japan" - }, - { - "author_name": "Kota Tsutsumi", - "author_inst": "Research & Development Headquarters, Lion Corporation, Tokyo, Japan" - }, - { - "author_name": "Motonori Tsuji", - "author_inst": "Institute of Molecular Function, Saitama, Japan" - }, - { - "author_name": "Satoru Morishita", - "author_inst": "Research & Development Headquarters, Lion Corporation, Tokyo, Japan" + "author_name": "Hoai Thi Thu Tran", + "author_inst": "University Medical Center Freiburg" }, { - "author_name": "Kei Kurita", - "author_inst": "Research & Development Headquarters, Lion Corporation, Tokyo, Japan" + "author_name": "Nguyen Phan Khoi Le", + "author_inst": "University Medical Center Freiburg" }, { - "author_name": "Yukio Yamamoto", - "author_inst": "Research & Development Headquarters, Lion Corporation, Tokyo, Japan" + "author_name": "Michael Gigl", + "author_inst": "Technical University of Munich" }, { - "author_name": "Eiji Nishinaga", - "author_inst": "Research & Development Headquarters, Lion Corporation, Tokyo, Japan" + "author_name": "Corinna Dawid", + "author_inst": "Technical University Munich" }, { - "author_name": "Keiichi Tsukinoki", - "author_inst": "Division of Environmental Pathology, Department of Oral Science, Kanagawa Dental University, Kanagawa, Japan" + "author_name": "Evelyn Lamy", + "author_inst": "University Medical Center Freiburg" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "molecular biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.03.19.436166", @@ -885377,57 +885300,57 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2021.03.15.21253581", - "rel_title": "Tocilizumab Effect in COVID-19 Hospitalized Patients: A Systematic Review and Meta-Analysis of Randomized Control Trials", + "rel_doi": "10.1101/2021.03.15.21253586", + "rel_title": "Rapid base-specific calling of SARS-CoV-2 variants of concern using combined RT-PCR melting curve screening and SIRPH technology", "rel_date": "2021-03-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253581", - "rel_abs": "Since the emergence of the first cases of COVID-19 viral pneumonia late 2019 several studies evaluated the benefits of different treatment modalities. Early in the pandemic, the interleukin 6 (IL-6) receptor antibody Tocilizumab was considered in view of the cytokine release syndrome associated with COVID-19 infection. Several early observational studies showed beneficial effect of treatment with Tocilizumab on mortality, however, results from well-designed randomized clinical trials (RCT) were contradicting.\n\nObjectivesTo perform a systematic literature review and meta-analysis of RCTs utilizing Tocilizumab in the treatment of COVID-19 pneumonia, with in-hospital mortality as a primary objective, while secondary objectives included composite outcome of mortality, intubation, or ICU admission, another secondary outcome was super added infection.\n\nMethodThis was a random effects model (DerSimonian and Laird) model of relative risk (RR), along with corresponding 95% confidence intervals, p values, and forest plots of both primary and secondary outcomes. A fixed effect sensitivity test was performed for the primary outcome, in addition to subgroup and meta-regression analyses with predefined criteria.\n\nResultsThe primary outcome of mortality showed statistically insignificant reduction of mortality with Tocilizumab (RR = 0.9, 95% CI: 0.8 - 1.01; p = 0.09) although with an unmistakable apparent clinical benefit. There was a significant reduction in the RR of the secondary composite outcome (RR = 0.83, 95% CI: 0.76 - 0.9; p < 0.001), and no difference between groups in super-added infection (RR = 0.77, 95% CI: 0.51 - 1.19; p = 0.24). Treatment protocol allowing a second dose was the only significant predictor of improved mortality in the meta-regression analysis. Certainty of evidence was reduced to moderate for the primary outcome and the secondary outcome of clinical deterioration, while it was reduced to low for the secondary outcome of super-added infection.\n\nConclusionModerate certainty of evidence suggest no statistically significant improvement of 28-30 day all-cause mortality of hospitalized COVID-19 patients treated with TCZ, although there may be clinically important value. Moderate certainty of evidence suggest lowered relative risk of a composite outcome of death or clinical deterioration, while, low grade evidence indicate no increase in the risk of super-added infection associated with TCZ treatment. A protocol allowing two doses of TCZ shows evidence of improved mortality as compared to a strictly single dose protocol.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253586", + "rel_abs": "The emergence of novel variants of concern of SARS-CoV-2 demands a fast and reliable detection of such variants in local populations. Here we present a cost-efficient and fast workflow combining a pre-screening of SARS-CoV-2 positive samples using RT-PCR melting curve analysis with multiplexed IP-RP-HPLC-based single nucleotide primer extensions (SIRPH). The entire workflow from positive SARS-CoV-2 testing to base-specific identification of variants requires about 24 h. We applied the sensitive method to monitor the local VOC outbreaks in a few hundred positive samples collected in a confined region of Germany.", "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Waleed Tharwat Aletreby", - "author_inst": "King Saud Medical City" + "author_name": "Sascha Tierling", + "author_inst": "Saarland University" }, { - "author_name": "Basheer Abdulrahman", - "author_inst": "King Saud Medical City" + "author_name": "Kathrin Kattler", + "author_inst": "Saarland University" }, { - "author_name": "Ahmed Fouad Mady", - "author_inst": "King Saud Medical City. Faculty of Medicine Tanta University." + "author_name": "Markus Vogelgesang", + "author_inst": "Saarland University Medical Center" }, { - "author_name": "Alfateh Mohammed Noor", - "author_inst": "King Saud Medical City" + "author_name": "Thorsten Pfuhl", + "author_inst": "Saarland University Medical Center" }, { - "author_name": "Mohammed H Lhmdi", - "author_inst": "King Saud Medical City" + "author_name": "Stefan Lohse", + "author_inst": "Saarland University Medical Center" }, { - "author_name": "Fahad Faqihi", - "author_inst": "King Saud Medical City" + "author_name": "Christina Lo Porto", + "author_inst": "Saarland University" }, { - "author_name": "Abdulrahman M Alharthy", - "author_inst": "King Saud Medical City" + "author_name": "Beate Schmitt", + "author_inst": "Saarland University" }, { - "author_name": "Mohammed A Al-Odat", - "author_inst": "King Saud Medical City" + "author_name": "Abdulrahman Salhab", + "author_inst": "Saarland University" }, { - "author_name": "Dimitrios Karakitsos", - "author_inst": "King Saud Medical City, Critical Care Department, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA. \tDepartment of Medicine, Sou" + "author_name": "Sigrun Smola", + "author_inst": "Saarland University Medical Center" }, { - "author_name": "Ziad Memish", - "author_inst": "King saud Medical City, \tHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA. \tCollege of Medicine, Alfaisa" + "author_name": "Joern Walter", + "author_inst": "Saarland University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -887399,47 +887322,51 @@ "category": "oncology" }, { - "rel_doi": "10.1101/2021.03.15.21253598", - "rel_title": "U.S. adolescents' mental health and COVID-19-related changes in technology use, Fall 2020", - "rel_date": "2021-03-17", + "rel_doi": "10.1101/2021.03.15.21253574", + "rel_title": "Understanding SARS-CoV-2 Infection and Dynamics with Long Term Wastewater based Epidemiological Surveillance", + "rel_date": "2021-03-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253598", - "rel_abs": "Preliminary reports suggest that during COVID-19, adolescents mental health has worsened while technology and social media use has increased. Much data derives from early in the pandemic, when schools were uniformly remote and personal/family stressors related to the pandemic were limited. This cross-sectional study, conducted during Fall 2020, examines the correlation between mental wellbeing and COVID-19-related changes in technology use, along with influence of COVID-19-related stressors, school status (in-person versus remote), and social media use for coping purposes, among 978 U.S. adolescents. Results suggest self-reported daily social media and technology use increased significantly from prior to COVID-19 through Fall 2020. Increased social media use was significantly associated with higher levels of anxiety and depressive symptoms regardless of other theoretical moderators or confounders of mental health (e.g., demographics, school status, importance of technology, COVID-19-related stress). Despite literature suggesting that remote learning may result in adverse mental health outcomes, we did not find local school reopening to be associated with current depressive/anxiety symptoms, nor with COVID-19-related increases in technology use. Self-reported use of social media for coping purposes moderated the association between increased social media use and mental health symptoms; in other words, some social media use may have positive effects. Although much prior research has focused on social media use as a marker of stress, we also found that increased video gaming and TV/movie watching were also associated with internalizing symptoms, in accordance with others' work. Future research should explore in more granular detail what, if any, social media and technology use is protective during a pandemic, and for whom, to help tailor prevention efforts.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.15.21253574", + "rel_abs": "Wastewater-based epidemiology (WBE) of SARS-CoV-2 emerged as an advantageous method to study the infection dynamics at substantial population level. A temporal glimpse at sewage viral genome helps as diagnostic tool to understand the viral spread at community level. In this study, for the long-term epidemiological surveillance, we monitored the SARS-CoV-2 genetic material in domestic sewage by adopting the longitudinal sampling to represent a selected community ([~]1.8 lakhs population which occupies 1.79% of the total population of Hyderabad city) to understand the dynamics of infection. Dynamics and spread of COVID-19 outbreak within the selected community were achieved by studying the longitudinal sampling for a specific period of time. WBE also promotes clinical scrutiny along with disease detection and management, in contrast to an advance warning signal to anticipate outbreaks.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Taylor A Burke", - "author_inst": "Alpert Medical School of Brown University" + "author_name": "Athmakuri Tharak Jr.", + "author_inst": "CSIR-Indian Institute of Chemical Technology (CSIR-IICT)" }, { - "author_name": "Emily R Kutok", - "author_inst": "Alpert Medical School of Brown University" + "author_name": "Harishankar Kopperi Jr.", + "author_inst": "CSIR-Indian Institute of Chemical Technology (CSIR-IICT)" }, { - "author_name": "Shira Dunsiger", - "author_inst": "Brown University" + "author_name": "Manupati Hemalatha Jr.", + "author_inst": "CSIR-Indian Institute of Chemical Technology (CSIR-IICT)" }, { - "author_name": "Nicole R Nugent", - "author_inst": "Brown University" + "author_name": "Uday Kiran Jr.", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB)" }, { - "author_name": "John V Patena", - "author_inst": "Alpert Medical School of Brown University" + "author_name": "C. G. Gokulan Jr.", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB)" }, { - "author_name": "Alison Riese", - "author_inst": "Alpert Medical School of Brown University" + "author_name": "Shivranjani Moharir Jr.", + "author_inst": "CSIR-Centre for Cellular and Molecular Biology (CSIR-CCMB)" }, { - "author_name": "Megan L Ranney", - "author_inst": "Alpert Medical School of Brown University" + "author_name": "Rakesh K Mishra", + "author_inst": "Centre for Cellular and Molecular Biology" + }, + { + "author_name": "S Venkata Mohan Sr.", + "author_inst": "CSIR-Indian Institute of Chemical Technology (CSIR-IICT)" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.03.15.435528", @@ -889593,39 +889520,43 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.03.14.435322", - "rel_title": "Effects of Mutations in the Receptor-Binding Domain of SARS-CoV-2 Spike on its Binding Affinity to ACE2 and Neutralizing Antibodies Revealed by Computational Analysis", + "rel_doi": "10.1101/2021.03.13.435222", + "rel_title": "BNT162b2 mRNA COVID-19 vaccine induces antibodies of broader cross-reactivity than natural infection but recognition of mutant viruses is up to 10-fold reduced", "rel_date": "2021-03-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.14.435322", - "rel_abs": "SARS-CoV-2 causing coronavirus disease 2019 (COVID-19) is responsible for one of the most deleterious pandemics of our time. The interaction between the ACE2 receptors at the surface of human cells and the viral Spike (S) protein triggers the infection making the receptor-binding domain (RBD) of the SARS-CoV-2 S-protein a focal target for the neutralizing antibodies (Abs). Despite the recent progress in the development and deployment of vaccines, the emergence of novel variants of SARS-CoV-2 insensitive to Abs produced in response to the vaccine administration and/or monoclonal ones represents upcoming jeopardy. Here, we assessed the possible effects of single and multiple mutations in the RBD of SARS-CoV-2 S-protein on its binding energy to various antibodies and the human ACE2 receptor. The performed computational analysis indicates that while single amino acid replacements in RBD may only cause partial impairment of the Abs binding, moreover, limited to specific epitopes, some variants of SARS-CoV-2 (with as few as 8 mutations), which are already present in the population, may potentially result in a much broader antigenic escape. We also identified a number of point mutations, which, in contrast to the majority of replacements, reduce RBD affinity to various antibodies without affecting its binding to ACE2. Overall, the results provide guidelines for further experimental studies aiming at the identification of the high-risk RBD mutations allowing for an antigenic escape.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.13.435222", + "rel_abs": "BackgroundSeveral new variants of SARS-CoV-2 have emerged since fall 2020 which have multiple mutations in the receptor binding domain (RBD) of the spike protein.\n\nObjectiveWe aimed to assess how mutations in RBD affected recognition of immune sera by antibodies induced by natural infection versus immunization with BNT162b2, a mRNA-based vaccine against COVID-19.\n\nMethodsWe produced SARS-CoV-2 RBD mutants with single mutations in the receptor binding domain (RBD) region (E484K, K417N, N501Y) or with all 3 mutations combined, as occurring in the newly emerged variants B.1.351 (South Africa) and P.1 (Brazil). Using standard and avidity ELISAs, we determined the binding capacities to mutant RBDs of antibodies induced by infection versus vaccination.\n\nResultsThese binding assays showed that vaccination induced antibodies recognize both wildtype and mutant RBDs with higher avidities than those raised by infection. Nevertheless, recognition of mutants RBDK417N and RBDN501Y was 2.5-3-fold reduced while RBDE484K and the triple mutant were 10-fold less well recognized, demonstrating that the mutation at position 484 was key for the observed loss in cross-reactivity.\n\nConclusionOur binding data demonstrate improved recognition of mutant viruses by BNT162b2-induced antibodies compared to those induced by natural infection. Recognition may, however, be 10-fold reduced for the variants B.1.351/P.1, suggesting that the development of a new vaccine is warranted. The E484K mutation is an key hurdle for immune recognition, convalescent plasma and monoclonal antibody therapy as well as serological assays based on the wildtype sequence may therefore seriously impaired.\n\nCapsule summaryBNT162b2 mRNA COVID-19 vaccine-induced antibodies recognize mutant viruses with up to 10-fold lower efficiency", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Marine E Bozdaganyan", - "author_inst": "Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow, Russia; N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Scienc" + "author_name": "Mona Mohsen Sr.", + "author_inst": "University of Bern" }, { - "author_name": "Olga S Sokolova", - "author_inst": "Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow, Russia; Biology Department, Shenzhen MSU-BIT University, Shenzhen, China" + "author_name": "Martin F Bachmann Sr.", + "author_inst": "University of Bern" }, { - "author_name": "Konstantin V Shaitan", - "author_inst": "Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow, Russia; N.N. Semenov Federal Research Center for Chemical Physics, Russian Academy of Scienc" + "author_name": "Monique Vogel IV", + "author_inst": "University of Bern" }, { - "author_name": "Mikhail P Kirpichnikov", - "author_inst": "Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow, Russia" + "author_name": "Gilles Sousa Augusto II", + "author_inst": "University of Oxford" }, { - "author_name": "Philipp S Orekhov", - "author_inst": "Faculty of Biology, M.V. Lomonosov Moscow State University, Moscow, Russia; Institute of Personalized Medicine, Sechenov University, Moscow, Russia" + "author_name": "Xuelan Liu III", + "author_inst": "Anhui Agricultural University" + }, + { + "author_name": "Xinyue Chang Jr.", + "author_inst": "university of Bern" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "", "type": "new results", - "category": "biophysics" + "category": "immunology" }, { "rel_doi": "10.1101/2021.03.12.435194", @@ -892039,37 +891970,101 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2021.03.08.21252883", - "rel_title": "Outcome of Different Therapeutic Interventions in Mild COVID-19 Patients in a Single OPD Clinic of West Bengal: A Retrospective study", + "rel_doi": "10.1101/2021.03.08.21252784", + "rel_title": "SARS-CoV-2 seroassay optimization and performance in a population with high background reactivity in Mali", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21252883", - "rel_abs": "IntroductionWith over 87,273,380 cases being reported and 1,899,440 deaths worldwide as of 9th January 2021, Coronavirus disease 2019 (COVID-19) has become the worst-hit pandemic till date. Every day clinicians are bombarded with many new treatment options that claim to be better than the others.\n\nMaterials and methodsAfter screening the electronic database of COVID-19 patients retrospectively, 56 patients with mild COVID-19 infection matched the inclusion criteria and were divided into the four following groups - group having used Hydroxychloroquine (HCQ), group using doxycycline (DOX) + Ivermectin (IVR) combination, group receiving only azithromycin (AZ) and, group receiving only symptomatic treatment. The studys primary objective was to see Clinical response of well-being (CRWB) reporting time after initiating treatment onset between the four different treatment arms.\n\nResultsCRWB did not differ between the four groups receiving four different managements (p-value 0.846). There was significant correlation between blood levels of LDH (p-value 0.001), CRP (p-value 0.03) and D-dimer (p-value 0.04) with CRWB in IVR+DOX group and, between LDH (p-value 0.001), CRP (p-value 0.01) and age (p-value 0.035) with CRWB in the symptomatic management group.\n\nConclusionMild COVID-19 infection in patients having low-risk to progress can be managed symptomatically without any specific drug intervention.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21252784", + "rel_abs": "Serological tests are an indispensable tool to understand the epidemiology of the SARS-CoV-2 pandemic, particularly in areas where molecular diagnostics are limited. Poor assay performance may hinder the utility of these tests, including high rates of false-positivity previously reported in sub-Saharan Africa. From 312 Malian samples collected prior to 2020, we measured antibodies to the commonly tested SARS-CoV-2 antigens and four other betacoronaviruses by ELISA, and assessed functional cross-reactivity in a subset by SARS-CoV-2 pseudovirus neutralization assay. We then evaluated the performance of an ELISA developed in the US, using two-antigen SARS-CoV-2 spike protein and receptor-binding domain. To optimize test performance, we compared single and two-antigen approaches using existing assay cutoffs and population-specific cutoffs for Malian control samples (positive and negative). Background reactivity to SARS-CoV-2 antigens was common in pre-pandemic samples compared to US controls (43.4% (135/311) for spike protein, 22.8% (71/312) for RBD, and 33.9% (79/233) for nucleocapsid protein). SARS-CoV-2 reactivity correlated weakly with other betacoronavirus reactivity, varied between Malian communities, and increased with age. No pre-pandemic samples demonstrated functional activity. Regardless of the cutoffs applied, specificity improved using a two-antigen approach. Test performance was optimal using a two-antigen assay with population-specific cutoffs derived from ROC curve analysis [Sensitivity: 73.9% (51.6-89.8), Specificity: 99.4% (97.7-99.9)]. In the setting of high background reactivity, such as sub-Saharan Africa, SARS-CoV-2 serological assays need careful qualification is to characterize the epidemiology of disease, prevent unnecessary harm, and allocate resources for targeted control measures.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Sayak Roy", - "author_inst": "Medica Superspeciality Hospital" + "author_name": "John Woodford", + "author_inst": "Laboratory of Malaria Immunology and Vaccinology (LMIV), National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryla" }, { - "author_name": "Shambo Samrat Samajdar", - "author_inst": "School of Tropical Medicine, Kolkata" + "author_name": "Issaka Sagara", + "author_inst": "Malaria research and Training Center (MRTC)/Faculty of Pharmacy and Faculty of Medicine and Dentistry, University of Science, Techniques, and Technologies of Ba" }, { - "author_name": "Santanu K Tripathi", - "author_inst": "School of Tropical Medicine, Kolkata; Dean (Academics) and Head, Dept of Pharmacology, Netaji Subhash Medical College & Hospital, Bihta, Patna" + "author_name": "Jennifer Kwan", + "author_inst": "Laboratory of Clinical Immunology and Microbiology (LCIM), NIAID, NIH, Bethesda, Maryland, US" }, { - "author_name": "Shatavisa Mukherjee", - "author_inst": "School of Tropical Medicine, Kolkata." + "author_name": "Amatigue Zeguime", + "author_inst": "Malaria research and Training Center (MRTC)/Faculty of Pharmacy and Faculty of Medicine and Dentistry, University of Science, Techniques, and Technologies of Ba" }, { - "author_name": "Kingshuk Bhattacharjee", - "author_inst": "Independent Biostatistician, Kolkata" + "author_name": "Irfan Zaidi", + "author_inst": "Laboratory of Malaria Immunology and Vaccinology (LMIV), National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryla" + }, + { + "author_name": "Oumar Attaher", + "author_inst": "Malaria research and Training Center (MRTC)/Faculty of Pharmacy and Faculty of Medicine and Dentistry, University of Science, Techniques, and Technologies of Ba" + }, + { + "author_name": "Mamady Kone", + "author_inst": "Malaria research and Training Center (MRTC)/Faculty of Pharmacy and Faculty of Medicine and Dentistry, University of Science, Techniques, and Technologies of Ba" + }, + { + "author_name": "Justin Y.A. Doritchamou", + "author_inst": "Laboratory of Malaria Immunology and Vaccinology (LMIV), National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryla" + }, + { + "author_name": "Jonathan Renn", + "author_inst": "Laboratory of Malaria Immunology and Vaccinology (LMIV), National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryla" + }, + { + "author_name": "Mahamadoun Maiga", + "author_inst": "Malaria research and Training Center (MRTC)/Faculty of Pharmacy and Faculty of Medicine and Dentistry, University of Science, Techniques, and Technologies of Ba" + }, + { + "author_name": "Halimatou Diawara", + "author_inst": "Malaria research and Training Center (MRTC)/Faculty of Pharmacy and Faculty of Medicine and Dentistry, University of Science, Techniques, and Technologies of Ba" + }, + { + "author_name": "Maryonne Snow-Smith", + "author_inst": "Laboratory of Malaria Immunology and Vaccinology (LMIV), National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryla" + }, + { + "author_name": "Nada Alani", + "author_inst": "Laboratory of Malaria Immunology and Vaccinology (LMIV), National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryla" + }, + { + "author_name": "M'Bouye Doucoure", + "author_inst": "Malaria research and Training Center (MRTC)/Faculty of Pharmacy and Faculty of Medicine and Dentistry, University of Science, Techniques, and Technologies of Ba" + }, + { + "author_name": "Ivan Kosik", + "author_inst": "Laboratory of Viral Diseases (LVD), NIAID, NIH, Bethesda, Maryland, US" + }, + { + "author_name": "Jaroslav Holly", + "author_inst": "Laboratory of Viral Diseases (LVD), NIAID, NIH, Bethesda, Maryland, US" + }, + { + "author_name": "Jonathan Yewdell", + "author_inst": "Laboratory of Viral Diseases (LVD), NIAID, NIH, Bethesda, Maryland, US" + }, + { + "author_name": "Dominic Esposito", + "author_inst": "Frederick National Laboratory for Cancer Research (FNLCR), NIH, Frederick, Maryland, US" + }, + { + "author_name": "Kaitlyn Sadtler", + "author_inst": "National Institute of Biomedical Imaging and Bioengineering (NIBIB), NIH, Bethesda, Maryland, US" + }, + { + "author_name": "Alassane Dicko", + "author_inst": "Malaria research and Training Center (MRTC)/Faculty of Pharmacy and Faculty of Medicine and Dentistry, University of Science, Techniques, and Technologies of Ba" + }, + { + "author_name": "Patrick E. Duffy", + "author_inst": "Laboratory of Malaria Immunology and Vaccinology (LMIV), National Institutes of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryla" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -893849,165 +893844,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.09.21252822", - "rel_title": "Genomic epidemiology of SARS-CoV-2 in the United Arab Emirates reveals novel virus mutation, patterns of co-infection and tissue specific host responses", + "rel_doi": "10.1101/2021.03.09.21253216", + "rel_title": "COVID-19: Optimal Allocation of Ventilator Supply under Uncertainty and Risk", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21252822", - "rel_abs": "To unravel the source of SARS-CoV-2 introduction and the pattern of its spreading and evolution in the United Arab Emirates, we conducted meta-transcriptome sequencing of 1,067 nasopharyngeal swab samples collected between May 9th and Jun 29th, 2020 during the first peak of the local COVID-19 epidemic. We identified global clade distribution and eleven novel genetic variants that were almost absent in the rest of the world defined five subclades specific to the UAE viral population. Cross-settlement human-to-human transmission was related to the local business activity. Perhaps surprisingly, at least 5% of the population were co-infected by SARS-CoV-2 of multiple clades within the same host. We also discovered an enrichment of cytosine-to-uracil mutation among the viral population collected from the nasopharynx, that is different from the adenosine-to-inosine change previously reported in the bronchoalveolar lavage fluid samples and a previously unidentified upregulation of APOBEC4 expression in nasopharynx among infected patients, indicating the innate immune host response mediated by ADAR and APOBEC gene families could be tissue-specific. The genomic epidemiological and molecular biological knowledge reported here provides new insights for the SARS-CoV-2 evolution and transmission and points out future direction on host-pathogen interaction investigation.", - "rel_num_authors": 37, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21253216", + "rel_abs": "This study presents a new risk-averse multi-stage stochastic epidemics-ventilator-logistics compartmental model to address the resource allocation challenges of mitigating COVID-19. This epidemiological logistics model involves the uncertainty of untested asymptomatic infections and incorporates short-term human migration. Disease transmission is also forecasted through a new formulation of transmission rates that evolve over space and time with respect to various non-pharmaceutical interventions, such as wearing masks, social distancing, and lockdown. The proposed multi-stage stochastic model overviews different scenarios on the number of asymptomatic individuals while optimizing the distribution of resources, such as ventilators, to minimize the total expected number of newly infected and deceased people. The Conditional Value at Risk (CVaR) is also incorporated into the multi-stage mean-risk model to allow for a trade-off between the weighted expected loss due to the outbreak and the expected risks associated with experiencing disastrous pandemic scenarios. We apply our multi-stage mean-risk epidemics-ventilator-logistics model to the case of controlling the COVID-19 in highly-impacted counties of New York and New Jersey. We calibrate, validate, and test our model using actual infection, population, and migration data. The results indicate that short-term migration influences the transmission of the disease significantly. The optimal number of ventilators allocated to each region depends on various factors, including the number of initial infections, disease transmission rates, initial ICU capacity, the population of a geographical location, and the availability of ventilator supply. Our data-driven modeling framework can be adapted to study the disease transmission dynamics and logistics of other similar epidemics and pandemics.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Rong Liu", - "author_inst": "BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Pei Wu", - "author_inst": "BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Pauline Ogrodzki", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Sally Mahmoud", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Ke Liang", - "author_inst": "MGI, BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Pengjuan Liu", - "author_inst": "MGI, BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Stephen S. Francis", - "author_inst": "Department of Neurological Surgery, University of California, San Francisco" - }, - { - "author_name": "Hanif Khalak", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Denghui Liu", - "author_inst": "Laboratory of Health Intelligence, Huawei Technologies Co., Ltd" - }, - { - "author_name": "Junhua Li", - "author_inst": "BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Tao Ma", - "author_inst": "MGI, BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Fang Chen", - "author_inst": "MGI, BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Weibin Liu", - "author_inst": "BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Xinyu Huang", - "author_inst": "MGI, BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Wenjun He", - "author_inst": "Laboratory of Health Intelligence, Huawei Technologies Co., Ltd" - }, - { - "author_name": "Zhaorong Yuan", - "author_inst": "Laboratory of Health Intelligence, Huawei Technologies Co., Ltd" - }, - { - "author_name": "Nan Qiao", - "author_inst": "Laboratory of Health Intelligence, Huawei Technologies Co., Ltd" - }, - { - "author_name": "Xin Meng", - "author_inst": "Laboratory of Health Intelligence, Huawei Technologies Co., Ltd" - }, - { - "author_name": "Budoor Alqarni", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Javier Quilez", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Vinay Kusuma", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Long Lin", - "author_inst": "BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Xin Jin", - "author_inst": "BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Chongguang Yang", - "author_inst": "Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven" - }, - { - "author_name": "Xavier Anton", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Ashish Koshy", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Huanming Yang", - "author_inst": "BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Xun Xu", - "author_inst": "BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Jian Wang", - "author_inst": "BGI-Shenzhen, Shenzhen" - }, - { - "author_name": "Peng Xiao", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Nawal Ahmed Mohamed Al Kaabi", - "author_inst": "SEHA, Abu Dhabi Health Services Co, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Mohammed Saifuddin Fasihuddin", - "author_inst": "SEHA, Abu Dhabi Health Services Co, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Francis Amirtharaj Selvaraj", - "author_inst": "SEHA, Abu Dhabi Health Services Co, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Stefan Weber", - "author_inst": "SEHA, Abu Dhabi Health Services Co, Abu Dhabi, United Arab Emirates" - }, - { - "author_name": "Farida Ismail Al Hosani", - "author_inst": "Department of Health, Abu Dhabi, United Arab Emirates" + "author_name": "Xuecheng Yin", + "author_inst": "New Jersey Institute of Technology" }, { - "author_name": "Siyang Liu", - "author_inst": "BGI-Shenzhen, Shenzhen" + "author_name": "I. Esra Buyuktahtakin", + "author_inst": "New Jersey Institute of Technology" }, { - "author_name": "Walid Abbas Zaher", - "author_inst": "Group42 Healthcare, Abu Dhabi, United Arab Emirates" + "author_name": "Bhumi Pritesh Patel", + "author_inst": "New Jersey Institute of Technology" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -895495,97 +895354,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.11.21253226", - "rel_title": "Analysis of Accumulated SARS-CoV-2 Seroconversion in North Carolina: The COVID-19 Community Research Partnership", + "rel_doi": "10.1101/2021.03.11.21253356", + "rel_title": "Optimal vaccination strategies for COVID-19 based on dynamical social networks with real-time updating", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253226", - "rel_abs": "IntroductionThe COVID-19 Community Research Partnership is a population-based longitudinal syndromic and sero-surveillance study. The study includes over 17,000 participants from six healthcare systems in North Carolina who submitted over 49,000 serology results. The purpose of this study is to use these serology data to estimate the cumulative proportion of the North Carolina population that has either been infected with SARS-CoV-2 or developed a measurable humoral response to vaccination.\n\nMethodsAdult community residents were invited to participate in the study between April 2020 and February 2021. Demographic information was collected and daily symptom screen was completed using a secure, HIPPA-compliant, online portal. A portion of participants were mailed kits containing a lateral flow assay to be used in-home to test for presence of anti-SARS-CoV-2 IgM or IgG antibodies. The cumulative proportion of participants who tested positive at least once during the study was calculated. A standard Cox proportional hazards model was constructed to illustrate the probability of seroconversion over time up to December 20, 2020 (before vaccines available). A separate analysis was performed to describe the influence of vaccines during an extended period through February 15, 2021.\n\nResults17,688 participants contributed at least one serology result. Approximately two-thirds of the population were female and almost three-quarters were between 30 and 64 years of age. The average number of serology test results submitted per participant was 3.0 ({+/-}1.9). At December 20, 2020, the overall probability of seropositivity in the CCRP population was 32.6%. At February 15, 2021 the probability among healthcare workers and non-healthcare workers was 83% and 49%, respectively. An inflection upward in the probability of seropositivity was demonstrated around the end of December, suggesting an influence of vaccinations, especially for healthcare workers. Among healthcare workers, those in the oldest age category (60+ years) were 38% less likely to have seroconverted by February 15, 2021.\n\nConclusionsResults of this study suggest more North Carolina residents may have been infected with SARS-CoV-2 than the number of documented cases as determined by positive RNA or antigen tests. The influence of vaccinations on seropositivity among North Carolina residents is also demonstrated. Additional research is needed to fully characterize the impact of seropositivity on immunity and the ultimate course of the pandemic.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253356", + "rel_abs": "Vaccination strategy is crucial in fighting the COVID-19 pandemic. Since the supply is still limited in many countries, contact network-based interventions can be most powerful to set an efficient strategy by identifying high-risk individuals or communities. However, due to the high dimension, only partial and noisy network information can be available in practice, especially for dynamic systems where contact networks are highly time-variant. Furthermore, the numerous mutations of SARS-CoV-2 have a significant impact on the infectious probability, requiring real-time network updating algorithms. In this study, we propose a sequential network updating approach based on data assimilation techniques to combine different sources of temporal information. We then prioritise the individuals with high-degree or high-centrality, obtained from assimilated networks, for vaccination. The assimilation-based approach is compared with the standard method (based on partially observed networks) and a random selection strategy in terms of vaccination effectiveness in a SIR model. The numerical comparison is first carried out using real-world face-to-face dynamic networks collected in a high school, followed by sequential multi-layer networks generated relying on the Barabasi-Albert model emulating large-scale social networks with several communities.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "John C Williamson", - "author_inst": "Wake Forest Baptist Health" - }, - { - "author_name": "Thomas F Wierzba", - "author_inst": "Wake Forest Baptist Health" - }, - { - "author_name": "Michele Santacatterina", - "author_inst": "George Washington Biostatistics Center" - }, - { - "author_name": "Iqra Munawar", - "author_inst": "Wake Forest Baptist Health" - }, - { - "author_name": "Austin L Seals", - "author_inst": "Wake Forest Baptist Health" - }, - { - "author_name": "Christine Ann Pittman Ballard", - "author_inst": "Wake Forest Baptist Health" - }, - { - "author_name": "Martha Alexander-Miller", - "author_inst": "Wake Forest Baptist Health" + "author_name": "Sibo Cheng", + "author_inst": "data science institute, Imperial College London" }, { - "author_name": "Michael S Runyon", - "author_inst": "Atrium Health" - }, - { - "author_name": "Lewis H McCurdy", - "author_inst": "Atrium Health" - }, - { - "author_name": "Michael A Gibbs", - "author_inst": "Atrium Health" - }, - { - "author_name": "Amina Ahmed", - "author_inst": "Atrium Health" - }, - { - "author_name": "William H Lagarde", - "author_inst": "WakeMed Health and Hospitals" - }, - { - "author_name": "Patrick D Maguire", - "author_inst": "New Hanover Regional Medical Center" + "author_name": "Christopher Pain", + "author_inst": "Faculty of Engineering, Department of Earth Science & Engineering, Imperial College London" }, { - "author_name": "Robin King-Thiele", - "author_inst": "Campbell University" - }, - { - "author_name": "Terri Hamrick", - "author_inst": "Campbell University" - }, - { - "author_name": "Abdalla Ihmeidan", - "author_inst": "Campbell University" - }, - { - "author_name": "Shakira Henderson", - "author_inst": "Vidant Health" - }, - { - "author_name": "Diane Uschner", - "author_inst": "George Washington Biostatistics Center" - }, - { - "author_name": "David M Herrington", - "author_inst": "Wake Forest Baptist Health" + "author_name": "Yike Guo", + "author_inst": "data science institute, Imperial College London" }, { - "author_name": "John W Sanders", - "author_inst": "Wake Forest Baptist Health" + "author_name": "Rossella Arcucci", + "author_inst": "data science institute, Imperial College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -897285,67 +897080,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.03.11.21253364", - "rel_title": "Analysis of severe outcomes associated with the SARS-CoV-2 Variant of Concern 202012/01 in England using ICNARC Case Mix Programme and QResearch databases.", + "rel_doi": "10.1101/2021.03.11.21253348", + "rel_title": "The role of connectivity on COVID-19 preventive approaches", "rel_date": "2021-03-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253364", - "rel_abs": "BackgroundA new, more transmissible variant of SARS-CoV-2, variant of concern (VOC) 202012/01 or lineage B.1.1.7, has emerged in the UK. We estimate the risk of critical care admission, mortality in critical ill patients, and overall mortality associated with VOC B.1.1.7 compared with the original variant. We also compare clinical outcomes between these variants groups.\n\nMethodsWe linked a large primary care (QResearch), the national critical care (ICNARC CMP) and the COVID-19 testing (PHE) database and extracted two cohorts. The first was used to explore the association between VOC B.1.1.7 and critical care admission and 28-day mortality. The second to determine the risk of mortality in critically ill patients with VOC B.1.1.7 compared to those without. We used Royston-Parmar models adjusted for age, sex, region, other socio-demographics and comorbidities (asthma, COPD, type I and II, hypertension). We reported information on types and duration of organ supports for the two variants groups.\n\nFindingsThe first cohort included 198,420 patients. Of these, 80,494 had VOC B.1.1.7, 712 were critically ill and 630 died by 28 days. The second cohort included 3432 critically ill patients. Of these, 2019 had VOC B.1.1.7 and 822 died at the end of critical care. Using the first cohort, we estimated adjusted hazard ratios for critical care admission and mortality to be 1.99 (95% CI: 1.59, 2.49) and 1.59 (95% CI: 1.25-2.03) for VOC B.1.1.7 compared with the original variant group, respectively. The adjusted hazard ratio for mortality in critical care, estimated using the second cohort, was 0.93 (95% CI 0.76-1.15) for patients with VOC B.1.1.7, compared to those without.\n\nInterpretationVOC B.1.1.7 appears to be more severe. Patients with VOC B.1.1.7 are at increased risk of critical care admission and mortality compared with patients without. For patients receiving critical care, mortality appears independent of virus strain.\n\nRESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSA new variant of the SARS-CoV-2 virus, variant of concern (VOC) 202012/01, or lineage B.1.1.7, was detected in England in September 2020. The characteristics and outcomes of patients infected with VOC B.1.1.7 are not yet known. VOC B.1.1.7 has been associated with increased transmissibility. Early analyses have suggested infection with VOC B.1.1.7 may be associated with a higher risk of mortality compared with infection with other virus variants, but these analyses had either limited ability to adjust for key confounding variables or did not consider critical care admission. The effects of VOC B.1.1.7 on severe COVID-19 outcomes remain unclear.\n\nAdded value of this studyThis study found a 60% higher risk of 28-day mortality associated with infection with VOC B.1.1.7 in patients tested in the community in comparison with the original variant, when adjusted for key confounding variables. The risk of critical care admission for those with VOC B.1.1.7 is double the risk associated with the original variant. For patients receiving critical care, the infecting variant is not associated with the risk of mortality at the end of critical care.\n\nImplications of all the available evidenceThe higher mortality and rate of critical care admission associated with VOC B.1.1.7, combined with its known increased transmissibility, are likely to put health care systems under further stress. These effects may be mitigated by the ongoing vaccination programme.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.11.21253348", + "rel_abs": "Preventive and modelling approaches to address the COVID-19 pandemic have been primarily based on the age or occupation, and often disregard the importance of heterogeneity in population contact structure and individual connectivity. To address this gap, we developed models based on Erd[o]s-Renyi and a power law degree distribution that first incorporate the role of heterogeneity and connectivity and then can be expanded to make assumptions about demographic characteristics. Results demonstrate that variations in the number of connections of individuals within a population modify the impact of public health interventions such as lockdown or vaccination approaches. We conclude that the most effective strategy will vary depending on the underlying contact structure of individuals within a population and on timing of the interventions.\n\nAuthor summaryThe best strategy for public health interventions, such as lockdown or vaccination, depends on the contact structure of the population and the timing of the intervention. In general, for heterogeneous contact structures that mimic the COVID-19 spread, which is characterized by the presence of super spreaders, vaccinating the most connected individuals first was the most effective strategy to prevent infections and deaths, especially when coupled to serological tests. Models considering heterogeneity in human interactions need be used to identify the best potential vaccine prioritization strategies.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Martina Patone", - "author_inst": "University of Oxford" - }, - { - "author_name": "Karen Thomas", - "author_inst": "Intensive Care National Audit & Research Centre" - }, - { - "author_name": "Robert Hatch", - "author_inst": "Intensive Care National Audit & Research Centre" - }, - { - "author_name": "Pui San Tan", - "author_inst": "University of Oxford" - }, - { - "author_name": "Weiqi Liao", - "author_inst": "University of Oxford" - }, - { - "author_name": "Carol Coupland", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Paul Mouncey", - "author_inst": "Intensive Care National Audit & Research Centre" + "author_name": "Veronica Miro Pina", + "author_inst": "Centre for Genomic Regulation" }, { - "author_name": "David Harrison", - "author_inst": "Intensive Care National Audit & Research Centre" + "author_name": "Julio E Nava-Trejo", + "author_inst": "National Autonomous University of Mexico (UNAM)" }, { - "author_name": "Kathryn Rowan", - "author_inst": "Intensive Care National Audit & Research Centre" + "author_name": "Andras Tobias", + "author_inst": "Technische Universitat Berlin, Berlin, Germany" }, { - "author_name": "Peter Horby", - "author_inst": "University of Oxford" + "author_name": "Etienne Nzabarushimana", + "author_inst": "Indiana University Bloomington, Indiana, USA" }, { - "author_name": "Peter Watkinson", - "author_inst": "Intensive Care National Audit & Research Centre" + "author_name": "Adrian Gonzalez-Casanova", + "author_inst": "National Autonomous University of Mexico (UNAM)" }, { - "author_name": "Julia Hippisley-Cox", - "author_inst": "University of Oxford" + "author_name": "Ines Gonzalez-Casanova", + "author_inst": "Indiana University Bloomington, Indiana, USA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "primary care research" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.03.11.435037", @@ -898862,47 +898633,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.03.09.21253155", - "rel_title": "High-resolution epigenome analysis in nasal samples derived from children with respiratory viral infections reveals striking changes upon SARS-CoV-2 infection", + "rel_doi": "10.1101/2021.03.08.21253135", + "rel_title": "Predicting the Efficacy of COVID-19 Convalescent Plasma Donor Units with the Lumit Dx anti-Receptor Binding Domain Assay.", "rel_date": "2021-03-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.09.21253155", - "rel_abs": "BackgroundDNA methylation patterns of the human genome can be modified by environmental stimuli and provide dense information on gene regulatory circuitries. We studied genome-wide DNA methylation in nasal samples from infants (<6 months) applying whole-genome bisulfite sequencing (WGBS) to characterize epigenome response to 10 different respiratory viral infections including SARS-CoV-2.\n\nResultsWe identified virus-specific differentially methylated regions (vDMR) with human metapneumovirus (hMPV) and SARS-CoV-2 followed by Influenza B (Flu B) causing the weakest vs. strongest epigenome response with 496 vs. 78541 and 14361 vDMR, respectively. We found a strong replication rate of FluB (52%) and SARS-CoV-2 (42%) vDMR in independent samples indicating robust epigenome perturbation upon infection. Among the FluB and SARS-CoV-2 vDMRs, around 70% were hypomethylated and significantly enriched among epithelial cell-specific regulatory elements whereas the hypermethylated vDMRs for these viruses mapped more frequently to immune cell regulatory elements, especially those of the myeloid lineage. The hypermethylated vDMRs were also enriched among genes and genetic loci in monocyte activation pathways and monocyte count. Finally, we perform single-cell RNA-sequencing characterization of nasal mucosa in response to these two viruses to functionally analyze the epigenome perturbations. Which supports the trends we identified in methylation data and highlights and important role for monocytes.\n\nConclusionsAll together, we find evidence indicating genetic predisposition to innate immune response upon a respiratory viral infection. Our genome-wide monitoring of infant viral response provides first catalogue of associated host regulatory elements. Assessing epigenetic variation in individual patients may reveal evidence for viral triggers of childhood disease.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.08.21253135", + "rel_abs": "BackgroundThe novel coronavirus SARS-CoV2 that causes COVID-19 has resulted in the death of more than 2.5 million people, but no cure exists. Although passive immunization with COVID-19 convalescent plasma (CCP) provides a safe and viable therapeutic option, the selection of optimal units for therapy in a timely fashion remains a barrier.\n\nStudy design and methodsSince virus neutralization is a necessary characteristic of plasma that can benefit recipients, the neutralizing titers of plasma samples were measured using a retroviral-pseudotype assay. Binding antibody titers to the spike (S) protein were also determined by a clinically available serological assay (Ortho-Vitros total IG), and an in-house ELISA. The results of these assays were compared to a measurement of antibodies directed to the receptor binding domain (RBD) of the SARS-CoV2 S protein (Promega Lumit Dx).\n\nResultsAll measures of antibodies were highly variable, but correlated, to different degrees, with each other. However, the anti-RBD antibodies correlated with viral neutralizing titers to a greater extent than the other antibody assays.\n\nDiscussionOur observations support the use of an anti-RBD assay such as the Lumit Dx assay, as an optimal predictor of the neutralization capability of CCP.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Konner Winkley", - "author_inst": "Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, Missouri, US" - }, - { - "author_name": "Boryana Koseva", - "author_inst": "Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, Missouri, US" - }, - { - "author_name": "Dithi Banerjee", - "author_inst": "Department of Pathology and Laboratory Medicine, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, Missouri, US" - }, - { - "author_name": "Warren Cheung", - "author_inst": "Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, Missouri, US" + "author_name": "Sanath Kumar Janaka", + "author_inst": "University of Wisconsin" }, { - "author_name": "Rangaraj Selvarangan", - "author_inst": "Department of Pathology and Laboratory Medicine, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, Missouri, US" + "author_name": "Natasha M Clark", + "author_inst": "University of Wisconsin" }, { - "author_name": "Tomi Pastinen", - "author_inst": "Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, Missouri, US" + "author_name": "David T Evans", + "author_inst": "University of Wisconsin" }, { - "author_name": "Elin Grundberg", - "author_inst": "Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, Missouri, US" + "author_name": "Joseph P Connor", + "author_inst": "University of Wisconsin" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.03.09.21252641", @@ -901023,81 +900782,185 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2021.03.09.434030", - "rel_title": "Development of Equine Immunoglobulin Fragment F(ab')2 with High Neutralizing Capability against SARS-CoV-2", + "rel_doi": "10.1101/2021.03.09.434607", + "rel_title": "The dual function monoclonal antibodies VIR-7831 and VIR-7832 demonstrate potent in vitro and in vivo activity against SARS-CoV-2", "rel_date": "2021-03-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.09.434030", - "rel_abs": "The ongoing pandemic, COVID-19, caused by SARS-CoV-2 has taken the world, and especially the scientific community by storm. While vaccines are being introduced into the market, there is also a pressing need to find potential drugs and therapeutic modules. Remdesivir is one of the antivirals currently being used with a limited window of action. As more drugs are being vetted, passive immunotherapy in the form of neutralizing antibodies can provide immediate action to combat the increasing numbers of COVID-positive cases. Herein, we demonstrate that equines hyper-immunized with chemically inactivated SARS-CoV-2 generate high titers of antibody with a strong virus neutralizing potential. ELISA performed with pooled antisera displayed highest immunoglobulin titer on 42 days post-immunization, at 1:51,200 dilutions. F(ab)2 immunoglobulin fragments generated from the pools also showed very high, antigen-specific affinity at 1:102,400 dilutions. Finally, in vitro virus neutralization assays confirmed that different pools of F(ab)2 fragments could successfully neutralize SARS-CoV-2 with titers well above 25,000, indicating the potential of this strategy in treating severe COVID-19 cases with high titers. The F(ab)2 was able to cross neutralize another SARS-CoV-2 strain, demonstrating its efficacy against the emerging viral variants and the importance of this approach in our efforts of eradication of COVID-19. In conclusion, this study demonstrates that virus-neutralizing antibodies raised in equines can potentially be used as a treatment regimen in the form of effective passive immunotherapy to combat COVID-19.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.09.434607", + "rel_abs": "Sotrovimab (VIR-7831) and VIR-7832 are dual action monoclonal antibodies (mAbs) targeting the spike glycoprotein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Sotrovimab and VIR-7832 were derived from a parent antibody (S309) isolated from memory B cells of a 2003 severe acute respiratory syndrome coronavirus (SARS-CoV) survivor. Both mAbs contain an \"LS\" mutation in the Fc region to prolong serum half-life. In addition, VIR-7832 encodes an Fc GAALIE mutation that has been shown previously to evoke CD8+ T-cells in the context of an in vivo viral respiratory infection. Sotrovimab and VIR-7832 neutralize wild-type and variant pseudotyped viruses and authentic virus in vitro. In addition, they retain activity against monoclonal antibody resistance mutations conferring reduced susceptibility to previously authorized mAbs. The sotrovimab/VIR-7832 epitope continues to be highly conserved among circulating sequences consistent with the high barrier to resistance observed in vitro. Furthermore, both mAbs can recruit effector mechanisms in vitro that may contribute to clinical efficacy via elimination of infected host cells. In vitro studies with these mAbs demonstrated no enhancement of infection. In a Syrian Golden hamster proof-of concept wildtype SARS-CoV-2 infection model, animals treated with sotrovimab had less weight loss, and significantly decreased total viral load and infectious virus levels in the lung compared to a control mAb. Taken together, these data indicate that sotrovimab and VIR-7832 are key agents in the fight against COVID-19.", + "rel_num_authors": 42, "rel_authors": [ { - "author_name": "Divya Gupta Ms", - "author_inst": "Centre for Cellular and Molecular Biology" + "author_name": "Andrea L Cathcart", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Farhan Ahmed Dr", - "author_inst": "University of Hyderabad" + "author_name": "Colin Havenar-Daughton", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Dixit Tandel Mr", - "author_inst": "Centre for Cellular and Molecular Biology, Academy of Scientific and Innovative Research" + "author_name": "Florian A Lempp", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Haripriya Parthasarathy Ms", - "author_inst": "Centre for Cellular and Molecular Biology" + "author_name": "Daphne Ma", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Dhiviya Vedagiri Ms", - "author_inst": "Centre for Cellular and Molecular Biology, Academy of Scientific and Innovative Research" + "author_name": "Michael Schmid", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Vishal Sah Mr", - "author_inst": "Centre for Cellular and Molecular Biology, Academy of Scientific and Innovative Research" + "author_name": "Maria L Agostini", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Krishna Mohan Bodduluru Dr", - "author_inst": "Vins Bioproducts Ltd" + "author_name": "Barbara Guarino", + "author_inst": "Humabs Biomed SA, a subsidiary of Vir Biotechnology" }, { - "author_name": "Siddarth Shreedas Daga Mr", - "author_inst": "Vins Bioproducts Ltd" + "author_name": "Julia Di iulio", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Rafiq Ahmad Khan Mr", - "author_inst": "University of Hyderabad" + "author_name": "Laura Rosen", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Chiranjeevi Kondiparthi Mr", - "author_inst": "Vins Bioproducts Ltd" + "author_name": "Heather Tucker", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Prabhudas Savari Mr", - "author_inst": "Vins Bioproducts Ltd" + "author_name": "Joshua Dillen", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Sandesh Hajarilal Jain Dr", - "author_inst": "Vins Bioproducts Ltd" + "author_name": "Sambhavi Subramanian", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Jaya Shreedas Daga Ms", - "author_inst": "Vins Bioproducts Ltd" + "author_name": "Barbara Sloan", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Shashikala Reddy Dr", - "author_inst": "Osmania Medical College" + "author_name": "Siro Bianchi", + "author_inst": "Humabs Biomed SA, a subsidiary of Vir Biotechnology" }, { - "author_name": "Nooruddin Khan Dr", - "author_inst": "University of Hyderabad" + "author_name": "Jason Wojcechowskyj", + "author_inst": "Vir Biotechnology" }, { - "author_name": "Krishnan Harinivas Harshan Dr", - "author_inst": "Centre for Cellular and Molecular Biology" + "author_name": "Jiayi Zhou", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Hannah Kaiser", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Arthur Chase", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Elvin Lauron", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Martin Montiel-Ruiz", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Roberto Spreafico", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Julia Noack", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Nadine Czudnochowski", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Anna Sahakyan", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Dora Pinto", + "author_inst": "Humabs Biomed SA" + }, + { + "author_name": "Christian Saliba", + "author_inst": "Humabs Biomed SA" + }, + { + "author_name": "Katja Culap", + "author_inst": "Humabs Biomed SA, a subsidiary of Vir Biotechnology" + }, + { + "author_name": "Exequiel Delotta Jr.", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Arnold Park", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Elisabetta Cameroni", + "author_inst": "Humabs Biomed SA, a subsidiary of Vir Biotechnology" + }, + { + "author_name": "Sarah Ledoux", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Yoshihiro Kawaoka", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Adam Werts", + "author_inst": "Lovelace Biomedical" + }, + { + "author_name": "Christophe Colas", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Leah Soriaga", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Amalio Telenti", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Lisa A Purcell", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Seungmin Hwang", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Gyorgy Snell", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Herbert W Virgin", + "author_inst": "Vir Biotechnology" + }, + { + "author_name": "Davide Corti", + "author_inst": "Humabs Biomed SA, a subsidiary of Vir Biotechnology" + }, + { + "author_name": "Christy M Hebner", + "author_inst": "Vir Biotechnology" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -903361,87 +903224,119 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.03.09.434219", - "rel_title": "The FDA-approved drug cobicistat synergizes with remdesivir to inhibit SARS-CoV-2 replication", + "rel_doi": "10.1101/2021.03.08.433764", + "rel_title": "Site-specific steric control of SARS-CoV-2 spike glycosylation", "rel_date": "2021-03-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.09.434219", - "rel_abs": "Combinations of direct-acting antivirals are needed to minimize drug-resistance mutations and stably suppress replication of RNA viruses. Currently, there are limited therapeutic options against the Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-CoV-2) and testing of a number of drug regimens has led to conflicting results. Here we show that cobicistat, which is an-FDA approved drug-booster that blocks the activity of the drug metabolizing proteins Cytochrome P450-3As (CYP3As) and P-glycoprotein (P-gp), inhibits SARS-CoV-2 replication. Cell-to-cell membrane fusion assays indicated that the antiviral effect of cobicistat is exerted through inhibition of spike protein-mediated membrane fusion. In line with this, incubation with low micromolar concentrations of cobicistat decreased viral replication in three different cell lines including cells of lung and gut origin. When cobicistat was used in combination with the putative CYP3A target and nucleoside analog remdesivir, a synergistic effect on the inhibition of viral replication was observed in cell lines and in a primary human colon organoid. The cobicistat/remdesivir combination was able to potently abate viral replication to levels comparable to mock-infected cells leading to an almost complete rescue of infected cell viability. These data highlight cobicistat as a therapeutic candidate for treating SARS-CoV-2 infection and as a potential building block of combination therapies for COVID-19.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.08.433764", + "rel_abs": "A central tenet in the design of vaccines is the display of native-like antigens in the elicitation of protective immunity. The abundance of N-linked glycans across the SARS-CoV-2 spike protein is a potential source of heterogeneity between the many different vaccine candidates under investigation. Here, we investigate the glycosylation of recombinant SARS-CoV-2 spike proteins from five different laboratories and compare them against infectious virus S protein. We find patterns which are conserved across all samples and this can be associated with site-specific stalling of glycan maturation which act as a highly sensitive reporter of protein structure. Molecular dynamics (MD) simulations of a fully glycosylated spike support s a model of steric restrictions that shape enzymatic processing of the glycans. These results suggest that recombinant spike-based SARS-CoV-2 immunogen glycosylation reproducibly recapitulates signatures of viral glycosylation.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Iart Luca Shytaj", - "author_inst": "Department of Infectious Diseases, Federal University of Sao Paulo, Sao Paulo, Brazil." + "author_name": "Joel D Allen", + "author_inst": "University of Southampton" }, { - "author_name": "Mohamed Fares", - "author_inst": "Department of Hydrobiology, Veterinary Research Division, National Research Centre, Cairo, Egypt." + "author_name": "Himanshi Chawla", + "author_inst": "University of Southampton" }, { - "author_name": "Bojana Lucic", - "author_inst": "Department of Infectious Diseases, Integrative Virology, CIID, Heidelberg University, Heidelberg, Germany" + "author_name": "Firdaus Samsudin", + "author_inst": "A*STAR Bioinformatics Institute, Singapore" }, { - "author_name": "Lara Gallucci", - "author_inst": "Department of Infectious Diseases, Integrative Virology, CIID, Heidelberg University, Heidelberg, Germany." + "author_name": "Lorena Zuzic", + "author_inst": "A*STAR Bioinformatics Institute, Singapore" }, { - "author_name": "Mahmoud M. Tolba", - "author_inst": "Pharmaceutical Division, Ministry of Health and Population, Faiyum, Egypt." + "author_name": "Aishwary Tukaram Shivgan", + "author_inst": "A*STAR Bioinformatics Institute, Singapore" }, { - "author_name": "Liv Zimmermann", - "author_inst": "Department of Infectious Diseases, Virology, CIID, Heidelberg University Hospital, Heidelberg, Germany" + "author_name": "Yasunori Watanabe", + "author_inst": "University of Southampton" }, { - "author_name": "Ahmed T. Ayoub", - "author_inst": "Department of Pharmaceutical Chemistry, Biomolecular Simulation Center, Heliopolis University, Cairo, Egypt." + "author_name": "Wan-Ting He", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Mirko Cortese", - "author_inst": "Department of Infectious Diseases, Molecular Virology, CIID, Heidelberg University, Heidelberg, Germany" + "author_name": "Sean Callaghan", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Christopher J. Neufeldt", - "author_inst": "Department of Infectious Diseases, Molecular Virology, CIID, Heidelberg University, Heidelberg, Germany" + "author_name": "Ge Song", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Vibor Laketa", - "author_inst": "Department of Infectious Diseases, Virology, CIID, Heidelberg University Hospital, Heidelberg, Germany" + "author_name": "Peter Yong", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Petr Chlanda", - "author_inst": "Department of Infectious Diseases, Virology, CIID, Heidelberg University Hospital, Heidelberg, Germany" + "author_name": "Philip J.M. Brouwer", + "author_inst": "Amsterdam UMC" }, { - "author_name": "Oliver T. Fackler", - "author_inst": "Department of Infectious Diseases, Integrative Virology, CIID, Heidelberg University, Heidelberg, Germany." + "author_name": "Yutong Song", + "author_inst": "School of Life Sciences, Tsinghua University" }, { - "author_name": "Steeve Boulant", - "author_inst": "Department of Infectious Diseases, Virology, CIID, Heidelberg University Hospital, Heidelberg, Germany" + "author_name": "Helen M E Duyvesteyn", + "author_inst": "University of Oxford" }, { - "author_name": "Ralf Bartenschlager", - "author_inst": "Department of Infectious Diseases, Molecular Virology, CIID, Heidelberg University, Heidelberg, Germany" + "author_name": "Tomas Malinauskas", + "author_inst": "University of Oxford" }, { - "author_name": "Megan Stanifer", - "author_inst": "Department of Infectious Diseases, Molecular Virology, CIID, Heidelberg University, Heidelberg, Germany" + "author_name": "Joeri Kint", + "author_inst": "Excellgene" }, { - "author_name": "Andrea Savarino", - "author_inst": "Department of Infectious and Immune-Mediated Diseases, Italian Institute of Health, Rome, Italy." + "author_name": "Paco Pino", + "author_inst": "Excellgene" }, { - "author_name": "Marina Lusic", - "author_inst": "Department of Infectious Diseases, Integrative Virology, CIID, Heidelberg University, Heidelberg, Germany." + "author_name": "Maria J. Wurm", + "author_inst": "Excellgene" + }, + { + "author_name": "Martin Frank", + "author_inst": "Biognos AB" + }, + { + "author_name": "David I Stuart", + "author_inst": "University of Oxford" + }, + { + "author_name": "Rogier W. Sanders", + "author_inst": "Amsterdam UMC" + }, + { + "author_name": "Raiees Andrabi", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Dennis R. Burton", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Sai Li", + "author_inst": "School of Life Sciences, Tsinghua University" + }, + { + "author_name": "Peter J Bond", + "author_inst": "A*STAR Bioinformatics Institute, Singapore" + }, + { + "author_name": "Max Crispin", + "author_inst": "University of Southampton" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2021.03.08.21253120", @@ -905419,49 +905314,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.04.21252880", - "rel_title": "Estimation and optimal control of the multi-scale dynamics of the Covid-19", + "rel_doi": "10.1101/2021.03.03.21252855", + "rel_title": "Bromhexine Hydrochloride Prophylaxis of COVID-19 for Medical Personnel: A Randomized Open-Label Study", "rel_date": "2021-03-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.04.21252880", - "rel_abs": "This work aims at a better understanding and the optimal control of the spread of the new severe acute respiratory corona virus 2 (SARS-CoV-2). We first propose a multi-scale model giving insights on the virus population dynamics, the transmission process and the infection mechanism. We consider 10 compartments in the human population in order to take into accounts the effects of different specific mitigation policies: susceptible, infected, infectious, quarantined, hospitalized, treated, recovered, non-infectious dead, infectious dead, buried. The population of viruses is also partitioned into 10 compartments corresponding respectively to each of the first nine human population compartments and the free viruses available in the environment. Indeed, we have human to human virus transmission, human to environment virus transmission, environment to human virus transmission and self infection by susceptible individuals. We show the global stability of the disease free equilibrium if a given threshold[T] 0 is less or equal to 1 and we provide how to compute the basic reproduction number[R] 0. A convergence index[T] 1 is also defined in order to estimate the speed at which the disease extincts and an upper bound to the time of extinction is given. The existence of the endemic equilibrium is conditional and its description is provided. We evaluate the sensitivity of[R] 0,[T] 0 and[T] 1 to control parameters such as the maximal human density allowed per unit of surface, the rate of disinfection both for people and environment, the mobility probability, the wearing mask probability or efficiency, and the human to human contact rate which results from the previous one. Except the maximal human density allowed per unit of surface, all those parameters have significant effects on the qualitative dynamics of the disease. The most significant is the probability of wearing mask followed by the probability of mobility and the disinfection rate. According to a functional cost taking into consideration economic impacts of SARS-CoV-2, we determine and discuss optimal fighting strategies. The study is applied to real available data from Cameroon and an estimation of model parameters is done. After several simulations, social distancing and the disinfection frequency appear as the main elements of the optimal control strategy.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.03.21252855", + "rel_abs": "BackgroundBromhexine hydrochloride has been suggested as a TMPRSS2 protease blocker that precludes the penetration of SARS-CoV-2 into cells. We aimed to assess the preventive potential of regular bromhexine hydrochloride intake for COVID-19 risk reduction in medical staff actively involved in the evaluation and treatment of patients with confirmed or suspected SARS-CoV-2 infection.\n\nMethodsIn a single-center randomized open-label study, medical staff managing patients with suspected and confirmed COVID-19 were enrolled and followed up for 8 weeks. The study began at the initiation of COVID-19 management in the clinic. The study was prematurely terminated after the enrollent of 50 participants without a history of SARS-CoV-2 infection: 25 were assigned to bromhexine hydrochloride treatment (8 mg 3 times per day), and 25 were controls. The composite primary endpoint was a positive nasopharyngeal swab polymerase chain reaction (PCR) test for SARS-CoV-2 or signs of clinical infection within 28 days and at week 8. Secondary endpoints included: time from the first contact with a person with COVID-19 to the appearance of respiratory infection symptoms; the number of days before a first positive SARS-CoV-2 test; the number of asymptomatic participants with a positive nasopharyngeal swab test; the number of symptomatic COVID-19 cases; adverse events.\n\nResultsThe rate of the combined primary endpoint did not differ significantly between the active treatment group (2/25 [8%]) and control group (7/25 [28%]); P=0.07. A fewer number of participants developed symptomatic COVID-19 in the treatment group compared to controls (0/25 vs 5/25; P = 0.02).\n\nConclusionAlthough the study was underpowered, it showed that Bromhexine hydrochloride prophylaxis was associated with a reduced rate of symptomatic COVID-19. The prophylactic treatment was not associated with a lower combined primary endpoint rate, a positive swab PCR test, or COVID-19. (ClinicalTrials.gov number, NCT04405999)", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "David Jaures FOTSA MBOGNE", - "author_inst": "The University of Ngaoundere" + "author_name": "Evgeny N Mikhaylov", + "author_inst": "Almazov National Medical Research Centre" }, { - "author_name": "Stephane Yanick TCHOUMI", - "author_inst": "The University of Ngaoundere" + "author_name": "Tamara A Lyubimtseva", + "author_inst": "Almazov National Medical Research Centre" }, { - "author_name": "Yannick Kouakep Tchaptchie", - "author_inst": "EGCIM, University of Ngaoundere" + "author_name": "Aleksandr D Vakhrushev", + "author_inst": "Almazov National Medical Research Centre" }, { - "author_name": "Vivient Corneille KAMLA", - "author_inst": "The University of Ngaoundere" + "author_name": "Dmitry Stepanov", + "author_inst": "Marienkrankenhaus Soest" }, { - "author_name": "Jean Claude KAMGANG", - "author_inst": "The University of Ngaoundere" + "author_name": "Dmitry S Lebedev", + "author_inst": "Almazov National Medical Research Centre" }, { - "author_name": "Duplex Elvis HOUPA DANGA", - "author_inst": "The University of Ngaoundere" + "author_name": "Elena Yu Vasilieva", + "author_inst": "Almazov National Medical Research Centre" }, { - "author_name": "Samuel BOWONG TSAKOU", - "author_inst": "The University of Douala" + "author_name": "Alexandra O Konradi", + "author_inst": "Almazov National Medical Research Centre" }, { - "author_name": "David BEKOLLE", - "author_inst": "The University of Ngaoundere" + "author_name": "Evgeny V Shlyakhto", + "author_inst": "Almazov National Medical Research Centre" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -907181,45 +907076,29 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.03.06.21251482", - "rel_title": "A Rapid Method to Evaluate Pre-Travel Testing Programs for COVID-19: A Study in Hawaii", + "rel_doi": "10.1101/2021.03.06.21252994", + "rel_title": "Meta-Analysis of the Dynamics of the Emergence of Mutations and Variants of SARS-CoV-2", "rel_date": "2021-03-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.06.21251482", - "rel_abs": "BackgroundPre-travel testing programs are being implemented around the world to curb COVID-19 and its variants from incoming travelers. A common approach is a single pre-travel test, 72 hours before departure, such as in Hawaii; however this raises concerns for those who are incubating or those infected after pre-travel testing or during transit. We need a rapid method to assess the effectiveness of pre-travel testing programs, and we use Hawaii as our case study.\n\nMethodsWe invited travelers departing from Kahului main airport at the end of their visit to Maui (major tourist destination among the Hawaiian islands) and performed COVID-19 PCR testing. Eligible participants needed a negative pre-travel test and a Hawaiian stay [≤] 14 days. We designed for anonymous testing at the end of travel so that travel plans would be unaffected, and we aimed for [≥] 70% study participation.\n\nResultsAmong consecutive eligible travelers, 282 consented and 111 declined to participate, leading to a 72% (67-76%, 95% confidence interval) participation rate. Among 281 tested participants, two were positive with COVID-19, with an estimated positivity rate of 7 cases per 1,000 travelers. The top states of residence are California (58%) and Washington (21%). The mean length of stay was 7.7 {+/-} 0.2 days. Regarding pre-travel testing, 87% had non-nasopharyngeal tests and 66% had self-administered tests.\n\nConclusionsThis positivity rate leads to an estimated 17-30 infected travelers arriving daily to Maui in November-December 2020, and an estimated 52-70 infected travelers arriving daily to Hawaii during the same period. These counts surpass the Maui District Health Offices projected ability to accommodate 10 infected visitors daily in Maui; therefore, an additional mitigation layer for travelers is recommended. This rapid field study can be replicated widely in airports to assess effectiveness of pre-travel programs and can be expanded to evaluate COVID-19 importation and its variants.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.06.21252994", + "rel_abs": "The novel Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) emerged in late December 2019 in Wuhan, China, and is the causative agent for the worldwide COVID-19 pandemic. SARS-CoV-2 is a 29,811 nucleotides positive-sense single-stranded RNA virus belonging to the betacoronavirus genus. Due to inefficient proofreading ability of the viral RNA-dependent polymerase complex, coronaviruses are known to acquire new mutations following replication, which constitutes one of the main factors driving the evolution of its genome and the emergence of new genetic variants. In the last few months, the identification of new B.1.1.7 (UK), B.1.351 (South Africa) and P.1 (Brazil) variants of concern (VOC) highlighted the importance of tracking the emergence of mutations in the SARS-CoV-2 genome and their impact on transmissibility, infectivity, and neutralizing antibody escape capabilities. These VOC demonstrate increased transmissibility and antibody escape, and reduce current vaccine efficacy. Here we analyzed the appearance and prevalence trajectory of mutations that appeared in all SARS-CoV-2 genes from December 2019 to January 2021. Our goals were to identify which modifications are the most frequent, study the dynamics of their spread, their incorporation into the consensus sequence, and their impact on virus biology. We also analyzed the structural properties of the spike glycoprotein of the B.1.1.7, B.1.351 and P.1 variants. This study offers an integrative view of the emergence, disappearance, and consensus sequence integration of successful mutations that constitute new SARS-CoV-2 variants and their impact on neutralizing antibody therapeutics and vaccines.\n\nIMPORTANCESARS-CoV-2 is the etiological agent of COVID-19, which has caused > 2 million deaths worldwide as of January, 2021. Mutations occur in the genome of SARS-CoV-2 during viral replication and affect viral infectivity, transmissibility and virulence. In early March 2020, the D614G mutation in the spike protein emerged, which increased the viral transmissibility and is now found in >90% of all SARS-CoV-2 genomic sequences in GISAID database. Between October and December 2020, B.1.1.7 (UK), B.1.351 (South Africa) and P.1 (Brazil) variants of concern (VOCs) emerged, which have increased neutralizing antibody escape capabilities because of mutations in the receptor binding domain of the spike protein. Characterizing mutations in these variants is crucial because of their effect on adaptive immune response, neutralizing antibody therapy, and their impact on vaccine efficacy. Here we tracked and analyzed mutations in SARS-CoV-2 genes over a twelve-month period and investigated functional alterations in the spike of VOCs.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Amy T. Hou", - "author_inst": "Medical Reserve Corps, Maui District Health Office, Hawaii Department of Health" - }, - { - "author_name": "Genevieve C. Pang", - "author_inst": "Maui District Health Office, Hawaii Department of Health" - }, - { - "author_name": "Kristin M. Mills", - "author_inst": "Maui District Health Office, Hawaii Department of Health" - }, - { - "author_name": "Krizhna L. Bayudan", - "author_inst": "Medical Reserve Corps, Maui District Health Office, Hawaii Department of Health" - }, - { - "author_name": "Dayna M. Moore", - "author_inst": "Medical Reserve Corps, Maui District Health Office, Hawaii Department of Health" + "author_name": "Nicolas Castonguay", + "author_inst": "University of Ottawa" }, { - "author_name": "Luz P. Medina", - "author_inst": "Maui County Medical Society" + "author_name": "Wandong Zhang", + "author_inst": "National Research Council Canada" }, { - "author_name": "Lorrin W. Pang", - "author_inst": "Maui District Health Office, Hawaii Department of Health" + "author_name": "Marc-Andr\u00e9 Langlois", + "author_inst": "University of Ottawa" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -909003,67 +908882,39 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.03.03.21252838", - "rel_title": "SARS-CoV-2 transmission in intercollegiate athletics not fully mitigated with daily antigen testing", + "rel_doi": "10.1101/2021.03.03.21252861", + "rel_title": "The COVID-19 health equity twindemic: Statewide epidemiologic trends of SARS-CoV-2 outcomes among racial minorities and in rural America", "rel_date": "2021-03-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.03.21252838", - "rel_abs": "BackgroundHigh frequency, rapid turnaround SARS-CoV-2 testing continues to be proposed as a way of efficiently identifying and mitigating transmission in congregate settings. However, two SARS-CoV-2 outbreaks occurred among intercollegiate university athletic programs during the fall 2020 semester despite mandatory directly observed daily antigen testing.\n\nMethodsDuring the fall 2020 semester, athletes and staff in both programs were tested daily using Quidels Sofia SARS Antigen Fluorescent Immunoassay (FIA), with positive antigen results requiring confirmatory testing with real-time reverse transcription polymerase chain reaction (RT-PCR). We used genomic sequencing to investigate transmission dynamics in these two outbreaks.\n\nResultsIn Outbreak 1, 32 confirmed cases occurred within a university athletics program after the index patient attended a meeting while infectious despite a negative antigen test on the day of the meeting. Among isolates sequenced from Outbreak 1, 24 (92%) of 26 were closely related, suggesting sustained transmission following an initial introduction event. In Outbreak 2, 12 confirmed cases occurred among athletes from two university programs that faced each other in an athletic competition despite receiving negative antigen test results on the day of the competition. Sequences from both teams were closely related and unique from strains circulating in the community, suggesting transmission during intercollegiate competition.\n\nConclusionsThese findings suggest that antigen testing alone, even when mandated and directly observed, may not be sufficient as an intervention to prevent SARS-CoV-2 outbreaks in congregate settings, and highlights the importance of supplementing serial antigen testing with appropriate mitigation strategies to prevent SARS-CoV-2 outbreak in congregate settings.\n\nSummaryHigh frequency, rapid turnaround SARS-CoV-2 testing continues to be proposed as a way of efficiently identifying and mitigating transmission in congregate settings. However, here we describe two SARS-CoV-2 outbreaks occurred among intercollegiate university athletic programs during the fall 2020 semester.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.03.21252861", + "rel_abs": "BackgroundEarly studies on COVID-19 identified unequal patterns in hospitalization and mortality in urban environments for racial and ethnic minorities. These studies were primarily single center observational studies conducted within the first few weeks or months of the pandemic. We sought to examine trends in COVID-19 morbidity and mortality over time for minority and rural populations, especially during the U.S. fall surge.\n\nMethodsStatewide cohort of all adult residents in Indiana tested for SARS-CoV-2 infection between March 1 and December 31, 2020, linked to electronic health records. Primary measures were per capita rates of infection, hospitalization, and death. Age adjusted rates were calculated for multiple time periods corresponding to public health mitigation efforts.\n\nResultsMorbidity and mortality increased over time with notable differences among sub-populations. Initially, per capita hospitalizations among racial minorities were 3-4 times higher than whites, and per capita deaths among urban residents were twice those of rural residents. By fall 2020, per capita hospitalizations and deaths in rural areas surpassed those of urban areas, and gaps between black/brown and white populations narrowed. Cumulative morbidity and mortality were highest among minority groups and in rural communities.\n\nConclusionsBurden of COVID-19 morbidity and mortality shifted over time, creating a twindemic involving disparities in outcomes based on race and geography. Health officials should explicitly measure disparities and adjust mitigation and vaccination strategies to protect vulnerable sub-populations with greater disease burden.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Gage Kahl Moreno", - "author_inst": "University of Wisconsin - Madison" - }, - { - "author_name": "Katarina M Braun", - "author_inst": "University of Wisconsin-Madison" - }, - { - "author_name": "Ian W Pray", - "author_inst": "Wisconsin Department of Health Services" - }, - { - "author_name": "Hannah E Seagaloff", - "author_inst": "Wisconsin Department of Health Services" - }, - { - "author_name": "Ailam Lim", - "author_inst": "University of Wisconsin - Madison" - }, - { - "author_name": "Keith Poulsen", - "author_inst": "University of Wisconsin - Madison" - }, - { - "author_name": "Jonathan Meiman", - "author_inst": "Wisconsin Department of Health Services" - }, - { - "author_name": "James Borchers", - "author_inst": "Ohio State University" + "author_name": "Brian E Dixon", + "author_inst": "IU Fairbanks School of Public Health and Regenstrief Institute" }, { - "author_name": "Ryan P Westergaard", - "author_inst": "Wisconsin Department of Health Services" + "author_name": "Shaun J Grannis", + "author_inst": "IU School of Medicine and Regenstrief Institute" }, { - "author_name": "Michael K Moll", - "author_inst": "University of Wisconsin - Madison" + "author_name": "Lauren R Lembcke", + "author_inst": "Regenstrief Institute" }, { - "author_name": "Thomas Friedrich", - "author_inst": "University of Wisconsin Madison" + "author_name": "Anna R Roberts", + "author_inst": "Regenstrief Institute" }, { - "author_name": "David H O'Connor", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Peter J Embi", + "author_inst": "Regenstrief Institute" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.03.01.21252651", @@ -911077,69 +910928,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.02.21252746", - "rel_title": "Providing a safe, in-person, residential college experience during the COVID-19 pandemic", + "rel_doi": "10.1101/2021.03.02.21252290", + "rel_title": "HiSpike: A high-throughput cost effective sequencing method for the SARS-CoV-2 spike gene", "rel_date": "2021-03-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.02.21252746", - "rel_abs": "Due to the COVID-19 pandemic, higher education institutions were forced to make difficult decisions regarding the 2020-2021 academic year. Many institutions decided to have courses in an online remote format, others decided to attempt an in-person experience, while still others took a hybrid approach. Hope College (Holland, MI) decided that an in-person semester would be safer and more equitable for students. To achieve this at a residential college required broad collaboration across multiple stakeholders. Here, we share lessons learned and detail Hope Colleges model, including wastewater surveillance, comprehensive testing, contact tracing and isolation procedures, that allowed us to deliver on our commitment of an in-person, residential college experience.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.02.21252290", + "rel_abs": "The changing nature of the corona virus of the SARS-CoV-2 pandemic poses unprecedented challenges to the worlds health systems. New and virulent emerging spike gene variants, such as the UK 20I/501Y.V1 and South African 20H/501Y.V2, could jeopardize global efforts to produce immunity and reduce mortality. These challenges require effective real-time genomic surveillance solutions that the medical community can quickly adopt. The SARS-CoV-2 spike protein mediates host receptor recognition and entry into the cell and therefore, it is most susceptible to generation of variants with increased transmissibility and pathogenicity. The spike protein is also the primary target of neutralizing antibodies in COVID-19 patients and the most common antigen for induction of effective vaccine immunity. Therefore, tight monitoring of the spike protein gene variants is key to mitigating COVID-19 spread and vaccine escape mutants. Currently, the ARTIC method for SARS-CoV-2 whole genome sequencing is applied worldwide. However, this method commonly requires more than 96 hours (4-5 days) from start to finish and at present high sample sequence demands, sequencing resources are quickly exhausted. In this work, we present HiSpike, a method for high-throughput targeted next generation sequencing (NGS) of the spike gene. This simple three-step method can be completed in less than 30 hours and can sequence 10-fold more samples compared to the conventional ARTIC method and at a fraction of the cost. HiSpike was proven valid, and has identified, at high quality, multiple spike variants from real-time field samples, such as the UK and the South African variants. This method will certainly be effective in discovering future spike mutations. Therefore, running HiSpike for full sequencing of the spike gene of all positive SARS-CoV-2 samples could be considered for near real-time detection of known and emerging spike mutations as they evolve. HiSpike provides affordable sequencing options to help laboratories conserve resources, hence it provides a tool for widespread monitoring, that can support critical knowledge-based decisions.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Scott A Travis", - "author_inst": "Hope College" + "author_name": "Ephraim Fass", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" }, { - "author_name": "Aaron A Best", - "author_inst": "Hope College" + "author_name": "Gal Zizelski Valenci", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" }, { - "author_name": "Kristyn S Bochniak", - "author_inst": "Hope College" + "author_name": "Mor Rubinstein", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" }, { - "author_name": "Nicole D Dunteman", - "author_inst": "Hope College" + "author_name": "Paul Jeffrey Freidlin", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" }, { - "author_name": "Jennifer Fellinger", - "author_inst": "Hope College" + "author_name": "Shira Rosencwaig", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" }, { - "author_name": "Peter D Folkert", - "author_inst": "Hope College" + "author_name": "Ina Kutikov", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" }, { - "author_name": "Timothy Koberna", - "author_inst": "Hope College" + "author_name": "Robert Werner", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" }, { - "author_name": "Benjamin G Kopek", - "author_inst": "Hope College" + "author_name": "Nofar Ben-Tovim", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" }, { - "author_name": "Brent P Krueger", - "author_inst": "Hope College" + "author_name": "Efrat Bucris", + "author_inst": "Central Virology Laboratory, Israel Ministry of Health, Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel" }, { - "author_name": "Jeff Pestun", - "author_inst": "Hope College" + "author_name": "Neta S Zuckerman", + "author_inst": "Central Virology Laboratory, Israel Ministry of Health, Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel" }, { - "author_name": "Michael J Pikaart", - "author_inst": "Hope College" + "author_name": "Orna Mor", + "author_inst": "Central Virology Laboratory, Israel Ministry of Health, Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel" }, { - "author_name": "Cindy Sabo", - "author_inst": "Hope College" + "author_name": "Ella Mendelson", + "author_inst": "Central Virology Laboratory, Israel Ministry of Health, Chaim Sheba Medical Center, Tel-Hashomer, Ramat Gan, Israel" }, { - "author_name": "Alex J Schuitema", - "author_inst": "Hope College" + "author_name": "Zeev Dveyrin", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" + }, + { + "author_name": "Efrat Rorman", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" + }, + { + "author_name": "Israel Nissan", + "author_inst": "National Public Health Laboratory Tel Aviv, Israel Ministry of Health, Israel" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -912927,43 +912786,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.03.04.433849", - "rel_title": "Efficient Inhibition of SARS-CoV-2 Using Chimeric Antisense Oligonucleotides through RNase L Activation", + "rel_doi": "10.1101/2021.03.04.433658", + "rel_title": "Inhibiting SARS-CoV-2 infection in vitro by suppressing its receptor, angiotensin-converting enzyme 2, via aryl-hydrocarbon receptor signal", "rel_date": "2021-03-04", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.04.433849", - "rel_abs": "There is an urgent need for effective antiviral drugs to alleviate the current COVID-19 pandemic. Here, we rationally designed and developed chimeric antisense oligonucleotides to degrade envelope and spike RNAs of SARS-CoV-2. Each oligonucleotide comprises a 3 antisense sequence for target recognition and a 5-phosphorylated 2-5 poly(A)4 for guided ribonuclease L (RNase L) activation. Since RNase L can potently cleave single strand RNA during innate antiviral response, the improved degradation efficiency of chimeric oligonucleotides was twice as much as classic antisense oligonucleotides in Vero cells, for both SARS-CoV-2 RNA targets. In pseudovirus infection models, one of chimeric oligonucleotides targeting spike RNA achieved potent and broad-spectrum inhibition of both SARS-CoV-2 and its recently reported N501Y and/or {Delta}H69/{Delta}V70 mutants. These results showed that the constructed chimeric oligonucleotides could efficiently degrade pathogenic RNA of SARS-CoV-2 facilitated by immune activation, showing promising potentials as antiviral nucleic acid drugs for COVID-19.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.03.04.433658", + "rel_abs": "Since understanding molecular mechanisms of SARS-CoV-2 infection is extremely important for developing effective therapies against COVID-19, we focused on the internalization mechanism of SARS-CoV-2 via ACE2. Although cigarette smoke is generally believed to be harmful to the pathogenesis of COVID-19, cigarette smoke extract (CSE) treatments were surprisingly found to suppress the expression of ACE2 in HepG2 cells. We thus tried to clarify the mechanism of CSE effects on expression of ACE2 in mammalian cells. Because RNA-seq analysis suggested that suppressive effects on ACE2 might be inversely correlated with induction of the genes regulated by aryl hydrocarbon receptor (AHR), the AHR agonists 6-formylindolo(3,2-b)carbazole (FICZ) and omeprazole (OMP) were tested to assess whether those treatments affected ACE2 expression. Both FICZ and OMP clearly suppressed ACE2 expression in a dose-dependent manner along with inducing CYP1A1. Knock-down experiments indicated a reduction of ACE2 by FICZ treatment in an AHR-dependent manner. Finally, treatments of AHR agonists inhibited SARS-CoV-2 infection into Vero E6 cells as determined with immunoblotting analyses detecting SARS-CoV-2 specific nucleocapsid protein. We here demonstrate that treatment with AHR agonists, including CSE, FICZ, and OMP, decreases expression of ACE2 via AHR activation, resulting in suppression of SARS-CoV-2 infection in mammalian cells.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Xiaoxuan Su", - "author_inst": "State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University" + "author_name": "Keiji Tanimoto", + "author_inst": "Department of Radiation Disaster Medicine, Research Institute for Radiation Biology and Medicine, Hiroshima University" }, { - "author_name": "Wenxiao Ma", - "author_inst": "State Key Laboratory of Natural and Biomimetic Drugs, the School of Pharmaceutical Sciences, Peking University" + "author_name": "Kiichi Hirota", + "author_inst": "Department of Human Stress Response Science, Institute of Biomedical Science, Kansai Medical University" }, { - "author_name": "Boyang Cheng", - "author_inst": "State Key Laboratory of Natural and Biomimetic Drugs, the School of Pharmaceutical Sciences, Peking University" + "author_name": "Takahiro Fukazawa", + "author_inst": "Natural Science Center for Basic Research and Development, Hiroshima University" }, { - "author_name": "Qian Wang", - "author_inst": "State Key Laboratory of Natural and Biomimetic Drugs, the School of Pharmaceutical Sciences, Peking University" + "author_name": "Yoshiyuki Matsuo", + "author_inst": "Department of Human Stress Response Science, Institute of Biomedical Science, Kansai Medical University" + }, + { + "author_name": "Toshihito Nomura", + "author_inst": "Department of Virology, Graduate School of Biomedical and Health Sciences, Hiroshima University" + }, + { + "author_name": "Nazmul Tanuza", + "author_inst": "Department of Virology, Graduate School of Biomedical and Health Sciences, Hiroshima University" }, { - "author_name": "Demin Zhou", - "author_inst": "State Key Laboratory of Natural and Biomimetic Drugs, the School of Pharmaceutical Sciences, Peking University" + "author_name": "Nobuyuki Hirohashi", + "author_inst": "Department of Radiation Disaster Medicine, Research Institute for Radiation Biology and Medicine, Hiroshima University" }, { - "author_name": "Xinjing Tang", - "author_inst": "State Key Laboratory of Natural and Biomimetic Drugs, the School of Pharmaceutical Sciences, Peking University" + "author_name": "Hidemasa Bono", + "author_inst": "Program of Biomedical Science, Graduate School of Integrated Sciences for Life, Hiroshima University" + }, + { + "author_name": "Takemasa Sakakuchi", + "author_inst": "Department of Virology, Graduate School of Biomedical and Health Sciences, Hiroshima University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2021.03.04.433966", @@ -914973,21 +914844,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.03.02.21250607", - "rel_title": "Modeling University Reopening in Low Risk Countries During COVID-19", + "rel_doi": "10.1101/2021.03.03.21252286", + "rel_title": "Impact of COVID-19 pandemic on Black, Asian and Minority Ethnic (BAME) communities: a qualitative study on the perspectives of BAME community leaders", "rel_date": "2021-03-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.02.21250607", - "rel_abs": "The safety of students worldwide remains a key issue during COVID-19. The reopening of universities in high risk countries during Fall 2020 resulted in numerous outbreaks. While regular screening and testing on campus can prevent the transmission of SARS-CoV-2, they are extremely challenging to implement due to various reasons such as cost and logistics. However, for low risk countries with minimal to no community spread, our study suggests that universities can fully reopen without testing, if students self-quarantine for 14 days on arrival and adopt proper nonpharmaceutical interventions (NPIs). This alternative strategy might save institutions millions of dollars. We adopt agent-based simulation to model virus transmission on campus and test the effectiveness of several NPIs when school reopens. Assuming one initially infected student, results indicate that transmission between roommates causes the most infections with visitors, ground floors, and elevators, being the next main contributors. Limiting density and/or population are not impactful at flattening the curve. However, adopting masks, minimizing movement, and increasing the frequency of cleaning can effectively minimize infection and prevent outbreak, allowing for classes and activities to resume as normal.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.03.21252286", + "rel_abs": "ObjectivesThe aim of this study was to explore the perspectives of BAME community leaders in relation to - the impact of the COVID-19 pandemic on their communities; and BAME communitys perception, understanding and adherence to Government guidelines on COVID-19 public health measures.\n\nDesignA phenomenological approach was adopted using qualitative semi-structured interviews.\n\nSettingsCommunity organisations and places of worships in the West Midlands region of England.\n\nParticipantsCommunity leaders were recruited through organisations representing BAME communities and religious places of worship.\n\nResultsA total of 19 participants took part. Participants alluded to historical and structural differences for the observed disparities in COVID-19 morbidity and mortality. Many struggled with lockdown measures which impeded cultural and religious gatherings that were deemed to be integral to the community. Cultural and social practices led to many suffering on their own as discussion of mental health was still deemed a taboo within many communities. Many expressed their communitys reluctance to report symptoms for the fear of financial and physical health implications. They reported increase in hate crime which was deemed to be exacerbated due to perceived insensitive messaging from authority officials and historical structural biases. Access and adherence to government guidelines was an issue for many due to language and digital barriers. Reinforcement from trusted community and religious leaders encouraged adherence. Points of support such as food banks were vital in ensuring essential supplies during the pandemic. Many could not afford masks and sanitisers.\n\nConclusionThe study highlights the perceived impact of COVID-19 pandemic on BAME communities. Government agencies and public health agencies need to integrate with the community, and community leaders to penetrate the key messages and deliver targeted yet sensitive public health advice which incorporates cultural and religious practices. Addressing route cause of disparities is imperative to mitigate current and future pandemics.\n\nStrengths and limitations of this studyO_LITo our knowledge, this is the first study in England to investigate the understanding of risk and impact of COVID-19 using the perspectives of BAME community leaders.\nC_LIO_LIParticipants represented diverse BAME community organisations and places of worship.\nC_LIO_LIParticipant recruitment was limited to one of the seven regions within England with the highest proportion of BAME populations.\nC_LIO_LIResults may not be generalizable to any BAME communities not represented in the data.\nC_LI", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jing Yang (Sunny) Xi", - "author_inst": "Tsinghua University" + "author_name": "Fesani Mahmood", + "author_inst": "University of Birmingham" }, { - "author_name": "Wai Kin (Victor) Chan", - "author_inst": "Tsinghua University" + "author_name": "Dev Acharya", + "author_inst": "University of Wolverhampton" + }, + { + "author_name": "Kanta Kumar", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Vibhu Paudyal", + "author_inst": "University of Birmingham" } ], "version": "1", @@ -917127,63 +917006,79 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.28.21252648", - "rel_title": "Shifting research priorities in maternal and child health in the COVID-19 pandemic era in India: a renewed focus on systems strengthening", + "rel_doi": "10.1101/2021.03.01.21252652", + "rel_title": "Early effectiveness of COVID-19 vaccination with BNT162b2 mRNA vaccine and ChAdOx1 adenovirus vector vaccine on symptomatic disease, hospitalisations and mortality in older adults in England", "rel_date": "2021-03-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.28.21252648", - "rel_abs": "BackgroundThe remarkable progress seen in maternal and child health (MCH) in India over the past two decades has been impacted by setbacks from the COVID-19 pandemic. We aimed to undertake a rapid assessment to identify key priorities for public health research in MCH in India within the context and aftermath of the COVID-19 pandemic.\n\nMethodsA web-based survey was developed to identify top research priorities in MCH. It consisted of 26 questions on six broad domains: vaccine preventable diseases, outbreak preparedness, primary healthcare integration, maternal health, neonatal health, and infectious diseases. Key stakeholders were invited to participate between September and November 2020. Participants assigned importance on a 5-point Likert scale, and assigned overall ranks to each sub-domain research priority. Descriptive statistics were used to examine Likert scale responses, and a ranking analysis was done to obtain an \"average ranking score\" and identify the top research priority under each domain.\n\nResultsAmongst the 84 respondents, 37% were public-health researchers, 25% healthcare providers, 20% academic faculty and 13% were policy makers. Across the six domains, most respondents considered conducting research on systems strengthening as extremely important. The highest ranked research priorities were strengthening the public sector workforce (vaccine preventable diseases), enhancing public-health surveillance networks (outbreak preparedness), nutrition support through community workers (primary care integration), encouraging at least 4-8 antenatal visits (maternal health), neonatal resuscitation to reduce birth asphyxia (neonatal health) and pediatric and maternal screening and treatment of tuberculosis (infectious diseases). Common themes identified through open-ended questions were also systems strengthening priorities across domains.\n\nConclusionsThe overall focus for research priorities in MCH in India during the COVID-19 pandemic is on strengthening existing services and service delivery, rather than novel research. Our results highlight pivotal steps within the roadmap for advancing and sustaining maternal and child health gains during the ongoing COVID-19 pandemic and beyond.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.03.01.21252652", + "rel_abs": "ObjectivesTo estimate the real-world effectiveness of the Pfizer/BioNTech BNT162b2 vaccine and Astrazeneca ChAdOx1 vaccine against Confirmed COVID-19, hospitalisations and deaths. To estimate effectiveness on the UK variant of concern.\n\nDesignTest negative case control design\n\nSettingCommunity COVID-19 PCR testing in England\n\nParticipantsAll adults in England aged 70 years and older (over 7.5 million). All COVID-19 testing in the community among eligible individuals who reported symptoms between 8th December 2020 and 19th February 2021 was included in the analysis.\n\nInterventionsOne and two doses of BNT162b2 vaccine. One dose of ChAdOx1 vaccine.\n\nMain outcome measuresSymptomatic PCR confirmed SARS-CoV-2 infection, hospitalisations and deaths with COVID-19.\n\nResultsIndividuals aged >=80 years vaccinated with BNT162b2 prior to 4th January, had a higher odds of testing positive in the first 9 days after vaccination (odds ratio up to 1.48, 95%CI 1.23-1.77), indicating that those initially targeted had a higher underlying risk of infection. Vaccine effectiveness was therefore estimated relative to the baseline post-vaccination period. Vaccine effects were noted from 10-13 days after vaccination, reaching an effectiveness of 70% (95% CI 59-78%) from 28-34 days, then plateauing. From 14 days after the second dose a vaccine effectiveness of 89% (95%CI: 85-93%) was seen.\n\nIndividuals aged >=70 years vaccinated from 4th January had a similar underlying risk of COVID-19 to unvaccinated individuals. With BNT162b2, vaccine effectiveness reached 61% (95%CI 51-69%) from 28-34 days after vaccination then plateaued. With the ChAdOx1 vaccine, vaccine effects were seen from 14-20 days after vaccination reaching an effectiveness of 60% (95%CI 41-73%) from 28-34 days and further increasing to 73% (95%CI 27-90%) from day 35 onwards.\n\nOn top of the protection against symptomatic disease, cases who had been vaccinated with one dose of BNT162b2 had an additional 43% (95%CI 33-52%) lower risk of emergency hospitalisation and an additional 51% (95%CI 37-62%) lower risk of death. Cases who had been vaccinated with one dose of ChAdOx1 had an additional 37% (95% CI 3-59%) lower risk of emergency hospitalisation. There was insufficient follow-up to assess the effect of ChAdOx1 on mortality due to the later rollout of this vaccine. Combined with the effect against symptomatic disease, this indicates that a single dose of either vaccine is approximately 80% effective at preventing hospitalisation and a single dose of BNT162b2 is 85% effective at preventing death with COVID-19.\n\nConclusionVaccination with either a single dose of BNT162b2 or ChAdOx1 COVID-19 vaccination was associated with a significant reduction in symptomatic SARS-CoV2 positive cases in older adults with even greater protection against severe disease. Both vaccines show similar effects. Protection was maintained for the duration of follow-up (>6 weeks). A second dose of BNT162b2 provides further protection against symptomatic disease but second doses of ChAdOx1 have not yet been rolled out in England. There is a clear effect of the vaccines against the UK variant of concern.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Kayur Mehta", - "author_inst": "Johns Hopkins University" + "author_name": "Jamie Lopez Bernal", + "author_inst": "Public Health England, London, United Kingdom" }, { - "author_name": "Sanjay Zodpey", - "author_inst": "Public Health Foundation of India" + "author_name": "Nick Andrews", + "author_inst": "Public Health England, London, United Kingdom" }, { - "author_name": "Preetika Banerjee", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Charlotte Gower", + "author_inst": "Public Health England, London, United Kingdom" }, { - "author_name": "Stephanie L Pocius", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Julia Stowe", + "author_inst": "Public Health England, London, United Kingdom" }, { - "author_name": "Baldeep Dhaliwal", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Chris Robertson", + "author_inst": "Public Health Scotland, Glasgow, United Kingdom" }, { - "author_name": "Andrea DeLuca", - "author_inst": "Amuptee Coalition" + "author_name": "Elise Tessier", + "author_inst": "Public Health England, London, United Kingdom" }, { - "author_name": "Sangeeta Das Bhattacharya", - "author_inst": "Indian Institute of Technology Kharagpur" + "author_name": "Ruth Simmons", + "author_inst": "Public Health England, London, United Kingdom" }, { - "author_name": "Shailendra Hegde", - "author_inst": "Piramal Swasthya" + "author_name": "Simon Cottrell", + "author_inst": "Public Health Wales, Cardiff, United Kingdom" }, { - "author_name": "Paramita Sengupta", - "author_inst": "All India Institute of Medical Sciences Kalyani" + "author_name": "Richard Robertson", + "author_inst": "Public Health Wales, Cardiff, United Kingdom" }, { - "author_name": "MADHU GUPTA", - "author_inst": "postgraduate institute of medical education and research" + "author_name": "Mark O'Doherty", + "author_inst": "Public Health Agency Northern Ireland, Belfast, United Kingdom" }, { - "author_name": "Anita Shet", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Kevin Brown", + "author_inst": "Public Health England, London, United Kingdom" + }, + { + "author_name": "Claire Cameron", + "author_inst": "Public Health Scotland, Glasgow, United Kingdom" + }, + { + "author_name": "Diane Stockton", + "author_inst": "Public Health Scotland, Glasgow, United Kingdom" + }, + { + "author_name": "Jim McMenamin", + "author_inst": "Public Health Scotland, Glasgow, United Kingdom" + }, + { + "author_name": "Mary Ramsay", + "author_inst": "Public Health England, London, United Kingdom" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.28.21252628", @@ -918997,59 +918892,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.27.21252593", - "rel_title": "Surgical activity in England and Wales during the COVID-19 pandemic: a nationwide observational cohort study", + "rel_doi": "10.1101/2021.02.26.21252497", + "rel_title": "Impact of the COVID-19 pandemic on cognitive function in Japanese community-dwelling older adults in a class for preventing cognitive decline", "rel_date": "2021-03-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.27.21252593", - "rel_abs": "ObjectivesTo report the volume of surgical activity and the number of cancelled surgical procedures during the COVID-19 pandemic.\n\nDesign and settingAnalysis of electronic health record data from the National Health Service (NHS) in England and Wales.\n\nMethodsWe used hospital episode statistics for all adult patients undergoing surgery between 1st January 2020 and 31st December 2020. We identified surgical procedures using a previously published list of procedure codes. Procedures were stratified by urgency of surgery as defined by NHS England. We calculated the deficit of surgical activity by comparing the expected number of procedures from the years 2016-2019 with the actual number of procedures in 2020. We estimated the cumulative number of cancelled procedures by 31st December 2021 according patterns of activity in 2020.\n\nResultsThe total number of surgical procedures carried out in England and Wales in 2020 was 3,102,674 compared to the predicted number of 4,671,338. This represents a 33.6% reduction in the national volume of surgical activity. There were 763,730 emergency surgical procedures (13.4% reduction), compared to 2,338,944 elective surgical procedures (38.6% reduction). The cumulative number of cancelled or postponed procedures was 1,568,664. We estimate that this will increase to 2,358,420 by 31st December 2021.\n\nConclusionsThe volume of surgical activity in England and Wales was reduced by 33.6% in 2020, resulting in over 1,568,664 cancelled operations. This deficit will continue to grow in 2021.\n\nSummary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSO_LIThe COVID-19 pandemic necessitated a rapid change in the provision of care, including the suspension of a large proportion of surgical activity\nC_LIO_LISurgical activity has yet to return to normal and has been further impacted by subsequent waves of the pandemic\nC_LIO_LIThis will lead to a large backlog of cases\nC_LI\n\nWhat this study addsO_LI3,102,674 surgical procedures were performed in England and Wales during 2020, a 33.6% reduction on the expected yearly surgical activity\nC_LIO_LIOver 1.5 million procedures were not performed, with this deficit likely to continue to grow to 2.3 million by the end of 2021\nC_LIO_LIThis deficit is the equivalent of more than 6 months of pre-pandemic surgical activity, requiring a monumental financial and logistic challenge to manage\nC_LI", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.26.21252497", + "rel_abs": "We examined the effects of lifestyle and thoughts on cognitive function and change in cognitive function due to restrictions in daily life during the coronavirus disease 2019 (COVID-19) pandemic in community-dwelling older adults with mild cognitive decline. This was a retrospective case-control study. The participants were 88 older adults with mild cognitive decline who participated in a class designed to help prevent cognitive decline. The class was suspended from early-March to end of May 2020 to prevent the spread of COVID-19, and resumed in June 2020. We collected demographic and cognitive function test data (Touch Panel-type Dementia Assessment Scale [TDAS]) before and after class suspension and questionnaire data on their lifestyle and thoughts during the suspension. Change in TDAS scores from before and after the suspension was used to divide the participants into decline (2 or more points worsening) and non-decline (all other participants) groups, with 16 (18.2%) and 72 (81.8%) participants in each group, respectively. A logistic regression model showed that the odds ratio (OR) for cognitive decline was lower in participants whose responses were \"engaged in hobbies\" (OR = 0.07, p = 0.015), \"worked on a worksheet about cognitive training provided by the town hall\" (OR = 0.19, p = 0.026), and \"had conversations over the phone\" (OR = 0.28, p = 0.0495). There was a significant improvement in TDAS scores after class was resumed (p < 0.01). A proactive approach to intellectual activities and social ties may be important for the prevention of cognitive decline during periods of restrictions due to COVID-19. We found that cognitive function test scores before class suspension significantly improved after resuming classes. We speculate that continued participation in the class led to positive behavioral changes in daily life during periods of restriction due to COVID-19.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Thomas D Dobbs", - "author_inst": "Swansea University Medical School" - }, - { - "author_name": "John A G Gibson", - "author_inst": "Swansea University Medical School" - }, - { - "author_name": "Alexander J Fowler", - "author_inst": "Queen Mary, University of London" - }, - { - "author_name": "Tom E Abbott", - "author_inst": "Queen Mary University of London" - }, - { - "author_name": "Tasnin Shahid", - "author_inst": "Queen Mary University of London" - }, - { - "author_name": "Fatemeh Torabi", - "author_inst": "Swansea University" - }, - { - "author_name": "Rowena Griffiths", - "author_inst": "Swansea University" + "author_name": "Minoru Kouzuki", + "author_inst": "Tottori University" }, { - "author_name": "Ronan A Lyons", - "author_inst": "Swansea University" + "author_name": "Shota Furukawa", + "author_inst": "Tottori University" }, { - "author_name": "Rupert M Pearse", - "author_inst": "Queen Mary University of London" + "author_name": "Keisuke Mitani", + "author_inst": "Tottori University" }, { - "author_name": "Iain S Whitaker", - "author_inst": "Swansea University Medical School" + "author_name": "Katsuya Urakami", + "author_inst": "Tottori University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "surgery" + "category": "geriatric medicine" }, { "rel_doi": "10.1101/2021.02.27.21252596", @@ -920855,51 +920726,71 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2021.02.27.21252577", - "rel_title": "Nationwide rollout reveals efficacy of epidemic control through digital contact tracing", + "rel_doi": "10.1101/2021.02.09.21249859", + "rel_title": "A precise score for the regular monitoring of COVID-19 patients condition validated within the first two waves of the pandemic", "rel_date": "2021-03-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.27.21252577", - "rel_abs": "Fueled by epidemiological studies of SARS-CoV-2, contact tracing by mobile phones has been put to use in many countries. A year into the pandemic, we lack conclusive evidence on its effectiveness. Here, we used a unique real world contact data set, collected during the rollout of the first Norwegian contact tracing app in the Spring of 2020, to address this gap. Our dataset involves millions of contacts between 12.5% of the adult population, and enabled us to measure the real-world app performance. The technological tracing efficacy was measured at 80%, and we estimated that at least 11.0% of the discovered close contacts could not be identified by manual contact tracing. The overall effectiveness of digital tracing depends strongly on app uptake, but significant impact can be achieved for moderate uptake numbers. Used as a supplement to manual tracing and other measures, digital tracing can be instrumental in controlling the pandemic. Our findings can thus help informing public health policies in the coming months.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.09.21249859", + "rel_abs": "PurposeThe sudden outbreak of COVID-19 pandemic have shown that medical community needs an accurate and interpretable aggregated score not only for an outcome prediction but also for a daily patients condition assessment. Due to a continuously changing pandemic landscape, a robustness becomes a crucial additional requirement for the score.\n\nMaterials and methodsIn this research a real-world data collected within the first two waves of COVID-19 pandemic was used. The first wave data (1349 cases collected from 27.04.2020 to 03.08.2020) was used as a training set for the score development, while the second wave data (1453 cases collected from 01.11.2020 to 19.01.2021) was used as a validating set. For all the available patients features we tested their association with an outcome using a robust linear regression. Statistically significant features were taken to the further analysis for each of which their partial sensitivity, specificity and promptness were estimated. The sensitivity and the specificity were further combined into a feature informativeness index.\n\nResultsThe developed score was derived as a weighted sum of the following 9 features showed the best trade-off between informativeness and promptness: APTT (> 42 sec, 4 points), CRP (> 146 mg/L, 3 points), D-dimer (> 2149 mkg/L, 4 points), Glucose (> 9 mmol/L, 4 points), Hemoglobin (< 115 g/L, 3 points), Lymphocytes (< 0,7*10^9/L, 3 points), Total protein (< 61 g/L, 6 points), Urea (> 11 mmol/L, 5 points) and WBC (> 13,5*10^9/L, 4 points). Thus, the proposed score ranges between 0 and 36 points. Internal and temporal validation showed that sensitivity and specificity over 90% may be achieved with an expected prediction range >7 days. Moreover, we demonstrated a high robustness of the score to the varying peculiarities of the pandemic. For the additional simplicity of application we split the full range of the score into five grades delimited with 9, 14, 19 and 24 points which determine expected death:discharge odds 1:100, 1:25, 1:5 and 1:1 correspondingly.\n\nConclusionsAn extensive application of the score within the second wave of COVID-19 pandemic showed its potential for the optimization of patients management as well as improvement of medical staff attentiveness during a high workload stress. The transparent structure of the score as well as tractable cut-off bounds simplified its implementation into a clinical practice.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Ahmed Elmokashfi", - "author_inst": "Simula Metropolitan CDE" + "author_name": "Evgeny A. Bakin", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" }, { - "author_name": "Joakim Sundnes", - "author_inst": "Simula Research Lab" + "author_name": "Oksana V. Stanevich", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" }, { - "author_name": "Amund Kvalbein", - "author_inst": "Simula Metropolitan CDE" + "author_name": "Vasiliy A. Belash", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" }, { - "author_name": "Valeriya Naumova", - "author_inst": "Simula Metropolitan CDE" + "author_name": "Anastasia A. Belash", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" }, { - "author_name": "Sven-Arne Reinemo", - "author_inst": "Simula Metropolitan CDE" + "author_name": "Galina A. Savvateeva", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" }, { - "author_name": "Per Magne Florvaag", - "author_inst": "Simula Research Lab" + "author_name": "Veronika A. Bokinova", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" }, { - "author_name": "H\u00e5kon Kvale Stensland", - "author_inst": "Simula Research Lab, University of Oslo" + "author_name": "Natalia A. Arsentieva", + "author_inst": "Saint Petersburg Pasteur Institute" }, { - "author_name": "Olav Lysne", - "author_inst": "Simula Metropolitan CDE and Oslo Metropolitan University" + "author_name": "Ludmila F. Sayenko", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" + }, + { + "author_name": "Evgeny A. Korobenkov", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" + }, + { + "author_name": "Dmitry A. Lioznov", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" + }, + { + "author_name": "Areg A. Totolian", + "author_inst": "Saint Petersburg Pasteur Institute" + }, + { + "author_name": "Yury S. Polushin", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" + }, + { + "author_name": "Alexander N. Kulikov", + "author_inst": "First Pavlov State Medical University, Saint-Petersburg, Russia" } ], - "version": "1", - "license": "cc_by_nd", + "version": "2", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.24.21252355", @@ -922425,25 +922316,49 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2021.02.26.21252553", - "rel_title": "Vaccination and herd immunity thresholds in heterogeneous populations", + "rel_doi": "10.1101/2021.02.27.21252583", + "rel_title": "Predicting the effects of COVID-19 related interventions in urban settings by combining activity-based modelling, agent-based simulation, and mobile phone data", "rel_date": "2021-03-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.26.21252553", - "rel_abs": "It has been suggested, without rigorous mathematical analysis, that the classical vaccine-induced herd immunity threshold (HIT) assuming a homogeneous population can be substantially higher than the minimum HIT obtained when considering population heterogeneities. We investigated this claim by developing, and rigorously analyzing, a vaccination model that incorporates various forms of heterogeneity and compared it with a model of a homogeneous population. By employing a two-group vaccination model in heterogeneous populations, we theoretically established conditions under which heterogeneity leads to different HIT values, depending on the relative values of the contact rates for each group, the type of mixing between groups, relative vaccine efficacy, and the relative population size of each group. For example, under biased random mixing and when vaccinating a given group results in disproportionate prevention of higher transmission per capita, it is optimal to vaccinate that group before vaccinating other groups. We also found situations, under biased assortative mixing assumption, where it is optimal to vaccinate more than one group. We show that regardless of the form of mixing between groups, the HIT values assuming a heterogeneous population are always lower than the HIT values obtained from a corresponding model with a homogeneous population. Using realistic numerical examples and parametrization (e.g., assuming assortative mixing together with vaccine efficacy of 95% and basic reproduction number of 2.5), we demonstrate that the HIT value considering heterogeneity (e.g., biased assortative mixing) is significantly lower (40%) compared with a HIT value of (63%) assuming a homogeneous population.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.27.21252583", + "rel_abs": "Epidemiological simulations as a method are used to better understand and predict the spreading of infectious diseases, for example of COVID-19.\n\nThis paper presents an approach that combines a well-established approach from transportation modelling that uses person-centric data-driven human mobility modelling with a mechanistic infection model and a person-centric disease progression model. The model includes the consequences of different room sizes, air exchange rates, disease import, changed activity participation rates over time (coming from mobility data), masks, indoors vs. outdoors leisure activities, and of contact tracing. The model is validated against the infection dynamics in Berlin (Germany).\n\nThe model can be used to understand the contributions of different activity types to the infection dynamics over time. The model predicts the effects of contact reductions, school closures/vacations, masks, or the effect of moving leisure activities from outdoors to indoors in fall, and is thus able to quantitatively predict the consequences of interventions. It is shown that these effects are best given as additive changes of the reinfection rate R. The model also explains why contact reductions have decreasing marginal returns, i.e. the first 50% of contact reductions have considerably more effect than the second 50%.\n\nOur work shows that is is possible to build detailed epidemiological simulations from microscopic mobility models relatively quickly. They can be used to investigate mechanical aspects of the dynamics, such as the transmission from political decisions via human behavior to infections, consequences of different lockdown measures, or consequences of wearing masks in certain situations. The results can be used to inform political decisions.\n\nAuthor summaryEvidently, there is an interest in models that are able to predict the effect of interventions in the face of pandemic diseases. The so-called compartmental models have difficulties to include effects that stem from spatial, demographic or temporal inhomongeneities. Person-centric models, often using social contact matrices, are difficult and time-consuming to build up. In the present paper, we describe how we built a largely data-driven person-centric infection model within less than a month when COVID-19 took hold in Germany. The model is based on our extensive experience with mobility modelling, and a synthetic data pipeline that starts with mobile phone data, while taking the infection dynamics and the disease progression from the literature. The approach makes the model portable to all places that have similar so-called activity-based models of travel in place, which are many places world-wide, and the number is continuously increasing. The model has been used since its inception to regularly advise the German government on expected consequences of interventions.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Elamin H Elbasha", - "author_inst": "Merck Inc." + "author_name": "Sebastian A. M\u00fcller", + "author_inst": "TU Berlin" }, { - "author_name": "Abba B. Gumel", - "author_inst": "Arizona State University" + "author_name": "Michael Balmer", + "author_inst": "Senozon AG" + }, + { + "author_name": "William Charlton", + "author_inst": "TU Berlin" + }, + { + "author_name": "Ricardo Ewert", + "author_inst": "TU Berlin" + }, + { + "author_name": "Andreas Neumann", + "author_inst": "Senozon GmbH" + }, + { + "author_name": "Christian Rakow", + "author_inst": "TU Berlin" + }, + { + "author_name": "Tilmann Schlenther", + "author_inst": "TU Berlin" + }, + { + "author_name": "Kai Nagel", + "author_inst": "TU Berlin" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -924227,57 +924142,97 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.02.24.21252135", - "rel_title": "Risk factors for increased COVID-19 case-fatality in the United States: A county-level analysis during the first wave", + "rel_doi": "10.1101/2021.02.24.21252316", + "rel_title": "A national mixed-mode seroprevalence random population-based cohort on SARS-CoV-2 epidemic in France: the socio-epidemiological EpiCov study", "rel_date": "2021-02-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.24.21252135", - "rel_abs": "The ongoing COVID-19 pandemic is causing significant morbidity and mortality across the US. In this ecological study, we identified county-level variables associated with the COVID-19 case-fatality rate (CFR) using publicly available datasets and a negative binomial generalized linear model. Variables associated with decreased CFR included a greater number of hospitals per 10,000 people, banning religious gatherings, a higher percentage of people living in mobile homes, and a higher percentage of uninsured people. Variables associated with increased CFR included a higher percentage of the population over age 65, a higher percentage of Black or African Americans, a higher asthma prevalence, and a greater number of hospitals in a county. By identifying factors that are associated with COVID-19 CFR in US counties, we hope to help officials target public health interventions and healthcare resources to locations that are at increased risk of COVID-19 fatalities.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.24.21252316", + "rel_abs": "Backgroundthe EpiCov study, initiated at the end of the first national lockdown in France, aimed to provide national and regional estimates of the seroprevalence of SARS-CoV-2 infection, and to analyze relations between living conditions and the dynamics of the epidemic. We present and discuss here the survey methodology, and describe the first-round fieldwork.\n\nMethod371,000 individuals aged 15 years or more were randomly selected from the national tax register, stratified by departments, including three overseas departments, and by poverty level with over-representation of people living below the poverty line. Health, socio-economics, migration history, and living conditions were collected through self-computed-assisted web interviews or via computer-assisted telephone interviews. The first-round survey was conducted in May. A random subsample was eligible to receive material for home blood self-sample on dried blood spot (DBS), in order to detect IgG antibodies against the spike protein (Euroimmun ELISA-S), and neutralizing antibodies for non-negative ELISA-S. For the second-round conducted in November, all respondents were eligible for the antibodies detection from home DBS sample, as well as the other household members aged 6 years or more for 20% of them.\n\nParticipation and adjustment for nonresponse134,391 respondents completed the first-round questionnaire from May 2 to June 1, 2020, including 16,970 (12.6%) respondents under the poverty line. Multimodal web/tel interviews was randomly assigned to 20% of the sample. The other were assigned to exclusive CAWI. Overall 17,441 respondents were eligible for home blood sample, among them 12,114 returned the DBS (interquartile date: May 25-June 5). The response probability was first estimated from logit models adjusted on a wide range of auxiliary demographic and socio-economic variables available from the sampling frame, and final weights calibrated to the margins of the population census permitted to correct for a large part of the non-response bias.\n\nConclusionThe Epicov study is one of the largest national random population-based seroprevalence cohort, with both an epidemiological and sociological approaches to evaluate the spread of the COVID-19 epidemic, and the impact on health and living conditions. One of the major interests of this study is the broad coverage of the socio-economic and territorial diversity of the population.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Jess A. Millar", - "author_inst": "University of Michigan" + "author_name": "Josiane WARSZAWSKI", + "author_inst": "Inserm CESP U1018 - UMRS 1018, Universit\u00e9 Paris-Saclay - AP-HP, Epidemiology and Public Health Service, Le Kremlin-Bicetre, France" }, { - "author_name": "Hanh Dung N. Dao", - "author_inst": "University of Oklahoma Health Sciences Center" + "author_name": "Nathalie BAJOS", + "author_inst": "IRIS, INSERM, EHESS, CNRS Aubervilliers, France" }, { - "author_name": "Marianne E. Stefopulos", - "author_inst": "Child Health Evaluative Sciences Program, SickKids Hospital" + "author_name": "Muriel BARLET", + "author_inst": "DREES - Direction de la Recherche, Etudes, Evaluation et Statistiques, Paris, France" }, { - "author_name": "Camila G. Estevam", - "author_inst": "State University of Campinas" + "author_name": "Xavier de LAMBALLERIE", + "author_inst": "Unit\u00e9 des Virus Emergents, UVE, Aix Marseille Univ, IRD 190, INSERM 1207, IHU M\u00e9 diterranee Infection, Marseille, France" }, { - "author_name": "Katharine Fagan-Garcia", - "author_inst": "University of Alberta" + "author_name": "Delphine RAHIB", + "author_inst": "Sant\u00e9 Publique France, Saint-Maurice France" }, { - "author_name": "Diana H. Taft", - "author_inst": "University of California Davis" + "author_name": "Nathalie LYDIE", + "author_inst": "Sant\u00e9 Publique France, Saint-Maurice France" }, { - "author_name": "Christopher Park", - "author_inst": "New York University" + "author_name": "Sylvain DURRLEMAN", + "author_inst": "Institut th\u00e9matique de Sant\u00e9 Publique, INSERM, Paris France" }, { - "author_name": "Amaal Alruwaily", - "author_inst": "Independent Scholar" + "author_name": "Remy SLAMA", + "author_inst": "Institut th\u00e9matique de Sant\u00e9 Publique, Inserm, Paris, CNRS, Team of Environmental Epidemiology applied to Reproduction and Respiratory Health, Institute for Adv" }, { - "author_name": "Angel N. Desai", - "author_inst": "University of California Davis Medical Center" + "author_name": "Remonie SENG", + "author_inst": "AP-HP Epidemiology and Public Health Service, Paris-Saclay, Le Kremlin-Bicetre, France" }, { - "author_name": "Maimuna S. Majumder", - "author_inst": "Harvard Medical School and Boston Children's Hospital" + "author_name": "Philippe RAYNAUD", + "author_inst": "DREES - Direction de la Recherche, des Etudes, Evaluation et Statistiques, Paris, France" + }, + { + "author_name": "Aude LEDUC", + "author_inst": "DREES - Direction de la Recherche, des Etudes, Evaluation et Statistiques, Paris, France" + }, + { + "author_name": "Guillaume BAGEIN", + "author_inst": "DREES - Direction de la Recherche, des Etudes, Evaluation et Statistiques, Paris, France" + }, + { + "author_name": "Nicolas PALIOD", + "author_inst": "INSEE - Institut National de la Statistique et des Etudes Economiques, Montrouge, France" + }, + { + "author_name": "Stephane LEGLEYE", + "author_inst": "INSEE - Institut National de la Statistique et des Etudes Economiques, Montrouge, and INSERM CESP U1018, Univ Paris-Saclay, Le Kremlin-Bicetre, France" + }, + { + "author_name": "Cyril FAVRE-MARTINOZ", + "author_inst": "INSEE - Institut National de la Statistique et des Etudes Economiques, Montrouge, France" + }, + { + "author_name": "Laura CASTELL", + "author_inst": "INSEE - Institut National de la Statistique et des Etudes Economiques, Montrouge, France" + }, + { + "author_name": "Patrick SILLARD", + "author_inst": "INSEE - Institut National de la Statistique et des Etudes Economiques, Montrouge, France" + }, + { + "author_name": "Laurence Meyer", + "author_inst": "Inserm CESP U1018 - UMRS 1018, Universit\u00e9 Paris-Saclay - AP-HP, Epidemiology and Public Health Service, Le Kremlin-Bicetre, France" + }, + { + "author_name": "Francois BECK", + "author_inst": "INSEE - Institut National de la Statistique et des Etudes Economiques, Montrouge, and INSERM CESP U1018, Univ Paris-Saclay, Le Kremlin-Bicetre, France" + }, + { + "author_name": "- The EPICOV study group", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -926297,59 +926252,55 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2021.02.25.432762", - "rel_title": "The type 2 asthma mediator IL-13 inhibits SARS-CoV-2 infection of bronchial epithelium", + "rel_doi": "10.1101/2021.02.22.21252240", + "rel_title": "Non-pharmaceutical interventions and inoculation rate shape SARS-COV-2 vaccination campaign success", "rel_date": "2021-02-25", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.25.432762", - "rel_abs": "RationaleAsthma is associated with chronic changes in the airway epithelium, a key target of SARS-CoV-2. Many epithelial changes are driven by the type 2 cytokine IL-13, but the effects of IL-13 on SARS-CoV-2 infection are unknown.\n\nObjectivesWe sought to discover how IL-13 and other cytokines affect expression of genes encoding SARS-CoV-2-associated host proteins in human bronchial epithelial cells (HBECs) and determine whether IL-13 stimulation alters susceptibility to SARS-CoV-2 infection.\n\nMethodsWe used bulk and single cell RNA-seq to identify cytokine-induced changes in SARS-CoV-2-associated gene expression in HBECs. We related these to gene expression changes in airway epithelium from individuals with mild-moderate asthma and chronic obstructive pulmonary disease (COPD). We analyzed effects of IL-13 on SARS-CoV-2 infection of HBECs.\n\nMeasurements and Main ResultsTranscripts encoding 332 of 342 (97%) SARS-CoV-2-associated proteins were detected in HBECs ([≥]1 RPM in 50% samples). 41 (12%) of these mRNAs were regulated by IL-13 (>1.5-fold change, FDR < 0.05). Many IL-13-regulated SARS-CoV-2-associated genes were also altered in type 2 high asthma and COPD. IL-13 pretreatment reduced viral RNA recovered from SARS-CoV-2 infected cells and decreased dsRNA, a marker of viral replication, to below the limit of detection in our assay. Mucus also inhibited viral infection.\n\nConclusionsIL-13 markedly reduces susceptibility of HBECs to SARS-CoV-2 infection through mechanisms that likely differ from those activated by type I interferons. Our findings may help explain reports of relatively low prevalence of asthma in patients diagnosed with COVID-19 and could lead to new strategies for reducing SARS-CoV-2 infection.", - "rel_num_authors": 10, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252240", + "rel_abs": "Nearly one year into the COVID-19 pandemic, the first SARS-COV-2 vaccines received emergency use authorization and vaccination campaigns began. A number of factors can reduce the averted burden of cases and deaths due to vaccination. Here, we use a dynamic model, parametrized with Bayesian inference methods, to assess the effects of non-pharmaceutical interventions, and vaccine administration and uptake rates on infections and deaths averted in the United States. We estimate that high compliance with non-pharmaceutical interventions could avert more than 60% of infections and 70% of deaths during the period of vaccine administration, and that increasing the vaccination rate from 5 to 11 million people per week could increase the averted burden by more than one third. These findings underscore the importance of maintaining non-pharmaceutical interventions and increasing vaccine administration rates.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Luke R Bonser", - "author_inst": "UCSF" - }, - { - "author_name": "Walter L Eckalbar", - "author_inst": "UCSF" + "author_name": "Marta Galanti", + "author_inst": "Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University" }, { - "author_name": "Lauren Rodriguez", - "author_inst": "UCSF" + "author_name": "Sen Pei", + "author_inst": "Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University" }, { - "author_name": "Jiangshan Shen", - "author_inst": "UCSF" + "author_name": "Teresa K Yamana", + "author_inst": "Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University" }, { - "author_name": "Kyung Duk Koh", - "author_inst": "UCSF" + "author_name": "Frederick J Angulo", + "author_inst": "Medical Development and Scientific/Clinical Affairs, Pfizer Vaccines" }, { - "author_name": "Lorna T Zlock", - "author_inst": "UCSF" + "author_name": "Apostolos Charos", + "author_inst": "Patient and Health Impact, Pfizer Vaccines" }, { - "author_name": "Stephanie Christenson", - "author_inst": "UCSF" + "author_name": "Farid Khan", + "author_inst": "Medical Development and Scientific/Clinical Affairs, Pfizer Vaccines" }, { - "author_name": "Prescott G Woodruff", - "author_inst": "UCSF" + "author_name": "Kimberly Shea", + "author_inst": "Patient and Health Impact, Pfizer Vaccines" }, { - "author_name": "Walter E Finkbeiner", - "author_inst": "UCSF" + "author_name": "David Swerdlow", + "author_inst": "Medical Development and Scientific/Clinical Affairs, Pfizer Vaccines" }, { - "author_name": "David J Erle", - "author_inst": "UCSF" + "author_name": "Jeffrey Shaman", + "author_inst": "Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "cell biology" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2021.02.24.21252338", @@ -928015,77 +927966,105 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.02.24.432656", - "rel_title": "SARS-CoV-2 ORF6 disturbs nucleocytoplasmic trafficking to advance the viral replication", + "rel_doi": "10.1101/2021.02.24.432759", + "rel_title": "Implications of central carbon metabolism in SARS-CoV-2 replication and disease severity", "rel_date": "2021-02-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.24.432656", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the virus responsible for the coronavirus disease 2019 pandemic. ORF6 is known to antagonize the interferon signaling by inhibiting the nuclear translocation of STAT1. Here we show that ORF6 acts as a virulence factor through two distinct strategies. First, ORF6 directly interacts with STAT1 in an IFN-independent manner to inhibit its nuclear translocation. Second, ORF6 directly binds to importin 1, which is a nuclear transport factor encoded by KPNA2, leading to a significant suppression of importin 1-mediated nuclear transport. Furthermore, we found that KPNA2 knockout enhances the viral replication, suggesting that importin 1 suppresses the viral propagation. Additionally, the analyses of gene expression data revealed that importin 1 levels decreased significantly in the lungs of older individuals. Taken together, SARS-CoV-2 ORF6 disrupts the nucleocytoplasmic trafficking to accelerate the viral replication, resulting in the disease progression, especially in older individuals.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.24.432759", + "rel_abs": "Viruses hijack host metabolic pathways for their replicative advantage. Several observational trans-omics analyses associated carbon and amino acid metabolism in coronavirus disease 2019 (COVID-19) severity in patients but lacked mechanistic insights. In this study, using patient- derived multi-omics data and in vitro infection assays, we aimed to understand i) role of key metabolic pathways in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) reproduction and ii) its association with disease severity. Our data suggests that monocytes are key to the altered immune response during COVID-19. COVID-19 infection was associated with increased plasma glutamate levels, while glucose and mannose levels were determinants of the disease severity. Monocytes showed altered expression pattern of carbohydrate and amino acid transporters, GLUT1 and xCT respectively in severe COVID-19. Furthermore, lung epithelial cells (Calu-3) showed a strong acute metabolic adaptation following infection in vitro by modulating central carbon metabolism. We found that glycolysis and glutaminolysis are essential for virus replication and blocking these metabolic pathways caused significant reduction in virus production. Taken together, our study highlights that the virus utilizes and re-wires pathways governing central carbon metabolism leading to metabolic toxicity. Thus, the host metabolic perturbation could be an attractive strategy to limit the viral replication and disease severity.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Yoichi Miyamoto", - "author_inst": "National Institutes of Biomedical Innovation, Health and Nutrition" + "author_name": "Shuba Krishnan", + "author_inst": "Karolinska Institute" }, { - "author_name": "Yumi Itoh", - "author_inst": "Research Institute for Microbial Diseases, Osaka University" + "author_name": "Hampus Nordqvist", + "author_inst": "The South Hospital" }, { - "author_name": "Tatsuya Suzuki", - "author_inst": "Research Institute for Microbial Diseases, Osaka University" + "author_name": "Anoop T Ambikan", + "author_inst": "Karolinska Institute" }, { - "author_name": "Tomohisa Tanaka", - "author_inst": "Faculty of Medicine, University of Yamanashi" + "author_name": "Soham Gupta", + "author_inst": "Karolinska Institute" }, { - "author_name": "Yusuke Sakai", - "author_inst": "Yamaguchi University" + "author_name": "Maike Sperk", + "author_inst": "Karolinska Institute" }, { - "author_name": "Masaru Koido", - "author_inst": "The University of Tokyo" + "author_name": "Sara Svensson-Akusjarvi", + "author_inst": "Karolinska Institute" }, { - "author_name": "Chiaki Hata", - "author_inst": "Cell Engineering Corporation" + "author_name": "Flora Mikaeloff", + "author_inst": "Karolinska Institute" }, { - "author_name": "Cai-Xia Wan", - "author_inst": "Cell Engineering Corporation" + "author_name": "Rui Benfeitas", + "author_inst": "Stockholm University" }, { - "author_name": "Mayumi Otani", - "author_inst": "National Institutes of Biomedical Innovation, Health and Nutrition" + "author_name": "Elisa Saccon", + "author_inst": "Karolinska Institute" }, { - "author_name": "Kohji Moriishi", - "author_inst": "Faculty of Medicine, University of Yamanashi" + "author_name": "Sivasankaran M Ponnan", + "author_inst": "Indian Institute of Science" }, { - "author_name": "Taro Tachibana", - "author_inst": "Osaka City University" + "author_name": "Jimmy E Rodriguez", + "author_inst": "Karolinska Institute" }, { - "author_name": "Yoichiro Kamatani", - "author_inst": "The University of Tokyo" + "author_name": "Negin Nikouyan", + "author_inst": "Karolinska Institute" }, { - "author_name": "Yoshihiro Yoneda", - "author_inst": "National Institutes of Biomedical Innovation, Health and Nutrition" + "author_name": "Amani Odeh", + "author_inst": "Karolinska Institute" }, { - "author_name": "Toru Okamoto", - "author_inst": "Research Institute for Microbial Diseases, Osaka University" + "author_name": "Gustaf Ahlen", + "author_inst": "Karolinska Institute" }, { - "author_name": "Masahiro Oka", - "author_inst": "National Institutes of Biomedical Innovation, Health and Nutrition" + "author_name": "Muhammad Asghar", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Matti Sallberg", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Jan Vesterbacka", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Piotr Nowak", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Akos Vegvari", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Anders Sonnerborg", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Carl J Treutiger", + "author_inst": "Karolinska Institute" + }, + { + "author_name": "Ujjwal Neogi", + "author_inst": "Karolinska Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "new results", "category": "microbiology" }, @@ -929961,41 +929940,65 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.22.21251534", - "rel_title": "The spatio-temporal distribution of COVID-19 infection in England between January and June 2020.", + "rel_doi": "10.1101/2021.02.20.20248421", + "rel_title": "Nosocomial outbreak of SARS-CoV-2 in a 'non-COVID-19' hospital ward: virus genome sequencing as a key tool to understand cryptic transmission", "rel_date": "2021-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21251534", - "rel_abs": "The spatio-temporal dynamics of an outbreak provide important insights to help direct public health resources intended to control transmission. They also provide a focus for detailed epidemiological studies and allow the timing and impact of interventions to be assessed.\n\nA common approach is to aggregate case data to administrative regions. Whilst providing a good visual impression of change over space, this method masks spatial variation and assumes that disease risk is constant across space. Risk factors for COVID-19 (e.g. population density, deprivation and ethnicity) vary from place to place across England so it follows that risk will also vary spatially. Kernel density estimation compares the spatial distribution of cases relative to the underlying population, unfettered by arbitrary geographical boundaries, to produce a continuous estimate of spatially varying risk.\n\nUsing test results from healthcare settings in England (Pillar 1 of the UK Government testing strategy) and freely available methods and software, we estimated the spatial and spatio-temporal risk of COVID-19 infection across England for the first six months of 2020. Widespread transmission was underway when partial lockdown measures were introduced on the 23rd March 2020 and the greatest risk erred towards large urban areas. The rapid growth phase of the outbreak coincided with multiple introductions to England from the European mainland. The spatio-temporal risk was highly labile throughout.\n\nIn terms of controlling transmission, the most important practical application is the accurate identification of areas within regions that may require tailored intervention strategies. We recommend that this approach is absorbed into routine surveillance outputs in England. Further risk characterisation using widespread community testing (Pillar 2) data is needed as is the increased use of predictive spatial models at fine spatial scales.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.20.20248421", + "rel_abs": "BackgroundDissemination of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in healthcare institutions affects both patients and health-care workers (HCW), as well as the institutional capacity to provide essential health services.\n\nMethodsWe conducted an investigation of a cluster of SARS-CoV-2 positive cases detected in a \"non-COVID-19\" hospital ward during Summer 2020. The magnitude of the nosocomial outbreak was disclosed by massive testing, challenging the retrospective reconstruction of the introduction and transmission events. An in-depth contact tracing investigation was carried out to identify the contacts network during the 15-day period before the screening. In parallel, positive SARS-CoV-2 RNA samples were subjected to virus genome sequencing.\n\nResultsOf the 245 tested individuals, 48 (21 patients and 27 HCWs) tested positive for SARS-CoV-2. HCWs were mostly asymptomatic, but the mortality among the vulnerable patient group reached 57.1% (12/21). Phylogenetic reconstruction revealed that all cases were part of the same transmission chain, thus confirming a single origin behind this nosocomial outbreak. By combining vast epidemiological and genomic data, including analysis of emerging minor variants, we unveiled a scenario of silent SARS-CoV-2 dissemination within the hospital ward, mostly driven by the close contact within the HCWs group and between HCWs and patients. This investigation triggered enhanced prevention and control measures, leading to a more timely detection and containment of novel nosocomial outbreaks.\n\nConclusionsThe present study shows the benefit of combining genomic and epidemiological data for the investigation of complex nosocomial outbreaks, and provides valuable data to minimize the risk of transmission of COVID-19 in healthcare facilities.\n\nShort summarySARS-CoV-2 nosocomial outbreaks are of utmost public health concern. Here, we performed an in-depth investigation of a high-fatality rate nosocomial outbreak by combining vast genomic and epidemiological data, providing valuable information to understand cryptic transmission of SARS-CoV-2 within healthcare institutions.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Richard Elson", - "author_inst": "Public Health England" + "author_name": "Vitor Borges", + "author_inst": "Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal." }, { - "author_name": "Tilman M Davies", - "author_inst": "University of Otago" + "author_name": "Joana Isidro", + "author_inst": "Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal." }, { - "author_name": "Iain R Lake", - "author_inst": "University of East Anglia" + "author_name": "Filipe Macedo", + "author_inst": "Local Coordination Group for the Prevention and Control of Infections and Antimicrobial Resistance Program, Vila Franca de Xira Hospital, Vila Franca de Xira, P" }, { - "author_name": "Roberto Vivancos", - "author_inst": "Public Health England" + "author_name": "Jose Neves", + "author_inst": "Local Coordination Group for the Prevention and Control of Infections and Antimicrobial Resistance Program, Vila Franca de Xira Hospital, Vila Franca de Xira, P" }, { - "author_name": "Paula B Blomquist", - "author_inst": "Public Health England" + "author_name": "Luis Silva", + "author_inst": "Clinical Pathology Director, Vila Franca de Xira Hospital, Vila Franca de Xira, Portugal." }, { - "author_name": "Andre Charlett", - "author_inst": "Public Health England" + "author_name": "Mario Paiva", + "author_inst": "Clinical Director, Vila Franca de Xira Hospital, Vila Franca de Xira, Portugal." }, { - "author_name": "Gavin Dabrera", - "author_inst": "Public Health England" + "author_name": "Jose Barata", + "author_inst": "Internal Medicine Director, Vila Franca de Xira Hospital, Vila Franca de Xira, Portugal." + }, + { + "author_name": "Judite Catarino", + "author_inst": "Public Health Authority, Regional Health Administration of Lisbon and Tagus Valley, Health Centers Groups of Tagus Valley, Portugal." + }, + { + "author_name": "Liliana Ciobanu", + "author_inst": "Public Health Authority, Regional Health Administration of Lisbon and Tagus Valley, Health Centers Groups of Tagus Valley, Portugal." + }, + { + "author_name": "Silvia Duarte", + "author_inst": "Innovation and Technology Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal." + }, + { + "author_name": "Luis Vieira", + "author_inst": "Innovation and Technology Unit, Department of Human Genetics, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal; Centre for Toxicogenom" + }, + { + "author_name": "Raquel Guiomar", + "author_inst": "National Reference Laboratory for Influenza and other Respiratory Viruses, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge " + }, + { + "author_name": "Joao Paulo Gomes", + "author_inst": "Bioinformatics Unit, Department of Infectious Diseases, National Institute of Health Doutor Ricardo Jorge (INSA), Lisbon, Portugal." } ], "version": "1", @@ -932023,81 +932026,69 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2021.02.22.21252207", - "rel_title": "Critical COVID-19 represents an endothelial disease with high similarity to kidney disease on the molecular level", + "rel_doi": "10.1101/2021.02.22.21252236", + "rel_title": "High-resolution longitudinal serum proteome trajectories in COVID-19 reveal patients-specific seroconversion", "rel_date": "2021-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252207", - "rel_abs": "In patients with critical or mild COVID19 (WHO stages 6-8 [n=53] and stages 1-3 [n=66]), 593 urinary peptides significantly affected by disease severity were identified, reflecting the molecular pathophysiology associated with the course of the infection. The peptide profiles were similar compared with those observed in kidney disease, a prototype of target organ damage with major microvascular involvement, thereby confirming the observation that endothelial damage is a hallmark of COVID19. The clinical corollary is that COVID19 is an indication for anti-oxidative, anti-inflammatory and immunosuppressive treatment modalities protecting the endothelial lining.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.22.21252236", + "rel_abs": "Biomarkers for COVID-19 are urgently needed. Here we bring the powerful technology of mass spectrometry (MS)-based proteomics to bear on this challenge. We measured serum proteomes of COVID-19 patients and symptomatic, but PCR-negative controls, in a time-resolved manner. In 262 controls and 458 longitudinal samples (average of 31 days) of 31 patients, hospitalized for COVID-19, a remarkable 26% of proteins changed significantly. Bioinformatics analyses revealed co-regulated groups and shared biological functions. Proteins of the innate immune system such as CRP, SAA1, CD14, LBP and LGALS3BP decreased early in the time course. In contrast, regulators of coagulation (APOH, FN1, HRG, KNG1, PLG) and lipid homeostasis (APOA1, APOC1, APOC2, APOC3, PON1) increased over the course of the disease. A global correlation map provides a systems-wide functional association between proteins, biological processes and clinical chemistry parameters. Importantly, five SARS-CoV-2 immunoassays against antibodies revealed excellent correlations with an extensive range of immunoglobulin regions, which were quantified by MS-based proteomics. The high-resolution profile of all immunoglobulin regions showed individual-specific differences and commonalities of potential pathophysiological relevance.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC=\"FIGDIR/small/21252236v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (86K):\norg.highwire.dtl.DTLVardef@4f1770org.highwire.dtl.DTLVardef@8bdc12org.highwire.dtl.DTLVardef@1d4e21org.highwire.dtl.DTLVardef@1f49622_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIA total of 720 proteomes of 262 symptomatic controls and 458 longitudinal samples (average 31 days) of hospitalized COVID-19 cases were analyzed\nC_LIO_LI26% of the 502 quantified proteins significantly changed in COVID-19 patients\nC_LIO_LIThe innate immune and the coagulation system were strongly regulated\nC_LIO_LIMS-based profiles of immunoglobulin regions allow the detection of seroconversion in a highly detailed fashion on the patient level\nC_LIO_LIITIH4 may be a prospective marker of COVID-19 mortality\nC_LI", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Justyna Siwy", - "author_inst": "Mosaiques-Diagnostics GmbH" - }, - { - "author_name": "Ralph Wendt", - "author_inst": "Hospital St. Georg, Leipzig" - }, - { - "author_name": "Amaya Albalat", - "author_inst": "University of Stirling, /UK" + "author_name": "Philipp Emanuel Geyer", + "author_inst": "OmicEra Diagnostics GmbH" }, { - "author_name": "Tianlin He", - "author_inst": "Mosaiques Diagnostics" - }, - { - "author_name": "Harald Mischak", - "author_inst": "Mosaiques Diagnostics" + "author_name": "Florian Maxime Arend", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich" }, { - "author_name": "William Mullen", - "author_inst": "University of Glasgow" + "author_name": "Sophia Doll", + "author_inst": "OmicEra Diagnostics GmbH" }, { - "author_name": "Agnieszka Latosinska", - "author_inst": "Mosaiques Diagnostics" + "author_name": "Marie-Luise Louiset", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich" }, { - "author_name": "Christoph Luebbert", - "author_inst": "University Leipzig" + "author_name": "Sebastian Virreira Winter", + "author_inst": "OmicEra Diagnostics GmbH" }, { - "author_name": "Sven Kalbitz", - "author_inst": "Hospital St. Georg, Leipzig, Germany" + "author_name": "Johannes Bruno Mueller-Reif", + "author_inst": "OmicEra Diagnostics GmbH" }, { - "author_name": "Alexandre Mebazaa", - "author_inst": "Universite de Paris, Paris, France." + "author_name": "Furkan M. Torun", + "author_inst": "OmicEra Diagnostics GmbH" }, { - "author_name": "Bjoern Peters", - "author_inst": "Department of Nephrology, Skaraborg Hospital, Skoevde, Sweden" + "author_name": "Michael Weigand", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich" }, { - "author_name": "Bernd Stegmayr", - "author_inst": "Department of Public Health and Clinical Medicine, Umea University, Umea, Sweden" + "author_name": "Peter Eichhorn", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich" }, { - "author_name": "Goce Spasovski", - "author_inst": "Department of Nephrology, Medical Faculty, University St.Cyril and Methodius, Skopje, Republic of N. Macedonia" + "author_name": "Mathias Bruegel", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich" }, { - "author_name": "Thorsten Wiech", - "author_inst": "Nephropathology Section, Institute for Pathology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany" + "author_name": "Maximilian T. Strauss", + "author_inst": "OmicEra Diagnostics GmbH" }, { - "author_name": "Jan Staessen", - "author_inst": "Alliance for the Promotion of Preventive Medicine (APPREMED), Mechelen, Belgium." + "author_name": "Lesca M. Holdt", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich" }, { - "author_name": "Johannes Wolf", - "author_inst": "Department of Laboratory Medicine, Hospital St. Georg, Leipzig, Germany" + "author_name": "Matthias Mann", + "author_inst": "NNF Center for Protein Research, Faculty of Health Sciences, University of Copenhagen" }, { - "author_name": "Joachim Beige", - "author_inst": "Department of Infectious Diseases/Tropical Medicine, Nephrology and Rheumatology, Hospital St. Georg, Leipzig, Germany" + "author_name": "Daniel Teupser", + "author_inst": "Institute of Laboratory Medicine, University Hospital, LMU Munich" } ], "version": "1", @@ -933681,55 +933672,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.20.432081", - "rel_title": "Nanoceutical Fabric Prevents COVID-19 Spread through Expelled Respiratory Droplets: A Combined Computational, Spectroscopic and Anti-microbial Study", + "rel_doi": "10.1101/2021.02.22.432359", + "rel_title": "SARS-CoV-2 B.1.1.7 and B.1.351 Spike variants bind human ACE2 with increased affinity", "rel_date": "2021-02-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.20.432081", - "rel_abs": "Centers for Disease Control and Prevention (CDC) warns the use of one-way valves or vents in free masks for potential threat of spreading COVID-19 through expelled respiratory droplets. Here, we have developed a nanoceutical cotton fabric duly sensitized with non-toxic zinc oxide nanomaterial for potential use as membrane filter in the one way valve for the ease of breathing without the threat of COVID-19 spreading. A detailed computational study revealed that zinc oxide nanoflowers (ZnO NF) with almost two-dimensional petals trap SARS-CoV-2 spike proteins, responsible to attach to ACE-2 receptors in human lung epithelial cells. The study also confirm significant denaturation of the spike proteins on the ZnO surface, revealing removal of virus upon efficient trapping. Following the computational study, we have synthesized ZnO NF on cotton matrix using hydrothermal assisted strategy. Electron microscopic, steady-state and picosecond resolved spectroscopic studies confirm attachment of ZnO NF to the cotton (i.e., cellulose) matrix at atomic level to develop the nanoceutical fabric. A detailed antimicrobial assay using Pseudomonas aeruginosa bacteria (model SARS-CoV-2 mimic) reveals excellent anti-microbial efficiency of the developed nanoceutical fabric. To our understanding the novel nanoceutical fabric used in one-way valve of a face mask would be the choice to assure breathing comfort along with source control of COVID-19 infection. The developed nanosensitized cloth can also be used as antibacterial/anti CoV-2 washable dress material in general.\n\nGRAPHICAL ABSTRACT O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY\n\nA novel nanoceutical cotton fabric duly sensitized with non-toxic zinc oxide nanoflower can potentially be used as membrane filter in the one way valve of face mask to assure breathing comfort along with source control of COVID-19 infection. The nanoceutical fabric denatures the SARS-CoV-2 spike protein and makes the microorganism ineffective.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.22.432359", + "rel_abs": "SARS-CoV2 being highly infectious has been particularly effective in causing widespread infection globally and more variants of SARS-CoV2 are constantly being reported with increased genomic surveillance. In particular, the focus is on mutations of Spike protein, which binds human ACE2 protein enabling SARS-CoV2 entry and infection. Here we present a rapid experimental method leveraging the speed and flexibility of Mircoscale Thermopheresis (MST) to characterize the interaction between Spike Receptor Binding Domain (RBD) and human ACE2 protein. The B.1.351 variant harboring three mutations, (E484K, N501Y, and K417N) binds the ACE2 at nearly five-fold greater affinity than the original SARS-COV-2 RBD. We also find that the B.1.1.7 variant, binds two-fold more tightly to ACE2 than the SARS-COV-2 RBD.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Aniruddha Adhikari", - "author_inst": "S N Bose National Centre for Basic Sciences" - }, - { - "author_name": "Uttam Pal", - "author_inst": "SN Bose National Centre for Basic Sciences" - }, - { - "author_name": "Sayan Bayan", - "author_inst": "SN Bose National Centre for Basic Sciences" - }, - { - "author_name": "Susmita Mondal", - "author_inst": "SN Bose National Centre for Basic Sciences" - }, - { - "author_name": "Ria Ghosh", - "author_inst": "SN Bose National Centre for Basic Sciences" - }, - { - "author_name": "Soumendra Darbar", - "author_inst": "Deys Medical Stores (Mfg.) Ltd" + "author_name": "Paul Khavari", + "author_inst": "Stanford" }, { - "author_name": "Tanusri Saha-Dasgupta", - "author_inst": "SN Bose National Centre for Basic Sciences" + "author_name": "Muthukumar Ramanathan", + "author_inst": "Stanford University" }, { - "author_name": "Samit Kumar Ray", - "author_inst": "SN Bose National Centre for Basic Sciences" + "author_name": "Ian D Ferguson", + "author_inst": "Stanford University" }, { - "author_name": "Samir Kumar Pal", - "author_inst": "SN Bose National Centre for Basic Sciences" + "author_name": "Weili Miao", + "author_inst": "Stanford University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "pathology" }, { "rel_doi": "10.1101/2021.02.22.432259", @@ -935279,63 +935250,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.18.21251793", - "rel_title": "Accessible LAMP-Enabled Rapid Test (ALERT) for detecting SARS-CoV-2", + "rel_doi": "10.1101/2021.02.18.21251243", + "rel_title": "A Multivariate Forecasting Model for the COVID-19 Hospital Census Based on Local Infection Incidence", "rel_date": "2021-02-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.18.21251793", - "rel_abs": "The COVID-19 pandemic has highlighted bottlenecks in large-scale, frequent testing of populations for infections. PCR-based diagnostic tests are expensive, reliant on expensive centralized labs, can take days to deliver results, and are prone to backlogs and supply shortages. Antigen tests, that bind and detect the surface proteins of a virus, are rapid and inexpensive but suffer from high false negative rates. To address this problem, we have created an inexpensive, simple, and robust 60-minute Do-It-Yourself (DIY) workflow to detect viral RNA from nasal swabs or saliva with high sensitivity (0.1 to 2 viral particles/{micro}l) and specificity (>97% True Negative Rate) utilizing reverse transcription loop-mediated isothermal amplification (RT-LAMP).\n\nOur workflow, ALERT (Accessible LAMP-Enabled Rapid Test), incorporates the following features: 1) Increased shelf-life and ambient temperature storage by using wax layers to isolate enzymes from reaction, 2) Improved specificity by using sequence-specific QUASR reporters, 3) Increased sensitivity through use of a magnetic wand to enable pipette-free concentration of sample RNA and cell debris removal, 4) Quality control with a nasopharyngeal-specific mRNA target, and 5) Co-detection of other respiratory viruses, such as Influenza B, by duplexing QUASR-modified RT-LAMP primer sets.\n\nThe flexible nature of the ALERT workflow allows easy, at-home and point-of-care testing for individuals and higher-throughput processing for centralized labs and hospitals. With minimal effort, SARS-CoV-2-specific primer sets can be swapped out for other targets to repurpose ALERT to detect other viruses, microorganisms or nucleic acid-based markers.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.18.21251243", + "rel_abs": "COVID-19 has been one of the most serious global health crises in world history. During the pandemic, healthcare systems require accurate forecasts for key resources to guide preparation for patient surges. Fore-casting the COVID-19 hospital census is among the most important planning decisions to ensure adequate staffing, number of beds, intensive care units, and vital equipment. In the literature, only a few papers have approached this problem from a multivariate time-series approach incorporating leading indicators for the hospital census. In this paper, we propose to use a leading indicator, the local COVID-19 infection incidence, together with the COVID-19 hospital census in a multivariate framework using a Vector Error Correction model (VECM) and aim to forecast the COVID-19 hospital census for the next 7 days. The model is also applied to produce scenario-based 60-day forecasts based on different trajectories of the pandemic. With several hypothesis tests and model diagnostics, we confirm that the two time-series have a cointegration relationship, which serves as an important predictor. Other diagnostics demonstrate the goodness-of-fit of the model. Using time-series cross-validation, we can estimate the out-of-sample Mean Absolute Percentage Error (MAPE). The model has a median MAPE of 5.9%, which is lower than the 6.6% median MAPE from a univariate Autoregressive Integrated Moving Average model. In the application of scenario-based long-term forecasting, future census exhibits concave trajectories with peaks lagging 2-3 weeks later than the peak infection incidence. Our findings show that the local COVID-19 infection incidence can be successfully in-corporated into a VECM with the COVID-19 hospital census to improve upon existing forecast models, and to deliver accurate short-term forecasts and realistic scenario-based long-term trajectories to help healthcare systems leaders in their decision making.\n\nAuthor summaryDuring the COVID-19 pandemic, healthcare systems need to have adequate resources to accommodate demand from COVID-19 cases. One of the most important metrics for planning is the COVID-19 hospital census. Only a few papers make use of leading indicators within multivariate time-series models for this problem. We incorporated a leading indicator, the local COVID-19 infection incidence, together with the COVID-19 hospital census in a multivariate framework called the Vector Error Correction model to make 7-day-ahead forecasts. This model is also applied to produce 60-day scenario forecasts based on different trajectories of the pandemic. We find that the two time-series have a stable long-run relationship. The model has a good fit to the data and good forecast performance in comparison with a more traditional model using the census data alone. When applied to different 60-day scenarios of the pandemic, the census forecasts show concave trajectories that peak 2-3 weeks later than the infection incidence. Our paper presents this new model for accurate short-term forecasts and realistic scenario-based long-term forecasts of the COVID-19 hospital census to help healthcare systems in their decision making. Our findings suggest using the local COVID-19 infection incidence data can improve and extend more traditional forecasting models.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Ali Bekta\u015f", - "author_inst": "Oakland Genomics Center" - }, - { - "author_name": "Mike F. Covington", - "author_inst": "Oakland Genomics Center, 355 30th St. Oakland, CA, 94609, USA, and Amaryllis Nucleics, 355 30th St, Oakland, CA, 94609, USA" - }, - { - "author_name": "Guy Aidelberg", - "author_inst": "Universit\u00e9 de Paris, INSERM U1284, Center for Research and Interdisciplinarity (CRI), F-75006 Paris, France" - }, - { - "author_name": "Anibal Arce", - "author_inst": "Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Cat\u00f3lica de Chile, Santiago 7820244, Chil" - }, - { - "author_name": "Tamara Matute", - "author_inst": "Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Cat\u00f3lica de Chile, Santiago 7820244, Chil" - }, - { - "author_name": "Isaac N\u00fa\u00f1ez", - "author_inst": "Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Cat\u00f3lica de Chile, Santiago 7820244, Chil" - }, - { - "author_name": "Julia Walsh", - "author_inst": "School of Public Health, University of California Berkeley, Berkeley, CA, 94720, USA" - }, - { - "author_name": "David Boutboul", - "author_inst": "Clinical Immunology Department, U976 HIPI, H\u00f4pital Saint Louis, Universit\u00e9 de Paris, Paris, France" - }, - { - "author_name": "Ariel B. Lindner", - "author_inst": "Universit\u00e9 de Paris, INSERM U1284, Center for Research and Interdisciplinarity (CRI), F-75006 Paris, France" + "author_name": "Hieu Minh Nguyen", + "author_inst": "Center for Outcomes Research and Evaluation, Atrium Health, Charlotte, NC 28204" }, { - "author_name": "Fern\u00e1n Federici", - "author_inst": "Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Cat\u00f3lica de Chile, Santiago 7820244, Chil" + "author_name": "Philip Turk", + "author_inst": "Center for Outcomes Research and Evaluation, Atrium Health, Charlotte, NC 28204" }, { - "author_name": "Anitha Jayaprakash", - "author_inst": "Oakland Genomics Center, 355 30th St. Oakland, CA, 94609, USA and Girihlet Inc, 355 30th St, Oakland, CA, 94609, USA" + "author_name": "Andrew McWilliams", + "author_inst": "Center for Outcomes Research and Evaluation, Atrium Health, Charlotte, NC 28204" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.02.18.21252004", @@ -936845,39 +936784,55 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.16.21251676", - "rel_title": "Incidence and Outcomes of Pulmonary embolism among hospitalized COVID-19 patients", + "rel_doi": "10.1101/2021.02.16.21250657", + "rel_title": "Worries about COVID-19 infection and psychological distress at work and while commuting", "rel_date": "2021-02-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.16.21251676", - "rel_abs": "BackgroundPatients with COVID-19 may be at high risk for thrombotic complications due to excess inflammatory response and stasis of blood flow. This study aims to assess the incidence of pulmonary embolism among hospitalized patients with COVID-19, risk factors and the impact on survival.\n\nMethodA retrospective case-control study was conducted at Al-Noor Specialist Hospital in, Saudi Arabia between March 15, 2020, and June 15, 2020. Patients with confirmed COVID-19 diagnosis by a real-time polymerase chain reaction (PCR) and confirmed diagnosis of pulmonary embolism by Computed Tomography pulmonary angiogram (CTPA) formed the case group. Patients with confirmed COVID-19 diagnosis by a real-time polymerase chain reaction (PCR) and without confirmed diagnose of pulmonary embolism formed the control group. Logistic regression analysis was used to identify predictors of pulmonary embolism and its survival.\n\nResultsA total of 159 patients participated were included in the study, of which 51 were the cases (patients with pulmonary embolism) and 108 patients formed the control group (patients without pulmonary embolism). The incidence of PE among hospitalized was around 32%. Smoking history, low level of oxygen saturation and higher D-dimer values were important risk factors that were associated with a higher risk of developing PE (p< 0.05). Higher respiratory rate was associated with higher odds of death, and decrease the possibility of survival among hospitalised patients with PE.\n\nConclusionPulmonary embolism is common among hospitalized patients with COVID-19. Preventive measures should be considered for hospitalized patients with smoking history, low level of oxygen saturation, high D-dimer values, and high respiratory rate.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.16.21250657", + "rel_abs": "ObjectiveThis study examined the relationship between worry about COVID-19 infection in the workplace and while commuting to work and psychological distress in Japan.\n\nMethodsAn internet monitor study was conducted. Out of a total of 33,302 participants, 26,841 people were included. The subjects were asked single-item questions about whether they were worried about COVID-19 infection in general, at work and while commuting to work. Kessler 6 (K6) was used to assess psychological distress.\n\nResultsThe OR was significantly higher in association with worry about infection in the workplace at 1.71 (95%CI 1.53-1.92) and worry about infection while commuting at 1.49 (95%CI 1.32-1.67).\n\nConclusionsThis study suggests the need for psychological intervention to reduce worry about infection in response to public mental health challenges associated with the COVID-19 pandemic.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Omaima Badr", - "author_inst": "Al Noor Specialist Hospital, Mecca" + "author_name": "Masamichi Uehara", + "author_inst": "Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan" }, { - "author_name": "Hassan Alwafi", - "author_inst": "Umm Al qura university" + "author_name": "Tomohiro Ishimaru", + "author_inst": "Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan" }, { - "author_name": "Wael Elrefaey", - "author_inst": "Al Noor Specialist Hospital, Mecca" + "author_name": "Hajime Ando", + "author_inst": "Department of Work Systems and Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan" }, { - "author_name": "Abdallah Y Naser", - "author_inst": "Isra University" + "author_name": "Seiichiro Tateishi", + "author_inst": "Department of Occupational Medicine, School of Medicine, University of Occupational and Environmental Health, Japan" }, { - "author_name": "Mohammed Shabrawishi", - "author_inst": "Al Noor Specialist Hospital, Mecca" + "author_name": "Hisashi Eguchi", + "author_inst": "Department of Mental Health, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan" + }, + { + "author_name": "Mayumi Tsuji", + "author_inst": "Department of Environmental Health, School of Medicine, University of Occupational and Environmental Health, Japan" + }, + { + "author_name": "Koji Mori", + "author_inst": "Department of Occupational Health Practice and Management, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Jap" + }, + { + "author_name": "Shinya Matsuda", + "author_inst": "Department of Preventive Medicine and Community Health, School of Medicine, University of Occupational and Environmental Health, Japan" + }, + { + "author_name": "Yoshihisa Fujino", + "author_inst": "Department of Environmental Epidemiology, Institute of Industrial Ecological Sciences, University of Occupational and Environmental Health, Japan" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "respiratory medicine" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2021.02.16.21251754", @@ -938599,41 +938554,33 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.17.21251725", - "rel_title": "Assessment of knowledge, attitude and practices among Accredited Social Health Activists (ASHAs) towards COVID-19: a descriptive cross-sectional study in Tripura, India", + "rel_doi": "10.1101/2021.02.17.21251957", + "rel_title": "Change in vaccine willingness in Australia: August 2020 to January 2021", "rel_date": "2021-02-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.17.21251725", - "rel_abs": "With the surge in COVID-19 cases, community healthcare workers (CHW) remain pivotal for proper dissemination of awareness of disease transmission and infection control measures among the communities in low- and middle-income countries. In this context, lack of adequate knowledge and appropriate attitude among the CHW can directly influence the COVID-19 management programme. Therefore, the present study was designed to assess the knowledge, attitude and practices towards COVID-19 among the CHW of India known as Accredited Social Health Activists (ASHAs). A descriptive cross-sectional was conducted in the state of Tripura, Northeast India, among ASHAs with 14-, 4- and 3-item self-administered questionnaire for knowledge, attitude and practice. Around 61.2% of participants had the mean correct answer rate and the mean score of knowledge was 8.57{+/-} 2.25 ({+/-}SD). As per Blooms cut-off, it was observed that only 10% of the ASHAs had adequate knowledge, 30.9% showed positive attitude and 88% adhered to the good practices. It was observed that the indigenous ASHAs were 1.79 times more likely to adhere to the good practice of wearing masks during filed visits in the community (OR: 1.791, 95% CI: 1.059-3.028, p=0.030). Multinomial regression analysis showed that practice was significantly associated with fear of getting infected during service and the communitys fearfulness of ASHAs spreading the disease. Urgent addressing of the provisions of support, guidance and training of grassroot level healthcare workers in rural tough terrains can ensure robust output from the existing community healthcare workers in future pandemic-like emergencies.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.17.21251957", + "rel_abs": "The ANU Centre for Social Research and Methods ANU COVID-19 Impact Monitoring Survey Program asked the same group of respondents about their vaccine intentions in August 2020 and January 2021. The paper provides data on the vaccine willingness in Australia as of January 2021 and how this changed since August 2020 both at the national level and for particular individuals. The paper provides estimates of how vaccine willingness has changed for different population sub-groups and the individual level characteristics which are associated with changes in vaccine willingness. We find an overall decrease in vaccine willingness, with the biggest decline being those who would definitely get a vaccine as of August 2020 but said they would only probably get a vaccine as of January 2021. We also look at the factors associated with vaccine willingness, as well as the factors associated with change through time.\n\nExecutive summaryO_LIThe paper provides data on the vaccine willingness in Australia as of January 2021 and how this changed since August 2020 both at the national level and for particular individuals.\nC_LIO_LIThere has been a substantial increase in vaccine resistance and hesitancy and a large decline in vaccine likeliness between August 2020 and January 2021\nO_LICombined, 21.7 per cent of Australians said they probably or definitely would not get a safe and effective COVID-19 vaccine in January 2021, a significant and substantial increase from the 12.7 per cent of Australians who gave the same responses in August 2020.\nC_LI\nC_LIO_LIAt the individual level, 31.9 per cent of Australians became less willing to get the vaccine between August 2020 and January 2021 in that they moved from a more to a less willing category.\nO_LIThere were still some Australians who became more willing over the period to get vaccinated (9.9 per cent).\nC_LI\nC_LIO_LIThe largest single flow across willingness categories was the 18.7 per cent of Australians who went from being definitely willing to get a COVID-19 vaccination to only probably willing to get one. There was a large decline in vaccine certainty, alongside increases in vaccine resistance.\nC_LIO_LIWe found three attitudinal factors that were particularly important in explaining the decline in willingness. Those Australians who think too much is being made of COVID-19, those who have low confidence in hospitals and the health care system, and those who are not optimistic about the next 12 months had all decreased in terms of their willingness to get vaccinated once a vaccine is available.\nO_LIIn addition to campaigns targeting vaccination directly, those programs that improve confidence, remind people of the dangers of COVID-19, but importantly highlight the potential for a much better 2022 all have the potential to improve vaccination rates.\nC_LI\nC_LIO_LIFemales, Indigenous Australians, those who speak a language other than English at home and those who have not completed Year 12 have all became less willing to get a vaccine since August 2020 compared to the rest of the Australian population.\nO_LIThese population groups are arguably the most urgent focus of any public health campaigns to improve willingness, both because they have low willingness to start with, but also because there is the potential opportunity to bring their willingness back to what it was in August 2020 when there was a smaller gap with the rest of the Australian population.\nC_LIO_LIThere is a real need to consider a significantly enhanced public health campaign in languages other than English\nC_LIO_LIThere is a need to convey information to the general public in a way that is informative, reassuring and salient for those without a degree\nC_LI\nC_LI", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "PURVITA CHOWDHURY", - "author_inst": "Model Rural Health Research Unit (MRHRU), Tripura" - }, - { - "author_name": "Subrata Baidya", - "author_inst": "Agartala Government Medical College, Tripura & Model Rural Health Research Unit (MRHRU), Tripura" - }, - { - "author_name": "Debosmita Paul", - "author_inst": "Model Rural Health Research Unit (MRHRU), Tripura" + "author_name": "Nicholas Biddle", + "author_inst": "Australian National University" }, { - "author_name": "Pinki Debbarma", - "author_inst": "Kherengbar Hospital, Khumulwng, Tripura" + "author_name": "Ben Edwards", + "author_inst": "Australian National University" }, { - "author_name": "Biraj Kalita", - "author_inst": "Model Rural Health Research Unit (MRHRU), Tripura" + "author_name": "Matthew Gray", + "author_inst": "Australian National University" }, { - "author_name": "Sanjoy Karmakar", - "author_inst": "Model Rural Health Research Unit (MRHRU), Tripura" + "author_name": "Kate Sollis", + "author_inst": "Australian National University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -940441,43 +940388,35 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2021.02.15.21251586", - "rel_title": "Epidemiology of COVID-19 infection amongst workers in Primary Healthcare in Qatar", + "rel_doi": "10.1101/2021.02.17.431721", + "rel_title": "Immune characterization and profiles of SARS-CoV-2 infected patients", "rel_date": "2021-02-18", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.15.21251586", - "rel_abs": "BackgroundCOVID-19 transmission was significant amongst Healthcare workers worldwide.\n\nAimThis study aims to estimate the risk of exposure for COVID-19 across Primary Healthcare workers in the State of Qatar. Methods: A cross-sectional descriptive study was conducted to study the burden of COVID-19 among staff working at PHCC during the COVID-19 pandemic from March 1 to October 31, 2020.\n\nResults1,048 (87.4%)of the infected HCWs belonged to the age group below 45 years, and 488 (40.7%) HCWs were females. 450 (37.5%) were HCWs clinical staff working in one of the 27 PHCC HCs; Despite the increased patient footfall and risk environment, the COVID HCs had an attack rate of 10.1%, which is not significantly different from the average attack rate of 8.9% among staff located in other HCs (p-value =0.26). Storekeepers, engineering & maintenance staff, housekeeping staff, support staff, and security staff (outsourced positions) had the highest positivity rates, 100%, 67.2%, 47.1%, 32.4%, and 29.5% respective positivity rates.\n\nConclusionsThe elevated risk of infection amongst outsourced healthcare workers can be explained by environmental factors such as living conditions. On the other hand, better containment within clinical healthcare workers can be attributed to strict safety training and compliance with preventative measures which is recommended to be implemented across all settings.", - "rel_num_authors": 6, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.17.431721", + "rel_abs": "The spread of SARS-CoV-2 and the increasing mortality rates of COVID-19 create an urgent need for treatments, which are currently lacking. Although vaccines have been approved by the FDA for emergency use in the U.S., patients will continue to require pharmacologic intervention to reduce morbidity and mortality as vaccine availability remains limited. The rise of new variants makes the development of therapeutic strategies even more crucial to combat the current pandemic and future outbreaks. Evidence from several studies suggests the host immune response to SARS-CoV-2 infection plays a critical role in disease pathogenesis. Consequently, host immune factors are becoming more recognized as potential biomarkers and therapeutic targets for COVID-19. To develop therapeutic strategies to combat current and future coronavirus outbreaks, understanding how the coronavirus hijacks the host immune system during and after the infection is crucial. In this study, we investigated immunological patterns or characteristics of the host immune response to SARS-CoV-2 infection that may contribute to the disease severity of COVID-19 patients. We analyzed large bulk RNASeq and single cell RNAseq data from COVID-19 patient samples to immunoprofile differentially expressed gene sets and analyzed pathways to identify human host protein targets. We observed an immunological profile of severe COVID-19 patients characterized by upregulated cytokines, interferon-induced proteins, and pronounced T cell lymphopenia, supporting findings by previous studies. We identified a number of host immune targets including PERK, PKR, TNF, NF-kB, and other key genes that modulate the significant pathways and genes identified in COVID-19 patients. Finally, we identified genes modulated by COVID-19 infection that are implicated in oncogenesis, including E2F transcription factors and RB1, suggesting a mechanism by which SARS-CoV-2 infection may contribute to oncogenesis. Further clinical investigation of these targets may lead to bonafide therapeutic strategies to treat the current COVID-19 pandemic and protect against future outbreaks and viral escape variants.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Mohamed Al Kuwari", - "author_inst": "Primary Healthcare Corporation" - }, - { - "author_name": "Mariam AbdelMalik", - "author_inst": "Primary HealthCare Corporation" - }, - { - "author_name": "Asma Al Nuaimi", - "author_inst": "PrimaryHealthCare Corporation" + "author_name": "Martine Policard", + "author_inst": "Georgetown University Medical Center" }, { - "author_name": "Jazeel AbdelMajeed", - "author_inst": "PrimaryHealthCare Corporation" + "author_name": "Sidharth Jain", + "author_inst": "Georgetown University Medical Center" }, { - "author_name": "Hamad Romaihi", - "author_inst": "Primary Healtcare Corporation" + "author_name": "Samantha Rego", + "author_inst": "Georgetown University Medical Center" }, { - "author_name": "sandy semaan", - "author_inst": "Primary Healthcare Corporation" + "author_name": "Sivanesan Dakshanamurthy", + "author_inst": "Georgetown University Medical Center" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.02.18.431811", @@ -942263,87 +942202,18 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.02.16.430500", - "rel_title": "Structural and functional ramifications of antigenic drift in recent SARS-CoV-2 variants", + "rel_doi": "10.1101/2021.02.17.431625", + "rel_title": "A rigorous framework for detecting SARS-CoV-2 spike protein mutational ensemble from genomic and structural features", "rel_date": "2021-02-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.16.430500", - "rel_abs": "The protective efficacy of neutralizing antibodies (nAbs) elicited during natural infection with SARS-CoV-2 and by vaccination based on its spike protein has been compromised with emergence of the recent SARS-CoV-2 variants. Residues E484 and K417 in the receptor-binding site (RBS) are both mutated in lineages first described in South Africa (B.1.351) and Brazil (B.1.1.28.1). The nAbs isolated from SARS-CoV-2 patients are preferentially encoded by certain heavy-chain germline genes and the two most frequently elicited antibody families (IGHV3-53/3-66 and IGHV1-2) can each bind the RBS in two different binding modes. However, their binding and neutralization are abrogated by either the E484K or K417N mutation, whereas nAbs to the cross-reactive CR3022 and S309 sites are largely unaffected. This structural and functional analysis illustrates why mutations at E484 and K417 adversely affect major classes of nAbs to SARS-CoV-2 with consequences for next-generation COVID-19 vaccines.", - "rel_num_authors": 17, - "rel_authors": [ - { - "author_name": "Meng Yuan", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Deli Huang", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Chang-Chun D. Lee", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Nicholas C. Wu", - "author_inst": "University of Illinois at Urbana-Champaign" - }, - { - "author_name": "Abigail M. Jackson", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Xueyong Zhu", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Hejun Liu", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Linghang Peng", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Marit J. van Gils", - "author_inst": "Amsterdam UMC" - }, - { - "author_name": "Rogier W. Sanders", - "author_inst": "Amsterdam UMC" - }, - { - "author_name": "Dennis R. Burton", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "S Momsen Reincke", - "author_inst": "Deutsches Zentrum f\u00fcr Neurodegenerative Erkrankungen" - }, - { - "author_name": "Harald Pr\u00fcss", - "author_inst": "Deutsches Zentrum f\u00fcr Neurodegenerative Erkrankungen" - }, - { - "author_name": "Jakob Kreye", - "author_inst": "Deutsches Zentrum f\u00fcr Neurodegenerative Erkrankungen" - }, - { - "author_name": "David Nemazee", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Andrew B. Ward", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Ian A. Wilson", - "author_inst": "The Scripps Research Institute" - } - ], + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.17.431625", + "rel_abs": "The recent release of SARS-CoV-2 genomic data from several countries has provided clues into the potential antigenic drift of the coronavirus population. In particular, the genomic instability observed in the spike protein necessitates immediate action and further exploration in the context of viralhost interactions. By temporally tracking 527,988 SARS-CoV-2 genomes, we identified invariant and hypervariable regions within the spike protein. We evaluated combination of mutations from SARS-CoV-2 lineages and found that maximum number of lineage-defining mutations were present in the N-terminal domain (NTD). Based on mutant 3D-structural models of known Variants of Concern (VOCs), we found that structural properties such as accessibility, secondary structural type, and intra-protein interactions at local mutation sites are greatly altered. Further, we observed significant differences between intra-protein networks of wild-type and Delta mutant, with the latter showing dense intra-protein contacts. Extensive molecular dynamics simulations of D614G mutant spike structure with hACE2 further revealed dynamic features with 47.7% of mutations mapping on flexible regions of spike protein. Thus, we propose that significant changes within spike protein structure have occurred that may impact SARS-CoV-2 pathogenesis, and repositioning of vaccine candidates is required to contain the spread of COVID-19 pathogen.", + "rel_num_authors": 0, + "rel_authors": null, "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "genomics" }, { "rel_doi": "10.1101/2021.02.17.431617", @@ -943956,43 +943826,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.12.21251479", - "rel_title": "Severe COVID-19 pneumonia and barotrauma: From the frying pan into the fire.", + "rel_doi": "10.1101/2021.02.10.21251484", + "rel_title": "An analysis of school absences in England during the Covid-19 pandemic", "rel_date": "2021-02-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.12.21251479", - "rel_abs": "AimCOVID-19 pneumonia with ARDS (C-ARDS) has a high mortality. Preliminary reports indicate a higher incidence of barotrauma in patients with C-ARDS[1] both on invasive mechanical ventilation (iMV) and non-invasive ventilation (NIV) This study examines the incidence and risk factors for barotrauma and change in outcomes after barotrauma in patients with severe C-ARDS on positive pressure respiratory support (PPRS).\n\nMethods and materialsThis is a retrospective study of C-ARDS associated barotrauma over 5 months in patients on PPRS in a tertiary COVID care center. The type of barotrauma, intervention, related factors, such as type of respiratory support (iMV vs NIV), airway pressure prior to the occurrence of barotrauma, and post-barotrauma outcomes were analyzed.\n\nResultsA total of 38/410 (9.3%) C-ARDS patients on PPRS [mean age 57.82 {+/-} 13.3 years, 32 males (84.2%)] developed barotrauma. Of these, 20 patients (52.6%) were on NIV and 18 (47.4%) patients were iMV on standard recommended settings. The median P/F ratio of patients on MV at the time of barotrauma was 116.4 (IQR 72.4, 193.25). The details of barotrauma were as follows: 24 patients had pneumothorax (PTX), 2 had pneumo-mediastinum and 12 had subcutaneous emphysema. Overall, 24/38 (63.2%) patients, including 15/18 (83.3%) on MV succumbed to their illness. The barotrauma happened a median of 6.5 days (IQR 4.75,13) after admission and 15 days (IQR 10.25,18.0) from symptom onset. The median duration from barotrauma to death was 7 days (IQR 2.25, 8.0) and barotrauma to discharge (for survivors) was 12.5 days (IQR 8.0, 21.25). All patients received steroids and 11/38 (28.9%) received additional immunosuppression with tocilizumab.\n\nConclusionA high incidence of barotrauma was seen in this large series of severe C-ARDS patients on PPRS. Barotrauma led to further deterioration in the clinical status leading to a fatal outcome in the majority of the MV patients, despite prompt treatment.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251484", + "rel_abs": "The introduction of SARS-CoV-2, the virus that causes COVID-19 infection, in the UK in early 2020, resulted in the UK government introducing several control policies in order to reduce the spread of disease. As part of these restrictions, schools were closed to all pupils in March (except for vulnerable and key worker children), before re-opening to certain year groups in June. Finally all school children returned to the classroom in September. In this paper, we analyse the data on school absences from September 2020 to December 2020 as a result of COVID-19 infection and how that varied through time as other measures in the community were introduced. We utilise data from the Educational Settings database compiled by the Department for Education and examine how pupil and teacher absences change in both primary and secondary schools.\n\nOur results show that absences as a result of COVID-19 infection rose steadily following the re-opening of schools in September. Cases in teachers were seen to decline during the November lockdown, particularly in those regions that had previously been in tier 3, the highest level of control at the time. Cases in secondary school pupils increased for the first two weeks of the November lockdown, before decreasing. Since the introduction of the tier system, the number of absences owing to confirmed infection in primary schools was observed to be significantly lower than in secondary schools across all regions and tiers.\n\nIn December, we observed a large rise in the number of absences per school in secondary school settings in the South East and Greater London, but such rises were not observed in other regions or in primary school settings. We conjecture that the increased transmissibility of the new variant in these regions may have contributed to this rise in cases in secondary schools. Finally, we observe a positive correlation between cases in the community and cases in schools in most regions, with weak evidence suggesting that cases in schools lag behind cases in the surrounding community. We conclude that there is not significant evidence to suggest that schools are playing a significant role in driving spread in the community and that careful monitoring may be required as schools re-open to determine the effect associated with open schools upon community incidence.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Hariprasad Kalpakam", - "author_inst": "Apollo Hospitals Bangalore" + "author_name": "Emma R Southall", + "author_inst": "University of Warwick" }, { - "author_name": "Sameer Bansal", - "author_inst": "Apollo Specialty Hospital, Bangalore" + "author_name": "Alex Holmes", + "author_inst": "University of Warwick" }, { - "author_name": "Nithya . Suresh", - "author_inst": "Apollo hospitals" + "author_name": "Edward M Hill", + "author_inst": "University of Warwick" }, { - "author_name": "Samson Kade", - "author_inst": "Apollo Specialty Hospitals, Bangalore, India" + "author_name": "Benjamin D Atkins", + "author_inst": "University of Warwick" }, { - "author_name": "Anmol Thorbole", - "author_inst": "Apollo Hospitals, Bangalore, India" + "author_name": "Trystan Leng", + "author_inst": "University of Warwick" }, { - "author_name": "Ravindra M Mehta", - "author_inst": "Apollo Super Specialty Hospital" + "author_name": "Robin N Thompson", + "author_inst": "University of Warwick" + }, + { + "author_name": "Louise J Dyson", + "author_inst": "University of Warwick" + }, + { + "author_name": "Matt J Keeling", + "author_inst": "University of Warwick" + }, + { + "author_name": "Michael Tildesley", + "author_inst": "University of Warwick" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.09.21251274", @@ -945778,29 +945660,73 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.02.11.21251562", - "rel_title": "Population Age-Ineligible for COVID-19 Vaccine in the United States: Implications for State, County, and Race/Ethnicity Vaccination Targets", + "rel_doi": "10.1101/2021.02.10.21251526", + "rel_title": "Impacts of school closures on physical and mental health of children and young people: a systematic review", "rel_date": "2021-02-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.11.21251562", - "rel_abs": "BackgroundWe examined the geographic and racial/ethnic distribution of the SARS-CoV-2 vaccine age-ineligible population (0-15 years old) in the U.S., and calculated the proportion of the age-eligible population that will need to be vaccinated in a given geo-demographic group in order to achieve either 60% or 75% vaccine coverage for that population as a whole.\n\nMethodsUS Census Bureau population estimates for 2019 were used to calculate the percent vaccine ineligible and related measures for counties, states, and the nation as a whole. Vaccination targets for the 30 largest counties by population were calculated. Study measures were calculated for racial/ethnic populations at the national (n=7) and state (n=6) levels.\n\nResultsPercent of population ineligible for vaccine varied widely both geographically and by race/ethnicity. State values ranged from 15.8% in Vermont to 25.7% in Utah, while percent ineligible of the major racial/ethnic groups was 16.4% of non-Hispanic whites, 21.6% of non-Hispanic Blacks, and 27.5% of Hispanics. Achievement of total population vaccine coverage of at least 75% will require vaccinating more than 90% of the population aged 16 years and older in 29 out of 30 of the largest counties in the U.S.\n\nConclusionsThe vaccine-ineligibility of most children for the next 1-2 years, coupled with reported pervasive vaccine hesitancy among adults, especially women and most minorities, means that achievement of adequate levels of vaccine coverage will be very difficult for many vulnerable geographic areas and for several racial/ethnic minority groups, particularly Hispanics, Blacks, and American Indians.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251526", + "rel_abs": "BackgroundThe well-documented links between education and health mean that school closures during the COVID-19 pandemic are likely to be associated with significant health harms to children and young people (CYP). A systematic review of the evidence is needed to inform policy decisions around school closures and re-openings during the pandemic.\n\nMethodsWe undertook a high-quality systematic review of observational quantitative studies (published or preprint) of the impacts of school closures (for any reason) on the health, wellbeing and educational outcomes of CYP, excluding impacts of closure on transmission of infection (PROSPERO CRD42020181658). We used a machine learning approach for screening articles, with decisions on inclusion and data extraction performed independently by 2 researchers. Quality was assessed for study type. A narrative synthesis of results was undertaken as data did not allow meta-analysis.\n\nResults16,817 records were screened, of which 151 were reviewed in full-text and 72 studies were included from 20 countries. 33% were cohort studies using historical control periods; 19% pre-post studies; and 46% cross-sectional studies which assessed change by comparison with population reference data. 63% were high-quality, 25% medium-quality and 13% low-quality. Cause of closure in all studies was the first COVID-19 pandemic wave with the exception of 5 influenza studies and 1 teacher strike.\n\n27 studies concerning mental health identified considerable impacts across emotional, behavioural and restlessness/inattention problems; 18-60% of CYP scored above risk thresholds for distress, particularly anxiety and depressive symptoms. Two studies reported non-significant rises in suicide rates. Self-harm and psychiatric attendances were markedly reduced, indicating a rise in unmet mental health need. Child protection referrals fell 27-39%, with a halving of the expected number of referrals originating in schools.\n\n19 studies concerning health service use showed marked reductions in emergency department (ED) presentations and hospital admissions, with evidence of delayed presentations and potential widening of inequalities in vaccination coverage. Data suggested marked rises in screen-time and social media use and reductions in physical activity however data on sleep and diet were inconclusive. Available data suggested likely higher harms in CYP from more deprived populations.\n\nConclusionsSchool closures as part of broader social distancing measures are associated with considerable harms to CYP health and wellbeing. Available data are short-term and longer-term harms are likely to be magnified by further school closures. Data are urgently needed on longer-term impacts using strong research designs, particularly amongst vulnerable groups. These findings are important for policy-makers seeking to balance the risks of transmission through school-aged children with the harms of closing schools.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Elizabeth B Pathak", - "author_inst": "Women's Institute for Independent Social Enquiry" + "author_name": "Russell M. Viner", + "author_inst": "UCL Great Ormond St. Institute of Child Health" + }, + { + "author_name": "Simon Russell", + "author_inst": "UCL Great Ormond St. Institute of Child Health" }, { - "author_name": "Janelle Menard", - "author_inst": "Women's Institute for Independent Social Enquiry (www.wiise-usa.org)" + "author_name": "Rosella Saulle", + "author_inst": "Department of Epidemiology, Lazio Regional Health Service, Rome" }, { - "author_name": "Rebecca B Garcia", - "author_inst": "Premise Health" + "author_name": "Helen Croker", + "author_inst": "UCL Great Ormond St. Institute of Child Health" + }, + { + "author_name": "Claire Stansfield", + "author_inst": "UCL Institute of Education" + }, + { + "author_name": "Jessica Packer", + "author_inst": "UCL Great Ormond St. Institute of Child Health" + }, + { + "author_name": "Dasha Nicholls", + "author_inst": "Division of Brain Sciences, Imperial College London" + }, + { + "author_name": "Anne-Lise Goddings", + "author_inst": "UCL Great Ormond St. Institute of Child Health" + }, + { + "author_name": "Chris Bonell", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Lee Hudson", + "author_inst": "UCL Great Ormond St. Institute of Child Health" + }, + { + "author_name": "Steven Hope", + "author_inst": "UCL Great Ormond St. Institute of Child Health" + }, + { + "author_name": "Nina Schwalbe", + "author_inst": "Heilbrunn Department of Population and Family Health, Columbia University, New York" + }, + { + "author_name": "Anthony Morgan", + "author_inst": "Glasgow Caledonian University, London" + }, + { + "author_name": "Silvia Minozzi", + "author_inst": "Department of Epidemiology, Lazio Regional Health Service, Rome" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0_ng", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -947352,39 +947278,87 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.02.12.430933", - "rel_title": "Rapidly Increasing SARS-CoV-2 Neutralization by Intravenous Immunoglobulins Produced from Plasma Collected During the 2020 Pandemic", + "rel_doi": "10.1101/2021.02.11.430866", + "rel_title": "A combination of cross-neutralizing antibodies synergizes to prevent SARS-CoV-2 and SARS-CoV pseudovirus infection", "rel_date": "2021-02-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.12.430933", - "rel_abs": "Immunoglobulin (IG) lots (N=176) released since March 2020 were tested for SARS-CoV-2 neutralizing antibodies, with first positive results for September 2020 lots, mean = 1.8 IU/ml, 46% of lots positive. From there, values steadily increased, in correlation with the cumulative COVID-19 incidence, to reach a mean of 36.7 IU/ml and 93% of lots positive by January 2021. Extrapolating the correlation, IGs could reach an anti-SARS-CoV-2 potency of ~400 IU/ml by July 2021. At that stage, prophylactic IG treatment for primary/secondary immunodeficiency could contain similar doses of anti-SARS-CoV-2 as convalescent plasma which is used for treatment of COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.11.430866", + "rel_abs": "Coronaviruses have caused several epidemics and pandemics including the ongoing coronavirus disease 2019 (COVID-19). Some prophylactic vaccines and therapeutic antibodies have already showed striking effectiveness against COVID-19. Nevertheless, concerns remain about antigenic drift in SARS-CoV-2 as well as threats from other sarbecoviruses. Cross-neutralizing antibodies to SARS-related viruses provide opportunities to address such concerns. Here, we report on crystal structures of a cross-neutralizing antibody CV38-142 in complex with the receptor binding domains from SARS-CoV-2 and SARS-CoV. Our structural findings provide mechanistic insights into how this antibody can accommodate antigenic variation in these viruses. CV38-142 synergizes with other cross-neutralizing antibodies, in particular COVA1-16, to enhance neutralization of SARS-CoV-2 and SARS-CoV. Overall, this study provides valuable information for vaccine and therapeutic design to address current and future antigenic drift in SARS-CoV-2 and to protect against zoonotic coronaviruses.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Maria R. Farcet", - "author_inst": "Baxter AG, part of Takeda" + "author_name": "Hejun Liu", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Michael Karbiener", - "author_inst": "Baxter AG, part of Takeda" + "author_name": "Meng Yuan", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Julia Schwaiger", - "author_inst": "Baxter AG, part of Takeda" + "author_name": "Deli Huang", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Reinhard Ilk", - "author_inst": "Baxter AG, part of Takeda" + "author_name": "Sandhya Bangaru", + "author_inst": "The Scripps Research Institute" }, { - "author_name": "Thomas R. Kreil", - "author_inst": "Baxter AG, part of Takeda" + "author_name": "Chang-Chun D. Lee", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Linghang Peng", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Xueyong Zhu", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "David Nemazee", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Marit J. van Gils", + "author_inst": "University of Amsterdam" + }, + { + "author_name": "Rogier W. Sanders", + "author_inst": "University of Amsterdam" + }, + { + "author_name": "Hans-Christian Kornau", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE) Berlin" + }, + { + "author_name": "S. Momsen Reincke", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE) Berlin" + }, + { + "author_name": "Harald Pruss", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE) Berlin" + }, + { + "author_name": "Jakob Kreye", + "author_inst": "German Center for Neurodegenerative Diseases (DZNE) Berlin" + }, + { + "author_name": "Nicholas C. Wu", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Andrew B. Ward", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Ian A. Wilson", + "author_inst": "The Scripps Research Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.02.11.429193", @@ -949024,26 +948998,70 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.10.21251533", - "rel_title": "County-Specific, Real-Time Projection of the Effect of Business Closures on the COVID-19 Pandemic", + "rel_doi": "10.1101/2021.02.10.21251543", + "rel_title": "Is Covid-19 seroprevalence different in health care workers as per their risk of exposure? A study from a tertiary care hospital in National Capital Region of India", "rel_date": "2021-02-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251533", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.10.21251543", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Dominic Yurk", - "author_inst": "California Institute of Technology" + "author_name": "Sushila Kataria", + "author_inst": "Medanta The Medicity" }, { - "author_name": "Yaser Abu-Mostafa", - "author_inst": "California Institute of Technology" + "author_name": "Rashmi Phogat Sr.", + "author_inst": "Medanta The Medicity" + }, + { + "author_name": "Pooja Sharma", + "author_inst": "Medanta Insitute of Education and Research" + }, + { + "author_name": "Vikas Deswal", + "author_inst": "Medanta The Medicity" + }, + { + "author_name": "Sazid Alam", + "author_inst": "Medanta The Medicity" + }, + { + "author_name": "Manish Singh", + "author_inst": "Medanta Institute of Education and Research" + }, + { + "author_name": "Kuldeep Kumar", + "author_inst": "Medanta Institute of Education and Research" + }, + { + "author_name": "Vaibhav Gupta", + "author_inst": "Medanta The Medicity" + }, + { + "author_name": "Padam Singh", + "author_inst": "Medanta Institute of Education and Research" + }, + { + "author_name": "Rohit Dutt", + "author_inst": "GD Goenka University" + }, + { + "author_name": "Smita Sarma", + "author_inst": "Medanta The Medicity" + }, + { + "author_name": "Renu Saxena", + "author_inst": "Medanta The Medicity" + }, + { + "author_name": "Naresh Trehan", + "author_inst": "Medanta The Medicity" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.11.21251324", @@ -951296,71 +951314,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.08.21251352", - "rel_title": "Assessment of Post SARS CoV 2 Fatigue among Physicians Working in COVID Designated Hospitals in Dhaka, Bangladesh", + "rel_doi": "10.1101/2021.02.08.21250113", + "rel_title": "Association between COVID-19, mobility and environment in Sao Paulo, Brazil", "rel_date": "2021-02-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.08.21251352", - "rel_abs": "BackgroundFatigue has been observed after a number of infectious disease outbreaks around the world. After the outbreak of SARS CoV-2 in Wuhan, China in 2019, the disease turned into a pandemic very rapidly. Mental health is a key issue associated with such outbreaks. To explore the fatigue level among physicians working in designated public and private hospitals in Bangladesh, we conducted a matched case-control study of post-SARS-CoV-2 fatigue.\n\nMethodIn this study 105 physicians who were diagnosed as COVID-19 infected, got treatment, and declared cured at least 6 weeks before the interview date, were recruited as cases and the same number of age and designation matched healthy physicians as control who are working in the same hospital. Case and control were selected in 1:1 ratio from each of the hospitals. The study population was selected by inclusion and exclusion criteria after taking informed written consent. Data collection was done by a semi-structured questionnaire. Diagnosis of COVID--19 infection was done by detection of SARS CoV-2 antigen by RT-PCR from reference laboratories in Bangladesh or by HRCT Chest.\n\nResultAround two-thirds of the physicians were male (67.6% versus 32.4%). Most of them aged less than forty years (80.5%). The cases had a greater number of comorbid conditions than those who were negative. The FSS score (mean) was much higher for cases (36.7 {+/-} 5.3 versus 19.3 {+/-} 3.8) than the control group with a statistically significant difference with no significant gender differentiation. Similarly, around 67.7% of the previously COVID positive physicians represented in the highest FSS score tertile compared to the respondents in the control group had a mean score of less than 3. The difference was also highly significant.\n\nConclusionPhysicians, who had a previous history of COVID-19 infection had a higher total and mean FSS score, signifying a more severe level of fatigue than the physicians who had never been COVID-19 positive while working in the same hospital irrespective of their age and sex.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.08.21250113", + "rel_abs": "Brazil, the country most impacted by the coronavirus disease 2019 (COVID-19) on the southern hemisphere, use intensive care admissions per day, mobility and other indices to monitor quarantines and prevent the transmissions of SARS-CoV-2. In this study we quantified the associations between residential mobility index (RMI), air pollution, meteorology, and daily cases and deaths of COVID-19 in Sao Paulo, Brazil. We applied a semiparametric generalized additive model (GAM) to estimate: 1) the association between RMI and COVID-19, accounting for ambient particulate matter (PM2.5), ozone (O3), relative humidity, temperature and delayed exposure between 3-21 days, and 2) the association between COVID-19 and exposure to for ambient particulate matter (PM2.5), ozone (O3), accounting for relative humidity, temperature and mobility. We found that an RMI of 45.28% results in 1,212 cases (95% CI: 1,189 to 1,235) and 44 deaths (95% CI: 40 to 47). Increasing the isolation from 45.28% to 50% would avoid 438 cases and 21 deaths. Also, we found that an increment of 10 g{middle dot}m-3 of PM2.5 results in a risk of 1.140 (95% CI: 1.021 to 1.274) for cases and 1.086 (95% CI: 1.008 to 1.170) for deaths, while O3 produces a relative risk of 1.075 (95% CI: 1.006 to 1.150) for cases and 1.063 (95% CI: 1.006 to 1.124) for deaths, respectively. We compared our results with observations and literature review, finding well agreement. Policymakers can use such mobility indices as tools to control social distance activities. Spatial distancing is an important factor to control COVID-19. Small increments of air pollution result in an increased number of COVID-19 cases and deaths.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "A T M Hasibul Hasan", - "author_inst": "National Institute of Neurosciences and Hospital" - }, - { - "author_name": "Muhammad Sougatul Islam", - "author_inst": "BioTED" - }, - { - "author_name": "Nushrat Khan", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Nazmul Hoque Munna", - "author_inst": "Mugda Medical College Hospital" + "author_name": "Sergio Ibarra-Espinosa", + "author_inst": "Departamento de Ci\u00eancias Atmosf\u00e9ricas, Universidade de S\u00e3o Paulo, Brazil" }, { - "author_name": "Wahidur Rahman Choton", - "author_inst": "Mymensingh Medical College and Hospital" + "author_name": "Edmilson Dias de Freitas", + "author_inst": "Departamento de Ci\u00eancias Atmosf\u00e9ricas, Universidade de S\u00e3o Paulo, Brazil" }, { - "author_name": "Mostofa Kamal Arefin", - "author_inst": "Dhaka Medical College Hospital" - }, - { - "author_name": "Mohammad Abdullah Az Zubayer Khan", - "author_inst": "National Institute of Laboratory Medicine and Referral Centre" - }, - { - "author_name": "Mohaimen Mansur", - "author_inst": "Institute of Statistical Research and Training, Dhaka University" - }, - { - "author_name": "Rashedul Hassan", - "author_inst": "Green Life Medical College & Hospital" + "author_name": "Karl Ropkins", + "author_inst": "Institute for Transport Studies, University of Leeds, UK" }, { - "author_name": "Numera Siddiqui", - "author_inst": "Dhaka Medical College & Hospital" - }, - { - "author_name": "Muhammad Shamsul Arefin", - "author_inst": "National Institute of Neurosciences & Hospital" - }, - { - "author_name": "Nayema Afroje", - "author_inst": "50 Bed District Hospital, Kishoreganj" + "author_name": "Francesca Dominici", + "author_inst": "Harvard TH Chan School of Public Health" }, { - "author_name": "Md. Salequl Islam", - "author_inst": "Jahangirnagar University" + "author_name": "Amanda Rehbein", + "author_inst": "Departamento de Ci\u00eancias Atmosf\u00e9ricas, Universidade de S\u00e3o Paulo, Brazil" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.02.08.21251348", @@ -953154,49 +953140,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.08.21251070", - "rel_title": "The protective association between statins use and adverse outcomes among COVID-19 patients: a systematic review and meta-analysis", + "rel_doi": "10.1101/2021.02.08.21251332", + "rel_title": "Current quantitative polymerase chain reaction to detect severe acute respiratory syndrome coronavirus 2 may give positive results for other described coronavirus", "rel_date": "2021-02-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.08.21251070", - "rel_abs": "IntroductionStatins may reduce a cytokine storm, which has been hypothesized as a possible mechanism of severe COVID-19 pneumonia. The aim of this study was to conduct a systematic review and meta-analysis to report on adverse outcomes among COVID-19 patients by statin usage.\n\nMethodsLiteratures were searched from January 2019 to December 2020 to identify studies that reported the association between statin usage and adverse outcomes, including mortality, ICU admissions, and mechanical ventilation. Studies were meta-analyzed for mortality by the subgroups of ICU status and statin usage before and after COVID-19 hospitalization. Studies reporting an odds ratio (OR) and hazard ratio (HR) were analyzed separately.\n\nResultsThirteen cohorts, reporting on 110,078 patients, were included in this meta-analysis. Individuals who used statins before their COVID-19 hospitalization showed a similar risk of mortality, compared to those who did not use statins (HR 0.80, 95% CI: 0.50, 1.28; OR 0.62, 95% CI: 0.38, 1.03). Patients who were administered statins after their COVID-19 diagnosis were at a lower risk of mortality (HR 0.53, 95% CI: 0.46, 0.61; OR 0.57, 95% CI: 0.43, 0.75). The use of statins did not reduce the mortality of COVID-19 patients admitted to the ICU (OR 0.65; 95% CI: 0.26, 1.64). Among non-ICU patients, statin users were at a lower risk of mortality relative to non-statin users (HR 0.53, 95% CI: 0.46, 0.62; OR 0.64, 95% CI: 0.46, 0.88).\n\nConclusionPatients administered statins after COVID-19 diagnosis or non-ICU admitted patients were at lower risk of mortality relative to non-statin users.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.08.21251332", + "rel_abs": "Some weeks after the first CoVID-19 outbreak, the WHO published some qPCR protocol assays developed by different institutions worldwide. These qPCR designs are being used to detect the presence of SARS-CoV-2 in the population, which allow us to monitore the prevalence of the virus during the pandemic. Moreover, the use of these designs is wide spreading and nowadays they are used to detect SARS-CoV-2 in environmental samples to act as epidemiological surveillance tool. However, at the time of designing the published RT-qPCR assays, a lack of SARS-CoV-2 genomes available may explain a low exclusivity in some cases. In this study, we are reporting experimental data which demonstrate that some of the current qPCR used to detect SARS-CoV-2 may give positive results for other described coronavirus different from SARS-CoV-2.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ronald Chow", - "author_inst": "Yale School of Public Health, Yale University, New Haven, CT, United States of America; Yale New Haven Health, Yale School of Medicine, Yale University, New Hav" - }, - { - "author_name": "James Im", - "author_inst": "Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada" - }, - { - "author_name": "Nicholas Chiu", - "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School, Harvard University, Boston, MA, United States of America" - }, - { - "author_name": "Leonard Chiu", - "author_inst": "Columbia University Vagelos College of Physicians and Surgeons, Columbia University, New York City, NY, United States of America" - }, - { - "author_name": "Rahul Aggarwal", - "author_inst": "Beth Israel Deaconess Medical Center, Harvard Medical School, Harvard University, Boston, MA, United States of America" + "author_name": "Antonio Martinez-Murcia", + "author_inst": "Universidad Miguel Hernandez" }, { - "author_name": "Jihui Lee", - "author_inst": "Weill Cornell Medicine, New York, NY, United States of America" + "author_name": "Adrian Garcia-Sirera", + "author_inst": "Genetic PCR Solutions" }, { - "author_name": "Young-Geun Choi", - "author_inst": "Sookmyung Womens Hospital, Seoul, Korea" + "author_name": "Aaron Navarro", + "author_inst": "Genetic PCR Solutions" }, { - "author_name": "Elizabeth Horn Prsic", - "author_inst": "Yale New Haven Health, Yale School of Medicine, Yale University, New Haven, CT, United States of America" + "author_name": "Patricia Ros-Tarraga", + "author_inst": "Genetic PCR Solutions" }, { - "author_name": "Hyun Joon Shin", - "author_inst": "Lemuel Shattuck Hospital, Massachusetts Department of Public Health, Jamaica Plain, MA, United States of America; Brigham and Women's Hospital, Boston, MA, Unit" + "author_name": "Laura Perez", + "author_inst": "Genetic PCR Solutions" } ], "version": "1", @@ -954872,43 +954842,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.04.21251171", - "rel_title": "Mapping internet activity in Australian cities during COVID-19 lockdown: how occupational factors drive inequality", + "rel_doi": "10.1101/2021.02.05.21251197", + "rel_title": "Development and validation of an algorithm to estimate the risk of severe complications of COVID-19 to prioritise vaccination", "rel_date": "2021-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.04.21251171", - "rel_abs": "During the COVID-19 pandemic, evidence has accumulated that movement restrictions enacted to combat virus spread produce disparate consequences along socioeconomic lines. We investigate the hypothesis that people engaged in financially secure employment are better able to adhere to mobility restrictions, due to occupational factors that link the capacity for flexible work arrangements to income security. We use high-resolution spatial data on household internet traffic as a surrogate for adaptation to home-based work, together with the geographical clustering of occupation types, to investigate the relationship between occupational factors and increased internet traffic during work hours under lockdown in two Australian cities. By testing our hypothesis based on the observed trends, and exploring demographic factors associated with divergences from our hypothesis, we are left with a picture of unequal impact dominated by two major influences: the types of occupations in which people are engaged, and the composition of households and families. During lockdown, increased internet traffic was correlated with income security and, when school activity was conducted remotely, to the proportion of families with children. Our findings suggest that response planning and provision of social and economic support for residents within lockdown areas should explicitly account for income security and household structure. Overall, the results we present contribute to the emerging picture of the impacts of COVID-19 on human behaviour, and will help policy makers to understand the balance between public health and social impact in making decisions about mitigation policies.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.05.21251197", + "rel_abs": "ObjectiveTo develop an algorithm (sCOVID) to predict the risk of severe complications of COVID- 19 in a community-dwelling population to optimise vaccination scenarios.\n\nDesignPopulation based cohort study\n\nSetting264 Dutch general practices contributing to the NL-COVID database\n\nParticipants6074 people aged 0-99 diagnosed with COVID-19\n\nMain outcome measuresSevere complications (hospitalisation, institutionalisation, death). The algorithm was developed from a training dataset comprising 70% of the patients and validated in the remaining 30%. Potential predictor variables included age, sex, a chronic co-morbidity score (CCS) based on risk factors for COVID-19 complications as defined by the National Institute of Public Health and the Environment (RIVM), obesity, neighborhood deprivation score (NDS), first or second COVID wave, and confirmation test. Six different population vaccination scenarios were explored: 1) random (naive), 2) random for persons above 60 years (60plus), 3) oldest patients first in age bands of five years (oldest first), 4) target population of the annual influenza vaccination program (influenza) and 5) those 25-65 years of age first (worker), and 6) risk-based using the prediction algorithm (sCOVID). For each vaccination strategy the amount of vaccinations needed to reach a 50% reduction of severe complications was calculated.\n\nResultsSevere complications were reported in 243 (4.8%) people with 59 (20.3%) nursing home admissions, 181 (62.2%) hospitalisations and 51 (17.5%) deaths. The algorithm included age, sex, CCS, NDS, wave, and confirmation test with a c statistic of 0.91 (95% CI 0.88-0.94) in the validation set. Applied to different vaccination scenarios, the proportion of people needed to be vaccinated to reach a 50% reduction of severe complications was 67.5%, 50.0%, 26.1%, 16.0%, 10.0%, and 8.4% for the worker, naive, infuenza, 60plus, oldest first, and sCOVID scenarios respectively.\n\nConclusionCOVID-19 related severe complications will be reduced most efficiently when vaccinations are risk-based, prioritizing the highest risk group using the sCOVID algorithm. The vaccination scenario, prioritising oldest people in age bands of 5 years down to 60 years of age, performed second best. The sCOVID algorithm can readily be applied to identify persons with highest risks from data in the electronic health records of GPs.\n\nWhat is already known on this topic?O_LISevere COVID-19 complications may be reduced when persons at the highest risk will be vaccinated first.\nC_LIO_LITo identify persons at a high risk for hospitalization or death in the general population, a limited number of prediction algorithms have been developed.\nC_LIO_LIMost of these algorithms were based on data from the first wave of infections (spring 2020) when widespread testing was not always possible, limiting the usefulness of these algorithms.\nC_LI\n\nWhat this study addsO_LIIncluding data up to January 2021, we developed and validated a prediction algorithm (sCOVID) with a c-statistic of 0.91 (95% CI 0.88-0.94) based on age, sex, chronic comorbidity score, economic status, wave, and a confirmation test to identify patients in the general population that are at risk of severe COVID-19 complication.\nC_LIO_LIUsing the algorithm, a 50% reduction of patients with severe complications could be obtained with a vaccination coverage of only 8%. This vaccination scenario based on this algorithm was superior to other calculated vaccination scenarios.\nC_LIO_LIThe sCOVID algorithm can readily be implemented in the electronic health records of general practitioners.\nC_LI", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Cameron Zachreson", - "author_inst": "The University of Melbourne" + "author_name": "Ron MC Herings", + "author_inst": "Department of Epidemiology & Data Science, Amsterdam UMC - Vrije Universiteit, Amsterdam Public Health, Amsterdam Cardiovascular Sciences, Amsterdam, the Nether" }, { - "author_name": "Erika Martino", - "author_inst": "The University of Melbourne" + "author_name": "Karin M.A. Swart", + "author_inst": "PHARMO Institute for Drug Outcome Research, Utrecht, the Netherlands" }, { - "author_name": "Martin Tomko", - "author_inst": "The University of Melbourne" + "author_name": "Bernard van der Zeijst", + "author_inst": "Department of Medical Microbiology, Leiden University Medical Center, Leiden, the Netherlands" }, { - "author_name": "Freya M Shearer", - "author_inst": "The University of Melbourne" + "author_name": "Amber A. van der Heijden", + "author_inst": "Department of General Practice, Amsterdam UMC - Vrije Universiteit, Amsterdam Public Health, Amsterdam, the Netherlands" }, { - "author_name": "Rebecca Bentley", - "author_inst": "The University of Melbourne" + "author_name": "Koos van der Velden", + "author_inst": "Department of Primary and Community Care, Academic Collaborative Center AMPHI, Integrated Health Policy, Radboud University Medical Center, the Nijmegen, Nether" }, { - "author_name": "Nicholas Geard", - "author_inst": "The University of Melbourne" + "author_name": "Eric G. Hiddink", + "author_inst": "Stichting Health Base, Houten, the Netherlands" + }, + { + "author_name": "Martijn W. Heymans", + "author_inst": "Department of Epidemiology & Data Science, Amsterdam UMC - Vrije Universiteit, Amsterdam Public Health, Amsterdam Cardiovascular Sciences, Amsterdam, the Nether" + }, + { + "author_name": "Reinier A.R. Herings", + "author_inst": "Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands" + }, + { + "author_name": "Hein P.J. van Hout", + "author_inst": "Department of General Practice, Amsterdam UMC - Vrije Universiteit, Amsterdam Public Health, Amsterdam, the Netherlands" + }, + { + "author_name": "Joline J.W. Beulens", + "author_inst": "Department of Epidemiology & Data Science, Amsterdam UMC - Vrije Universiteit, Amsterdam Public Health, Amsterdam Cardiovascular Sciences, Amsterdam, the Nether" + }, + { + "author_name": "Giel Nijpels", + "author_inst": "Department of General Practice, Amsterdam UMC - Vrije Universiteit, Amsterdam Public Health, Amsterdam, the Netherlands" + }, + { + "author_name": "Petra J.M. Elders", + "author_inst": "Department of General Practice, Amsterdam UMC - Vrije Universiteit, Amsterdam Public Health, Amsterdam, the Netherlands" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "primary care research" }, { "rel_doi": "10.1101/2021.02.05.429860", @@ -956846,41 +956840,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.07.21250586", - "rel_title": "The impact of mobility network properties on predicted epidemic dynamics in Dhaka and Bangkok", + "rel_doi": "10.1101/2021.02.06.21251265", + "rel_title": "COVIDHunter: An Accurate, Flexible, and Environment-Aware Open-Source COVID-19 Outbreak Simulation Model", "rel_date": "2021-02-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.07.21250586", - "rel_abs": "1Properties of city-level commuting networks are expected to influence epidemic potential of cities and modify the speed and spatial trajectory of epidemics when they occur. In this study, we use aggregated mobile phone user data to reconstruct commuter mobility networks for Bangkok (Thailand) and Dhaka (Bangladesh), two megacities in Asia with populations of 16 and 21 million people, respectively. We model the dynamics of directly-transmitted infections (such as SARS-CoV2) propagating on these commuting networks, and find that differences in network structure between the two cities drive divergent predicted epidemic trajectories: the commuting network in Bangkok is composed of geographically-contiguous modular communities and epidemic dispersal is correlated with geographic distance between locations, whereas the network in Dhaka has less distinct geographic structure and epidemic dispersal is less constrained by geographic distance. We also find that the predicted dynamics of epidemics vary depending on the local topology of the network around the origin of the outbreak. Measuring commuter mobility, and understanding how commuting networks shape epidemic dynamics at the city level, can support surveillance and preparedness efforts in large cities at risk for emerging or imported epidemics.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.06.21251265", + "rel_abs": "MotivationEarly detection and isolation of COVID-19 patients are essential for successful implementation of mitigation strategies and eventually curbing the disease spread. With a limited number of daily COVID-19 tests performed in every country, simulating the COVID-19 spread along with the potential effect of each mitigation strategy currently remains one of the most effective ways in managing the healthcare system and guiding policy-makers. We introduce COVIDHunter, a flexible and accurate COVID-19 outbreak simulation model that evaluates the current mitigation measures that are applied to a region and provides suggestions on what strength the upcoming mitigation measure should be. The key idea of COVIDHunter is to quantify the spread of COVID-19 in a geographical region by simulating the average number of new infections caused by an infected person considering the effect of external factors, such as environmental conditions (e.g., climate, temperature, humidity) and mitigation measures.\n\nResultsUsing Switzerland as a case study, COVIDHunter estimates that the policy-makers need to keep the current mitigation measures for at least 30 days to prevent demand from quickly exceeding existing hospital capacity. Relaxing the mitigation measures by 50% for 30 days increases both the daily capacity need for hospital beds and daily number of deaths exponentially by an average of 23.8 x, who may occupy ICU beds and ventilators for a period of time. Unlike existing models, the COVIDHunter model accurately monitors and predicts the daily number of cases, hospitalizations, and deaths due to COVID-19. Our model is flexible to configure and simple to modify for modeling different scenarios under different environmental conditions and mitigation measures.\n\nAvailabilityhttps://github.com/CMU-SAFARI/COVIDHunter\n\nContactalserm@ethz.ch, omutlu@ethz.ch\n\nSupplementary informationSupplementary data is available at Bioinformatics online.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Tyler S Brown", - "author_inst": "Massachusetts General Hospital" - }, - { - "author_name": "Kenth Eng\u00f8-Monsen", - "author_inst": "Telenor Group" + "author_name": "Mohammed Alser", + "author_inst": "ETH Zurich" }, { - "author_name": "Mathew V Kiang", - "author_inst": "Stanford University School of Medicine, Department of Epidemiology and Population Health" + "author_name": "Jeremie S. Kim", + "author_inst": "ETH Zurich" }, { - "author_name": "Ayesha S Mahmud", - "author_inst": "University of California, Berkeley, Demography Department" + "author_name": "Nour Almadhoun Alserr", + "author_inst": "ETH Zurich" }, { - "author_name": "Richard J Maude", - "author_inst": "Mahidol-Oxford Tropical Medicine Research Unit, Faculty of Tropical Medicine, Mahidol University" + "author_name": "Stefan W. Tell", + "author_inst": "ETH Zurich" }, { - "author_name": "Caroline O Buckee", - "author_inst": "Harvard T.H. Chan School of Public Health, Center for Communicable Disease Dynamics" + "author_name": "Onur Mutlu", + "author_inst": "ETH Zurich" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -958808,47 +958798,35 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.02.21251042", - "rel_title": "Mental Health, Substance Use, and Suicidal Ideation Among Unpaid Caregivers in the United States During the COVID-19 Pandemic: Relationships to Age, Race/Ethnicity, Employment, and Caregiver Intensity", + "rel_doi": "10.1101/2021.02.03.21251068", + "rel_title": "Estimating vaccine confidence levels among future healthcare workers and their trainers: A quantitative study protocol", "rel_date": "2021-02-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.02.21251042", - "rel_abs": "ObjectivesTo estimate the prevalence of unpaid caregiving during the coronavirus disease 2019 (COVID-19) pandemic, and to identify factors associated with adverse mental health symptoms, substance use, and suicidal ideation in this population, which provides critical support in health care systems by providing care to older adults and those with chronic conditions.\n\nMethodsIn June 2020, Internet-based surveys with questions about demographics, caregiving responsibilities, and mental health were administered to US adults aged [≥]18 years. Demographic quota sampling and survey weighting to improve cross-sectional sample representativeness of age, gender, and race/ethnicity. Prevalence ratios for adverse mental health symptoms were estimated using multivariable Poisson regressions.\n\nResultsOf 9,896 eligible invited adults, 5,412 (54.7%) completed surveys; 5,011 (92.6%) respondents met screening criteria and were analysed, including 1,362 (27.2%) caregivers. Caregivers had higher prevalences of adverse mental health symptoms than non-caregivers, including anxiety or depressive disorder symptoms (57.6% vs 21.5%, respectively, p<0.0001) having recently seriously considered suicide (33.4% vs 3.7%, p<0.0001). Symptoms were more common among caregivers who were young vs older adults (e.g., aged 18-24 vs [≥]65 years, aPR 2.75, 95% CI 1.95-3.88, p<0.0001), Hispanic or Latino vs non-Hispanic White (1.14, 1.04-1.25, p=0.0044), living with vs without disabilities (1.18, 1.10-1.26, p<0.0001), and with moderate and high vs low Caregiver Intensity Index scores (2.31, 1.65-3.23; 2.81, 2.00-3.94; both p<0.0001). Suicidal ideation was more prevalent among non-Hispanic Black vs non-Hispanic White caregivers (1.48, 1.15-1.90, p=0.0022).\n\nConclusionsCaregivers, who accounted for one in four US adult respondents in this nationally representative sample, more commonly reported adverse mental health symptoms than non-caregivers. Increased visibility of and access to mental health care resources are urgently needed to address mental health challenges of caregiving.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.03.21251068", + "rel_abs": "IntroductionThe outbreak of novel coronavirus disease 2019 (COVID-19) caught the world off guard in the first quarter of the year 2020. To stem the tide of this pandemic, the development, testing, and pre-licensure approval for emergency use of some COVID 19 vaccine candidates were accelerated. This led to raised public concern about their safety and efficacy, compounding the challenges of vaccine hesitancy which was already declared one of the top ten threats to global health in the year 2019. The onus of managing and administering these vaccines to a skeptical populace when they do become available rests mostly on the shoulders of healthcare workers (HCWs). Therefore, the vaccine confidence levels of HCWs becomes critical to the success of vaccination endeavors, especially COVID 19 vaccination. This proposed study aims to estimate the level of vaccine confidence and the intention to receive a COVID 19 vaccine among future HCWs and their trainers at a specific university in Cape Town, South Africa, and to identify any vaccination concerns early for targeted intervention.\n\nMethods and analysisAn online survey will be distributed to current staff and students of an academic institution for HCWs. The survey questionnaire will consist of a demographic questions section consisting of six items and a vaccine confidence section comprising six items in Likert scale format.\n\nA multinomial logistic regression model will be employed to identify factors associated with vaccine confidence and intention. The strength of association will be assessed using odds ratio and its 95% confidence interval. Statistical significance will be defined at a p-value <0.05.\n\nEthics and disseminationEthics approval has been obtained for the study from Stellenbosch University (HREC Reference # S19/01/014 (PhD)). The results will be shared with relevant health authorities, presented at conferences, and published in a peer-reviewed journal.\n\nARTICLE SUMMARYO_ST_ABSStrengths and limitations of this studyC_ST_ABS{blacktriangleright} The proposed study will generate baseline knowledge of the vaccine confidence among future healthcare workers and their trainers in its specific context.\n{blacktriangleright}It will contribute to addressing the knowledge gap about the intention to receive a COVID 19 vaccine among health care workers in Africa.\n{blacktriangleright}It will enable the early identification of vaccine concerns of healthcare workers while they are still in training and assist in informing tailored measures to address them.\n{blacktriangleright}A limitation of the study is the possibility of a low response rate which is an inherent challenge of online surveys.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Mark \u00c9 Czeisler", - "author_inst": "Monash University" - }, - { - "author_name": "Alexandra Drane", - "author_inst": "ARCHANGELS" - }, - { - "author_name": "Sarah S. Winnay", - "author_inst": "ARCHANGELS" - }, - { - "author_name": "Emily R. Capodilupo", - "author_inst": "WHOOP, Inc." + "author_name": "Elizabeth O. Oduwole", + "author_inst": "Stellenbosch University" }, { - "author_name": "Charles A. Czeisler", - "author_inst": "Brigham & Women's Hospital" + "author_name": "Hassan Mahomed", + "author_inst": "Stellenbosch University" }, { - "author_name": "Shantha M.W. Rajaratnam", - "author_inst": "Monash University" + "author_name": "Brihanu T Ayele", + "author_inst": "Stellenbosch University" }, { - "author_name": "Mark E. Howard", - "author_inst": "Austin Health" + "author_name": "Charles S. Wiysonge", + "author_inst": "South African Medical Resaerch Council" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.02.01.21250371", @@ -960494,1199 +960472,43 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2021.02.03.21250974", - "rel_title": "Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US", + "rel_doi": "10.1101/2021.02.05.429917", + "rel_title": "Catching SARS-CoV-2 by sequence hybridization: a comparative analysis", "rel_date": "2021-02-05", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.03.21250974", - "rel_abs": "Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multi-model ensemble forecast that combined predictions from dozens of different research groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naive baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-week horizon 3-5 times larger than when predicting at a 1-week horizon. This project underscores the role that collaboration and active coordination between governmental public health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks.\n\nSignificance StatementThis paper compares the probabilistic accuracy of short-term forecasts of reported deaths due to COVID-19 during the first year and a half of the pandemic in the US. Results show high variation in accuracy between and within stand-alone models, and more consistent accuracy from an ensemble model that combined forecasts from all eligible models. This demonstrates that an ensemble model provided a reliable and comparatively accurate means of forecasting deaths during the COVID-19 pandemic that exceeded the performance of all of the models that contributed to it. This work strengthens the evidence base for synthesizing multiple models to support public health action.", - "rel_num_authors": 295, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.05.429917", + "rel_abs": "Controlling and monitoring the still ongoing SARS-CoV-2 pandemic regarding geographical distributions, evolution and emergence of new mutations of the SARS-CoV-2 virus is only possible due to continuous next-generation sequencing (NGS) and worldwide sequence data sharing. Efficient sequencing strategies enabling the retrieval of the maximum number of high quality, full-length genomes are hence indispensable. Here, we describe for the first time a combined approach of digital droplet PCR (ddPCR) and NGS to evaluate five commercially available sequence capture panels targeting SARS-CoV-2. In doing so, we were not only able to determine the most sensitive and specific capture panel, but to discriminate their mode of action and number of read pairs needed to recover a high quality full length genome. Thereby, we are providing essential information for all sequencing laboratories worldwide striving for maximizing the sequencing output and simultaneously minimizing time, costs and sequencing resources.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Estee Y Cramer", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Evan L Ray", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Velma K Lopez", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Johannes Bracher", - "author_inst": "Chair of Econometrics and Statistics, Karlsruhe Institute of Technology; Computational Statistics Group, Heidelberg Institute for Theoretical Studies" - }, - { - "author_name": "Andrea Brennen", - "author_inst": "IQT" - }, - { - "author_name": "Alvaro J Castro Rivadeneira", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Aaron Gerding", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Tilmann Gneiting", - "author_inst": "Institute of Stochastics, Karlsruhe Institute of Technology" - }, - { - "author_name": "Katie H House", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Yuxin Huang", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Dasuni Jayawardena", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Abdul H Kanji", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Ayush Khandelwal", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Khoa Le", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Anja Muehlemann", - "author_inst": "Institute of Mathematical Statistics and Actuarial Science, University of Bern" - }, - { - "author_name": "Jarad Niemi", - "author_inst": "Iowa State University" - }, - { - "author_name": "Apurv Shah", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Ariane Stark", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Yijin Wang", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Nutcha Wattanachit", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Martha W Zorn", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Youyang Gu", - "author_inst": "Unaffiliated" - }, - { - "author_name": "Sansiddh Jain", - "author_inst": "Wadhwani Institute of Artificial Intelligence" - }, - { - "author_name": "Nayana Bannur", - "author_inst": "Wadhwani Institute of Artificial Intelligence" - }, - { - "author_name": "Ayush Deva", - "author_inst": "Wadhwani Institute of Artificial Intelligence" - }, - { - "author_name": "Mihir Kulkarni", - "author_inst": "Wadhwani Institute of Artificial Intelligence" - }, - { - "author_name": "Srujana Merugu", - "author_inst": "Wadhwani Institute of Artificial Intelligence" - }, - { - "author_name": "Alpan Raval", - "author_inst": "Wadhwani Institute of Artificial Intelligence" - }, - { - "author_name": "Siddhant Shingi", - "author_inst": "Wadhwani Institute of Artificial Intelligence" - }, - { - "author_name": "Avtansh Tiwari", - "author_inst": "Wadhwani Institute of Artificial Intelligence" - }, - { - "author_name": "Jerome White", - "author_inst": "Wadhwani Institute of Artificial Intelligence" - }, - { - "author_name": "Neil F Abernethy", - "author_inst": "University of Washington" - }, - { - "author_name": "Spencer Woody", - "author_inst": "University of Texas at Austin" - }, - { - "author_name": "Maytal Dahan", - "author_inst": "Texas Advanced Computing Center" - }, - { - "author_name": "Spencer Fox", - "author_inst": "University of Texas at Austin" - }, - { - "author_name": "Kelly Gaither", - "author_inst": "Texas Advanced Computing Center" - }, - { - "author_name": "Michael Lachmann", - "author_inst": "Santa Fe Institute" - }, - { - "author_name": "Lauren Ancel Meyers", - "author_inst": "University of Texas at Austin" - }, - { - "author_name": "James G Scott", - "author_inst": "University of Texas at Austin" - }, - { - "author_name": "Mauricio Tec", - "author_inst": "University of Texas at Austin" - }, - { - "author_name": "Ajitesh Srivastava", - "author_inst": "University of Southern California" - }, - { - "author_name": "Glover E George", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Jeffrey C Cegan", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Ian D Dettwiller", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "William P England", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Matthew W Farthing", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Robert H Hunter", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Brandon Lafferty", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Igor Linkov", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Michael L Mayo", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Matthew D Parno", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Michael A Rowland", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Benjamin D Trump", - "author_inst": "US Army Engineer Research and Development Center" - }, - { - "author_name": "Yanli Zhang-James", - "author_inst": "State University of New York Upstate Medical University" - }, - { - "author_name": "Samuel Chen", - "author_inst": "State University of New York Upstate Medical University" - }, - { - "author_name": "Stephen V Faraone", - "author_inst": "State University of New York Upstate Medical University" - }, - { - "author_name": "Jonathan Hess", - "author_inst": "State University of New York Upstate Medical University" - }, - { - "author_name": "Christopher P Morley", - "author_inst": "State University of New York Upstate Medical University" - }, - { - "author_name": "Asif Salekin", - "author_inst": "Syracuse University" - }, - { - "author_name": "Dongliang Wang", - "author_inst": "State University of New York Upstate Medical University" - }, - { - "author_name": "Sabrina M Corsetti", - "author_inst": "University of Michigan - Ann Arbor" - }, - { - "author_name": "Thomas M Baer", - "author_inst": "Trinity University, San Antonio" - }, - { - "author_name": "Marisa C Eisenberg", - "author_inst": "University of Michigan - Ann Arbor" - }, - { - "author_name": "Karl Falb", - "author_inst": "University of Michigan - Ann Arbor" - }, - { - "author_name": "Yitao Huang", - "author_inst": "University of Michigan - Ann Arbor" - }, - { - "author_name": "Emily T Martin", - "author_inst": "University of Michigan - Ann Arbor" - }, - { - "author_name": "Ella McCauley", - "author_inst": "University of Michigan - Ann Arbor" - }, - { - "author_name": "Robert L Myers", - "author_inst": "University of Michigan - Ann Arbor" - }, - { - "author_name": "Tom Schwarz", - "author_inst": "University of Michigan - Ann Arbor" - }, - { - "author_name": "Daniel Sheldon", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Graham Casey Gibson", - "author_inst": "University of Massachusetts, Amherst" - }, - { - "author_name": "Rose Yu", - "author_inst": "Northeastern University; University of California, San Diego" - }, - { - "author_name": "Liyao Gao", - "author_inst": "University of Washington" - }, - { - "author_name": "Yian Ma", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Dongxia Wu", - "author_inst": "University of California, San Diego" - }, - { - "author_name": "Xifeng Yan", - "author_inst": "University of California at Santa Barbara" - }, - { - "author_name": "Xiaoyong Jin", - "author_inst": "University of California at Santa Barbara" - }, - { - "author_name": "Yu-Xiang Wang", - "author_inst": "University of California at Santa Barbara" - }, - { - "author_name": "YangQuan Chen", - "author_inst": "University of California, Merced" - }, - { - "author_name": "Lihong Guo", - "author_inst": "Jilin University" - }, - { - "author_name": "Yanting Zhao", - "author_inst": "University of Science and Technology of China" - }, - { - "author_name": "Quanquan Gu", - "author_inst": "University of California, Los Angeles" - }, - { - "author_name": "Jinghui Chen", - "author_inst": "University of California, Los Angeles" - }, - { - "author_name": "Lingxiao Wang", - "author_inst": "University of California, Los Angeles" - }, - { - "author_name": "Pan Xu", - "author_inst": "University of California, Los Angeles" - }, - { - "author_name": "Weitong Zhang", - "author_inst": "University of California, Los Angeles" - }, - { - "author_name": "Difan Zou", - "author_inst": "University of California, Los Angeles" - }, - { - "author_name": "Hannah Biegel", - "author_inst": "University of Arizona" - }, - { - "author_name": "Joceline Lega", - "author_inst": "University of Arizona" - }, - { - "author_name": "Steve McConnell", - "author_inst": "Construx" - }, - { - "author_name": "VP Nagraj", - "author_inst": "Signature Science, LLC" - }, - { - "author_name": "Stephanie L Guertin", - "author_inst": "Signature Science, LLC" - }, - { - "author_name": "Christopher Hulme-Lowe", - "author_inst": "Signature Science, LLC" - }, - { - "author_name": "Stephen D Turner", - "author_inst": "Signature Science, LLC" - }, - { - "author_name": "Yunfeng Shi", - "author_inst": "Rensselaer Polytechnic Institute" - }, - { - "author_name": "Xuegang Ban", - "author_inst": "University of Washington" - }, - { - "author_name": "Robert Walraven", - "author_inst": "Unaffiliated" - }, - { - "author_name": "Qi-Jun Hong", - "author_inst": "Arizona State University; Brown University" - 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"author_inst": "Oliver Wyman" - }, - { - "author_name": "Michael Moloney", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "James Morgan", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Ninad Nirgudkar", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Gokce Ozcan", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Noah Piwonka", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Matt Ravi", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Chris Schrader", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Elizabeth Shakhnovich", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Daniel Siegel", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Ryan Spatz", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Chris Stiefeling", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Barrie Wilkinson", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Alexander Wong", - "author_inst": "Oliver Wyman" - }, - { - "author_name": "Sean Cavany", - "author_inst": "University of Notre Dame" - }, - { - "author_name": "Guido Espana", - "author_inst": "University of Notre Dame" - }, - { - "author_name": "Sean Moore", - "author_inst": "University of Notre Dame" - }, - { - "author_name": "Rachel Oidtman", - "author_inst": "University of Chicago; University of Notre Dame" - }, - { - "author_name": "Alex Perkins", - "author_inst": "University of Notre Dame" - }, - { - "author_name": "David Kraus", - "author_inst": "Masaryk University" - }, - { - "author_name": "Andrea Kraus", - "author_inst": "Masaryk University" - }, - { - "author_name": "Zhifeng Gao", - "author_inst": "Microsoft" - }, - { - "author_name": "Jiang Bian", - "author_inst": "Microsoft" - }, - { - "author_name": "Wei Cao", - "author_inst": "Microsoft" - }, - { - "author_name": "Juan Lavista Ferres", - "author_inst": "Microsoft" - }, - { - "author_name": "Chaozhuo Li", - "author_inst": "Microsoft" - }, - { - "author_name": "Tie-Yan Liu", - 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Antwerpen", + "author_inst": "Bundeswehr Institute of Microbiology" }, { - "author_name": "Nicholas G Reich", - "author_inst": "University of Massachusetts, Amherst" + "author_name": "Mathias C. Walter", + "author_inst": "Bundeswehr Institute of Microbiology" } ], "version": "1", - "license": "cc0", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "genomics" }, { "rel_doi": "10.1101/2021.02.05.428650", @@ -963220,31 +962042,71 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.02.01.21250877", - "rel_title": "Optimal time to return to normality: parallel use of COVID-19 vaccines and circuit breakers", + "rel_doi": "10.1101/2021.02.01.21250900", + "rel_title": "RAY: CRISPR diagnostic for rapid and accurate detection of SARS-CoV2 variants on a paper strip", "rel_date": "2021-02-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.01.21250877", - "rel_abs": "By January 2020, the COVID-19 illness has caused over two million deaths. Countries have restricted disease spread through non-pharmaceutical interventions (e.g., social distancing). More severe \"lockdowns\" have also been required. Although lockdowns keep people safer from the virus, they substantially disrupt economies and individual well-being. Fortunately, vaccines are becoming available. Yet, vaccination programs may take several months to implement, requiring further time for individuals to develop immunity following inoculation. To prevent health services being overwhelmed it may be necessary to implement further lockdowns in conjunction with vaccination. Here, we investigate optimal approaches for vaccination under varying lockdown lengths and/or severities to prevent COVID-19-related deaths exceeding critical thresholds. We find increases in vaccination rate cause a disproportionately larger decrease in lockdowns: with vaccination, severe lockdowns can reduce infections by up to 89%. Notably, we include demographics, modelling three groups: vulnerable, front-line workers, and non-vulnerable. We investigate the sequence of vaccination. One counter-intuitive finding is that even though the vulnerable group is high risk, demographically, this is a small group (per person, vaccination occurs more slowly) so vaccinating this group first achieves limited gains in overall disease control. Better disease control occurs by vaccinating the non-vulnerable group with longer and/or more severe lockdowns.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.01.21250900", + "rel_abs": "The COVID-19 pandemic originating in the Wuhan province of China in late 2019 has impacted global health, causing increased mortality among elderly patients and individuals with comorbid conditions. During the passage of the virus through affected populations, it has undergone mutations- some of which have recently been linked with increased viral load and prognostic complexities. Interestingly, several of these variants are point mutations that are difficult to diagnose using the gold standard quantitative real-time PCR (qPCR) method. This necessitates widespread sequencing which is expensive, has long turn-around times, and requires high viral load for calling mutations accurately. In this study, we show that the high specificity of Francisella novicida Cas9 (FnCas9) to point mismatches can be successfully adapted for the simultaneous detection of SARS-CoV2 infection as well as for detecting point mutations in the sequence of the virus obtained from patient samples. We report the detection of the mutation N501Y (earlier shown to be present in the British N501Y.V1, South African N501Y.V2, and Brazilian N501Y.V3 variants of SARS-CoV2) within an hour using paper strip chemistry. The results were corroborated using deep sequencing. Our design principle can be rapidly adapted for other mutations, highlighting the advantages of quick optimization and roll-out of CRISPR diagnostics (CRISPRDx) for disease surveillance even beyond COVID-19.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Michael Bonsall", - "author_inst": "University of Oxford" + "author_name": "Manoj Kumar", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" }, { - "author_name": "Chris Huntingford", - "author_inst": "UK Centre for Ecology and Hydrology, Wallingford" + "author_name": "Sneha Gulati", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" }, { - "author_name": "Thomas Rawson", - "author_inst": "Dept of Zoology, University of Oxford" + "author_name": "Asgar H Ansari", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Rhythm Phutela", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Sundaram Acharya", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Poorti Kathpalia", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Akshay Kanakan", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Ranjeet Maurya", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Janani Srinivasa Vasudevan", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Aparna Murali", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Rajesh Pandey", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Souvik Maiti", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" + }, + { + "author_name": "Debojyoti Chakraborty", + "author_inst": "CSIR Institute of Genomics and Integrative Biology" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2021.02.01.21250898", @@ -965434,41 +964296,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.02.02.21250985", - "rel_title": "Rapid vaccination and early reactive partial lockdown will minimize deaths from emerging highly contagious SARS-CoV-2 variants", + "rel_doi": "10.1101/2021.02.01.21250839", + "rel_title": "Extremely high SARS-CoV-2 seroprevalence in a strictly-Orthodox Jewish community in the UK", "rel_date": "2021-02-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.02.21250985", - "rel_abs": "The goals of SARS-CoV-2 vaccination programs are to maximally reduce cases and deaths, and to limit the amount of time required under lockdown. Using a mathematical model calibrated to data from King County Washington but generalizable across states, we simulated multiple scenarios with different vaccine efficacy profiles, vaccination rates, and case thresholds for triggering and relaxing partial lockdowns. We assumed that a contagious variant is currently present at low levels. In all scenarios, it rapidly becomes dominant by early summer. Low case thresholds for triggering partial lockdowns during current and future waves of infection strongly predict lower total numbers of COVID-19 infections, hospitalizations and deaths in 2021. However, in regions with relatively higher current seroprevalence, there is a predicted delay in onset of a subsequent surge in new variant infections. For all vaccine efficacy profiles, increasing vaccination rate lowers the total number of infections and deaths, as well as the total number of days under partial lockdown. Due to variable current estimates of emerging variant infectiousness, vaccine efficacy against these variants, vaccine refusal, and future adherence to masking and physical distancing, we project considerable uncertainty regarding the timing and intensity of subsequent waves of infection. Nevertheless, under all plausible scenarios, rapid vaccination and early implementation of partial lockdown are the two most critical variables to save the greatest number of lives.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.02.01.21250839", + "rel_abs": "BackgroundEthnic and religious minorities have been disproportionately affected by SARS-CoV-2 worldwide. The UK strictly-Orthodox Jewish community has been severely affected by the pandemic. This group shares characteristics with other ethnic minorities including larger family sizes, higher rates of household crowding and relative socioeconomic deprivation. We studied a UK strictly-Orthodox Jewish population to understand how COVID-19 had spread within this community.\n\nMethodsWe performed a household-focused cross-sectional SARS-CoV-2 serosurvey specific to three antigen targets. Randomly-selected households completed a standardised questionnaire and underwent serological testing with a multiplex assay for SARS-CoV-2 IgG antibodies. We report clinical illness and testing before the serosurvey, seroprevalence stratified by age and gender. We used random-effects models to identify factors associated with infection and antibody titres.\n\nFindingsA total of 343 households, consisting of 1,759 individuals, were recruited. Serum was available for 1,242 participants. The overall seroprevalence for SARS-CoV-2 was 64.3% (95% CI 61.6-67.0%). The lowest seroprevalence was 27.6% in children under 5 years and rose to 73.8% in secondary school children and 74% in adults. Antibody titres were higher in symptomatic individuals and declined over time since reported COVID-19 symptoms, with the decline more marked for nucleocapsid titres.\n\nInterpretationIn this tight-knit religious minority population in the UK, we report one of the highest SARS-CoV-2 seroprevalence levels in the world to date. In the context of this high force of infection, all age groups experienced a high burden of infection. Actions to reduce the burden of disease in this and other minority populations are urgently required.\n\nFundingThis work was jointly funded by UKRI and NIHR [COV0335; MR/V027956/1], a donation from the LSHTM Alumni COVID-19 response fund, HDR UK, the MRC and the Wellcome Trust. The funders had no role in the design, conduct or analysis of the study or the decision to publish. The authors have no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.\n\nResearch In ContextO_ST_ABSEvidence before the studyC_ST_ABSIn January 2020, we searched PubMed for articles on rates of SARS-CoV-2 infection amongst ethnic minority groups and amongst the Jewish population. Search teams included \"COVID-19\", \"SARS-CoV-2\", seroprevalence, \"ethnic minority\", and \"Jewish\" with no language restrictions. We also searched UK government documents on SARS-CoV-2 infection amongst minority groups. By January 2020, a large number of authors had reported that ethnic minority groups experienced higher numbers of cases and increased hospitalisations due to COVID-19. A small number of articles provided evidence that strictly-Orthodox Jewish populations had experienced a high rate of SARS-CoV-2 infection but extremely limited data was available on overall population level rates of infection amongst specific ethnic minority population groups. There was also extremely limited data on rates of infection amongst young children from ethnic minority groups.\n\nAdded value of the studyWe report findings from a population representative, household survey of SARS-CoV-2 infection amongst a UK strictly Orthodox Jewish population. We demonstrate an extremely high seroprevalence rate of SARS-CoV-2 in this population which is more than five times the estimated seroprevalence nationally and five times the estimated seroprevalence in London. In addition the large number of children in our survey, reflective of the underlying population structure, allows us to demonstrate that in this setting there is a significant burden of disease in all age groups with secondary school aged children having an equivalent seroprevalence to adults.\n\nImplications of the available evidenceOur data provide clear evidence of the markedly disproportionate impact of SARS-CoV-2 in minority populations. In this setting infection occurs at high rates across all age groups including pre-school, primary school and secondary school-age children. Contextually appropriate measures to specifically reduce the impact of SARS-CoV-2 amongst minority populations are urgently required.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Daniel B Reeves", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Katherine M Gaskell", + "author_inst": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" }, { - "author_name": "Chloe Bracis", - "author_inst": "Universite Grenoble Alpes" + "author_name": "Marina Johnson", + "author_inst": "Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London" }, { - "author_name": "David A Swan", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Victoria Gould", + "author_inst": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" }, { - "author_name": "Mia Moore", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Adam Hunt", + "author_inst": "Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London" }, { - "author_name": "Dobromir Dimitrov", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Neil RH Stone", + "author_inst": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK & Hospital for Tropical Diseases, University C" }, { - "author_name": "Joshua T Schiffer", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "William Waites", + "author_inst": "Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" + }, + { + "author_name": "Ben Kasstan", + "author_inst": "Centre for Health, Law and Society, University of Bristol Law School, Bristol. BS1 1RJ" + }, + { + "author_name": "Tracey Chantler", + "author_inst": "Department of Global Health and Development, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" + }, + { + "author_name": "Sham Lal", + "author_inst": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" + }, + { + "author_name": "Chrissy h. Roberts", + "author_inst": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" + }, + { + "author_name": "David Goldblatt", + "author_inst": "Great Ormond Street Institute of Child Health Biomedical Research Centre, University College London" + }, + { + "author_name": "Rosalind M Eggo", + "author_inst": "Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK" + }, + { + "author_name": "Michael M Marks", + "author_inst": "Department of Clinical Research, London School of Hygiene & Tropical Medicine, Keppel Street, London. WC1E 7HT UK & Hospital for Tropical Diseases, University C" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -967484,27 +966374,39 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2021.02.03.429201", - "rel_title": "'Phytopathological strolls' in the dual context of COVID-19 lockdown and IYPH2020: transforming constraints into an opportunity for public education about plant pathogens", + "rel_doi": "10.1101/2021.02.02.429476", + "rel_title": "LIFE AND WORK OF RESEARCHERS TRAPPED IN THE COVID-19PANDEMIC VICIOUS CYCLE", "rel_date": "2021-02-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.03.429201", - "rel_abs": "The experience presented here relates to 2020, a particularly timely year for plant disease-related communication ( International Year of Plant Health IYPH2020), but also a unique year because of the COVID-19 pandemic. Our goal was to illustrate the diversity and beauty of fungal plant pathogens through a naturalist approach that could be followed by any amateur. We achieved this end through phytopathological strolls, in which we observed and determined the origin of symptoms on diseased plants found in our garden, in the local streets, in nearby open spaces, and sharing this matter with a broad public. The lockdown imposed in France created an additional motivation to take up the challenge, and to involve our children, even under strong constraints, such as movement restrictions. We observed and described fungal pathogens through hundreds of photographs, shared our findings with a large audience on Twitter, and received feedback. The material used was deliberately simple and transportable: a digital reflex camera, an old microscope, a mobile phone, some books and an Internet connexion. Between March 17, 2020 and June 20, 2021 we found 196 plant pathogens, including 97 rusts, 27 powdery mildews and 28 septoria-like diseases. We discuss here the importance of promoting searches for plant pathogens, their description and conservation, through a combination of classical approaches and digital tools in tune with the times, such as Twitter, by treating pathogen identification like a detective game and, more surprisingly, by making use of the addictive nature of collection approaches, drawing a parallel with Pokemon Go.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.02.02.429476", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWCOVID-19 has disrupted researchers work and posed challenges to their life routines. We have surveyed 740 researchers of which 66% experienced a decrease in productivity, 50% indicated increased workload, and 66% reported they have been feeling internal pressure to make progress. Those whose research required physical presence in a lab or the field experienced considerable disruption and productivity decrease. About 82% of this group will try to permanently reduce their work dependency on physical presence. Parents and those taking care of vulnerable dependents have been spending less time on research due to their role conflict. We further observed a gender gap in the overall disruption consequences; more female researchers have been experiencing a reduction in productivity and external pressure to make progress. The results of this study can help institution leaders and policymakers better understand the pandemics challenges for the research community and motivate appropriate measures to instill long-term solutions.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Fr\u00e9d\u00e9ric Suffert", - "author_inst": "INRAE" + "author_name": "S. Aryan Ghaffarizadeh", + "author_inst": "University of Toronto" }, { - "author_name": "Muriel Suffert", - "author_inst": "EPPO" + "author_name": "S. Arman Ghaffarizadeh", + "author_inst": "Carnegie Mellon University" + }, + { + "author_name": "Amir H. Behbahani", + "author_inst": "California Institute of Technology" + }, + { + "author_name": "Mohammad Mehdizadeh", + "author_inst": "Louisiana State University" + }, + { + "author_name": "Alison Olechowski", + "author_inst": "University of Toronto" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "new results", - "category": "microbiology" + "category": "scientific communication and education" }, { "rel_doi": "10.1101/2021.02.01.429069", @@ -969170,63 +968072,39 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2021.01.30.428979", - "rel_title": "Production of SARS-CoV-2 virus-like particles in insect cells", + "rel_doi": "10.1101/2021.01.28.21250718", + "rel_title": "Prediction Models for Severe Manifestations and Mortality due to COVID-19: A Rapid Systematic Review", "rel_date": "2021-02-01", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.30.428979", - "rel_abs": "Coronavirus disease (COVID-19) causes a serious threat to human health. To production of SARS-COV-2 virus-like particles (VLPs) in insect cells for vaccine development and scientific research. The E, M and S genes were cloned into multiple cloning sites of the new triple expression plasmid with one p10 promoter, two pPH promoters and three multiple cloning sites. The plasmid was transformed into DH10 BacTM Escherichia coli competent cells to obtain recombinant bacmid. Then the recombinant bacmid was transfected in ExpiSf9 insect cells to generate recombinant baculovirus. After ExpiSf9 infected with the recombinant baculovirus, the E, M, and S protein co-expressed in insect cells. Finally, SARS-CoV-2 VLPs were self-assembled in insect cells after infection. The morphology and the size of SARS-CoV-2 VLPs are similar to the native virions.", - "rel_num_authors": 11, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250718", + "rel_abs": "BackgroundThroughout 2020, the coronavirus disease 2019 (COVID-19) has become a threat to public health on national and global level. There has been an immediate need for research to understand the clinical signs and symptoms of COVID-19 that can help predict deterioration including mechanical ventilation, organ support, and death. Studies thus far have addressed the epidemiology of the disease, common presentations, and susceptibility to acquisition and transmission of the virus; however, an accurate prognostic model for severe manifestations of COVID-19 is still needed because of the limited healthcare resources available.\n\nObjectiveThis systematic review aims to evaluate published reports of prediction models for severe illnesses caused COVID-19.\n\nMethodsSearches were developed by the primary author and a medical librarian using an iterative process of gathering and evaluating terms. Comprehensive strategies, including both index and keyword methods, were devised for PubMed and EMBASE. The data of confirmed COVID-19 patients from randomized control studies, cohort studies, and case-control studies published between January 2020 and July 2020 were retrieved. Studies were independently assessed for risk of bias and applicability using the Prediction Model Risk Of Bias Assessment Tool (PROBAST). We collected study type, setting, sample size, type of validation, and outcome including intubation, ventilation, any other type of organ support, or death. The combination of the prediction model, scoring system, performance of predictive models, and geographic locations were summarized.\n\nResultsA primary review found 292 articles relevant based on title and abstract. After further review, 246 were excluded based on the defined inclusion and exclusion criteria. Forty-six articles were included in the qualitative analysis. Inter observer agreement on inclusion was 0.86 (95% confidence interval: 0.79 - 0.93). When the PROBAST tool was applied, 44 of the 46 articles were identified to have high or unclear risk of bias, or high or unclear concern for applicability. Two studied reported prediction models, 4C Mortality Score from hospital data and QCOVID from general public data from UK, and were rated as low risk of bias and low concerns for applicability.\n\nConclusionSeveral prognostic models are reported in the literature, but many of them had concerning risks of biases and applicability. For most of the studies, caution is needed before use, as many of them will require external validation before dissemination. However, two articles were found to have low risk of bias and low applicability can be useful tools.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Youjun mi", - "author_inst": "lanzhou university" - }, - { - "author_name": "Tao Xie", - "author_inst": "lanzhou university" - }, - { - "author_name": "BingDong Zhu", - "author_inst": "Lanzhou university" - }, - { - "author_name": "JiYing tan", - "author_inst": "LanZhou University" - }, - { - "author_name": "XueFeng Li", - "author_inst": "LanZhou University" - }, - { - "author_name": "YanPing Luo", - "author_inst": "LanZhou University" + "author_name": "Jamie Miller", + "author_inst": "The University of Iowa Carver College of Medicine" }, { - "author_name": "Fei Li", - "author_inst": "LanZhou University" - }, - { - "author_name": "HongXia Niu", - "author_inst": "LanZhou Uiversity" + "author_name": "Masafumi Tada", + "author_inst": "Kyoto University" }, { - "author_name": "JiangYuan Han", - "author_inst": "LanZhou University" + "author_name": "Michihiko Goto", + "author_inst": "University of Iowa Carver College of Medicine" }, { - "author_name": "Wei Lv", - "author_inst": "LanZhou University" + "author_name": "Nicholas M Mohr", + "author_inst": "The University of Iowa Carver College of Medicine" }, { - "author_name": "Juan Wang", - "author_inst": "LanZhou University" + "author_name": "Sangil Lee", + "author_inst": "The University of Iowa" } ], "version": "1", - "license": "", - "type": "new results", - "category": "bioengineering" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "emergency medicine" }, { "rel_doi": "10.1101/2021.01.28.21250622", @@ -970884,57 +969762,69 @@ "category": "rehabilitation medicine and physical therapy" }, { - "rel_doi": "10.1101/2021.01.29.21250757", - "rel_title": "Updated SARS-CoV-2 Single Nucleotide Variants and Mortality Association", + "rel_doi": "10.1101/2021.01.29.20248125", + "rel_title": "Estimating the COVID-19 Prevalence in Spain with Indirect Reporting via Open Surveys", "rel_date": "2021-02-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.29.21250757", - "rel_abs": "Since its outbreak in December 2019, COVID-19 has caused 100,5844,555 cases and 2,167,313 deaths as of Jan 27, 2021. Comparing our previous study of SARS-CoV-2 single nucleotide variants (SNVs) before June 2020, we found out that the SNV clustering had changed considerably since June 2020. Apart from that the group SNVs represented by two non-synonymous mutations A23403G (S: D614G) and C14408T (ORF1ab: P4715L) became dominant and carried by over 95% genomes, a few emerging groups of SNVs were recognized with sharply increased monthly occurrence ratios up to 70% in November 2020. Further investigation revealed that several SNVs were strongly associated with the mortality, but they presented distinct distribution in specific countries, e.g., Brazil, USA, Saudi Arabia, India, and Italy. SNVs including G25088T, T25A, G29861T and G29864A were adopted in a regularized logistic regression model to predict the mortality status in Brazil with the AUC of 0.84. Protein structure analysis showed that the emerging subgroups of non-synonymous SNVs and those mortality-related ones in Brazil were located on protein surface area. The clashes in protein structure introduced by these mutations might in turn affect virus pathogenesis through conformation changes, leading to the difference in transmission and virulence. Particularly, we found that SNVs tended to occur in intrinsic disordered regions (IDRs) of Spike (S) and ORF1ab, suggesting a critical role of SNVs in protein IDRs to determine protein folding and immune evasion.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.29.20248125", + "rel_abs": "During the initial phases of the COVID-19 pandemic, accurate tracking has proven unfeasible. Initial estimation methods pointed towards case numbers that were much higher than officially reported. In the CoronaSurveys project, we have been addressing this issue using open online surveys with indirect reporting. We compare our estimates with the results of a serology study for Spain, obtaining high correlations (R squared 0.89). In our view, these results strongly support the idea of using open surveys with indirect reporting as a method to broadly sense the progress of a pandemic.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Shuyi Fang", - "author_inst": "Indiana University" + "author_name": "Augusto Garcia-Agundez", + "author_inst": "TU Darmstadt" }, { - "author_name": "Sheng Liu", - "author_inst": "Indiana University School of Medicine" + "author_name": "Oluwasegun Ojo", + "author_inst": "IMDEA Networks Institute" }, { - "author_name": "Jikui Shen", - "author_inst": "Johns Hopkins University" + "author_name": "Harold Hernandez", + "author_inst": "Universidad Carlos III de Madrid" }, { - "author_name": "Alex Z Lu", - "author_inst": "Park Tudor School, Indianapolis, Indiana USA" + "author_name": "Carlos Baquero", + "author_inst": "Universidade do Minho" }, { - "author_name": "Yucheng Zhang", - "author_inst": "Indiana University School of Medicine" + "author_name": "Davide Frey", + "author_inst": "Inria" }, { - "author_name": "Kailing Li", - "author_inst": "Indiana University" + "author_name": "Chryssis Georgiou", + "author_inst": "University of Cyprus" }, { - "author_name": "Juli Liu", - "author_inst": "Indiana University School of Medicine" + "author_name": "Mathieu Goessens", + "author_inst": "University of Rennes" }, { - "author_name": "Lei Yang", - "author_inst": "Indiana University School of Medicine" + "author_name": "Rosa Lillo", + "author_inst": "Universidad Carlos III de Madrid" }, { - "author_name": "Chang-Deng Hu", - "author_inst": "Purdue University" + "author_name": "Raquel Menezes", + "author_inst": "Universidade do Minho" }, { - "author_name": "Jun Wan", - "author_inst": "Indiana University School of Medicine" + "author_name": "Nicolas Nicolaou", + "author_inst": "Algolysis" + }, + { + "author_name": "Antonio Ortega", + "author_inst": "USC Viterbi School of Engineering" + }, + { + "author_name": "Efstathios Stavrakis", + "author_inst": "Algolysis" + }, + { + "author_name": "Antonio Fernandez Anta", + "author_inst": "IMDEA Networks Institute" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "health informatics" }, @@ -972350,35 +971240,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.29.21250653", - "rel_title": "Robust spike antibody responses and increased reactogenicity in seropositive individuals after a single dose of SARS-CoV-2 mRNA vaccine", - "rel_date": "2021-02-01", + "rel_doi": "10.1101/2021.01.28.21250666", + "rel_title": "Structural basis of fitness of emerging SARS-COV-2 variants and considerations for screening, testing and surveillance strategy to contain their threat.", + "rel_date": "2021-01-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.29.21250653", - "rel_abs": "An important question is arising as COVID-19 vaccines are getting rolled out: Should individuals who already had a SARS-CoV-2 infection receive one or two shots of the currently authorized mRNA vaccines. In this short report, we show that the antibody response to the first vaccine dose in individuals with pre-existing immunity is equal to or even exceeds the titers found in naive individuals after the second dose. We also show that the reactogenicity is significantly higher in individuals who have been infected with SARS-CoV-2 in the past. Changing the policy to give these individuals only one dose of vaccine would not negatively impact on their antibody titers, spare them from unnecessary pain and free up many urgently needed vaccine doses.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.28.21250666", + "rel_abs": "While emergence of new SAS-COV-2 variants is posing grave challenge to efforts to deal with the COVID-19 pandemic, the structural and molecular basis of their fitness remain poorly understood. We performed in silico analysis of structures of two most frequent SARS-COV-2 mutations, namely, N501Y and E484K, to identify plausible basis of their fitness over the original strain. The analysis suggested that the N501Y mutation is associated with strengthening of intra- as well as intermolecular H-bond in the hACE2 receptor-spike protein complex, which could result in increased affinity and, therefore, higher infectivity. While E484K mutation did not seem to directly affect the binding with hACE2 receptor, it disrupted H-bonding and salt-bridge interaction associated with binding with neutralizing antibody, which could affect chance of re-infection, disease outcome. Survey of several other mutations showing reduction in antibody-mediated neutralization also revealed that similar disruption of H-bonding or salt-bridge or Van der Waals interaction might explain their phenotype. Analysis of GESS database indicated that N501Y, EK484 as well as these other mutations existed since March-April, 2020, might have evolved independently across the world and may keep accumulating, which could affect efficacy of vaccination and antibody-based therapies. Our analysis also indicated that these may spread in spite of current travel restrictions focused on few countries and evolve indigenously warranting intensification of surveillance for emerging mutations among all travellers as well as people in their dwelling zones. Meta-analysis of existing literature showed that repeat testing of travellers, contacts and others under scrutiny 7-11 days after the initial RT-PCR test may significantly help to contain the spread of emerging variants by catching false negative results. In addition, existing evidence calls for development of strain-specific tests, escalated sequencing and broadening the scope of surveillance including in hospitals and animal farms to contain the threat of emerging variants.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Florian Krammer", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Komal Srivastava", - "author_inst": "Icahn School of Medicine at Mount Sinai" + "author_name": "Sk Ramiz Islam", + "author_inst": "Saha Institute of Nuclear Physics (HBNI)" }, { - "author_name": "- PARIS team", - "author_inst": "" + "author_name": "Debasish Prusty", + "author_inst": "Saha Institute of Nuclear Physics (HBNI)" }, { - "author_name": "Viviana Simon", - "author_inst": "Icahn School of Medicine" + "author_name": "Soumen Kanti Manna", + "author_inst": "Saha Institute of Nuclear Physics (HBNI)" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.01.27.21250645", @@ -974548,65 +973434,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.26.21250533", - "rel_title": "Lumipulse G SARS-CoV-2 Ag Assay Evaluation for SARS-CoV-2 Antigen Detection Using 594 Nasopharyngeal Swab Samples from Different Testing Groups", + "rel_doi": "10.1101/2021.01.26.21250580", + "rel_title": "THE AIRBORNE CONTAGIOUSNESS OF RESPIRATORY VIRUSES: A COMPARATIVE ANALYSIS AND IMPLICATIONS FOR MITIGATION", "rel_date": "2021-01-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.26.21250533", - "rel_abs": "Compared to RT-PCR, lower performance of antigen detection assays, including the Lumipulse G SARS-CoV-2 Ag assay, may depend on specific testing scenarios. We tested 594 nasopharyngeal swab samples from individuals with COVID-19 (RT-PCR cycle threshold [Ct] values [≤]40) or non-COVID-19 (Ct values [≤]40) diagnoses. RT-PCR positive samples were assigned to diagnostic, screening, or monitoring groups of testing. With a limit of detection of 1.2 x 104 SARS-CoV-2 RNA copies/ml, Lumipulse showed positive percent agreement (PPA) of 79.9% (155/194) and negative percent agreement of 99.3% (397/400), whereas PPAs were 100% for samples with Ct values of <18 or 18-<25 and 92.5% for samples with Ct values of 25-<30. By three groups, Lumipulse showed PPA of 87.0% (60/69), 81.1% (43/53), or 72.2% (52/72), respectively, whereas PPA was 100% for samples with Ct values of <18 or 18-<25, and was 94.4%, 80.0%, or 100% for samples with Ct values of 25-<30, respectively. RT-PCR positive samples were also tested for SARS-CoV-2 subgenomic RNA and, by three groups, testing showed that PPA was 63.8% (44/69), 62.3% (33/53), or 33.3% (24/72), respectively. PPAs dropped to 55.6%, 20.0%, or 41.7% for samples with Ct values of 25-<30, respectively. All 101 samples with a subgenomic RNA positive result had a Lumipulse assays antigen positive result, whereas only 54 (58.1%) of remaining 93 samples had a Lumipulse assays antigen positive result. In conclusion, Lumipulse assay was highly sensitive in samples with low RT-PCR Ct values, implying repeated testing to reduce consequences of false-negative results.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.26.21250580", + "rel_abs": "BackgroundThe infectious emission rate is a critical input parameter for airborne contagion models, but data are limited due to reliance on estimates from chance superspreading events. A predictive estimation approach for the quanta emission rate (ERq) was recently proposed for SARS-CoV-2 using the droplet volume concentration of various expiratory activities. This study assesses the strength of the approach and uses novel predictive estimates of ERq to compare the contagiousness of respiratory pathogens.\n\nMethodsWe applied the predictive approach to SARS-CoV-1, SARS-CoV-2, MERS, measles virus, adenovirus, rhinovirus, coxsackievirus, seasonal influenza virus and Mycobacterium tuberculosis (TB) and compared ERq estimates to values reported in literature. We calculated infection risk in a prototypical classroom and barracks to assess the relative ability of ventilation to mitigate airborne transmission.\n\nResultsOur median standing and speaking ERq estimate for SARS-CoV-2 (2.6 quanta hour (h)-1) is similar to active, untreated TB (3.1 h-1), higher than seasonal influenza (0.17 quanta h-1), and lower than measles virus (15 quanta h-1). We calculated event reproduction numbers above 1 for SARS-CoV-2, measles virus, and untreated TB in both the classroom and barracks for an activity level of standing and speaking at low, medium and high ventilation rates of 2.3, 6.6 and 14 liters per second per person, respectively.\n\nConclusionsOur predictive ERq estimates are consistent with the range of values reported over decades of research. In congregate settings, current ventilation standards are unlikely to control the spread of viruses with upper quartile ERq values above 10 quanta h-1, such as SARS-CoV-2, indicating the need for additional control measures.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Giulia Menchinelli", - "author_inst": "Universit\u00e0 Cattolica del S. Cuore" - }, - { - "author_name": "Licia Bordi", - "author_inst": "National Institute for Infectious Diseases" - }, - { - "author_name": "Flora Marzialiotti", - "author_inst": "Fondazione Policlinico Universitario A. Gemelli, IRCCS" - }, - { - "author_name": "Ivana Palucci", - "author_inst": "Catholic University of the Sacred Hearth" - }, - { - "author_name": "Maria R. Capobianchi", - "author_inst": "National Institute for Infectious Diseases" - }, - { - "author_name": "Giuseppe Sberna", - "author_inst": "National Institute for Infectious Diseases L. Spallanzani-IRCCS" - }, - { - "author_name": "Eleonora Lalle", - "author_inst": "National Institute for Infectious Diseases" - }, - { - "author_name": "Lucio Romano", - "author_inst": "Fondazione Policlinico Universitario A. Gemelli, IRCCS" - }, - { - "author_name": "Giulia De Angelis", - "author_inst": "Catholic University" - }, - { - "author_name": "Simona Marchetti", - "author_inst": "Fondazione Policlinico Universitario A. Gemelli, IRCCS" + "author_name": "Alex Mikszewski", + "author_inst": "Queensland University of Technology, Brisbane, Queensland, Australia; The City University of New York, New York, NY, USA" }, { - "author_name": "Maurizio Sanguinetti", - "author_inst": "Fondazione Policlinico Universitario" + "author_name": "Luca Stabile", + "author_inst": "University of Cassino and Southern Lazio, Cassino, FR, Italy" }, { - "author_name": "Paola Cattani", - "author_inst": "Fondazione Policlinico Universitario A. Gemelli, IRCCS" + "author_name": "Giorgio Buonanno", + "author_inst": "University of Cassino and Southern Lazio, Cassino, FR, Italy" }, { - "author_name": "Brunella Posteraro", - "author_inst": "Universit\u00e0 Cattolica del S. Cuore" + "author_name": "Lidia Morawska", + "author_inst": "Queensland University of Technology" } ], "version": "1", @@ -976050,35 +974900,43 @@ "category": "obstetrics and gynecology" }, { - "rel_doi": "10.1101/2021.01.27.21250153", - "rel_title": "The prevalence of olfactory dysfunction and its associated factors in patients with COVID-19 infection", + "rel_doi": "10.1101/2021.01.27.21250487", + "rel_title": "Self-Reported Mask Wearing Greatly Exceeds Directly Observed Use: Urgent Need for Policy Intervention in Kenya", "rel_date": "2021-01-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.27.21250153", - "rel_abs": "ObjectiveTo determine the prevalence of olfactory dysfunctions, mainly, anosmia and to identify its associated factors in patients with COVID-19 infection.\n\nStudy designA hospital-based prospective observational cohort study\n\nSettingA COVID dedicated hospital, Square Hospitals Ltd., Dhaka, Bangladesh.\n\nMethodsWe collected patients information including laboratory-confirmed COVID-19 test results. We used Pearson Chi-square test and logistic regression model to assess the associations between demographic and clinical characteristics and olfactory outcomes.\n\nResultsOut of 600 COVID-19 positive patients, 38.7% were diagnosed with olfactory dysfunction. Our analyses showed that patients age, smoking status, cough, dyspnea, sore throat, asthenia, and nausea or vomiting were significantly associated with the anosmia. We observed the risk of developing anosmia was greater in younger patients than in older patients, and this risk decreased as age increased [odds ratio (OR) range for different age groups: 1.26 to 1.08]. Smoking patients were 1.73 times more likely to experience anosmia than non-smoking patients [OR=1.73, 95% confidence interval (CI) = 1.01-2.98]. In addition, patients complained asthenia had a significantly double risk of developing the anosmia [OR = 1.96, CI = 1.23-3.06].\n\nConclusionsOur study shows that about 39% of patients diagnosed with olfactory dysfunction. Patients age, smoking status, and asthenia are significantly positively associated with the anosmia. Since anosmia can be a significant marker for the diagnosis of COVID-19, we suggest regular screening of olfactory dysfunction in patients with early symptoms of COVID-19, particularly younger patients, smoker, and complained asthenia.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.27.21250487", + "rel_abs": "BackgroundMany countries in sub-Saharan Africa have so far avoided large outbreaks of COVID-19, perhaps due to the strict lockdown measures that were imposed early in the pandemic. Yet the harsh socio-economic consequences of the lockdowns have led many governments to ease the restrictions in favor of less stringent mitigation strategies. In the absence of concrete plans for widespread vaccination, masks remain one of the few tools available to low-income populations to avoid the spread of SARS-CoV-2 for the foreseeable future.\n\nMethodsWe compare mask use data collected through self-reports from phone surveys and direct observations in public spaces from population-representative samples in Ugunja subcounty, a rural setting in Western Kenya. We examine mask use in different situations and compare mask use by gender, age, location, and the riskiness of the activity\n\nFindingsWe assess mask use data from 1,960 phone survey respondents and 9,549 direct observations. While only 12% of people admitted in phone interviews to not wearing a mask in public, 90% of people we observed did not have a mask visible (77.7% difference, 95% CI 0.742, 0.802). Self-reported mask use was significantly higher than observed mask use in all scenarios (i.e. in the village, in the market, on public transportation).\n\nInterpretationWe find limited compliance with the national government mask mandate in Kenya using directly observed data, but high rates of self-reported mask use. This vast gap suggests that people are aware that mask use is socially desirable, but in practice they do not adopt this behavior.\n\nFocusing public policy efforts on improving adoption of mask use via education and behavioral interventions may be needed to improve compliance.\n\nFundingWeiss Family Foundation, International Growth Centre", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Md. Mehedi Hasan", - "author_inst": "Square Hospitals Ltd." + "author_name": "Aleksandra Jakubowski", + "author_inst": "University of California Berkeley" }, { - "author_name": "Naima Ahmed Tamanna", - "author_inst": "Jagannath University" + "author_name": "Dennis Egger", + "author_inst": "University of California Berkeley" }, { - "author_name": "Mohammad Nasimul Jamal", - "author_inst": "Square Hospitals Ltd." + "author_name": "Carolyne Nekesa", + "author_inst": "Vyxer Remit Kenya" }, { - "author_name": "Md. Jamal Uddin", - "author_inst": "Shahjalal University of Science and Technology, Sylhet 3114, Bangladesh" + "author_name": "Layna Lowe", + "author_inst": "University of California Berkeley" + }, + { + "author_name": "Michael Walker", + "author_inst": "University of California Berkeley" + }, + { + "author_name": "Edward Miguel", + "author_inst": "University of California Berkeley" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "otolaryngology" + "category": "health policy" }, { "rel_doi": "10.1101/2021.01.27.21250388", @@ -978000,63 +976858,83 @@ "category": "endocrinology" }, { - "rel_doi": "10.1101/2021.01.25.21250040", - "rel_title": "COVID-19-related disruptions to routine vaccination services in India: perspectives from pediatricians", + "rel_doi": "10.1101/2021.01.26.21250518", + "rel_title": "Impact of COVID-19 on education, health and lifestyle behaviour of Brazilian urology residents", "rel_date": "2021-01-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.25.21250040", - "rel_abs": "Background and ObjectiveThe COVID-19 pandemic has led to disruptions to routine immunization programs in India and around the world, setting the stage for potentially serious outbreaks of vaccine-preventable diseases.\n\nMethodsWe surveyed pediatric healthcare providers in India in 2 rounds in April-June and September 2020 to understand how COVID-19 control measures may have impacted routine vaccination.\n\nResultsRespondents were predominantly pediatricians working in primary, secondary or tertiary healthcare centers, across 21 Indian states and two union territories. Among the 424 (survey 1) and 141 (survey 2) respondents, 33.4% and 7.8%, respectively, reported near complete suspension of vaccination services due to COVID-19. A 50% or greater drop in vaccination services was reported by 83.1% of respondents in June, followed by 32.6% four months later, indicating slow recovery of services. By September 2020, 83.6% were aware of updated guidelines on safe provision of immunization services, although awareness of specific catch-up vaccination plans was low, and 76.6% expressed concern about a vaccine coverage gap that could potentially lead to increased non-COVID-19 illnesses and deaths.\n\nConclusionsPandemic-related disruptions to vaccination services were reported by pediatricians across India. Concerted efforts are needed from governing and academic groups to ensure that routine immunization and catch-up programs are implemented during this pandemic, which can sustain gains in vaccination coverage and provide a robust blueprint for the national roll-out of the COVID-19 vaccine.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.26.21250518", + "rel_abs": "ObjectivesTo evaluate the impact of COVID-19 on clinical and surgical practice, educational activities, health and lifestyle behavior of Brazilian urology residents.\n\nMaterials and MethodsA web-based survey was sent to 468 Brazilian urology residents from postgraduate years (PGY) 3 to 5 to collect data on clinical practice and training after 4 months of COVID-19. We also assessed health-related and behavior changes, rate of infection by SARS-CoV-2, deployment to the front line of COVID-19, residents concerns, and access to personal protective equipment (PPE).\n\nResultsMassive reductions in elective and emergency patient consultations, diagnostic procedures and surgeries were reported across the country, affecting PGY 3 to 5 alike. Most in-person educational activities were abolished. The median damage to the urological training expected for 2020 was 6.0 [3.4 -7.7], on a scale from 0 to 10, with senior residents estimating a greater damage (P< 0.001). Educational interventions developed included online case-based discussions, subspeciality conferences and lectures, and grand rounds. Most senior residents favored extending residency to compensate for training loss and most younger residents favored no additional training (p< 0.001). Modifications in health and lifestyle included weight gain (43.8%), reduced physical activity (68.6%), increased alcoholic intake (44.9%) and cigarette consumption (53.6%), worsening of sexual life (25.2%) and feelings of sadness or depression (48,2%). Almost half were summoned to work on the COVID-19 front-line and 24.4% had COVID-19. Most residents had inadequate training to deal with COVID-19 patients and most reported a shortage of PPE. Residents concerns included the risk of contaminating family members, being away from residency program, developing severe COVID-19 and overloading colleagues.\n\nConclusionsCOVID-19 had a massive impact in Brazilian urology residents training, health and lifestyle behavior, which may reflect what happened in other medical specialties. Studies should confirm these findings to help developing strategies to mitigate residents losses.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Anita Shet", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Jose A Prezotti Sr.", + "author_inst": "1.\tDivision of Urology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil" }, { - "author_name": "Baldeep Dhaliwal", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Joao Victor T Henriques Sr.", + "author_inst": "1.\tDivision of Urology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil" }, { - "author_name": "Preetika Banerjee", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Luciano Favorito", + "author_inst": "2.\tDivision of Urology, Rio de Janeiro State University, Rio de Janeiro, Brazil" }, { - "author_name": "Kelly Carr", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Alfredo F Canalini Sr.", + "author_inst": "2.\tDivision of Urology, Rio de Janeiro State University, Rio de Janeiro, Brazil" + }, + { + "author_name": "Marcos G Machado Sr.", + "author_inst": "1.\tDivision of Urology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil" }, { - "author_name": "Andrea DeLuca", - "author_inst": "Amputee Coalition, Washington DC, USA" + "author_name": "Thulio Bosi Sr.", + "author_inst": "1.\tDivision of Urology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil" }, { - "author_name": "Carl Britto", - "author_inst": "St Johns Research Institute, Bangalore, India" + "author_name": "Akemi M Barbosa", + "author_inst": "1.\tDivision of Urology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil" }, { - "author_name": "Rajeev Seth", - "author_inst": "Bal Umang Drishya Sanstha, New Delhi, India" + "author_name": "Julyana Moromizato", + "author_inst": "1.\tDivision of Urology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil" + }, + { + "author_name": "Karin Anzolch", + "author_inst": "3.\tDivision of Urology, Hospital Moinhos de Vento, Porto Alegre, Brazil" + }, + { + "author_name": "Roni Fernandes", + "author_inst": "4. School of Medical Sciences, Santa Casa de Sao Paulo, Sao Paulo, Brazil" + }, + { + "author_name": "Fransber Rodrigues", + "author_inst": "5.\tDivision of Urology, University of Brasilia, Brasilia, Brazil" + }, + { + "author_name": "Carlos Henrique Bellucci", + "author_inst": "1.\tDivision of Urology, University of Sao Paulo School of Medicine, Sao Paulo, Brazil" }, { - "author_name": "Bakul Parekh", - "author_inst": "Indian Academy of Pediatrics" + "author_name": "Caroline Santos Silva", + "author_inst": "6.\tDepartment of Surgery, State University of Feira de Santana, Feira de Santana, Brazil" }, { - "author_name": "GV Basavaraj", - "author_inst": "Indian Academy of Pediatrics" + "author_name": "Antonio Carlos Lima Pompeo", + "author_inst": "7.\tDivision of Urology, Federal University of ABC, Santo Andre, Brazil" }, { - "author_name": "Digant Shastri", - "author_inst": "Indian Academy of Pediatrics" + "author_name": "Jose de Bessa Jr.", + "author_inst": "6.\tDepartment of Surgery, State University of Feira de Santana, Feira de Santana, Brazil" }, { - "author_name": "Piyush Gupta", - "author_inst": "Indian Academy of Pediatrics" + "author_name": "Cristiano M Gomes", + "author_inst": "University of Sao Paulo School of Medicine" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "urology" }, { "rel_doi": "10.1101/2021.01.26.21250184", @@ -979650,31 +978528,43 @@ "category": "pediatrics" }, { - "rel_doi": "10.1101/2021.01.20.21250204", - "rel_title": "Rule of thumb in human intelligence for assessing the COVID-19 outbreak in Japan", + "rel_doi": "10.1101/2021.01.22.21250302", + "rel_title": "Willingness to volunteer of medical students during the COVID-19 pandemic: Assessment at a tertiary care hospital in India", "rel_date": "2021-01-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.20.21250204", - "rel_abs": "BackgroundThe COVID-19 outbreak in Japan exhibited its third peak at the end of 2020. Mathematical modelling and developed AI cannot explain several peaks in a single year.\n\nObjectThis study was conducted to evaluate a rule of thumb for prediction from past wave experiences.\n\nMethodWe rescaled the number of newly infected patients as 100% at the peak and checked similarities among waves. Then we extrapolated the courses of the third and later waves.\n\nResultsResults show some similarity around the second and the third waves. Based on this similarity, we expected the bottom of the third wave will show 2131 newly positive patients including asymptomatic patients at around the end of February, 2021.\n\nDiscussion and ConclusionWe can infer the course of the third wave from similarity with the second wave. Mathematical modelling has been unable to do it, even when AI was used for prediction. Performance of the rule of thumb used with human intelligence might be superior to that of AI under these circumstances.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.22.21250302", + "rel_abs": "Background and ObjectivesThe involvement of medical students in strategies to control COVID-19 might be considered to cope with the shortage of healthcare workers. This study aims at assessing the level of knowledge about COVID-19, willingness to volunteer, potential areas of involvement and reasons for deterrence towards volunteering among medical students.\n\nMethodsA cross-sectional study was conducted among undergraduate medical students of a tertiary care teaching hospital in New Delhi. A web-based questionnaire was used to elicit demographic information, knowledge of COVID-19, willingness to volunteer and reasons for deterrence for working during COVID-19 pandemic and self-declared knowledge in six domains.\n\nResultsA total of 292 students participated in the study with a mean age of 19.9{+/-}3.1 years. The mean (S.D.) knowledge score of COVID-19 was 6.9 (1.1) (maximum score 10). Knowledge score was significantly different among preclinical (6.5), paraclinical (7.18), and clinical groups (7.03). Almost three fourth (75.3%) participants were willing to volunteer in COVID-19 pandemic, though 67.8% had not received any training in emergency medicine or public health crisis management. Willingness to work was maximum in areas of social work and indirect patient care (62.3% each). Lack of personal protective equipment was cited as a highly deterrent factor for volunteering (62.7%) followed by fear of transmitting the infection to family (45.9%), fear of causing harm to the patient (34.2%), and absence of treatment (22.2%).\n\nInterpretation & conclusionsMajority of the students were willing to volunteer even though they had not received adequate training. Students may serve as an auxiliary force during the pandemic, especially in the non-clinical setting.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Junko Kurita", - "author_inst": "Tokiwa University, Ibaraki, Japan" + "author_name": "Manraj Singh Sra", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Tamie Sugawara", - "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan" + "author_name": "Amulya Gupta", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Yasushi Ohkusa", - "author_inst": "National Institute of Infectious Diseases, Tokyo, Japan" + "author_name": "Abhishek Jaiswal", + "author_inst": "Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Kapil Yadav", + "author_inst": "Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Anil Goswami", + "author_inst": "Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Kiran Goswami", + "author_inst": "Centre for Community Medicine, All India Institute of Medical Sciences, New Delhi" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "medical education" }, { "rel_doi": "10.1101/2021.01.22.21250070", @@ -981560,55 +980450,63 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2021.01.25.21250233", - "rel_title": "Contamination of air and surfaces in workplaces with SARS-CoV-2 virus: a systematic review", + "rel_doi": "10.1101/2021.01.25.20248984", + "rel_title": "Impulse dispersion of aerosols during playing wind instruments", "rel_date": "2021-01-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.25.21250233", - "rel_abs": "ObjectivesThis systematic review aimed to evaluate the evidence for air and surface contamination of workplace environments with SARS-CoV-2 RNA and the quality of the methods used to identify actions necessary to improve the quality of the data.\n\nMethodsWe searched Web of Science and Google Scholar until 24th December 2020 for relevant articles and extracted data on methodology and results.\n\nResultsThe vast majority of data come from healthcare settings, with typically around 6 % of samples having detectable concentrations of SARS-CoV-2 RNA and almost none of the samples collected had viable virus. There were a wide variety of methods used to measure airborne virus, although surface sampling was generally undertaken using nylon flocked swabs. Overall, the quality of the measurements was poor. Only a small number of studies reported the airborne concentration of SARS-CoV-2 virus RNA, mostly just reporting the detectable concentration values without reference to the detection limit. Imputing the geometric mean air concentration assuming the limit of detection was the lowest reported value, suggests typical concentrations in health care settings may be around 0.01 SARS-CoV-2 virus RNA copies/m3. Data on surface virus loading per unit area were mostly unavailable.\n\nConclusionThe reliability of the reported data is uncertain. The methods used for measuring SARS-CoV-2 and other respiratory viruses in work environments should be standardised to facilitate more consistent interpretation of contamination and to help reliably estimate worker exposure.\n\nKey messagesO_LIWhat is already known about this subject?\nO_LILow level contamination of air and surfaces in hospitals with SARS-CoV-2 RNA have been reported during the Covid-19 pandemic.\nC_LIO_LILimited data have published from non-healthcare settings.\nC_LI\nC_LIO_LIWhat are the new findings?\nO_LITypically, around 6% of air and surface samples in hospitals were positive for SARS-COV-2 RNA, although there is very limited data for non-healthcare settings.\nC_LIO_LIThe quality of the available measurement studies is generally poor, with little consistency in the sampling and analytical methods used.\nC_LIO_LIFew studies report the concentration of SARS-CoV-2 in air or as surface loading of virus RNA, and very few studies have reported culture of the virus.\nC_LIO_LIThe best estimate of typical air concentrations in health care settings is around 0.01 SARS-CoV-2 virus RNA copies/m3\nC_LI\nC_LIO_LIHow might this impact on policy or clinical practice in the foreseeable future?\nO_LIThere should be concerted efforts to standardise the methods used for measuring SARS-CoV-2 and other respiratory viruses in work environments.\nC_LI\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.25.20248984", + "rel_abs": "Musical activities especially singing and playing wind instruments have been singled out as potentially high-risk activities for transmission of SARS CoV-2, because of a higher rate of aerosol production and emission. Playing wind instruments can produce condensation water, droplets of saliva, and aerosol particles, which hover and convectional spread in the environmental air and can be potentially infectious.\n\nThe aim of this study is to investigate the primary impulse dispersion of aerosols during playing different wind instruments in comparison to breathing and speaking. Nine professional musicians (3 trumpeters, 3 cross flutists and 3 clarinetists) of the Bavarian Symphony Orchestra performed the main theme of Ludwig van Beethoven s 9th symphony, 4th movement in different pitches and loudness. Thereby, the inhaled air volume was marked with small aerosol particles produced with a commercial e-cigarette. The expelled aerosol cloud was recorded by cameras from different perspectives. Afterwards, the dimensions and dynamics of the aerosol cloud was measured by segmenting the video footage at every time point.\n\nOverall, the cross flutes produced the largest dispersion at the end of task of up to maximum distances of 1.88 m in front direction. Thereby it was observed an expulsion of aerosol in different directions: upwards and downwards at the mouthpiece, at the end of the instrument and along the cross flute at the key plane. In comparison, the maximum impulse dispersion generated by the trumpets and clarinets were lower in frontal and lateral direction (1.2 m and 1.0 m in front-direction). The expulsion to the sides was also lower. Consequently, a distance of 3 m to the front and to the sides of 2 m for the cross flutes in an orchestral formation is proposed, for trumpets and clarinets a safety distance of 2 m to the front and 1.5 m between instrumentalists are recommendable.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "John Cherrie", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Sophia Gantner", + "author_inst": "LMU Munich" }, { - "author_name": "Mark Cherrie", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Matthias Echternach", + "author_inst": "LMU Munich" }, { - "author_name": "Alice Davis", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Reinhard Veltrup", + "author_inst": "University Erlangen" }, { - "author_name": "David Holmes", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Caroline Westphalen", + "author_inst": "LMU Munich" }, { - "author_name": "Sean Semple", - "author_inst": "University of Stirling" + "author_name": "Marie Christine Koeberlein", + "author_inst": "LMU Munich" }, { - "author_name": "Susanne Steinle", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Liudmila Kuranova", + "author_inst": "LMU Munich" }, { - "author_name": "Ewan MacDonald", - "author_inst": "University of Glasgow" + "author_name": "Gregor Peters", + "author_inst": "University Erlangen" }, { - "author_name": "Ginny Moore", - "author_inst": "Public Health England" + "author_name": "Bernhard Jakubass", + "author_inst": "University Erlangen" }, { - "author_name": "Miranda Loh", - "author_inst": "Institute of Occupational Medicine" + "author_name": "Tobias Benthaus", + "author_inst": "LMU Munich" + }, + { + "author_name": "Michael Doellinger", + "author_inst": "University Erlangen" + }, + { + "author_name": "Stefan Kniesburges", + "author_inst": "Erlangen University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "otolaryngology" }, { "rel_doi": "10.1101/2021.01.24.21250324", @@ -983338,99 +982236,79 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.01.25.428137", - "rel_title": "Increased Resistance of SARS-CoV-2 Variants B.1.351 and B.1.1.7 to Antibody Neutralization", + "rel_doi": "10.1101/2021.01.26.428251", + "rel_title": "A single intranasal dose of chimpanzee adenovirus-vectored vaccine protects against SARS-CoV-2 infection in rhesus macaques", "rel_date": "2021-01-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.25.428137", - "rel_abs": "The COVID-19 pandemic has ravaged the globe, and its causative agent, SARS-CoV-2, continues to rage. Prospects of ending this pandemic rest on the development of effective interventions. Single and combination monoclonal antibody (mAb) therapeutics have received emergency use authorization1-3, with more in the pipeline4-7. Furthermore, multiple vaccine constructs have shown promise8, including two with ~95% protective efficacy against COVID-199,10. However, these interventions were directed toward the initial SARS-CoV-2 that emerged in 2019. The recent emergence of new SARS-CoV-2 variants B.1.1.7 in the UK11 and B.1.351 in South Africa12 is of concern because of their purported ease of transmission and extensive mutations in the spike protein. We now report that B.1.1.7 is refractory to neutralization by most mAbs to the N-terminal domain (NTD) of spike and relatively resistant to a few mAbs to the receptor-binding domain (RBD). It is not more resistant to convalescent plasma or vaccinee sera. Findings on B.1.351 are more worrisome in that this variant is not only refractory to neutralization by most NTD mAbs but also by multiple individual mAbs to the receptor-binding motif on RBD, largely due to an E484K mutation. Moreover, B.1.351 is markedly more resistant to neutralization by convalescent plasma (9.4 fold) and vaccinee sera (10.3-12.4 fold). B.1.351 and emergent variants13,14 with similar spike mutations present new challenges for mAb therapy and threaten the protective efficacy of current vaccines.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.26.428251", + "rel_abs": "The deployment of a vaccine that limits transmission and disease likely will be required to end the Coronavirus Disease 2019 (COVID-19) pandemic. We recently described the protective activity of an intranasally-administered chimpanzee adenovirus-vectored vaccine encoding a pre-fusion stabilized spike (S) protein (ChAd-SARS-CoV-2-S) in the upper and lower respiratory tract of mice expressing the human angiotensin-converting enzyme 2 (ACE2) receptor. Here, we show the immunogenicity and protective efficacy of this vaccine in non-human primates. Rhesus macaques were immunized with ChAd-Control or ChAd-SARS-CoV-2-S and challenged one month later by combined intranasal and intrabronchial routes with SARS-CoV-2. A single intranasal dose of ChAd-SARS-CoV-2-S induced neutralizing antibodies and T cell responses and limited or prevented infection in the upper and lower respiratory tract after SARS-CoV-2 challenge. As this single intranasal dose vaccine confers protection against SARS-CoV-2 in non-human primates, it is a promising candidate for limiting SARS-CoV-2 infection and transmission in humans.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Pengfei Wang", - "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" - }, - { - "author_name": "Manoj S Nair", - "author_inst": "Columbia University" - }, - { - "author_name": "Lihong Liu", - "author_inst": "Columbia University Irving Medical Center" - }, - { - "author_name": "Sho Iketani", - "author_inst": "Columbia University Irving Medical Center" - }, - { - "author_name": "Yang Luo", - "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA" - }, - { - "author_name": "Yicheng Guo", - "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" + "author_name": "Ahmed O Hassan", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Maple Wang", - "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" + "author_name": "Friederike Feldmann", + "author_inst": "Rocky Mountain Veterinary Branch Division of Intramural Research, NIAID, NIH, Rocky Mountain Laboratories" }, { - "author_name": "Jian Yu", - "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" + "author_name": "Haiyan Zhao", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Baoshan Zhang", - "author_inst": "Vaccine Research Center, National Institutes of Health, Bethesda, MD, USA." + "author_name": "David T Curiel", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Peter D Kwong", - "author_inst": "Vaccine Research Center, National Institutes of Health, Bethesda, MD, USA; Department of Biochemistry, Columbia University, New York, NY, USA." + "author_name": "Atsushi Okumura", + "author_inst": "Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Rocky Mountain Laboratories" }, { - "author_name": "Barney S Graham", - "author_inst": "Vaccine Research Center, National Institutes of Health, Bethesda, MD, USA" + "author_name": "Tsing-Lee Tang-Huau", + "author_inst": "Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Rocky Mountain Laboratories, Hamilton" }, { - "author_name": "John R Mascola", - "author_inst": "Vaccine Research Center, NIAID, NIH" + "author_name": "James Brett Case", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Jennifer Y Chang", - "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" + "author_name": "Kimberly Meade-White", + "author_inst": "Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Rocky Mountain Laboratories" }, { - "author_name": "Michael T Yin", - "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" + "author_name": "Julie Callison", + "author_inst": "Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Rocky Mountain Laboratories" }, { - "author_name": "Magdalena E Sobieszczyk", - "author_inst": "Columbia University Medical Center" + "author_name": "Jamie Lovaglio", + "author_inst": "Rocky Mountain Veterinary Branch Division of Intramural Research, NIAID, NIH, Rocky Mountain Laboratories" }, { - "author_name": "Christos A Kyratsous", - "author_inst": "Regeneron Pharmaceuticals, Inc." + "author_name": "Patrick W Hanley", + "author_inst": "Rocky Mountain Veterinary Branch Division of Intramural Research, NIAID, NIH, Rocky Mountain Laboratories" }, { - "author_name": "Lawrence Shapiro", - "author_inst": "Columbia University Vagelos College of Physicians and Surgeons" + "author_name": "Dana P Scott", + "author_inst": "Rocky Mountain Veterinary Branch Division of Intramural Research, NIAID, NIH, Rocky Mountain Laboratories" }, { - "author_name": "Zizhang Sheng", - "author_inst": "Columbia University" + "author_name": "Daved H. Fremont", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Yaoxing Huang", - "author_inst": "Columbia University" + "author_name": "Heinz Feldmann", + "author_inst": "Laboratory of Virology, Division of Intramural Research, NIAID, NIH, Rocky Mountain Laboratories" }, { - "author_name": "David D Ho", - "author_inst": "Columbia University Irving Medical Center" + "author_name": "Michael S. Diamond", + "author_inst": "Washington University School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "microbiology" }, { "rel_doi": "10.1101/2021.01.26.426986", @@ -985128,29 +984006,173 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.24.21250416", - "rel_title": "Social, economic, and environmental factors influencing the basic reproduction number of COVID-19 across countries", + "rel_doi": "10.1101/2021.01.22.21250304", + "rel_title": "Rates of serious clinical outcomes in survivors of hospitalisation with COVID-19: a descriptive cohort study within the OpenSAFELY platform", "rel_date": "2021-01-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.24.21250416", - "rel_abs": "ObjectiveTo assess whether the basic reproduction number (R0) of COVID-19 is different across countries and what national-level demographic, social, and environmental factors characterize initial vulnerability to the virus.\n\nMethodsWe fit logistic growth curves to reported daily case numbers, up to the first epidemic peak. This fitting estimates R0. We then use a generalized additive model to discern the effects, and include 5 random effect covariates to account for potential differences in testing and reporting that can bias the estimated R0.\n\nFindingsWe found that the mean R0 is 1.70 (S.D. 0.57), with a range between 1.10 (Ghana) and 3.52 (South Korea). We identified four factors-population between 20-34 years old (youth), population residing in urban agglomerates over 1 million (city), social media use to organize offline action (social media), and GINI income inequality-as having strong relationships with R0. An intermediate level of youth and GINI inequality are associated with high R0, while high city population and high social media use are associated with high R0. Environmental and climate factors were not found to have strong relationships with R0.\n\nConclusionStudies that aim to measure the effectiveness of interventions should account for the intrinsic differences between populations.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.22.21250304", + "rel_abs": "BackgroundPatients with COVID-19 are thought to be at higher risk of cardiometabolic and pulmonary complications, but quantification of that risk is limited. We aimed to describe the overall burden of these complications in survivors of severe COVID-19.\n\nMethodsWorking on behalf of NHS England, we used linked primary care records, death certificate and hospital data from the OpenSAFELY platform. We constructed three cohorts: patients discharged following hospitalisation with COVID-19, patients discharged following hospitalisation with pneumonia in 2019, and a frequency-matched cohort from the general population in 2019. We studied eight cardiometabolic and pulmonary outcomes. Absolute rates were measured in each cohort and Cox regression models were fitted to estimate age/sex adjusted hazard ratios comparing outcome rates between discharged COVID-19 patients and the two comparator cohorts.\n\nResultsAmongst the population of 31,716 patients discharged following hospitalisation with COVID-19, rates for majority of outcomes peaked in the first month post-discharge, then declined over the following four months. Patients in the COVID-19 population had markedly increased risk of all outcomes compared to matched controls from the 2019 general population, especially for pulmonary embolism (HR 12.86; 95% CI: 11.23 - 14.74). Outcome rates were more similar when comparing patients discharged with COVID-19 to those discharged with pneumonia in 2019, although COVID-19 patients had increased risk of type 2 diabetes (HR 1.23; 95% CI: 1.05 - 1.44).\n\nInterpretationCardiometabolic and pulmonary adverse outcomes are markedly raised following hospitalisation for COVID-19 compared to the general population. However, the excess risks were more comparable to those seen following hospitalisation with pneumonia. Identifying patients at particularly high risk of outcomes would inform targeted preventive measures.\n\nFundingWellcome, Royal Society, National Institute for Health Research, National Institute for Health Research Oxford Biomedical Research Centre, UK Medical Research Council, UK Research and Innovation, Health and Safety Executive.", + "rel_num_authors": 39, "rel_authors": [ { - "author_name": "Jude Dzevela Kong", - "author_inst": "York University" + "author_name": "John Tazare", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Edward Tekwa", - "author_inst": "Rutgers University" + "author_name": "Alex J Walker", + "author_inst": "University of Oxford" + }, + { + "author_name": "Laurie Tomlinson", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "George Hickman", + "author_inst": "University of Oxford" + }, + { + "author_name": "Christopher T Rentsch", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Elizabeth J Williamson", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Krishnan Bhaskaran", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "David Evans", + "author_inst": "University of Oxford" + }, + { + "author_name": "Kevin Wing", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Rohini Mathur", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Angel YS Wong", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Anna Schultze", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Sebastian CJ Bacon", + "author_inst": "University of Oxford" + }, + { + "author_name": "Christopher Bates", + "author_inst": "TPP" + }, + { + "author_name": "Caroline E Morton", + "author_inst": "University of Oxford" + }, + { + "author_name": "Helen J Curtis", + "author_inst": "University of Oxford" + }, + { + "author_name": "Emily Nightingale", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Helen I McDonald", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Amir Mehrkar", + "author_inst": "University of Oxford" + }, + { + "author_name": "Peter Inglesby", + "author_inst": "University of Oxford" + }, + { + "author_name": "Simon Davy", + "author_inst": "University of Oxford" + }, + { + "author_name": "Brian MacKenna", + "author_inst": "University of Oxford" + }, + { + "author_name": "Jonathan Cockburn", + "author_inst": "TPP" + }, + { + "author_name": "William J Hulme", + "author_inst": "University of Oxford" + }, + { + "author_name": "Charlotte Warren-Gash", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Ketaki Bhate", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Emma Powell", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Any Mulick", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Harriet Forbes", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Caroline Minassian", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Richard Croker", + "author_inst": "University of Oxford" }, { - "author_name": "Sarah Gignoux-Wolfsohn", - "author_inst": "6Smithsonian Environmental Research Center, Edgewater" + "author_name": "John Parry", + "author_inst": "TPP" + }, + { + "author_name": "Frank Hester", + "author_inst": "TPP" + }, + { + "author_name": "Sam Harper", + "author_inst": "TPP" + }, + { + "author_name": "Rosalind M Eggo", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Stephen JW Evans", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Liam Smeeth", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Ian J Douglas", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Ben Goldacre", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -986882,47 +985904,39 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2021.01.24.427089", - "rel_title": "Meta-analysis reveals consistent immune response patterns in COVID-19 infected patients at single-cell resolution", + "rel_doi": "10.1101/2021.01.24.427965", + "rel_title": "An Autoantigen Atlas from Human Lung HFL1 Cells Offers Clues to Neurological and Diverse Autoimmune Manifestations of COVID-19", "rel_date": "2021-01-24", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.24.427089", - "rel_abs": "A number of single-cell RNA studies looking at the human immune response to the coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been recently published. However, the number of samples used in each individual study typically is small, moreover the technologies and protocols used in different studies vary, thus somewhat restricting the range of conclusions that can be made with high confidence. To better capture the cellular gene expression changes upon SARS-CoV-2 infection at different levels and stages of disease severity and to minimise the effect of technical artefacts, we performed meta-analysis of data from 9 previously published studies, together comprising 143 human samples, and a set of 16 healthy control samples (10X). In particular, we used generally accepted immune cell markers to discern specific cell subtypes and to look at the changes of the cell proportion over different disease stages and their consistency across the studies. While half of the observations reported in the individual studies can be confirmed across multiple studies, half of the results seem to be less conclusive. In particular, we show that the differentially expressed genes consistently point to upregulation of type I Interferon signal pathway and downregulation of the mitochondrial genes, alongside several other reproducibly consistent changes. We also confirm the presence of expanded B-cell clones in COVID-19 patients, however, no consistent trend in T-cell clonal expansion was observed.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.24.427965", + "rel_abs": "COVID-19 is accompanied by a myriad of both transient and long-lasting autoimmune responses. Dermatan sulfate (DS), a glycosaminoglycan crucial for wound healing, has unique affinity for autoantigens (autoAgs) from apoptotic cells. DS-autoAg complexes are capable of stimulating autoreactive B cells and autoantibody production. Using DS affinity, we identified an autoantigenome of 408 proteins from human fetal lung fibroblast HFL11 cells, at least 231 of which are known autoAgs. Comparing with available COVID data, 352 proteins of the autoantigenome have thus far been found to be altered at protein or RNA levels in SARS-Cov-2 infection, 210 of which are known autoAgs. The COVID-altered proteins are significantly associated with RNA metabolism, translation, vesicles and vesicle transport, cell death, supramolecular fibrils, cytoskeleton, extracellular matrix, and interleukin signaling. They offer clues to neurological problems, fibrosis, smooth muscle dysfunction, and thrombosis. In particular, 150 altered proteins are related to the nervous system, including axon, myelin sheath, neuron projection, neuronal cell body, and olfactory bulb. An association with the melanosome is also identified. The findings from our study illustrate a strong connection between viral infection and autoimmunity. The vast number of COVID-altered proteins with propensity to become autoAgs offers an explanation for the diverse autoimmune complications in COVID patients. The variety of autoAgs related to mRNA metabolism, translation, and vesicles raises concerns about potential adverse effects of mRNA vaccines. The COVID autoantigen atlas we are establishing provides a detailed molecular map for further investigation of autoimmune sequelae of the pandemic.\n\nSummary sentenceAn autoantigenome by dermatan sulfate affinity from human lung HFL1 cells may explain neurological and autoimmune manifestations of COVID-19", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Manik Garg", - "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" - }, - { - "author_name": "Xu Li", - "author_inst": "School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, P.R. China" - }, - { - "author_name": "Pablo Andres Moreno Cortez", - "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" + "author_name": "Julia Y. Wang", + "author_inst": "Curandis" }, { - "author_name": "Irene Papatheodorou", - "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" + "author_name": "Wei Zhang", + "author_inst": "Guizhou Medical University" }, { - "author_name": "Yuelong Shu", - "author_inst": "School of Public Health (Shenzhen), Sun Yat-sen University, Guangzhou, P.R. China" + "author_name": "Michael W. Roehrl", + "author_inst": "Curandis" }, { - "author_name": "Alvis Brazma", - "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" + "author_name": "Victor B. Roehrl", + "author_inst": "Curandis" }, { - "author_name": "Zhichao Miao", - "author_inst": "European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI)" + "author_name": "Michael H. Roehrl", + "author_inst": "Memorial Sloan Kettering Cancer Center" } ], "version": "1", - "license": "cc_by_nc", - "type": "confirmatory results", - "category": "bioinformatics" + "license": "cc_by", + "type": "new results", + "category": "immunology" }, { "rel_doi": "10.1101/2021.01.16.21249950", @@ -988372,75 +987386,207 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2021.01.22.427737", - "rel_title": "Human embryonic stem cell-derived cardiomyocytes express SARS-CoV-2 host entry proteins: screen to identify inhibitors of infection", + "rel_doi": "10.1101/2021.01.22.427567", + "rel_title": "Bispecific antibody prevents SARS-CoV-2 escape and protects mice from disease", "rel_date": "2021-01-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.22.427737", - "rel_abs": "Patients with cardiovascular comorbidities are more susceptible to severe infection with SARS-CoV-2, known to directly cause pathological damage to cardiovascular tissue. We outline a screening platform using human embryonic stem cell-derived cardiomyocytes, confirmed to express the protein machinery critical for SARS-CoV-2 infection, and a pseudotyped virus system. The method has allowed us to identify benztropine and DX600 as novel inhibitors of SARS-CoV-2 infection.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.22.427567", + "rel_abs": "Neutralizing antibodies targeting the receptor binding domain (RBD) of the SARS-CoV-2 Spike (S) are among the most promising approaches against coronavirus disease 2019 (COVID-19)1,2. We developed a bispecific, IgG1-like molecule (CoV-X2) based on two antibodies derived from COVID-19 convalescent donors, C121 and C1353. CoV-X2 simultaneously binds two independent sites on the RBD and, unlike its parental antibodies, prevents detectable S binding to Angiotensin-Converting Enzyme 2 (ACE2), the virus cellular receptor. Furthermore, CoV-X2 neutralizes SARS-CoV-2 and its variants of concern, as well as the escape mutants generated by the parental monoclonals. In a novel animal model of SARS-CoV-2 infection with lung inflammation, CoV-X2 protects mice from disease and suppresses viral escape. Thus, simultaneous targeting of non-overlapping RBD epitopes by IgG-like bispecific antibodies is feasible and effective, combining into a single molecule the advantages of antibody cocktails.", + "rel_num_authors": 47, "rel_authors": [ { - "author_name": "Thomas L Williams", - "author_inst": "University of Cambridge" + "author_name": "Raoul De Gasparo", + "author_inst": "Institute for Research in Biomedicine, Universit\u00e0 della Svizzera italiana (USI), Bellinzona, Switzerland" }, { - "author_name": "Maria T Colzani", - "author_inst": "University of Cambridge" + "author_name": "Mattia Pedotti", + "author_inst": "Institute for Research in Biomedicine, Universit\u00e0 della Svizzera italiana (USI), Bellinzona, Switzerland" }, { - "author_name": "Robyn GC Macrae", - "author_inst": "University of Cambridge" + "author_name": "Luca Simonelli", + "author_inst": "Institute for Research in Biomedicine, Universit\u00e0 della Svizzera italiana (USI), Bellinzona, Switzerland" }, { - "author_name": "Emma L Robinson", - "author_inst": "University of Colorado Denver" + "author_name": "Petr Nickl", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" }, { - "author_name": "Stuart Bloor", - "author_inst": "University of Cambridge" + "author_name": "Frauke Muecksch", + "author_inst": "Laboratory of Retrovirology, The Rockefeller University, New York, NY, USA" }, { - "author_name": "Edward JD Greenwood", - "author_inst": "University of Cambridge" + "author_name": "Irene Cassaniti", + "author_inst": "Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy" }, { - "author_name": "Jun Ru Zhan", - "author_inst": "University of Cambridge" + "author_name": "Elena Percivalle", + "author_inst": "Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy" }, { - "author_name": "Gregory Strachan", - "author_inst": "University of Cambridge" + "author_name": "Julio C. C. Lorenzi", + "author_inst": "Laboratory of Molecular Immunology, The Rockefeller University, New York, NY, USA" }, { - "author_name": "Rhoda E Kuc", - "author_inst": "University of Cambridge" + "author_name": "Federica Mazzola", + "author_inst": "Institute for Research in Biomedicine, Universit\u00e0 della Svizzera italiana (USI), Bellinzona, Switzerland" }, { - "author_name": "Duuamene Nyimanu", - "author_inst": "University of Cambridge" + "author_name": "Davide Magr\u00ec", + "author_inst": "European Commission, Joint Research Centre, Ispra, VA, Italy" }, { - "author_name": "Janet J Maguire", - "author_inst": "University of Cambridge" + "author_name": "Tereza Michalcikova", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" }, { - "author_name": "Paul J Lehner", - "author_inst": "University of Cambridge" + "author_name": "Jan Haviernik", + "author_inst": "Veterinary Research Institute, Brno, Czech Republic" }, { - "author_name": "Sanjay Sinha", - "author_inst": "University of Cambridge" + "author_name": "Vaclav Honig", + "author_inst": "Veterinary Research Institute, Brno, Czech Republic and Institute of Parasitology, Biology Centre of the Czech Academy of Sciences, Ceske Budejovice, Czech Repu" }, { - "author_name": "Anthony P Davenport", - "author_inst": "University of Cambridge" + "author_name": "Blanka Mrazkova", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" + }, + { + "author_name": "Natalie Polakova", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" + }, + { + "author_name": "Andrea Fortova", + "author_inst": "Veterinary Research Institute, Brno, Czech Republic" + }, + { + "author_name": "Jolana Tureckova", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" + }, + { + "author_name": "Veronika Iatsiuk", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" + }, + { + "author_name": "Salvatore Di Girolamo", + "author_inst": "Institute for Research in Biomedicine, Universit\u00e0 della Svizzera italiana (USI), Bellinzona, Switzerland" + }, + { + "author_name": "Martin Palus", + "author_inst": "Veterinary Research Institute, Brno, Czech Republic and Institute of Parasitology, Biology Centre of the Czech Academy of Sciences, Ceske Budejovice, Czech Repu" + }, + { + "author_name": "Dagmar Zudova", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" + }, + { + "author_name": "Petr Bednar", + "author_inst": "Veterinary Research Institute, Brno, Czech Republic and Faculty of Science, University of South Bohemia, Ceske Budejovice, Czech Republic" + }, + { + "author_name": "Ivana Bukova", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" + }, + { + "author_name": "Filippo Bianchini", + "author_inst": "Institute for Research in Biomedicine, Universit\u00e0 della Svizzera italiana (USI), Bellinzona, Switzerland" + }, + { + "author_name": "Dora Mehn", + "author_inst": "European Commission, Joint Research Centre, Ispra, VA, Italy" + }, + { + "author_name": "Radim Nencka", + "author_inst": "Institute of Organic Chemistry and Biochemistry of the Czech Academy of Sciences, Prague, Czech Republic" + }, + { + "author_name": "Petra Strakova", + "author_inst": "Veterinary Research Institute, Brno, Czech Republic" + }, + { + "author_name": "Oto Pavlis", + "author_inst": "Center of Biological Defense, Military Health Institute, Military Medical Agency, Techonin, Czech Republic" + }, + { + "author_name": "Jan Rozman", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" + }, + { + "author_name": "Sabrina Gioria", + "author_inst": "European Commission, Joint Research Centre, Ispra, VA, Italy" + }, + { + "author_name": "Jos\u00e8 Camilla Sammartino", + "author_inst": "Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy" + }, + { + "author_name": "Federica Giardina", + "author_inst": "Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy" + }, + { + "author_name": "Stefano Gaiarsa", + "author_inst": "Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy" + }, + { + "author_name": "Qiang Pan Hammarstr\u00f6m", + "author_inst": "Department of Biosciences and Nutrition, Karolinska Institutet, SE14183, Huddinge, Sweden" + }, + { + "author_name": "Christopher O. Barnes", + "author_inst": "Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA" + }, + { + "author_name": "Pamela J. Bjorkman", + "author_inst": "Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA" + }, + { + "author_name": "Luigi Calzolai", + "author_inst": "European Commission, Joint Research Centre, Ispra, VA, Italy" + }, + { + "author_name": "Antonio Piralla", + "author_inst": "Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy" + }, + { + "author_name": "Fausto Baldanti", + "author_inst": "Molecular Virology Unit, Microbiology and Virology Department, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy" + }, + { + "author_name": "Michel C. Nussenzweig", + "author_inst": "Laboratory of Molecular Immunology, The Rockefeller University, New York, NY, USA and Howard Hughes Medical Institute, The Rockefeller University, New York, NY," + }, + { + "author_name": "Paul D. Bieniasz", + "author_inst": "Laboratory of Retrovirology, The Rockefeller University, New York, NY, USA and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA" + }, + { + "author_name": "Theodora Hatziioannou", + "author_inst": "Laboratory of Retrovirology, The Rockefeller University, New York, NY, USA" + }, + { + "author_name": "Jan Prochazka", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" + }, + { + "author_name": "Radislav Sedlacek", + "author_inst": "Czech Centre of Phenogenomics, Institute of Molecular Genetics of the Czech Academy of Sciences, Vestec, Czech Republic" + }, + { + "author_name": "Davide F. Robbiani", + "author_inst": "Institute for Research in Biomedicine, Universit\u00e0 della Svizzera italiana (USI), Bellinzona, Switzerland" + }, + { + "author_name": "Daniel Ruzek", + "author_inst": "Veterinary Research Institute, Brno, Czech Republic and Institute of Parasitology, Biology Centre of the Czech Academy of Sciences, Ceske Budejovice, Czech Repu" + }, + { + "author_name": "Luca Varani", + "author_inst": "Institute for Research in Biomedicine, Universit\u00e0 della Svizzera Italiana" } ], "version": "1", - "license": "cc_no", + "license": "", "type": "new results", - "category": "pharmacology and toxicology" + "category": "immunology" }, { "rel_doi": "10.1101/2021.01.22.427802", @@ -989770,47 +988916,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.01.18.21250025", - "rel_title": "COVID-19 in 823 Transplant patients: A Systematic Scoping Review", + "rel_doi": "10.1101/2021.01.18.21250050", + "rel_title": "Analysis of communities of countries with similar dynamics of the COVID-19 pandemic evolution", "rel_date": "2021-01-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.18.21250025", - "rel_abs": "BackgroundManagement of COVID-19 in transplant patients is a big challenge. Data on immunosuppression management, clinical picture, and outcomes are lacking.\n\nObjectivesTo summarize the current literature on COVID-19 in transplant patients especially the data regarding the immunosuppression protocols, clinical presentation, and outcomes.\n\nSearch strategyA systematic search of MEDLINE, EBSCO, CENTRAL, CINAHL, LitCovid, Web of Science, and Scopus electronic databases. The references of the relevant studies were also searched. The search was last updated on June 3, 2020.\n\nSelection CriteriaPrimary reports of solid organ transplant patients who developed COVID-19. An overlap of cases in different reports was checked.\n\nData collection and analysisA descriptive summary of immunosuppression therapy (before and after COVID-19), clinical presentation (symptoms, imaging, laboratory, and disease severity), management (oxygen therapy, antiviral, and antibacterial), major outcomes (Intensive care admission, invasive mechanical ventilation, acute kidney injury), and mortality.\n\nMain resultsWe identified 74 studies reporting 823 cases of solid organ transplantation with COVID-19. Among 372 patients, 114 (30.6%) were mild COVID-19, 101 (27.2%) moderate, and 157 (42.2%) severe or critical.\n\nMajor outcomes included intensive care unit admission, invasive ventilation, and acute kidney injury, which occurred in 121 (14.7%), 97 (11.8%), and 63 (7.7%) of patients, respectively. Mortality was reported in 160 (19.4%) patients. Missing individual data hindered making clinical correlations.\n\nConclusionCOVID-19 in solid organ transplant patients probably has a more disease severity, worse major outcomes (Intensive care admission, invasive ventilation, acute kidney injury), and higher mortality than in non-transplant patients.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.18.21250050", + "rel_abs": "This work addresses the spread of the coronavirus through a non-parametric approach, with the aim of identifying communities of countries based on how similar their evolution of the disease is. The analysis focuses on the number of daily new COVID-19 cases per ten thousand people during a period covering at least 250 days after the confirmation of the tenth case. Dynamic analysis is performed by constructing Minimal Spanning Trees (MST) and identifying groups of similarity in contagions evolution in 95 time windows of a 150-day amplitude that moves one day at a time. The number of times countries belonged to a similar performance group in constructed time windows was the intensity measure considered. Groups composition is not stable, indicating that the COVID-19 evolution needs to be treated as a dynamic problem in the context of complex systems. Three communities were identified by applying the Louvain algorithm. Identified communities analysis according to each countrys socioeconomic characteristics and variables related to the disease sheds light on whether there is any suggested course of action. Even when strong testing and tracing cases policies may be related with a more stable dynamic of the disease, results indicate that communities are conformed by countries with diverse characteristics. The best option to counteract the harmful effects of a pandemic may be having strong health systems in place,with contingent capacity to deal with unforeseen events and available resources capable of a rapid expansion of its capacity.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Moataz Maher Emara", - "author_inst": "Department of Anesthesiology and Intensive Care and Pain medicine, Mansoura University, Egypt" - }, - { - "author_name": "Mahmoud Elsedeiq", - "author_inst": "Department of Anesthesiology and Intensive Care and Pain Medicine, Mansoura University, Egypt" - }, - { - "author_name": "Mohamed Elmorshedi", - "author_inst": "Department of Anesthesiology and Intensive Care and Pain Medicine, Mansoura University, Egypt" - }, - { - "author_name": "Hamed Neamatallah", - "author_inst": "Department of Anesthesiology and Intensive Care and Pain Medicine, Mansoura University, Egypt" + "author_name": "Emiliano Alvarez", + "author_inst": "Universidad de la Republica" }, { - "author_name": "Mostafa Abdelkhalek", - "author_inst": "Department of Anesthesiology and Intensive Care and Pain Medicine, Mansoura University, Egypt" + "author_name": "Juan Gabriel Brida", + "author_inst": "Universidad de la Republica" }, { - "author_name": "Amr Yassen", - "author_inst": "Department of Anesthesiology and Intensive Care and Pain Medicine, Mansoura University, Egypt" + "author_name": "Erick Limas", + "author_inst": "Institute for Latin American Studies and School of Business & Economics, Freie Universitat Berlin" }, { - "author_name": "Ashraf Nabhan", - "author_inst": "Department of Obstetrics and Gynecology, Faculty of Medicine, Ain Shams University, Cairo, Egypt" + "author_name": "Lucia Rosich", + "author_inst": "Universidad de la Republica" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "transplantation" + "category": "health economics" }, { "rel_doi": "10.1101/2021.01.18.21250034", @@ -991240,51 +990374,71 @@ "category": "nephrology" }, { - "rel_doi": "10.1101/2021.01.18.21249976", - "rel_title": "Covid-19 respiratory protection: the filtration efficiency assessment of decontaminated FFP2 masks responding to associated shortages", + "rel_doi": "10.1101/2021.01.18.21249433", + "rel_title": "The burden of nosocomial covid-19: results from the Wales multi-centre retrospective observational study of 2518 hospitalised adults.", "rel_date": "2021-01-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.18.21249976", - "rel_abs": "During the Covid-19 pandemic, healthcare workers were extremely vulnerable to infection with the virus and needed continuous protection. One of the most effective and widely used means of protection was the FFP2 respirator. Unfortunately, this crisis created a shortage of these masks, prompting hospitals to explore opportunities to reuse them after decontamination.\n\nAn approach for assessing the filtration efficiency of decontaminated FFP2 masks has been proposed and applied to evaluate the possibilities of their safe reuse. The decontamination processes adopted are those based on moist heat or hydrogen peroxide. The approach introduces efficiency measures that define the filtration and protection capacity of the masks, which characterize both chemical and structural changes, and encompasses many techniques including scanning electron microscopy (SEM), Fourier transforms infrared spectroscopy (FTIR), and thermogravimetric analysis (TGA). The test protocol was applied to mask samples that had endured different decontamination cycles and the results of their efficiency measures were compared to brand-new masks performances.\n\nThe main result was that chemical and structural characterization of the decontaminated masks have shown no substantial change or deformation of their filter media structures. Indeed, the respiratory resistance test has shown that the results of both the FFP2 masks that have undergone a hydrogen peroxide disinfection cycle or a steam autoclave cycle remained constant with a small variation of 10 Pa from the EN149 standard. The chemical characterization, on the other hand, has shown that the filter media of the decontaminated masks remains unchanged, with no detectable chemical derivatives in its constituents.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.18.21249433", + "rel_abs": "ObjectivesTo define the burden of nosocomial (hospital-acquired) novel pandemic coronavirus (covid-19) infection among adults hospitalised across Wales.\n\nDesignRetrospective observational study of adult patients with polymerase chain reaction (PCR)-confirmed SARS-CoV-2 infection between 1st March - 1st July 2020 with a recorded hospital admission within the subsequent 31 days. Outcomes were collected up to 20th November using a standardised online data collection tool.\n\nSettingService evaluation performed across 18 secondary or tertiary care hospitals.\n\nParticipants4112 admissions with a positive SARS-CoV-2 PCR result between 1st March to 1st July 2020 were screened. Anonymised data from 2518 participants were returned, representing over 60% of adults hospitalised across the nation of Wales.\n\nMain outcome measuresThe prevalence and outcomes (death, discharge) for nosocomial covid-19, assessed across of a range of possible case definitions.\n\nResultsInpatient mortality rates for nosocomial covid-19 ranged from 38% to 42% and remained consistently higher than participants with community-acquired infection (31% to 35%) across a range of case definitions. Participants with nosocomial-acquired infection were an older, frailer, and multi-morbid population than those with community-acquired infection. Based on the Public Health Wales case definition, 50% of participants had been admitted for 30 days prior to diagnostic testing.\n\nConclusionsThis represents the largest assessment of clinical outcomes for patients with nosocomial covid-19 in the UK to date. These findings suggest that inpatient mortality rates from nosocomial-infection are likely higher than previously reported, emphasizing the importance of infection control measures, and supports prioritisation of vaccination for covid-19 negative admissions and trials of post-exposure prophylaxis in inpatient cohorts.\n\nTrial registrationThis project was approved and sponsored by the Welsh Government, as part of a national audit and quality improvement scheme for patients hospitalised covid-19 across Wales.\n\nKey MessagesO_ST_ABSWhat is already known on this topicC_ST_ABSWe searched PubMed and ISI Web of Science up until 31-December-2020 for studies reporting on patient outcomes following hospital-acquired infection due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We identified a range of case-definitions for hospital-acquired infection, based on timing of diagnostic testing 5 to 15 days following admission. The largest and only multi-centre study concluded individuals with nosocomial infection are at a lower risk of death from SARS-CoV-2 than those infected in the community, however, was performed early in the pandemic and utilised a conservative definition of nosocomial infection.\n\nWhat this study addsOur multi-centre observational study represents the largest assessment of clinical outcomes for patients with nosocomial covid-19 in the UK to date, and suggests the burden of nosocomial SARS-CoV-2 infection has been underestimated. Nosocomial-infection occurred in older, frailer, and multi-morbid individuals, and was consistently associated with greater inpatient mortality than amongst those who were infected in the community across a spectrum of case-definitions. Our findings support implementation of enhanced infection control measures to reduce this burden during future waves, especially given the recent emergence of novel viral variants with enhanced transmissibility. Furthermore, roughly half of the patients meeting the Public Health Wales definition of definite nosocomial SARS-CoV-2 infection had been admitted for 30 days prior to diagnosis, highlighting a potential window of opportunity for inpatient pre-exposure and/or post-exposure prophylaxis.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "benboubker moussa", - "author_inst": "USMBA,Fez,Morocco" + "author_name": "Mark J Ponsford", + "author_inst": "School of Medicine, Cardiff University" + }, + { + "author_name": "Rhys Jefferies", + "author_inst": "Respiratory Health Implementation Group" + }, + { + "author_name": "Chris Davies", + "author_inst": "Institute for Clinical Science and Technology, Cardiff" + }, + { + "author_name": "Daniel Farewell", + "author_inst": "Division of Population Medicine, School of Medicine, Cardiff University" }, { - "author_name": "Bouchra Omokhtar", - "author_inst": "USMBA,Fez,Morocco" + "author_name": "Ian R Humphreys", + "author_inst": "Systems Immunity Research Institute, Cardiff University, Cardiff, CF14 4XN" + }, + { + "author_name": "Stephen Jolles", + "author_inst": "Immunodeficiency Centre for Wales, University Hospital of Wales, Cardiff" + }, + { + "author_name": "Sara Fairbairn", + "author_inst": "Department of Respiratory Medicine, Aneurin Bevan University Health Board" }, { - "author_name": "Fouzia hmami", - "author_inst": "USMBA,Fez,Morocco" + "author_name": "Keir Lewis", + "author_inst": "Department of Medicine, Prince Philip Hospital, Hywel Dda University Health Board" }, { - "author_name": "Khalil El mabrouk", - "author_inst": "UEMF,Fez,Morocco" + "author_name": "Daniel Menzies", + "author_inst": "Department of Respiratory Medicine, Betsi Cadwaladr University Health Board" }, { - "author_name": "Leena El alami", - "author_inst": "USMBA,Fez,Morocco" + "author_name": "Amit Benjamin", + "author_inst": "Department of Respiratory Medicine, Cwm Taf University Health Board" }, { - "author_name": "Btissam Arhoune", - "author_inst": "USMBA,Fez,Morocco" + "author_name": "Favas Thaivalappil", + "author_inst": "Department of Respiratory Medicine, Swansea Bay University Health Board" }, { - "author_name": "Mohammed Faouzi Belahcen", - "author_inst": "USMBA,Fez,Morocco" + "author_name": "Christopher Williams", + "author_inst": "Communicable Disease Surveillance Centre, Public Health Wales, Cardiff, Wales" }, { - "author_name": "Ahmed Aboutajeddine", - "author_inst": "USMBA,Fez,Morocco" + "author_name": "Simon M Barry", + "author_inst": "Department of Respiratory Medicine, Cardiff and Vale University Health Board" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2021.01.19.21249840", @@ -993210,39 +992364,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.19.21250137", - "rel_title": "A Label-Free SARS-CoV-2 Surrogate Virus Neutralization Test and a Longitudinal Study of Antibody Characteristics in COVID-19 Patients", + "rel_doi": "10.1101/2021.01.19.21250114", + "rel_title": "Modeling the population effects of epitope specific escape mutations in SARS-CoV-2 to guide vaccination strategies", "rel_date": "2021-01-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.19.21250137", - "rel_abs": "Background. The laboratory-based methods to measure the SARS-CoV-2 humoral response include virus neutralization tests (VNTs) to determine antibody neutralization potency. For ease of use and universal applicability, surrogate virus neutralization tests (sVNTs) based on antibody-mediated blockage of molecular interactions have been proposed. Methods. A surrogate virus neutralization test established on a label-free immunoassay platform (LF-sVNT). The LF-sVNT analyzes the binding ability of RBD to ACE2 after neutralizing RBD with antibodies in serum. Results. The LF-sVNT neutralizing antibody titers (IC50) were determined from serum samples (n=246) from COVID-19 patients (n=113), as well as the IgG concentrations and the IgG avidity indices. Although there is variability in the kinetics of the IgG concentrations and neutralizing antibody titers between individuals, there is an initial rise, plateau and then in some cases a gradual decline at later timepoints after 40 days post-symptom onset. The IgG avidity indices, in the same cases, plateau after the initial rise and did not show a decline. Conclusions. The LF-sVNT can be a valuable tool in clinical laboratories for the assessment of the presence of neutralizing antibodies to COVID-19. This study is the first to provide longitudinal neutralizing antibody titers beyond 200 days post-symptom onset. Despite the decline of IgG concentration and neutralizing antibody titer, IgG avidity index increases, reaches a plateau and then remains constant up to 8 months post-infection. The decline of antibody neutralization potency can be attributed to the reduction in antibody quantity rather than the deterioration of antibody avidity, a measure of antibody quality.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.19.21250114", + "rel_abs": "Escape mutations (EM) to SARS-Cov-2 have been detected and are spreading. Vaccines may need adjustment to respond to these or future mutations. We designed a population level model integrating both waning immunity and EM. We also designed a set of criteria for elaborating and fitting this model to cross-neutralization and other data in a manner that minimizes vaccine decision errors. We formulated four model variations. These define criteria for which prior infections provide immunity that can be escaped. They also specify different sequences where one EM follows another. At all reasonable parameter values, these model variations led to patterns where: 1) EM were rare in the first epidemic, 2) rebound epidemics after the first epidemic were accelerated more by increasing drifting than by increasing waning (with some exceptions), 3) the long term endemic level of infection was determined mostly by waning rates with small effects of the drifting parameter, 4) EM caused loss of vaccine effectiveness and under some conditions, vaccines induced EM that caused higher levels of infection with vaccines than without them. The differences and similarities across the four models suggest paths for developing models specifying the epitopes where EM act. This model is a base on which to construct epitope specific evolutionary models using new high-throughput assay data from population samples to guide vaccine decisions.\n\nHighlightsO_LIThis model is the first to integrate both antigenic drifting from escape mutations and immunity waning in continuous time.\nC_LIO_LITiny amounts of only waning or only escape mutation drifting have small or no effects. Together, they have large effects.\nC_LIO_LIThere are no or few escape mutations during the first epidemic peak and no effect of drifting parameters on the size of that wave.\nC_LIO_LIAfter the first epidemic peak, escape mutations accumulate rapidly. They increase with increases in waning rates and with increases in the drifting rate. Escape mutations then amplify other escape mutations since these raise the frequency of reinfections.\nC_LIO_LIEscape mutations can completely negate the effects of vaccines and even lead to more infections with vaccination than without, especially at very low waning rates.\nC_LIO_LIThe model generates population level cross-neutralization patterns that enable the model to be fitted to population level serological data.\nC_LIO_LIThe model can be modified to use laboratory data that determine the epitope specific effects of mutations on ACE2 attachment strength or escape from antibody effects.\nC_LIO_LIThe model, although currently unable to predict the effects of escape mutations in the real world, opens up a path that can guide model incorporation of molecularly studied escape mutations and improve predictive value. We describe that path.\nC_LIO_LIModel analysis indicates that vaccine trials and serological surveys are needed now to detect the effects of epitope specific escape mutations that could cause the loss of vaccine efficacy.\nC_LI", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Yiqi Ruben Luo", - "author_inst": "University of California San Francisco" - }, - { - "author_name": "Cassandra Yun", - "author_inst": "University of California San Francisco" + "author_name": "James S Koopman", + "author_inst": "University of Michigan" }, { - "author_name": "Indrani Chakraborty", - "author_inst": "Gator Bio" + "author_name": "Carl P Simon", + "author_inst": "University of Michigan" }, { - "author_name": "Alan H.B. Wu", - "author_inst": "University of California San Francisco" + "author_name": "Wayne M Getz", + "author_inst": "University of California at Berkeley" }, { - "author_name": "Kara Lake Lynch", - "author_inst": "University of California San Francisco" + "author_name": "Richard Salter", + "author_inst": "Oberlin College" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.01.19.21250106", @@ -995240,43 +994390,99 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2021.01.18.427092", - "rel_title": "A national analysis of trends in COVID-19 infection and clinical management in Veterans Health Administration medical facilities", - "rel_date": "2021-01-18", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.18.427092", - "rel_abs": "OBJECTIVEWe explored longitudinal trends in sociodemographic characteristics, reported symptoms, laboratory findings, pharmacological and non-pharmacological treatment, comorbidities, and 30-day in-hospital mortality among hospitalized patients with coronavirus disease 2019 (COVID-19).\n\nMETHODSThis retrospective cohort study included 43,267 patients diagnosed with COVID-19 in the Veterans Health Administration between 03/01/20 and 08/31/20 and followed until 09/30/20. We focused our analysis on patients that were subsequently hospitalized, and categorized them into groups based on the month of hospitalization. We summarized our findings through descriptive statistics. We used a nonparametric rank-sum test for trend to examine any differences in the distribution of our study variables across the six months.\n\nRESULTSDuring our study period, 8,240 patients were hospitalized, and 1,081 (13.1%) died within 30 days of admission. Hospitalizations increased over time, but the proportion of patients that died consistently declined from March (N=221/890, 24.8%) to August (N=111/1,396, 8.0%). Patients hospitalized in March compared to August were younger on average, mostly black, and symptomatic. They also had a higher frequency of baseline comorbidities, including hypertension and diabetes, and were more likely to present with abnormal laboratory findings including low lymphocyte counts and elevated creatinine. Lastly, receipt of mechanical ventilation and Hydroxychloroquine declined from March to August, while treatment with Dexamethasone and Remdesivir increased.\n\nCONCLUSIONWe found evidence of declining COVID-19 severity and fatality over time within a national health care system.", - "rel_num_authors": 6, + "rel_doi": "10.1101/2021.01.15.21249691", + "rel_title": "SARS-CoV-2 viral load distribution in different patient populations and age groups reveals that viral loads increase with age.", + "rel_date": "2021-01-17", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.15.21249691", + "rel_abs": "ObjectiveTo describe the SARS-CoV-2 viral load distribution in different patient groups and age categories.\n\nMethodsAll SARS-CoV-2 RT-PCR results from nasopharyngeal (NP) and oropharyngeal (OP) swabs (first PCR from unique patients only) that were collected between January 1 and December 1, 2020, predominantly in the Public Health Services regions Kennemerland and Hollands Noorden, province of North Holland, the Netherlands were included in this study. Swabs were derived from patients with respiratory symptoms who were presented at the general practitioner (GP), hospital, or hospital health care workers (HCWs) of four regional hospitals, nursing home residents and HCWs of multiple nursing homes, and in majority (>75%) from Public Health testing facilities of the two Public Health Services. SARS-CoV-2 PCR crossing point (Cp) values were used to estimate viral loads (higher Cp-values indicate lower viral loads).\n\nResultsIn total, 278.455 unique patients were tested of whom 9{middle dot}1% (n=25.374) were SARS-CoV-2 positive. As there were differences in viral load distribution between tested populations, further analyses focused on PCRs performed by public health services (n=211.914) where sampling and inclusion were uniform. These data reveal a clear relation between age and SARS-CoV-2 viral load, with especially children aged<12 years showing lower viral loads than shown in adults ({beta}: -0{middle dot}03, 95CI% -0{middle dot}03 to -0{middle dot}02, p<0{middle dot}001), independent of sex and/or symptom duration. Interestingly, the median Cp-values between the oldest (>79 years) and youngest (<12 years) population differed by over 4 PCR cycles, suggesting approximately a 16-fold difference in viral load. In addition, the proportion of children aged <12 years with a low load (Cp-value >30) was significantly higher compared to the other patients (31{middle dot}1% vs. 17{middle dot}2%, p-value<0.001).\n\nConclusionWe observed that in patients tested by Public Health Services, SARS-CoV2 viral load increases significantly with age. Previous studies suggest that young children (<12 years) play a limited role in SARS-CoV-2 transmission. Currently, the relation between viral load and infectivity is not yet well understood, and further studies should elucidate whether the lower viral load in children is indeed related to their suggested limited role in SARS-CoV-2 transmission. Moreover, as rapid antigen tests are less sensitive than PCR, these results suggest that SARS-CoV-2 antigen tests could have lower sensitivity in children than in adults.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Maya Aboumrad", - "author_inst": "White River Junction VA Medical Center" + "author_name": "Sjoerd Euser", + "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" }, { - "author_name": "Brian Shiner", - "author_inst": "White River Junction VA Medical Center" + "author_name": "Sem Aronson", + "author_inst": "Spaarne Gasthuis, Hoofddorp/Haarlem, the Netherlands" }, { - "author_name": "Natalie Riblet", - "author_inst": "White River Junction VA Medical Center" + "author_name": "Irene Manders", + "author_inst": "Public Health Service Kennemerland, Haarlem, the Netherlands & Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" }, { - "author_name": "Hugh Huizenga", - "author_inst": "White River Junction VA Medical Center" + "author_name": "Steven van Lelyveld", + "author_inst": "Spaarne Gasthuis, Hoofddorp/Haarlem, the Netherlands" }, { - "author_name": "Nabin Neupane", - "author_inst": "White River Junction VA Medical Center" + "author_name": "Bjorn Herpers", + "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" }, { - "author_name": "Yinong Young-Xu", - "author_inst": "White River Junction VA Medical Center" + "author_name": "Jan Sinnige", + "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem" + }, + { + "author_name": "Jayant Kalpoe", + "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem" + }, + { + "author_name": "Claudia van Gemeren", + "author_inst": "Spaarne Gasthuis, Hoofddorp/Haarlem" + }, + { + "author_name": "Dominic Snijders", + "author_inst": "Spaarne Gasthuis, Hoofddorp/Haarlem" + }, + { + "author_name": "Ruud Jansen", + "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" + }, + { + "author_name": "Sophie Schuurmans Stekhoven", + "author_inst": "Spaarne Gasthuis, Hoofddorp/Haarlem, the Netherlands" + }, + { + "author_name": "Marlies van Houten", + "author_inst": "Spaarne Gasthuis, Hoofddorp/Haarlem, the Netherlands" + }, + { + "author_name": "Ivar Lede", + "author_inst": "Comicro BV medical microbiology, Hoorn, the Netherlands" + }, + { + "author_name": "James Cohen Stuart", + "author_inst": "Department of Medical Microbiology, Noordwest Ziekenhuisgroep, Alkmaar, The Netherlands" + }, + { + "author_name": "Fred Slijkerman Megelink", + "author_inst": "Public Health Service Hollands Noorden, Alkmaar, the Netherlands" + }, + { + "author_name": "Erik Kapteijns", + "author_inst": "Rode Kruis Ziekenhuis, Beverwijk, the Netherlands" + }, + { + "author_name": "Jeroen den Boer", + "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" + }, + { + "author_name": "Elisabeth Sanders", + "author_inst": "Wilhelmina Childrens Hospital, University Medical Center Utrecht, Utrecht, the Netherlands & Center for Infectious Disease Control, National Institute for Publi" + }, + { + "author_name": "Alex Wagemakers", + "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" + }, + { + "author_name": "Dennis Souverein", + "author_inst": "Regional Public Health Laboratory Kennemerland, Haarlem, the Netherlands" } ], "version": "1", - "license": "cc0", - "type": "new results", - "category": "scientific communication and education" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2021.01.12.21249713", @@ -997685,33 +996891,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.14.21249853", - "rel_title": "The Use of Procalcitonin as an Antimicrobial Stewardship Tool and a Predictor of Disease Severity in COVID-19", + "rel_doi": "10.1101/2021.01.14.21249836", + "rel_title": "Persistently increased systemic ACE2 activity and Furin levels are associated with increased inflammatory response in smokers with SARS-CoV-2 COVID-19", "rel_date": "2021-01-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.14.21249853", - "rel_abs": "In our study, procalcitonin was associated with both antibiotic use and duration in patients with COVID-19, as well as established biochemical markers of COVID-19 disease severity and oxygen requirement, suggesting a potential role for procalcitonin in COVID-19 antimicrobial stewardship.", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.14.21249836", + "rel_abs": "BackgroundTobacco smoking is known to be involved in the pathogenesis of several cardiopulmonary diseases, and smokers are susceptible to infectious agents. However, the progression of lung injury based on COVID-19 susceptibility and severity amongst smokers and those with pre-existing pulmonary diseases is not known. We determined the systemic expression and activity of COVID-19 related proteins, cytokine/chemokines, and lipid mediators (lipidomics) amongst COVID-19 patients with and without a history of smoking with a view to define biomarkers.\n\nMethodsWe obtained serum from COVID-19 positive and COVID-19 recovered patients with and without a history of smoking. We conducted a Luminex multiplex assay (cytokine levels), LC/MS (eicosanoids or oxylipin panel) and enzymatic activity assays on the serum samples to study the systemic changes in COVID-19 patients.\n\nResultsOn comparing the cytokine profiles among COVID-19 positive and COVID-19 negative patients, we found a significant upregulation in the production of pro-inflammatory cytokines like IL-1, IL-8, IL-2, VEGF and IL-10 in COVID-19 positive patients as compared to the respective controls. Interestingly, smoking history resulted in further augmentation of the release of some hyper-inflammatory cytokines, like IFN-{gamma}, Eotaxin, MCP-1 and IL-9 amongst COVID-19 positive patients. The enzymatic activity for ACE2, the binding partner for SARS-CoV2 virus in the host cell, was found to be significantly increased in the serum of patients with a smoking history compared to the serum collected from the non-smoking controls. Similarly to our cytokine analysis, our measurement of serum Furin levels was also affected by the patients smoking history, in which we reported a substantial rise in serum Furin levels of COVID-19 patients. The analysis of lipid mediators revealed a distinct signature amongst the COVID-19 positive versus recovered subjects in PGF2, HETEs, LXA4 and LTB4 levels. However, we did not find any changes in the levels of any lipid mediators based on the smoking history of the patients. Overall, our results point towards distinct systemic signatures amongst COVID-19 positive patients. We also show that smoking adversely affects the systemic levels of inflammatory markers and COVID-19 related proteins, thus suggesting that COVID-19 infection may have severe outcomes amongst smokers which is reflected systemically.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "George Peter Drewett", - "author_inst": "Austin Health" + "author_name": "Gagandeep Kaur", + "author_inst": "University of Rochester" }, { - "author_name": "Olivia C Smibert", - "author_inst": "Austin Health" + "author_name": "Shaiesh Yogeswaran", + "author_inst": "University of Rochester" }, { - "author_name": "Natasha E Holmes", - "author_inst": "Austin Health" + "author_name": "Thivanka Muthumalage", + "author_inst": "University of Rochester" }, { - "author_name": "Jason A Trubiano", - "author_inst": "Austin Health" + "author_name": "Irfan Rahman", + "author_inst": "University of Rochester" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -999691,51 +998897,55 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2021.01.11.21249324", - "rel_title": "A national survey of potential acceptance of COVID-19 vaccines in healthcare workers in Egypt", + "rel_doi": "10.1101/2021.01.12.20248726", + "rel_title": "Changes in the Health of Adolescent Athletes: A Comparison of Health Measures Collected Before and During the CoVID-19 Pandemic", "rel_date": "2021-01-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.11.21249324", - "rel_abs": "BackgroundSince the start of COVID-19 outbreak investigators are competing to develop and exam vaccines against COVID-19. It would be valuable to protect the population especially health care employees from COVID-19 infection. The success of COVID-19 vaccination programs will rely heavily on public willingness to accept the vaccine.\n\nAimsThis study aimed to describe the existing COVID-19 vaccine approval landscape among the health care providers and to identify the most probable cause of agreement or disagreement of COVID-19 vaccine.\n\nMethodsA cross-sectional online survey was done.\n\nResultsThe present study included 496 health care employees, 55% were at age group from 18-45 years old. History of chronic diseases was recorded in 40.4%, and definite history of drug/food allergy in 10.1%. Only 13.5% totally agree to receive the vaccine, 32.4% somewhat agree and 40.9% disagreed to take the vaccine. Causes of disagreement were none safety, fear of genetic mutation and recent techniques and believe that the vaccine is not effective (57%, 20.2%, 17.7% and 16.6% respectively). The most trusted vaccine was the mRNA based vaccine. The age of health care employees and the presence of comorbidities or chronic diseases were the main factors related to COVID-19 acceptance (P<0.001 and 0.02 respectively).\n\nConclusionVaccine hesitancy is not uncommon in healthcare employees in Egypt and this may be an alarming barrier of vaccine acceptance in the rest of population. There is an urgent need to start campaigns to increase the awareness of the vaccine importance.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.12.20248726", + "rel_abs": "ContextIn the spring of 2020, schools closed to in-person teaching and sports were cancelled to control the transmission of CoVID-19. The changes that took place to the physical and mental health among young athletes during this time remain unknown, however.\n\nObjectiveIdentify changes in the health (mental health, physical activity and quality of life) of athletes that occurred during the CoVID-19 pandemic.\n\nDesignCross sectional study.\n\nSettingSample recruited via social media.\n\nPatients or Other Participants3243 Wisconsin adolescent athletes (age=16.2{+/-}1.2 yrs., female=58% female) completed an online survey in May 2020 (DuringCoVID-19). Health measures for this cohort were compared with previously reported data for Wisconsin adolescent athletes (n=5231, age=15.7{+/-}1.2, 47% female) collected in 2016-2018 (PreCoVID-19).\n\nMain Outcome Measure(s)Demographic information included: sex, grade and sports played. Health assessments included the Patient Health Questionnaire-9 Item (PHQ-9) to identify depression symptoms, the Pediatric Functional Activity Brief Scale (PFABS) for physical activity, and the Pediatric Quality of Life Inventory 4.0 (PedsQL) for health related quality of life (HRQoL). Univariable comparisons of these variables between groups were made via t-tests or chi-square tests. Means and 95% confidence intervals (CI) for each group were estimated by survey weighted ANOVA models.\n\nRESULTSCompared to PreCoVID-19, a larger proportion of the During-CoVID-19 participants reported rates of moderate to severe levels of depression (9.7% vs 32.9%, p<0.001). During-CoVID-19 participants reported 50% lower (worse) PFABS scores (mean:12.2 [95%CI: 11.9, 12.5] vs 24.7 [24.5, 24.9] p<0.001) and lower (worse) PedsQL total scores compared to the PreCoVID-19 participants (78.4 [78.0, 78.8] vs. 90.9 [90.5, 91.3] p<0.001).\n\nCONCLUSIONSDuring the CoVID-19 pandemic, adolescent athletes reported increased symptoms of depression, decreased physical activity and decreased quality of life compared to adolescent athletes in previous years.\n\nKey pointsO_LIAdolescent athletes during CoVID-19 were three times more likely to report moderate to severe symptoms of depression compared to data collected prior to CoVID-19.\nC_LIO_LIAdolescent athletes during CoVID-19 reported significantly lower physical activity and quality of life scores compared to high school athletes prior to the CoVID-19 pandemic\nC_LIO_LIPost CoVID-19 policies should be implemented to improve the health of adolescent athletes in the US.\nC_LI", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Aliae AR Mohamed-Hussein", - "author_inst": "Faculty of medicine, Assiut University" + "author_name": "Timothy McGuine", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "islam g sayed", - "author_inst": "Aswan University" + "author_name": "Kevin Biese", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "nahed Makhlouf", - "author_inst": "Faculty of medicine, Assiut University" + "author_name": "Scott Hetzel", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Hoda Makhlouf", - "author_inst": "Assiut Faculty of Medicine" + "author_name": "Labina Petrovska", + "author_inst": "University of Wisconsin- Madison" }, { - "author_name": "Howaida Abd El Aal", - "author_inst": "Assiut Faculty of Nursing" + "author_name": "Stephanie Kliethermes", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Karima Kholief", - "author_inst": "Assiut Faculty of Medicine" + "author_name": "Claudia Reardon", + "author_inst": "University of Wiscosin-Madison" }, { - "author_name": "Mahmoud M Saad", - "author_inst": "Assiut Faculty of Medicine" + "author_name": "David Bell", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Doaa Abdeltawab Abdellal", - "author_inst": "Assiut Faculty of Medicine" + "author_name": "M. Alison Brooks", + "author_inst": "University of Wisconsin-Madison" + }, + { + "author_name": "Andrew Watson", + "author_inst": "University of Wisconsin-Madison" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "sports medicine" }, { "rel_doi": "10.1101/2021.01.14.21249845", @@ -1001457,23 +1000667,51 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.01.08.21249273", - "rel_title": "Modeling the COVID-19 transmission in Italy: The roles of asymptomatic cases, social distancing, and lockdowns", + "rel_doi": "10.1101/2021.01.09.20248472", + "rel_title": "Magnitude, change over time, demographic characteristics and geographic distribution of excess deaths among nursing home residents during the first wave of COVID-19 in France: a nationwide cohort study", "rel_date": "2021-01-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.08.21249273", - "rel_abs": "The SEIR model of COVID-19 is developed to investigate the roles of physical distancing, lockdowns and asymptomatic cases in Italy. In doing so, two types of policies including behavioral measures and lockdown measures are embedded in the model. Compared with existing models, the model successfully reproduces similar multiple observed outputs such as infected and recovered patients in Italy by July 2020. This study concludes that the first policy is important once the number of infected cases is relatively low. However, once the number of infected cases is very high so the society cannot identify infected and disinfected people, the second policy must be applied soon. It is thus this study suggests that relaxed lockdowns lead to the second wave of the COVID-19 around the world. It is hoped that the model can enhance our understanding on the roles of behavioral measures, lockdowns, and undocumented cases, so-called asymptomatic cases, on the COVID-19 flow.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.09.20248472", + "rel_abs": "ImportanceNursing home (NH) residents are particularly vulnerable to SARS-CoV-2 infections and coronavirus disease 2019 (COVID-19) lethality. However, excess deaths in this population have rarely been documented.\n\nObjectivesThe primary objective was to assess the number of excess deaths among NH residents during the first wave of the COVID-19 pandemic in France. The secondary objectives were to determine the number of excess deaths as a proportion of the total excess deaths in the general population and determine whether a harvesting effect was present.\n\nDesignWe studied a cohort of 494,753 adults (as of March 1st, 2020) aged 60 and over in 6,515 NHs in mainland France. This cohort was exposed to the first wave of the COVID-19 pandemic (from March 1st to May 31st, 2020) and was compared with the corresponding, reference cohorts from 2014 to 2019 (using data from the French National Health Data System).\n\nMain outcome and measuresThe main outcome was all-cause death. Weekly excess deaths and standardized mortality ratios (SMRs) were estimated.\n\nResultThere were 13,505 excess deaths among NH residents. Mortality increased by 43% (SMR: 1.43). The mortality excess was higher among males than among females (SMR: 1.51 and 1.38, respectively) and decreased with age (SMRs in females: 1.61 in the 60-74 age group, 1.58 for 75-84, 1.41 for 85-94, and 1.31 for 95 or over; Males: SMRs: 1.59 for 60-74, 1.69 for 75-84, 1.47 for 85-94, and 1.41 for 95 or over). We did not observe a harvesting effect (up until August 30th, 2020). By extrapolating to all NH residents nationally (N=570,003), the latter accounted for 51% of the total excess deaths in the general population (N=15,114 out of 29,563).\n\nConclusionNH residents accounted for about half of the total excess deaths in France during the first wave of the COVID-19 pandemic. The excess death rate was higher among males than females and among younger residents than among older residents. We did not observe a harvesting effect. A real-time mortality surveillance system and the identification of individual and environmental risk factors might help to design the future model of care for older dependent adults.\n\nKey pointsO_LIDuring the first wave of the COVID-19 pandemic in France, the mortality among nursing home residents increased by 43%.\nC_LIO_LINursing home residents accounted for 51% of the total excess deaths in France.\nC_LIO_LIThe excess mortality was higher among younger residents than among older residents.\nC_LIO_LIThe excess mortality was higher among males than among females.\nC_LIO_LIWe did not observe a harvesting effect during the study period (ending on August 30th, 2020, i.e., three months after the end of the first wave).\nC_LI", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Muhamad Khairulbahri", - "author_inst": "Bandung Institute of Technology" + "author_name": "Florence Canoui-Poitrine", + "author_inst": "Univ Paris Est/Inserm/APHP" + }, + { + "author_name": "Antoine Rachas", + "author_inst": "Caisse Nationale d'Assurance Maladie" + }, + { + "author_name": "Martine Thomas", + "author_inst": "Caisse nationale d'Assurance Maladie" + }, + { + "author_name": "Laure Carcaillon-Bentata", + "author_inst": "Sante Publique France" + }, + { + "author_name": "Romeo Fontaine", + "author_inst": "INED" + }, + { + "author_name": "Gaetan Gavazzi", + "author_inst": "CHU Grenoble" + }, + { + "author_name": "Marie Laurent", + "author_inst": "Univ Paris Est Creteil/Inserm/APHP" + }, + { + "author_name": "Jean-Marie Robine", + "author_inst": "INED/Inserm/EPHE" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2021.01.06.20248760", @@ -1003487,65 +1002725,105 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.01.11.21249626", - "rel_title": "Aerosol tracer testing in the cabin of wide-bodied Boeing 767 and 777 aircraft to simulate exposure potential of infectious particulate such as SARS-CoV-2", + "rel_doi": "10.1101/2021.01.05.21249196", + "rel_title": "Genomic and mobility data reveal mass population movement as a driver of SARS-CoV-2 dissemination and diversity in Bangladesh", "rel_date": "2021-01-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.11.21249626", - "rel_abs": "The COVID-19 pandemic has reintroduced questions regarding the potential risk of SARS-CoV-2 exposure amongst passengers on an aircraft. Quantifying risk with computational fluid dynamics models or contact tracing methods alone is challenging, as experimental results for inflight biological aerosols is lacking. Using fluorescent aerosol tracers and real time optical sensors, coupled with DNA-tagged tracers for aerosol deposition, we executed ground and inflight testing on Boeing 767 and 777 airframes.\n\nAnalysis here represents tracer particles released from a simulated infected passenger, in multiple rows and seats, to determine the exposure risk via penetration into breathing zones in that row and numerous rows ahead and behind the index case. We completed over 65 releases of 180,000,000 fluorescent particles from the source, with 40+ Instantaneous Biological Analyzer and Collector sensors placed in passenger breathing zones for real-time measurement of simulated virus particle penetration.\n\nResults from both airframes showed a minimum reduction of 99.54% of 1 {micro}m aerosols from the index source to the breathing zone of a typical passenger seated directly next to the source. An average 99.97 to 99.98% reduction was measured for the breathing zones tested in the 767 and 777, respectively. Contamination of surfaces from aerosol sources was minimal, and DNA-tagged 3 {micro}m tracer aerosol collection techniques agreed with fluorescent methodologies.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.05.21249196", + "rel_abs": "BackgroundNew data streams are being used to track the pandemic of SARS-CoV-2, including genomic data which provides insights into patterns of importation and spatial spread of the virus, as well as population mobility data obtained from mobile phones. Here, we analyse the emergence and outbreak trajectory of SARS-CoV-2 in Bangladesh using these new data streams, and identify mass population movements as a key early event driving the ongoing epidemic.\n\nMethodsWe sequenced complete genomes of 67 SARS-CoV-2 samples (March-July 2020) and combined this dataset with 324 genomes from Bangladesh. For phylogenetic context, we also used 68,000 GISAID genomes collected globally. We paired this genomic data with population mobility information from Facebook and three mobile phone operators.\n\nFindingsThe majority (85%) of the Bangladeshi sequenced isolates fall into either pangolin lineage B.1.36 (8%), B.1.1 (19%) or B.1.1.25 (58%). Bayesian time-scaled phylogenetic analysis predicted SARS-COV-2 first appeared in mid-February, through international introductions. The first case was reported on March 8th. This pattern of repeated international introduction changed at the end of March when three discrete lineages expanded and spread clonally across Bangladesh. The shifting pattern of viral diversity across Bangladesh is reflected in the mobility data which shows the mass migration of people from cities to rural areas at the end of March, followed by frequent travel between Dhaka and the rest of the country during the following months.\n\nInterpretationIn Bangladesh, population mobility out of Dhaka as well as frequent travel from urban hotspots to rural areas resulted in rapid country-wide dissemination of SARS-CoV-2. The strains in Bangladesh reflect the local expansion of global lineages introduced early from international travellers to and from major international travel hubs. Importantly, the Bangladeshi context is consistent with epidemiologic and phylogenetic findings globally. Bangladesh is one of the few countries in the world with a rich history of conducting mass vaccination campaigns under complex circumstances. Combining genomics and these new data streams should allow population movements to be modelled and anticipated rendering Bangladesh extremely well prepared to immunize citizens rapidly. Based on our genomics data and the countrys successful immunization history, vaccines becoming available globally will be suitable for implementation in Bangladesh while ongoing genomic surveillance is conducted to monitor for new variants of the virus.\n\nFundingGovernment of Bangladesh, Bill and Melinda Gates Foundation, Wellcome Trust.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe emergence of SARS-CoV-2, leading to the COVID-19 pandemic, has motivated all countries in the world to obtain high resolution data on the virus. Globally over 300,000 strains have been sequenced and information made available in GISAID. Within the first 100 days of the emergence of SARS-CoV-2, genomic analysis from different countries led to the development of vaccines which have now reached market. Information on the prevailing genotypes of SARS-CoV-2 since introduction is needed in low and middle-income countries (LMICs), including Bangladesh, in order to determine the suitability of therapeutics and vaccines in the pipeline and help vaccine deployment.\n\nAdded value of this studyWe sequenced SARS-CoV-2 genomes from strains that were prospectively collected during the height of the pandemic and combined these genomic data with mobility data to comprehensively describe i) how repeated international importations of SARS-CoV-2 were ultimately linked to nationwide spread, ii) 85% of strains belonged to the Pangolin lineages B.1.1, B.1.1.25 and B.1.36 and that similar mutation rates were observed as seen globally iii) the switch in genomic dynamics of SARS-CoV-2 coincided with mass migration out of cities to the rest of the country. We have assessed the contributions of population mobility on the maintenance and spread of clonal lineages of SARS-CoV-2. This is the first time these data types have been combined to look at the spread of this virus nationally.\n\nImplications of all the available evidenceSARS-CoV-2 genomic diversity and mutation rate in Bangladesh is comparable to strains circulating globally. Notably, the data on the genomic changes of SARS-CoV-2 in Bangladesh is reassuring, suggesting that immunotherapeutic and vaccines being developed globally should also be suitable for this population. Since Bangladesh already has extensive experience of conducting mass vaccination campaigns, such as the rollout of the oral Cholera vaccine, experience of developing and using new data streams will enable efficient and targeted immunization of the population in 2021 with COVID-19 vaccine(s).", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Sean M Kinahan", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Lauren A. Cowley", + "author_inst": "University of Bath" }, { - "author_name": "David B Silcott", - "author_inst": "S3I LLC" + "author_name": "Mokibul Hassan Afrad", + "author_inst": "International Centre for Diarrhoeal Disease Research, Bangladesh" }, { - "author_name": "Blake E Silcott", - "author_inst": "S3I LLC." + "author_name": "Sadia Isfat Ara Rahman", + "author_inst": "International Centre for Diarrhoeal Disease Research, Bangladesh" }, { - "author_name": "Ryan M Silcott", - "author_inst": "S3I LLC" + "author_name": "Md. Mahfuz-Al-Mamun", + "author_inst": "Institute for develoging science and health initiatives" }, { - "author_name": "Peter J Silcott", - "author_inst": "S3I LLC" + "author_name": "Taylor Chin", + "author_inst": "Harvard School of Public Health" }, { - "author_name": "Braden J Silcott", - "author_inst": "S3I LLC" + "author_name": "Ayesha S. Mahmud", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Steven L Distelhorst", - "author_inst": "National Strategic Research Institute" + "author_name": "Mohammed Ziaur Rahman", + "author_inst": "International Centre for Diarrhoeal Disease Research, Bangladesh" }, { - "author_name": "Vicki L Herrera", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Mallick Masum Billah", + "author_inst": "IEDCR" }, { - "author_name": "Danielle N Rivera", - "author_inst": "National Strategic Research Institute" + "author_name": "Manjur Hossain Khan", + "author_inst": "IEDCR" }, { - "author_name": "Kevin K Crown", - "author_inst": "National Strategic Research Institute" + "author_name": "Sharmin Sultana", + "author_inst": "IEDCR" }, { - "author_name": "Gabriel A Lucero", - "author_inst": "National Strategic Research Institute" + "author_name": "Tilovatul Khondaker", + "author_inst": "IEDCR" }, { - "author_name": "Joshua Santarpia", - "author_inst": "University of Nebraska Medical Center" + "author_name": "Stephen Baker", + "author_inst": "Cambridge University" + }, + { + "author_name": "Nandita Banik", + "author_inst": "IEDCR" + }, + { + "author_name": "Ahmed Nawsher Alam", + "author_inst": "IEDCR" + }, + { + "author_name": "Kaiissar Mannoor", + "author_inst": "Institute for develoging science and health initiatives" + }, + { + "author_name": "Sayera Banu", + "author_inst": "International Centre for Diarrhoeal Disease Research, Bangladesh" + }, + { + "author_name": "Anir Chowdhury", + "author_inst": "Aspire to Innovate (a2i) Program" + }, + { + "author_name": "Meerjady Sabrina Flora", + "author_inst": "Directorate General of Health Services" + }, + { + "author_name": "Nicholas Thomson", + "author_inst": "Sanger" + }, + { + "author_name": "Caroline Buckee", + "author_inst": "Harvard School of Public Health" + }, + { + "author_name": "Firdausi Qadri", + "author_inst": "International Centre for Diarrhoeal Disease Research, Bangladesh" + }, + { + "author_name": "Tahmina Shirin", + "author_inst": "IEDCR" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1004985,27 +1004263,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.01.09.21249505", - "rel_title": "Wastewater Virus Detection Complements Clinical COVID-19 Testing to Limit Spread of Infection at Kenyon College", + "rel_doi": "10.1101/2021.01.09.21249508", + "rel_title": "Exploration of interethnic variation in the ibuprofen metabolizing enzyme CYP2C9: a cautionary guide for treatment of COVID-19 symptoms", "rel_date": "2021-01-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.09.21249505", - "rel_abs": "In-person college instruction during the 2020 pandemic required effective and economical monitoring of COVID-19 prevalence. Kenyon College and the Village of Gambier conducted measurement of SARS-CoV-2 RNA from the village wastewater plant and from an on-campus sewer line. Wastewater RNA detection revealed virus prevalence leading to individual testing and case identification. Wastewater surveillance also showed when case rates had subsided, thus limiting the need for individual clinical testing. Overall, wastewater virus surveillance allows more targeted use of individual testing and increases community confidence in student population management.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.09.21249508", + "rel_abs": "Coronavirus disease 2019 (COVID-19), is a rapidly spreading infectious illness that causes a debilitating respiratory syndrome. While non-steroidal anti-inflammatory drugs (NSAIDs), may be prescribed for the management of pain and fever, there was early controversy on the use of ibuprofen for symptomatic treatment of COVID-19. P450 enzyme CYP2C9 are known to be involved in the metabolism of NSAIDs. Although no study has been conducted in the setting of population genetics in patients with COVID-19 yet, there are plausible mechanisms by which genetic determinants may play a role in adverse drug reactions (ADRs). In this work, we adjusted expected phenotype frequencies based on racial demographic models dependent on population ancestry in drug responses and toxicity events associated with ibuprofen treatment. A cohort of 101 Jordanian Arab samples retrospectively were selected and genotyped using Affymetrix DMET Plus Premier Package, within the context of over 100,000 global subjects in 417 published reports. European populations are 7.2x more likely to show impaired ibuprofen metabolism than Sub-Saharan populations, and 4.5x more likely than East Asian ancestry populations. Hence, a proactive assessment of the most likely gene-drug candidates will lead to more effective treatments and a better understanding of the role of pharmacogenetics for COVID-19.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Daniel Barich", - "author_inst": "Kenyon College" - }, - { - "author_name": "Joan L Slonczewski", - "author_inst": "Kenyon College" + "author_name": "Ammar Ali Almarzooq", + "author_inst": "Galore Consultancy" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2021.01.09.21249499", @@ -1006899,125 +1006173,53 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2021.01.09.426032", - "rel_title": "Immunogenicity and efficacy of the COVID-19 candidate vector vaccine MVA SARS 2 S in preclinical vaccination", + "rel_doi": "10.1101/2021.01.11.426209", + "rel_title": "COVID-19 Severity Is Associated with Differential Antibody Fc-mediated Innate Immune Functions", "rel_date": "2021-01-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.09.426032", - "rel_abs": "The severe acute respiratory syndrome (SARS) coronavirus 2 (SARS-CoV-2) has emerged as the infectious agent causing the pandemic coronavirus disease 2019 (COVID-19) with dramatic consequences for global human health and economics. Previously, we reached clinical evaluation with our vector vaccine based on vaccinia virus MVA against the Middle East respiratory syndrome coronavirus (MERS-CoV), which causes an infection in humans similar to SARS and COVID-19. Here, we describe the construction and preclinical characterization of a recombinant MVA expressing full-length SARS-CoV-2 spike (S) protein (MVA-SARS-2-S). Genetic stability and growth characteristics of MVA-SARS-2-S, plus its robust synthesis of S antigen, make it a suitable candidate vaccine for industrial scale production. Vaccinated mice produced S antigen-specific CD8+ T cells and serum antibodies binding to S glycoprotein that neutralized SARS-CoV-2. Prime-boost vaccination with MVA-SARS-2-S protected mice sensitized with a human ACE2-expressing adenovirus from SARS-CoV-2 infection. MVA-SARS-2-S is currently being investigated in a phase I clinical trial as aspirant for developing a safe and efficacious vaccine against COVID-19.\n\nSignificance StatementThe highly attenuated vaccinia virus MVA is licensed as smallpox vaccine, and as vector it is a component of the approved Adenovirus-MVA-based prime-boost vaccine against Ebola virus disease. Here we provide results from testing the COVID-19 candidate vaccine MVA-SARS-2-S, a poxvirus-based vector vaccine that proceeded to clinical evaluation. When administered by intramuscular inoculation, MVA-SARS-2-S expresses and safely delivers the full-length SARS-CoV-2 spike (S) protein, inducing balanced SARS-CoV-2-specific cellular and humoral immunity, and protective efficacy in vaccinated mice. Substantial clinical experience has already been gained with MVA vectors using homologous and heterologous prime-boost applications, including the immunization of children and immunocompromised individuals. Thus, MVA-SARS-2-S represents an important resource for developing further optimized COVID-19 vaccines.", - "rel_num_authors": 28, + "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.11.426209", + "rel_abs": "Beyond neutralization, antibodies elicit several innate immune functions including complement deposition (ADCD), phagocytosis (ADCP), and cytotoxicity (ADCC). These functions can be both beneficial (by clearing pathogens) and/or detrimental (by inducing inflammation). We tested the possibility that qualitative differences in SARS-CoV-2 specific antibody-mediated innate immune functions contribute to Coronavirus disease 2019 (COVID-19) severity. We found that antibodies from hospitalized COVID-19 patients elicited higher ADCD but lower ADCP compared to antibodies from non-hospitalized COVID-19 patients. Consistently, higher ADCD was associated with higher systemic inflammation during COVID-19. Our study points to qualitative, differential features of anti-SARS-CoV-2 antibodies as potential contributors to COVID-19 severity.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Alina Tscherne", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" - }, - { - "author_name": "Jan Hendrik Schwarz", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" - }, - { - "author_name": "Cornelius Rohde", - "author_inst": "Institute of Virology, Philipps University Marburg, Marburg, Germany" - }, - { - "author_name": "Alexandra Kupke", - "author_inst": "Institute of Virology, Philipps University Marburg, Marburg, Germany" - }, - { - "author_name": "Georgia Kalodimou", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" - }, - { - "author_name": "Leonard Limpinsel", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" - }, - { - "author_name": "Nisreen M.A. Okba", - "author_inst": "Erasmus MC" - }, - { - "author_name": "Berislav Bosnjak", - "author_inst": "Institute of Immunology, Hannover Medical School, Hannover, Germany" - }, - { - "author_name": "Inga Sandrock", - "author_inst": "Institute of Immunology, Hannover Medical School, Hannover, Germany" - }, - { - "author_name": "Sandro Halwe", - "author_inst": "Institute of Virology, Philipps University Marburg, Marburg, Germany" - }, - { - "author_name": "Lucie Sauerhering", - "author_inst": "Institute of Virology, Philipps University Marburg, Marburg, Germany" - }, - { - "author_name": "Katrin Printz", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" - }, - { - "author_name": "Liangliang Nan", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" - }, - { - "author_name": "Elke Duell", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" - }, - { - "author_name": "Sylvia Jany", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" - }, - { - "author_name": "Astrid Freudenstein", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" - }, - { - "author_name": "Joerg Schmidt", - "author_inst": "Institute of Virology, Philipps University Marburg, Marburg, Germany" - }, - { - "author_name": "Anke Werner", - "author_inst": "Institute of Virology, Philipps University Marburg, Marburg, Germany" - }, - { - "author_name": "Michelle Gellhorn", - "author_inst": "Institute of Virology, Philipps University Marburg, Marburg, Germany" + "author_name": "Opeyemi S. Adeniji", + "author_inst": "The Wistar Institute" }, { - "author_name": "Michael Kluever", - "author_inst": "Institute of Virology, Philipps University Marburg, Marburg, Germany" + "author_name": "Leila B. Giron", + "author_inst": "The Wistar Institute" }, { - "author_name": "Wolfgang Guggemos", - "author_inst": "Munich Clinic Schwabing, Academic Teaching Hospital, LMU Munich, Munich, Germany" + "author_name": "Netanel F Zilberstein", + "author_inst": "Rush University" }, { - "author_name": "Michael Seilmaier", - "author_inst": "Munich Clinic Schwabing, Academic Teaching Hospital, LMU Munich, Munich, Germany" + "author_name": "Maliha W Shaikh", + "author_inst": "Ruch University" }, { - "author_name": "Clemens Wendtner", - "author_inst": "Munich Clinic Schwabing, Academic Teaching Hospital, LMU Munich, Munich, Germany" + "author_name": "Robert A Balk", + "author_inst": "Rush University" }, { - "author_name": "Reinhold Foerster", - "author_inst": "Institute of Immunology, Hannover Medical School, Hannover, Germany" + "author_name": "James N Moy", + "author_inst": "Rush University" }, { - "author_name": "Bart Haagmans", - "author_inst": "Erasmus Medical Center" + "author_name": "Christopher B Forsyth", + "author_inst": "Rush University" }, { - "author_name": "Stephan Becker", - "author_inst": "Institute of Virology, Philipps University Marburg, Marburg, Germany" + "author_name": "Ali Keshavarzian", + "author_inst": "Rush University" }, { - "author_name": "Gerd Sutter", - "author_inst": "Division of Virology, Department of Veterinary Sciences, LMU Munich, Munich, Germany" + "author_name": "Alan L Landay", + "author_inst": "Rush University" }, { - "author_name": "Asisa Volz", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Mohamed Abdel-Mohsen", + "author_inst": "The Wistar Institute" } ], "version": "1", @@ -1009137,39 +1008339,159 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2021.01.06.21249349", - "rel_title": "Identifying silent COVID-19 infections among children is critical for controlling the pandemic", + "rel_doi": "10.1101/2021.01.06.21249352", + "rel_title": "OpenSAFELY NHS Service Restoration Observatory 1: describing trends and variation in primary care clinical activity for 23.3 million patients in England during the first wave of COVID-19", "rel_date": "2021-01-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.06.21249349", - "rel_abs": "ImportanceA significant proportion of COVID-19 transmission occurs silently during the pre-symptomatic and asymptomatic stages of infection. Children, while being important drivers of silent transmission, are not included in the current COVID-19 vaccination campaigns.\n\nObjectiveTo investigate the benefits of identifying silent infections among children as a proxy for their vaccination.\n\nDesignThis study used an age-structured disease transmission model, parameterized with census data and estimates from published literature, to simulate the synergistic effect of interventions in reducing attack rates over the course of one year.\n\nSettingA synthetic population representative of the United States (US) demographics.\n\nParticipantsSix age groups of 0-4, 5-10, 11-18, 19-49, 50-64, 65+ years based on US census data.\n\nInterventionsIn addition to the isolation of symptomatic cases within 24 hours of symptom onset, vaccination of adults was implemented to reach a 40%-60% coverage over the course of one year with an efficacy of 95% against symptomatic and severe COVID-19.\n\nMain Outcomes and MeasuresThe combinations of proportion and speed for detecting silent infections among children which would suppress future attack rates below 5%.\n\nResultsIn the base-case scenarios with an effective reproduction number Re = 1.2, a targeted approach that identifies 11% and 14% of silent infections among children within 2 or 3 days post-infection, respectively, would bring attack rates under 5% with 40% vaccination coverage of adults. If silent infections among children remained undetected, achieving the same attack rates would require an unrealistically high vaccination coverage (at least 81%) of this age group, in addition to 40% vaccination coverage of adults. The effect of identifying silent infections was robust in sensitivity analyses with respect to vaccine efficacy against infection and reduced susceptibility of children to infection.\n\nConclusions and RelevanceIn this simulation modeling study of a synthetic US population, in the absence of vaccine availability for children, a targeted approach to rapidly identify silent COVID-19 infections in this age group was estimated to significantly mitigate disease burden. Without measures to interrupt transmission chains from silent infections, vaccination of adults is unlikely to contain the outbreaks in the near term.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat is the effect of a targeted strategy for identification of silent COVID-19 infections among children in the absence of their vaccination?\n\nFindingsIn this simulation modeling study, it was found that identifying 10-20% of silent infections among children within three days post-infection would bring attack rates below 5% if only adults were vaccinated. If silent infections among children remained undetected, achieving the same attack rate would require an unrealistically high vaccination coverage (over 80%) of this age group, in addition to vaccination of adults.\n\nMeaningRapid identification of silent infections among children can achieve comparable effects as would their vaccination.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.06.21249352", + "rel_abs": "BackgroundThe COVID-19 pandemic has disrupted healthcare activity globally. The NHS in England stopped most non-urgent work by March 2020, but later recommended that services should be restored to near-normal levels before winter where possible. The authors are developing the OpenSAFELY NHS Service Restoration Observatory, using data to describe changes in service activity during COVID-19, and reviewing signals for action with commissioners, researchers and clinicians. Here we report phase one: generating, managing, and describing the data.\n\nObjectiveTo describe the volume and variation of coded clinical activity in English primary care across 23.8 million patients records, taking respiratory disease and laboratory procedures as key examples.\n\nMethodsWorking on behalf of NHS England we developed an open source software framework for data management and analysis to describe trends and variation in clinical activity across primary care EHR data on 23.8 million patients; and conducted a population cohort-based study to describe activity using CTV3 coding hierarchy and keyword searches from January 2019-September 2020.\n\nResultsMuch activity recorded in general practice declined to some extent during the pandemic, but largely recovered by September 2020, with some exceptions. There was a large drop in coded activity for commonly used laboratory tests, with broad recovery to pre-pandemic levels by September. One exception was blood coagulation tests such as International Normalised Ratio (INR), with a smaller reduction (median tests per 1000 patients in 2020: February 8.0; April 6.2; September 7.0). The overall pattern of recording for respiratory symptoms was less affected, following an expected seasonal pattern and classified as \"no change\" from the previous year. Respiratory tract infections exhibited a sustained drop compared with pre-pandemic levels, not returning to pre-pandemic levels by September 2020. Various COVID-19 codes increased through the period. We observed a small decline associated with high level codes for long-term respiratory conditions such as chronic obstructive pulmonary disease (COPD) and asthma. Asthma annual reviews experienced a small drop but since recovered, while COPD annual reviews remain below baseline.\n\nConclusionsWe successfully delivered an open source software framework to describe trends and variation in clinical activity across an unprecedented scale of primary care data. The COVD-19 pandemic led to a substantial change in healthcare activity. Most laboratory tests showed substantial reduction, largely recovering to near-normal levels by September 2020, with some important tests less affected. Records of respiratory infections decreased with the exception of codes related to COVID-19, whilst activity of other respiratory disease codes was mixed. We are expanding the NHS Service Restoration Observatory in collaboration with clinicians, commissioners and researchers and welcome feedback.", + "rel_num_authors": 35, "rel_authors": [ { - "author_name": "Seyed M. Moghadas", - "author_inst": "York University" + "author_name": "Helen J Curtis", + "author_inst": "University of Oxford" }, { - "author_name": "Meagan C. Fitzpatrick", - "author_inst": "University of Maryland" + "author_name": "Brian MacKenna", + "author_inst": "University of Oxford" }, { - "author_name": "Affan Shoukat", - "author_inst": "Yale University" + "author_name": "Richard Croker", + "author_inst": "University of Oxford" }, { - "author_name": "Kevin Zhang", - "author_inst": "University of Toronto" + "author_name": "Alex J Walker", + "author_inst": "University of Oxford" }, { - "author_name": "Alison P. Galvani", - "author_inst": "Yale University" + "author_name": "Peter Inglesby", + "author_inst": "University of Oxford" + }, + { + "author_name": "Jessica Morley", + "author_inst": "University of Oxford" + }, + { + "author_name": "Amir Mehrkar", + "author_inst": "University of Oxford" + }, + { + "author_name": "Caroline E Morton", + "author_inst": "University of Oxford" + }, + { + "author_name": "Seb Bacon", + "author_inst": "University of Oxford" + }, + { + "author_name": "George Hickman", + "author_inst": "University of Oxford" + }, + { + "author_name": "Chris Bates", + "author_inst": "TPP" + }, + { + "author_name": "David Evans", + "author_inst": "University of Oxford" + }, + { + "author_name": "Tom Ward", + "author_inst": "University of Oxford" + }, + { + "author_name": "Jonathan Cockburn", + "author_inst": "TPP" + }, + { + "author_name": "Simon Davy", + "author_inst": "University of Oxford" + }, + { + "author_name": "Krishnan T. Bhaskaran", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Anna Schultze", + "author_inst": "LSHTM" + }, + { + "author_name": "Christopher T. Rentsch", + "author_inst": "US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Elizabeth J Williamson", + "author_inst": "LSHTM" + }, + { + "author_name": "Will Hulme", + "author_inst": "University of Oxford" + }, + { + "author_name": "Helen I McDonald", + "author_inst": "London School of Medicine and Tropical Medicine" + }, + { + "author_name": "Laurie Tomlinson", + "author_inst": "LSHTM" + }, + { + "author_name": "Kevin Wing", + "author_inst": "LSHTM" + }, + { + "author_name": "Rohini I Mathur", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Harriet Forbes", + "author_inst": "LSHTM" + }, + { + "author_name": "Angel Wong", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Rosalind M Eggo", + "author_inst": "LSHTM" + }, + { + "author_name": "Henry Drysdale", + "author_inst": "University of Oxford" + }, + { + "author_name": "John Parry", + "author_inst": "TPP" + }, + { + "author_name": "Frank Hester", + "author_inst": "TPP" + }, + { + "author_name": "Sam Harper", + "author_inst": "TPP" + }, + { + "author_name": "Ian J Douglas", + "author_inst": "LSHTM" + }, + { + "author_name": "Stephen Evans", + "author_inst": "LSHTM" + }, + { + "author_name": "Liam Smeeth", + "author_inst": "LSHTM" + }, + { + "author_name": "Ben Goldacre", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2021.01.06.21249345", @@ -1010686,127 +1010008,39 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2021.01.08.425915", - "rel_title": "Ad26.COV2.S-elicited immunity protects against G614 spike variant SARS-CoV-2 infection in Syrian hamsters and does not enhance respiratory disease in challenged animals with breakthrough infection after sub-optimal vaccine dosing", + "rel_doi": "10.1101/2021.01.08.21249439", + "rel_title": "Inflight Transmission of COVID-19 Based on Aerosol Dispersion Data", "rel_date": "2021-01-08", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2021.01.08.425915", - "rel_abs": "Previously we have shown that a single dose of recombinant adenovirus serotype 26 (Ad26) vaccine expressing a prefusion stabilized SARS-CoV-2 spike antigen (Ad26.COV2.S) is immunogenic and provides protection in Syrian hamster and non-human primate SARS-CoV-2 infection models. Here, we investigated the immunogenicity, protective efficacy and potential for vaccine-associated enhanced respiratory disease (VAERD) mediated by Ad26.COV2.S in a moderate disease Syrian hamster challenge model, using the currently most prevalent G614 spike SARS-CoV-2 variant. Vaccine doses of 1x109 vp and 1x1010 vp elicited substantial neutralizing antibodies titers and completely protected over 80% of SARS-CoV-2 inoculated Syrian hamsters from lung infection and pneumonia but not upper respiratory tract infection. A second vaccine dose further increased neutralizing antibody titers which was associated with decreased infectious viral load in the upper respiratory tract after SARS-CoV-2 challenge. Suboptimal non-protective immune responses elicited by low-dose A26.COV2.S vaccination did not exacerbate respiratory disease in SARS-CoV-2-inoculated Syrian hamsters with breakthrough infection. In addition, dosing down the vaccine allowed to establish that binding and neutralizing antibody titers correlate with lower respiratory tract protection probability. Overall, these pre-clinical data confirm efficacy of a 1-dose vaccine regimen with Ad26.COV2.S in this G614 spike SARS-CoV-2 virus variant Syrian hamster model, show the added benefit of a second vaccine dose, and demonstrate that there are no signs of VAERD under conditions of suboptimal immunity.", - "rel_num_authors": 27, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.08.21249439", + "rel_abs": "BackgroundAn issue of concern to the travelling public is the possibility of in-flight transmission of COVID-19 during long- and short-haul flights. The aviation industry maintain the probability of contracting the illness is small based on reported cases, modelling and data from aerosol dispersion experiments conducted on-board aircraft.\n\nMethodsUsing experimentally derived aerosol dispersion data for a B777-200 aircraft and a modified version of the Wells-Riley equation we estimate inflight infection probability for a range of scenarios involving quanta generation rate and face mask efficiency. Quanta generation rates were selected based on COVID-19 events reported in the literature while mask efficiency was determined from the aerosol dispersion experiments.\n\nResultsThe MID-AFT cabin exhibits the highest infection probability. The calculated maximum individual infection probability (without masks) for a 2-hour flight in this section varies from 4.5% for the \"Mild Scenario\" to 60.2% for the \"Severe Scenario\" although the corresponding average infection probability varies from 0.1% to 2.5%. For a 12-hour flight, the corresponding maximum individual infection probability varies from 24.1% to 99.6% and the average infection probability varies from 0.8% to 10.8%. If all passengers wear face masks throughout the 12-hour flight, the average infection probability can be reduced by approximately 73%/32% for high/low efficiency masks. If face masks are worn by all passengers except during a one-hour meal service, the average infection probability is increased by 59%/8% compared to the situation where the mask is not removed.\n\nConclusionsThis analysis has demonstrated that while there is a significant reduction in aerosol concentration due to the nature of the cabin ventilation and filtration system, this does not necessarily mean that there is a low probability or risk of in-flight infection. However, mask wearing, particularly high-efficiency ones, significantly reduces this risk.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Joan E.M. van der Lubbe", - "author_inst": "Janssen Vaccines & Prevention" - }, - { - "author_name": "Sietske K. Rosendahl Huber", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Aneesh Vijayan", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Liesbeth Dekking", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Ella van Huizen", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Jessica Vreugdenhil", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Ying Choi", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Miranda R.M. Baert", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Karin Feddes-de Boer", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Ana Izquierdo Gil", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Marjolein van Heerden", - "author_inst": "Janssen Non-Clinical Safety B.V., Beerse, Belgium" - }, - { - "author_name": "Tim J. Dalebout", - "author_inst": "Molecular Virology Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands" - }, - { - "author_name": "Sebenzile K. Myeni", - "author_inst": "Molecular Virology Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands" - }, - { - "author_name": "Marjolein Kikkert", - "author_inst": "Molecular Virology Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands" - }, - { - "author_name": "Eric J. Snijder", - "author_inst": "Molecular Virology Laboratory, Department of Medical Microbiology, Leiden University Medical Center, Leiden, The Netherlands" - }, - { - "author_name": "Leon de Waal", - "author_inst": "Viroclinics Biosciences B.V., Viroclinics Xplore, Schaijk, The Netherlands" - }, - { - "author_name": "Koert J. Stittelaar", - "author_inst": "Wageningen Bioveterinary Research, Lelystad, The Netherlands" - }, - { - "author_name": "Jeroen T.B.M. Tolboom", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Jan Serroyen", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Leacky Muchene", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Leslie van der Fits", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Lucy Rutten", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" - }, - { - "author_name": "Johannes P.M. Langedijk", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" + "author_name": "Zhaozhi Wang", + "author_inst": "University of Greenwich" }, { - "author_name": "Dan H. Barouch", - "author_inst": "Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA" + "author_name": "Edwin R Galea", + "author_inst": "University of Greenwich" }, { - "author_name": "Hanneke Schuitemaker", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" + "author_name": "Angus J Grandison", + "author_inst": "University of Greenwich" }, { - "author_name": "Roland C. Zahn", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" + "author_name": "John Ewer", + "author_inst": "University of Greenwich" }, { - "author_name": "Frank Wegmann", - "author_inst": "Janssen Vaccines & Prevention B.V., Leiden, The Netherlands" + "author_name": "Fuchen Jia", + "author_inst": "University of Greenwich" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "immunology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2021.01.05.20248921", @@ -1012476,59 +1011710,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.05.21249131", - "rel_title": "Ivermectin shows clinical benefits in mild to moderate Covid19 disease: A randomised controlled double blind dose response study in Lagos.", + "rel_doi": "10.1101/2021.01.05.21249293", + "rel_title": "Modelling Decay of Population Immunity With Proposed Second Dose Deferral Strategy", "rel_date": "2021-01-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.05.21249131", - "rel_abs": "IntroductionIn vitro studies have shown the efficacy of Ivermectin (IV) to inhibit the SARS - CoV-2 viral replication, but questions remained as to In-vivo applications. We set out to explore the efficacy and safety of Ivermectin in persons infected with COVID19.\n\nMethodsWe conducted a translational proof of concept (PoC) randomized, double blind placebo controlled, dose response, parallel group study of IV efficacy in RT - PCR proven COVID 19 positive patients. 62 patients were randomized to 3 treatment groups. (A) IV 6mg regime, (B)IV 12 mg regime (given Q84hrs for 2weeks) (C, control) Lopinavir/Ritonavir. All groups plus standard of Care.\n\nResultsThe Days to COVID negativity [DTN] was significantly and dose dependently reduced by IV (p = 0.0066). The DTN for Control were, = 9.1+/-5.2, for A 6.0 +/- 2.9, and for B 4.6 +/-3.2. 2 Way repeated measures ANOVA of ranked COVID 19 + / - scores at 0, 84, 168, 232 hours showed a significant IV treatment effect (p=0.035) and time effect (p <0.0001). IV also tended to increase SPO2 % compared to controls, p = 0.073, 95% CI - 0.39 to 2.59 and increased platelet count compared to C (p = 0.037) 95%CI 5.55 - 162.55 x 103/ml. The platelet count increase was inversely correlated to DTN (r = -0.52, p = 0.005). No SAE was reported.\n\nConclusions12 mg IV regime may have superior efficacy. IV should be considered for use in clinical management of SARS-Cov-2, and may find applications in community prophylaxis in high-risk areas.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.05.21249293", + "rel_abs": "A second dose deferred strategy has been proposed to increase initial population immunity as an alternative to the default two dose vaccine regimen with spacing of 21 or 28 days between vaccine doses for the mRNA vaccines from Pfizer and Moderna. This increased initial population immunity is only of value if one dose immunity does not decay so fast as to nullify the benefit. Because decay rates of one dose and two dose efficacy are currently unknown, a model to project population immunity between the two strategies was created. By evaluating the decay rate of one dose efficacy, two dose efficacy, and time until the second dose is given, the model shows that if there is an increased decay rate of one dose efficacy relative to the two dose decay rate, it is highly unlikely to nullify the benefit of increased population immunity seen in a second dose deferral strategy. Rather, all reasonable scenarios strongly favour a second dose deferral strategy with much higher projected population immunity in comparison to the default regimen.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Olufemi Emmanuel Babalola", - "author_inst": "Department of Ophthalmology, Bingham University, Karu-Jos, Nigeria" - }, - { - "author_name": "Christopher Olusanjo Bode", - "author_inst": "Department of Surgery,Faculty of Clinical Sciences, College of Medicine & Lagos University Teaching Hospital, Lagos, Nigeria" - }, - { - "author_name": "Adesuyi Adeyinka Ajayi", - "author_inst": "Division of Hypertension and Clinical pharmacology, Keck Department of Medicine, Baylor College of Medicine Texas, USA" - }, - { - "author_name": "Felix M Alakaloko", - "author_inst": "Department of Surgery, Lagos University Teaching Hospital, Lagos, Nigeria" - }, - { - "author_name": "Iorhen Ephraim Akase", - "author_inst": "Department of Medicine, Lagos University Teaching Hospital" - }, - { - "author_name": "Erere Otrofanowei", - "author_inst": "Department of Medicine, Faculty of Clinical Sciences, College of Medicine/ Lagos University Teaching Hospital" - }, - { - "author_name": "Olumuyiwa Babalola Salu", - "author_inst": "Centre for Human and Zoonotic Virology, Central Research Laboratory/Department of Medical Microbiology and Parasitology, College of Medicine, University of Lago" - }, - { - "author_name": "Wasiu Lanre Adeyemo", - "author_inst": "Department of Oral and Maxillofacial Surgery, College of Medicine, University of Lagos" - }, - { - "author_name": "Adesoji O Ademuyiwa", - "author_inst": "Department of Surgery, Faculty of Clinical Sciences, College of Medicine & Lagos University Teaching Hospital, Lagos, Nigeria" - }, - { - "author_name": "Sunday A Omilabu", - "author_inst": "Centre for Human and Zoonotic Virology, Central Research Laboratory/Department of Medical Microbiology and Parasitology, College of Medicine, University of Lago" + "author_name": "Graham T Jurgens", + "author_inst": "Unaffiliated" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "allergy and immunology" }, { "rel_doi": "10.1101/2021.01.05.20249027", @@ -1013946,55 +1013144,127 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2021.01.03.21249175", - "rel_title": "Modelling COVID -19 Transmission in a Hemodialysis Centre Using Simulation Generated Contacts Matrices", + "rel_doi": "10.1101/2021.01.04.21249227", + "rel_title": "Antithrombotic Therapy in COVID-19: Systematic Summary of Ongoing or Completed Randomized Trials", "rel_date": "2021-01-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.03.21249175", - "rel_abs": "The COVID-19 pandemic has been particularly threatening to the patients with end-stage kidney disease (ESKD) on intermittent hemodialysis and their care providers. Hemodialysis patients who receive life-sustaining medical therapy in healthcare settings, face unique challenges as they need to be at a dialysis unit three or more times a week, where they are confined to specific settings and tended to by dialysis nurses and staff with physical interaction and in close proximity. Despite the importance and critical situation of the dialysis units, modelling studies of the SARS-CoV-2 spread in these settings are very limited. In this paper, we have used a combination of discrete event and agent-based simulation models, to study the operations of a typical large dialysis unit and generate contact matrices to examine outbreak scenarios. We present the details of the contact matrix generation process and demonstrate how the simulation calculates a micro-scale contact matrix comprising the number and duration of contacts at a micro-scale time step. We have used the contacts matrix in an agent-based model to predict disease transmission under different scenarios. The results show that micro-simulation can be used to estimate contact matrices, which can be used effectively for disease modelling in dialysis and similar settings.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.04.21249227", + "rel_abs": "Endothelial injury and microvascular/macrovascular thrombosis are common pathophysiologic features of coronavirus disease-2019 (COVID-19). However, the optimal thromboprophylactic regimens remain unknown across the spectrum of illness severity of COVID-19. A variety of antithrombotic agents, doses and durations of therapy are being assessed in ongoing randomized controlled trials (RCTs) that focus on outpatients, hospitalized patients in medical wards, and critically-ill patients with COVID-19. This manuscript provides a perspective of the ongoing or completed RCTs related to antithrombotic strategies used in COVID-19, the opportunities and challenges for the clinical trial enterprise, and areas of existing knowledge, as well as data gaps that may motivate the design of future RCTs.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Mohammadali Tofighi", - "author_inst": "York University (ADERSIM) and Ale-Taha Institute of Higher Education" + "author_name": "Azita H. Talasaz", + "author_inst": "Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran" }, { - "author_name": "Ali Asgary", - "author_inst": "York University (ADERSIM)" + "author_name": "Parham Sadeghipour", + "author_inst": "Cardiovascular Intervention Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Asad A. Merchant", - "author_inst": "University Health Network (UHN)" + "author_name": "Hessam Kakavand", + "author_inst": "Department of Clinical Pharmacy, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Mohammad Ali Shafiee", - "author_inst": "University Health Network (UHN)" + "author_name": "Maryam Aghakouchakzadeh", + "author_inst": "Department of Clinical Pharmacy, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Mahdi M. Najafabadi", - "author_inst": "York University (ADERSIM)" + "author_name": "Benjamin W Van Tassell", + "author_inst": "Department of Pharmacotherapy and Outcome Science, School of Pharmacy, Virginia Commonwealth University, Richmond, VA, USA." }, { - "author_name": "Nazanin Nadri", - "author_inst": "York University (ADERSIM)" + "author_name": "Elahe Kordzadeh-Kermani", + "author_inst": "Department of Clinical Pharmacy, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Mehdi Aarabi", - "author_inst": "University Health Network (UHN)" + "author_name": "Azin Gheymati", + "author_inst": "Department of Clinical Pharmacy, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Jane Heffernan", - "author_inst": "York University" + "author_name": "Hamid Ariannrjad", + "author_inst": "Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran." }, { - "author_name": "Jianhong Wu", - "author_inst": "York University" + "author_name": "Seyed Hossein Hosseini", + "author_inst": "Department of Clinical Pharmacy, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran." + }, + { + "author_name": "Sepehr Jamalkhani", + "author_inst": "Cardiovascular Intervention Research Center, Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran." + }, + { + "author_name": "Michelle Sholzberg", + "author_inst": "Departments of Medicine and Laboratory Medicine & Pathobiology, University of Toronto, Toronto, Canada." + }, + { + "author_name": "Manuel Monreal", + "author_inst": "Department of Internal Medicine, Hospital Universitari Germans Trials i Pujol, Universidad Catolica San Antonio de Murcia, Barcelona, Spain." + }, + { + "author_name": "David Jimenez", + "author_inst": "Respiratory Department, Hospital Ramon y Cajal and Medicine Department, Universidad de Alcala (Instituto de Ramon y Cajal de Investigacion Sanitaria), Centro de" + }, + { + "author_name": "Gregory Piazza", + "author_inst": "Cardiovascular Medicine Division, Brigham and Women Hospital, Harvard Medical School, Boston, MA, USA." + }, + { + "author_name": "Sahil A Parikh", + "author_inst": "Clinical Trials Center, Cardiovascular Research Foundation, New York, NY, USA." + }, + { + "author_name": "Ajay J Kirtane", + "author_inst": "Clinical Trials Center, Cardiovascular Research Foundation, New York, NY, USA." + }, + { + "author_name": "John W Eikelboom", + "author_inst": "Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, Ontario, Canada." + }, + { + "author_name": "Jean M Connors", + "author_inst": "Hematology Division, Department of Medicine, Brigham and Women Hospital, Harvard Medical School, Boston, MA." + }, + { + "author_name": "Beverley J Hunt", + "author_inst": "Haemostasis and Thrombosis Centre, St Thomas' Hospital, Westminster Bridge Road, London, United Kingdom." + }, + { + "author_name": "Stavros V Konstantinides", + "author_inst": "Center for Thrombosis and Hemostasis, Johannes Gutenberg University of Mainz, Mainz, Germany." + }, + { + "author_name": "Mary Cushman", + "author_inst": "Department of Medicine, University of Vermont Larner College of Medicine and University of Vermont Medical Center, Burlington, VT, USA." + }, + { + "author_name": "Jeffrey I Weitz", + "author_inst": "McMaster University, Hamilton, Ontario, Canada." + }, + { + "author_name": "Gregg Stone", + "author_inst": "Zena and Michael A. Wiener Cardiovascular Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA." + }, + { + "author_name": "Harlan Krumholz", + "author_inst": "Yale University" + }, + { + "author_name": "Gregory Y.H. Lip", + "author_inst": "Liverpool Centre for Cardiovascular Science, Liverpool Heart and Chest Hospital, University of Liverpool, Liverpool, United Kingdom." + }, + { + "author_name": "Samuel Z Goldhaber", + "author_inst": "Cardiovascular Medicine Division, Brigham and Women Hospital, Harvard Medical School, Boston, MA, USA." + }, + { + "author_name": "Behnood Bikdeli", + "author_inst": "Cardiovascular Medicine Division, Brigham and Women Hospital, Harvard Medical School, Boston, MA, USA." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2021.01.05.425384", @@ -1015292,33 +1014562,29 @@ "category": "hematology" }, { - "rel_doi": "10.1101/2020.12.29.20248975", - "rel_title": "COVID-19: Can early home treatment with Azithromycin alone or with Zinc help prevent hospitalisation, death, and long-COVID-19? A review", + "rel_doi": "10.1101/2020.12.28.20248967", + "rel_title": "Postlockdown Dynamics of COVID-19 in New York, Florida, Arizona, and Wisconsin", "rel_date": "2021-01-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.29.20248975", - "rel_abs": "IntroductionThe effects of the SARS-CoV-2 pandemic continues to disrupt health systems worldwide, leading to population lockdowns in many countries. Preventing hospitalisation, death and long-COVID-19 with repurposed drugs remains a priority. Hydroxychloroquine (HCQ) and azithromycin (AZM) are the most commonly used in ambulatory care, with divergent results. With the aim of decentralizing early treatment to family practitioners, we addressed the question: Can early home treatment with AZM alone or with zinc help prevent hospitalisation, death, and long-COVID-19?\n\nMethodologyWe conducted a scoping review of articles published from 31st December 2019 to 5th November 2020 in Pubmed, Google Scholar, MedRxiv, and BioRxiv databases, and a review of undergoing clinical trials published in the Clinicaltrial.gov database.\n\nResultsMany studies report on outpatient treatment with a combination of AZM + HCQ versus AZM alone, and few studies propose the addition of Zinc (Zn) to AZM. In addition, we identified 5 clinical trials currently recruiting individuals for early outpatient treatment with AZM. However, we failed in identifying any study or clinical trial conducted with family practitioners responding to our question.\n\nDiscussionThe antiviral, anti-inflammatory, immunomodulatory benefits of AZM + Zn make this drugs combination a good candidate therapy to treat flu-like-COVID-19 and atypical pneumoniae. The antibacterial action of AZM can also help disrupting the bacteria/virus cooperation that is poorly documented. Considering pros and cons of macrolide use (including antimicrobial resistance), we call for early use of this therapy by family practitioners for home treatment of individuals presenting mild or moderate symptoms under rigorous scientific guidance to prevent hospitalisation, death and long-COVID.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.28.20248967", + "rel_abs": "The COVID-19 pandemic is widely studied as it continues to threaten many populations of people especially in the USA, the leading country in terms of both deaths and cases. Although vaccines are being distributed, control and mitigation strategies must still be properly enforced. More and more reports show that the spread of COVID-19 involves infected individuals first passing through a pre-symptomatic infectious stage in addition to the incubation period and that many of the infectious individuals are asymptomatic. In this study, we design and use a mathematical model to primarily address the question of who are the main drivers of COVID-19 - the symptomatic infectious or the pre-symptomatic and asymptomatic infectious in the states of Florida, Arizona, New York, Wisconsin and the entire United States. We emphasize the benefit of lockdown by showing that for all four states, earlier and later lockdown dates decrease the number of cumulative deaths. This benefit of lockdown is also evidenced by the decrease in the infectious cases for Arizona and the entire US when lockdown is implemented earlier. When comparing the influence of the symptomatic infectious versus the pre-sympomatic/asymptomatic infectious, it is shown that, in general, the larger contribution comes from the latter group. This is seen from several perspectives, as follows: (1) in terms of daily cases, (2) in terms of daily cases when the influence of one group is targeted over the other by setting the effective contact rate(s) for the non-targeted group to zero, and (3) in terms of cumulative cases and deaths for the US and Arizona when the influence of one group is targeted over the other by setting the effective contact rate(s) for the non-targeted group to zero. The consequences of the difference in the contributions of the two infectious groups is simulated in terms of testing and these simulations show that an increase in testing and isolating for the pre-symptomatic and asymptomatic infectious group has more impact than an increase in testing for the symptomatic infectious. For example, for the entire US, a 50% increase in testing for the pre-symptomatic and asymptomatic infectious group results in a 25% decrease in deaths as opposed to a lower 6% decrease in deaths when a 50% increase in testing rate for the symptomatic infectious is implemented. We also see that if the testing for infectious symptomatic is kept at the baseline value and the testing for the pre-symptomatic and asymptomatic is increased from 0.2 to 0.25, then the control reproduction number falls below 1. On the other hand, to get even close to such a result when keeping the pre-symptomatic and asymptomatic at baseline fitted values, the symptomatic infectious testing rate must be increased considerably more - from 0.4 to 1.7. Lastly, we use our model to simulate an implementation of a natural herd immunity strategy for the entire U.S. and for the state of Wisconsin (the most recent epicenter) and we find that such a strategy requires a significant number of deaths and as such is questionable in terms of success. We conclude with a brief summary of our results and some implications regarding COVID-19 control and mitigation strategies.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Philippe LEPERE", - "author_inst": "University of Geneva" - }, - { - "author_name": "Bruno Escarguel", - "author_inst": "Saint Joseph Hospital, Marseille, France" + "author_name": "Shery Scott", + "author_inst": "ADJOINT at MSRI" }, { - "author_name": "Selda Yolartiran", - "author_inst": "Saint Joseph Hospital, Marseille, France" + "author_name": "Keisha Cook", + "author_inst": "Tulane University" }, { - "author_name": "Claude Escarguel", - "author_inst": "Association Biologie et Cooperation, France" + "author_name": "Kamal Barley", + "author_inst": "Stonybrook University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1016806,25 +1016072,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.30.20248908", - "rel_title": "Unsupervised Discovery of Risk Profiles on Negative and Positive COVID-19 Hospitalized Patients", + "rel_doi": "10.1101/2020.12.29.20248990", + "rel_title": "Identical trends of SARS-Cov-2 transmission and retail and transit mobility during non-lockdown periods", "rel_date": "2021-01-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.30.20248908", - "rel_abs": "COVID-19 is a viral disease that affects people in different ways: Most people will develop mild symptoms; others will require hospitalization, and a few others will die. Hence identifying risk factors is vital to assist physicians in the treatment decision. The objective of this paper is to determine whether unsupervised analysis of risk factors of positive and negative COVID-19 subjects may be useful for the discovery of a small set of reliable and clinically relevant risk-profiles. We selected 13367 positive and 19958 negative hospitalized patients from the Mexican Open Registry. Registry patients were described by 13 risk factors, three different outcomes, and COVID-19 test results. Hence, the dataset could be described by 6144 different risk-profiles per age group. To discover the most common risk-profiles, we propose the use of unsupervised learning. The data was split into discovery (70%) and validation (30%) sets. The discovery set was analyzed using the partition around medoids (PAM) method and robust consensus clustering was used to estimate the stable set of risk-profiles. We validated the reliability of the PAM models by predicting the risk-profile of the validation set subjects. The clinical relevance of the risk-profiles was evaluated on the validation set by characterizing the prevalence of the three patient outcomes: pneumonia diagnosis, ICU, or death. The analysis discovered six positives and five negative COVID-19 risk-profiles with strong statistical differences among them. Henceforth PAM clustering with consensus mapping is a viable method for unsupervised risk-profile discovery among subjects with critical respiratory health issues.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.29.20248990", + "rel_abs": "Recent literature strongly supports the idea that mobility reduction and social distancing play a crucial role in transmission of SARS-Cov-2 infections. It was shown during the first wave that mobility restrictions reduce significantly infection transmission. Here we document the reverse relationship by showing, between the first two Covid-19 waves, a high positive correlation between the trends of SARS-Cov-2 transmission and mobility. These two trends oscillate simultaneously and increased mobility following lockdown relaxation has a significant positive relationship with increased transmission. From a public health perspective, these results highlight the importance of following the evolution of mobility when relaxing mitigation measures to anticipate the future evolution of the spread of the SARS-Cov-2.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Fahimeh Nezhadmoghadam", - "author_inst": "Tec de Monterrey" + "author_name": "Bernard Cazelles", + "author_inst": "Sorbonne University" + }, + { + "author_name": "Catherine Comiskey", + "author_inst": "Trinity College Dublin, The University of Dublin" + }, + { + "author_name": "Benjamin Nguyen Van Yen", + "author_inst": "Ecole Normale Superieure" + }, + { + "author_name": "Clara Champagne", + "author_inst": "Swiss Tropical and Public Health Institute, Universty of Basel" }, { - "author_name": "Jose Tamez-Pena", - "author_inst": "Tec de Monterrey" + "author_name": "Benjamin Roche", + "author_inst": "IRD" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1018140,55 +1017418,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2021.01.03.20248715", - "rel_title": "Humoral and cell-mediated response in colostrum after exposure to severe acute respiratory syndrome coronavirus 2", + "rel_doi": "10.1101/2021.01.03.21249170", + "rel_title": "Nested pool testing strategy for the reliable identification of individuals infected with SARS-CoV-2", "rel_date": "2021-01-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.03.20248715", - "rel_abs": "BackgroundColostrum provides an immune sharing between a mother and her infant. The transfer in colostrum of antibodies against SARS-CoV-2 and the elicited cytokines may provide crucial protection to the infant. There is limited literature on the immune response to SARS-CoV-2 present in colostrum.\n\nObjectiveTo evaluate the presence of antibodies specific to SARS-CoV-2 and the associated cytokines in colostrum from women who tested positive for the virus.\n\nStudy DesignBetween March and September 2020 we obtained bilateral colostrum samples collected on spot cards within 48 hours of delivery from 15 new mothers who had previously tested positive for SARS-CoV-2. Five of these 15 COVID-19 positive women also provided bilateral liquid colostrum within 1-2 days of providing the spot card samples. Archived bilateral colostrum samples collected from 8 women during 2011-2013 were used as pre-COVID-19 controls. All samples were tested for reactivity to the Receptor Binding Domain (RBD) of the SARS-CoV-2 spike protein using an ELISA that measures SARS-CoV-2 RBD-specific IgA, IgG, and IgM, and for concentrations of 10 inflammatory cytokines (IFN{gamma}, TNF, IL-1{beta}, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12, IL-13) using a multiplex electrochemiluminescent sandwich assay.\n\nResultsBilateral colostrum samples from 73%, 73% and 33% of the 15 COVID-19 mothers exhibited IgA, IgG, and IgM reactivity to RBD respectively. Colostrum samples from two of the 8 pre-pandemic controls showed IgA and IgG reactivity to RBD. Additionally, COVID-19 mothers had significantly higher levels of 9 of the 10 inflammatory markers (all except IFN{gamma}) as compared to the pre-COVID-19 controls. Comparable results were obtained with both the spot card-eluates and liquid samples.\n\nConclusionsA strong humoral immune response is present in the colostrum of women who were infected with SARS-CoV-2 before delivering. High levels of 9 inflammatory markers were also present in the colostrum. The evolution and duration of the antibody response, as well as dynamics of the cytokine response, remain to be determined. Our results also indicate that future large-scale studies can be conducted with milk easily collected on paper spot cards.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2021.01.03.21249170", + "rel_abs": "The progress of the SARS-CoV-2 pandemic requires the design of cost-effective testing programs at large scale. To this end, pooling multiple samples can provide a solution. Defining a cost-effective strategy requires the establishment of an efficient deconvolution and re-testing procedure that eventually allows the identifcation of the carrier. Based on Dorfmans algorithm, we developed an adaptive nested strategy for which we have, for a given prevalence, simple analytic expressions of the optimal number of samples in the starting pool, of the number of partitioning steps (stages) in the optimal path, of the pool sizes in each of these stages and of the expected average number of tests needed to identify the infected individuals. In this paper we analyze the strategy in detail focusing on its practical implementation when there are restrictions that prevent the use of the optimum. More specifically, we analyze how to proceed when the infection prevalence is poorly known a priori or when the optimal requires starting with pool sizes that are too large for the reliable detection of an infected sample. The sensitivity of the RT-qPCR assay, the gold standard RNA detection method, is a major concern in the case of SARS-CoV-2: it is estimated that half of the infected individuals give false negative results. Recently, droplet digital PCR (ddPCR) was shown to be 10 - 100 times more sensitive than RT-qPCR, making this technology suitable for pool testing. ddPCR has the added value of providing the direct quantification of the RNA content at the end of the test. In the paper we show how this feature can be used for verification purposes. The analyses and strategies presented here should be useful to those considering the adoption of a pooling approach for RNA detection, particularly, for the identification of individuals infected with SARS-CoV-2.\n\nAuthor summaryThe progress of the SARS-CoV-2 pandemic requires the design of cost-effective testing programs at large scale. Running tests on pooled samples can provide a solution if the tests sensitivity is high enough. In the case of SARS-CoV-2, the current gold standard test, RT-qPCR, has shown some limitations that only allow the use of pools with relatively few samples. In this regard, Droplet digital PCR (ddPCR) has been shown to be 10 - 100 times more sensitive than RT-qPCR, making it suitable for test pooling. In this paper we describe a nested pool testing method in which the properties that make it optimal are simple analytic functions of the infection prevalence. We discuss how to proceed in practical implementations of the strategy, particularly when there are constraints that prevent the use of the optimal. We also show how its nested nature can be combined with the direct RNA quantification that the ddPCR test provides to identify the presence of unviable samples in the pools and for self-consistency tests. The studies of this paper should be useful for those considering the adoption of test pooling for RNA detection.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Vignesh Narayanaswamy", - "author_inst": "University of Massachusetts Amherst" - }, - { - "author_name": "Brian Pentecost", - "author_inst": "University of Massachusetts Amherst" - }, - { - "author_name": "Dominique Alfandari", - "author_inst": "University of Massachusetts Amherst" - }, - { - "author_name": "Emily Chin", - "author_inst": "University of Massachusetts Medical School Worcester" + "author_name": "Ines Armendariz", + "author_inst": "Universidad de Buenos Aires & CONICET" }, { - "author_name": "Kathleen Minor", - "author_inst": "University of Massachusetts Medical School Worcester" + "author_name": "Pablo A Ferrari", + "author_inst": "Universidad de Buenos Aires & CONICET" }, { - "author_name": "Alyssa Kastrinakis", - "author_inst": "University of Massachusetts Medical School Worcester" + "author_name": "Daniel Fraiman", + "author_inst": "Universidad de San Andres & CONICET" }, { - "author_name": "Tanya Lieberman", - "author_inst": "University of Massachusetts Amherst" + "author_name": "Jose Mario Martinez", + "author_inst": "Universidad Estadual de Campinas" }, { - "author_name": "Kathleen F Arcaro", - "author_inst": "University of Massachusetts Amherst" + "author_name": "Hugo G Menzella", + "author_inst": "Universidad Nacional de Rosario & CONICET" }, { - "author_name": "Heidi Leftwich", - "author_inst": "University of Massachusetts Medical School Worcester" + "author_name": "Silvina Ponce Dawson", + "author_inst": "Universidad de Buenos Aires & CONICET" } ], "version": "1", "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "category": "health informatics" }, { "rel_doi": "10.1101/2021.01.02.20248998", @@ -1020066,37 +1019332,69 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.27.20248896", - "rel_title": "Vaccination and Non-Pharmaceutical Interventions: when can the UK relax about COVID-19?", + "rel_doi": "10.1101/2020.12.26.20248855", + "rel_title": "Quantitative plasma proteomics of survivor and non-survivor COVID-19 patients admitted to hospital unravels potential prognostic biomarkers and therapeutic targets", "rel_date": "2021-01-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.27.20248896", - "rel_abs": "BackgroundThe announcement of efficacious vaccine candidates against SARS-CoV-2 has been met with worldwide acclaim and relief. Many countries already have detailed plans for vaccine targeting based on minimising severe illness, death and healthcare burdens. Normally, relatively simple relationships between epidemiological parameters, vaccine efficacy and vaccine uptake predict the success of any immunisation programme. However, the dynamics of vaccination against SARS-CoV-2 is made more complex by age-dependent factors, changing levels of infection and the potential relaxation of non-pharmaceutical interventions (NPIs) as the perceived risk declines.\n\nMethodsIn this study we use an age-structured mathematical model, matched to a range of epidemiological data in the UK, that also captures the roll-out of a two-dose vaccination programme targeted at specific age groups.\n\nFindingsWe consider the interaction between the UK vaccination programme and future relaxation (or removal) of NPIs. Our predictions highlight the population-level risks of early relaxation leading to a pronounced wave of infection, hospital admissions and deaths. Only vaccines that offer high infection-blocking efficacy with high uptake in the general population allow relaxation of NPIs without a huge surge in deaths.\n\nInterpretationWhile the novel vaccines against SARS-CoV-2 offer a potential exit strategy for this outbreak, this is highly contingent on the infection-blocking (or transmission-blocking) action of the vaccine and the population uptake, both of which need to be carefully monitored as vaccine programmes are rolled out in the UK and other countries.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSVaccination has been seen as a key tool in the fight against SARS-CoV-2. The vaccines already developed represent a major technological achievement and have been shown to generate significant immune responses, as well as offering considerable protection against disease. However, to date there is limited information on the degree of infection-blocking these vaccines are likely to induce. Mathematical models have already successfully been used to consider age- and risk-structured targeting of vaccination, highlighting the importance of prioritising older and high-risk individuals.\n\nAdded value of this studyTranslating current knowledge and uncertainty of vaccine behaviour into meaningful public health messages requires models that fully capture the within-country epidemiology as well as the complex roll-out of a two-dose vaccination programme. We show that under reasonable assumptions for vaccine efficacy and uptake the UK is unlikely to reach herd immunity, which means that non-pharmaceutical interventions cannot be released without generating substantial waves of infection.\n\nImplications of all the available evidenceVaccination is likely to provide substantial individual protection to those receiving two doses, but the degree of protection to the wider population is still uncertain. While substantial immunisation of the most vulnerable groups will allow for some relaxation of controls, this must be done gradually to prevent large scale public health consequences.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.26.20248855", + "rel_abs": "The development of new approaches that allow early assessment of which cases of COVID-19 will likely become critical and the discovery of new therapeutic targets are urgent demands. In this cohort study, we performed proteomic and laboratorial profiling of plasma from 163 patients admitted to Bauru State Hospital (Bauru, SP, Brazil) between May 4th and July 4th, 2020, who were diagnosed with COVID-19 by RT-PCR nasopharyngeal swab samples. Plasma samples were collected upon admission for routine laboratory analyses and shotgun quantitative label-free proteomics. Based on the course of the disease, the patients were further divided into 3 groups: a) mild symptoms, discharged without admission to an intensive care unit (ICU) (n=76); b) severe symptoms, discharged after admission to an ICU (n=56); c) critical, died after admission to an ICU (n=31). White cells and neutrophils were significantly higher in severe and critical patients compared to mild ones. Lymphocytes were significantly lower in critical patients compared to mild ones and platelets were significantly lower in critical patients compared to mild and severe ones. Ferritin, TGO, urea and creatinine were significantly higher in critical patients compared to mild and severe ones. Albumin, CPK, LDH and D-dimer were significantly higher in severe and critical patients compared to mild ones. PCR was significantly higher in severe patients compared to mild ones. Proteomic analysis revealed marked changes between the groups in plasma proteins related to complement activation, blood coagulation, antimicrobial humoral response, acute inflammatory response, and endopeptidase inhibitor activity. Higher levels of IREB2, GELS, POLR3D, PON1 and ULBP6 upon admission to hospital were found in patients with mild symptoms, while higher levels of Gal-10 were found in critical and severe patients. This needs to be validated in further studies. If confirmed, pathways involving these proteins might be potential new therapeutic targets for COVID-19.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Sam Moore", - "author_inst": "University of Warwick" + "author_name": "Daniele Castro di Flora", + "author_inst": "University of Sao Paulo and Bauru State Hospital" }, { - "author_name": "Edward M Hill", - "author_inst": "University of Warwick" + "author_name": "Aline Dionizio Valle", + "author_inst": "University of Sao Paulo" }, { - "author_name": "Michael Tildesley", - "author_inst": "University of Warwick" + "author_name": "Heloisa Aparecida Barbosa da Silva Pereira", + "author_inst": "University of Sao Paulo" }, { - "author_name": "Louise M Dyson", - "author_inst": "University of Warwick" + "author_name": "Thais Francini Garbieri", + "author_inst": "University of Sao Paulo" }, { - "author_name": "Matt J Keeling", - "author_inst": "University of Warwick" + "author_name": "Nathalia Rabelo Buzalaf", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Fernanda Navas Reis", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Larissa Tercilia Grizzo", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Thiago Jose Dionisio", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Aline de Lima Leite", + "author_inst": "University of Nebraska-Lincoln" + }, + { + "author_name": "Virginia Bodelao Richini Pereira", + "author_inst": "Adolfo Lutz Institute" + }, + { + "author_name": "Deborah Maciel Cavalcanti Rosa", + "author_inst": "Bauru State Hospital" + }, + { + "author_name": "Carlos Ferreira dos Santos", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Marilia Afonso Rabelo Buzalaf", + "author_inst": "Bauru School of Dentistry, University of Sao Paulo" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1021408,41 +1020706,93 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.24.20248814", - "rel_title": "S gene dropout patterns in SARS-CoV-2 tests suggest spread of the H69del/V70del mutation in the US.", + "rel_doi": "10.1101/2020.12.23.20245316", + "rel_title": "Smoking and SARS-CoV-2 Impair Dendritic Cells and Regulate DC-SIGN Expression in Tissues", "rel_date": "2020-12-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.24.20248814", - "rel_abs": "Recently, multiple novel strains of SARS-CoV-2 have been found to share the same deletion of amino acids H69 and V70 in the virus S gene. This includes strain B.1.1.7 / SARS-CoV-2 VUI 202012/01, which has been found to be more infectious than other strains of SARS-CoV-2, and its increasing presence has resulted in new lockdowns in and travel restrictions leaving the UK. Here, we analyze 2 million RT-PCR SARS-CoV-2 tests performed at Helix to identify the rate of S gene dropout, which has been recently shown to occur in tests from individuals infected with strains of SARS-CoV-2 that carry the H69del/V70del mutation. We observe a rise in S gene dropout in the US starting in early October, with 0.25% of our daily SARS-CoV-2-positive tests exhibiting this pattern during the first week. The rate of positive samples with S gene dropout has grown slowly over time, with last week exhibiting the highest level yet, at 0.5%. Focusing on the 14 states for which we have sufficient sample size to assess the frequency of this rare event (n>1000 SARS-CoV-2-positive samples), we see a recent expansion in the Eastern part of the US, concentrated in MA, OH, and FL. However, we cannot say from these data whether the S gene dropout samples we observe here represent the B.1.1.7. strain. Only with an expansion of genomic surveillance sequencing in the US will we know for certain the prevalence of the B.1.1.7 strain in the US.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20245316", + "rel_abs": "The current spreading novel coronavirus SARS-CoV-2 is highly infectious and pathogenic. In this study, we screened the gene expression of three SARS-CoV-2 host receptors (ACE2, DC-SIGN and L-SIGN) and DC status in bulk and single cell transcriptomic datasets of upper airway, lung or blood of smokers, non-smokers and COVID-19 patients. We found smoking increased DC-SIGN gene expression and inhibited DC maturation and its ability of T cell stimulation. In COVID-19, DC-SIGN gene expression was interestingly decreased in lung DCs but increased in blood DCs. Strikingly, DCs shifted from cDCs to pDCs in COVID-19, but the shift was trapped in an immature stage (CD22+ or ANXA1+ DC) with MHCII downregulation in severe cases. This observation indicates that DCs in severe cases stimulate innate immune responses but fail to specifically recognize SARS-CoV-2. Our study provides insights into smoking effect on COVID-19 risk and the profound modulation of DC function in severe COVID-19.\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=139 SRC=\"FIGDIR/small/20245316v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (59K):\norg.highwire.dtl.DTLVardef@11a509borg.highwire.dtl.DTLVardef@a1faeforg.highwire.dtl.DTLVardef@619bb4org.highwire.dtl.DTLVardef@357bf5_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsSmoking upregulates the expression of ACE2 and CD209 and inhibits DC maturation in lungs. SARS-CoV-2 modulates the DCs proportion and CD209 expression differently in lung and blood.\n\nSevere infection is characterized by DCs less capable of maturation, antigen presentation and MHCII expression.\n\nDCs shift from cDCs to pDCs with SARS-CoV-2 infection but are trapped in an immature stage in severe cases.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Nicole L Washington", - "author_inst": "Helix" + "author_name": "Guoshuai Cai", + "author_inst": "University of South Carolina" }, { - "author_name": "Simon White", - "author_inst": "Helix" + "author_name": "Yohan Boss\u00e9", + "author_inst": "Laval University" }, { - "author_name": "Kelly m Schiabor Barrett", - "author_inst": "Helix" + "author_name": "Mulong Du", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Elizabeth T Cirulli", - "author_inst": "Helix" + "author_name": "Helmut Albrecht", + "author_inst": "Prisma Health Medical Group" }, { - "author_name": "Alexandre Bolze", - "author_inst": "Helix" + "author_name": "Fei Qin", + "author_inst": "Arnold School of Public Health, University of South Carolina" }, { - "author_name": "James T Lu", - "author_inst": "Helix" + "author_name": "Xuanxuan Yu", + "author_inst": "Arnold School of Public Health, University of South Carolina" + }, + { + "author_name": "Xizhi Luo", + "author_inst": "Arnold School of Public Health, University of South Carolina" + }, + { + "author_name": "Michelle Androulakis", + "author_inst": "Columbia VA Health System" + }, + { + "author_name": "Xia Zhu", + "author_inst": "Arnold School of Public Health, University of South Carolina" + }, + { + "author_name": "Jun Zhou", + "author_inst": "Arnold School of Public Health, University of South Carolina" + }, + { + "author_name": "Xiang Cui", + "author_inst": "Arnold School of Public Health, University of South Carolina" + }, + { + "author_name": "Changhua Yi", + "author_inst": "the Second Hospital of Nanjing, Southeast University" + }, + { + "author_name": "Chao Cheng", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Mitz Nagarkatti", + "author_inst": "School of Medicine, University of South Carolina" + }, + { + "author_name": "Prakash Nagarkatti", + "author_inst": "School of Medicine, University of South Carolina" + }, + { + "author_name": "David Christiani", + "author_inst": "Harvard T.H. Chan School of Public Health" + }, + { + "author_name": "Michael Whitfield", + "author_inst": "Geisel School of Medicine at Dartmouth" + }, + { + "author_name": "Christopher Amos", + "author_inst": "Baylor College of Medicine" + }, + { + "author_name": "Feifei Xiao", + "author_inst": "Arnold School of Public Health, University of South Carolina" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1023088,93 +1022438,89 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2020.12.28.424554", - "rel_title": "Human neutralizing antibodies against SARS-CoV-2 require intact Fc effector functions and monocytes for optimal therapeutic protection", + "rel_doi": "10.1101/2020.12.28.424451", + "rel_title": "SARS-CoV-2 escape in vitro from a highly neutralizing COVID-19 convalescent plasma", "rel_date": "2020-12-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.28.424554", - "rel_abs": "SARS-CoV-2 has caused the global COVID-19 pandemic. Although passively delivered neutralizing antibodies against SARS-CoV-2 show promise in clinical trials, their mechanism of action in vivo is incompletely understood. Here, we define correlates of protection of neutralizing human monoclonal antibodies (mAbs) in SARS-CoV-2-infected animals. Whereas Fc effector functions are dispensable when representative neutralizing mAbs are administered as prophylaxis, they are required for optimal protection as therapy. When given after infection, intact mAbs reduce SARS-CoV-2 burden and lung disease in mice and hamsters better than loss-of-function Fc variant mAbs. Fc engagement of neutralizing antibodies mitigates inflammation and improves respiratory mechanics, and transcriptional profiling suggests these phenotypes are associated with diminished innate immune signaling and preserved tissue repair. Immune cell depletions establish that neutralizing mAbs require monocytes for therapeutic efficacy. Thus, potently neutralizing mAbs require Fc effector functions for maximal therapeutic benefit during therapy to modulate protective immune responses and mitigate lung disease.", - "rel_num_authors": 19, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.28.424451", + "rel_abs": "To investigate the evolution of SARS-CoV-2 in the immune population, we co-incubated authentic virus with a highly neutralizing plasma from a COVID-19 convalescent patient. The plasma fully neutralized the virus for 7 passages, but after 45 days, the deletion of F140 in the spike N-terminal domain (NTD) N3 loop led to partial breakthrough. At day 73, an E484K substitution in the receptor-binding domain (RBD) occurred, followed at day 80 by an insertion in the NTD N5 loop containing a new glycan sequon, which generated a variant completely resistant to plasma neutralization. Computational modeling predicts that the deletion and insertion in loops N3 and N5 prevent binding of neutralizing antibodies. The recent emergence in the United Kingdom and South Africa of natural variants with similar changes suggests that SARS-CoV-2 has the potential to escape an effective immune response and that vaccines and antibodies able to control emerging variants should be developed.\n\nOne Sentence SummaryThree mutations allowed SARS-CoV-2 to evade the polyclonal antibody response of a highly neutralizing COVID-19 convalescent plasma.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Emma S. Winkler", - "author_inst": "Washington University" - }, - { - "author_name": "Pavlo Gilchuk", - "author_inst": "Vanderbilt University" + "author_name": "Emanuele Andreano", + "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences" }, { - "author_name": "Jinsheng Yu", - "author_inst": "Washington University" + "author_name": "Giulia Piccini", + "author_inst": "VisMederi S.r.l, Siena, Italy" }, { - "author_name": "Adam L. Bailey", - "author_inst": "Washington University" + "author_name": "Danilo Licastro", + "author_inst": "ARGO Open Lab Platform for Genome sequencing, AREA Science Park, Padriciano, 99, 34149, Trieste, Italy" }, { - "author_name": "Rita E. Chen", - "author_inst": "Washington University" + "author_name": "Lorenzo Casalino", + "author_inst": "Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093, USA" }, { - "author_name": "Seth J. Zost", - "author_inst": "Vanderbilt University" + "author_name": "Nicole V. Johnson", + "author_inst": "Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA" }, { - "author_name": "Hyesun Jang", - "author_inst": "University of Georgia" + "author_name": "Ida Paciello", + "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences" }, { - "author_name": "Ying Huang", - "author_inst": "University of Georgia" + "author_name": "Simeone Dal Monego", + "author_inst": "ARGO Open Lab Platform for Genome sequencing, AREA Science Park, Padriciano, 99, 34149, Trieste, Italy" }, { - "author_name": "James D. Allen", - "author_inst": "University of Georgia" + "author_name": "Elisa Pantano", + "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences" }, { - "author_name": "James Brett Case", - "author_inst": "Washington University" + "author_name": "Noemi Manganaro", + "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences" }, { - "author_name": "Rachel E. Sutton", - "author_inst": "Vanderbilt University" + "author_name": "Alessandro Manenti", + "author_inst": "VisMederi S.r.l, Siena, Italy; VisMederi Research S.r.l., Siena, Italy" }, { - "author_name": "Robert H. Carnahan", - "author_inst": "Vanderbilt University" + "author_name": "Rachele Manna", + "author_inst": "VisMederi S.r.l, Siena, Italy" }, { - "author_name": "Tamarand L. Darling", - "author_inst": "Washington University" + "author_name": "Elisa Casa", + "author_inst": "VisMederi S.r.l, Siena, Italy; VisMederi Research S.r.l., Siena, Italy" }, { - "author_name": "Adrianus C. M. Boon", - "author_inst": "Washington University" + "author_name": "Inesa Hyseni", + "author_inst": "VisMederi S.r.l, Siena, Italy; VisMederi Research S.r.l., Siena, Italy" }, { - "author_name": "Matthias Mack", - "author_inst": "University Hospital Regensburg" + "author_name": "Linda Benincasa", + "author_inst": "VisMederi Research S.r.l., Siena, Italy" }, { - "author_name": "Richard D. Head", - "author_inst": "Washington University" + "author_name": "Emanuele Montomoli", + "author_inst": "VisMederi S.r.l, Siena, Italy; VisMederi Research S.r.l., Siena, Italy; Department of Molecular and Developmental Medicine, University of Siena, Siena, Italy" }, { - "author_name": "Ted M. Ross", - "author_inst": "University of Georgia" + "author_name": "Rommie E. Amaro", + "author_inst": "Department of Chemistry and Biochemistry, University of California San Diego, La Jolla, CA 92093, USA" }, { - "author_name": "James E. Crowe Jr.", - "author_inst": "Vanderbilt University" + "author_name": "Jason S McLellan", + "author_inst": "Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA" }, { - "author_name": "Michael Diamond", - "author_inst": "Washington University" + "author_name": "Rino Rappuoli", + "author_inst": "Monoclonal Antibody Discovery (MAD) Lab, Fondazione Toscana Life Sciences; Faculty of Medicine, Imperial College, London, United Kingdom" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -1024870,23 +1024216,75 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.12.23.424283", - "rel_title": "The SARS-CoV-2 S1 spike protein mutation N501Y alters the protein interactions with both hACE2 and human derived antibody: A Free energy of perturbation study", + "rel_doi": "10.1101/2020.12.23.424172", + "rel_title": "Pulmonary stromal expansion and intra-alveolar coagulation are primary causes of Covid-19 death", "rel_date": "2020-12-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.23.424283", - "rel_abs": "The N501Y and K417N mutations in spike protein of SARS-CoV-2 and their combination arise questions but the data about their mechanism of action at molecular level is limited. Here, we present Free energy perturbation (FEP) calculations for the interactions of the spike S1 receptor binding domain (RBD) with both the ACE2 receptor and an antibody derived from COVID-19 patients. Our results shown that the S1 RBD-ACE2 interactions were significantly increased whereas those with the STE90-C11 antibody dramatically decreased; about over 100 times. The K417N mutation had much more pronounced effect and in a combination with N501Y fully abolished the antibody effect. This may explain the observed in UK and South Africa more spread of the virus but also raise an important question about the possible human immune response and the success of already available vaccines.", - "rel_num_authors": 1, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.23.424172", + "rel_abs": "Most Covid-19 victims are old and die from unrelated causes. Here we present twelve complete autopsies, including two rapid autopsies of young patients where the cause of death was Covid-19 ARDS. The main virus induced pathology was in the lung parenchyma and not in the airways. Most coagulation events occurred in the intra-alveolar and not in the intra-vascular space and the few thrombi were mainly composed of aggregated thrombocytes. The dominant inflammatory response was the massive accumulation of CD163+ macrophages and the disappearance of T killer, NK and B-cells. The virus was replicating in the pneumocytes and macrophages but not in bronchial epithelium, endothel, pericytes or stromal cells. The lung consolidations were produced by a massive regenerative response, stromal and epithelial proliferation and neovascularization. We suggest that thrombocyte aggregation inhibition, angiogenesis inhibition and general proliferation inhibition may have a roll in the treatment of advanced Covid-19 ARDS.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Filip Fratev", - "author_inst": "Micar Innovation (Micar21)" + "author_name": "Laszlo Szekely", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Bela Bozoky", + "author_inst": "Karolinska University Hospital" + }, + { + "author_name": "Matyas Bendek", + "author_inst": "Karolinska University Hospital" + }, + { + "author_name": "Masih Ostad", + "author_inst": "Karolinska University Hospital" + }, + { + "author_name": "Pablo Lavignasse", + "author_inst": "Karolinska University Hospital" + }, + { + "author_name": "Lars Haag", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Jieyu Wu", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Xu Jing", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Soham Gupta", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Elisa Saccon", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Anders Sonnerborg", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Yihai Cao", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Mikael Bjornstedt", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Attila Szakos", + "author_inst": "Karolinska University Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "molecular biology" + "category": "pathology" }, { "rel_doi": "10.1101/2020.12.18.20248498", @@ -1026716,39 +1026114,91 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2020.12.17.20248360", - "rel_title": "Identifying communities at risk for COVID-19-related burden across 500 U.S. Cities and within New York City", + "rel_doi": "10.1101/2020.12.23.20248514", + "rel_title": "Risk factors for community transmission of SARS-CoV-2. A cross-sectional study in 116,678 people.", "rel_date": "2020-12-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.17.20248360", - "rel_abs": "BackgroundWhile it is well-known that older individuals with certain comorbidities are at highest risk for complications related to COVID-19 including hospitalization and death, we lack tools to identify communities at highest risk with fine-grained spatial and temporal resolution. Information collected at a county level obscures local risk and complex interactions between clinical comorbidities, the built environment, population factors, and other social determinants of health.\n\nMethodsWe develop a robust COVID-19 Community Risk Score (C-19 Risk Score) that summarizes the complex disease co-occurrences for individual census tracts with unsupervised learning, selected on their basis for association with risk for COVID complications, such as death. We mapped the C-19 Risk Score onto neighborhoods in New York City and associated the score with C-19 related death. We further predict the C-19 Risk Score using satellite imagery data to map the built environment in C-19 Risk.\n\nResultsThe C-19 Risk Score describes 85% of variation in co-occurrence of 15 diseases that are risk factors for COVID complications among 26K census tract neighborhoods (median population size of tracts: 4,091). The C-19 Risk Score is associated with a 40% greater risk for COVID-19 related death across NYC (April and September 2020) for a 1SD change in the score (Risk Ratio for 1SD change in C19 Risk Score: 1.4, p < .001). Satellite imagery coupled with social determinants of health explain nearly 90% of the variance in the C-19 Risk Score in the United States in held-out census tracts (R2 of 0.87).\n\nConclusionsThe C-19 Risk Score localizes COVID-19 risk at the census tract level and predicts COVID-19 related morbidity and mortality.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.23.20248514", + "rel_abs": "BackgroundThe risk factors for SARS-CoV-2 transmission are not well characterised in Western populations. We sought to identify potential risk factors for transmission and actionable information to prevent for SARS-CoV-2.\n\nMethodsIndividuals tested for SARS-CoV-2 at four major laboratories were invited. In addition, participants were sampled by convenience after a media campaign. Self-reported test results were compared with laboratory results, demographic data and behavioural facts were collected using a digital platform. In a cross-sectional design positive cases were compared with negative and untested control groups.\n\nFindingsApproximately 14 days after a countrywide lockdown in Norway, 116,678 participants were included. Median age was 46 years, 44% had children in preschool or in school; 18% were practicing health professionals. International flights, contact with infected, and gatherings of more than 50 people, were associated with high risk. Health professionals who used public transport were at higher risk of testing positive than those who did not. Having undergone light infections, the last six months was strongly associated with lower odds ratio of SARS-CoV-2 positivity. Contact with children, use of hand sanitiser and use of protective gloves in private were also associated with lower odds ratio of testing positive for SARS-CoV-2.\n\nInterpretationFurther research is needed to explore if being a parent or looking after children is associated with lower risk of SARS-CoV-2 positivity in the next phases of the pandemic. Immunological research should be done to determine the effects of prior trivial infections on SARS-CoV-2 infection. We confirm that large gatherings during the pandemic should be avoided and those who are infected, or under suspicion thereof, posed very high risks to others this population.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Chirag J Patel", - "author_inst": "XY Health, Inc" + "author_name": "Eyrun F Kjetland", + "author_inst": "Oslo University Hospital" + }, + { + "author_name": "Karl Trygve Kalleberg", + "author_inst": "Age Labs AS" + }, + { + "author_name": "Camilla Lund Soraas", + "author_inst": "Oslo University Hospital" + }, + { + "author_name": "Bato Hammarstrom", + "author_inst": "Oslo University Hospital" + }, + { + "author_name": "Tor Age Myklebust", + "author_inst": "Cancer Registry of Norway" + }, + { + "author_name": "Synne Jenum", + "author_inst": "Oslo University Hospital" + }, + { + "author_name": "Eyvind Axelsen", + "author_inst": "Furst Medical Laboratory" + }, + { + "author_name": "Andreas Lind", + "author_inst": "Oslo University Hospital" + }, + { + "author_name": "Roar Bevre-Jensen", + "author_inst": "Vestre Viken Hospital Trust" + }, + { + "author_name": "Silje Bakken Jorgensen", + "author_inst": "Akershus University Hospital" + }, + { + "author_name": "Frank Olav Pettersen", + "author_inst": "Oslo University Hospital" + }, + { + "author_name": "Lene B Solberg", + "author_inst": "Oslo University Hospital" + }, + { + "author_name": "Cathrine Lund Hadley", + "author_inst": "Age Labs AS" }, { - "author_name": "Andrew Deonarine", - "author_inst": "XY.Health, Inc" + "author_name": "Mette Stausland Istre", + "author_inst": "Oslo University Hospital" }, { - "author_name": "Genevieve Lyons", - "author_inst": "XY.Health, Inc" + "author_name": "Knut Liestol", + "author_inst": "University of Oslo" }, { - "author_name": "Chirag Lakhani", - "author_inst": "XY.Health, Inc." + "author_name": "John Arne Dahl", + "author_inst": "Oslo University Hospital" }, { - "author_name": "Arjun K Manrai", - "author_inst": "XY.Health, Inc." + "author_name": "Giske Ursin", + "author_inst": "Cancer Registry of Norway" + }, + { + "author_name": "Arne Soraas", + "author_inst": "Oslo University Hospital" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.12.23.20248795", @@ -1028325,81 +1027775,41 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.12.23.424232", - "rel_title": "Remdesivir-Ivermectin combination displays synergistic interaction with improved in vitro antiviral activity against SARS-CoV-2", - "rel_date": "2020-12-24", + "rel_doi": "10.1101/2020.12.23.424169", + "rel_title": "SARS-CoV-2 sensing by RIG-I and MDA5 links epithelial infection to macrophage inflammation", + "rel_date": "2020-12-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.23.424232", - "rel_abs": "A key element for the prevention and management of COVID-19 is the development of effective therapeutics. Drug combination strategies of repurposed drugs offer several advantages over monotherapies, including the potential to achieve greater efficacy, the potential to increase the therapeutic index of drugs and the potential to reduce the emergence of drug resistance. Here, we report on the in vitro synergistic interaction between two FDA approved drugs, remdesivir and ivermectin resulting in enhanced antiviral activity against SARS-CoV-2. These findings warrant further investigations into the clinical potential of this combination, together with studies to define the underlying mechanism.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.23.424169", + "rel_abs": "SARS-CoV-2 infection causes broad-spectrum immunopathological disease, exacerbated by inflammatory co-morbidities. A better understanding of mechanisms underpinning virus-associated inflammation is required to develop effective therapeutics. Here we discover that SARS-CoV-2 replicates rapidly in lung epithelial cells despite triggering a robust innate immune response through activation of cytoplasmic RNA-ensors RIG-I and MDA5. The inflammatory mediators produced during epithelial cell infection can stimulate primary human macrophages to enhance cytokine production and drive cellular activation. Critically, this can be limited by abrogating RNA sensing, or by inhibiting downstream signalling pathways. SARS-CoV-2 further exacerbates the local inflammatory environment when macrophages or epithelial cells are primed with exogenous inflammatory stimuli. We propose that RNA sensing of SARS-CoV-2 in lung epithelium is a key driver of inflammation, the extent of which is influenced by the inflammatory state of the local environment, and that specific inhibition of innate immune pathways may beneficially mitigate inflammation-associated COVID-19.\n\nHighlightsO_LISARS-CoV-2 activates RNA sensors and consequent inflammatory responses in lung epithelial cells\nC_LIO_LIEpithelial RNA sensing responses drive pro-inflammatory macrophage activation\nC_LIO_LIExogenous inflammatory stimuli exacerbate responses to SARS-CoV-2 in both eplithelial cells and macrophages\nC_LIO_LIImmunomodulators inhibit RNA sensing responses and consequent macrophage inflammation\nC_LI\n\nGraphical Abstract\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC=\"FIGDIR/small/424169v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (65K):\norg.highwire.dtl.DTLVardef@b07adborg.highwire.dtl.DTLVardef@51ddf7org.highwire.dtl.DTLVardef@c38f9aorg.highwire.dtl.DTLVardef@108db57_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Laura Jeffreys", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Shaun H Pennington", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Jack Duggan", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Claire H Caygill", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Rose C Lopeman", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Alastair Breen", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Jessica Jinks", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Alison Ardrey", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Samantha Donnellan", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Edward I Patterson", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Grant I Hughes", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Lucy G Thorne", + "author_inst": "University College London" }, { - "author_name": "W. David Hong", - "author_inst": "University of Liverpool" + "author_name": "Ann-Kathrin Reuschl", + "author_inst": "University College London" }, { - "author_name": "Ghaith Aljayyoussi", - "author_inst": "Liverpool School of tropical Medicine" + "author_name": "Lorena Zuliani-Alvarez", + "author_inst": "University College London" }, { - "author_name": "Andrew Owen", - "author_inst": "University of Liverpool" + "author_name": "Mahdad Noursadeghi", + "author_inst": "University College London" }, { - "author_name": "Steve A Ward", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Clare Jolly", + "author_inst": "University College London" }, { - "author_name": "Giancarlo A Biagini", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Greg J Towers", + "author_inst": "University College London" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -1030195,59 +1029605,47 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.12.16.423122", - "rel_title": "Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning", + "rel_doi": "10.1101/2020.12.22.20248696", + "rel_title": "A comparative analysis of COVID-19 mortality rate across the globe: An extensive analysis of the associated factors", "rel_date": "2020-12-22", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.16.423122", - "rel_abs": "Individuals with systemic symptoms long after COVID-19 has cleared represent approximately ~10% of all COVID-19 infected individuals. Here we present a bioinformatics approach to predict and model the phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 144 individuals including normal individuals and patients spanning the COVID-19 disease continuum. We collected plasma and isolated PBMCs from 29 normal individuals, 26 individuals with mild-moderate COVID-19, 25 individuals with severe COVID-19, and 64 individuals with Chronic COVID-19 symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients. Data was analyzed using machine learning methods to predict and distinguish the groups from each other.Using a multi-class deep neural network classifier to better fit our prediction model, we recapitulated a 100% precision, 100% recall and F1 score of 1 on the test set. Moreover, a first score specific for the chronic COVID-19 patients was defined as S1 = (IFN-{gamma} + IL-2)/ CCL4-MIP-1{beta}. Second, a score specific for the severe COVID-19 patients was defined as S2 = (10*IL-10 + IL-6) - (IL-2 + IL-8). Severe cases are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While chronic patients are characterized by a profile able to induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus but without the proper recruitment signals to attract activated T cells.\n\nSummaryImmunologic Modeling of Severity and Chronicity of COVID-19", - "rel_num_authors": 10, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.22.20248696", + "rel_abs": "BackgroundThe vast variation in COVID 19 mortality across the globe draws attention to potential risk factors other than the patient characteristics that determine COVID-19 mortality.\n\nSubjects and MethodsWe have quantified and analyzed one of the broadest set of clinical factors associated with COVID-19-related death, ranging from disease related co-morbities, socioeconomic factors, healthcare capacity and government policy and interventions. Data for population, total cases, total COVID mortality, tests done, and GDP per capita were extracted from the worldometers database. Datasets for health expenditure by government, hospital beds, rural population, prevalence of smoking, prevalence of overweight population, deaths due to communicable disease and incidence of malaria were extracted from the World Bank website. Prevalence of diabetes was retrieved from the indexmundi rankings. The average population age, 60+ population, delay in lockdown, population density and BCG data were also included for analysis. The COVID-19 mortality per million and its associated factors were retrieved for 56 countries across the globe. Quantitative analysis was done at the global as well as continent level. All the countries included in the study were categorized continent and region wise for comparative analysis determining the correlation between COVID 19 mortality and the aforementioned factors.\n\nResultsThere was significant association found between mortality per million and 60+ population of country, average age, prevalence of diabetes mellitus, and case fatality rate with correlation and p value (p) of 0.422 (p 0.009), 0.386 (p 0.0186), -0.384 (p 0.019) and 0.753 (p 0.000) respectively at 95% CI.\n\nConclusionThe study observations will serve as a evidence based management strategy for generating predictive model for COVID-19 infection and mortality rate.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Bruce Patterson", - "author_inst": "IncellDx" - }, - { - "author_name": "Jose Guevara-Coto", - "author_inst": "Universidad de Costa Rica" - }, - { - "author_name": "Ram Yogendra", - "author_inst": "ECA Wellness" - }, - { - "author_name": "Edgar B. Francisco", - "author_inst": "IncellDx, Inc" + "author_name": "Vineet Jain", + "author_inst": "Department of Medicine, Hamdard Institute of Medical Sciences & Research (HIMSR), New Delhi, India" }, { - "author_name": "emily long", - "author_inst": "incelldx, Inc" + "author_name": ", Nusrat Nabi", + "author_inst": "Department of Pharmacology, HIMSR" }, { - "author_name": "Amruta Pise", - "author_inst": "IncellDx, Inc" + "author_name": "Kailash Chandra", + "author_inst": "Hamdard Institute of Medical Sciences and Research" }, { - "author_name": "Hallison Rodrigues", - "author_inst": "IncellDx, Inc" + "author_name": "Sana Irshad", + "author_inst": "epartment of Medicine, Hamdard Institute of Medical Sciences & Research (HIMSR), New Delhi, India." }, { - "author_name": "Purvi Parikh", - "author_inst": "NYU" + "author_name": "Varun kashyap", + "author_inst": "Department of community medicine, HIMSR, New Delhi" }, { - "author_name": "Javier Mora", - "author_inst": "Universidad de Costa Rica" + "author_name": "Sunil Kohli", + "author_inst": "Department of Medicine, Hamdard Institute of Medical Sciences & Research (HIMSR), New Delhi, India," }, { - "author_name": "Rodrigo A. Mora-Rodriguez", - "author_inst": "Universidad de Costa Rica" + "author_name": "Arun Gupta", + "author_inst": "Head Medical Affairs and clinical Research, Dabur Research and development center" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "public and global health" }, { "rel_doi": "10.1101/2020.12.22.20248693", @@ -1031729,39 +1031127,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.20.20248581", - "rel_title": "Early empirical assessment of the N501Y mutant strains of SARS-CoV-2 in the United Kingdom, October to November 2020", + "rel_doi": "10.1101/2020.12.21.20248153", + "rel_title": "Changes in hospital prescribing activity at a specialist children's hospital during the COVID-19 pandemic - an observational study", "rel_date": "2020-12-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.20.20248581", - "rel_abs": "Two new SARS-CoV-2 lineages with the N501Y mutation in the receptor binding domain of the spike protein have rapidly become prevalent in the UK. We estimated that the earlier 501Y lineage without amino acid deletion {Delta}69/{Delta}70 circulating mainly between early September to mid-November was 10% (6-13%) more transmissible than the 501N lineage, and the currently dominant 501Y lineage with amino acid deletion {Delta}69/{Delta}70 circulating since late September was 75% (70-80%) more transmissible than the 501N lineage.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248153", + "rel_abs": "ObjectiveTo compare hospital activity, patient casemix and medication prescribing and administration before and during the COVID-19 emergency.\n\nDesignRetrospective observational study\n\nSettingA specialist childrens hospital in the UK\n\nPatientsInpatients aged 25 and younger treated at a specialist childrens hospital between 29 April 2019 and 6 September 2020\n\nResultsThere were 21,471 day cases and inpatients treated during the 16 month study period. Day cases (no overnight stay) dropped by around 37% per week. Both admissions and discharges for inpatients (at least one overnight stay) decreased leading to a small reduction in hospital bed days but no reduction in hospital bed nights. The effect on hospital activity on different patient groups varied substantially with some groups such as medical oncology day cases increasing by 13%. As a result, the patient case mix in the hospital was very different during the pandemic. Overall weekly medication administrations decreased for day cases and inpatients, but weekly medication administrations per bed day increased by 10% for day cases and 6% for inpatients.\n\nConclusionsDespite not being badly affected by the disease itself, specialist paediatric hospital services have been greatly affected by the pandemic. The average number of medications per inpatient bed day increased, likely reflecting changes to the patient population, with only those children with severe conditions being treated during the pandemic. These data demonstrate the complex pattern of implications on specialist services and provide evidence for planning the impact of future emergencies and resolution strategies.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Kathy Leung", - "author_inst": "The University of Hong Kong" + "author_name": "Emma Vestesson", + "author_inst": "UCL Great Ormond Street Institute of Child Health" }, { - "author_name": "Marcus HH Shum", - "author_inst": "The University of Hong Kong" + "author_name": "Carlos Alonso", + "author_inst": "Great Ormond Street Hospital, London, UK" }, { - "author_name": "Gabriel M Leung", - "author_inst": "The University of Hong Kong" + "author_name": "John Booth", + "author_inst": "Great Ormond Street Hospital, London, UK" }, { - "author_name": "Tommy TY Lam", - "author_inst": "The University of Hong Kong" + "author_name": "Neil J Sebire", + "author_inst": "UCL Great Ormond Street Institute of Child Health and NIHR GOSH BRC, London, UK" }, { - "author_name": "Joseph T Wu", - "author_inst": "The University of Hong Kong" + "author_name": "Adam Steventon", + "author_inst": "The Health Foundation, London, UK" + }, + { + "author_name": "Steve Tomlin", + "author_inst": "Great Ormond Street Hospital, London, UK" + }, + { + "author_name": "Joseph F Standing", + "author_inst": "UCL Great Ormond Street Institute of Child Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pediatrics" }, { "rel_doi": "10.1101/2020.12.20.20248583", @@ -1033843,49 +1033249,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.21.20248288", - "rel_title": "Comparative analysis of loop-mediated isothermal amplification (LAMP)-based assays for rapid detection of SARS-CoV-2 genes", + "rel_doi": "10.1101/2020.12.21.20248140", + "rel_title": "Rapid Detection of SARS-CoV-2 Antigen from Serum in a Hospitalized Population", "rel_date": "2020-12-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248288", - "rel_abs": "The COVID-19 pandemic caused by SARS-CoV-2 has infected millions worldwide and there is an urgent need to increase our diagnostic capacity to identify infected cases. Although RT-qPCR remains the gold standard for SARS-CoV-2 detection, this method requires specialised equipment in a diagnostic laboratory and has a long turn-around time to process the samples. To address this, several groups have recently reported development of loop-mediated isothermal amplification (LAMP) as a simple, low cost and rapid method for SARS-CoV-2 detection. Herein we present a comparative analysis of three LAMP-based assays that target different regions of the SARS-CoV-2: ORF1ab RdRP, ORF1ab nsp3 and Gene N. We perform a detailed assessment of their sensitivity, kinetics and false positive rates for SARS-CoV-2 diagnostics in LAMP or RT-LAMP reactions, using colorimetric or fluorescent detection. Our results independently validate that all three assays can detect SARS-CoV-2 in 30 minutes, with robust accuracy at detecting as little as 1000 RNA copies and the results can be visualised simply by color changes. We also note the shortcomings of these LAMP-based assays, including variable results with shorter reaction time or lower load of SARS-CoV-2, and false positive results in some experimental conditions. Overall for RT-LAMP detection, the ORF1ab RdRP and ORF1ab nsp3 assays have higher sensitivity and faster kinetics for detection, whereas the Gene N assay exhibits no false positives in 30 minutes reaction time. This study provides validation of the performance of LAMP-based assays for SARS-CoV-2 detection, which have important implications in development of point-of-care diagnostic for SARS-CoV-2.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.21.20248140", + "rel_abs": "SARS-CoV-2 viremia has been demonstrated in some patients using molecular assays. Here we demonstrate detection of SARS-CoV-2 antigen in a cohort of hospitalized patients using a rapid diagnostic test from Anhui Deepblue Medical Technology Co., Ltd. We detected antigen in serum from 11 of 13 patients at time points ranging from three to eighteen days from symptom onset and observed that the disappearance of an antigen signal was associated with seroconversion. These results demonstrate proof of principle use of a rapid antigen test with serum samples in a format compatible with point of care testing.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Daniel Urrutia-Cabrera", - "author_inst": "Centre for Eye Research Australia, University of Melbourne" - }, - { - "author_name": "Roxanne Hsiang-Chi Liou", - "author_inst": "Centre for Eye Research Australia, University of Melbourne" - }, - { - "author_name": "Jianxiong Chan", - "author_inst": "Monash University" - }, - { - "author_name": "Sandy Shen-Chi Hung", - "author_inst": "Centre for Eye Research Australia, University of Melbourne" - }, - { - "author_name": "Alex W Hewitt", - "author_inst": "Centre for Eye Research Australia, University of Melbourne" - }, - { - "author_name": "Keith Martin", - "author_inst": "Centre for Eye Research Australia, University of Melbourne" + "author_name": "Kathrine McAulay", + "author_inst": "Mayo Clinic" }, { - "author_name": "Patrick Kwan", - "author_inst": "Monash University" + "author_name": "Erin J Kaleta", + "author_inst": "Mayo Clinic" }, { - "author_name": "Raymond Ching-Bong Wong", - "author_inst": "Centre for Eye Research Australia Ltd/ University of Melbourne" + "author_name": "Thomas E Grys", + "author_inst": "Mayo Clinic" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1035833,55 +1035219,67 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.12.20.423603", - "rel_title": "Fatty Acid Synthase inhibition prevents palmitoylation of SARS-CoV2 SpikeProtein and improves survival of mice infected with murine hepatitis virus.", + "rel_doi": "10.1101/2020.12.20.422820", + "rel_title": "In vitro measurements of protein-protein interactions show that antibody affinity governs the inhibition of SARS-CoV-2 spike/ACE2 binding in convalescent serum", "rel_date": "2020-12-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.20.423603", - "rel_abs": "The Spike protein of SARS-CoV2 and other coronaviruses mediate host cell entry and are S-acylated on multiple phylogenetically conserved cysteine residues. Multiple protein acyltransferase enzymes of the ZDHHC family have been reported to modify Spike proteins post-translationally. Using resin-assisted capture mass spectrometry, we demonstrate that the Spike protein is S-acylated in SARS-CoV2 infected human and monkey cells. We further show that increased abundance of the human acyltransferase ZDHHC5 results in increased S-acylation of the SARS-CoV2 Spike protein, whereas ZDHHC5 knockout cells had a 40% reduction in the incorporation of an alkynyl-palmitate using click chemistry detection. We also find that the S-acylation of the Spike protein is not limited to palmitate, as clickable versions of myristate and stearate were also found on the immunocaptured protein. Yet, ZDHHC5 was highly selective for palmitate, suggesting that other ZDHHC enzymes mediated the incorporation of other fatty acyl chains. Thus, since multiple ZDHHC isoforms may modify the Spike protein, we examined the ability of the fatty acid synthase inhibitor TVB-3166 to prevent the S-acylation of the Spike proteins of SARS-CoV-2 and human CoV-229E. Treating cells with TVB-3166 inhibited S-acylation of ectopically expressed SARS-CoV2 Spike and attenuated the ability of SARS-CoV2 and human CoV-229E to spread in vitro. Additionally, treatment of mice with a comparatively low dose of TVB-3166 promoted survival from an otherwise fatal murine coronavirus infection. Our findings further substantiate the necessity of CoV Spike protein S-acylation and the potential use of fatty acid synthase inhibitors.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.20.422820", + "rel_abs": "The humoral immune response plays a key role in suppressing the pathogenesis of SARS-CoV-2. The molecular determinants underlying the neutralization of the virus remain, however, incompletely understood. Here, we show that the ability of antibodies to disrupt the binding of the viral spike protein to the angiotensin-converting enzyme 2 (ACE2) receptor on the cell, the key molecular event initiating SARS-CoV-2 entry into host cells, is controlled by the affinity of these antibodies to the viral antigen. By using microfluidic antibody-affinity profiling, we were able to quantify the serum-antibody mediated inhibition of ACE2-spike binding in two SARS-CoV-2 seropositive individuals. Measurements to determine the affinity, concentration, and neutralization potential of antibodies were performed directly in human serum. Using this approach, we demonstrate that the level of inhibition in both samples can be quantitatively described using the binding energies of the binary interactions between the ACE2 receptor and the spike protein, and the spike protein and the neutralizing antibody. These experiments represent a new type of in-solution receptor binding competition assay, which has further potential areas of application ranging from decisions on donor selection for convalescent plasma therapy, to identification of lead candidates in therapeutic antibody development, and vaccine development.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Katrina Mekhail", - "author_inst": "University of Toronto" + "author_name": "Sebastian Fiedler", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Minhyoung Lee", - "author_inst": "University of Toronto" + "author_name": "Monika A. Piziorska", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Michael Sugiyama", - "author_inst": "Ryerson University" + "author_name": "Viola Denninger", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Audrey Astori", - "author_inst": "University of Toronto" + "author_name": "Alexey S. Morgunov", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Jonathan St-Germain", - "author_inst": "University of Toronto" + "author_name": "Alison Ilsley", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Elyse Latreille", - "author_inst": "University of Toronto" + "author_name": "Anisa Y. Malik", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Costin N Antonescu", - "author_inst": "Ryerson University" + "author_name": "Matthias M. Schneider", + "author_inst": "University of Cambridge" }, { - "author_name": "Brian Raught", - "author_inst": "University of Toronto" + "author_name": "Sean R.A. Devenish", + "author_inst": "Fluidic Analytics" }, { - "author_name": "Greg D Fairn", - "author_inst": "University of Toronto" + "author_name": "Georg Meisl", + "author_inst": "Fluidic Analytics" + }, + { + "author_name": "Adriano Aguzzi", + "author_inst": "University of Zurich" + }, + { + "author_name": "Heike Fiegler", + "author_inst": "Fluidic Analytics" + }, + { + "author_name": "Tuomas P.J. Knowles", + "author_inst": "University of Cambridge" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "new results", - "category": "cell biology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.12.21.423733", @@ -1037674,91 +1037072,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.18.423106", - "rel_title": "Furin cleaves SARS-CoV-2 spike-glycoprotein at S1/S2 and S2'for viral fusion/entry: indirect role for TMPRSS2", + "rel_doi": "10.1101/2020.12.19.423584", + "rel_title": "Identification of NPC1 as a novel SARS-CoV-2 intracellular target", "rel_date": "2020-12-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.18.423106", - "rel_abs": "The spike (S)-protein of SARS-CoV-2 binds ACE2 and requires proteolytic \"priming\" at PRRAR685{downarrow} into S1 and S2 (cleavage at S1/S2), and \"fusion-activation\" at a S2 site for viral entry. In vitro, Furin cleaved peptides mimicking the S1/S2 cleavage site more efficiently than at the putative S2, whereas TMPRSS2 inefficiently cleaved both sites. In HeLa cells Furin-like enzymes mainly cleaved at S1/S2 during intracellular protein trafficking, and S2 processing by Furin at KPSKR815{downarrow} was strongly enhanced by ACE2, but not for the optimized S2 KRRKR815{downarrow} mutant (S2), whereas individual/double KR815AA mutants were retained in the endoplasmic reticulum. Pharmacological Furin-inhibitors (Boston Pharmaceuticals, BOS-inhibitors) effectively blocked endogenous S-protein processing in HeLa cells. Furthermore, we show using pseudotyped viruses that while entry by a \"pH-dependent\" endocytosis pathway in HEK293 cells did not require Furin processing at S1/S2, a \"pH-independent\" viral entry in lung-derived Calu-3 cells was sensitive to inhibitors of Furin (BOS) and TMPRSS2 (Camostat). Consistently, these inhibitors potently reduce infectious viral titer and cytopathic effects, an outcome enhanced when both compounds were combined. Quantitative analyses of cell-to-cell fusion and spike processing revealed the key importance of the Furin sites for syncytia formation. Our assays showed that TMPRSS2 enhances fusion and proteolysis at S2 in the absence of cleavage at S1/S2, an effect that is linked to ACE2 shedding by TMPRSS2. Overall, our results indicate that Furin and TMPRSS2 play synergistic roles in generating fusion-competent S-protein, and in promoting viral entry, supporting the combination of Furin and TMPRSS2 inhibitors as potent antivirals against SARS-CoV-2.\n\nIMPORTANCESARS-CoV-2 is the etiological agent of COVID-19 that resulted in >5 million deaths. The spike protein (S) of the virus directs infection of the lungs and other tissues by binding the angiotensin-converting enzyme 2 (ACE2) receptor. For effective infection, the S-protein is cleaved at two sites: S1/S2 and S2. Cleavage at S1/S2, induces a conformational change favoring the recognition of ACE2. The S2 cleavage is critical for cell-to-cell fusion and virus entry into host cells. Our study contributes to a better understanding of the dynamics of interaction between Furin and TMPRSS2 during SARS-CoV-2 entry and suggests that the combination of a non-toxic Furin inhibitor with a TMPRSS2 inhibitor could significantly reduce viral entry in lung cells, as evidenced by an average synergistic [~]95% reduction of viral infection. This represents a powerful novel antiviral approach to reduce viral spread in individuals infected by SARS-CoV-2 or future related coronaviruses.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.19.423584", + "rel_abs": "Niemann-Pick type C1 (NPC1) receptor is an endosomal membrane protein that regulates intracellular cholesterol trafficking, which is crucial in the Ebola virus (EBOV) cycle. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) enters the cell by binding of the viral spike (S) protein to the ACE2 receptor. This requires S-protein processing either by the surface transmembrane serine protease TMPRSS2 for plasma membrane fusion or cathepsin L for endosomal entry. Additional host factors are required for viral fusion at endosomes. Here, we report a novel interaction of the SARS-CoV-2 nucleoprotein (N) with the cholesterol transporter NPC1. Moreover, small molecules interfering with NPC1 that inhibit EBOV entry, also inhibited human coronavirus. Our findings suggest an important role for NPC1 in SARS-CoV-2 infection, a common strategy shared with EBOV, and a potential therapeutic target to fight against COVID-19.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Rachid Essalmani", - "author_inst": "IRCM" - }, - { - "author_name": "Jaspreet Jain", - "author_inst": "IRCM" - }, - { - "author_name": "Delia Susan-Resiga", - "author_inst": "IRCM" - }, - { - "author_name": "Ursula Andreo", - "author_inst": "IRCM" - }, - { - "author_name": "Alexandra Evagelidis", - "author_inst": "IRCM" - }, - { - "author_name": "Rabeb Mouna Derbali", - "author_inst": "IRCM" - }, - { - "author_name": "David Huynh", - "author_inst": "IRCM" + "author_name": "Isabel Garcia-Dorival", + "author_inst": "Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria, INIA" }, { - "author_name": "Frederic Dallaire", - "author_inst": "IRCM" + "author_name": "Miguel Angel Cuesta-Geijo", + "author_inst": "Instituto Nacional de Investigacioon y Tecnologia Agraria y Alimentaria INIA - Centro de Investigaciones Biologicas Margarita Salas CSIC" }, { - "author_name": "Melanie Laporte", - "author_inst": "IRCM" + "author_name": "Lucia Barrado-Gil", + "author_inst": "Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria INIA - Centro de Investigaciones Biologicas Margarita Salas CSIC" }, { - "author_name": "Adrien Delpal", - "author_inst": "AFMB Polytech" + "author_name": "Inmaculada Galindo", + "author_inst": "Instituto Nacional de Investigacioon y Tecnologiia Agraria y Alimentaria INIA" }, { - "author_name": "Priscila Sutto-Ortiz", - "author_inst": "AFMB Polytech" + "author_name": "Jesus Urquiza", + "author_inst": "Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria" }, { - "author_name": "Bruno Coutard", - "author_inst": "UVE: Aix-Marseille" - }, - { - "author_name": "Claudine Mapa", - "author_inst": "Boston Pharmaceuticals" + "author_name": "Ana Del Puerto", + "author_inst": "Instituto Nacional de Investigacion y Tecnologiia Agraria y Alimentaria INIA" }, { - "author_name": "Keith Wilcoxen", - "author_inst": "Boston Pharmaceuticals" - }, - { - "author_name": "Etienne Decroly", - "author_inst": "UVE: Aix-Marseille" + "author_name": "Carmen Gil", + "author_inst": "Centro de Investigaciones Biologicas Margarita Salas CSIC" }, { - "author_name": "Tram Pham", - "author_inst": "IRCM" + "author_name": "Nuria Campillo", + "author_inst": "Centro de Investigaciones Biologicas Margarita Salas CSIC" }, { - "author_name": "Eric A. Cohen", - "author_inst": "IRCM" + "author_name": "Ana Martinez", + "author_inst": "Centro de Investigaciones Biologicas Margarita Salas CSIC" }, { - "author_name": "Nabil G. Seidah", - "author_inst": "IRCM" + "author_name": "Covadonga Alonso", + "author_inst": "Instituto Nacional de Investigacion y Tecnologia Agraria y Alimentaria INIA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biochemistry" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.12.20.423533", @@ -1039348,103 +1038714,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.16.20248180", - "rel_title": "Seroprevalence of anti-SARS-CoV-2 IgG antibodies, risk factors for infection and associated symptoms in Geneva, Switzerland: a population-based study", + "rel_doi": "10.1101/2020.12.16.20248134", + "rel_title": "No evidence of association between schools and SARS-CoV-2 second wave in Italy.", "rel_date": "2020-12-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.16.20248180", - "rel_abs": "BackgroundPopulation-based serological surveys provide a means for assessing the immunologic landscape of a community, without the biases related to health-seeking behaviors and testing practices typically associated with rt-PCR testing. This study assesses SARS-CoV-2 seroprevalence over the first epidemic wave in Canton Geneva, Switzerland, as well as biological and socio-economic risk factors for infection and symptoms associated with IgG seropositivity.\n\nMethods and findingsBetween April 6 and June 30, 2020, former participants of a yearly representative cross-sectional survey of the 20-75-year-old population of the canton of Geneva were invited to participate in a seroprevalence study, along with household members five years and older. We collected blood and tested it for anti-SARS-CoV-2 immunoglobulins G (IgG). Questionnaires were self-administered. We estimated seroprevalence with a Bayesian model accounting for test performance and sampling design. We included 8344 participants (53.5% women, mean age 46.9 years). The population-level seroprevalence over the 12-week study period was 7.8 % (95% Credible Interval (CrI) 6.8-8.9), accounting for sex, age and household random effects. Seroprevalence was highest among 18-49 year olds (9.5%, 95%CrI 8.1-10.9), with young children (5-9 years) and those >65 years having significantly lower seroprevalence (4.3% and 4.7-5.4% respectively). Men were more likely to be seropositive than women (relative risk 1.2, 95%CrI 1.1-1.4). Odds of seropositivity were reduced for female retirees (0.46, 95%CI 0.23-0.93) and unemployed men (0.35, 95%CI 0.13-1.0) compared to employed individuals, and for current smokers (0.36, 95%CI 0.23-0.55) compared to never-smokers. We found no significant association between occupation, level of education, neighborhood income and the risk of being seropositive. Symptoms most strongly associated with seropositivity were anosmia/dysgeusia, loss of appetite, fever, fatigue and myalgia and/or arthralgia. Thirteen percent of seropositive participants reported no symptoms.\n\nConclusionsOur results confirm a low population seroprevalence of anti-SARS-CoV-2 antibodies after the first wave in Geneva, a region hard hit by the COVID-19 pandemic. Socioeconomic factors were not associated with seropositivity in this sample. The elderly and young children were less frequently seropositive, though it is not clear how biology and behaviors shape these differences. These specificities should be considered when assessing the need for targeted public health measures.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.16.20248134", + "rel_abs": "BackgroundDuring the Covid19 pandemic, school closure has been mandated in analogy to its known effect against influenza, but it is unclear whether schools are early amplifiers of Covid19 cases.\n\nMethodsWe performed a cross-sectional and prospective cohort study in Italy. We used databases from the Italian Ministry of Education containing the number of new positive SARS-CoV-2 cases per school from September 20 to November 8, 2020 to calculate incidence among students and staff. We calculated incidence across each age group using databases from the Veneto Region system of SARS-CoV-2 cases notification in the period August 26- November 24, 2020. We used a database from the Veneto Region system of SARS-CoV-2 secondary cases tracing in Verona province schools to estimate number of tests, the frequency of secondary infections at school by type of index case and the ratio positive cases/ number of tests per school institute using an adjusted multivariable generalized linear regression model. We estimated the reproduction number Rt at the regional level from the Italian Civil Protection of regional SARS-CoV-2 cases notification database in the period 6 August-2 December 2020.\n\nFindingsFrom September 12 to November 7 2020, SARS-CoV-2 incidence among students was lower than that in the general population of all but two Italian regions. Secondary infections were <1%, and clusters of >2 secondary cases per school were 5-7% in a representative November week. Incidence among teachers was greater than in the general population. However, when compared with incidence among similar age groups, the difference was not significant (P=0.23). Secondary infections among teachers were more frequent when the index case was a teacher than a student (38% vs. 11%, P=0.007). From August 28 to October 25 in Veneto where school reopened on September 14, the growth of SARS-CoV- 2 incidence was lower in school age individuals, maximal in 20-29 and 45-49 years old individuals. The delay between the different school opening dates in the different Italian regions and the increase in the regional Covid19 reproduction number Rt was not uniform. Reciprocally, school closures in two regions where they were implemented before other measures did not affect the rate of Rt decline.\n\nInterpretationOur analysis does not support a role for school opening as a driver of the second wave of SARS-CoV-2 epidemics in Italy, a large European country with high SARS-CoV-2 incidence.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe role of schools and at large of children as amplifiers of the Covid19 pandemics is debated. Despite biological and epidemiological evidence that children play a marginal role in Sars-CoV-2 spread, policies of school closures have been predicated, mostly based on the temporal coincidence between school reopening in certain countries and Covid19 outbreaks. Whether schools contributed to the so called \"second wave\" of Covid19 is uncertain. Italys regionalized calendar of school reopening and databases of positivity at school allows to estimate the impact of schools on the increase of Sars-CoV-2 that occurred in autumn 2020.\n\nAdded value of this studyWe found that incidence among students is lower than in the general population and that whereas incidence among teachers appears higher than that in the general population, it is comparable to that among individuals of the same age bracket. Moreover, secondary infections at school are rare and clusters even less common. The index case of a secondary teacher case is more frequently a teacher than a student. In Veneto, during the first phase of the second wave incidence among school age individuals was low as opposed to the sustained incidence among individuals of 45-49 years. Finally, the time lag between school opening and Rt increase was not uniform across different Italian regions with different school opening dates, with lag times shorter in regions where schools opened later.\n\nImplications of the available evidenceThese findings contribute to indicate that Covid19 infections rarely occur at school and that transmission from students to teachers is very rare. Moreover, they fail to support a role for school age individuals and school openings as a driver of the Covid19 second wave. Overall, our findings could help inform policy initiatives of school openings during the current Covid19 pandemic.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Aude Richard", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Ania Wisniak", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Javier Perez-Saez", - "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland" - }, - { - "author_name": "Henri Garrison-Desany", - "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA" - }, - { - "author_name": "Dusan Petrovic", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Giovanni Piumatti", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Helene Baysson", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Attilio Picazio", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Francesco Pennacchio", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "David De Ridder", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Francois Chappuis", - "author_inst": "Division of Tropical and Humanitarian Medicine, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Nicolas Vuilleumier", - "author_inst": "Division of Laboratory Medicine, Geneva University Hospitals, Geneva, Switzerland" - }, - { - "author_name": "Nicola Low", - "author_inst": "University of BernInstitute of Social and Preventive Medicine, Faculty of Medicine, University of Bern, Bern, Switzerland" - }, - { - "author_name": "Samia Hurst", - "author_inst": "Institute for Ethics, History, and the Humanities, Faculty of Medicine, University of Geneva, Geneva, Switzerland" - }, - { - "author_name": "Isabella Eckerle", - "author_inst": "Department of Microbiology and Molecular Medicine, Faculty of Medicine, University of Geneva, Geneva, Switzerland" - }, - { - "author_name": "Antoine Flahault", - "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland" + "author_name": "Sara Gandini", + "author_inst": "European Institute of Oncology" }, { - "author_name": "Laurent Kaiser", - "author_inst": "Division of Infectious Diseases, Geneva University Hospitals, Geneva, Switzerland" + "author_name": "Maurizio Rainisio", + "author_inst": "AbaNovus srl Saremo Italy" }, { - "author_name": "Anderw S Azman", - "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland" + "author_name": "Maria Luisa Iannuzzo", + "author_inst": "AULSS 9 Scaligera-Dipartimento di Prevenzione-UOC Medicina Legale- Verona" }, { - "author_name": "Idris Guessous", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" + "author_name": "Federica Bellerba", + "author_inst": "European Institute of Oncology" }, { - "author_name": "Silvia Stringhini", - "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" + "author_name": "Francesco Cecconi", + "author_inst": "Dept. of Biology, University of Rome Tor Vergata" }, { - "author_name": "- SEROCOV-POP study group", - "author_inst": "" + "author_name": "Luca Scorrano", + "author_inst": "University of Padua, Venetian Institute of Molecular Medicine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.12.16.20247684", @@ -1041334,45 +1040640,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.16.20248357", - "rel_title": "Understanding the net benefit of antigen-based rapid diagnostic tests for COVID-19: An enhanced decision-curve analysis", + "rel_doi": "10.1101/2020.12.16.20248343", + "rel_title": "Impaired ICOS signaling between Tfh and B cells distinguishes hospitalized from ambulatory CoViD-19 patients", "rel_date": "2020-12-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.16.20248357", - "rel_abs": "BackgroundSARS-CoV-2 antigen-detection rapid diagnostic tests (Ag-RDTs) can diagnose COVID-19 rapidly and at low cost, but their lower sensitivity than nucleic acid amplification testing (NAAT) has limited clinical adoption.\n\nMethodsWe compared Ag-RDT, NAAT, and clinical judgment alone for diagnosing symptomatic COVID-19. We considered an outpatient setting (10% COVID-19 prevalence among the patients tested, 3-day NAAT turnaround) and a hospital setting (40% prevalence, 24-hour NAAT turnaround). We simulated transmission from cases and contacts and relationships between time, viral burden, transmission, and case detection. We compared diagnostic approaches using a measure of net benefit that incorporated both clinical and public health benefits and harms of intervention.\n\nResultsIn the outpatient setting, we estimated that using Ag-RDT instead of NAAT to test 200 individuals could have a net benefit equivalent to preventing all symptomatic transmission from one person with COVID-19 (one \"transmission-equivalent\"). In the hospital setting, net benefit analysis favored NAAT, and testing 25 patients with NAAT instead of Ag-RDT achieved one \"transmission-equivalent\" of incremental benefit. In both settings, Ag-RDT was preferred to NAAT if NAAT turnaround time exceeded two days. Both Ag-RDT and NAAT provided greater net benefit than management based on clinical judgment alone, unless intervention carried minimal harm and was provided equally regardless of diagnostic approach.\n\nConclusionsFor diagnosis of symptomatic COVID-19, the speed of diagnosis with Ag-RDT is likely to outweigh its lower accuracy compared to NAAT wherever NAAT turnaround times are two days or longer. This advantage may be even greater if Ag-RDTs are also less expensive.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.16.20248343", + "rel_abs": "Emerging evidence suggests that SARS-CoV-2 infections are characterized by systemic immune responses that appear to be dysregulated with more severe CoViD-19 disease. Lymphopenia and delayed antibody responses are commonly identified in CoViD-19 subjects, and recent reports have demonstrated abrogation of germinal centers in severe CoViD-19. This work assessed a potential mechanistic basis for impaired humoral responses, focusing on the T follicular helper (Tfh) and B cell interface that is critical for germinal center reactions. Here we demonstrated that Tfh activity is impaired in hospitalized relative to ambulatory CoViD-19 subjects, potentially due to decreased expression of the costimulatory molecule ICOS-L on B cells. Functional impairment manifested as a diminished ability to stimulated Tfh derived IFN{gamma} and IL-21, the latter of which is critical for B cell proliferation and differentiation. Activation of Tfh cells by agonism of the ICOS receptor ex vivo by an agonistic antibody stimulated the generation of IFN{gamma}/IL-21 double positive cells from hospitalized CoViD-19 subjects. This report establishes an immunological defect that differentiates ambulatory from hospitalized CoViD and suggests that agents that could restore impaired mechanisms at the Tfh-B cell interface may be of therapeutic value.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Emily A Kendall", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Amanda Hanson", + "author_inst": "Jounce Therapeutics" }, { - "author_name": "Nimalan Arinaminpathy", - "author_inst": "Imperial College London" + "author_name": "Heather Cohen", + "author_inst": "Jounce Therapeutics" }, { - "author_name": "Jilian A Sacks", - "author_inst": "FIND" + "author_name": "Hao Wang", + "author_inst": "Jounce Therapeutics" }, { - "author_name": "Yukari C Manabe", - "author_inst": "Johns Hopkins University School of Medicine" + "author_name": "Nandini Shekhar", + "author_inst": "Jounce Therapeutics" }, { - "author_name": "Sabine Dittrich", - "author_inst": "FIND" + "author_name": "Chinmayee Shah", + "author_inst": "Jounce Therapeutics" }, { - "author_name": "Samuel G Schumacher", - "author_inst": "FIND" + "author_name": "Abha Dhaneshwar", + "author_inst": "Jounce Therapeutics" }, { - "author_name": "David W Dowdy", - "author_inst": "Johns Hopkins Bloomberg School of Public Health" + "author_name": "Bethany W Harvey", + "author_inst": "Jounce Therapeutics" + }, + { + "author_name": "Richard Murray", + "author_inst": "Jounce Therapeutics" + }, + { + "author_name": "Christopher J Harvey", + "author_inst": "Jounce Therapeutics" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1042948,37 +1042262,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.14.20248209", - "rel_title": "The Presence of Ambulatory Hypoxia as an Early Predictor of Moderate to Severe COVID-19 Disease", + "rel_doi": "10.1101/2020.12.14.20248192", + "rel_title": "A Comprehensive Clinical Description of Pediatric SARS-CoV-2 Infection in Western Pennsylvania", "rel_date": "2020-12-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.14.20248209", - "rel_abs": "BackgroundThe importance of ambulatory hypoxia without resting hypoxia in COVID-19 is unknown. Ambulatory hypoxia without resting hypoxia may help objectively identify high-risk patients hospitalized with COVID-19. Interventions may be initiated earlier with sufficient lead-time between development of ambulatory hypoxia and other outcome measures.\n\nMethodsWe performed a retrospective study of adult patients hospitalized with COVID-19 from March 1, 2020 to October 30, 2020 in ten hospitals in an integrated academic medical system in the Chicagoland area. We analyzed patients who had daily ambulatory oximetry measurements, excluding patients who had first ambulatory oximetry measurements after the use of oxygen therapies (nasal cannula or advanced oxygen therapies). We determined the association of ambulatory hypoxia without resting hypoxia with the eventual need for nasal cannula or advanced oxygen therapies (defined as high flow nasal cannula, Bi-PAP, ventilator, or extracorporeal membrane oxygenation). We also calculated the time between development of ambulatory hypoxia and the need for oxygen therapies.\n\nResultsOf 531 patients included in the study, 132 (24.9%) had ambulatory hypoxia. Presence of ambulatory hypoxia was strongly associated with subsequent use of nasal cannula (OR 4.8, 95% CI 2.8 - 8.4) and advanced oxygen therapy (IRR 7.7, 95% CI 3.4 - 17.5). Ambulatory hypoxia preceded nasal cannula use by a median 12.5 hours [IQR 3.25, 29.25] and advanced oxygenation therapies by 54 hours [IQR 25, 82].\n\nConclusionAmbulatory hypoxia without resting hypoxia may serve as an early, non-invasive physiologic marker for the likelihood of developing moderate to severe COVID-19 and help clinicians triage patients and initiate earlier interventions.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.14.20248192", + "rel_abs": "ObjectiveWe sought to characterize clinical presentation and healthcare utilization for pediatric COVID-19 in Western Pennsylvania (PA).\n\nMethodsWe established and analyzed a registry of pediatric COVID-19 in Western PA that includes cases in patients <22 years of age cared for by the pediatric quaternary medical center in the area and its associated pediatric primary care network from March 11 through August 20, 2020.\n\nResultsOur cohort included 424 pediatric COVID-19 cases (mean age 12.5 years, 47.4% female); 65% reported exposure and 79% presented with symptoms. The most common initial healthcare contact was through telehealth (45%). Most cases were followed as outpatients, but twenty-two patients (4.5%) were hospitalized: 19 with acute COVID-19 disease, and three for multisystem inflammatory syndrome of children (MIS-C). Admitted patients were younger (p<0.001) and more likely to have pre-existing conditions (p<0.001). Black/Hispanic patients were 5.8 times more likely to be hospitalized than white patients (p=0.012). Five patients (1.2%) were admitted to the PICU, including all three MIS-C cases; two required BiPAP and one mechanical ventilation. All patients survived.\n\nConclusionsWe provide a comprehensive snapshot of pediatric COVID-19 disease in an area with low to moderate incidence. In this cohort, COVID-19 was generally a mild disease; however, [~]5% of children were hospitalized. Pediatric patients can be critically ill with this infection, including those presenting with MIS-C.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Ajay Bhasin", - "author_inst": "Northwestern Univeristy" + "author_name": "Megan Culler Freeman", + "author_inst": "UPMC Children's Hospital of Pittsburgh" }, { - "author_name": "Melissa Bregger", - "author_inst": "Northwestern University" + "author_name": "Kristina Gaietto", + "author_inst": "UPMC Children's Hospital of Pittsburgh" }, { - "author_name": "Mark Kluk", - "author_inst": "Northwestern University" + "author_name": "Leigh Anne DiCicco", + "author_inst": "UPMC Children's Hospital of Pittsburgh" }, { - "author_name": "Peter Park", - "author_inst": "Northwestern University" + "author_name": "Sherry Rauenswinter", + "author_inst": "Children's Community Pediatrics" }, { - "author_name": "Joseph Feinglass", - "author_inst": "Northwestern University" + "author_name": "Joseph R Squire", + "author_inst": "Children's Community Pediatrics" }, { - "author_name": "Jeffrey Barsuk", - "author_inst": "Northwestern University" + "author_name": "Zachary Aldewereld", + "author_inst": "UPMC Children's Hospital of Pittsburgh" + }, + { + "author_name": "Glenn Rapsinski", + "author_inst": "UPMC Children's Hospital of Pittsburgh" + }, + { + "author_name": "Jennifer Iagnemma", + "author_inst": "Children's Community Pediatrics" + }, + { + "author_name": "Brian T. Campfield", + "author_inst": "UPMC Children's Hospital of Pittsburgh" + }, + { + "author_name": "David Wolfson", + "author_inst": "Children's Community Pediatrics" + }, + { + "author_name": "Traci M. Kazmerski", + "author_inst": "UPMC Children's Hospital of Pittsburgh" + }, + { + "author_name": "Erick Forno", + "author_inst": "UPMC Children's Hospital of Pittsburgh" } ], "version": "1", @@ -1044774,27 +1044112,35 @@ "category": "bioengineering" }, { - "rel_doi": "10.1101/2020.12.16.423071", - "rel_title": "One Year of SARS-CoV-2: How Much Has the Virus Changed?", + "rel_doi": "10.1101/2020.12.16.20248308", + "rel_title": "The effectiveness of Non Pharmaceutical Interventions in reducing the outcomes of the COVID-19 epidemic in the UK, an observational and modelling study.", "rel_date": "2020-12-16", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.16.423071", - "rel_abs": "SARS-CoV-2 coronavirus has caused a world-wide crisis with profound effects on both healthcare and the economy. In order to combat the COVID-19 pandemic, research groups have shared viral genome sequence data through the GISAID initiative. We collected and computationally profiled [~]223,000 full SARS-CoV-2 proteome sequences from GISAID over one year for emergent nonsynonymous mutations. Our analysis shows that SARS-CoV-2 proteins are mutating at substantially different rates, with most viral proteins exhibiting little mutational variability. As anticipated, our calculations capture previously reported mutations occurred in the first period of the pandemic, such as D614G (Spike), P323L (NSP12), and R203K/G204R (Nucleocapsid), but also identify recent mutations like A222V and L18F (Spike) and A220V (Nucleocapsid). Our comprehensive temporal and geographical analyses show two periods with different mutations in the SARS-CoV-2 proteome: December 2019 to June 2020 and July to November 2020. Some mutation rates differ also by geography; the main mutations in the second period occurred in Europe. Furthermore, our structure-based molecular analysis provides an exhaustive assessment of mutations in the context of 3D protein structure. Emerging sequence-to-structure data is beginning to reveal the site-specific mutational tolerance of SARS-CoV2 proteins as the virus continues to spread around the globe.", - "rel_num_authors": 2, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.16.20248308", + "rel_abs": "Epidemiological models used to inform government policies aimed to contain the contagion of COVID-19, assume that the reproduction rate is reduced through Non-Pharmaceutical Interventions (NPIs) leading to physical distancing. Available data in the UK show an increase in physical distancing before the NPIs were implemented and a fall soon after implementation. We aimed to estimate the effect of peoples behaviour on the epidemic curve and the effect of NPIs taking into account this behavioural component. We have estimated the effects of confirmed daily cases on physical distancing and we used this insight to design a bevavioural SEIR model (BeSEIR), simulated different scenaria regarding NPIs and compared the results to the standard SEIR. Taking into account behavioural insights improves the description of the contagion dynamics of the epidemic significantly. The BeSEIR predictions regarding the number of infections without NPIs were several orders of magnitude less than the SEIR. However, the BeSEIR prediction showed that early measures would still have an important influence in the reduction of infections. The BeSEIR model shows that even with no intervention the percentage of the cumulative infections within a year will not be enough for the epidemic to resolve due to a herd immunity effect. On the other hand, a standard SEIR model significantly overestimates the effectiveness of measures. Without taking into account the behavioural component the epidemic is predicted to be resolved much sooner than when taking it into account.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Santiago Vilar", - "author_inst": "Department of Molecular and Cellular Pharmacology, University of Miami Miller School of Medicine" + "author_name": "Giorgos Galanis", + "author_inst": "Goldsmiths, University of London" }, { - "author_name": "Daniel G. Isom", - "author_inst": "University of Miami, Miller School of Medicine" + "author_name": "Corrado Di Guilmi", + "author_inst": "University of Technology Sydney" + }, + { + "author_name": "David L. Bennett", + "author_inst": "University of Oxford" + }, + { + "author_name": "Georgios Baskozos", + "author_inst": "University of Oxford" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "health policy" }, { "rel_doi": "10.1101/2020.12.15.20229286", @@ -1046384,61 +1045730,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.13.20248142", - "rel_title": "COVID-19 vaccines that reduce symptoms but do not block infection need higher coverage and faster rollout to achieve population impact", + "rel_doi": "10.1101/2020.12.13.20248147", + "rel_title": "Association of Mortality and Aspirin Prescription for COVID-19 Patients at the Veterans Health Administration", "rel_date": "2020-12-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.13.20248142", - "rel_abs": "BackgroundSeveral COVID-19 vaccine candidates are in the final stage of testing. Interim trial results for two vaccines suggest at least 90% efficacy against symptomatic disease (VEDIS). It remains unknown whether this efficacy is mediated predominately by lowering SARS-CoV-2 infection susceptibility (VESUSC) or development of symptoms after infection (VESYMP). A vaccine with high VESYMP but low VESUSC has uncertain population impact.\n\nMethodsWe developed a mathematical model of SARS-CoV-2 transmission, calibrated to demographic, physical distancing and epidemic data from King County, Washington. Different rollout scenarios starting December 2020 were simulated assuming different combinations of VESUSC and VESYMP resulting in up to 100% VEDIS with constant vaccine effects over 1 year. We assumed no further increase in physical distancing despite expanding case numbers and no reduction of infectivity upon infection conditional on presence of symptoms. Proportions of cumulative infections, hospitalizations and deaths prevented over 1 year from vaccination start are reported.\n\nResultsRollouts of 1M vaccinations (5,000 daily) using vaccines with 50% VEDIS are projected to prevent 30%-58% of infections and 38%-58% of deaths over one year. In comparison, vaccines with 90% VEDIS are projected to prevent 47%-78% of the infections and 58%-77% of deaths over one year. In both cases, there is a greater reduction if VEDIS is mediated mostly by VESUSC. The use of a \"symptom reducing\" vaccine will require twice as many people vaccinated than a \"susceptibility reducing\" vaccine with the same 90% VEDIS to prevent 50% of the infections and death over one year. Delaying the start of the vaccination by 3 months decreases the expected population impact by approximately 40%.\n\nConclusionsVaccines which prevent COVID-19 disease but not SARS-CoV-2 infection, and thereby shift symptomatic infections to asymptomatic infections, will prevent fewer infections and require larger and faster vaccination rollouts to have population impact, compared to vaccines that reduce susceptibility to infection. If uncontrolled transmission across the U.S. continues, then expected vaccination in Spring 2021 will provide only limited benefit.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.13.20248147", + "rel_abs": "There is growing evidence that thrombotic and inflammatory pathways contribute to the severity of COVID-19. Common medications such as aspirin, that mitigate these pathways, may decrease COVID-19 mortality. This assessment was designed to quantify the correlation between aspirin and mortality for COVID-19 positive patients in our care. Data from the Veterans Health Administration national electronic health record database was utilized for the evaluation. Veterans from across the country with a first positive COVID-19 polymerase chain reaction lab result were included in the evaluation which comprised 28,350 patients from March 2, 2020 to September 13, 2020 for the 14-day mortality cohort and 26,346 patients from March 2, 2020 to August 28, 2020 for the 30-day mortality cohort. Patients were matched via propensity scores and the odds of mortality were then compared. Among COVID-19 positive Veterans, preexisting aspirin prescription was associated with a statistically and clinically significant decrease in overall mortality at 14-days (OR 0.38, 95% CI 0.32-0.46) and at 30-days (OR 0.38, 95% CI 0.33-0.45), cutting the odds of mortality by more than half. Findings demonstrated that pre-diagnosis aspirin prescription was strongly associated with decreased mortality rates for Veterans diagnosed with COVID-19. Prospective evaluation is required to more completely assess this correlation and its implications for patient care.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "David A Swan", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Chloe Bracis", - "author_inst": "Universit\u00e9 Grenoble Alpes" - }, - { - "author_name": "Holly Janes", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Mia Moore", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Laura Matrajt", - "author_inst": "Fred Hutchinson Cancer Research Center" - }, - { - "author_name": "Daniel B Reeves", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Thomas F Osborne", + "author_inst": "US Department of Veterans Affairs Palo Alto Healthcare System. Stanford University School of Medicine" }, { - "author_name": "Eileen Burns", - "author_inst": "Independent Researcher" + "author_name": "Zachary P Veigulis", + "author_inst": "US Department of Veterans Affairs Palo Alto Healthcare System" }, { - "author_name": "Deborah Donnell", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "David M Arreola", + "author_inst": "US Department of Veterans Affairs Palo Alto Healthcare System" }, { - "author_name": "Myron S Cohen", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Satish M Mahajan", + "author_inst": "US Department of Veterans Affairs Palo Alto Healthcare System" }, { - "author_name": "Joshua Schiffer", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Eliane M Roosli", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Dobromir T Dimitrov", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Catherine M Curtin", + "author_inst": "US Department of Veterans Affairs Palo Alto Healthcare System. Stanford University School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1048238,59 +1047564,67 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.12.13.420406", - "rel_title": "Identification of bis-benzylisoquinoline alkaloids as SARS-CoV-2 entry inhibitors from a library of natural products in vitro", + "rel_doi": "10.1101/2020.12.13.422511", + "rel_title": "Hepatitis C Virus Drugs Simeprevir and Grazoprevir Synergize with Remdesivir to Suppress SARS-CoV-2 Replication in Cell Culture", "rel_date": "2020-12-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.13.420406", - "rel_abs": "Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major public health issue. To screen for antiviral drugs for COVID-19 treatment, we constructed a SARS-CoV-2 spike (S) pseudovirus system using an HIV-1-based lentiviral vector with a luciferase reporter gene to screen 188 small potential antiviral compounds. Using this system, we identified nine compounds, specifically, bis-benzylisoquinoline alkaloids, that potently inhibited SARS-CoV-2 pseudovirus entry, with EC50 values of 0.1-10 M. Mechanistic studies showed that these compounds, reported as calcium channel blockers (CCBs), inhibited Ca2+-mediated membrane fusion and consequently suppressed coronavirus entry. These candidate drugs showed broad-spectrum efficacy against the entry of several coronavirus pseudotypes (SARS-CoV, MERS-CoV, SARS-CoV-2 [S-D614, S-G614, N501Y.V1 and N501Y.V2]) in different cell lines (293T, Calu-3, and A549). Antiviral tests using native SARS-CoV-2 in Vero E6 cells confirmed that four of the drugs (SC9/cepharanthine, SC161/hernandezine, SC171, and SC185/neferine) reduced cytopathic effect and supernatant viral RNA load. Among them, cepharanthine showed the strongest anti-SARS-CoV-2 activity. Collectively, this study offers new lead compounds for coronavirus antiviral drug discovery.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.13.422511", + "rel_abs": "Effective control of COVID-19 requires antivirals directed against SARS-CoV-2 virus. Here we assess ten available HCV protease inhibitor drugs as potential SARS-CoV-2 antivirals. There is a striking structural similarity of the substrate binding clefts of SARS- CoV-2 Mpro and HCV NS3/4A proteases, and virtual docking experiments show that all ten HCV drugs can potentially bind into the Mpro binding cleft. Seven of these HCV drugs inhibit SARS-CoV-2 Mpro protease activity, while four dock well into the PLpro substrate binding cleft and inhibit PLpro protease activity. These same seven HCV drugs inhibit SARS-CoV-2 virus replication in Vero and/or human cells, demonstrating that HCV drugs that inhibit Mpro, or both Mpro and PLpro, suppress virus replication. Two HCV drugs, simeprevir and grazoprevir synergize with the viral polymerase inhibitor remdesivir to inhibit virus replication, thereby increasing remdesivir inhibitory activity as much as 10-fold.\n\nHighlightsO_LISeveral HCV protease inhibitors are predicted to inhibit SARS-CoV-2 Mpro and PLpro.\nC_LIO_LISeven HCV drugs inhibit Mpro enzyme activity, four HCV drugs inhibit PLpro.\nC_LIO_LISeven HCV drugs inhibit SARS-CoV-2 replication in Vero and/or human cells.\nC_LIO_LIHCV drugs simeprevir and grazoprevir synergize with remdesivir to inhibit SARS- CoV-2.\nC_LI\n\neTOC blurbBafna, White and colleagues report that several available hepatitis C virus drugs inhibit the SARS-CoV-2 Mpro and/or PLpro proteases and SARS-CoV-2 replication in cell culture. Two drugs, simeprevir and grazoprevir, synergize with the viral polymerase inhibitor remdesivir to inhibit virus replication, increasing remdesivir antiviral activity as much as 10-fold.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=185 HEIGHT=200 SRC=\"FIGDIR/small/422511v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (35K):\norg.highwire.dtl.DTLVardef@1c12181org.highwire.dtl.DTLVardef@7ed993org.highwire.dtl.DTLVardef@1fe56aaorg.highwire.dtl.DTLVardef@ebc34e_HPS_FORMAT_FIGEXP M_FIG C_FIG", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Chang-Long He", - "author_inst": "Chongqing Medical University" + "author_name": "Khushboo Bafna", + "author_inst": "Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute" }, { - "author_name": "Lu-Yi Huang", - "author_inst": "Chongqing Medical University" + "author_name": "Kris White", + "author_inst": "Department of Microbiology, and Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Kai Wang", - "author_inst": "Chongqing Medical University" + "author_name": "Balasubramanian Harish", + "author_inst": "Department of Biology, Rensselaer Polytechnic Institute" }, { - "author_name": "Chen-Jian Gu", - "author_inst": "Fudan University" + "author_name": "Romel Rosales", + "author_inst": "Department of Microbiology, and Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Jie Hu", - "author_inst": "Chongqing Medical University" + "author_name": "Theresa A Ramelot", + "author_inst": "Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute" }, { - "author_name": "Gui-Ji Zhang", - "author_inst": "Chongqing Medical University" + "author_name": "Thomas B. Acton", + "author_inst": "Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute" }, { - "author_name": "Wei Xu", - "author_inst": "Fudan University" + "author_name": "Elena Moreno", + "author_inst": "Department of Microbiology, and Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "You-Hua Xie", - "author_inst": "Fudan University" + "author_name": "Thomas Kehrer", + "author_inst": "Department of Microbiology, and Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Ni Tang", - "author_inst": "Chongqing Medical University" + "author_name": "Catherine A. Royer", + "author_inst": "Department of Biology, Rensselaer Polytechnic Institute" }, { - "author_name": "Ai-Long Huang", - "author_inst": "Chongqing Medical University" + "author_name": "Adolfo Garcia-Sastre", + "author_inst": "Department of Microbiology, and Global Health and Emerging Pathogens Institute, Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Robert M Krug", + "author_inst": "Department of Molecular Biosciences, John Ring LaMontagne Center for Infectious Disease, Institute for Cellular and Molecular Biology, University of Texas at Au" + }, + { + "author_name": "Gaetano T. Montelione", + "author_inst": "Department of Chemistry and Chemical Biology, Rensselaer Polytechnic Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.12.12.422477", @@ -1049955,119 +1049289,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.08.20246314", - "rel_title": "Antibody landscape against SARS-CoV-2 proteome revealed significant differences between non-structural/ accessory proteins and structural proteins", + "rel_doi": "10.1101/2020.12.08.20238154", + "rel_title": "Bayesian back-calculation and nowcasting for line list data during the COVID-19 pandemic", "rel_date": "2020-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.08.20246314", - "rel_abs": "The immunogenicity of SARS-CoV-2 proteome is largely unknown, especially for non-structural proteins and accessory proteins. Here we collected 2,360 COVID-19 sera and 601 control sera. We analyzed these sera on a protein microarray with 20 proteins of SARS-CoV-2, built an antibody response landscape for IgG and IgM. We found that non-structural proteins and accessory proteins NSP1, NSP7, NSP8, RdRp, ORF3b and ORF9b elicit prevalent IgG responses. The IgG patterns and dynamic of non-structural/ accessory proteins are different from that of S and N protein. The IgG responses against these 6 proteins are associated with disease severity and clinical outcome and declined sharply about 20 days after symptom onset. In non-survivors, sharp decrease of IgG antibodies against S1 and N protein before death was observed. The global antibody responses to non-structural/ accessory proteins revealed here may facilitate deeper understanding of SARS-CoV-2 immunology.\n\nHighlightsO_LIAn antibody response landscape against SARS-CoV-2 proteome was constructed\nC_LIO_LINon-structural/accessory proteins elicit prevalent antibody responses but likely through a different mechanism to that of structural proteins\nC_LIO_LIIgG antibodies against non-structural/accessory proteins are more associated with disease severity and clinical outcome\nC_LIO_LIFor non-survivors, the levels of IgG antibodies against S1 and N decline significantly before death\nC_LI", - "rel_num_authors": 25, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.08.20238154", + "rel_abs": "Surveillance is the key of controling the COVID-19 pandemic, and it typically suffers from reporting delays and thus can be misleading. Previous methods for adjusting reporting delays are not particularly appropriate for line list data, which usually have lots of missing values that are non-ignorable for modeling reporting delays. In this paper, we develop a Bayesian approach that dynamically integrates imputation and estimation for line list data. We show this Bayesian approach lead to accurate estimates of the epidemic curve and time-varying reproductive numbers and is robust to deviations from model assumptions. We apply the Bayesian approach to a COVID-19 line list data in Massachusetts and find the reproductive number estimates correspond more closely to the control measures than the ones based on the reported curve.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Yang Li", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Zhaowei Xu", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Qing Lei", - "author_inst": "Huazhong University of Science and Technology" - }, - { - "author_name": "Danyun Lai", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Hongyan Hou", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Hewei Jiang", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "yunxiao Zheng", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Xuening Wang", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Jiaoxiang Wu", - "author_inst": "Tongren Hospital, Shanghai Jiao Tong University School of Medicine" - }, - { - "author_name": "Mingliang Ma", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Bo Zhang", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Hong Chen", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Caizheng Yu", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Junbiao Xue", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Nainang Zhang", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Huan Qi", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Shujuan Guo", - "author_inst": "Shanghai Jiao Tong University" - }, - { - "author_name": "Yandi Zhang", - "author_inst": "Huazhong University of Science and Technology" - }, - { - "author_name": "Xiaosong Lin", - "author_inst": "Huazhong University of Science and Technology" - }, - { - "author_name": "Zongjie Yao", - "author_inst": "Huazhong University of Science and Technology" - }, - { - "author_name": "Huiming Sheng", - "author_inst": "Tongren Hospital, Shanghai Jiao Tong University School of Medicine" - }, - { - "author_name": "Ziyong Sun", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Feng Wang", - "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Xionglin Fan", - "author_inst": "Huazhong University of Science and Technology" + "author_name": "Tenglong Li", + "author_inst": "Boston University" }, { - "author_name": "Sheng-ce Tao", - "author_inst": "Shanghai Jiao Tong University" + "author_name": "Laura F. White", + "author_inst": "Boston University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.11.29.20240515", @@ -1051805,27 +1051047,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.12.09.20246538", - "rel_title": "The trade-off between mobility and vaccination for COVID-19 control: a metapopulation modeling approach", + "rel_doi": "10.1101/2020.12.10.20244699", + "rel_title": "Will the COVID-19 pandemic lead to a tsunami of suicides? A Swedish nationwide analysis of historical and 2020 data", "rel_date": "2020-12-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.09.20246538", - "rel_abs": "November 2020 received a string of encouraging results from leading vaccine developers raising hopes for the imminent availability of an effective and safe vaccine against the SARS-CoV-2. In the present work, we discuss the theoretical impact of introducing a vaccine across a range of scenarios. In particular, we investigate how vaccination coverage, efficacy, and delivery time affect the control of the transmission dynamics in comparison to mobility restrictions. The analysis is based on a metapopulation epidemic model structured by risk. We perform a global sensitivity analysis using the Sobol method. Our analysis suggest that the reduction of mobility among patches play a significant role in the mitigation of the disease close to the effect of immunization coverage of 30% achieved in 4 months. Moreover, for an immunization coverage between 20%-50% achieved in the first half of 2021 with a vaccine efficacy between 70%-95%, the percentage reduction in the total number of SARS-CoV-2 infections is between 30%-50% by the end of 2021 in comparison with the no vaccination scenario.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.10.20244699", + "rel_abs": "BackgroundVarious surveys have documented a negative impact of the COVID-19 pandemic on the populations mental health. There is widespread concern about a surge of suicides, but evidence supporting a link between global pandemics and suicide is very limited. Using historical data from the three major influenza pandemics of the 20th century, and recently released data from the first half of 2020, we aimed to investigate whether an association exists between influenza deaths and suicide deaths.\n\nMethodsAnnual data on influenza death rates and suicide rates were extracted from the Statistical Yearbook of Sweden from 1910-1978, covering the three 20th century pandemics, and from Statistics Sweden for the period from January to June of each year during 2000-2020. COVID-19 death data were available for the first half of 2020. We implemented non-linear autoregressive distributed lag (NARDL) models to explore if there is a short-term and/or long-term effect of increases and decreases in influenza death rates on suicide rates during 1910-1978. Analyses were done separately for men and women. Descriptive analyses were used for the available 2020 data.\n\nFindingsBetween 1910-1978, there was no evidence of either short-term or long-term significant associations between influenza death rates and changes in suicides. The same pattern emerged in separate analyses for men and women. Suicide rates in January-June 2020 revealed a slight decrease compared to the corresponding rates in January-June 2019 (relative decrease by -1.2% among men and -12.8% among women).\n\nInterpretationWe found no evidence of short or long-term association between influenza death rates and suicide death rates across three 20th century pandemics or during the first six months of 2020 (when the first wave of COVID-19 occurred). Concerns about a substantial increase of suicides may be exaggerated. The media should be cautious when reporting news about suicides during the current pandemic.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Fernando Saldana", - "author_inst": "Universidad Nacional Autonoma de Mexico" + "author_name": "Christian Ruck", + "author_inst": "Karolinska Institutet" }, { - "author_name": "Jorge X. Velasco-Hernandez", - "author_inst": "Universidad Nacional Autonoma de Mexico" + "author_name": "David Mataix-Cols", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Kinda Malki", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Mats Adler", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Oskar Flygare", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Bo Runeson", + "author_inst": "Karolinska Institutet" + }, + { + "author_name": "Anna Sidorchuk", + "author_inst": "Karolinska Institutet" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.12.09.20246439", @@ -1053691,47 +1052953,31 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.12.11.416818", - "rel_title": "Duplex formation between the template and the nascent strand in the transcription-regulating sequences determines the site of template switching in SARS - CoV-2", + "rel_doi": "10.1101/2020.12.11.421784", + "rel_title": "Conformational Ensembles of Non-Coding Elements in the SARS-CoV-2 Genome from Molecular Dynamics Simulations", "rel_date": "2020-12-11", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.11.416818", - "rel_abs": "Recently published transcriptomic data of the SARS-CoV-2 coronavirus show that there is a large variation in the frequency and steady state levels of subgenomic mRNA sequences. This variation is derived from discontinuous subgenomic RNA synthesis where the polymerase switches template from a 3 proximal genome body sequence to a 5 untranslated leader sequence. This leads to a fusion between the common 5 leader sequence and a 3 proximal body sequence in the RNA product. This process revolves around a common core sequence (CS) that is present at both the template sites that make up the fusion junction. Base-pairing between the leader CS and the nascent complementary minus strand body CS, and flanking regions (together called the transcription regulating sequence, TRS) is vital for this template switching event. However, various factors can influence the site of template switching within the same TRS duplex. Here, we model the duplexes formed between the leader and complementary body TRS regions, hypothesising the role of the stability of the TRS duplex in determining the major sites of template switching for the most abundant mRNAs. We indicate that the stability of secondary structures and the speed of transcription play key roles in determining the probability of template switching in the production of subgenomic RNAs.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.11.421784", + "rel_abs": "The 5' untranslated region (UTR) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genome is a conserved, functional and structured genomic region consisting of several RNA stem-loop elements. While the secondary structure of such elements has been determined experimentally, their three-dimensional structures are not known yet. Here, we predict structure and dynamics of five RNA stem loops in the 5'-UTR of SARS-CoV-2 by extensive atomistic molecular dynamics simulations, more than 0.5ms of aggregate simulation time, in combination with enhanced sampling techniques. We compare simulations with available experimental data, describe the resulting conformational ensembles, and identify the presence of specific structural rearrangements in apical and internal loops that may be functionally relevant. Our atomic-detailed structural predictions reveal a rich dynamics in these RNA molecules, could help the experimental characterisation of these systems, and provide putative three-dimensional models for structure-based drug design studies.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Amanda B Buckingham", - "author_inst": "University of Cambridge, Department of Medicine, Level 5 Addenbrookes Hospital, Hills Rd, Cambridge, CB2 0QQ" - }, - { - "author_name": "Fanny Salasc", - "author_inst": "University of Cambridge Department of Medicine, Level 5 Addenbrookes Hospital, Hills Rd, Cambridge, CB2 0QQ" - }, - { - "author_name": "Gennaro Iaconis", - "author_inst": "University of Cambridge Department of Medicine, Level 5 Addenbrookes Hospital, Hills Rd, Cambridge, CB2 0QQ" - }, - { - "author_name": "Isobel Jarvis", - "author_inst": "University of Cambridge Department of Medicine, Level 5 Addenbrookes Hospital, Hills Rd, Cambridge, CB2 0QQ" - }, - { - "author_name": "Harriet C T Groom", - "author_inst": "University of Cambridge Department of Medicine, Level 5 Addenbrookes Hospital, Hills Rd, Cambridge, CB2 0QQ" + "author_name": "Sandro Bottaro", + "author_inst": "University of Copenhagen" }, { - "author_name": "Julia Kenyon", - "author_inst": "University of Cambridge Department of Medicine, Level 5 Addenbrookes Hospital, Hills Rd, Cambridge, CB2 0QQ" + "author_name": "Giovanni Bussi", + "author_inst": "Scuola Internazionale Superiore di Studi Avanzati" }, { - "author_name": "Andrew M L Lever", - "author_inst": "University of Cambridge Department of Medicine, Level 5 Addenbrookes Hospital, Hills Rd, Cambridge, CB2 0QQ" + "author_name": "Kresten Lindorff-Larsen", + "author_inst": "University of Copenhagen" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "biophysics" }, { "rel_doi": "10.1101/2020.12.11.421008", @@ -1055681,65 +1054927,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.08.20245910", - "rel_title": "SARS-CoV-2 infections in kindergartens and associated households at the start of the second wave in Berlin, Germany - a cross sectional study", + "rel_doi": "10.1101/2020.12.08.20245753", + "rel_title": "A novel multi-omics-based identification of symptoms, comorbid conditions, and possible long-term complications in COVID-19", "rel_date": "2020-12-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.08.20245910", - "rel_abs": "ObjectivesThe comparatively large proportion of asymptomatic SARS-CoV-2 infections in the youngest children opens up the possibility that kindergartens represent reservoirs of infection. However, actual surveys in kindergartens beyond individual outbreaks are rare. At the beginning of the second pandemic wave in Berlin, Germany, i.e., end of September 2020, we screened SARS-CoV-2 infections among kindergarten children, staff and connected household members.\n\nMethodsTwelve kindergartens were randomly selected in the Berlin metropolitan area, and a total of 720 participants were recruited (155 pre-school children, 78 staff, 487 household members). Participants were briefly examined and interviewed, and SARS-CoV-2 infections and anti-SARS-Cov-2 IgG antibodies were assessed.\n\nResultsSigns and symptoms, largely resembling common cold, were present in 24.2% of children and 28.9% of staff. However, no SARS-CoV-2 infection was detected among 701 PCR-tested individuals, and only one childcare worker showed IgG seroreactivity (0.15%; 1/672).\n\nConclusionsAgainst a backdrop of increased pandemic activity in the community, this cross-sectional study does not suggest that kindergartens are silent transmission reservoirs. Nevertheless, at increasing pandemic activity, reinforced precautionary measures and repeated routine testing appears advisable.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.08.20245753", + "rel_abs": "Till date the comprehensive clinical pictures, comorbid conditions, and long-term complications of COVID-19 are not known. Recently using a multi-omics-based strategy, we have predicted the drugs for COVID-19 management with [~]70% accuracy. Here, using a similar multi-omics-based bioinformatics approach and three-ways of analysis, we identified the symptoms, comorbid conditions, and short, mid and possible long-term complications of COVID-19 with [~]90% precision. In our analysis (i) we identified 27 parent, 170 child, and 403 specific conditions associated with COVID-19. (ii) Among the specific conditions, 36 are viral and 53 short-term, 62 short to mid to long-term, 194 mid to long-term, and 57 are congenital conditions. (iii) At a cut off \"count of occurrence\" of 4, we found [~] 90% of the enriched conditions are associated with COVID-19. (iv) Except the dry cough and loss of taste, all other COVID-19 associated mild and severe symptoms are enriched. (v) Cardiovascular, pulmonary, metabolic, musculoskeletal, neuropsychiatric, kidney, liver, and immune system disorders are found as top comorbid conditions. (vi) Specific diseases such as myocardial infarction, hypertension, COPD, lung injury, diabetes, cirrhosis, mood disorders, dementia, macular degeneration, chronic kidney disease, lupus, arthritis etc. along with several other diseases are also enriched as top candidates. (vii) Interestingly, many cancers and congenital disorders associated with COVID-19 severity are also identified. (viii) Arthritis, dermatomyositis, glioma, diabetes, psychiatric disorder, cardiovascular diseases having bidirectional relationship with COVID-19 are also found as top ranked conditions. Based on the accuracy ([~]90%) of this analysis, long presence of SARS-CoV-2 RNA in human, and our previously proposed \"genetic remittance\" assumption, we hypothesize that all the identified comorbid conditions including the short-long-mid and mid-long non-communicable diseases (NCDs) could also be long-term consequences in COVID-19 survivors and warrants long-term observational studies.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Marlene Thielecke", - "author_inst": "Charite Universitaetsmedizin Berlin, Institute of Tropical Medicine and International Health" - }, - { - "author_name": "Stefanie Theuring", - "author_inst": "Charite Universitaetsmedizin Berlin, Institute of Tropical Medicine and International Health" - }, - { - "author_name": "Welmoed van Loon", - "author_inst": "Charite Universitaetsmedizin Berlin, Institute of Tropical Medicine and International Health" - }, - { - "author_name": "Franziska Hommes", - "author_inst": "Charite Universitaetsmedizin Berlin, Institute of Tropical Medicine and International Health" - }, - { - "author_name": "Marcus A. Mall", - "author_inst": "Charite Universitaetsmedizin Berlin, Department of Pediatric Pulmonology, Immunology and Critical Care Medicine" - }, - { - "author_name": "Alexander Rosen", - "author_inst": "Charite Universitaetsmedizin Berlin, Department of Pediatric Pulmonology, Immunology and Critical Care Medicine" + "author_name": "Debmalya Barh", + "author_inst": "Institute of Integrative Omics and Applied Biotechnology (IIOAB)" }, { - "author_name": "Falko Boehringer", - "author_inst": "Labor Berlin Charite Vivantes Services GmbH" + "author_name": "Sandeep Tiwari", + "author_inst": "Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" }, { - "author_name": "Christof von Kalle", - "author_inst": "Charite Universitaetsmedizin Berlin, Clinical Study Center" + "author_name": "Bruno Silva Andrade", + "author_inst": "Universidade Estadual do Sudoeste da Bahia (UESB), Bahia, Brazil" }, { - "author_name": "Valerie Kirchberger", - "author_inst": "Charite Universitaetsmedizin Berlin, Medical Directorate" + "author_name": "Marianna E. Weener", + "author_inst": "Clinical Research Center, Oftalmic, CRO, 119334 Bardina str.22/4 Moscow, Russia" }, { - "author_name": "Tobias Kurth", - "author_inst": "Charite Universitaetsmedizin Berlin, Institute of Public Health" + "author_name": "Aristoteles Goes-Neto", + "author_inst": "Universidade Federal de Minas Gerais (UFMG), Belo Horizonte, Minas Gerais, Brazil" }, { - "author_name": "Joachim Seybold", - "author_inst": "Charite Universitaetsmedizin Berlin, Medical Directorate" + "author_name": "Vasco Azevedo", + "author_inst": "Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil" }, { - "author_name": "Frank P. Mockenhaupt", - "author_inst": "Charite Universitaetsmedizin Berlin, Institute of Tropical Medicine and International Health" + "author_name": "Preetam Ghosh", + "author_inst": "Virginia Commonwealth University, Richmond, VA, 23284, USA" }, { - "author_name": "- BECOSS Study Group", - "author_inst": "" + "author_name": "Nirmal Kumar Ganguly", + "author_inst": "Translational Health Science & Technology Institute, Faridabad, Haryana, India" } ], "version": "1", @@ -1057434,73 +1056660,37 @@ "category": "zoology" }, { - "rel_doi": "10.1101/2020.12.08.415836", - "rel_title": "Anti-SARS-CoV-2 activity of Andrographis paniculata extract and its major component Andrographolide in human lung epithelial cells and cytotoxicity evaluation in major organ cell representatives", + "rel_doi": "10.1101/2020.12.08.415018", + "rel_title": "Extended in vitro inactivation of SARS-CoV-2 by titanium dioxide surface coating", "rel_date": "2020-12-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.08.415836", - "rel_abs": "The coronavirus disease 2019 (COVID-19) caused by a novel coronavirus (SARS-CoV-2) has become a major health problem affecting more than fifty million cases with over one million deaths globally. The effective antivirals are still lacking. Here, we optimized a high-content imaging platform and the plaque assay for viral output study using the legitimate model of human lung epithelial cells, Calu-3, to determine anti-SARS-CoV-2 activity of Andrographis paniculata extract and its major component andrographolide. SARS-CoV-2 at 25TCID50 was able to reach the maximal infectivity of 95% in Calu-3 cells. Post-infection treatment of A. paniculata and andrographolide in SARS-CoV-2 infected Calu-3 cells significantly inhibited the production of infectious virions with the IC50 of 0.036 g/mL and 0.034 M, respectively, as determined by plaque assay. The cytotoxicity profile developed over the cell line representatives of major organs, including liver (HepG2 and imHC), kidney (HK-2), intestine (Caco-2), lung (Calu-3) and brain (SH-SY5Y), showed the CC50 of >100 g/mL for A. paniculata extract and 13.2-81.5 M for andrographolide, respectively, corresponding to the selectivity index over 380. In conclusion, this study provided experimental evidence in favor of A. paniculata and andrographolide for further development as a monotherapy or in combination with other effective drugs against SARS-CoV-2 infection.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.08.415018", + "rel_abs": "SARS-CoV-2 transmission occurs via airborne droplets and surface contamination. We show tiles coated with TiO2 120 days previously can inactivate SARS-CoV-2 under ambient indoor lighting with 87% reduction in titres at 1h and complete loss by 5h exposure. TiO2 coatings could be an important tool in containing SARS-CoV-2.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Khanit Sa-ngiamsuntorn", - "author_inst": "Department of Biochemistry, Faculty of Pharmacy, Mahidol University, Bangkok 10400, Thailand." - }, - { - "author_name": "Ampa Suksatu", - "author_inst": "Department of Microbiology, Faculty of Science, Mahidol University, Bangkok 10400 Thailand" - }, - { - "author_name": "Yongyut Pewkliang", - "author_inst": "Section for Translational Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand" - }, - { - "author_name": "Piyanoot Thongsri", - "author_inst": "Section for Translational Medicine, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand" - }, - { - "author_name": "Phongthon Kanjanasirirat", - "author_inst": "Excellent Center for Drug Discovery (ECDD), Faculty of Science, Mahidol University, Bangkok, 10400, Thailand" - }, - { - "author_name": "Suwimon Manopwisedjaroen", - "author_inst": "Department of Microbiology, Faculty of Science, Mahidol University, Bangkok 10400 Thailand" - }, - { - "author_name": "Sitthivut Charoensutthivarakul", - "author_inst": "School of Bioinnovation and Bio Based Product Intelligence, Faculty of Science, Mahidol University, Bangkok 10400, Thailand" - }, - { - "author_name": "Patompon Wongtrakoongate", - "author_inst": "Department of Biochemistry, Faculty of Science, Mahidol University, Bangkok 10400, Thailand" - }, - { - "author_name": "Supaporn Pitiporn", - "author_inst": "ChaoPhya Abhaibhubejhr Hospital, Prachin Buri 25000, Thailand" - }, - { - "author_name": "Phisit Khemawoot", - "author_inst": "Chakri Naruebodindra Medical Institute, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Samutprakarn 10540 Thailand" + "author_name": "Petra Mlcochova", + "author_inst": "University of Cambridge" }, { - "author_name": "Somchai Chutipongtanate", - "author_inst": "Department of Pediatrics, Faculty of Medicine Ramathibodi Hospital, Mahidol University" + "author_name": "Ambika Chadha", + "author_inst": "Cambridge University Hospitals NHS Trust" }, { - "author_name": "Suparerk Borwornpinyo", - "author_inst": "Department of Biotechnology, Faculty of Science, Mahidol University, Bangkok 10400, Thailand" + "author_name": "Timi Hesselhoj", + "author_inst": "Invisismart Technologies" }, { - "author_name": "Arunee Thitithanyanont", - "author_inst": "Department of Microbiology, Faculty of Science, Mahidol University, Bangkok 10400 Thailand" + "author_name": "Jeremy Ramsden", + "author_inst": "University of Buckingham" }, { - "author_name": "Suradej Hongeng", - "author_inst": "Department of Pediatrics, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok 10400, Thailand" + "author_name": "Ravindra K Gupta", + "author_inst": "University of Cambridge" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", "category": "microbiology" }, @@ -1058787,73 +1057977,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.12.05.20244673", - "rel_title": "Handling and accuracy of four rapid antigen tests for the diagnosis of SARS-CoV-2 compared to RT-qPCR.", + "rel_doi": "10.1101/2020.12.07.20245241", + "rel_title": "Lack of antibodies against seasonal coronavirus OC43 nucleocapsid protein identifies patients at risk of critical COVID-19", "rel_date": "2020-12-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.05.20244673", - "rel_abs": "BackgroundSARS-CoV-2 molecular diagnostics is facing material shortages and long turnaround times due to exponential increase of testing demand.\n\nObjectiveWe evaluated the analytic performance and handling of four rapid Antigen Point of Care Tests (AgPOCTs) I-IV (Distributors: (I) Roche, (II) Abbott, (III) MEDsan and (IV) Siemens).\n\nMethods100 RT-PCR negative and 84 RT-PCR positive oropharyngeal swabs were prospectively collected and used to determine performance and accuracy of these AgPOCTs. Handling was evaluated by 10 healthcare workers/users through a questionnaire.\n\nResultsThe median duration from symptom onset to sampling was 6 days (IQR 2-12 days). The overall relative sensitivity was 49.4%, 44.6%, 45.8% and 54.9 % for tests I, II, III and IV, respectively. In the high viral load subgroup (containing >106 copies of SARS-CoV-2 /swab, n=26), AgPOCTs reached sensitivities of 92.3% or more (range 92.3%-100%). Specificity was 100% for tests I, II and IV and 97% for test III. Regarding handling, test I obtained the overall highest scores, while test II was considered to have the most convenient components. Of note, users considered all assays, with the exception of test I, to pose a significant risk for contamination by drips or spills.\n\nDiscussionBesides some differences in sensitivity and handling, all four AgPOCTs showed acceptable performance in high viral load samples. However, due to the significantly lower sensitivity compared to RT-qPCR, a careful consideration of pro and cons of AgPOCT has to be taken into account before clinical implementation.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.07.20245241", + "rel_abs": "Most COVID-19 patients experience a mild disease; a minority suffers from critical disease.\n\nWe report about a biomarker validation study regarding 296 patients with confirmed SARS-CoV-2 infections from four tertiary care referral centers in Germany and France.\n\nPatients with critical disease had significantly less anti-HCoV OC43 nucleocapsid protein antibodies compared to other COVID-19 patients (p=0.007). In multivariate analysis, OC43 negative inpatients had an increased risk of critical disease, higher than the risk by increased age or BMI, and lower than the risk by male sex. A risk stratification based on sex and OC43 serostatus was derived from this analysis.\n\nOur results indicate that prior infections with seasonal human coronaviruses can protect against a severe course of COVID-19. Anti-OC43 antibodies should be measured for COVID-19 inpatients and considered as part of the risk assessment. We expect individuals tested negative for anti-OC43 antibodies to particularly benefit from vaccination, especially with other risk factors prevailing.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Flaminia Olearo", - "author_inst": "University Medical Center Hamburg-Eppendorf, Hamburg, Germany" + "author_name": "Martin Dugas", + "author_inst": "University of Muenster" }, { - "author_name": "Dominik Noerz", - "author_inst": "University Medical Center Hamburg-Eppendorf" + "author_name": "Tanja Grote-Westrick", + "author_inst": "Institute of Virology, Department of Clinical Virology, University Hospital Muenster, Germany" }, { - "author_name": "Fabian Heinrich", - "author_inst": "University Medical Center Hamburg-Eppendorf, Hamburg, Germany" + "author_name": "Uta Merle", + "author_inst": "Medizinische Klinik, Abteilung Innere Medizin IV, University Hospital Heidelberg, Germany" }, { - "author_name": "Jan Peter Sutter", - "author_inst": "University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany" + "author_name": "Michaela Fontenay", + "author_inst": "Assistance Publique-Hopitaux de Paris, AP-HP. Centre-Universite de Paris, Hopital Cochin, Service d'hematologie biologique, Paris, France" }, { - "author_name": "Kevin Roedel", - "author_inst": "University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany" + "author_name": "Andreas E. Kremer", + "author_inst": "Department of Medicine 1, University Hospital Erlangen and Friedrich-Alexander-University Erlangen-Nuernberg, Erlangen, Germany" }, { - "author_name": "Alexander Schultze", - "author_inst": "University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany" + "author_name": "Frank Hanses", + "author_inst": "Emergency Department, University Hospital Regensburg, Germany" }, { - "author_name": "Julian Schulze Zur Wiesch", - "author_inst": "University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany" + "author_name": "Richard Vollenberg", + "author_inst": "Medizinische Klinik B (Gastroenterologie, Hepatologie, Endokrinologie, Klinische Infektiologie), University Hospital Muenster, Germany" }, { - "author_name": "Platon Braun", - "author_inst": "University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany" + "author_name": "Eva Lorentzen", + "author_inst": "Institute of Virology, Department of Clinical Virology, University Hospital Muenster, Germany" }, { - "author_name": "Lisa Oesterreich", - "author_inst": "Department of Tropical Medicine, Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany" + "author_name": "Shilpa Tiwari-Heckler", + "author_inst": "Medizinische Klinik, Abteilung Innere Medizin IV, University Hospital Heidelberg, Germany" }, { - "author_name": "Benno Kreuels", - "author_inst": "University Medical Center Hamburg-Eppendorf, Hamburg, Germany" + "author_name": "Jerome Duchemin", + "author_inst": "Assistance Publique-Hopitaux de Paris, AP-HP. Centre-Universite de Paris, Hopital Cochin, Service d'hematologie biologique, Paris, France" }, { - "author_name": "Dominic Wichmann", - "author_inst": "University Medical Center Hamburg-Eppendorf, Hamburg, Germany" + "author_name": "Syrine Ellouze", + "author_inst": "Assistance Publique-Hopitaux de Paris, AP-HP. Centre-Universite de Paris, Hopital Cochin, Service d'hematologie biologique, Paris, France" }, { - "author_name": "Martin Aepfelbacher", - "author_inst": "University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany" + "author_name": "Marcel Vetter", + "author_inst": "Department of Medicine 1, University Hospital Erlangen and Friedrich-Alexander-University Erlangen-Nuernberg, Erlangen, Germany" }, { - "author_name": "Susanne Pfefferle", - "author_inst": "University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany" + "author_name": "Julia Fuerst", + "author_inst": "Department of Medicine 1, University Hospital Erlangen and Friedrich-Alexander-University Erlangen-Nuernberg, Erlangen, Germany" }, { - "author_name": "Marc Luetgehetmann", - "author_inst": "University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany" + "author_name": "Philipp Schuster", + "author_inst": "Institute of Medical Microbiology and Hygiene, University of Regensburg, Regensburg, Germany" + }, + { + "author_name": "Tobias Brix", + "author_inst": "Institute of Medical Informatics, University of Muenster, Germany" + }, + { + "author_name": "Claudia M. Denkinger", + "author_inst": "Division of Tropical Medicine, Center of Infectious Diseases, University Hospital Heidelberg, Germany" + }, + { + "author_name": "Carsten Mueller-Tidow", + "author_inst": "Medizinische Klinik, Abteilung Innere Medizin V, University Hospital Heidelberg, Germany" + }, + { + "author_name": "Hartmut Schmidt", + "author_inst": "Medizinische Klinik B (Gastroenterologie, Hepatologie, Endokrinologie, Klinische Infektiologie), University Hospital Muenster, Germany" + }, + { + "author_name": "Phil-Robin Tepasse", + "author_inst": "Medizinische Klinik B (Gastroenterologie, Hepatologie, Endokrinologie, Klinische Infektiologie), University Hospital Muenster, Germany" + }, + { + "author_name": "Joachim Kuehn", + "author_inst": "Institute of Virology, Department of Clinical Virology, University Hospital Muenster, Germany" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1060433,103 +1059647,107 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.12.04.410092", - "rel_title": "Ribavirin shows antiviral activity against SARS-CoV-2 and downregulates the activity of TMPRSS2 and the expression of ACE2 in vitro", + "rel_doi": "10.1101/2020.12.04.412155", + "rel_title": "Chromatin remodeling in peripheral blood cells reflects COVID-19 symptom severity", "rel_date": "2020-12-05", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.04.410092", - "rel_abs": "Ribavirin is a guanosine analog and has a broad-spectrum antiviral activity against RNA viruses. Based on this, we aimed to show the anti-SARS-CoV-2 activity of this drug molecule via in vitro, in silico and molecular techniques. Ribavirin showed antiviral activity in Vero E6 cells following SARS-CoV-2 infection. In silico analysis suggested that Ribarivin has a broad-spectrum impact on Vero E6 cells. According to the detailed molecular techniques, Ribavirin was shown to decrease TMPRSS2 expression both at mRNA and protein level 48 hours after treatment. The suppressive effect of Ribavirin in ACE2 protein expression was shown to be dependent on cell types. Finally, proteolytic activity assays showed that Ribavirin also showed an inhibitory effect on TMPRSS2 enzyme. As a conclusion, Ribavirin is a potential antiviral drug for the treatment against SARS-CoV-2, and it interferes with the effect of TMPRSS2 and ACE2 expression.", - "rel_num_authors": 21, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.04.412155", + "rel_abs": "SARS-CoV-2 infection triggers highly variable host responses and causes varying degrees of illness in humans. We sought to harness the peripheral blood mononuclear cell (PBMC) response over the course of illness to provide insight into COVID-19 physiology. We analyzed PBMCs from subjects with variable symptom severity at different stages of clinical illness before and after IgG seroconversion to SARS-CoV-2. Prior to seroconversion, PBMC transcriptomes did not distinguish symptom severity. In contrast, changes in chromatin accessibility were associated with symptom severity. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif occupancy for individual PBMC cell types. The most extensive remodeling occurred in CD14+ monocytes where sub-populations with distinct chromatin accessibility profiles were associated with disease severity. Our findings indicate that pre-seroconversion chromatin remodeling in certain innate immune populations is associated with divergence in symptom severity, and the identified transcription factors, regulatory elements, and downstream pathways provide potential prognostic markers for COVID-19 subjects.\n\nOne sentence summaryChromatin accessibility in immune cells from COVID-19 subjects is remodeled prior to seroconversion to reflect disease severity.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Mehmet Altay Unal", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Nicholas S. Giroux", + "author_inst": "Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA" }, { - "author_name": "Ceylan Verda Bitirim", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Shengli Ding", + "author_inst": "Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA" }, { - "author_name": "Gokce Yagmur Summak", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Micah T. McClain", + "author_inst": "Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USA" }, { - "author_name": "Sidar Bereketoglu", - "author_inst": "Ankara University, Faculty of Science, Department of Biology" + "author_name": "Thomas W. Burke", + "author_inst": "Center for Applied Genomics and Precision Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Inci Cevher Zeytin", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Elizabeth W. Petzold", + "author_inst": "Center for Applied Genomics and Precision Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Omur Besbinar", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Hong A. Chung", + "author_inst": "Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA" }, { - "author_name": "Cansu Gurcan", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Grecia R. Palomino", + "author_inst": "Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA" }, { - "author_name": "Dunya Aydos", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Ergang Wang", + "author_inst": "Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA" }, { - "author_name": "Ezgi Goksoy", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Rui Xi", + "author_inst": "Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA" }, { - "author_name": "Ebru Kocakaya", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Shree Bose", + "author_inst": "Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA" }, { - "author_name": "Zeynep Eran", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Tomer Rotstein", + "author_inst": "Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA" }, { - "author_name": "Merve Murat", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Bradly P. Nicholson", + "author_inst": "Institute for Medical Research, Durham, NC, USA" }, { - "author_name": "Nil Demir", - "author_inst": "Ankara University Stem Cell Institute" + "author_name": "Tianyi Chen", + "author_inst": "Department of Molecular Genetics and Microbiology, School of Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Julia Somers", - "author_inst": "Oregon Health & Sciences Univerity Department of Molecular and Medical Genetics" + "author_name": "Ricardo Henao", + "author_inst": "Center for Applied Genomics and Precision Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Emek Demir", - "author_inst": "Oregon Health & Sciences Univerity Department of Molecular and Medical Genetics" + "author_name": "Gregory D. Sempowski", + "author_inst": "Duke Human Vaccine Institute and Department of Medicine, School of Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Hasan Nazir", - "author_inst": "Ankara University, Faculty of Science, Department of Chemistry" + "author_name": "Thomas N. Denny", + "author_inst": "Duke Human Vaccine Institute and Department of Medicine, School of Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Sibel Aysil Ozkan", - "author_inst": "Ankara University, Faculty of Pharmacy, Department of Analytical Chemistry" + "author_name": "Emily R. Ko", + "author_inst": "Center for Applied Genomics and Precision Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Aykut Ozkul", - "author_inst": "Ankara University, Faculty of Veterinary, Department of Virology" + "author_name": "Geoffrey S. Ginsburg", + "author_inst": "Center for Applied Genomics and Precision Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Alpay Azap", - "author_inst": "Ankara University, School of Medicine, Department of Infectious Diseases and Clinical Microbiology" + "author_name": "Bryan D. Kraft", + "author_inst": "Center for Applied Genomics and Precision Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Acelya Yilmazer", - "author_inst": "Ankara University Stem Cell Institute; Ankara University, Faculty of Engineering, Department of Biomedical Engineering" + "author_name": "Ephraim L. Tsalik", + "author_inst": "Center for Applied Genomics and Precision Medicine, Duke University, Durham, NC, USA" }, { - "author_name": "Kamil Can Akcali", - "author_inst": "Ankara University Stem Cell Institute; Ankara University, School of Medicine, Department of Biophysics" + "author_name": "Christopher W. Woods", + "author_inst": "Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USA" + }, + { + "author_name": "Xiling Shen", + "author_inst": "Department of Biomedical Engineering, Pratt School of Engineering, Duke University, Durham, NC, USA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "pharmacology and toxicology" + "category": "genomics" }, { "rel_doi": "10.1101/2020.12.04.411744", @@ -1062363,35 +1061581,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.12.03.20243345", - "rel_title": "Long Covid and the role of physical activity: a qualitative study", + "rel_doi": "10.1101/2020.12.03.20243550", + "rel_title": "The application of Hybrid deep learning Approach to evaluate chest ray images for the diagnosis of pneumonia in children", "rel_date": "2020-12-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.03.20243345", - "rel_abs": "ObjectivesTo explore the lived experience of Long Covid with particular focus on the role of physical activity\n\nDesignQualitative study using semi-structured interviews\n\nParticipants18 people living with Long Covid (9 male, 9 female; aged between 18-74; 10 White British, 3 White Other, 3 Asian, 1 Black, 1 mixed ethnicity) recruited via a UK-based research interest database for people with Long Covid\n\nSettingTelephone interviews with 17 participants living in the UK and 1 participant living in the US\n\nResultsFour themes were generated. Theme one highlights the physical and social isolation experienced by people with Long Covid, compounded by a lack of support and advice from medical professionals. Theme two describes how participants sought information and validation through online sources and communities. Theme three captures the challenges associated with managing physical and cognitive effects of Long Covid including fatigue and brain fog whilst trying to resume and maintain activities of daily living and other forms of exercise. Theme four illustrates the battle with self-concept to accept reduced function (even temporarily) and the fear of permanent reduction in physical and cognitive ability.\n\nConclusionsThis study provides insight into the challenges of managing physical activity alongside the extended symptoms associated with Long Covid. Findings highlight the need for greater consensus around physical activity-related advice for people with Long Covid and improved support to resume activities considered important for wellbeing.\n\nArticle Summary\n\nStrengths and limitations of this studyO_LITo our knowledge, this paper is the first to explore the role of physical activity in the lived experience of Long Covid using a qualitative approach\nC_LIO_LIThe study design enabled in-depth inquiry of lived experiences in a diverse sample\nC_LIO_LIInductive thematic analysis ensured descriptions and interpretations of the lived experience were tested and found to be grounded in the data\nC_LIO_LIParticipants were recruited from members of a Long Covid research interest database who registered via an on-line form, meaning study findings might not capture the views of digitally excluded populations\nC_LI\n\nFunding statementThis work was supported by Sheffield Hallam University.\n\nCompeting interestsAll authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organization for the submitted work; no financial relationships with any organizations that might have an interest in the submitted work in the previous three years; no other relationships or activities that could appear to have influenced the submitted work.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.03.20243550", + "rel_abs": "BackgroundPneumonia is a leading cause of morbidity and mortality worldwide, particularly among the developing nations. Pneumonia is the most common cause of death in children due to infectious etiology. Early and accurate Pneumonia diagnosis could play a vital role in reducing morbidity and mortality associated with this ailment. In this regard, the application of a new hybrid machine learning vision-based model may be a useful adjunct tool that can predict Pneumonia from chest X-ray (CXR) images.\n\nAim & Objectivewe aimed to assess the diagnostic accuracy of hybrid machine learning vision-based model for the diagnosis of Pneumonia by evaluating chest X-ray (CXR) images\n\nMaterials & MethodsA total of five thousand eight hundred and fifty-six digital X-ray images of children from ages one to five were obtained from the Chest X-Ray Pneumonia dataset using the Kaggle site. The dataset contains fifteen hundred and eighty-three digital X-ray images categorized as normal, where four thousand two hundred and seventy-three digital X-ray images are categorized as Pneumonia by an expert clinician. In this research project, a new hybrid machine learning vision-based model has been evaluated that can predict Pneumonia from chest X-ray (CXR) images. The proposed model is a hybrid of convolutional neural network and tree base algorithms (random forest and light gradient boosting machine). In this study, a hybrid architecture with four variations and two variations of ResNet architecture are employed, and a comparison is made between them.\n\nResultsIn the present study, the analysis of digital X-ray images by four variations of hybrid architecture RN-18 RF, RN-18 LGBM, RN-34 RF, and RN-34 LGBM, along with two variations of ResNet architecture, ResNet-18 and ResNet-30 have revealed the diagnostic accuracy of 97.78%, 96.42%, 97.1%,96.59%, 95.05%, and 95.05%, respectively.\n\nDiscussionThe analysis of the present study results revealed more than 95% diagnostic accuracy for the diagnosis of Pneumonia by evaluating chest x-ray images of children with the help of four variations of hybrid architectures and two variations of ResNet architectures. Our findings are in accordance with the other published study in which the author used the deep learning algorithm Chex-Net with 121 layers.\n\nConclusionThe hybrid machine learning vision-based model is a useful tool for the assessment of chest x rays of children for the diagnosis of Pneumonia.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Helen Humphreys", - "author_inst": "Sheffield Hallam University" + "author_name": "Mohammad Ali Abbasa", + "author_inst": "Department of Computer Science, University of Lahore, Islamabad, Pakistan" }, { - "author_name": "Laura Kilby", - "author_inst": "Sheffield Hallam University" + "author_name": "Syed Usama Khalid Bukhari", + "author_inst": "The University of Lahore" }, { - "author_name": "Nik Kudiersky", - "author_inst": "Sheffield Hallam University" + "author_name": "Syed Khuzaima Arssalan Bokhari", + "author_inst": "Pediatric medicine, Doctors hospital, Lahore, Pakistan" }, { - "author_name": "Robert Copeland", - "author_inst": "Sheffield Hallam University" + "author_name": "manal niazi", + "author_inst": "Radiology department, Islamabad medical and dental college, Islamabad, Pakistan" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2020.12.03.20243543", @@ -1063929,203 +1063147,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.30.20239095", - "rel_title": "Establishment of CORONET; COVID-19 Risk in Oncology Evaluation Tool to identify cancer patients at low versus high risk of severe complications of COVID-19 infection upon presentation to hospital", + "rel_doi": "10.1101/2020.12.01.20241828", + "rel_title": "Accuracy of automated computer aided-risk scoring systems to estimate the risk of COVID-19 and in-hospital mortality: a retrospective cohort study", "rel_date": "2020-12-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.30.20239095", - "rel_abs": "BackgroundCancer patients are at increased risk of severe COVID-19. As COVID-19 presentation and outcomes are heterogeneous in cancer patients, decision-making tools for hospital admission, severity prediction and increased monitoring for early intervention are critical.\n\nObjectiveTo identify features of COVID-19 in cancer patients predicting severe disease and build a decision-support online tool; COVID-19 Risk in Oncology Evaluation Tool (CORONET)\n\nMethodData was obtained for consecutive patients with active cancer with laboratory confirmed COVID-19 presenting in 12 hospitals throughout the United Kingdom (UK). Univariable logistic regression was performed on pre-specified features to assess their association with admission ([≥]24 hours inpatient), oxygen requirement and death. Multivariable logistic regression and random forest models (RFM) were compared with patients randomly split into training and validation sets. Cost function determined cut-offs were defined for admission/death using RFM. Performance was assessed by sensitivity, specificity and Brier scores (BS). The CORONET model was then assessed in the entire cohort to build the online CORONET tool.\n\nResultsTraining and validation sets comprised 234 and 66 patients respectively with median age 69 (range 19-93), 54% males, 46% females, 71% vs 29% had solid and haematological cancers. The RFM, selected for further development, demonstrated superior performance over logistic regression with AUROC predicting admission (0.85 vs. 0.78) and death (0.76 vs. 0.72). C-reactive protein was the most important feature predicting COVID-19 severity. CORONET cut-offs for admission and mortality of 1.05 and 1.8 were established. In the training set, admission prediction sensitivity and specificity were 94.5% and 44.3% with BS 0.118; mortality sensitivity and specificity were 78.5% and 57.2% with BS 0.364. In the validation set, admission sensitivity and specificity were 90.7% and 42.9% with BS 0.148; mortality sensitivity and specificity were 92.3% and 45.8% with BS 0.442. In the entire cohort, the CORONET decision support tool recommended admission of 99% of patients requiring oxygen and of 99% of patients who died.\n\nConclusions and RelevanceCORONET, a decision support tool validated in hospitals throughout the UK showed promise in aiding decisions regarding admission and predicting COVID-19 severity in patients with cancer presenting to hospital. Future work will validate and refine the tool in further datasets.", - "rel_num_authors": 46, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.12.01.20241828", + "rel_abs": "ObjectivesAlthough a set of computer-aided risk scoring systems (CARSS), that use the National Early Warning Score and routine blood tests results, have been validated for predicting in-hospital mortality and sepsis in unplanned admission to hospital, little is known about their performance for COVID-19 patients. We compare the performance of CARSS in unplanned admissions with COVID-19 during the first phase of the pandemic.\n\nDesigna retrospective cross-sectional study\n\nSettingTwo acute hospitals (Scarborough and York) are combined into a single dataset and analysed collectively.\n\nParticipantsAdult (>=18 years) non-elective admissions discharged between 11-March-2020 to 13-June-2020 with an index NEWS electronically recorded within {+/-}24 hours. We assessed the performance of all four risk score (for sepsis: CARS_N, CARS_NB; for mortality: CARM_N, CARM_NB) according to discrimination (c-statistic) and calibration (graphically) in predicting the risk of COVID-19 and in-hospital mortality.\n\nResultsThe risk of in-hospital mortality following emergency medical admission was 8.4% (500/6444) and 9.6% (620/6444) had a diagnosis of COVID-19. For predicting COVID-19 admissions, the CARS_N model had the highest discrimination 0.73 (0.71 to 0.75) and calibration slope 0.81 (0.72 to 0.89). For predicting in-hospital mortality, the CARM_NB model had the highest discrimination 0.84 (0.82 to 0.75) and calibration slope 0.89 (0.81 to 0.98).\n\nConclusionsTwo of the computer-aided risk scores (CARS_N and CARM_NB) are reasonably accurate for predicting the risk of COVID-19 and in-hospital mortality, respectively. They may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions because they are automated and require no additional data collection.\n\nArticle SummaryO_LIIn this study, we found that two of the automated computer-aided risk scores are reasonably accurate for predicting the risk of COVID-19 and in-hospital mortality, respectively.\nC_LIO_LIThey may be clinically useful as an early warning system at the time of admission especially to triage large numbers of unplanned hospital admissions because they are automated and require no additional data collection.\nC_LIO_LIAlthough we focused on in-hospital mortality (because we aimed to aid clinical decision making in the hospital), the impact of this selection bias needs to be assessed by capturing out-of-hospital mortality by linking death certification data and hospital data.\nC_LIO_LIWe identified COVID-19 based on ICD-10 code U071 which was determined by COVID-19 swab test results (hospital or community) and clinical judgment and so our findings are constrained by the accuracy of these methods\nC_LI", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Rebecca J Lee Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX; The University of Manchester, Oxford road, M13 9PL" - }, - { - "author_name": "Cong Zhou Dr", - "author_inst": ". Digital experimental cancer medicine and Bioinformatics and Biostatistics teams, Cancer Research UK Manchester Institute Cancer Biomarker Centre, The Universi" - }, - { - "author_name": "Oskar Wysocki Dr", - "author_inst": "The University of Manchester, Oxford road, M13 9PL; Digital experimental cancer medicine team, Manchester Centre for Cancer Biomarker Sciences, Alderley Park, S" - }, - { - "author_name": "Rohan Shotton Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX" - }, - { - "author_name": "Ann Tivey Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX" - }, - { - "author_name": "Louise Lever Dr", - "author_inst": "The University of Manchester, Oxford road, M13 9PL" - }, - { - "author_name": "Joshua Woodcock Dr", - "author_inst": "The University of Manchester, Oxford road, M13 9PL" - }, - { - "author_name": "Angelos Angelakas Dr", - "author_inst": "University Hospitals of Morecambe Bay, Kendal LA9 7RG" - }, - { - "author_name": "Theingi Aung Dr", - "author_inst": "Weston Park Cancer Centre, Sheffield Teaching Hospitals NHS foundation Trust, Sheffield S10 2JF" - }, - { - "author_name": "Kathryn Banfill Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX; The University of Manchester, Oxford road, M13 9PL" - }, - { - "author_name": "Mark Baxter Dr", - "author_inst": "University of Dundee, Dundee DD1 4HN" - }, - { - "author_name": "Talvinder Bhogal Dr", - "author_inst": "The Clatterbridge Cancer Centre NHS Foundation Trust, Liverpool, UK" - }, - { - "author_name": "Hayley Boyce Dr", - "author_inst": "Weston Park Cancer Centre, Sheffield Teaching Hospitals NHS foundation Trust, Sheffield S10 2JF" - }, - { - "author_name": "Ellen Copson Dr", - "author_inst": "Cancer Sciences Academic Unit, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD" - }, - { - "author_name": "Elena Dickens Dr", - "author_inst": "Oncology Department, University Hospitals of Leicester NHS Trust, Leicester, LE1 5WW" - }, - { - "author_name": "Leonie Eastlake Dr", - "author_inst": "University Hospitals Plymouth NHS Trust, Plymouth, PL6 8DH" - }, - { - "author_name": "Hannah Frost Ms", - "author_inst": ". Digital experimental cancer medicine and Bioinformatics and Biostatistics teams, Cancer Research UK Manchester Institute Cancer Biomarker Centre, The Universi" - }, - { - "author_name": "Fabio Gomes Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX" - }, - { - "author_name": "Donna Graham Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX" - }, - { - "author_name": "Christina Hague Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX" - }, - { - "author_name": "Michelle Harrison Dr", - "author_inst": "Ninewells Hospital, Dundee DD2 1SG" - }, - { - "author_name": "Laura Horsley Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX" - }, - { - "author_name": "Prerana Huddar Dr", - "author_inst": "Lancashire Teaching Hospitals NHS Trust, Preston PR2 9HT" - }, - { - "author_name": "Zoe Hudson Dr", - "author_inst": "Bristol Haematology and Oncology Centre, Bristol BS2 8ED" - }, - { - "author_name": "Sam Khan Dr", - "author_inst": "Oncology Department, University Hospitals of Leicester NHS Trust, Leicester, LE1 5WW; Leicester Cancer Research Centre, University of Leicester, Leicester, LE2 " - }, - { - "author_name": "Umair T Khan Dr", - "author_inst": "Clatterbridge Cancer Centre, 65 Pembroke Place, Liverpool, L7 8YA; The University of Liverpool, Liverpool, L69 3BX" - }, - { - "author_name": "Alec Maynard Dr", - "author_inst": "Sheffield Teaching Hospitals NHS foundation Trust, Sheffield S10 2JF" - }, - { - "author_name": "Hayley McKenzie Dr", - "author_inst": "Cancer Sciences Academic Unit, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton SO16 6YD" - }, - { - "author_name": "Tim Robinson Dr", - "author_inst": "Bristol Haematology and Oncology Centre, Bristol BS2 8ED" - }, - { - "author_name": "Michael Rowe Dr", - "author_inst": "Sunrise Centre, Royal Cornwall Hospital, Truro, Cornwall, TR1 3LJ" - }, - { - "author_name": "Anne Thomas Prof", - "author_inst": "Oncology Department, University Hospitals of Leicester NHS Trust, Leicester, LE1 5WW; Leicester Cancer Research Centre, University of Leicester, Leicester, LE2 " - }, - { - "author_name": "Lance Turtle", - "author_inst": "Institute of Infection, Ecological and Veterinary Sciences, University of Liverpool and Tropical and Infectious Diseases Unit, Liverpool University Hospitals" - }, - { - "author_name": "Roseleen Sheehan Dr", - "author_inst": "Sheffield Teaching Hospitals NHS foundation Trust, Sheffield S10 2JF" - }, - { - "author_name": "Alexander Stockdale", - "author_inst": "Institute of Infection, Ecological and Veterinary Sciences, University of Liverpool and Tropical and Infectious Diseases Unit, Liverpool University Hospitals" - }, - { - "author_name": "Jamie Weaver Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX" - }, - { - "author_name": "Sophie Williams Dr", - "author_inst": "Sheffield Teaching Hospitals NHS foundation Trust, Sheffield S10 2JF" - }, - { - "author_name": "Caroline Wilson Dr", - "author_inst": "Sheffield Teaching Hospitals NHS foundation Trust, Sheffield S10 2JF" - }, - { - "author_name": "Richard Hoskins Dr", - "author_inst": "The University of Manchester, Oxford road, M13 9PL" - }, - { - "author_name": "Julie Stevenson Dr", - "author_inst": ". Digital experimental cancer medicine and Bioinformatics and Biostatistics teams, Cancer Research UK Manchester Institute Cancer Biomarker Centre, The Universi" - }, - { - "author_name": "Paul Fitzpartick Dr", - "author_inst": ". Digital experimental cancer medicine and Bioinformatics and Biostatistics teams, Cancer Research UK Manchester Institute Cancer Biomarker Centre, The Universi" - }, - { - "author_name": "Carlo Palmieri Prof", - "author_inst": "Clatterbridge Cancer Centre, 65 Pembroke Place, Liverpool, L7 8YA" - }, - { - "author_name": "Donal Landers Dr", - "author_inst": ". Digital experimental cancer medicine and Bioinformatics and Biostatistics teams, Cancer Research UK Manchester Institute Cancer Biomarker Centre, The Universi" + "author_name": "Muhammad Faisal", + "author_inst": "Faculty of Health Studies, University of Bradford, Bradford, UK Bradford Institute for Health Research Bradford, UK NIHR Yorkshire and Humber Patient Safety Tra" }, { - "author_name": "Tim Cooksley Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX" + "author_name": "Mohammed Amin Mohammed", + "author_inst": "Faculty of Health Studies, University of Bradford, Bradford, UK NHS Midlands and Lancashire Commissioning Support Unit, The Strategy Unit, Kingston House, We" }, { - "author_name": "Caroline Dive Prof", - "author_inst": "Cancer Research UK Manchester Institute Cancer Biomarker Centre, Alderley Park, SK10 4TG" + "author_name": "Donald Richardson", + "author_inst": "York Teaching Hospitals NHS Foundation Trust, England UK" }, { - "author_name": "Andre Freitas Dr", - "author_inst": "The University of Manchester, Oxford road, M13 9PL; Digital experimental cancer medicine team, Manchester Centre for Cancer Biomarker Sciences, Alderley Park, S" + "author_name": "Massimo Fiori", + "author_inst": "York Teaching Hospitals NHS Foundation Trust, England UK" }, { - "author_name": "Anne C Armstrong Dr", - "author_inst": "The Christie NHS Foundation Trust, Wilmslow road, M20 4BX; The University of Manchester, Oxford road, M13 9PL" + "author_name": "Kevin Beatson", + "author_inst": "York Teaching Hospitals NHS Foundation Trust, England UK" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "oncology" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.12.01.20241786", @@ -1065335,39 +1064389,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.12.02.408575", - "rel_title": "In Vitro Analysis of the Anti-viral Potential of nasal spray constituents against SARS-CoV-2", + "rel_doi": "10.1101/2020.12.03.410233", + "rel_title": "Horizontal gene transfer and recombination analysis of SARS-CoV-2 genes helps discover its close relatives and shed light on its origin", "rel_date": "2020-12-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.02.408575", - "rel_abs": "Viral pandemics have taken a significant toll on humanity and the world now is contending with the SARS-CoV-2 epidemic. Readily available economical preventive measures should be immediately explored. Xylitol has been reported to reduce the severity of viral infections as well as the severity of pneumonia, and increase the survivability of animal subjects. Since pneumonia and acute respiratory distress syndrome are potentially fatal complications of COVID-19, the present study tested the in vitro effectiveness of xylitol against SARS-CoV-2. Virus titers and LRV of SARS-CoV-2, were incubated with a single concentration of nasal spray. Toxicity was observed in the top dilution (1/10). Virus was seen below that dilution so it did not affect calculations of virus titer or LRV. After a 25-minute contact time, the nasal spray (11% Pure Xylitol, 0.85%NaCL (Saline), and 0.20% grapefruit seed extract) reduced virus from 4.2 to 1.7 log10 CCID50 per 0.1 mL, a statistically significant reduction (P<0.001) of 2.5 log10 CCID50. STEM Images obtained at the BIoCryo Laboratory revealed virus contained on the cell wall but none intra-cellular, possibly due to D-xylose (xylitol) production of glycoaminoglycans decoy targets. Xylitol and grapefruit seed extract are not exotic nor expensive rare high technology answers to viral epidemics. The potential in saving lives and the economies of the world by using X-GSE combination therapy should inspire large clinical trials, especially in those nations whereas the healthcare system would be dangerously compromised by the adoption of less effective and significantly more financially demanding therapies. Because there are no risk factors in using the X/GSE combination therapy, and the nasal spray is over the counter available without a prescription, and the spray allows for comfortable long term mask-wearing, adoption of this preventive anti-viral therapy should be encouraged.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.03.410233", + "rel_abs": "BackgroundThe SARS-CoV-2 pandemic is among the most dangerous infectious diseases that have emerged in recent history. Human CoV strains discovered during previous SARS outbreaks have been hypothesized to pass from bats to humans using intermediate hosts, e.g. civets for SARS-CoV and camels for MERS-CoV. The discovery of an intermediate host of SARS-CoV-2 and the identification of specific mechanism of its emergence in humans are topics of primary evolutionary importance. In this study we investigate the evolutionary patterns of 11 main genes of SARS-CoV-2. Previous studies suggested that the genome of SARS-CoV-2 is highly similar to the horseshoe bat coronavirus RaTG13 for most of the genes and to some Malayan pangolin coronavirus (CoV) strains for the receptor binding (RB) domain of the spike protein.\n\nResultsWe provide a detailed list of statistically significant horizontal gene transfer and recombination events (both intergenic and intragenic) inferred for each of 11 main genes of the SARS-Cov-2 genome. Our analysis reveals that two continuous regions of genes S and N of SARS-CoV-2 may result from intragenic recombination between RaTG13 and Guangdong (GD) Pangolin CoVs. Statistically significant gene transfer-recombination events between RaTG13 and GD Pangolin CoV have been identified in region [1215-1425] of gene S and region [534-727] of gene N. Moreover, some significant recombination events between the ancestors of SARS-CoV-2, RaTG13, GD Pangolin CoV and bat CoV ZC45-ZXC21 coronaviruses have been identified in genes ORF1ab, S, ORF3a, ORF7a, ORF8 and N. Furthermore, topology-based clustering of gene trees inferred for 25 CoV organisms revealed a three-way evolution of coronavirus genes, with gene phylogenies of ORF1ab, S and N forming the first cluster, gene phylogenies of ORF3a, E, M, ORF6, ORF7a, ORF7b and ORF8 forming the second cluster, and phylogeny of gene ORF10 forming the third cluster.\n\nConclusionsThe results of our horizontal gene transfer and recombination analysis suggest that SARS-Cov-2 could not only be a chimera resulting from recombination of the bat RaTG13 and Guangdong pangolin coronaviruses but also a close relative of the bat CoV ZC45 and ZXC21 strains. They also indicate that a GD pangolin may be an intermediate host of SARS-CoV-2.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Mark L Cannon", - "author_inst": "Northwestern University" + "author_name": "Vladimir Makarenkov", + "author_inst": "Universite du Quebec a Montreal" }, { - "author_name": "Jonna B Westover", - "author_inst": "Utah State University" + "author_name": "Bogdan Mazoure", + "author_inst": "McGill University, Quebec Artificial Intelligence Institute" }, { - "author_name": "Reiner Bleher", - "author_inst": "Northwestern University" + "author_name": "Guillaume Rabusseau", + "author_inst": "Universite de Montreal, Quebec Artificial Intelligence Institute" }, { - "author_name": "Marcos A Sanchez-Gonzalez", - "author_inst": "Lake Erie College of Osteopathic Medicine" - }, - { - "author_name": "Gustavo Ferrer", - "author_inst": "Nova Southeastern University" + "author_name": "Pierre Legendre", + "author_inst": "Universite de Montreal" } ], "version": "1", - "license": "cc_by_nd", - "type": "confirmatory results", - "category": "molecular biology" + "license": "cc_by", + "type": "new results", + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2020.12.03.409458", @@ -1066781,85 +1065831,141 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.30.20241208", - "rel_title": "Rapid and accurate point-of-care testing for SARS-CoV2 antibodies", + "rel_doi": "10.1101/2020.11.30.20218560", + "rel_title": "Convalescent Plasma in COVID-19. Mortality-Safety First Results of the Prospective Multicenter FALP 001-2020 Trial", "rel_date": "2020-12-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.30.20241208", - "rel_abs": "The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has grown into worst public health crisis since the 1918 influenza pandemic. As COVID-19 continues to spread around the world, there is urgent need for a rapid, yet accurate antibody test to identify infected individuals in populations to inform health decisions. We have developed a rapid, accurate and cost-effective serologic test based on antibody-dependent agglutination of antigen-coated latex particles, which uses [~]5 {micro}l plasma and takes <5 min to complete with no instrument required. The simplicity of this test makes it ideal for point-of-care (POC) use at the community level. When validated using plasma samples that are positive or negative for SARS-CoV-2, the agglutination assay detected antibodies against the receptor-binding domain of the spike (S-RBD) or the nucleocapsid (N) protein of SARS-CoV-2 with 100% specificity and [~]98% sensitivity. Furthermore, we found that the strength of the S-RBD antibody response measured by the agglutination assay correlated with the efficiency of the plasma in blocking RBD binding to the angiotensin converting enzyme 2 (ACE2) in a surrogate neutralization assay, suggesting that the agglutination assay may be used to identify individuals with virus-neutralizing antibodies. Intriguingly, we found that >92% of patients had detectable antibodies on the day of positive viral RNA test, suggesting that seroconversion may occur earlier than previously thought and that the agglutination antibody test may complement RNA testing for POC diagnosis of SARS-CoV-2 infection.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.30.20218560", + "rel_abs": "BackgroundThe use of convalescent plasma (CP) to treat COVID-19 has shown promising results; however, its effectiveness remains uncertain. The purpose of this study was to determine the safety and mortality of CP among patients hospitalized with COVID-19.\n\nStudy Design and MethodsThis multicenter, open-label, uncontrolled clinical trial is currently being conducted at nine hospitals in Chile. Patients hospitalized due to COVID-19 who were still within 14 days since symptom onset were classified into four groups: Patients with cancer and severe COVID-19. Patients with cancer and non-severe COVID-19. Patients with severe COVID-19 and patients with non-severe COVID-19 only. The intervention involved two 200-cc. CP transfusions with anti-SARS-CoV-2 IgG titers [≥] 1:320 collected from COVID-19-recovered donors.\n\nResults192 patients hospitalized for COVID-19 received CP transfusions. At the first transfusion, 90.6% fulfilled the criteria for severity, and 41.1% required mechanical ventilation. 11.5% of the patients had cancer. Overall 7-day and 30-day mortality since the first CP transfusion was 5.7% and 16.1% respectively. There were no differences at either time point in mortality between the four groups. Patients on mechanical ventilation when receiving CP had higher mortality rates than those who were not (22.8% vs. 11.5%; p = 0.037). Overall 30-day mortality was higher in patients over 65 than in younger patients (p = 0.019). Severe adverse events were reported in four patients (2.1%) with an overall transfusion-related lung injury rate of 1.56%. No CP-related deaths occurred.\n\nDiscussionCP is safe when used in patients with COVID-19 even when also presenting severity criteria or risk factors. Our mortality rate is comparable to reports from larger studies. Controlled clinical trials are required to determine efficacy.\n\nRegistrationNCT04384588", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Shawn SC Li", - "author_inst": "Western University" + "author_name": "raimundo gazitua", + "author_inst": "Fundacion Arturo Lopez Perez" }, { - "author_name": "Sally Esmail", - "author_inst": "Western University" + "author_name": "jose luis Briones", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Michael Knauer", - "author_inst": "Western University" + "author_name": "Carolina Selman", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Husam Abdoh", - "author_inst": "Western University" + "author_name": "Franz Villarroel-Espindola", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Benjamin Chin-Yee", - "author_inst": "Western University" + "author_name": "Adam Aguirre", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Lori Lowes", - "author_inst": "Western University" + "author_name": "Roxana Gonzalez-Steigmaier", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Courtney Voss", - "author_inst": "Western University" + "author_name": "Karina cereceda", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Benjamin Hedley", - "author_inst": "Western University" + "author_name": "Mauricio Mahave", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Vipin Bhayana", - "author_inst": "Western University" + "author_name": "Betzabe Rubio", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Ian Chin-Yee", - "author_inst": "Western University" + "author_name": "Pedro Ferrer-Rosende", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Alma Seitova", - "author_inst": "University of Toronto" + "author_name": "Jorge Sapunar", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Ashley Hutchinson", - "author_inst": "University of Toronto" + "author_name": "Hugo Marsiglia", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Farhad Yusifov", - "author_inst": "University of Toronto" + "author_name": "Ricardo Morales", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Tatiana Skarina", - "author_inst": "University of Toronto" + "author_name": "Fernanda Yarad", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" }, { - "author_name": "Elena Evdokimova", - "author_inst": "University of Toronto" + "author_name": "Maria Elvira Balcells", + "author_inst": "Pontificia Universidad Catolica de Chile" }, { - "author_name": "Suzanne Ackloo", - "author_inst": "University of Toronto" + "author_name": "Luis Rojas", + "author_inst": "Pontificia Universidad Catolica de Chile" }, { - "author_name": "Peter Stogios", - "author_inst": "University of Toronto" + "author_name": "Bruno Nervi", + "author_inst": "Pontificia Universidad Catolica de Chile" + }, + { + "author_name": "Jyh Kae Nien", + "author_inst": "Clinica Davila" + }, + { + "author_name": "Javier Garate", + "author_inst": "Clinica Redsalud" + }, + { + "author_name": "Carolina Prieto", + "author_inst": "Hospital Dipreca" + }, + { + "author_name": "Sofia Palma", + "author_inst": "Hospital Dipreca" + }, + { + "author_name": "Carolina Escobar", + "author_inst": "Hospital Dipreca" + }, + { + "author_name": "Josefina bascunan", + "author_inst": "12.\tHospital del Trabajador, Asociacion Chilena de Seguridad" + }, + { + "author_name": "Rodrigo Munoz", + "author_inst": "Hospital Clinico de Magallanes" + }, + { + "author_name": "Monica Pinto", + "author_inst": "Hospital Clinico de Magallanes" + }, + { + "author_name": "Daniela Cardemil", + "author_inst": "Hospital Clinico de Magallanes" + }, + { + "author_name": "Marcelo Navarrete", + "author_inst": "Universidad de Magallanes" + }, + { + "author_name": "Soledad Reyes", + "author_inst": "Clinica Alemana de Temuco" + }, + { + "author_name": "Victoria Espinoza", + "author_inst": "Clinica Alemana de Temuco" + }, + { + "author_name": "Nicolas Yanez", + "author_inst": "Hospital Regional de Talca" + }, + { + "author_name": "Christian Caglevic", + "author_inst": "Instituto Oncologico Fundacion Arturo Lopez Perez" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1068943,63 +1068049,79 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.12.01.407007", - "rel_title": "Multimodal Single-Cell Omics Analysis of COVID-19 Sex Differences in Human Immune Systems", - "rel_date": "2020-12-01", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.12.01.407007", - "rel_abs": "Sex differences in the risk of SARS-CoV-2 infection have been controversial and the underlying mechanisms of COVID-19 sexual dimorphism remain understudied. Here we inspected sex differences in SARS-CoV-2 positivity, hospitalization, admission to the intensive care unit (ICU), sera immune profiling, and two single-cell RNA-sequencing (snRNA-seq) profiles from nasal tissues and peripheral blood mononuclear cells (PBMCs) of COVID-19 patients with varying degrees of disease severity. Our propensity score-matching observations revealed that male individuals have a 29% increased likelihood of SARS-CoV-2 positivity, with a hazard ration (HR) 1.32 (95% confidence interval [CI] 1.18-1.48) for hospitalization and HR 1.51 (95% CI 1.24-1.84) for admission to ICU. Sera from male patients at hospital admission had decreased lymphocyte count and elevated inflammatory markers (C-reactive protein, procalcitonin, and neutrophils). We found that SARS-CoV-2 entry factors, including ACE2, TMPRSS2, FURIN and NRP1, have elevated expression in nasal squamous cells from males with moderate and severe COVID-19. Cell-cell network proximity analysis suggests possible epithelium-immune cell interactions and immune vulnerability underlying a higher mortality in males with COVID-19. Monocyte-elevated expression of Toll like receptor 7 (TLR7) and Bruton tyrosine kinase (BTK) is associated with severe outcomes in males with COVID-19. These findings provide basis for understanding immune responses underlying sex differences, and designing sex-specific targeted treatments and patient care for COVID-19.", - "rel_num_authors": 11, + "rel_doi": "10.1101/2020.11.26.20232728", + "rel_title": "COVID-19 Antigen Rapid Test as Screening Strategy at the Points-of-Entry: Experience in Lazio Region, Central Italy, August-October 2020.", + "rel_date": "2020-11-30", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.26.20232728", + "rel_abs": "COVID-19 pandemic is becoming one of the most dramatic health, social and economic global challenges in recent history. Testing is one of the main components of the public health response to contain the virus spreading. There is an urgent need to expand testing capacity and antigen rapid tests (Ag RDT) represent good candidates for point-of-care and mass surveillance testing to rapidly identify people with SARS-CoV-2 infection, counterbalancing lower sensitivity as compared to the gold standard molecular tests with timeliness of results and possibility of recurred testing. Here, we report preliminary data of the testing algorithm implemented at the points-of-entry (airports and port) in Lazio Region (Central Italy) on travelers arriving between 17th of August to 15th of October, 2020, using the STANDARD F COVID-19 Antigen Fluorescence ImmunoAssay. Our findings show that the probability of molecular confirmation of Ag RDT positive results is directly dependent from the semi-quantitative results of this Ag RDT, and that the molecularly confirmed samples actually harbor infectious virus. These results support the public health strategies based on early screening campaigns in settings where molecular testing is not feasible or easily accessible, using rapid and simple point of care tests, able to rapidly identify those subjects who are at highest risk of spreading SARS-CoV-2 infection.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Yuan Hou", - "author_inst": "Cleveland Clinic" + "author_name": "Francesca Colavita", + "author_inst": "National Institute for Infectious Dieseases \"L. Spallanzani\", Rome, Italy" }, { - "author_name": "Yadi Zhou", - "author_inst": "Cleveland Clinic" + "author_name": "Francesco Vairo", + "author_inst": "Regional Service for Surveillance and Control of Infectious Diseases (SERESMI), National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" }, { - "author_name": "Michaela Gack", - "author_inst": "Cleveland Clinic Florida" + "author_name": "Silvia Meschi", + "author_inst": "National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" }, { - "author_name": "Justin Lathia", - "author_inst": "Cleveland Clinic" + "author_name": "Beatrice Valli", + "author_inst": "National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" }, { - "author_name": "Asha Kallianpur", - "author_inst": "Cleveland Clinic" + "author_name": "Eleonora Lalle", + "author_inst": "National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" }, { - "author_name": "Reena Mehra", - "author_inst": "Cleveland Clinic" + "author_name": "Concetta Castilletti", + "author_inst": "National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" }, { - "author_name": "Timothy Chan", - "author_inst": "Cleveland Clinic" + "author_name": "Danilo Fusco", + "author_inst": "Lazio Regional Health Service, Rome, Italy" }, { - "author_name": "Jae U. Jung", - "author_inst": "Cleveland Clinic" + "author_name": "Giuseppe Spiga", + "author_inst": "Lazio Regional Health Service, Rome, Italy" }, { - "author_name": "Lara Jehi", - "author_inst": "Cleveland Clinic" + "author_name": "Pierluigi Bartoletti", + "author_inst": "Regional Special Unit for Community Health Care (USCAR), National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" }, { - "author_name": "Charis Eng", - "author_inst": "Cleveland Clinic Genomic Medicine Institute" + "author_name": "Simona Ursino", + "author_inst": "Local Health Authority Roma 4, Civitavecchia, Rome, Italy" }, { - "author_name": "Feixiong Cheng", - "author_inst": "Cleveland Clinic" + "author_name": "Maurizio Sanguinetti", + "author_inst": "Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy" + }, + { + "author_name": "Antonino Di Caro", + "author_inst": "National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" + }, + { + "author_name": "Francesco Vaia", + "author_inst": "National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" + }, + { + "author_name": "Giuseppe Ippolito", + "author_inst": "National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" + }, + { + "author_name": "Maria Rosaria Capobianchi", + "author_inst": "National Institute for Infectious Diseases \"L. Spallanzani\", Rome, Italy" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "systems biology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.11.26.20238469", @@ -1070425,51 +1069547,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.26.20239418", - "rel_title": "Predictors of QT Interval Prolongation in Critically-ill Patients with SARS-CoV-2 Infection Treated with Hydroxychloroquine", + "rel_doi": "10.1101/2020.11.27.20239657", + "rel_title": "Quantifying superspreading for COVID-19 using Poisson mixture distributions", "rel_date": "2020-11-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.26.20239418", - "rel_abs": "BackgroundHydroxychloroquine (HCQ) has been described as a potential treatment for SARS-CoV-2 infection. However, there are safety concerns regarding its QT interval and pro-arrhythmic effects.\n\nObjectiveThis trial aimed to determine the predictors of QT interval prolongation and pro-arrhythmic effects in patients hospitalized for SARS-CoV-2 infection and receiving HCQ.\n\nMethodsWe performed a retrospective observational study of 45 critically-ill patients hospitalized because of SARS-CoV-2 infection and treated with 800 mg of HCQ at day 1 and 400 mg on days 2-5. Clinical aspects and outcomes, basal and final corrected QT (QTc) interval, and the incidence of arrhythmias and arrhythmogenic death were observed. Independent predictors of QTc prolongation were identified using multivariable logistic regression analysis. QT interval prolongation was considered substantial at final QTc [≥] 480 ms.\n\nResultsThe mean age was 60.9 {+/-} 16.67 years and 28 (62.2%) patients were men. Basal QTc was 442 {+/-} 28 ms, and the final QTc interval was 458 {+/-} 34 ms, for a mean QTc interval variation of 15 {+/-} 11 ms. There was no arrhythmogenic death. The need for hemodialysis remained a statistically significant predictor of QT interval enlargement (odds ratio, 10.34; 95% confidence interval, 1.04 - 102.18; p = 0.045).\n\nConclusionsHCQ promotes mild to moderate QT interval prolongation. The risk of QT interval prolongation is higher among patients with acute renal failure requiring hemodialysis.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.27.20239657", + "rel_abs": "The number of secondary cases is an important parameter for the control of infectious diseases. When individual variation in disease transmission is present, like for COVID-19, the number of secondary cases is often modelled using a negative binomial distribution. However, this may not be the best distribution to describe the underlying transmission process. We propose the use of three other offspring distributions to quantify heterogeneity in transmission, and we assess the possible bias in estimates of the offspring mean and its overdispersion when the data generating distribution is different from the one used for inference. We find that overdispersion estimates may be biased when there is a substantial amount of heterogeneity, and that the use of other distributions besides the negative binomial should be considered. We revisit three previously analysed COVID-19 datasets and quantify the proportion of cases responsible for 80% of transmission, p80%, while acknowledging the variation arising from the assumed offspring distribution. We find that the number of secondary cases for these datasets is better described by a Poisson-lognormal distribution.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Frederico Scuotto", - "author_inst": "Hospital Samaritano Higien\u00f3polis, United Health Group - S\u00e3o Paulo, SP, Brazil" + "author_name": "C\u00e9cile Kremer", + "author_inst": "Hasselt University" + }, + { + "author_name": "Andrea Torneri", + "author_inst": "University of Antwerp" }, { - "author_name": "Rog\u00e9rio Marra", - "author_inst": "Hospital Samaritano Higien\u00f3polis, United Health Group - S\u00e3o Paulo, SP, Brazil" + "author_name": "Sien Boesmans", + "author_inst": "Hasselt University" }, { - "author_name": "Lilian Leite de Almeida", - "author_inst": "Hospital Samaritano Higien\u00f3polis, United Health Group - S\u00e3o Paulo, SP, Brazil" + "author_name": "Hanne Meuwissen", + "author_inst": "Hasselt University" }, { - "author_name": "Mariana Santa Rita Soares", - "author_inst": "Hospital Samaritano Higien\u00f3polis, United Health Group - S\u00e3o Paulo, SP, Brazil" + "author_name": "Selina Verdonschot", + "author_inst": "Hasselt University" }, { - "author_name": "Gabriela Kurita Silva", - "author_inst": "Hospital Samaritano Higien\u00f3polis, United Health Group - S\u00e3o Paulo, SP, Brazil" + "author_name": "Koen Vanden Driessche", + "author_inst": "Antwerp University Hospital & Radboud University Medical Center" }, { - "author_name": "Luiz Carlos Paul", - "author_inst": "Hospital Samaritano Higien\u00f3polis, United Health Group - S\u00e3o Paulo, SP, Brazil" + "author_name": "Christian L. Althaus", + "author_inst": "University of Bern" }, { - "author_name": "Guilherme Drummond Fenelon Costa", - "author_inst": "Hospital Samaritano Higien\u00f3polis, United Health Group - S\u00e3o Paulo, SP, Brazil" + "author_name": "Christel Faes", + "author_inst": "Hasselt University" }, { - "author_name": "Cl\u00e1udio Cirenza", - "author_inst": "Hospital Samaritano Higien\u00f3polis, United Health Group - S\u00e3o Paulo, SP, Brazil" + "author_name": "Niel Hens", + "author_inst": "Hasselt University & University of Antwerp" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.11.26.20233627", @@ -1071947,47 +1071073,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.11.29.20240614", - "rel_title": "AI4CoV: Matching COVID-19 Patients to Treatment Options Using Artificial Intelligence", + "rel_doi": "10.1101/2020.11.29.20240606", + "rel_title": "A Retrospective Longitudinal Study of COVID-19 as Seen by a Large Urban Hospital in Chicago", "rel_date": "2020-11-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.29.20240614", - "rel_abs": "We developed AI4CoV, a novel AI system to match thousands of COVID-19 clinical trials to patients based on each patients eligibility to clinical trials in order to help physicians select treatment options for patients. AI4CoV leveraged Natural Language Processing (NLP) and Machine Learning to parse through eligibility criteria of trials and patients clinical manifestations in their clinical notes, both presented in English text, to accomplish 92.76% AUROC on a cross-validation test with 3,156 patient-trial pairs labeled with ground truth of suitability. Our retrospective multiple-site review shows that according to AI4CoV, severe patients of COVID-19 generally have less treatment options suitable for them than mild and moderate patients and that suitable and unsuitable treatment options are different for each patient. Our results show that the general approach of AI4CoV is useful during the early stage of a pandemic when the best treatments are still unknown.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.29.20240606", + "rel_abs": "The rapid spread of the novel coronavirus disease 2019 (COVID-19) has created high demand for medical resources, including personnel, intensive care unit beds, and ventilators. As thousands of patients are hospitalized, the disease has shown remarkable diversity in its manifestation; many patients with mild to no symptoms recover from the disease requiring minimal care, but some patients with severe disease progression require mechanical ventilation support in intensive care units (ICU) with an increased risk of death. Studying the characteristics of patients in these various strata can help us understand the varied progression of this disease, enable earlier interventions for at-risk patients, and help manage medical resources more efficiently. This paper presents a retrospective analysis of 10,123 COVID-19 patients treated at the Rush University Medical Center in Chicago, including their demographics, symptoms, comorbidities, laboratory values, vital signs, and clinical history. Specifically, we present a staging scheme based on discrete clinical events (i.e., admission to the hospital, admission to the ICU, mechanical ventilation, and death), and investigate the temporal trend of clinical variables and the effect of comorbidities in each of those stages. We then developed a prognostic model to predict ventilation demands at an individual patient level by analyzing baseline clinical variables, which entails (1) a least absolute shrinkage and selection operator (LASSO) regression and a decision tree model to identify predictors for mechanical ventilation; and (2) a logistic regression model based on these risk factors to predict which patients will eventually need ventilatory support. Our results indicate that the prognostic model achieves an AUC of 0.823 (95% CI: 0.765-0.880) in identifying patients who will eventually require mechanical ventilation.", "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Andrew I Hsu", - "author_inst": "AI4WARD Inc." + "author_name": "Haotian Chen", + "author_inst": "The University of Illinois at Urbana-Champaign" }, { - "author_name": "Amber Yeh", - "author_inst": "AI4WARD Inc." + "author_name": "Yogatheesan Varatharajah", + "author_inst": "The University of Illinois at Urbana Champaign" }, { - "author_name": "Shao-Lang Chen", - "author_inst": "AI4WARD Inc." + "author_name": "Sarah A Stewart de Ramirez", + "author_inst": "OSF Healthcare" }, { - "author_name": "Jerry J Yeh", - "author_inst": "AI4WARD Inc." + "author_name": "Paul Arnold", + "author_inst": "Carle Foundation Hospital" }, { - "author_name": "DongQing Lv", - "author_inst": "2.\tDepartment of Respiratory Medicine, Taizhou Hospital of Zhejiang Province, Wenzhou Medical University, Taizhou, China" + "author_name": "Casey Frankenberger", + "author_inst": "Rush University Medical Center" }, { - "author_name": "Jane Yung-jen Hsu", - "author_inst": "Department of Computer Science & Information Engineering, National Taiwan University, Taiwan" + "author_name": "Bala Hota", + "author_inst": "Rush University Medical Center" }, { - "author_name": "Pai Jung Huang", - "author_inst": "Institute of Medical Science and Technology, Taipei Medical University" + "author_name": "Ravishankar Iyer", + "author_inst": "The University of Illinois at Urbana Champaign" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.11.28.20240077", @@ -1073597,35 +1072723,31 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.11.25.20238675", - "rel_title": "Autosomal Dominant Polycystic Kidney Disease does not significantly alter major COVID-19 outcomes among veterans", + "rel_doi": "10.1101/2020.11.25.20236752", + "rel_title": "Symptom-based prediction model of SARS-1 CoV-2 infection developed from self-reported symptoms of SARS-CoV-2-infected individuals in an online survey", "rel_date": "2020-11-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20238675", - "rel_abs": "Chronic kidney disease (CKD), as well as its common causes (e.g., diabetes and obesity), are recognized risk factors for severe COVID-19 illness. To explore whether the most common inherited cause of CKD, autosomal dominant polycystic kidney disease (ADPKD), is also an independent risk factor, we studied data from the VA health system and the VA COVID-19-shared resources (e.g., ICD codes, demographics, pre-existing conditions, pre-testing symptoms, and post-testing outcomes). Among 61 COVID-19-positive ADPKD patients, 21 (34.4%) were hospitalized, 10 (16.4%) were admitted to ICU, 4 (6.6%) required ventilator, and 4 (6.6%) died by August 18, 2020. These rates were comparable to patients with other cystic kidney diseases and cystic liver-only diseases. ADPKD was not a significant risk factor for any of the four outcomes in multivariable logistic regression analyses when compared with other cystic kidney diseases and cystic liver-only diseases. In contrast, diabetes was a significant risk factor for hospitalization [OR 2.30 (1.61, 3.30), p<0.001], ICU admission [OR 2.23 (1.47, 3.42), p<0.001], and ventilator requirement [OR 2.20 (1.27, 3.88), p=0.005]. Black race significantly increased the risk for ventilator requirement [OR 2.00 (1.18, 3.44), p=0.011] and mortality [OR 1.60 (1.02, 2.51), p=0.040]. We also examined the outcome of starting dialysis after COVID-19 confirmation. The main risk factor for starting dialysis was CKD [OR 6.37 (2.43, 16.7)] and Black race [OR 3.47 (1.48, 8.1)]. After controlling for CKD, ADPKD did not significantly increase the risk for newly starting dialysis comparing with other cystic kidney diseases and cystic liver-only diseases. In summary, ADPKD did not significantly alter major COVID-19 outcomes among veterans when compared to other cystic kidney and liver patients.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20236752", + "rel_abs": "BackgroundInfections with the newly emerged severe acute respiratory syndrome virus 2 (SARS-CoV-2) have quickly reached pandemic proportions and are causing a global health crisis. First recognized for the induction of severe disease, the virus also causes asymptomatic infections or infections with mild symptoms that can resemble common colds. Since infections with mild course are probably a major contributor to the spread of SARS-CoV-2, better detection of such cases is important. To provide better understanding of these mild SARS-CoV-2 infections and to improve information for potentially infected individuals, we performed a detailed analysis of self-reported symptoms of SARS-CoV-2 positive and SARS-CoV-2 negative individuals.\n\nMethodsIn an online-based survey, 963 individuals provided information on symptoms associated with an acute respiratory infection, 336 of the participants had tested positive for SARS-CoV-2 infection, 107 had tested negative, and 520 had not been tested for SARS-CoV-2 infection.\n\nResultsThe symptoms reported most frequently by SARS-CoV-2 infected individuals were tiredness, loss of appetite, impairment of smell or taste and dry cough. The symptoms with the highest odds ratios between SARS-CoV-2 positive and negative individuals were loss of appetite and impairment of smell or taste. Based on the most distinguishing symptoms, we developed a Bayesian prediction model, which had a positive predictive value of 0.80 and a negative predictive value of 0.72 on the SARS-CoV-2 tested individuals. The model predicted 56 of 520 non-tested individuals to be SARS-CoV-2 positive with more than 75% probability, and another 84 to be SARS-CoV-2 positive with probability between 50% and 75%.\n\nConclusionsA combination of symptoms can provide a good estimate of the probability of SARS-CoV-2 infection.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Xiangqin Cui", - "author_inst": "Emory University and Atlanta VA Medical Center" - }, - { - "author_name": "Julia W. Gallini", - "author_inst": "Foundation for Atlanta Veterans Education and Research" + "author_name": "Hansjoerg Schulze", + "author_inst": "Institute for Virology, University Hospital Essen, University Duisburg-Essen" }, { - "author_name": "Christine L. Jasien", - "author_inst": "Atlanta VA Mecial Center" + "author_name": "Daniel Hoffmann", + "author_inst": "Bioinformatics and Computational Biophysics, Faculty of Biology, University Duisburg-Essen" }, { - "author_name": "Michal Mrug", - "author_inst": "University of Alabama at Birmingham and Birmingham VA Medical Center" + "author_name": "Wibke Bayer", + "author_inst": "Institute for Virology, University Hospital Essen, University Duisburg-Essen" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.11.25.20238592", @@ -1074759,115 +1073881,75 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2020.11.19.20234237", - "rel_title": "Association of Toll-like receptor 7 variants with life-threatening COVID-19 disease in males", + "rel_doi": "10.1101/2020.11.25.20144139", + "rel_title": "Disentangling the roles of human mobility and deprivation on the transmission dynamics of COVID-19 using a spatially explicit simulation model.", "rel_date": "2020-11-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.19.20234237", - "rel_abs": "BackgroundCOVID-19 clinical presentation ranges from asymptomatic to fatal outcome. This variability is due in part to host genome specific mutations. Recently, two families in which COVID-19 segregates like an X-linked recessive monogenic disorder environmentally conditioned by SARS-CoV-2 have been reported leading to identification of loss-of-function variants in TLR7.\n\nObjectiveWe sought to determine whether the two families represent the tip of the iceberg of a subset of COVID-19 male patients.\n\nMethodsWe compared male subjects with extreme phenotype selected from the Italian GEN-COVID cohort of 1178 SARS-CoV-2-infected subjects (<60y, 79 severe cases versus 77 control cases). We applied the LASSO Logistic Regression analysis, considering only rare variants on the young male subset, picking up TLR7 as the most important susceptibility gene.\n\nResultsRare TLR7 missense variants were predicted to impact on protein function in severely affected males and in none of the asymptomatic subjects. We then investigated a similar white European cohort in Spain, confirming the impact of TRL7 variants. A gene expression profile analysis in peripheral blood mononuclear cells after stimulation with TLR7 agonist demonstrated a reduction of mRNA level of TLR7, IRF7, ISG15, IFN-{square} and IFN-{gamma} in COVID-19 patients compared with unaffected controls demonstrating an impairment in type I and II INF responses.\n\nConclusionYoung males with TLR7 loss-of-function mutations and severe COVID-19 in the two reported families represent only a fraction of a broader and complex host genome situation. Specifically, missense mutations in the X-linked recessive TLR7 disorder may significantly contribute to disease susceptibility in up to 4% of severe COVID-19.\n\nClinical ImplicationIn this new yet complex scenario, our observations provide the basis for a personalized interferon-based therapy in patients with rare TLR7 variants.\n\nCAPSULE SUMMARYOur results in large cohorts from Italy and Spain showed that X-linked recessive TLR7 disorder may represent the cause of disease susceptibility to COVID-19 in up to 4% of severely affected young male cases.", - "rel_num_authors": 24, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.25.20144139", + "rel_abs": "Restrictions on mobility are a key component of infectious disease controls, preventing the spread of infections to as yet unexposed areas, or to regions which have previously eliminated outbreaks. However, even under the most severe restrictions, some travel must inevitably continue, at the very minimum to retain essential services. For COVID-19, most countries imposed severe restrictions on travel at least as soon as it was clear that containment of local outbreaks would not be possible. Such restrictions are known to have had a substantial impact on the economy and other aspects of human health, and so quantifying the impact of such restrictions is an essential part of evaluating the necessity for future implementation of similar measures.\n\nIn this analysis, we built a simulation model using National statistical data to record patterns of movements to work, and implement levels of mobility recorded in real time via mobile phone apps. This model was fitted to the pattern of deaths due to COVID-19 using approximate Bayesian inference. Our model is able to recapitulate mortality considering the number of deaths and datazones (DZs, which are areas containing approximately 500-1000 residents) with deaths, as measured across 32 individual council areas (CAs) in Scotland. Our model recreates a trajectory consistent with the observed data until 1st of July. According to the model, most transmission was occurring \"locally\" (i.e. in the model, 80% of transmission events occurred within spatially defined \"communities\" of approximately 100 individuals). We show that the net effect of the various restrictions put into place in March can be captured by a reduction in transmission down to 12% of its pre-lockdown rate effective 28th March. By comparing different approaches to reducing transmission, we show that, while the timing of COVID-19 restrictions influences the role of the transmission rate on the number of COVID-related deaths, early reduction in long distance movements does not reduce death rates significantly. As this movement of individuals from more infected areas to less infected areas has a minimal impact on transmission, this suggests that the fraction of population already immune in infected communities was not a significant factor in these early stages of the national epidemic even when local clustering of infection is taken into account.\n\nThe best fit model also shows a considerable influence of the health index of deprivation (part of the \"index of multiple deprivations\") on mortality. The most likely value has the CA with the highest level of health-related deprivation to have on average, a 2.45 times greater mortality rate due to COVID-19 compared to the CA with the lowest, showing the impact of health-related deprivation even in the early stages of the COVID-19 national epidemic.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Chiara Fallerini", - "author_inst": "Medical Genetics, University of Siena; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" - }, - { - "author_name": "Sergio Daga", - "author_inst": "Medical Genetics, University of Siena; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" - }, - { - "author_name": "Stefania Mantovani", - "author_inst": "Division of Infectious Diseases and Immunology, Department of Medical Sciences and Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy" - }, - { - "author_name": "Elisa Benetti", - "author_inst": "Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" - }, - { - "author_name": "Aurora Pujol", - "author_inst": "Neurometabolic Diseases Laboratory, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; CIBERER, Centro de Investigacion Biomedica en Red de En" - }, - { - "author_name": "Nicola Picchiotti", - "author_inst": "Department of Mathematics, University of Pavia, Pavia, Italy; University of Siena, DIISM-SAILAB, Siena, Italy" - }, - { - "author_name": "Agatha Schluter", - "author_inst": "Neurometabolic Diseases Laboratory, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; CIBERER, Centro de Investigacion Biomedica en Red de En" - }, - { - "author_name": "Laura Planas-Serra", - "author_inst": "Neurometabolic Diseases Laboratory, Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain; CIBERER, Centro de Investigacion Biomedica en Red de En" - }, - { - "author_name": "Jesus Troya", - "author_inst": "Infanta Leonor University Hospital, Madrid, Spain" - }, - { - "author_name": "Margherita Baldassarri", - "author_inst": "Medical Genetics, University of Siena; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" - }, - { - "author_name": "Francesca Fava", - "author_inst": "Medical Genetics, University of Siena; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy; Genetica Medica" + "author_name": "Christopher J. Banks", + "author_inst": "University of Edinburgh" }, { - "author_name": "Serena Ludovisi", - "author_inst": "Division of Infectious Diseases and Immunology, Department of Medical Sciences and Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; D" + "author_name": "Ewan Colman", + "author_inst": "University of Edinburgh" }, { - "author_name": "Francesco Castelli", - "author_inst": "Department of Infectious and Tropical Diseases, University of Brescia and ASST Spedali Civili Hospital, Brescia, Italy" + "author_name": "Thomas Doherty", + "author_inst": "University of Edinburgh" }, { - "author_name": "Maria Eugenia Quiros-Roldan", - "author_inst": "Department of Infectious and Tropical Diseases, University of Brescia and ASST Spedali Civili Hospital, Brescia, Italy" + "author_name": "Oliver Tearne", + "author_inst": "Animal and Plant Health Agency" }, { - "author_name": "Massimo Vaghi", - "author_inst": "Chirurgia Vascolare, Ospedale Maggiore di Crema, Italy" + "author_name": "Mark E. Arnold", + "author_inst": "Animal and Plant Health Agency" }, { - "author_name": "Stefano Rusconi", - "author_inst": "III Infectious Diseases Unit, ASST-FBF-Sacco, Milan, Italy; Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan, Italy" + "author_name": "Katherine Elizabeth Atkins", + "author_inst": "University of Edinburgh" }, { - "author_name": "Matteo Siano", - "author_inst": "Department of Biomedical and Clinical Sciences Luigi Sacco, University of Milan, Milan, Italy" + "author_name": "Daniel Balaz", + "author_inst": "University of Edinburgh" }, { - "author_name": "Maria Bandini", - "author_inst": "Department of Preventive Medicine, Azienda USL Toscana Sud Est, Italy" + "author_name": "Ga\u00ebl Beaun\u00e9e", + "author_inst": "Animal Health Division - BIOEPAR, INRAE, Nantes, France" }, { - "author_name": "Simone Furini", - "author_inst": "Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" + "author_name": "Paul Bessell", + "author_inst": "University of Edinburgh" }, { - "author_name": "Francesca Mari", - "author_inst": "Medical Genetics, University of Siena; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy; Genetica Medica" + "author_name": "Jessica Enright", + "author_inst": "University of Glasgow" }, { - "author_name": "- GEN-COVID Multicenter Study", - "author_inst": "" + "author_name": "Adam Kleczkowski", + "author_inst": "University of Strathclyde" }, { - "author_name": "Alessandra Renieri", - "author_inst": "Medical Genetics, University of Siena; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy; Genetica Medica" + "author_name": "Gianluigi Rossi", + "author_inst": "University of Edinburgh" }, { - "author_name": "Mario U Mondelli", - "author_inst": "Division of Infectious Diseases and Immunology, Department of Medical Sciences and Infectious Diseases, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy; D" + "author_name": "Anne-Sophie Ruget", + "author_inst": "University of Edinburgh" }, { - "author_name": "Elisa Frullanti", - "author_inst": "Medical Genetics, University of Siena; Med Biotech Hub and Competence Center, Department of Medical Biotechnologies, University of Siena, Italy" + "author_name": "Rowland Raymond Kao", + "author_inst": "University of Edinburgh" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.11.24.20216663", @@ -1076981,35 +1076063,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.11.21.20236216", - "rel_title": "Use of alternative RNA storage and extraction reagents and development of a hybrid PCR-based method for SARS-CoV-2 detection", + "rel_doi": "10.1101/2020.11.22.20236414", + "rel_title": "The variation of genome sites associated with severe COVID-19 across populations: the worldwide and national pattern", "rel_date": "2020-11-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.21.20236216", - "rel_abs": "The COVID-19 pandemic has presented multiple healthcare challenges, one of which is adequately meeting the need for large-scale diagnostic testing. The most commonly used assays for detection of SARS-CoV-2, including those recommended by the Center for Disease Control and Prevention (CDC), rely on a consistent set of core reagents. This has put a serious strain on the reagent supply chain, resulting in insufficient testing. It has also led to restricted animal testing, even though there are now multiple reports of animals, particularly cats, ferrets and minks, contracting the disease. We aimed to address the diagnostic bottleneck by developing a PCR-based SARS-CoV-2 detection assay for cats (and, potentially, other animals) which avoids the use of most common reagents, such as collection kits optimized for RNA stabilization, RNA isolation kits and TaqMan-based RT-PCR reagents. We demonstrated that an inexpensive solid-phase reversible immobilization (SPRI) method can be used for RNA extraction from feline samples collected with DNAGenoteks ORAcollect RNA OR-100 and PERFORMAgene DNA PG-100 sample collection kits, optimized for RNA or DNA stabilization, respectively. We developed a dual method SARS-CoV-2 detection assay relying on SYBR RT-PCR and Sanger sequencing, using the same set of custom synthesized oligo primers. We validated our tests specificity with a commercially available SARS-CoV-2 plasmid positive control, as well as two in-house positive control RNA samples. Our assays sensitivity was determined to be 10 viral copies per reaction. Our results suggest that a simple SPRI-dependent RNA extraction protocol and certain sample collection kits not specifically optimized for RNA stabilization could potentially be used in cases where reagent shortages are hindering adequate COVID-19 testing. These alternative reagents could be used in combination with our COVID-19 testing method, which relies on inexpensive and readily available SYBR RT-PCR and non-fluorescent PCR reagents. Depending on the detection goals and the laboratory setup available, the SYBR RT-PCR method and the Sanger sequencing based method can be used alone or in conjunction, for improved accuracy. Although the test is intended for animal use, it is, in theory, possible to use it with human samples, especially those with higher viral loads.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.22.20236414", + "rel_abs": "BackgroundThe knowledge of clinically relevant markers distribution might become a useful tool in COVID-19 therapy using personalized approach in the lack of unified recommendations for COVID-19 patients management during pandemic. We aimed to identify the frequencies and distribution patterns of rs11385942 and rs657152 polymorphic markers, associated with severe COVID-19, among populations of the world, as well at the national level within Russia. The study was also dedicated to reveal whether population frequencies of both polymorphic markers are associated with COVID-19 cases, recovery and death rates.\n\nMethodsWe genotyped 1883 samples from 91 ethnic populations from Russia and neighboring countries by rs11385942 and rs657152 markers. Local populations which were geographically close and genetically similar were pooled into 28 larger groups. In the similar way we compiled a dataset on the other regions of the globe using genotypes extracted or imputed from the available datasets (32 populations worldwide). The differences in alleles frequencies between groups were estimated and the frequency distribution geographic maps have been constructed. We run the correlation analysis of both markers frequencies in various populations with the COVID-19 epidemiological data on the same populations.\n\nFindingsThe cartographic analysis revealed that distribution of rs11385942 follows the West Eurasian pattern: it is frequent in Europeans, West Asians, and particularly in South Asians but rare or absent in all other parts of the globe. Notably, there is no abrupt changes in frequency across Eurasia but the clinal variation instead. The distribution of rs657152 is more homogeneous. Higher population frequencies of both risk alleles correlated positively with the death rate. For the rs11385942 we can state the tendency only (r=0,13, p=0.65), while for rs657152 the correlation was significantly high (r=0,59, p=0,02). These reasonable correlations were obtained on the Russian dataset, but not on the world dataset.\n\nInterpretationUsing epidemiological statistics on Russia and neighboring countries we revealed the evident correlation of the risk alleles frequencies with the death rate from COVID-19. The lack of such correlations at the world level should be attributed to the differences in the ways epidemiological data have been counted in different countries. So that, we believe that genetic differences between populations make small but real contribution into the heterogeneity of the pandemic worldwide. New studies on the correlations between COVID-19 recovery/mortality rates and populations gene pool are urgently needed.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Julie Yang", - "author_inst": "Basepaws" + "author_name": "Oleg Balanovsky", + "author_inst": "1 - Vavilov Institute of General Genetics, Moscow 119991, Russia; 2 - Research Centre for Medical Genetics, Moscow 115522, Russia; 3 - Biobank of North Eurasia," }, { - "author_name": "Elias Salfati", - "author_inst": "Basepaws" + "author_name": "Valerie Petrushenko", + "author_inst": "1- Vavilov Institute of General Genetics, Moscow 119991, Russia; 2 - Moscow Institute of Physics and Technology, Moscow 117303, Russia" }, { - "author_name": "Damian Kao", - "author_inst": "Basepaws" + "author_name": "Karin Mirzaev", + "author_inst": "Russian Medical Academy of Continuous Professional Education" }, { - "author_name": "Yuliana Mihaylova", - "author_inst": "Basepaws" + "author_name": "Sherzod Abdullaev", + "author_inst": "Russian Medical Academy of Continuous Professional Education" + }, + { + "author_name": "Igor Gorin", + "author_inst": "1 - Vavilov Institute of General Genetics, Moscow 119991, Russia; 2 - Moscow Institute of Physics and Technology, Moscow 117303, Russia" + }, + { + "author_name": "Denis Chernevskiy", + "author_inst": "Research Centre for Medical Genetics, Moscow 115522, Russia" + }, + { + "author_name": "Anastasiya Agdzhoyan", + "author_inst": "1 - Vavilov Institute of General Genetics, Moscow 119991, Russia; 2 - Moscow Institute of Physics and Technology, Moscow 117303, Russia" + }, + { + "author_name": "Elena Balanovska", + "author_inst": "1 - Research Centre for Medical Genetics, Moscow 115522, Russia; 2 - Biobank of North Eurasia, Moscow 115201, Russia" + }, + { + "author_name": "Alexander Kryukov", + "author_inst": "Russian Medical Academy of Continuous Professional Education" + }, + { + "author_name": "Dmitriy Sychev", + "author_inst": "Russian Medical Academy of Continuous Professional Education" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2020.11.23.20237107", @@ -1078547,33 +1077653,197 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.23.20237487", - "rel_title": "How closely is COVID-19 related to HCoV, SARS, and MERS? : Clinical comparison of coronavirus infections and identification of risk factors influencing the COVID-19 severity using common data model (CDM)", + "rel_doi": "10.1101/2020.11.24.20237719", + "rel_title": "Seroprevalence of SARS-CoV-2 infection in the craft and manual worker population of Qatar", "rel_date": "2020-11-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.23.20237487", - "rel_abs": "BackgroundSouth Korea was one of the epicenters for both the 2015 Middle East Respiratory Syndrome and 2019 COVID-19 outbreaks. However, there has been a lack of published literature, especially using the Electronic Medical Records (EMR), that provides a comparative summary of the prognostic factors present in the coronavirus-derived diseases. Therefore, in this study, we aimed to evaluate the distinct clinical traits between the infected patients of different coronaviruses to observe the extent of resemblance within the clinical features and to identify unique factors by disease severity that may influence the prognosis of COVID-19 patients.\n\nMethodsWe utilized the common data model (CDM), which is the database that houses the standardized EMR. We set COVID-19 as a reference group in comparative analyses. For statistical methods, we used Levenes test, one-way Anova test, Scheffe post-hoc test, Games-howell post-hoc test, and Students t-test for continuous variables, and chi-squared test and Fishers exact test for categorical variables. With the variables that reflected similarity in more than two comparisons between the disease groups yet significantly different between the COVID-19 severity groups, we performed univariate logistic regression to identify which common manifestations in coronaviruses are risk factors for severe COVID-19 outcomes.\n\nFindingsWe collected the records of 2840 COVID-19 patients, 67 MERS patients (several suspected cases included), 43 SARS suspected patients, and 87 HCoV patients. We found that a significantly higher number of COVID-19 patients had been diagnosed with comorbidities compared to the MERS and HCoV groups (48.5% vs. 10.4 %, p < 0.001 and 48.5% vs. 35.6%, p < 0.05) and also that the non-mild COVID-19 patients reported more comorbidities than the mild group (55.7% vs. 47.8%, p < 0.05). There were overall increases in the levels of fibrinogen in both sets of disease and severity groups. The univariate logistic regression showed that the male sex (OR: 1.66; CI: 1.29-2.13, p < 0.001), blood type A (OR: 1.80; CI: 1.40-2.31, p < 0.001), renal disease (OR: 3.27; CI: 2.34-4.55, p < 0.001), decreased creatinine level (OR: 2.05; CI: 1.45-2.88, p < 0.001), and elevated fibrinogen level (OR: 1.59, CI: 1.21-2.09, p < 0.001) are associated with the severe COVID-19 prognosis, whereas the patients reporting gastrointestinal symptoms (OR: 0.42; CI: 0.23-0.72, p < 0.01) and increased alkaline phosphatase (OR: 0.73; CI: 0.56-0.94, p < 0.05) are more less likely to experience complications and other severe outcomes from the SARS-CoV-2 infection.\n\nInterpretationThe present study observed the highest resemblance between the COVID-19 and SARS groups as clinical manifestations that were present in SARS group were linked to the severity of COVID-19. In particular, male individuals with blood type A and previous diagnosis of kidney failure were shown to be more susceptible to developing the poorer outcomes during COVID-19 infection, with a presentation of elevated level of fibrinogen.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.24.20237719", + "rel_abs": "BackgroundQatar experienced a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) epidemic that disproportionately affected the craft and manual worker (CMW) population who comprise 60% of the total population. This study aimed to assess the proportions of ever and/or current infection in this population.\n\nMethodsA cross-sectional population-based survey was conducted during July 26-September 09, 2020 to assess both anti-SARS-CoV-2 positivity through serological testing and polymerase chain reaction (PCR) positivity through PCR testing. Associations with antibody and PCR positivity were identified through regression analyses.\n\nResultsStudy included 2,641 participants, 69.3% of whom were <40 years of age. Anti-SARS-CoV-2 positivity was estimated at 55.3% (95% CI: 53.3-57.3%) and was significantly associated with nationality, geographic location, educational attainment, occupation, presence of symptoms in the two weeks preceding the survey, and previous infection diagnosis. PCR positivity was assessed at 11.3% (95% CI: 9.9-12.8%) and was significantly associated with geographic location, contact with an infected person, and reporting two or more symptoms. Infection positivity (antibody and/or PCR positive) was assessed at 60.6% (95% CI: 9.9-12.8%). The proportion of antibody-positive CMWs that had a prior SARS-CoV-2 diagnosis was 9.3% (95% CI: 7.9-11.0%). Only seven infections were ever severe and one was ever critical--an infection severity rate of 0.5% (95% CI: 0.2-1.0%).\n\nConclusionsSix in every 10 CMWs have been infected, suggestive of reaching the herd immunity threshold. Infection severity was low with only one in every 200 infections progressing to be severe or critical. Only one in every 10 infections had been previously diagnosed suggestive of mostly asymptomatic or minimally mild infections.", + "rel_num_authors": 45, "rel_authors": [ { - "author_name": "Yeon Hee Kim", - "author_inst": "Biomedical Research Institute, Seoul National University Hospital" + "author_name": "Mohamed H. Al-Thani", + "author_inst": "Ministry of Public Health, Doha, Qatar" + }, + { + "author_name": "Elmoubasher Farag", + "author_inst": "Ministry of Public Health, Doha, Qatar" + }, + { + "author_name": "Roberto Bertollini", + "author_inst": "Ministry of Public Health, Doha, Qatar" + }, + { + "author_name": "Hamad Eid Al Romaihi", + "author_inst": "Ministry of Public Health, Doha, Qatar" + }, + { + "author_name": "Sami Abdeen", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Ashraf Abdelkarim", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Faisal Daraan", + "author_inst": "Ministry of Public Health, Doha, Qatar" + }, + { + "author_name": "Ahmed Ismail", + "author_inst": "Ministry of Public Health, Doha, Qatar" + }, + { + "author_name": "Nahid Mostafa", + "author_inst": "Ministry of Public Health, Doha, Qatar" + }, + { + "author_name": "Mohamed Sahl", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Jinan Suliman", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Elias Tayar", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Hasan Ali Kasem", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Meynard J. A. Agsalog", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Bassam K. Akkarathodiyil", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Ayat A. Alkhalaf", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Mohamed Morhaf M. H. Alakshar", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Abdulsalam Ali A. H. Al-Qahtani", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Monther H. A. Al-Shedifat", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Anas Ansari", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Ahmad Ali Ataalla", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Sandeep Chougule", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Abhilash K. K. V. Gopinathan", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Feroz J. Poolakundan", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Sanjay U. Ranbhise", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Saed M. A. Saefan", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Mohamed M. Thaivalappil", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Abubacker S. Thoyalil", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Inayath M. Umar", + "author_inst": "Qatar Red Crescent Society, Doha, Qatar" + }, + { + "author_name": "Zaina Al Kanaani", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Abdullatif Al Khal", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Einas Al Kuwari", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Adeel A. Butt", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Peter Coyle", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Andrew Jeremijenko", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Anvar Hassan Kaleeckal", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Ali Nizar Latif", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" + }, + { + "author_name": "Riyazuddin Mohammad Shaik", + "author_inst": "Hamad Medical Corporation, Doha, Qatar" }, { - "author_name": "Ye-Hee Ko", - "author_inst": "Biomedical Research Institute, Seoul National University Hospital" + "author_name": "Hanan F. Abdul Rahim", + "author_inst": "College of Health Sciences, QU Health, Qatar University, Doha, Qatar" }, { - "author_name": "Sooyoung Kim", - "author_inst": "Biomedical Research Institute, Seoul National University Hospital" + "author_name": "Hadi M. Yassine", + "author_inst": "Biomedical Research Center, Qatar University, Doha, Qatar" }, { - "author_name": "Kwangsoo Kim", - "author_inst": "Transdisciplinary Department of Medicine & Advanced Technology, Seoul National University Hospital" + "author_name": "Gheyath K. Nasrallah", + "author_inst": "Biomedical Research Center, Qatar University, Doha, Qatar" + }, + { + "author_name": "Mohamed G. Al Kuwari", + "author_inst": "Primary Health Care Corporation, Doha, Qatar" + }, + { + "author_name": "Odette Chaghoury", + "author_inst": "Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar" + }, + { + "author_name": "Hiam Chemaitelly", + "author_inst": "Infectious Disease Epidemiology Group, Weill Cornell Medicine-Qatar, Cornell University, Doha, Qatar" + }, + { + "author_name": "Laith J Abu-Raddad", + "author_inst": "Weill Cornell Medicine-Qatar" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1080045,77 +1079315,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.20.20231696", - "rel_title": "Antibody response patterns in COVID-19 patients with different levels of disease severity-Japan", + "rel_doi": "10.1101/2020.11.20.20235390", + "rel_title": "Improved RT-PCR SARS-Cov2 results interpretation by indirect determination of cut-off cycle threshold value.", "rel_date": "2020-11-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20231696", - "rel_abs": "BackgroundWe analyzed antibody response patterns according to level of disease severity in patients with novel coronavirus disease 2019 (COVID-19) in Japan.\n\nMethodsWe analyzed 611 serum specimens from 231 patients with COVID-19 (mild, 170; severe, 31; critical, 30). IgM and IgG antibodies against nucleocapsid protein (N) and spike 1 protein (S1) were detected by enzyme-linked immunosorbent assays.\n\nFindingsThe peaks of fitting curves for the OD values of IgM and IgG antibodies against N appeared simultaneously, while those against S1 were delayed compared with N. The OD values of IgM against N and IgG against both N and S1 were significantly higher in the severe and critical cases than in the mild cases at 11 days after symptom onset. The seroconversion rates of IgG were higher than those of IgM against both N and S1 during the clinical course based on the optimal cut-off values defined in this study. The seroconversion rates of IgG and IgM against N and S1 were higher in the severe and critical cases than in the mild cases.\n\nConclusionOur findings show that a stronger antibody response occurred in COVID-19 patients with greater disease severity and there were low seroconversion rates of antibodies against N and S1 in the mild cases. The antibody response patterns in our population suggest a second infection pattern, leading us to hypothesize that cross-reactivity occurs between SARS-CoV-2 and past infection with other human coronaviruses.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20235390", + "rel_abs": "Clinical laboratories of the developing world are overwhelmed with RT-PCR SARS-Cov2 testing demands. It is of paramount importance that each clinical laboratory use an appropriate cut-off value in the interpretation of SARS-Cov2 real-time RT-PCR results, which is specific to their laboratory performances as ISO 15189 recommendations stipulate. We applied an indirect statistical method to a large mixed data set of Ct values (ORF1ab and N) to estimate cut-off Ct value ([~]32 cycles).we conclude that the use of indirect statistical approaches to estimate cut-off value in the interpretation of SARS-Cov2 real-time RT-PCR results may improve differential diagnosis of COVID-19 cases with low risk of infectivity, and may help to better estimates of the burden of COVID-19 disease.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Kazuo Imai", - "author_inst": "Saitama Medical University" - }, - { - "author_name": "Yutaro Kitagawa", - "author_inst": "Saitama Medical University Hospital" - }, - { - "author_name": "Sakiko Tabata", - "author_inst": "Self-Defense Forces Central Hospital" - }, - { - "author_name": "Katsumi Kubota", - "author_inst": "Saitama Medical University Hospital" - }, - { - "author_name": "Mayu Ikeda", - "author_inst": "Self-Defense Forces Central Hospital" - }, - { - "author_name": "Masaru Matuoka", - "author_inst": "Saitama Medical University Hospital" - }, - { - "author_name": "Kazuyasu Miyoshi", - "author_inst": "Self-Defense Forces Central Hospital" - }, - { - "author_name": "Jun Sakai", - "author_inst": "Saitama Medical University" - }, - { - "author_name": "Noriomi Ishibashi", - "author_inst": "Saitama Medical University" - }, - { - "author_name": "Norihito Tarumoto", - "author_inst": "Saitama Medical University" - }, - { - "author_name": "Shinichi Takeuchi", - "author_inst": "Saitama Medical University Hospital" - }, - { - "author_name": "Toshimitsu Ito", - "author_inst": "Self-Defense Forces Central Hospital" - }, - { - "author_name": "Shigefumi Maesaki", - "author_inst": "Saitama Medical University" - }, - { - "author_name": "Kaku Tamura", - "author_inst": "Self-Defense Forces Central Hospital" - }, - { - "author_name": "Takuya Maeda", - "author_inst": "Saitama Medical University" + "author_name": "khelil mohamed mokhtar", + "author_inst": "institut pasteur Algeria" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1081611,59 +1080825,75 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2020.11.20.20235440", - "rel_title": "Coagulation factors and COVID-19 severity: Mendelian randomization analyses and supporting evidence", + "rel_doi": "10.1101/2020.11.20.20227355", + "rel_title": "Single cell profiling of COVID-19 patients: an international data resource from multiple tissues", "rel_date": "2020-11-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20235440", - "rel_abs": "BackgroundThe evolving pandemic of COVID-19 is arousing alarm to public health. According to epidemiological and observational studies, coagulopathy was frequently seen in severe COVID-19 patients, yet the causality from specific coagulation factors to COVID-19 severity and the underlying mechanism remain elusive.\n\nMethodsFirst, we leveraged Mendelian randomization (MR) analyses to assess causal relationship between 12 coagulation factors and severe COVID-19 illness based on two genome-wide association study (GWAS) results of COVID-19 severity. Second, we curated clinical evidence supporting causal associations between COVID-19 severity and particular coagulation factors which showed significant results in MR analyses. Third, we validated our results in an independent cohort from UK Biobank (UKBB) using polygenic risk score (PRS) analysis and logistic regression model. For all MR analyses, GWAS summary-level data were used to ascertain genetic effects on exposures against disease risk.\n\nResultsWe revealed that genetic predisposition to the antigen levels of von Willebrand factor (VWF) and the activity levels of its cleaving protease ADAMTS13 were causally associated with COVID-19 severity, wherein elevated VWF antigen level (P = 0.005, odds ratio (OR) = 1.35, 95% confidence interval (CI): 1.09-1.68 in the Severe COVID-19 GWAS Group cohort; P = 0.039, OR = 1.21, 95% CI: 1.01-1.46 in the COVID-19 Host Genetics Initiative cohort) and lowered ADAMTS13 activity (P = 0.025, OR = 0.69, 95% CI: 0.50-0.96 in the Severe COVID-19 GWAS Group cohort) lead to increased risk of severe COVID-19 illness. No significant causal association of tPA, PAI-1, D-dimer, FVII, PT, FVIII, FXI, aPTT, FX or ETP with COVID-19 severity was observed. In addition, as an independent factor, VWF PRS explains a 31% higher risk of severe COVID-19 illness in the UKBB cohort (P = 0.047, OR per SD increase = 1.31, 95% CI: 1.00-1.71). In combination with age, sex, BMI and several pre-existing disease statues, our model can predict severity risks with an AUC of 0.70.\n\nConclusionTogether with the supporting evidence of recent retrospective cohort studies and independent validation based on UKBB data, our results suggest that the associations between coagulation factors VWF/ADAMTS13 and COVID-19 severity are essentially causal, which illuminates one of possible mechanisms underlying COVID-19 severity. This study also highlights the importance of dynamically monitoring the plasma levels of VWF/ADAMTS13 after SARS-CoV-2 infection, and facilitates the development of treatment strategy for controlling COVID-19 severity and associated thrombotic complication.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.20.20227355", + "rel_abs": "[Abstract]In late 2019 and through 2020, the COVID-19 pandemic swept the world, presenting both scientific and medical challenges associated with understanding and treating a previously unknown disease. To help address the need for great understanding of COVID-19, the scientific community mobilized and banded together rapidly to characterize SARS-CoV-2 infection, pathogenesis and its distinct disease trajectories. The urgency of COVID-19 provided a pressing use-case for leveraging relatively new tools, technologies, and nascent collaborative networks. Single-cell biology is one such example that has emerged over the last decade as a powerful approach that provides unprecedented resolution to the cellular and molecular underpinnings of biological processes. Early foundational work within the single-cell community, including the Human Cell Atlas, utilized published and unpublished data to characterize the putative target cells of SARS-CoV-2 sampled from diverse organs based on expression of the viral receptor ACE2 and associated entry factors TMPRSS2 and CTSL (Muus et al., 2020; Sungnak et al., 2020; Ziegler et al., 2020). This initial characterization of reference data provided an important foundation for framing infection and pathology in the airway as well as other organs. However, initial community analysis was limited to samples derived from uninfected donors and other previously-sampled disease indications. This report provides an overview of a single-cell data resource derived from samples from COVID-19 patients along with initial observations and guidance on data reuse and exploration.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Yao Zhou", - "author_inst": "Tianjin Medical University" + "author_name": "Esteban Ballestar", + "author_inst": "Josep Carreras Research Institute (IJC)" }, { - "author_name": "Zipeng Liu", - "author_inst": "The University of Hong Kong" + "author_name": "Donna L Farber", + "author_inst": "Columbia University" }, { - "author_name": "Hongxi Yang", - "author_inst": "Tianjin Medical University" + "author_name": "Sarah Glover", + "author_inst": "University Mississippi Medical Center" }, { - "author_name": "Jianhua Wang", - "author_inst": "Tianjin Medical University" + "author_name": "Bruce Horwitz", + "author_inst": "Boston Children's Hospital" }, { - "author_name": "Tong Liu", - "author_inst": "Tianjin Medical University" + "author_name": "Kerstin Meyer", + "author_inst": "Wellcome Sanger Genome Center" }, { - "author_name": "Kexin Chen", - "author_inst": "Tianjin Medical University" + "author_name": "Marko Nikolic", + "author_inst": "University College London" }, { - "author_name": "Yaogang Wang", - "author_inst": "Tianjin Medical University" + "author_name": "Jose Ordovas-Montanes", + "author_inst": "Boston Children's Hospital" }, { - "author_name": "Pak Chung Sham", - "author_inst": "The University of Hong Kong" + "author_name": "Peter A Sims", + "author_inst": "Columbia University Medical Center" }, { - "author_name": "Ying Yu", - "author_inst": "Tianjin Medical University" + "author_name": "Alex K Shalek", + "author_inst": "Massachusetts Institute of Technology" }, { - "author_name": "Mulin Jun Li", - "author_inst": "Tianjin Medical University" + "author_name": "Niels Vandamme", + "author_inst": "Vlaams Instituut voor Biotechnologie" + }, + { + "author_name": "Linos Vandekerckhove", + "author_inst": "University of Ghent" + }, + { + "author_name": "Roser Vento-Tormo", + "author_inst": "Wellcome Sanger Genome Center" + }, + { + "author_name": "Alexandra Chloe Villani", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "- Chan Zuckerberg Initiative Single-Cell COVID-19 Consortia", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "genetic and genomic medicine" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.11.20.20235705", @@ -1083937,25 +1083167,109 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.17.20231290", - "rel_title": "Secondary Attack Rate (SAR) in household contacts of expired primary cases of COVID-19: A study from Western India", + "rel_doi": "10.1101/2020.11.18.20230599", + "rel_title": "Remdesivir induced viral RNA and subgenomic RNA suppression, and evolution of viral variants in SARS-CoV-2 infected patients.", "rel_date": "2020-11-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.17.20231290", - "rel_abs": "Secondary attack rate (SAR) in household contacts of expired primary COVID-19 cases is not well studied yet. Based on our previous pilot study conducted in Gandhinagar district of Gujarat state, we developed a new research protocol to understand SAR statistics in household contacts of COVID-19 cases that died/expired. The details of expired COVID positive primary cases were obtained from Government records and the details of secondary cases were retrieved using telephonic interviews of the household members. Forty-nine expired cases were registered between March to August, 2020. Out of 49 deaths, 28 families could be reached on phone. Rest were not reachable or refused to give information. These were interviewed after taking verbal consent. The study reported 25% SAR in household contact of expired primary cases with 7.4% of mortality in secondary cases. Though this is representative data only from a single district, it was observed that 75% of the household contacts were still not infected in spite of repeated contact with the sever cases. More such studies in various regions are needed to understand disease transmission.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.18.20230599", + "rel_abs": "While changes in SARS-CoV-2 viral load over time have been documented, detailed information on the impact of remdesivir and how it might alter intra-host viral evolution is limited. Sequential viral loads and deep sequencing of SARS-CoV-2 recovered from the upper respiratory tract of hospitalised children revealed that remdesivir treatment suppressed viral RNA levels in one patient but not in a second infected with an identical strain. Evidence of drug resistance to explain this difference was not found. Reduced levels of subgenomic (sg) RNA during treatment of the second patient, suggest an additional effect of remdesivir on viral replication that is independent of viral RNA levels. Haplotype reconstruction uncovered persistent SARS-CoV-2 variant genotypes in four patients. We conclude that these are likely to have arisen from within-host evolution, and not co-transmission, although superinfection cannot be excluded in one case. Sample-to-sample heterogeneity in the abundances of variant genotypes is best explained by the presence of discrete viral populations in the lung with incomplete population sampling in diagnostic swabs. Such compartmentalisation is well described in serious lung infections caused by influenza and Mycobacterium tuberculosis and has been associated with poor drug penetration, suboptimal treatment and drug resistance. Our data provide evidence that remdesivir is able to suppress SARS-CoV-2 replication in vivo but that its efficacy may be compromised by factors reducing penetration into the lung. Based on data from influenza and Mycobacterium tuberculosis lung infections we conclude that early use of remdesivir combined with other agents should now be evaluated.\n\nSummary SentenceDeep sequencing of longitudinal samples from SARS-CoV-2 infected paediatric patients identifies evidence of remdesivir-associated inhibition of viral replication in vivo and uncovers evidence of within host evolution of distinct viral genotypes.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Komal Shah", - "author_inst": "Indian Institute of Public Health Gandhinagar" + "author_name": "Florencia A.T. Boshier", + "author_inst": "Department of Infection, Immunity and Inflammation, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom" }, { - "author_name": "Nupur Desai", - "author_inst": "Newyork university" + "author_name": "Juanita Pang", + "author_inst": "Department of Infection, Immunity and Inflammation, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom" }, { - "author_name": "Dileep Mavalankar", - "author_inst": "Indian Institute of Public Health Gandhinagar" + "author_name": "Justin Penner", + "author_inst": "Department of Infectious Disease, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom." + }, + { + "author_name": "Joseph Hughes", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom." + }, + { + "author_name": "Matthew Parker", + "author_inst": "Department of Infection, Immunity and Cardiovascular Diseases, The Florey Institute, University of Sheffield, Sheffield, United Kingdom." + }, + { + "author_name": "James G Shepherd", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom." + }, + { + "author_name": "Nele Alders", + "author_inst": "Department of Infectious Disease, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom." + }, + { + "author_name": "Alasdair Bamford", + "author_inst": "Department of Infectious Disease, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom." + }, + { + "author_name": "Louis Grandjean", + "author_inst": "Department of Infection, Immunity and Inflammation, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom" + }, + { + "author_name": "Stephanie Grunewald", + "author_inst": "Department of Metabolic Medicine, UCL Great Ormond Street Institute of Child Health, London, London United Kindgom.." + }, + { + "author_name": "James Hatcher", + "author_inst": "Department of Microbiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom." + }, + { + "author_name": "Timothy Best", + "author_inst": "Department of Microbiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom." + }, + { + "author_name": "Caroline Dalton", + "author_inst": "Department of Pharmacy, Great Ormond Street Hospital for Children NHS Trust, London, UK" + }, + { + "author_name": "Patricia Dyal Bynoe", + "author_inst": "Department of Infection, Immunity and Inflammation, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom" + }, + { + "author_name": "Claire Frauenfelder", + "author_inst": "Department of Ears, Nose and Throat, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom." + }, + { + "author_name": "Jutta Koeglmeier", + "author_inst": "Department of Gastroenterology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, United Kingdom." + }, + { + "author_name": "Phoebe Myerson", + "author_inst": "Department of Infection, Immunity and Inflammation, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom" + }, + { + "author_name": "Sunando Roy", + "author_inst": "Department of Infection, Immunity and Inflammation, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom" + }, + { + "author_name": "Rachel Williams", + "author_inst": "Department of Infection, Immunity and Inflammation, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom" + }, + { + "author_name": "- The COVID-19 Genomics UK (COG-UK) Consortium", + "author_inst": "" + }, + { + "author_name": "Emma C Thomson", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, Glasgow, United Kingdom." + }, + { + "author_name": "Thushan I de Silva", + "author_inst": "Department of Infection, Immunity and Cardiovascular Diseases, The Florey Institute, University of Sheffield, Sheffield, United Kingdom." + }, + { + "author_name": "Richard A Goldstein", + "author_inst": "Division of Infection and Immunity, University College London, London, United Kingdom." + }, + { + "author_name": "Judith Breuer", + "author_inst": "Department of Infection, Immunity and Inflammation, UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom" } ], "version": "1", @@ -1085787,23 +1085101,43 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.11.19.20234716", - "rel_title": "A precise measure of the impact of the first wave of Covid-19 on life expectancy. Regional differentials in Switzerland", + "rel_doi": "10.1101/2020.11.17.20233312", + "rel_title": "Temporal Associations between Community Incidence of COVID-19 and Nursing Home Outbreaks in Ontario, Canada", "rel_date": "2020-11-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.19.20234716", - "rel_abs": "Based on publicly available data supplied by the Swiss Federal Statistical Office (FSO), we calculated life tables by sex and by week for seven major regions of Switzerland in 2020, up to October 26th. These life tables provide information on the trends of life expectancy at birth and at the age of 65 years during the first wave of the coronavirus disease 2019 (COVID-19) epidemic.\n\nThe results show a strong cyclical decrease in life expectancy, particularly in Ticino, where this variable has decreased by almost 6 years compared to the 2019 life expectancy, and in the Lake Geneva region. The other regions of Switzerland observed more modest decreases during the first wave, generally not exceeding a 2-year reduction. This decrease can be explained to some extent by seasonal variations in this indicator.\n\nIn conclusion, the very sharp decrease in the average lifespan observed in the two regions mentioned above suggests that the first wave of the epidemic had a significant impact. It also reflects an unfavourable health situation. The life expectancy at the age of 65 years observed at the end of March 2020 in Ticino corresponded to the average life expectancy observed in Switzerland forty years ago.\n\nThe calculated indicators have the advantage of accounting for the age structures of the respective populations. They therefore demonstrate their usefulness in monitoring during a pandemic, such as the one occurring currently.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.17.20233312", + "rel_abs": "The risk of nursing home COVID-19 outbreaks is strongly associated with the rate of infection in the communities surrounding homes, yet the temporal relationship between rising rates of community COVID-19 infection and the risk threshold for subsequent nursing home COVID-19 outbreaks is not well defined. This population-based cohort study included all COVID-19 cases in Canadas most populous Province of Ontario between March 1-July 16, 2020. We evaluated the temporal relationship between trends in the number of active community COVID-19 cases and the number of nursing home outbreaks. We found that the average lag time between community cases and nursing home outbreaks was 23 days for Ontario overall, with substantial variability across geographic regions. We also determined thresholds of community incidence of COVID-19 associated with a 75% probability of observing a nursing home outbreak 5, 10 and 15 days into the future. For the province overall, when daily active COVID-19 community cases are 2.30 per 100,000 population, there is a 75% probability of a nursing home outbreak occurring five days later.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Philippe Wanner", - "author_inst": "University of Geneva" + "author_name": "Kamil Malikov", + "author_inst": "Capacity Planning and Analytics Division, Ontario Ministry of Health, Toronto, Canada" + }, + { + "author_name": "Qing Huang", + "author_inst": "Capacity Planning and Analytics Division, Ontario Ministry of Health, Toronto, Canada" + }, + { + "author_name": "Shengli Shi", + "author_inst": "Capacity Planning and Analytics Division, Ontario Ministry of Health, Toronto, Canada" + }, + { + "author_name": "Nathan M. Stall", + "author_inst": "University of Toronto" + }, + { + "author_name": "Ashleigh Tuite", + "author_inst": "University of Toronto" + }, + { + "author_name": "Michael P. Hillmer", + "author_inst": "Capacity Planning and Analytics Division, Ontario Ministry of Health, Toronto, Canada" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "geriatric medicine" }, { "rel_doi": "10.1101/2020.11.18.20233874", @@ -1087465,57 +1086799,33 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.11.17.20220681", - "rel_title": "An efficient distributed algorithm with application to COVID-19 data from heterogeneous clinical sites", + "rel_doi": "10.1101/2020.11.17.20231548", + "rel_title": "Meta-analysis of the SARS-CoV-2 serial interval and the impact of parameter uncertainty on the COVID-19 reproduction number", "rel_date": "2020-11-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.17.20220681", - "rel_abs": "ObjectivesIntegrating electronic health records (EHR) data from several clinical sites offers great opportunities to improve estimation with a more general population compared to analyses based on a single clinical site. However, sharing patient-level data across sites is practically challenging due to concerns about maintaining patient privacy. The objective of this study is to develop a novel distributed algorithm to integrate heterogeneous EHR data from multiple clinical sites without sharing patient-level data.\n\nMaterials and MethodsThe proposed distributed algorithm for binary regression can effectively account for between-site heterogeneity and is communication-efficient. Our method is built on a pairwise likelihood function in the extended Mantel-Haenszel regression, which is known to be statistically highly efficient. We construct a surrogate pairwise likelihood function through approximating the target pairwise likelihood by its surrogate. We show that the proposed surrogate pairwise likelihood leads to a consistent and asymptotically normal estimator by effective communication without sharing individual patient-level data. We study the empirical performance of the proposed method through a systematic simulation study and an application with data of 14,215 COVID-19 patients from 230 clinical sites at UnitedHealth Group Clinical Research Database.\n\nResultsThe proposed method was shown to perform close to the gold standard approach under extensive simulation settings. When the event rate is <5%, the relative bias of the proposed estimator is 30% smaller than that of the meta-analysis estimator. The proposed method retained high accuracy across different sample sizes and event rates compared with meta-analysis. In the data evaluation, the proposed estimate has a relative bias <9% when the event rate is <1%, whereas the meta-analysis estimate has a relative bias at least 10% higher than that of the proposed method.\n\nConclusionsOur simulation study and data application demonstrate that the proposed distributed algorithm provides an estimator that is robust to heterogeneity in event rates when effectively integrating data from multiple clinical sites. Our algorithm is therefore an effective alternative to both meta-analysis and existing distributed algorithms for modeling heterogeneous multi-site binary outcomes.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.17.20231548", + "rel_abs": "The serial interval of an infectious disease, commonly interpreted as the time between onset of symptoms in sequentially infected individuals within a chain of transmission, is a key epidemiological quantity involved in estimating the reproduction number. The serial interval is closely related to other key quantities, including the incubation period, the generation interval (the time between sequential infections) and time delays between infection and the observations associated with monitoring an outbreak such as confirmed cases, hospital admissions and deaths. Estimates of these quantities are often based on small data sets from early contact tracing and are subject to considerable uncertainty, which is especially true for early COVID-19 data. In this paper we estimate these key quantities in the context of COVID-19 for the UK, including a meta-analysis of early estimates of the serial interval. We estimate distributions for the serial interval with a mean 5.6 (95% CrI 5.1-6.2) and SD 4.2 (95% CrI 3.9-4.6) days (empirical distribution), the generation interval with a mean 4.8 (95% CrI 4.3-5.41) and SD 1.7 (95% CrI 1.0-2.6) days (fitted gamma distribution), and the incubation period with a mean 5.5 (95% CrI 5.1-5.8) and SD 4.9 (95% CrI 4.5-5.3) days (fitted log normal distribution). We quantify the impact of the uncertainty surrounding the serial interval, generation interval, incubation period and time delays, on the subsequent estimation of the reproduction number, when pragmatic and more formal approaches are taken. These estimates place empirical bounds on the estimates of most relevant model parameters and are expected to contribute to modelling COVID-19 transmission.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Jiayi Tong", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Chongliang Luo", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Md Nazmul Islam", - "author_inst": "UnitedHealth Group" - }, - { - "author_name": "Natalie Sheils", - "author_inst": "UnitedHealth Group" - }, - { - "author_name": "John Buresh", - "author_inst": "UnitedHealth Group" - }, - { - "author_name": "Mackenzie Edmondson", - "author_inst": "University of Pennsylvania" - }, - { - "author_name": "Peter A. Merkel", - "author_inst": "University of Pennsylvania" + "author_name": "Robert Challen", + "author_inst": "EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, Devon, UK" }, { - "author_name": "Ebbing Lautenbach", - "author_inst": "University of Pennsylvania" + "author_name": "Ellen Brooks-Pollock", + "author_inst": "Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK." }, { - "author_name": "Rui Duan", - "author_inst": "Harvard University" + "author_name": "Krasimira Tsaneva-Atanasova", + "author_inst": "EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, Devon, UK" }, { - "author_name": "Yong Chen", - "author_inst": "University of Pennsylvania" + "author_name": "Leon Danon", + "author_inst": "Data Science Institute, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK." } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1088723,47 +1088033,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.16.20232900", - "rel_title": "High throughput wastewater SARS-CoV-2 detection enables forecasting of community infection dynamics in San Diego county", + "rel_doi": "10.1101/2020.11.18.20233957", + "rel_title": "Early impact of school closure and social distancing for COVID-19 on the number of inpatients with childhood non-COVID-19 acute infections in Japan", "rel_date": "2020-11-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20232900", - "rel_abs": "Large-scale wastewater surveillance has the ability to greatly augment the tracking of infection dynamics especially in communities where the prevalence rates far exceed the testing capacity. However, current methods for viral detection in wastewater are severely lacking in terms of scaling up for high throughput. In the present study, we employed an automated magnetic-bead based concentration approach for viral detection in sewage that can effectively be scaled up for processing 24 samples in a single 40-minute run. The method compared favorably to conventionally used methods for viral wastewater concentrations with higher recovery efficiencies from input sample volumes as low as 10ml and can enable the processing of over 100 wastewater samples in a day. The sensitivity of the high-throughput protocol was shown to detect cases as low as 2 in a hospital building with a known COVID-19 caseload. Using the high throughput pipeline, samples from the influent stream of the primary wastewater treatment plant of San Diego county (serving 2.3 million residents) were processed for a period of 13 weeks. Wastewater estimates of SARS-CoV-2 viral genome copies in raw untreated wastewater correlated strongly with clinically reported cases by the county, and when used alongside past reported case numbers and temporal information in an autoregressive integrated moving average (ARIMA) model enabled prediction of new reported cases up to 3 weeks in advance. Taken together, the results show that the high-throughput surveillance could greatly ameliorate comprehensive community prevalence assessments by providing robust, rapid estimates.\n\nImportanceWastewater monitoring has a lot of potential for revealing COVID-19 outbreaks before they happen because the virus is found in the wastewater before people have clinical symptoms. However, application of wastewater-based surveillance has been limited by long processing times specifically at the concentration step. Here we introduce a much faster method of processing the samples, and show that its robustness by demonstrating direct comparisons with existing methods and showing that we can predict cases in San Diego by a week with excellent accuracy, and three weeks with fair accuracy, using city sewage. The automated viral concentration method will greatly alleviate the major bottleneck in wastewater processing by reducing the turnaround time during epidemics.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.18.20233957", + "rel_abs": "Many countries have implemented school closures as part of social distancing measures intended to control the spread of coronavirus disease 2019 (COVID-19). The aim of this study was to assess the early impact of nationwide school closure (March-May 2020) and social distancing for COVID-19 on the number of inpatients with major childhood infectious diseases in Japan. Using data from the Diagnosis Procedure Combination system in Japan, we identified patients aged 15 years or younger with admissions for a diagnosis of upper respiratory tract infection (URTI), lower respiratory tract infection (LRTI), influenza, gastrointestinal infection (GII), appendicitis, urinary tract infection (UTI), or skin and soft tissue infection (SSTI) between July 2018 and June 2020. Two periods were considered in the analysis: a pre- and a post-school-closure period. Changes in the trend of the weekly number of inpatients between the two periods were assessed using interrupted time-series analysis. A total of 75,053 patients in 210 hospitals were included. We found a marked reduction in the number of inpatients in the post-school-closure period, with an estimated reduction of 581 (standard error 42.9) inpatients per week (p < 0.001). The main part of the reduction was for pre-school children. Remarkable decreases in the number of inpatients with URI, LRTI, and GII were observed, while there were relatively mild changes in the influenza, appendicitis, UTI, and SSTI groups. We confirmed a marked reduction in the number of inpatients with childhood non-COVID-19 acute infections in the post-school-closure period.", "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Smruthi Karthikeyan", - "author_inst": "University of California - San Diego School of Medicine" + "author_name": "Kenji Kishimoto", + "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" }, { - "author_name": "Nancy Ronquillo", - "author_inst": "University of California, San Diego" + "author_name": "Seiko Bun", + "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" }, { - "author_name": "Pedro Belda-Ferre", - "author_inst": "University of California, San Diego" + "author_name": "Jung-ho Shin", + "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" }, { - "author_name": "Destiny Alvarado", - "author_inst": "University of California, San Diego" + "author_name": "Daisuke Takada", + "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" }, { - "author_name": "Tara Javidi", - "author_inst": "University of California, San Diego" + "author_name": "Tetsuji Morishita", + "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" }, { - "author_name": "Christopher A. Longhurst", - "author_inst": "UCSD" + "author_name": "Susumu Kunisawa", + "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" }, { - "author_name": "Rob Knight", - "author_inst": "University of California, San Diego" + "author_name": "Yuichi Imanaka", + "author_inst": "Department of Healthcare Economics and Quality Management, Graduate School of Medicine, Kyoto University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pediatrics" }, { "rel_doi": "10.1101/2020.11.17.20233585", @@ -1090473,23 +1089783,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.11.16.20149377", - "rel_title": "The effects of hypertension as an existing comorbidity on mortality rate in patients with COVID-19: a systematic review and meta-analysis.", + "rel_doi": "10.1101/2020.11.17.387068", + "rel_title": "Assessment of protein-protein interfaces in cryo-EM derived assemblies", "rel_date": "2020-11-17", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.16.20149377", - "rel_abs": "IntroductionCoronavirus has spread throughout the world rapidly, and there is a growing need to identify host risk factors to identify those most at risk. There is a growing body of evidence suggesting a close link exists between an increased risk of infection and an increased severity of lung injury and mortality, in patients infected with COVID-19 who have existing hypertension. This is thought to be due to the possible involvement of the virus target receptor, ACE2, in the renin-angiotensin-aldosterone blood pressure management system.\n\nObjectiveTo investigate the association between hypertension as an existing comorbidity and mortality in hospitalized patients with confirmed coronavirus disease 2019 (COVID-19).\n\nMethodsA systematic literature search in several databases was performed to identify studies that comment on hypertension as an existing comorbidity, and its effect on mortality in hospitalized patients with confirmed COVID-19 infection. The results of these studies were then pooled, and a meta-analysis was peformed to assess the overall effect of hypertension as an existing comorbidity on risk of mortality in hospitalized COVID-19 positive patients.\n\nResultsA total of 12243 hospitalised patients were pooled from 19 studies. All studies demonstrated a higher fatality rate in hypertensive COVID-19 patients when compared to non-hypertensive patients. Meta-analysis of the pooled studies also demonstrated that hypertension was associated with increased mortality in hospitalized patients with confirmed COVID-19 infection (risk ratio (RR) 2.57 (95% confidence interval (CI) 2.10, 3.14), p < 0.001; I2 =74.98%).\n\nConclusionHypertension is associated with 157% increased risk of mortality in hospitalized COVID-19 positive patients. These results have not been adjusted for age, and a meta-regression of covariates including age is required to make these findings more conclusive.\n\nSummaryRisk of mortality is considerably higher in hospitalised COVID-19 patients who have hypertension as an existing comorbidity prior to admission.", - "rel_num_authors": 1, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.17.387068", + "rel_abs": "Structures of macromolecular assemblies derived from cryo-EM maps often contain errors that become more abundant with decreasing resolution. Despite efforts in the cryo-EM community to develop metrics for the map and atomistic model validation, thus far, no specific scoring metrics have been applied systematically to assess the interface between the assembly subunits. Here, we have assessed protein-protein interfaces in macromolecular assemblies derived by cryo-EM. To this end, we developed PI-score, a density-independent machine learning-based metric, trained using protein-protein interfaces features in high-resolution crystal structures. Using PI-score, we were able to identify errors at interfaces in the PDB-deposited cryo-EM structures (including SARS-CoV-2 complexes) and in the models submitted for cryo-EM targets in CASP13 and the EM model challenge. Some of the identified errors, especially at medium-to-low resolution structures, were not captured by density-based assessment scores. Our method can therefore provide a powerful complementary assessment tool for the increasing number of complexes solved by cryo-EM.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Elena Whiteman", - "author_inst": "University of Warwick" + "author_name": "Sony Malhotra", + "author_inst": "Birkbeck College, University of London" + }, + { + "author_name": "Agnel Praveen Joseph", + "author_inst": "SCD, STFC" + }, + { + "author_name": "Jeyan Thiyagalingam", + "author_inst": "SCD, STFC" + }, + { + "author_name": "Maya Topf", + "author_inst": "Birkbeck" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.11.17.385252", @@ -1092587,37 +1091909,49 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.11.14.20231142", - "rel_title": "Capability impacts of the Covid-19 lockdown in association with mental well-being, social connections and existing vulnerabilities: an Austrian survey study", + "rel_doi": "10.1101/2020.11.14.20231886", + "rel_title": "Modeling the Effect of Lockdown Timing as a COVID-19 Control Measure in Countries with Differing Social Contacts", "rel_date": "2020-11-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.14.20231142", - "rel_abs": "BackgroundImpacts of the Covid-19 pandemic and its public health measures go beyond physical and mental health and incorporate wider well-being impacts in terms of what people are free to do or be. We explored these capability impacts of the Covid-19 lockdown in association with peoples mental well-being, social support and existing vulnerabilities in Austria.\n\nMethodsAdult Austrian residents (n=560) provided responses to a cross-sectional online survey about their experiences during Covid-19 lockdown (15 March-15 April 2020). Instruments measuring capabilities (OxCAP-MH), depression and anxiety (HADS), social support (MSPSS) and mental well-being (WHO-5) were used in association with six pre-defined vulnerabilities using multivariable linear regression.\n\nResults31% of the participants reported low mental well-being and only 30% of those with a history of mental health treatment received treatment during lockdown. Past mental health treatment had a significant negative effect across all outcome measures with an associated capability well-being score reduction of -6.54 (95%CI: -9.26,-3.82). Direct Covid-19 experience and being at risk due to age and/or physical health conditions were also associated with significant capability deprivations. When adjusted for vulnerabilities, significant capability reductions were observed in association with increased levels of depression (-1.79) and anxiety (-1.50), and significantly higher capability levels (+3.77) were associated with higher levels of social support. Compared to the cohort average, individual capability impacts varied between -9% for those reporting past mental health treatment and +5% for those reporting one score higher on the social support scale.\n\nConclusionsOur study is the first to assess the capability limiting aspects of a lockdown in association with specific vulnerabilities. The negative impacts of the Covid-19 lockdown were strongest for people with a history of mental health treatment. In future public health policies, special attention should be also paid to improving social support levels to increase public resilience.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.14.20231886", + "rel_abs": "The application, timing, and duration of lockdown strategies during a pandemic remain poorly quantified with regards to expected public health outcomes. Previous projection models have reached conflicting conclusions about the effect of complete lockdowns on COVID-19 outcomes. We developed a stochastic continuous-time Markov chain (CTMC) model with eight states including the environment (SEAMHQRD-V), and derived a formula for the basic reproduction number, R0, for that model. Applying the R0 formula as a function in previously-published social contact matrices from 152 countries, we produced the distribution and four categories of possible R0 for the 152 countries and chose one country from each quarter as a representative for four social contact categories (Canada, China, Mexico, and Niger). The model was then used to predict the effects of lockdown timing in those four categories through the representative countries. The analysis for the effect of a lockdown was performed without the influence of the other control measures, like social distancing and mask wearing, to quantify its absolute effect. Hypothetical lockdown timing was shown to be the critical parameter in ameliorating pandemic peak incidence. More importantly, we found that well-timed lockdowns can split the peak of hospitalizations into two smaller distant peaks while extending the overall pandemic duration. The timing of lockdowns reveals that a \"tunneling\" effect on incidence can be achieved to bypass the peak and prevent pandemic caseloads from exceeding hospital capacity.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Judit Simon", - "author_inst": "Department of Health Economics, Center for Public Health, Medical University of Vienna, Kinderspitalgasse 15, 1090 Vienna, Austria" + "author_name": "Tamer Oraby", + "author_inst": "The University of Texas Rio Grande Valley" }, { - "author_name": "Timea M Helter", - "author_inst": "Department of Health Economics, Center for Public Health, Medical University of Vienna, Kinderspitalgasse 15, 1090 Vienna, Austria" + "author_name": "Michael G Tyshenko", + "author_inst": "McLaughlin Centre for Population Health Risk Assessment" }, { - "author_name": "Ross G White", - "author_inst": "Primary Care and Mental Health, Institute of Population Health, University of Liverpool, School of Psychology, Brownlow Hill, Liverpool, L69 3GB, UK" + "author_name": "Jose Campo Maldonado", + "author_inst": "The University of Texas Rio Grande Valley" }, { - "author_name": "Catharina van der Boor", - "author_inst": "Primary Care and Mental Health, Institute of Population Health, University of Liverpool, School of Psychology, Brownlow Hill, Liverpool, L69 3GB, UK" + "author_name": "Kristina Vatcheva", + "author_inst": "The University of Texas Rio Grande Valley" }, { - "author_name": "Agata Laszewska", - "author_inst": "Department of Health Economics, Center for Public Health, Medical University of Vienna, Kinderspitalgasse 15, 1090 Vienna, Austria" + "author_name": "Susie Elsaadany", + "author_inst": "University of Ottawa" + }, + { + "author_name": "Walid Q Alali", + "author_inst": "Kuwait University" + }, + { + "author_name": "Joseph C Longenecker", + "author_inst": "Kuwait University" + }, + { + "author_name": "Mustafa Al-Zoughool", + "author_inst": "Kuwait University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1094245,34 +1093579,26 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.11.16.385468", - "rel_title": "Examining the Persistence of Human Coronaviruses on Fresh Produce", + "rel_doi": "10.1101/2020.11.14.382697", + "rel_title": "Gene Expression Meta-Analysis Identifies Molecular Changes Associated with SARS-CoV Infection in Lungs", "rel_date": "2020-11-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.16.385468", - "rel_abs": "Human coronaviruses (HCoVs) are mainly associated with respiratory infections. However, there is evidence that highly pathogenic HCoVs, including severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and Middle East Respiratory Syndrome (MERS-CoV), infect the gastrointestinal (GI) tract and are shed in the fecal matter of the infected individuals. These observations have raised questions regarding the possibility of fecal-oral route as well as foodborne transmission of SARS-CoV-2 and MERS-CoV. Studies regarding the survival of HCoVs on inanimate surfaces demonstrate that these viruses can remain infectious for hours to days, however, to date, there is no data regarding the viral survival on fresh produce, which is usually consumed raw or with minimal heat processing. To address this knowledge gap, we examined the persistence of HCoV-229E, as a surrogate for highly pathogenic HCoVs, on the surface of commonly consumed fresh produce, including: apples, tomatoes and cucumbers. Herein, we demonstrated that viral infectivity declines within a few hours post-inoculation (p.i) on apples and tomatoes, and no infectious virus was detected at 24h p.i, while the virus persists in infectious form for 72h p.i on cucumbers. The stability of viral RNA was examined by droplet-digital RT-PCR (ddRT-PCR), and it was observed that there is no considerable reduction in viral RNA within 72h p.i.", - "rel_num_authors": 4, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.14.382697", + "rel_abs": "BackgroundSevere Acute Respiratory Syndrome (SARS) corona virus (CoV) infections are a serious public health threat because of their pandemic-causing potential. This work analyzes mRNA expression data from SARS infections through meta-analysis of gene signatures, possibly identifying therapeutic targets associated with major SARS infections.\n\nMethodsThis work defines 37 gene signatures representing SARS-CoV, Middle East Respiratory Syndrome (MERS)-CoV, and SARS-CoV2 infections in human lung cultures and/or mouse lung cultures or samples and compares them through Gene Set Enrichment Analysis (GSEA). To do this, positive and negative infectious clone SARS (icSARS) gene panels are defined from GSEA-identified leading-edge genes between two icSARS-CoV derived signatures, both from human cultures. GSEA then is used to assess enrichment and identify leading-edge icSARS panel genes between icSARS gene panels and 27 other SARS-CoV gene signatures. The meta-analysis is expanded to include five MERS-CoV and three SARS-CoV2 gene signatures. Genes associated with SARS infection are predicted by examining the intersecting membership of GSEA-identified leading-edges across gene signatures.\n\nResultsSignificant enrichment (GSEA p<0.001) is observed between two icSARS-CoV derived signatures, and those leading-edge genes defined the positive (233 genes) and negative (114 genes) icSARS panels. Non-random significant enrichment (null distribution p<0.001) is observed between icSARS panels and all verification icSARSvsmock signatures derived from human cultures, from which 51 over- and 22 under-expressed genes are shared across leading-edges with 10 over-expressed genes already associated with icSARS infection. For the icSARSvsmock mouse signature, significant, non-random significant enrichment held for only the positive icSARS panel, from which nine genes are shared with icSARS infection in human cultures. Considering other SARS strains, significant, non-random enrichment (p<0.05) is observed across signatures derived from other SARS strains for the positive icSARS panel. Five positive icSARS panel genes, CXCL10, OAS3, OASL, IFIT3, and XAF1, are found across mice and human signatures regardless of SARS strains.\n\nConclusionThe GSEA-based meta-analysis approach used here identifies genes with and without reported associations with SARS-CoV infections, highlighting this approachs predictability and usefulness in identifying genes that have potential as therapeutic targets to preclude or overcome SARS infections.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Madeleine Blondin-Brosseau", - "author_inst": "Health Canada" + "author_name": "Amber Park", + "author_inst": "Davenport University" }, { - "author_name": "Jennifer Harlow", - "author_inst": "Health Canada" - }, - { - "author_name": "Tanushka Doctor", - "author_inst": "Health Canada" - }, - { - "author_name": "Neda Nasheri", - "author_inst": "Health Canada" + "author_name": "Laura Harris", + "author_inst": "Michigan State University" } ], "version": "1", - "license": "cc_no", - "type": "new results", + "license": "cc_by_nd", + "type": "confirmatory results", "category": "microbiology" }, { @@ -1096279,95 +1095605,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.12.20145318", - "rel_title": "Critical care workers have lower seroprevalence of SARS-CoV-2 IgG compared with non-patient facing staff in first wave of COVID19.", + "rel_doi": "10.1101/2020.11.13.381194", + "rel_title": "In Vitro Activity of Itraconazole Against SARS-CoV-2", "rel_date": "2020-11-13", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.12.20145318", - "rel_abs": "With the first 2020 surge of the COVID-19 pandemic, many health care workers (HCW) were re-deployed to critical care environments to support intensive care teams to look after high numbers of patients with severe COVID-19. There was considerable anxiety of increased risk of COVID19 for staff working in these environments.\n\nUsing a multiplex platform to assess serum IgG responses to SARS-CoV-2 N, S and RBD proteins, and detailed symptom reporting, we screened over 500 HCW (25% of the total workforce) in a quaternary level hospital to explore the relationship between workplace and evidence of exposure to SARS-CoV-2.\n\nWhilst 45% of the cohort reported symptoms that they consider may have represented COVID-19, overall seroprevalence was 14% with anosmia and fever being the most discriminating symptoms for seropositive status. There was a significant difference in seropositive status between staff working in clinical and non-clinical roles (9% patient facing critical care, 15% patient facing non-critical care, 22% nonpatient facing). In the seropositive cohort, symptom severity increased with age for men and not for women. In contrast, there was no relationship between symptom severity and age or sex in the seronegative cohort reporting possible COVID-19 symptoms. Of the 12 staff screened PCR positive (10 symptomatic), 3 showed no evidence of seroconversion in convalescence.\n\nConclusionThe current approach to Personal Protective Equipment (PPE) appears highly effective in protecting staff from patient acquired infection in the critical care environment including protecting staff managing interhospital transfers of COVID-19 patients. The relationship between seroconversion and disease severity in different demographics warrants further investigation. Longitudinally paired virological and serological surveillance, with symptom reporting are urgently required to better understand the role of antibody in the outcome of HCW exposure during subsequent waves of COVID-19 in health care environments.", - "rel_num_authors": 19, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.13.381194", + "rel_abs": "BackgroundAs long as there is no vaccine available, having access to inhibitors of SARS-CoV-2 will be of utmost importance. Antivirals against coronaviruses do not exist, hence global drug re-purposing efforts have been carried out to identify agents that may provide clinical benefit to patients with COVID-19. Itraconazole, an antifungal agent, has been reported to have potential activity against animal coronaviruses.\n\nMethodsUsing cell-based phenotypic assays, the in vitro antiviral activity of itraconazole and 17-OH itraconazole was assessed against clinical isolates from a German and Belgian patient infected with SARS-CoV-2.\n\nResultsItraconazole demonstrated antiviral activity in human Caco-2 cells (EC50 = 2.3 M; MTT assay). Similarly, its primary metabolite, 17-OH itraconazole, showed inhibition of SARS-CoV-2 activity (EC50 = 3.6 M). Remdesivir inhibited viral replication with an EC50 = 0.4 M. Itraconazole and 17-OH itraconazole resulted in a viral yield reduction in vitro of approximately 2-log10 and approximately 1-log10, as measured in both Caco-2 cells and VeroE6-eGFP cells, respectively. The viral yield reduction brought about by remdesivir or GS-441524 (parent nucleoside of the antiviral prodrug remdesivir; positive control) was more pronounced, with an approximately 3 log10 drop and >4 log10 drop in Caco-2 cells and VeroE6-eGFP cells, respectively.\n\nDiscussionItraconazole and 17-OH itraconazole exert in vitro low micromolar activity against SARS-CoV-2. Despite the in vitro antiviral activity, itraconazole did not result in a beneficial effect in hospitalized COVID-19 patients in a clinical study (EudraCT Number: 2020-001243-15).\n\nHighlightsO_LIItraconazole exerted in vitro low micromolar activity against SARS-CoV-2 (EC50 = 2.3 M)\nC_LIO_LIRemdesivir demonstrated potent antiviral activity, confirming validity of the assay\nC_LIO_LIItraconazole has since shown no efficacy in a clinical study in hospitalized COVID-19 patients\nC_LI", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Dr HE Baxendale", - "author_inst": "Royal Papworth Hospital NHS Foundation Trust" - }, - { - "author_name": "Rainer Doffinger", - "author_inst": "Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK" - }, - { - "author_name": "Jonathan Luke Heeney", - "author_inst": "Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom." - }, - { - "author_name": "David Wells", - "author_inst": "Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom." - }, - { - "author_name": "Jessica Gronlund", - "author_inst": "Royal Papworth NHS Trust, Cambridge, CB2 0AY, United Kingdom" - }, - { - "author_name": "George Carnell", - "author_inst": "Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom" - }, - { - "author_name": "Minna Paloniemi", - "author_inst": "Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom" - }, - { - "author_name": "Paul Tonks", - "author_inst": "Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom" - }, - { - "author_name": "Lourdes CeronGutierrez", - "author_inst": "Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK" + "author_name": "Ellen Van Damme", + "author_inst": "Janssen Pharmaceutica NV, Beerse, Belgium" }, { - "author_name": "Ashleigh Sayer", - "author_inst": "Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK" + "author_name": "Sandra De Meyer", + "author_inst": "Janssen Pharmaceutica NV, Beerse, Belgium" }, { - "author_name": "James Nathan", - "author_inst": "Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, United Kingdom" + "author_name": "Denisa Bojkova", + "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany" }, { - "author_name": "Leo James", - "author_inst": "Protein and Nucleic Acid Chemistry Division, Medical Research Council Laboratory of Molecular Biology, Cambridge CB2 0QH, United Kingdom" + "author_name": "Sandra Ciesek", + "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany" }, { - "author_name": "Jakob luptak", - "author_inst": "Protein and Nucleic Acid Chemistry Division, Medical Research Council Laboratory of Molecular Biology, Cambridge CB2 0QH, United Kingdom" + "author_name": "Jindrich Cinatl", + "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany" }, { - "author_name": "Guinevere L Grice", - "author_inst": "Cambridge Institute of Therapeutic Immunology & Infectious Disease (CITIID), University of Cambridge, Cambridge, United Kingdom" + "author_name": "Steven De Jonghe", + "author_inst": "KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Leuven, Belgium" }, { - "author_name": "Soraya Ebrahimi", - "author_inst": "Department of Clinical Biochemistry and Immunology, Addenbrooke's Hospital, Cambridge, UK" + "author_name": "Dirk Jochmans", + "author_inst": "KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Leuven, Belgium" }, { - "author_name": "Xiaoli Xiong", - "author_inst": "Structural Studies Division, Medical Research Council Laboratory of Molecular Biology, Cambridge, CB2 0QH, United Kingdom" + "author_name": "Peter Leyssen", + "author_inst": "KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Leuven, Belgium" }, { - "author_name": "John AG Briggs", - "author_inst": "Structural Studies Division, Medical Research Council Laboratory of Molecular Biology, Cambridge, CB2 0QH, United Kingdom" + "author_name": "Christophe Buyck", + "author_inst": "Janssen Pharmaceutica NV, Beerse, Belgium" }, { - "author_name": "Sumita Pai", - "author_inst": "ROYAL PAPWORTH HOSPITAL NHS FOUNDATION TRUST" + "author_name": "Johan Neyts", + "author_inst": "KU Leuven, Department of Microbiology, Immunology and Transplantation, Rega Institute, Laboratory of Virology and Chemotherapy, Leuven, Belgium" }, { - "author_name": "angalee nadesalingham", - "author_inst": "Laboratory of Viral Zoonotics, Department of Veterinary Medicine, University of Cambridge, Cambridge CB3 0ES, United Kingdom" + "author_name": "Marnix Van Loock", + "author_inst": "Janssen Pharmaceutica NV, Beerse, Belgium" } ], "version": "1", - "license": "cc_by_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2020.11.13.381079", @@ -1097749,91 +1097043,219 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2020.11.10.20229401", - "rel_title": "Using Real World Data to Understand HIV and COVID-19 in the U.S.A. and Spain: Characterizing Co-Infected Patients Across the Care Cascade", + "rel_doi": "10.1101/2020.11.11.20228692", + "rel_title": "Impact of the COVID-19 nonpharmaceutical interventions on influenza and other respiratory viral infections in New Zealand", "rel_date": "2020-11-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.10.20229401", - "rel_abs": "ObjectiveMost patients severely affected by COVID-19 have been elderly and patients with underlying chronic disease such as diabetes, cardiovascular disease, or respiratory disease. People living with HIV (PLHIV) may have greater risk of contracting or developing severe COVID-19 due to the underlying HIV infection or higher prevalence of comorbidities.\n\nDesignThis is a cohort study, including PLHIV diagnosed, hospitalized, or requiring intensive services for COVID-19.\n\nMethodsData sources include routine electronic medical record or claims data from the U.S. and Spain. Patient demographics, comorbidities, and medication history are described.\n\nResultFour data sources had a population of HIV/COVID-19 coinfected patients ranging from 288 to 4606 lives. PLHIV diagnosed with COVID-19 were younger than HIV-negative patients diagnosed with COVID-19. PLHIV diagnosed with COVID-19 diagnosis had similar comorbidities as HIV-negative COVID-19 patients with higher prevalence of those comorbidities and history of severe disease. Treatment regimens were similar between PLHIV diagnosed with COVID-19 or PLHIV requiring intensive services.\n\nConclusionsOur study uses routine practice data to explore HIV impact on COVID-19, providing insight into patient history prior to COVID-19. We found that HIV and COVID-19 coinfected patients have higher prevalence of underlying comorbidities such as cardiovascular and respiratory disease as compared to HIV-negative COVID-19 infected patients. We also found that, across the care cascade, co-infected patients who received intensive services were more likely to have more serious underlying disease or a history of more serious events as compared to PLHIV who were diagnosed with COVID-19.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.11.20228692", + "rel_abs": "Stringent nonpharmaceutical interventions (NPIs) such as lockdowns and border closures are not currently recommended for pandemic influenza control. New Zealand used these NPIs to eliminate coronavirus disease 2019 during its first wave. Using multiple surveillance systems, we observed a parallel and unprecedented reduction of influenza and other respiratory viral infections in 2020. This finding supports the use of these NPIs for controlling pandemic influenza and other severe respiratory viral threats.", + "rel_num_authors": 50, "rel_authors": [ { - "author_name": "Julianna Kohler", - "author_inst": "United States Agency for International Development" + "author_name": "Sue Huang", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" }, { - "author_name": "Kristin M Kostka", - "author_inst": "IQVIA" + "author_name": "Tim Wood", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" }, { - "author_name": "Rupa Makadia", - "author_inst": "Janssen Research and Development, Titusville, NJ, US" + "author_name": "Lauren Jelley", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" }, { - "author_name": "Roger Paredes", - "author_inst": "IrsiCaixa AIDS Research Institute" + "author_name": "Tineke Jennings", + "author_inst": "Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand" }, { - "author_name": "Talita Duarte-Salles", - "author_inst": "Fundacio Institut Universitari per a la recerca a l'Atencio Primaria de Salut Jordi Gol i Gurina (IDIAPJGol), Barcelona, Spain" + "author_name": "Sarah Jeffries", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" }, { - "author_name": "Scott L Duvall", - "author_inst": "VINCI Resource Center, VA Salt Lake City Health Care System, Salt Lake City, UT; Division of Epidemiology, University of Utah, Salt Lake City, UT" + "author_name": "Karen Daniels", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" }, { - "author_name": "Michael Matheny", - "author_inst": "VINCI Resource Center, Tennessee Valley Healthcare System VA, Nashville, TN; Departments of Biomedical Informatics, Biostatistics, and Medicine, Vanderbilt Univ" + "author_name": "Annette Nesdale", + "author_inst": "Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand" }, { - "author_name": "Kristine E Lynch", - "author_inst": "VINCI Resource Center, VA Salt Lake City Health Care System, Salt Lake City, UT; Division of Epidemiology, University of Utah, Salt Lake City, UT" + "author_name": "Tony Dowell", + "author_inst": "University of Otago, School of Medicine in Wellington, Wellington, New Zealand" }, { - "author_name": "Alison Cheng", - "author_inst": "United States Agency for International Development" + "author_name": "Nikki Turner", + "author_inst": "University of Auckland, Auckland, New Zealand" }, { - "author_name": "Asieh Golozar", - "author_inst": "Johns Hopkins Bloomberg School of Public Health, Baltimore, MD US; Regeneron Pharmaceuticals, NY USA" + "author_name": "Priscilla Campbell-Stokes", + "author_inst": "Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand" }, { - "author_name": "Jennifer C E Lane", - "author_inst": "Centre for Statistics in Medicine, NDORMS, University of Oxford" + "author_name": "Michelle Balm", + "author_inst": "Capital Coast District Health Board, Wellington, New Zealand" }, { - "author_name": "Anthony G Sena", - "author_inst": "Janssen Research and Development, Titusville, NJ, US; Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands" + "author_name": "Hazel C Dobinson", + "author_inst": "Capital Coast District Health Board, Wellington, New Zealand" }, { - "author_name": "Peter J Rijnbeek", - "author_inst": "Department of Medical Informatics, Erasmus University Medical Center, Rotterdam, The Netherlands" + "author_name": "Cameron C Grant", + "author_inst": "University of Auckland, Auckland, New Zealand" }, { - "author_name": "Daniel R Morales", - "author_inst": "University of Dundee" + "author_name": "Shelley James", + "author_inst": "Capital Coast District Health Board, Wellington, New Zealand" }, { - "author_name": "Patrick B Ryan", - "author_inst": "Janssen Research and Development, Titusville, NJ, US; Department of Biomedical Informatics, Columbia University, New York, New York, US" + "author_name": "Nayyereh Aminisani", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" }, { - "author_name": "Christian G Reich", - "author_inst": "Real World Solutions, IQVIA, Cambridge, MA, US" + "author_name": "Jacqui Ralston", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" }, { - "author_name": "George Siberry", - "author_inst": "United States Agency for International Development" + "author_name": "Wendy Gunn", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" }, { - "author_name": "Daniel Prieto-Alhambra", - "author_inst": "University of Oxford" + "author_name": "Judy Bucacao", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Jessica Danielewicz", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Tessa Moncrieff", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Andrea McNeill", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Lisa Lopez", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Ben Waite", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Tomasz Kiedrzynski", + "author_inst": "Ministry of Health, Wellington, New Zealand" + }, + { + "author_name": "Hannah Schrader", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Rebekah Gray", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Kayla Cook", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Danielle Currin", + "author_inst": "Institute of Environmental Science and Research, Wellington, New Zealand" + }, + { + "author_name": "Chaune Engelbrecht", + "author_inst": "Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand" + }, + { + "author_name": "Whitney Tapurau", + "author_inst": "Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand" + }, + { + "author_name": "Leigh Emmerton", + "author_inst": "Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand" + }, + { + "author_name": "Maxine Martin", + "author_inst": "Regional Public Health, Hutt Valley District Health Board, Wellington, New Zealand" + }, + { + "author_name": "Michael G Baker", + "author_inst": "University of Otago, School of Medicine in Wellington, Wellington, New Zealand" + }, + { + "author_name": "Susan Taylor", + "author_inst": "Counties Manukau District Health Board, Auckland, New Zealand" + }, + { + "author_name": "Adrian Trenholme", + "author_inst": "Counties Manukau District Health Board, Auckland, New Zealand" + }, + { + "author_name": "Conroy Wong", + "author_inst": "Counties Manukau District Health Board, Auckland, New Zealand" + }, + { + "author_name": "Shirley Lawrence", + "author_inst": "Counties Manukau District Health Board, Auckland, New Zealand" + }, + { + "author_name": "Colin McArthur", + "author_inst": "Auckland District Health Board, Auckland, New Zealand" + }, + { + "author_name": "Alicia Stanley", + "author_inst": "Auckland District Health Board, Auckland, New Zealand" + }, + { + "author_name": "Sally Roberts", + "author_inst": "Auckland District Health Board, Auckland, New Zealand" + }, + { + "author_name": "Fahimeh Ranama", + "author_inst": "Auckland District Health Board, Auckland, New Zealand" + }, + { + "author_name": "Jenny Bennett", + "author_inst": "Waikato District Health Board, Hamilton, New Zealand" + }, + { + "author_name": "Chris Mansell", + "author_inst": "Waikato District Health Board, Hamilton, New Zealand" + }, + { + "author_name": "Meik Dilcher", + "author_inst": "Canterbury District Health Board, Christchurch, New Zealand" + }, + { + "author_name": "Anja Werno", + "author_inst": "Canterbury District Health Board, Christchurch, New Zealand" + }, + { + "author_name": "Jennifer Grant", + "author_inst": "Southern District Health Board, Dunedin, New Zealand" + }, + { + "author_name": "Antje van der Linden", + "author_inst": "Southern District Health Board, Dunedin, New Zealand" + }, + { + "author_name": "Ben Youngblood", + "author_inst": "WHO Collaborating Centre, St Jude Childrens Research Hospital, Memphis, Tennessee, USA" + }, + { + "author_name": "Paul G Thomas", + "author_inst": "WHO Collaborating Centre, St Jude Childrens Research Hospital, Memphis, USA" + }, + { + "author_name": "Richard J Webby", + "author_inst": "St Jude Children's Research Hospital" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "hiv aids" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.11.10.20226886", @@ -1099551,49 +1098973,25 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.11.09.20228007", - "rel_title": "Analysis of mitigation of Covid-19 outbreaks in workplaces and schools by hybrid telecommuting", + "rel_doi": "10.1101/2020.11.08.20227322", + "rel_title": "COVID-19 pandemic risk analytics: Data mining with reliability engineering methods for analyzing spreading behavior and comparison with infectious diseases", "rel_date": "2020-11-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.09.20228007", - "rel_abs": "The COVID-19 outbreak has forced most countries to impose new contact-limiting restrictions at workplaces, universities, schools, and more broadly in our societies. Yet, the power and limitations of these unprecedented strategies for containing virus spread within the populations remain unquantified. Here, we develop a simulation study to analyze COVID-19 outbreak magnitudes on three real-life contact networks stemming from a workplace, a primary school and a high school in France.\n\nOur study provides the first fine-grained analysis of the impact of contact-limiting strategies at work-places, schools and high schools, including (1) Rotating, in which workers are evenly split into two shifts that alternate on a daily or weekly basis; and (2) On-Off, where the whole group alternates periods of normal work interactions with complete telecommuting. We model epidemics spread in these different setups using an SEIR transmission model enriched with the coronavirus most salient specificities: super-spreaders, infectious asymptomatic individuals, and pre-symptomatic infectious periods. Our study yields clear results: The ranking of the strategies based on their ability to mitigate epidemic propagation in the network from a first index case is the same for all network topologies (work place, primary school and high school). Namely, from best to worst: Rotating week-by-week, Rotating day-by-day, On-Off week-by-week, and On-Off day-by-day. Moreover, our results show that when the baseline reproduction number R0 within the network is < 1.38, all four strategies efficiently control outbreak by decreasing effective Re to {inverted exclamation}1. These results can support public health decisions and telecommuting organization locally.\n\nO_TEXTBOXSignificance statement\n\nWe take advantage of available individual-level contact data for school and workplace social networks, to simulate COVID-19 epidemics on real-life networks. This framework enable us to compare and rank natural prevention strategies that require hybrid telecommuting, either for everyone synchronously (On-Off) or periodically switching between two groups of people (Rotating): weekly or daily Rotating, weekly or daily On-Off, and full telecommuting. All strategies have a significant impact when the reproduction number within the network is moderately high (< 1.3). These results can inform public health decisions and telecommuting organization at the local scale.\n\nC_TEXTBOX", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.08.20227322", + "rel_abs": "In December 2019, the world was confronted with the outbreak of the respiratory disease COVID-19 (Corona). The first infection (confirmed case) was detected in the City Wuhan, Hubei, China. First, it was an epidemic in China, but in the first quarter of 2020, it evolved into a pandemic, which continues to this day. The COVID-19 pandemic with its incredible speed of spread shows the vulnerability of a globalized and networked world. The first months of the pandemic were characterized by heavy burden on health systems. Worldwide, the population of countries was affected with severe restrictions, like educational system shutdown, public traffic system breakdown or a comprehensive lockdown. The severity of the burden was dependent on many factors, e.g. government, culture or health system. However, the burden happened regarding each country with slight time lags, cf. Bracke et al. (2020). This paper focuses on data analytics regarding infection data of the COVID-19 pandemic. It is a continuation of the research study COVID-19 pandemic data analytics: Data heterogeneity, spreading behavior, and lockdown impact, published by Bracke et al. (2020). The goal of this assessment is the evaluation/analysis of infection data mining considering model uncertainty, pandemic spreading behavior with lockdown impact and early second wave in Germany, Italy, Japan, New Zealand and France. Furthermore, a comparison with other infectious diseases (measles and influenza) is made. The used data base from Johns Hopkins University (JHU) runs from 01/22/2020 until 09/22/2020 with daily data, the dynamic development after 09/22/2020 is not considered. The measles/influenza analytics are based on Robert Koch Institute (RKI) data base 09/22/2020. Statistical models and methods from reliability engineering like Weibull distribution model or trend test are used to analyze the occurrence of infection.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Simon Mauras", - "author_inst": "IRIF" - }, - { - "author_name": "Vincent Cohen-Addad", - "author_inst": "Google Research" - }, - { - "author_name": "Guillaume Duboc", - "author_inst": "IRIF" - }, - { - "author_name": "Max Dupre la Tour", - "author_inst": "IRIF" - }, - { - "author_name": "Paolo Frasca", - "author_inst": "Univ. Grenoble Alpes, CNRS, Inria, Grenoble INP, Gipsa-lab" - }, - { - "author_name": "Claire Mathieu", - "author_inst": "CNRS, IRIF" - }, - { - "author_name": "Lulla Opatowski", - "author_inst": "Univ Versailles Saint Quentin / Institut pasteur / Inserm" + "author_name": "Alicia Puls", + "author_inst": "University of Wuppertal, Germany" }, { - "author_name": "Laurent Viennot", - "author_inst": "INRIA, IRIF" + "author_name": "Stefan Bracke", + "author_inst": "University of Wuppertal" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1101601,85 +1100999,165 @@ "category": "pharmacology and toxicology" }, { - "rel_doi": "10.1101/2020.11.11.375972", - "rel_title": "ACE2-Targeting Monoclonal Antibody As A \"Pan\" Coronavirus Blocker In Vitro and In A Mouse Model", + "rel_doi": "10.1101/2020.11.12.379115", + "rel_title": "Neuraminidase inhibitors rewire neutrophil function in murine sepsis and COVID-19 patient cells", "rel_date": "2020-11-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.11.375972", - "rel_abs": "The evolution of coronaviruses, such as SARS-CoV-2, makes broad-spectrum coronavirus preventional or therapeutical strategies highly sought after. Here we report a human angiotensin-converting enzyme 2 (ACE2)-targeting monoclonal antibody, 3E8, blocked the S1-subunits and pseudo-typed virus constructs from multiple coronaviruses including SARS-CoV-2, SARS-CoV-2 mutant variants (SARS-CoV-2-D614G, B.1.1.7, B.1.351, B.1.617.1 and P.1), SARS-CoV and HCoV-NL63, without markedly affecting the physiological activities of ACE2 or causing severe toxicity in ACE2 \"knock-in\" mice. 3E8 also blocked live SARS-CoV-2 infection in vitro and in a prophylactic mouse model of COVID-19. Cryo-EM and \"alanine walk\" studies revealed the key binding residues on ACE2 interacting with the CDR3 domain of 3E8 heavy chain. Although full evaluation of safety in non-human primates is necessary before clinical development of 3E8, we provided a potentially potent and \"broad-spectrum\" management strategy against all coronaviruses that utilize ACE2 as entry receptors and disclosed an anti-coronavirus epitope on human ACE2.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.12.379115", + "rel_abs": "Neutrophil overstimulation plays a crucial role in tissue damage during severe infections. Neuraminidase (NEU)-mediated cleavage of surface sialic acid has been demonstrated to regulate leukocyte responses. Here, we report that antiviral NEU inhibitors constrain host NEU activity, surface sialic acid release, ROS production, and NETs released by microbial-activated human neutrophils. In vivo, treatment with Oseltamivir results in infection control and host survival in peritonitis and pneumonia models of sepsis. Single-cell RNA sequencing re-analysis of publicly data sets of respiratory tract samples from critical COVID-19 patients revealed an overexpression of NEU1 in infiltrated neutrophils. Moreover, Oseltamivir or Zanamivir treatment of whole blood cells from severe COVID-19 patients reduces host NEU-mediated shedding of cell surface sialic acid and neutrophil overactivation. These findings suggest that neuraminidase inhibitors can serve as host-directed interventions to dampen neutrophil dysfunction in severe infections.\n\nAt a GlanceIn a severe systemic inflammatory response, such as sepsis and COVID-19, neutrophils play a central role in organ damage. Thus, finding new ways to inhibit the exacerbated response of these cells is greatly needed. Here, we demonstrate that in vitro treatment of whole blood with the viral neuraminidase inhibitors Oseltamivir or Zanamivir, inhibits the activity of human neuraminidases as well as the exacerbated response of neutrophils. In experimental models of severe sepsis, oseltamivir decreased neutrophil activation and increased the survival rate of mice. Moreover, Oseltamivir or Zanamivir ex vivo treatment of whole blood cells from severe COVID-19 patients rewire neutrophil function.", + "rel_num_authors": 37, "rel_authors": [ { - "author_name": "Yuning Chen", - "author_inst": "Biotherapeutics Discovery Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 200126, China." + "author_name": "Rodrigo O. Formiga", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Yanan Zhang", - "author_inst": "Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, Hubei 430" + "author_name": "Fl\u00e1via C. Amaral", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Renhong Yan", - "author_inst": "Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School " + "author_name": "Camila Fernandes Souza", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Guifeng Wang", - "author_inst": "Biotherapeutics Discovery Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 200126, China." + "author_name": "Daniel A. G. B. Mendes", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Yuanyuan Zhang", - "author_inst": "Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School " + "author_name": "Carlos W. S. Wanderley", + "author_inst": "School of Medicine of Ribeirao Preto, University of Sao Paulo" }, { - "author_name": "Zherui Zhang", - "author_inst": "Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, Hubei 430" + "author_name": "Cristina B. Lorenzini", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Yaning Li", - "author_inst": "Beijing Advanced Innovation Center for Structural Biology, Tsinghua-Peking Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing" + "author_name": "Adara A. Santos", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "jianxia ou", - "author_inst": "School of Chinese Materia Medica, Nanjing University of Chinese Medicine" + "author_name": "Juliana Ant\u00f4nia", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Wendi Chu", - "author_inst": "Biotherapeutics Discovery Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 200126, China." + "author_name": "Lucas F. Faria", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Zhijuan Liang", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Caio C. Natale", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "yongmei wang", - "author_inst": "Shanghai Institute of Materia Medica" + "author_name": "Nicholas M. Paula", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Yili Chen", - "author_inst": "Dartsbio Pharmaceuticals, Zhongshan, Guangdong 528400, China" + "author_name": "Priscila C. S. Silva", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Ganjun Chen", - "author_inst": "Dartsbio Pharmaceuticals, Zhongshan, Guangdong 528400, China" + "author_name": "Fernanda R. Fonseca", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Qi Wang", - "author_inst": "Biotherapeutics Discovery Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 200126, China." + "author_name": "Luan Aires", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Qiang Zhou", - "author_inst": "Center for Infectious Disease Research, Westlake Laboratory of Life Sciences and Biomedicine, Key Laboratory of Structural Biology of Zhejiang Province, School " + "author_name": "Nicoli Heck", + "author_inst": "Federal University of Santa Catarina" }, { - "author_name": "Bo Zhang", - "author_inst": "Key Laboratory of Special Pathogens and Biosafety, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences, Wuhan, Hubei 430" + "author_name": "M\u00e1rick R. Starick", + "author_inst": "Federal University of Santa Catarina" + }, + { + "author_name": "Shana P. C. Barroso", + "author_inst": "Institute of Biomedical Research, Marcilio Dias Naval Hospital" + }, + { + "author_name": "Alexandre Morrot", + "author_inst": "Federal University of Rio de Janeiro and Oswaldo Cruz Foundation" + }, + { + "author_name": "Johan Van Weyenbergh", + "author_inst": "KU Leuven" }, { - "author_name": "Chunhe Wang", - "author_inst": "Biotherapeutics Discovery Research Center, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 200126, China." + "author_name": "Regina Sordi", + "author_inst": "Federal University of Santa Catarina" + }, + { + "author_name": "Frederico Alisson-Silva", + "author_inst": "Federal University of Rio de Janeiro" + }, + { + "author_name": "Daniel S. Mansur", + "author_inst": "Universidade Federal de Santa Catarina" + }, + { + "author_name": "Fernando Q. Cunha", + "author_inst": "Universidade de Sao Paulo Campus de Ribeirao Preto" + }, + { + "author_name": "Edroaldo Lummertz da Rocha", + "author_inst": "Federal University of Santa Catarina" + }, + { + "author_name": "Pierre-Regis Burgel", + "author_inst": "Universite de Paris, Institut Cochin, INSERM U1016, CNRS; Department of Pneumology, AP-HP, Hopital Cochin, F-75014 PARIS-France." + }, + { + "author_name": "Clemence Martin", + "author_inst": "Universite de Paris, Institut Cochin, INSERM U1016, CNRS; Department of Pneumology, AP-HP, Hopital Cochin, F-75014 PARIS-France" + }, + { + "author_name": "Maria Margarita Hurtado-Nedelec", + "author_inst": "INSERM U1149, Faculte de Medecine, Site Xavier Bichat, CNRS, Universite de Paris" + }, + { + "author_name": "Sylvie Chollet Martin", + "author_inst": "Universite Paris-Saclay" + }, + { + "author_name": "Felipe R. S. Santos", + "author_inst": "Universidade Federal de Minas Gerais" + }, + { + "author_name": "Filipe R. O. de Souza", + "author_inst": "Universidade Federal de Minas Gerais" + }, + { + "author_name": "Celso Martins Queiroz-Junior", + "author_inst": "Universidade Federal de Minas Gerais" + }, + { + "author_name": "Vivian Vasconcelos Costa", + "author_inst": "Universidade Federal de Minas Gerais" + }, + { + "author_name": "Rosemeri Maurici", + "author_inst": "Federal University of Santa Catarina" + }, + { + "author_name": "Matthew S Macauley", + "author_inst": "University of Alberta" + }, + { + "author_name": "Andre Bafica", + "author_inst": "Universidade Federal de Santa Catarina" + }, + { + "author_name": "Veronique Witko-Sarsat", + "author_inst": "Universite de Paris, Institut Cochin, INSERM U1016, CNRS, Paris, France." + }, + { + "author_name": "Fernando Spiller", + "author_inst": "Federal University of Santa Catarina" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "immunology" }, @@ -1103551,69 +1103029,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.07.20227082", - "rel_title": "A saliva-based RNA extraction-free workflow integrated with Cas13a for SARS-CoV-2 detection", + "rel_doi": "10.1101/2020.11.09.20228171", + "rel_title": "Risk factors for mortality of residents in nursing homes with Covid-19: a retrospective cohort study", "rel_date": "2020-11-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.07.20227082", - "rel_abs": "A major bottleneck in scaling-up COVID-19 testing is the need for sophisticated instruments and well-trained healthcare professionals, which are already overwhelmed due to the pandemic. Moreover, the high-sensitive SARS-CoV-2 diagnostics are contingent on an RNA extraction step, which, in turn, is restricted by constraints in the supply chain. Here, we present CASSPIT (Cas13 Assisted Saliva-based & Smartphone Integrated Testing), which will allow direct use of saliva samples without the need for an extra RNA extraction step for SARS-CoV-2 detection. CASSPIT utilizes CRISPR-Cas13a based SARS-CoV-2 RNA detection, and lateral-flow assay (LFA) readout of the test results. The sample preparation workflow includes an optimized chemical treatment and heat inactivation method, which, when applied to COVID-19 clinical samples, showed a 97% positive agreement with the RNA extraction method. With CASSPIT, LFA based visual limit of detection (LoD) for a given SARS-CoV-2 RNA spiked into the saliva samples was [~]200 copies; image analysis-based quantification further improved the analytical sensitivity to [~]100 copies. Upon validation of clinical sensitivity on RNA extraction-free saliva samples (n=76), a 98% agreement between the lateral-flow readout and RT-qPCR data was found (Ct<35). To enable user-friendly test results with provision for data storage and online consultation, we subsequently integrated lateral-flow strips with a smartphone application. We believe CASSPIT will eliminate our reliance on RT-qPCR by providing comparable sensitivity and will be a step toward establishing nucleic acid-based point-of-care (POC) testing for COVID-19.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.09.20228171", + "rel_abs": "BackgroundNursing homes have shown remarkably high Covid-19 incidence and mortality. We aimed to explore the contribution of structural factors of nursing home facilities and the surrounding district to all-cause and Covid-19-related deaths during a SARS-CoV-2 outbreak.\n\nMethodsIn this retrospective cohort study, we investigated the risk factors of Covid-19 mortality at the facility level in nursing homes in Catalonia (North-East Spain). The investigated factors included characteristics of the residents (age, gender, comorbidities, and complexity and/or advanced disease), structural features of the nursing home (total number of residents, residents who return home during the pandemic, and capacity for pandemic response, based on an ad hoc score of availability of twelve essential items for implementing preventive measures), and sociodemographic profile of the catchment district (household income, population density, and population incidence of Covid-19). Study endpoints included all-cause death and Covid-19-related death (either PCR-confirmed or clinical suspicion).\n\nFindingsThe analysis included 167 nursing homes that provide long-term care to 8,716 residents. Between March 1 and June 1, 2020, 1,629 deaths were reported in these nursing homes; 1,089 (66{square}9%) of them were Covid-19-confirmed. The multivariable regression showed a higher risk of death associated with a higher percentage of complex patients (HR 1{square}09; 95%CI 1{square}05-1{square}12 per 10% increase) or those with advanced diseases (1{square}13; 1{square}07-1{square}19), lower capacity for implementing preventive measures (1{square}08; 1{square}05-1{square}10 per 1-point increase), and districts with a higher incidence of Covid-19 (2{square}98; 2{square}53-3{square}50 per 1000 cases/100,000 population increase). A higher population density of the catchment area was a protective factor (0{square}60; 0{square}50-0{square}72 per log10 people/Km2 increase).\n\nInterpretationPresence of residents with complex/advance disease, low capacity for pandemic response and location in areas with high incidence of Covid-19 are risk factors for Covid-19 mortality in nursing homes and may help policymakers to prioritize preventative interventions for pandemic containment.\n\nFundingCrowdfunding campaign YoMeCorono (https://www.yomecorono.com/), and Generalitat de Catalunya.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for studies exploring the management of Covid-19 in long-term care settings. The search was performed on May 1, 2020, and included the keywords \"Covid-19\", \"nursing home\", \"long term care\", and \"skilled nursing facility\" with no language restriction. In addition to descriptive reports of Covid-19 mortality in the long-term care setting, we found studies providing evidence on the influence of age and comorbidities to mortality at the individual level. Some authors reported comparisons in the incidence and mortality of Covid-19 between facilities and country areas, and suggested the characteristics of each area/facility that may explain differences in mortality. However, we found no published works specifically investigating the contribution of structural features of the facility and sociodemographic characteristics of the area to explaining differences in Covid-19 mortality among long-term care facilities.\n\nAdded value of this studyThis is the first analysis of risk of mortality at a facility level of residents with Covid-19 in nursing homes. We enrolled up to 167 nursing homes providing long-term care to 8,716 residents and we actively identified risk factors for Covid-19 mortality at the facility level. We found that nursing homes with lower capacity for pandemic response, and located in districts with a higher incidence of Covid-19 had significantly higher risks of Covid-19 mortality. The percentage of complex and/or advanced disease patients was also a risk factor.\n\nImplications of all the available evidenceOur findings provide policymakers with critical information to prioritize long-term care facilities at higher risk when deploying preventative interventions to minimize mortality in this setting. The association between mortality within the nursing home and Covid-19 incidence in the catchment area reinforces the importance of preventing the entry of SARS-CoV-2 into facilities. Nursing homes with limited capacity to implement containment measures should be prioritized when deploying preventative interventions for minimizing Covid-19 mortality in long-term care facilities.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Iqbal Azmi", - "author_inst": "Jamia Millia Islamia" + "author_name": "Clara Suner", + "author_inst": "Fight AIDS and Infectious Diseases Foundation, Badalona, Badalona, Spain" }, { - "author_name": "Md Imama Faizan", - "author_inst": "Jamia Millia Islamia" + "author_name": "Dan Ouchi", + "author_inst": "Fight AIDS and Infectious Diseases Foundation, Badalona, Badalona, Spain" }, { - "author_name": "Rohit Kumar", - "author_inst": "Safdarjung Hospital" + "author_name": "Miquel Angel Mas", + "author_inst": "Direccio Clinica Territorial de Cronicitat Metropolitana Nord, Institut Catala de la Salut, Barcelona, Catalonia, Spain / Geriatrics Department, Hospital Unive" }, { - "author_name": "Siddharth Raj Yadav", - "author_inst": "Safdarjung Hospital" + "author_name": "Rosa Lopez Alarcon", + "author_inst": "Direccio Organitzacio i Sistemes Informacio. Gerencia Territorial Metropolitana Nord. Institut Catala de la Salut, Barcelona, Catalonia, Spain" }, { - "author_name": "Nisha Chaudhary", - "author_inst": "Jamia Millia Islamia" + "author_name": "Mireia Massot Mesquida", + "author_inst": "Direccio Clinica Territorial de Cronicitat Metropolitana Nord, Institut Catala de la Salut, Barcelona, Catalonia, Spain" }, { - "author_name": "Deepak Kumar Singh", - "author_inst": "Jamia Millia Islamia" + "author_name": "Eugenia Negredo", + "author_inst": "Fight AIDS and Infectious Diseases Foundation, Badalona, Badalona, Spain; Infectious Diseases Department, Hospital University of Vicari Germans Trias i Pujol, B" }, { - "author_name": "Ruchika Butola", - "author_inst": "360 Diagnostic and Health Services" + "author_name": "Nuria Prat", + "author_inst": "Direccio Atencio Primaria Metropolitana Nord, Institut Catala de la Salut, Barcelona, Catalonia, Spain" }, { - "author_name": "Aryan Ganotra", - "author_inst": "Delhi Technological University" + "author_name": "Josep Maria Bonet Simo", + "author_inst": "Direccio Atencio Primaria Metropolitana Nord, Institut Catala de la Salut, Barcelona, Catalonia, Spain" }, { - "author_name": "Gopal Datt Joshi", - "author_inst": "Noodle Analytics Pvt Ltd" + "author_name": "Ramon Miralles", + "author_inst": "Direccio Clinica Territorial de Cronicitat Metropolitana Nord, Institut Catala de la Salut, Barcelona, Catalonia, Spain ;Geriatrics Department, Hospital Univers" }, { - "author_name": "Gagan Deep Jhingan", - "author_inst": "Vallerian Chem Pvt. Ltd. K37A, Ground Floor, Green Park MAIN, New Delhi 110016, India" + "author_name": "Montserrat Teixido Colet", + "author_inst": "Direccio Atencio Primaria Metropolitana Nord, Institut Catala de la Salut, Barcelona, Catalonia, Spain" }, { - "author_name": "Jawed Iqbal", - "author_inst": "Jamia Millia Islamia" + "author_name": "Joaquim Verdaguer Puigvendrello", + "author_inst": "Direccio Atencio Primaria Metropolitana Nord, Institut Catala de la Salut, Barcelona, Catalonia, Spain" }, { - "author_name": "Mohan C Joshi", - "author_inst": "Jamia Millia Islamia" + "author_name": "Norma Henriquez", + "author_inst": "Direccio Atencio Primaria Metropolitana Nord, Institut Catala de la Salut, Barcelona, Catalonia, Spain" }, { - "author_name": "Tanveer Ahmad", - "author_inst": "Jamia Millia Islamia" + "author_name": "Michael Marks", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Jordi Ara", + "author_inst": "Direccio Atencio Primaria Metropolitana Nord, Institut Catala de la Salut, Barcelona, Catalonia, Spain" + }, + { + "author_name": "Oriol Mitja", + "author_inst": "Fight AIDS and Infectious Diseases Foundation, Badalona, Badalona, Spain; Infectious Diseases Department, Hospital Universitari Germans Trias i Pujol, Badalona," } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1105165,35 +1104651,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.11.07.20201335", - "rel_title": "Socio-economic disparities in social distancing during the COVID-19 pandemic in the United States", + "rel_doi": "10.1101/2020.11.06.20227405", + "rel_title": "Gout, rheumatoid arthritis and the risk of death from COVID-19: an analysis of the UK Biobank", "rel_date": "2020-11-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.07.20201335", - "rel_abs": "ImportanceEliminating disparities in the burden of COVID-19 requires equitable access to control measures across socio-economic groups. Limited research on socio-economic differences in mobility hampers our ability to understand whether inequalities in social distancing are occurring during the SARS-CoV-2 pandemic.\n\nObjectiveTo assess how mobility patterns have varied across the United States during the COVID-19 pandemic, and identify associations with socio-economic factors of populations.\n\nDesign, Setting, and ParticipantsWe used anonymized mobility data from tens of millions of devices to measure the speed and depth of social distancing at the county level between February and May 2020. Using linear mixed models, we assessed the associations between social distancing and socio-economic variables, including the proportion of people below the poverty level, the proportion of Black people, the proportion of essential workers, and the population density.\n\nMain outcomes and ResultsWe find that the speed, depth, and duration of social distancing in the United States is heterogeneous. We particularly show that social distancing is slower and less intense in counties with higher proportions of people below the poverty level and essential workers; and in contrast, that social distancing is intense in counties with higher population densities and larger Black populations.\n\nConclusions and relevanceSocio-economic inequalities appear to be associated with the levels of adoption of social distancing, potentially resulting in wide-ranging differences in the impact of COVID-19 in communities across the United States. This is likely to amplify existing health disparities, and needs to be addressed to ensure the success of ongoing pandemic mitigation efforts.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.06.20227405", + "rel_abs": "ObjectivesTo assess whether gout and / or rheumatoid arthritis (RA) are risk factors for coronavirus disease 19 (COVID-19) diagnosis. To assess whether gout and / or RA are risk factors for death with COVID-19.\n\nMethodsWe used data from the UK Biobank. Multivariable-adjusted logistic regression was employed in the following analyses: Analysis A, to test for association between gout or RA and COVID-19 diagnosis (n=473,139); Analysis B, to test for association between gout or RA and death with COVID-19 in a case-control cohort of people who died or survived with COVID-19 (n=2,059); Analysis C, to test for association with gout or RA and death with COVID-19 in the entire UK Biobank cohort (n=473,139)\n\nResultsRA, but not gout, associated with COVID-19 diagnosis in analysis A. Neither RA nor gout associated with risk of death in the COVID-19-diagnosed group in analysis B. However RA associated with risk of death related to COVID-19 using the UK Biobank cohort in analysis C independent of comorbidities and other measured risk factors (OR=1.9 [95% CI 1.2 ; 3.0]). Gout was not associated with death related to COVID-19 in the same UK Biobank analysis (OR=1.2 [95% CI 0.8 ; 1.7]).\n\nConclusionRheumatoid arthritis is a risk factor for death with COVID-19 using the UK Biobank cohort. These findings require replication in larger data sets that also allow inclusion of a wider range of factors.\n\nKey messagesInformation on the risk of death from COVID-19 for people with gout and rheumatoid arthritis is scarce.\n\nIn an analysis of the UK Biobank there is an increased risk of death related to COVID-19 for people with rheumatoid arthritis independent of included co-morbidities, but not gout.\n\nThe findings need to be replicated in other datasets where the influence of therapies for rheumatoid arthritis can be tested.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Romain Garnier", - "author_inst": "Georgetown University" + "author_name": "Ruth Topless", + "author_inst": "University of Otago" }, { - "author_name": "Jan R Benetka", - "author_inst": "Unacast" + "author_name": "Amanda Phipps-Green", + "author_inst": "University of Otago" }, { - "author_name": "John Kraemer", - "author_inst": "Georgetown University" + "author_name": "Megan Leask", + "author_inst": "University of Otago" }, { - "author_name": "Shweta Bansal", - "author_inst": "Georgetown University" + "author_name": "Nicola Dalbeth", + "author_inst": "University of Auckland" + }, + { + "author_name": "Lisa Stamp", + "author_inst": "University of Otago" + }, + { + "author_name": "Philip Robinson", + "author_inst": "University of Queensland" + }, + { + "author_name": "Tony Merriman", + "author_inst": "University of Alabama at Birmingham" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "rheumatology" }, { "rel_doi": "10.1101/2020.11.09.374082", @@ -1107142,63 +1106640,95 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.11.06.20227017", - "rel_title": "Predicting the impact of disruptions in lymphatic filariasis elimination programmes due to the outbreak of coronavirus disease (COVID-19) and possible mitigation strategies", + "rel_doi": "10.1101/2020.11.06.20220087", + "rel_title": "Seroprevalence of Anti-SARS-CoV-2 Antibodies in a Cohort of New York City Metro Blood Donors using Multiple SARS-CoV-2 Serological Assays: Implications for Controlling the Epidemic and Reopening.", "rel_date": "2020-11-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.06.20227017", - "rel_abs": "BackgroundIn view of the current global COVID-19 pandemic, mass drug administration interventions for neglected tropical diseases, including lymphatic filariasis, have been halted. We used mathematical modelling to estimate the impact of delaying or cancelling treatment rounds and explore possible mitigation strategies.\n\nMethodsWe used three established lymphatic filariasis transmission models to simulate infection trends in settings with annual treatment rounds and programme delays in 2020 of 6, 12, 18 or 24 months. We then evaluated the impact of various mitigation strategies upon resuming activities.\n\nResultsThe delay in achieving the elimination goals is on average similar to the number of years the treatment rounds are missed. Enhanced interventions implemented for as little as one year can allow catch-up on the progress lost, and if maintained throughout the programme can lead to acceleration of up to 3 years.\n\nConclusionsIn general, a short delay in the programme does not cause major delay in achieving the goals. Impact is strongest in high endemicity areas. Mitigation strategies such as biannual treatment or increased coverage are key to minimizing the impact of the disruption once the programme resumes; and lead to potential acceleration, should these enhanced strategies be maintained.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.06.20220087", + "rel_abs": "Projections of the stage of the Severe Acute Respiratory Syndrome-Coronavirus-2 (SARS-CoV-2) pandemic and local, regional and national public health policies designed to limit the spread of the epidemic as well as \"reopen\" cities and states, are best informed by serum neutralizing antibody titers measured by reproducible, high throughput, and statically credible antibody (Ab) assays. To date, a myriad of Ab tests, both available and authorized for emergency use by the FDA, has led to confusion rather than insight per se. The present study reports the results of a rapid, point-in-time 1,000-person cohort study using serial blood donors in the New York City metropolitan area (NYC) using multiple serological tests, including enzyme-linked immunosorbent assays (ELISAs) and high throughput serological assays (HTSAs). These were then tested and associated with assays for neutralizing Ab (NAb). Of the 1,000 NYC blood donor samples in late June and early July 2020, 12.1% and 10.9% were seropositive using the Ortho Total Ig and the Abbott IgG HTSA assays, respectively. These serological assays correlated with neutralization activity specific to SARS-CoV-2. The data reported herein suggest that seroconversion in this population occurred in approximately 1 in 8 blood donors from the beginning of the pandemic in NYC (considered March 1, 2020). These findings deviate with an earlier seroprevalence study in NYC showing 13.7% positivity. Collectively however, these data demonstrate that a low number of individuals have serologic evidence of infection during this \"first wave\" and suggest that the notion of \"herd immunity\" at rates of [~]60% or higher are not near. Furthermore, the data presented herein show that the nature of the Ab-based immunity is not invariably associated with the development of NAb. While the blood donor population may not mimic precisely the NYC population as a whole, rapid assessment of seroprevalence in this cohort and serial reassessment could aid public health decision making.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Joaquin M Prada", - "author_inst": "School of Veterinary Medicine, Faculty of Health and Medical Sciences, University of Surrey" + "author_name": "Daniel K Jin", + "author_inst": "New York Blood Center" }, { - "author_name": "Wilma A Stolk", - "author_inst": "Department of Public Health, Erasmus MC, University Medical Center Rotterdam" + "author_name": "Daniel J Nesbitt", + "author_inst": "New York Blood Center" }, { - "author_name": "Emma L Davis", - "author_inst": "Big Data Institute, Li Ka Shing Center for Health Information and Discovery, University of Oxford" + "author_name": "Jenny Yang", + "author_inst": "New York Blood Center" }, { - "author_name": "Panayiota Touloupou", - "author_inst": "Department of Statistics, University of Warwick" + "author_name": "Haidee Chen", + "author_inst": "New York Blood Center" }, { - "author_name": "Swarnali Sharma", - "author_inst": "College of Public Health, University of South Florida" + "author_name": "Julie Horowitz", + "author_inst": "Regeneron Genetics Center" }, { - "author_name": "Johanna Munoz", - "author_inst": "Department of Public Health, Erasmus MC, University Medical Center Rotterdam" + "author_name": "Marcus Jones", + "author_inst": "Regeneron Genetics Center" }, { - "author_name": "Rocio M Caja Rivera", - "author_inst": "College of Public Health, University of South Florida" + "author_name": "Rianna Vandergaast", + "author_inst": "Imanis Life Sciences" }, { - "author_name": "Lisa J Reimer", - "author_inst": "Department of Vector Biology, Liverpool School of Tropical Medicine" + "author_name": "Timothy Carey", + "author_inst": "Imanis Life Sciences" }, { - "author_name": "Edwin Michael", - "author_inst": "College of Public Health, University of South Florida" + "author_name": "Samantha Reiter", + "author_inst": "Imanis Life Sciences" }, { - "author_name": "Sake J de Vlas", - "author_inst": "Department of Public Health, Erasmus MC, University Medical Center Rotterdam" + "author_name": "Stephen J Russell", + "author_inst": "Imanis Life Sciences" }, { - "author_name": "Deirdre Hollingsworth", - "author_inst": "Big Data Institute, Li Ka Shing Center for Health Information and Discovery, University of Oxford" + "author_name": "Christos Kyratsous", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Andrea Hooper", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Jennifer Hamilton", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Manuel Ferreira", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Sarah Deng", + "author_inst": "Regeneron Pharmaceuticals, Inc." + }, + { + "author_name": "Donna Straus", + "author_inst": "New York Blood Center" + }, + { + "author_name": "Aris Baras", + "author_inst": "Regeneron Genetics Center" + }, + { + "author_name": "Christopher D Hillyer", + "author_inst": "New York Blood Center" + }, + { + "author_name": "Larry L Luchsinger", + "author_inst": "New York Blood Center" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.11.05.20226621", @@ -1109028,39 +1108558,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.04.20226092", - "rel_title": "Nowcasting and forecasting provincial-level SARS-CoV-2 case positivity using google search data in South Africa", + "rel_doi": "10.1101/2020.11.05.20225300", + "rel_title": "Children hospitalized for COVID-19 during first winter of the pandemic in Buenos Aires, Argentina", "rel_date": "2020-11-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.04.20226092", - "rel_abs": "Data from non-traditional data sources, such as social media, search engines, and remote sensing, have previously demonstrated utility for disease surveillance. Few studies, however, have focused on countries in Africa, particularly during the SARS-CoV-2 pandemic. In this study, we use searches of COVID-19 symptoms, questions, and at-home remedies submitted to Google to model COVID-19 in South Africa, and assess how well the Google search data forecast short-term COVID-19 trends. Our findings suggest that information seeking trends on COVID-19 could guide models for anticipating COVID-19 trends and coordinating appropriate response measures.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.05.20225300", + "rel_abs": "BackgroundAlthough there are reports on COVID-19 in pediatrics, it is possible that the characteristics of each population, their health systems and how they faced the pandemic made the disease show distinctive features in different countries.\n\nObjectiveWe aimed to describe the characteristics of patients hospitalized for COVID-19 in a tertiary pediatric hospital in the City of Buenos Aires, Argentina.\n\nMethodsDescriptive study, including all patients hospitalized for COVID-19 in a tertiary pediatric hospital, from 04/26/2020 to 10/31/2020. Demographic, clinical and epidemiological characteristics of the patients are described.\n\nResultsIn the studied period 578 patients were hospitalized for COVID-19. The median age was 4.2 years and 83% had a history of close contact with a confirmed COVID-19 case. Regarding severity, 30.8% were asymptomatic, 60.4% mild, 7.4% moderate, and 1.4% severe. Among those with symptoms, the most frequent was fever, followed by sore throat and cough.\n\nConclusionWe reported 578 cases of children and adolescents hospitalized for COVID-19, most of them showed a mild or asymptomatic condition.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Elaine O. Nsoesie", - "author_inst": "Boston University School of Public Health" + "author_name": "Silvina Raiden", + "author_inst": "Hospital General de Ninos Pedro de Elizalde" }, { - "author_name": "Karla Therese L. Sy", - "author_inst": "Boston University School of Public Health" + "author_name": "Hector Cairoli", + "author_inst": "Hospital General de Ninos Pedro de Elizalde" }, { - "author_name": "Olubusola Oladeji", - "author_inst": "Boston University School of Public Health" + "author_name": "Javier Potasnik", + "author_inst": "Hospital General de Ninos Pedro de Elizalde" }, { - "author_name": "Raesetje Sefala", - "author_inst": "University of the Witwatersrand" + "author_name": "Sandra Di Lalla", + "author_inst": "Hospital General de Ninos Pedro de Elizalde" }, { - "author_name": "Brooke E. Nichols", - "author_inst": "Boston University School of Public Health" + "author_name": "Maria Jose Chiolo", + "author_inst": "Hospital General de Ninos Pedro de Elizalde" + }, + { + "author_name": "Fernando Adrian Torres", + "author_inst": "Hospital General de Ninos Pedro de Elizalde" + }, + { + "author_name": "Paula Dominguez", + "author_inst": "Hospital General de Ninos Pedro de Elizalde" + }, + { + "author_name": "Fernando Ferrero", + "author_inst": "Hospital General de Ninos Pedro de Elizalde" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pediatrics" }, { "rel_doi": "10.1101/2020.11.03.20225102", @@ -1110901,23 +1110443,43 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.11.03.20225425", - "rel_title": "Per capita COVID-19 Case Rates are Lower in U.S. Counties Voting more Heavily Democratic in the 2016 Presidential Election, except not in States with a Republican Governor and Legislature", + "rel_doi": "10.1101/2020.11.03.20225326", + "rel_title": "Coronavirus Disease 2019 (COVID-19) Candidate Chest CT Features: A Systematic Review of Extracted Imaging Features from 7571 Individuals", "rel_date": "2020-11-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.03.20225425", - "rel_abs": "In our recent paper Why do per capita COVID-19 Case Rates Differ Between U.S. States? we established that U.S. states with a Democratic governor and a Democratic legislature have lower COVID-19 per capita case rates than states with a Republican governor and a Republican legislature, and case rates of states with a mixed government fall between the two. This difference remained after accounting for differences between states in several demographic and socio-economic variables. In a recent working paper The Changing Political Geographies of COVID-19 in the U.S. it was found that that early in the pandemic U.S. counties at higher levels of percentage Democratic vote in the 2016 presidential election had higher weekly per capita COVID-19 rates, but that the situation was in the opposite direction by August 2020. We show here that counties with a higher percentage of Democratic vote in the 2016 presidential election have a lower mean cumulative per capita rate of COVID-19 cases and of COVID-19 deaths, adjusted for county demographic and socio-economic characteristics, but only for counties in states that currently have a Democratic governor and both chambers of the legislature Democratic or in states that have a mixed government, but not for states that currently have a Republican governor and both chambers in the legislature Republican. One possible contributor to this difference is that some state Republican governments have restricted local action to fight the spread of COVID-19.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.03.20225326", + "rel_abs": "Since the outbreak of Coronavirus Disease 2019 (COVID-19) causing novel coronavirus (2019-nCoV)-infected pneumonia (NCIP), over 45 million affected cases have been reported worldwide. Many patients with COVID-19 have involvement of their respiratory system. According to studies in the radiology literature, chest computed tomography (CT) is recommended in suspected cases for initial detection, evaluating the disease progression and monitoring the response to therapy. The aim of this article is to review the most frequently reported imaging features in COVID-19 patients in order to provide a reliable insight into expected CT imaging manifestations in patients with positive reverse-transcription polymerase chain reaction (RT-PCR) test results, and also for the initial detection of patients with suspicious clinical presentation whose RT-PCR test results are false negative. A total of 60 out of 173 initial COVID-19 studies, comprising 7571 individuals, were identified by searching PubMed database for articles published between the months of January and June 2020. The data of these studies were related to patients from China, Japan, Italy, USA, Iran and Singapore. Among 40 reported features, presence of ground glass opacities (GGO), consolidation, bilateral lung involvement and peripheral distribution are the most frequently observed ones, reported in 100%, 91.7%, 85%, and 83.3% of articles, respectively. In a similar way, we extracted CT imaging studies of similar pulmonary syndromes outbreaks caused by other strains of coronavirus family: Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). For MERS and SARS, 2 out of 21 and 5 out of 153 initially retrieved studies had CT findings, respectively. Herein, we have indicated the most common coronavirus family related and COVID-19 specific features. Presence of GGO, consolidation, bilateral lung involvement and peripheral distribution were the features reported in at least 83% of COVID-19 articles, while air bronchogram, multi-lobe involvement and linear opacity were the three potential COVID-19 specific CT imaging findings. This is necessary to recognize the most promising imaging features for diagnosis and follow-up of patients with COVID-19. Furthermore, we identified co-existed CT imaging features.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Lloyd Chambless", - "author_inst": "Retired" + "author_name": "Javad Zahiri", + "author_inst": "Bioinformatics and Computational Omics Lab (BioCOOL), Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran" + }, + { + "author_name": "Mohammad Hossein Afsharinia", + "author_inst": "Bioinformatics and Computational Omics Lab (BioCOOL), Department of Biophysics, Faculty of Biological Sciences, Tarbiat Modares University, Tehran, Iran" + }, + { + "author_name": "Zhaleh Hekmati", + "author_inst": "Dr Khodarahmi Medical Imaging Center, Karaj, Iran" + }, + { + "author_name": "Mohsen Khodarahmi", + "author_inst": "Dr Khodarahmi Medical Imaging Center, Karaj, Iran" + }, + { + "author_name": "Shahrzad Hekmati", + "author_inst": "Department of Radiology, Madaran Hospital, Tehran, Iran" + }, + { + "author_name": "Ramin Pourghorban", + "author_inst": "Department of Radiology, Sina Hospital, EBIR Tehran University of Medical Sciences, Tehran, Iran" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2020.11.03.20225136", @@ -1113231,25 +1112793,89 @@ "category": "sports medicine" }, { - "rel_doi": "10.1101/2020.11.01.20217943", - "rel_title": "CovidSIMVL - Agent-Based Modeling of Localized Transmission within a Heterogeneous Array of Locations: Motivation, Configuration and Calibration", + "rel_doi": "10.1101/2020.11.01.20220475", + "rel_title": "Hospital based contact tracing of COVID-19 patients and health care workers and risk stratification of exposed health care workers during the COVID-19 Pandemic in Eastern India", "rel_date": "2020-11-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.01.20217943", - "rel_abs": "CovidSIMVL is an agent-based infectious disease modeling tool that is designed specifically to simulate localized spread of infectious disease. It is intended to support tactical decision-making around localized/staged re-institution of pre-pandemic levels and patterns of social/economic/health service delivery activity, following an initial stage of pan-societal closures of social/economic institutions and broad-based reductions in services.\n\nBy design, CovidSIMVL supports the generation of dynamic models that reflect heterogeneity within and between a network of interacting localized contexts. This heterogeneity is embodied in a hierarchically organized set of rules. Primary rules reflect the pathophysiology of transmission. Secondary rules (\"HazardRadius\" and \"Mingle Factor\" in CovidSIMVL) relate transmission to proximity and movement within physically demarcated and relatively contained spaces (\"Universes\"). Tertiary rules (\"Schedules\") relate probabilities of transmission to movement of people between a network of localized contexts (a CovidSIMVL \"Multiverse\").\n\nThis report focuses mainly on calibration of secondary rules. To calibrate the HazardRadius and MingleFactor parameters, growth curves were generated with CovidSIMVL by setting different configurations of values on those two proximal determinants of viral transmission. These were compared to the characteristic shapes of curves generated by equation-based compartmental models (e.g., SEIR models) that fit different real-world datasets embodying different reproduction numbers (R0).\n\nBy operating with parameter values in CovidSIMVL that generate \"real-world\" growth curves, the tool can be used to produce plausible simulations of localized chains of transmission. These include transmission among different groups of persons (e.g., staff, patients) who are co-located within a single setting such as a long-term care facility. The Multiverse version of CovidSIMVL can be used to simulate localized cross-over transmission among arrays consisting of both unaffected and impacted contexts and associated sub-populations, via agents who interact within and across arrays of contexts such as schools, multigenerational families, recreational facilities, places of work, emergency shelters for homeless persons, or other settings in which people are in close physical proximity.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.01.20220475", + "rel_abs": "IntroductionContact tracing and subsequent quarantining of Health Care Workers (HCWs) is essential to minimize further transmission of COVID-19 infection. In this study, we have reported the yield of Contact Tracing of COVID-19 Patients and HCWs and risk stratification of exposed HCWs.\n\nMethodologyThis is a secondary analysis of routine data collected for contact tracing from 19th March to 31st August 2020 at All India Institute of Medical Sciences, Bhubaneswar, Odisha, India. HCWs exposed to COVID-19 infections were categorized as per the risk stratification guidelines and the high-risk contacts were quarantined for 14 days and tested on 7th day from last day of exposure. The low risk contacts were encouraged to closely monitor their symptoms while continuing to work.\n\nResultsOut of 3411 HCWs exposed to COVID 19 patients (n=269) and HCWs (n=91), 890 (26.1%) were high risk contacts and 2521 (73.9%) were low risk contacts. The test positivity rate of high-risk contact was 3.82% and for low risk contact was 1.90%. Average number of high-risk contacts was significantly higher; for admitted patients (6.6) as compared to HCWs (4.0) and outpatients (0.2), p value = 0.009; for patients admitted in non-COVID areas (15.8) as compared to COVID areas (0.27), p value < 0.001; and when clustering of cases was present (14.3) as compared to isolated cases (8.2); p value < 0.001. Trend analysis (15 days block period) showed a significant decline in number of mean numbers of high-risk contacts during the study period.\n\nConclusionContact tracing and risk stratification was effective and helped in reducing the number of HCWs going for quarantine. There was also a decline in high-risk contacts during study period suggesting role of implementation of hospital based COVID related infection control strategies. This contact tracing and risk stratification approach designed in the current study can also be implemented in other healthcare settings.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Kenneth Andrew Moselle", - "author_inst": "Island Health (Vancouver Island Health Authority)" + "author_name": "Durgesh Prasad Sahoo", + "author_inst": "All India Institute of Medical Sciences Bibinagar" }, { - "author_name": "Ernie Chang", - "author_inst": "Contractor" + "author_name": "Arvind Kumar Singh", + "author_inst": "All India Institute of Medical Sciences,Bhubaneswar" + }, + { + "author_name": "Dinesh Prasad Sahu", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Somen Kumar Pradhan", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Binod Kumar Patro", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Gitanjali Batmanabane", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Baijayantimala Mishra", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Bijayini Behera", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Ambarish Dash", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "G Susmita Dora", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Anand L", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Azhar S M", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Jyolsna Nair", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Sasmita Panigrahi", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Akshaya R", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Bimal Kumar sahoo", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Subhakanta Sahu", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" + }, + { + "author_name": "Suchismita Sahoo", + "author_inst": "ALL INDIA INSTITITE OF MEDICAL SCIENCES, BHUBNESAR" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1114669,35 +1114295,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.31.20223776", - "rel_title": "Cell phone mobility data reveals heterogeneity in stay-at-home behavior during the SARS-CoV-2 pandemic", + "rel_doi": "10.1101/2020.11.02.20222778", + "rel_title": "SARS-CoV-2 responsive T cell numbers are associated with protection from COVID-19: A prospective cohort study in keyworkers", "rel_date": "2020-11-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.31.20223776", - "rel_abs": "As COVID-19 cases resurge in the United States, understanding the complex interplay between human behavior, disease transmission, and non-pharmaceutical interventions during the pandemic could provide valuable insights to focus future public health efforts. Cell-phone mobility data offers a modern measurement instrument to investigate human mobility and behavior at an unprecedented scale. We investigate mobility data collected, aggregated, and anonymized by SafeGraph Inc. which measures how populations at the census-block-group geographic scale stayed at home in California, Georgia, Texas, and Washington since the beginning of the pandemic. Using manifold learning techniques, we find patterns of mobility behavior that align with stay-at-home orders, correlate with socioeconomic factors, cluster geographically, and reveal sub-populations that likely migrated out of urban areas. The analysis and approach provides policy makers a framework for interpreting mobility data and behavior to inform actions aimed at curbing the spread of COVID-19.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.02.20222778", + "rel_abs": "Immune correlates of protection from COVID-19 are incompletely understood. 2,826 keyworkers had T-SPOT(R) Discovery SARS-CoV-2 tests (measuring interferon-{gamma} secreting, SARS-CoV-2 responsive T cells, Oxford Immunotec Ltd), and anti-Spike S1 domain IgG antibody levels (EuroImmun AG) performed on recruitment into a cohort study. 285/2,826 (10.1%) of participants had positive SARS-CoV-2 RT-PCR tests, predominantly associated with symptomatic illness, during 200 days followup. T cell responses to Spike, Nucleoprotein and Matrix proteins (SNM responses) were detected in some participants at recruitment, as were anti-Spike S1 IgG antibodies; higher levels of both were associated with protection from subsequent SARS-CoV-2 test positivity. In volunteers with moderate antibody responses, who represented 39% (252/654) of those with detectable anti-Spike IgG, protection was partial, and higher with higher circulating T cell SNM responses. SARS-CoV-2 responsive T cell numbers predict protection in individuals with low anti-Spike IgG responses; serology alone underestimates the proportion of the population protected after infection.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Roman Levin", - "author_inst": "University of Washington" + "author_name": "David H Wyllie", + "author_inst": "Public Health England" }, { - "author_name": "Dennis L Chao", - "author_inst": "Institute for Disease Modeling, Bill and Melinda Gates Foundation" + "author_name": "Ranya Mulchandani", + "author_inst": "Public Health England" }, { - "author_name": "Edward A. Wenger", - "author_inst": "Institute for Disease Modeling, Bill and Melinda Gates Foundation" + "author_name": "Hayley E Jones", + "author_inst": "University of Bristol" }, { - "author_name": "Joshua L Proctor", - "author_inst": "Institute for Disease Modeling, Bill and Melinda Gates Foundation" + "author_name": "Sian Taylor-Phillips", + "author_inst": "University of Warwick" + }, + { + "author_name": "Tim Brooks", + "author_inst": "Public Health England" + }, + { + "author_name": "Andre Charlett", + "author_inst": "Public Health England" + }, + { + "author_name": "AE Ades", + "author_inst": "University of Bristol" + }, + { + "author_name": "- EDSAB-HOME Investigators", + "author_inst": "" + }, + { + "author_name": "Andrew Makin", + "author_inst": "Oxford ImmunoTech" + }, + { + "author_name": "Isabel Oliver", + "author_inst": "Public Health England" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.11.02.20223891", @@ -1116363,71 +1116013,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.30.20221440", - "rel_title": "The relationship between anxiety, health, and potential stressors among adults in the United States during the COVID-19 pandemic", + "rel_doi": "10.1101/2020.11.03.20225466", + "rel_title": "Delirium and Post-Discharge Neuropsychological Outcomes in Critically Ill Patients with COVID-19: an Institutional Case Series", "rel_date": "2020-11-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.30.20221440", - "rel_abs": "ObjectiveTo estimate the prevalence of anxiety symptoms and the association between moderate or severe anxiety symptoms and health and potential stressors among adults in the U.S. during the COVID-19 pandemic\n\nMethodsThis analysis includes data from 5,250 adults in the Communities, Households and SARS/CoV-2 Epidemiology (CHASING) COVID Cohort Study surveyed in April 2020. Poisson models were used to estimate the association between moderate or severe anxiety symptoms and health and potential stressors among U.S. adults during the COVID-19 pandemic.\n\nResultsGreater than one-third (35%) of participants reported moderate or severe anxiety symptoms. Having lost income due to COVID-19 (adjusted prevalence ratio [aPR] 1.27 (95% CI 1.16, 1.30), having recent COVID-like symptoms (aPR 1.17 (95% CI 1.05, 1,31), and having been previously diagnosed with depression (aPR 1.49, (95% CI 1.35, 1.64) were positively associated with anxiety symptoms.\n\nConclusionsAnxiety symptoms were common among adults in the U.S. during the COVID-19 pandemic. Strategies to screen and treat individuals at increased risk of anxiety, such as individuals experiencing financial hardship and individuals with prior diagnoses of depression, should be developed and implemented.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.11.03.20225466", + "rel_abs": "ObjectiveTo characterize the clinical course of delirium for COVID-19 patients in the intensive care unit, including post-discharge cognitive outcomes.\n\nPatients and MethodsA retrospective chart review was conducted for patients diagnosed with COVID-19 (n=148) admitted to an intensive care unit at Michigan Medicine between March 1, 2020 and May 31, 2020. A validated chart review method was used to identify presence of delirium, and various measures (e.g., Family Confusion Assessment Method, Short Blessed Test, Patient-Health Questionnaire-9) were used to determine neuropsychological outcomes between 1-2 months after hospital discharge.\n\nResultsDelirium was identified in 108/148 (73%) patients in the study cohort, with median (interquartile range) duration lasting 10 (4 - 17) days. In the delirium cohort, 50% (54/108) of patients were African American, and delirious patients were more likely to be female (76/108, 70%) (absolute standardized differences >.30). Sedation regimens, inflammation, deviation from delirium prevention protocols, and hypoxic-ischemic injury were likely contributing factors, and the most common disposition for delirious patients was a skilled care facility (41/108, 38%). Among patients who were delirious during hospitalization, 4/17 (24%) later screened positive for delirium at home based on caretaker assessment, 5/22 (23%) demonstrated signs of questionable cognitive impairment or cognitive impairment consistent with dementia, and 3/25 (12%) screened positive for depression within two months after discharge.\n\nConclusionPatients with COVID-19 commonly experience a prolonged course of delirium in the intensive care unit, likely with multiple contributing factors. Furthermore, neuropsychological impairment may persist after discharge.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Angela Parcesepe", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "McKaylee Robertson", - "author_inst": "CUNY ISPH" - }, - { - "author_name": "Amanda Berry", - "author_inst": "CUNY ISPH" - }, - { - "author_name": "Andrew R Maroko", - "author_inst": "CUNY ISPH; CUNY Graduate School of Public Health and Health Policy, Department of Environmental, Occupational, and Geospatial Health Sciences" + "author_name": "Jacqueline Ragheb", + "author_inst": "Michigan Medicine" }, { - "author_name": "Rebecca Zimba", - "author_inst": "CUNY ISPH" + "author_name": "Amy McKinney", + "author_inst": "Michigan Medicine" }, { - "author_name": "Christian Grov", - "author_inst": "CUNY ISPH; Department of Community Health and Social Services, Graduate School of Public Health and Health Policy, City University of New York" + "author_name": "Mackenzie Zierau", + "author_inst": "Michigan Medicine" }, { - "author_name": "Drew Westmoreland", - "author_inst": "CUNY ISPH" + "author_name": "Joseph Brooks", + "author_inst": "Michigan Medicine" }, { - "author_name": "Sarah Kulkarni", - "author_inst": "CUNY ISPH" + "author_name": "Maria Hill-Caruthers", + "author_inst": "Michigan Medicine" }, { - "author_name": "Madhura Rane", - "author_inst": "CUNY ISPH" + "author_name": "Mina Iskander", + "author_inst": "New York Medical College" }, { - "author_name": "William Salgado-You", - "author_inst": "CUNY ISPH" + "author_name": "Yusuf Ahmed", + "author_inst": "Michigan Medicine" }, { - "author_name": "Chloe Mirzayi", - "author_inst": "CUNY ISPH; CUNY Graduate School of Public Health and Health Policy, Department of Epidemiology and Biostatistics" + "author_name": "Remy Lobo", + "author_inst": "Michigan Medicine" }, { - "author_name": "Levi Waldron", - "author_inst": "CUNY ISPH; CUNY Graduate School of Public Health and Health Policy, Department of Epidemiology" + "author_name": "Graciela Mentz", + "author_inst": "Michigan Medicine" }, { - "author_name": "Denis Nash", - "author_inst": "CUNY ISPH; CUNY Graduate School of Public Health and Health Policy; Department of Epidemiology and Biostatistics" + "author_name": "Phillip E. Vlisides", + "author_inst": "Michigan Medicine" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "anesthesia" }, { "rel_doi": "10.1101/2020.11.04.20225573", @@ -1117853,71 +1117491,43 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2020.10.29.20215996", - "rel_title": "''Necessity is the mother of invention'': Specialist palliative care service innovation and practice change in response to COVID-19. Results from a multi-national survey (CovPall)", + "rel_doi": "10.1101/2020.10.29.20222430", + "rel_title": "The prevalence of common mental disorders among health care professionals during the COVID-19 pandemic at a tertiary Hospital in East Africa", "rel_date": "2020-11-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.29.20215996", - "rel_abs": "BackgroundSpecialist palliative care services have a key role in a whole system response to COVID-19. There is a need to understand service response to share good practice and prepare for future care.\n\nAimTo map and understand specialist palliative care services innovations and practice changes in response to COVID-19 (CovPall).\n\nDesignOnline survey of specialist palliative care providers, disseminated via key stakeholders. Data collected on service characteristics, innovations and changes in response to COVID-19. Statistical analysis included frequencies, proportions and means, and free-text comments were analysed using a qualitative framework approach.\n\nSetting/participantsInpatient palliative care units, home nursing services, hospital and home palliative care teams from any country.\n\nResults458 respondents: 277 UK, 85 Europe (except UK), 95 World (except UK and Europe), 1 missing country. 54.8% provided care across 2+ settings; 47.4% hospital palliative care teams, 57% in-patient palliative care units, and 57% home palliative care teams. The crisis context meant services implemented rapid changes. Changes involved streamlining, extending and increasing outreach of services, using technology to facilitate communication, and implementing staff wellbeing innovations. Barriers included; fear and anxiety, duplication of effort, information overload, funding, and IT infrastructure issues. Enablers included; collaborative teamwork, pooling of staffing resources, staff flexibility, a pre-existing IT infrastructure and strong leadership.\n\nConclusionsSpecialist palliative care services have been flexible, highly adaptive and have adopted a frugal innovation model in response to COVID-19. In addition to financial support, greater collaboration is essential to minimise duplication of effort and optimise resource use.\n\nISRCTN16561225https://doi.org/10.1186/ISRCTN16561225\n\nKey StatementsO_ST_ABSWhat is already known about the topic?C_ST_ABSO_LISpecialist palliative care is part of a whole healthcare system response to COVID-19.\nC_LIO_LIServices need to make practice changes in response to the global pandemic.\nC_LI\n\nWhat this paper addsO_LISpecialist palliative care services responded rapidly to COVID-19 in both planning for change and then adapting to needs and requirements.\nC_LIO_LIServices often relied on improvisation, quick fixes and making do when responding to the COVID-19 crisis.\nC_LI\n\nImplications for practice, theory or policyO_LIIn addition to financial support, greater collaboration is essential to build organisational resilience and drive forward innovation, by minimising duplication of effort and optimising resource use.\nC_LIO_LIThe effectiveness and sustainability of any changes made during the crisis needs further evaluation.\nC_LI", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.29.20222430", + "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) has resulted in unprecedented morbidity, mortality, and health system crisis leading to a significant psychological distress on healthcare workers (HCWs). The study aimed to determine the prevalence of symptoms of common mental disorders among HCWs during the COVID-19 pandemic at St. Pauls Hospital, Ethiopia.\n\nMethodsA self-administered cross-sectional study was conducted to collect socio-demographic information and symptoms of mental disorders using validated measurement tools. Accordingly, PHQ-9, GAD-7, ISI, and IES-R were used to assess the presence of symptoms of depression, anxiety, insomnia, and distress, respectively. Chi-square test, non-parametric, and logistic regression analysis were used to detect risk factors for common mental disorders.\n\nResultsA total of 420 healthcare workers participated in the survey. The prevalence of depression, anxiety, insomnia, and psychological distress was 20.2%, 21.9%, 12.4%, and 15.5% respectively. Frontline HCWs had higher scores of mental health symptoms than other health care workers. Logistic regression analysis showed that being married was associated with a high level of depression. Working in a frontline position was an independent factor associated with a high-level depression, anxiety, and psychological distress.\n\nLimitationsIt is a single-centre cross-sectional study and the findings may not be generalizable or reveal causality.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Lesley Dunleavy", - "author_inst": "Lancaster University" - }, - { - "author_name": "Nancy Preston", - "author_inst": "Lancaster University" - }, - { - "author_name": "Sabrina Bajwah", - "author_inst": "King's College London" - }, - { - "author_name": "Andy Bradshaw", - "author_inst": "University of Hull" - }, - { - "author_name": "Rachel Cripps", - "author_inst": "King's College London" - }, - { - "author_name": "Lorna K Fraser", - "author_inst": "University of York" - }, - { - "author_name": "Matthew Maddocks", - "author_inst": "King's College London" - }, - { - "author_name": "Mevhibe Hocaoglu", - "author_inst": "King's College London" + "author_name": "Hailu Abera Mulatu", + "author_inst": "St. Paul's Hospital Millennium Medical College" }, { - "author_name": "Fliss EM Murtagh", - "author_inst": "University of Hull" + "author_name": "Muluken Tesfaye", + "author_inst": "St. Paul's Hospital Millennium Medical College" }, { - "author_name": "Adejoke Oluyase", - "author_inst": "King's College London" + "author_name": "Esubalew Woldeyes", + "author_inst": "St. Paul's Hospital Millennium Medical College" }, { - "author_name": "Katherine E Sleeman", - "author_inst": "King's College London" + "author_name": "Tola Bayisa", + "author_inst": "St. Paul's Hospital Millennium Medical College" }, { - "author_name": "Irene Higginson", - "author_inst": "King's College London" + "author_name": "Henok Fisseha", + "author_inst": "St. Paul's Hospital Millennium Medical College" }, { - "author_name": "Catherine Walshe", - "author_inst": "Lancaster University" + "author_name": "Rodas Asrat", + "author_inst": "St. Paul's Hospital Millennium Medical College" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "palliative medicine" + "category": "psychiatry and clinical psychology" }, { "rel_doi": "10.1101/2020.10.29.20222182", @@ -1119974,41 +1119584,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.30.20222604", - "rel_title": "Growth of respiratory droplets in cold and humid air", + "rel_doi": "10.1101/2020.10.30.20222877", + "rel_title": "Quantification of occupational and community risk factors for SARS-CoV-2 seropositivity among healthcare workers in a large U.S. healthcare system", "rel_date": "2020-11-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.30.20222604", - "rel_abs": "The ambient conditions surrounding liquid droplets determine their growth or shrinkage. However, the precise fate of a liquid droplet expelled from a respiratory puff as dictated by its surroundings and the puff itself has not yet been fully quantified. From the view of airborne disease transmission, such as SARS-CoV-2, knowledge of such dependencies are critical. Here we employ direct numerical simulations (DNS) of a turbulent respiratory vapour puff and account for the mass and temperature exchange with respiratory droplets and aerosols. In particular, we investigate how droplets respond to different ambient temperatures and relative humidity (RH) by tracking their Lagrangian statistics. We reveal and quantify that in cold and humid environments, as there the respiratory puff is supersaturated, expelled droplets can first experience significant growth, and only later followed by shrinkage, in contrast to the monotonic shrinkage of droplets as expected from the classical view by William F. Wells (1934). Indeed, cold and humid environments diminish the ability of air to hold water vapour, thus causing the respiratory vapour puff to super-saturate. Consequently, the super-saturated vapour field drives the growth of droplets that are caught and transported within the humid puff. To analytically predict the likelihood for droplet growth, we propose a model for the axial RH based on the assumption of a quasi-stationary jet. Our model correctly predicts super-saturated RH conditions and is in good quantitative agreement with our DNS. Our results culminate in a temperature-RH map that can be employed as an indicator for droplet growth or shrinkage.\n\nSignificance StatementInfluence of environmental conditions on airborne diseases transmission is an important issue, especially during the pandemic of COVID-19. Human-to-human transmission is mediated by the transport of virus-laden respiratory droplets. Here we investigate the problem from a fluid mechanics perspective by conducting numerical simulations to quantify the fate of respiratory droplets in a warm humid coughing puff under different ambient conditions. We reveal a non-intuitive regime with considerable growth of respiratory droplets, dominated by a super-saturated vapour field, preferentially occurring in cold and humid environments. We further propose a theoretical model that accurately predicts the condition for droplet growth. Our work should inform socializing policies and ventilation strategies for controlling indoor ambient conditions to mitigate dispersion of droplets from asymptomatic individuals.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.30.20222877", + "rel_abs": "BackgroundQuantifying occupational risk factors for SARS-CoV-2 infection among healthcare workers can inform efforts to improve healthcare worker and patient safety and reduce transmission. This study aimed to quantify demographic, occupational, and community risk factors for SARS-CoV-2 seropositivity among healthcare workers in a large metropolitan healthcare system.\n\nMethodsWe analyzed data from a cross-sectional survey conducted from April through June of 2020 linking risk factors for occupational and community exposure to COVID-19 with SARS-CoV-2 seropositivity. A multivariable logistic regression model was fit to quantify risk factors for infection. Participants were employees and medical staff members who elected to participate in SARS-CoV-2 serology testing offered to all healthcare workers as part of a quality initiative, and who completed a survey on exposure to COVID-19 and use of personal protective equipment. Exposures of interest included known demographic risk factors for COVID-19, residential zip code incidence of COVID-19, occupational exposure to PCR test-positive healthcare workers or patients, and use of personal protective equipment. The primary outcome of interest was SARS-CoV-2 seropositivity.\n\nResultsSARS-CoV-2 seropositivity was estimated to be 5.7% (95% CI: 5.2%-6.1%) among 10,275 healthcare workers. Community contact with a person known or suspected to have COVID-19 (aOR=1.9, 95% CI:1.4-2.5) and zip code level COVID-19 incidence (aOR: 1.4, 95% CI: 1.0-2.0) increased the odds of infection. Black individuals were at high risk (aOR=2.0, 95% CI:1.6-2.4). Overall, occupational risk factors accounted for 27% (95% CI: 25%-30%) of the risk among healthcare workers and included contact with a PCR test-positive healthcare worker (aOR=1.2, 95% CI:1.0-1.6).\n\nConclusionsCommunity risk factors, including contact with a COVID-19 positive individual and residential COVID-19 incidence, are more strongly associated with SARS-CoV-2 seropositivity among healthcare workers than exposure in the workplace.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Chong Shen Ng", - "author_inst": "University of Twente" + "author_name": "Julia M Baker", + "author_inst": "Rollins School of Public Health, Emory University" }, { - "author_name": "Kai Leong Chong", - "author_inst": "University of Twente" + "author_name": "Kristin N Nelson", + "author_inst": "Rollins School of Public Health, Emory University" }, { - "author_name": "Rui Yang", - "author_inst": "University of Twente" + "author_name": "Elizabeth Overton", + "author_inst": "Emory Healthcare" }, { - "author_name": "Mogeng Li", - "author_inst": "University of Twente" + "author_name": "Benjamin A Lopman", + "author_inst": "Rollins School of Public Health, Emory University" }, { - "author_name": "Roberto Verzicco", - "author_inst": "University of Rome 'Tor Vergata'" + "author_name": "Timothy L Lash", + "author_inst": "Rollins School of Public Health, Emory University" }, { - "author_name": "Detlef Lohse", - "author_inst": "University of Twente" + "author_name": "Mark Photakis", + "author_inst": "Emory Healthcare" + }, + { + "author_name": "Jesse T Jacob", + "author_inst": "Emory University School of Medicine, Emory University" + }, + { + "author_name": "John Roback", + "author_inst": "Emory University School of Medicine, Emory University" + }, + { + "author_name": "Scott K Fridkin", + "author_inst": "Emory University School of Medicine, Emory University" + }, + { + "author_name": "James P Steinberg", + "author_inst": "Emory University School of Medicine, Emory University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1121688,119 +1121314,55 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.11.01.363812", - "rel_title": "Structural basis for repurpose and design of nucleoside drugs for treating COVID-19", + "rel_doi": "10.1101/2020.11.02.364497", + "rel_title": "The SARS-CoV-2 RNA interactome", "rel_date": "2020-11-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.01.363812", - "rel_abs": "SARS-CoV-2 has caused a global pandemic of COVID-19 that urgently needs an effective treatment. Nucleoside analog drugs including favipiravir have been repurposed for COVID-19 despite of unclear mechanism of their inhibition of the viral RNA polymerase (RdRp). Here we report the cryo-EM structures of the viral RdRp in complex with favipiravir and two other nucleoside inhibitor drugs ribavirin and penciclovir. Ribavirin and the ribosylated form of favipiravir share a similar ribose scaffold that is distinct from penciclovir. However, the structures reveal that all three inhibitors are covalently linked to the primer strand in a monophosphate form despite the different chemical scaffolds between favipiravir and penciclovir. Surprisingly, the base moieties of these inhibitors can form mismatched pairs with the template strand. Moreover, in view of the clinical disadvantages of remdesivir mainly associated with its prodrug form, we designed several orally-available remdesivir parent nucleoside derivatives, including VV16 that showed 5-fold more potent than remdesivir in inhibition of viral replication. Together, these results demonstrate an unexpected promiscuity of the viral RNA polymerase and provide a basis for repurpose and design of nucleotide analog drugs for COVID-19.\n\nOne Sentence SummaryCryo-EM structures of the RNA polymerase of SARS-CoV-2 reveals the basis for repurposing of old nucleotide drugs to treat COVID-19.", - "rel_num_authors": 25, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.02.364497", + "rel_abs": "SARS-CoV-2 is an RNA virus whose success as a pathogen relies on its ability to repurpose host RNA-binding proteins (RBPs) to form its own RNA interactome. Here, we developed and applied a robust ribonucleoprotein capture protocol to uncover the SARS-CoV-2 RNA interactome. We report 109 host factors that directly bind to SARS-CoV-2 RNAs including general antiviral factors such as ZC3HAV1, TRIM25, and PARP12. Applying RNP capture on another coronavirus HCoV-OC43 revealed evolutionarily conserved interactions between viral RNAs and host proteins. Network and transcriptome analyses delineated antiviral RBPs stimulated by JAK-STAT signaling and proviral RBPs responsible for hijacking multiple steps of the mRNA life cycle. By knockdown experiments, we further found that these viral-RNA-interacting RBPs act against or in favor of SARS-CoV-2. Overall, this study provides a comprehensive list of RBPs regulating coronaviral replication and opens new avenues for therapeutic interventions.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Wanchao Yin", - "author_inst": "Shanghai Institute of Materia Medica" - }, - { - "author_name": "Xiaodong Luan", - "author_inst": "School of Medicine, Tsinghua University, Haidian District, Beijing, China" - }, - { - "author_name": "Zhihai Li", - "author_inst": "The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China" - }, - { - "author_name": "Yuanchao Xie", - "author_inst": "The CAS Key Laboratory of Receptor Research, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China" - }, - { - "author_name": "Ziwei Zhou", - "author_inst": "Shanghai Institute of Materia Medica" - }, - { - "author_name": "Jia Liu", - "author_inst": "Shanghai Institute of Materia Medica" - }, - { - "author_name": "Minqi Gao", - "author_inst": "WuxiBiortus Biosciences Co. Ltd" - }, - { - "author_name": "Xiaoxi Wang", - "author_inst": "Shanghai Institute of Materia Medica Chinese Academy of Sciences" - }, - { - "author_name": "Fulai Zhou", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "Qingxia Wang", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" - }, - { - "author_name": "Qingxing Wang", - "author_inst": "Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" - }, - { - "author_name": "Dandan Shen", - "author_inst": "Zhejiang University School of Medicine" - }, - { - "author_name": "Yan Zhang", - "author_inst": "Zhejiang University School of Medicine" - }, - { - "author_name": "Guanghui Tian", - "author_inst": "Vigonvita Life Science Co., Ltd." + "author_name": "Sungyul Lee", + "author_inst": "Institute for Basic Science / Seoul National University" }, { - "author_name": "Haji A. Aisa", - "author_inst": "Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences" - }, - { - "author_name": "Tianwen Hu", - "author_inst": "Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences" - }, - { - "author_name": "Daibao Wei", - "author_inst": "Xinjiang Technical Institute of Physics and Chemistry, Chinese Academy of Sciences" - }, - { - "author_name": "Yi Jiang", - "author_inst": "Shanghai Institute of Materia Medica Chinese Academy of Sciences" + "author_name": "Young-suk Lee", + "author_inst": "Institute for Basic Science / Seoul National University" }, { - "author_name": "Gengfu Xiao", - "author_inst": "Chinese Academy of Sciences" + "author_name": "Yeon Choi", + "author_inst": "Institute for Basic Science / Seoul National University" }, { - "author_name": "Hualiang Jiang", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Ahyeon Son", + "author_inst": "Institute for Basic Science / Seoul National University" }, { - "author_name": "Leike Zhang", - "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" + "author_name": "Youngran Park", + "author_inst": "Institute for Basic Science / Seoul National University" }, { - "author_name": "Xuekui Yu", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Kyung-Min Lee", + "author_inst": "International Vaccine Institute" }, { - "author_name": "Jingshan Shen", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "Jeesoo Kim", + "author_inst": "Institute for Basic Science / Seoul National University" }, { - "author_name": "Shuyang Zhang", - "author_inst": "Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College and Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Beijin" + "author_name": "Jong-Seo Kim", + "author_inst": "Institute for Basic Science / Seoul National University" }, { - "author_name": "H. Eric Xu", - "author_inst": "Shanghai Institute of Materia Medica, Chinese Academy of Sciences" + "author_name": "V. Narry Kim", + "author_inst": "Institute for Basic Science / Seoul National University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.11.02.365015", @@ -1123350,23 +1122912,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.11.01.363788", - "rel_title": "Discovery of five HIV nucleoside analog reverse-transcriptase inhibitors (NRTIs) as potent inhibitors against the RNA-dependent RNA polymerase (RdRp) of SARS-CoV and 2019-nCoV", - "rel_date": "2020-11-01", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.11.01.363788", - "rel_abs": "The outbreak of SARS in 2002-2003 caused by SARS-CoV, and the pandemic of COVID-19 in 2020 caused by 2019-nCoV (SARS-CoV-2), have threatened human health globally and raised the urgency to develop effective antivirals against the viruses. In this study, we expressed and purified the RNA-dependent RNA polymerase (RdRp) nsp12 of SARS-CoV and developed a primer extension assay for the evaluation of nsp12 activity. We found that nsp12 could efficiently extend single-stranded RNA, while having low activity towards double-stranded RNA. Nsp12 required a catalytic metal (Mg2+ or Mn2+) for polymerase activity and the activity was also K+-dependent, while Na+ promoted pyrophosphorylation, the reverse process of polymerization. To identify antivirals against nsp12, a competitive assay was developed containing 4 natural rNTPs and a nucleotide analog, and the inhibitory effects of 24 FDA-approved nucleotide analogs were evaluated in their corresponding active triphosphate forms. Ten of the analogs, including 2 HIV NRTIs, could inhibit the RNA extension of nsp12 by more than 40%. The 10 hits were verified which showed dose-dependent inhibition. In addition, the 24 nucleotide analogs were screened on SARS-CoV primase nsp8 which revealed stavudine and remdesivir were specific inhibitors to nsp12. Furthermore, the 2 HIV NRTIs were evaluated on 2019-nCoV nsp12 which showed inhibition as well. Then we expanded the evaluation to all 8 FDA-approved HIV NRTIs and discovered 5 of them, tenofovir, stavudine, abacavir, zidovudine and zalcitabine, could inhibit the RNA extension by nsp12 of SARS-CoV and 2019-nCoV. In conclusion, 5 FDA-approved HIV NRTIs inhibited the RNA extension by nsp12 and were promising candidates for the treatment of SARS and COVID-19.", - "rel_num_authors": 1, + "rel_doi": "10.1101/2020.10.26.20220160", + "rel_title": "Features of C-reactive protein in COVID-19 patients with different ages, clinical types and outcomes: a cohort study", + "rel_date": "2020-10-31", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.26.20220160", + "rel_abs": "BackgroundTo characterize C-reactive protein (CRP) changes features from patients with coronavirus disease 2019 (COVID-19) and to quantify the correlation between CRP value and clinical classification.\n\nMethodsThis was a bidirectional observational cohort study. All laboratory confirmed COVID-19 patients hospitalized in Xiangyang No.1 Peoples Hospital were included. Patients general information, clinical type, CRP value and outcome were collected. Patients were grouped according to the age, clinical type and outcome, and their CRP were compared. The CRP value, age gender, and clinical type were used to build a categorical regression model to investigate the association between CRP and clinical type.\n\nResultsThe 131 patients aged 50.13{+/-}17.13 years old. There were 4 mild, 88 moderate, 21 severe and 18 critical cases. Statistical significance of CRP median exists between different clinical types and ages. There were 10 deaths and 121 cases have been discharged. The CRP in death group dramatically increased continuously until died, while increased firstly and decreased later in the survivor and survivor in critical type. The categorical regression model also showed that CRP and age had significant coefficient. During the first 15 days from symptom onset, the maximum of CRP ranged between 0.47-53.37 mg/L were related to mild combined with moderate type, ranged 53.84-107.08 mg/L were related to severe type, and 107.42-150.00 mg/L were related to the critical type.\n\nConclusionsCRP showed different distribution feature and existed differences in various ages, clinical types and outcomes of COVID-19 patients. The features corresponded with disease progression.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jialei Sun", - "author_inst": "Global Health Drug Discovery Institute" + "author_name": "Gaojing Qu", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, Hubei, China" + }, + { + "author_name": "Guoxin Huang", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, Hubei, China" + }, + { + "author_name": "Meiling Zhang", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, Hubei, China" + }, + { + "author_name": "Hui Yu", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, Hubei, China" + }, + { + "author_name": "Xiaoming Song", + "author_inst": "Department of Equipment Division, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, China" + }, + { + "author_name": "Haoming Zhu", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, Hubei, China" + }, + { + "author_name": "Lei Chen", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, Hubei, China" + }, + { + "author_name": "Yunfu Wang", + "author_inst": "Department of Neurology, Taihe Hospital, Hubei University of Medicine, Shiyan, Hubei 442000 China" + }, + { + "author_name": "Bin Pei", + "author_inst": "Center of Evidence-Based Medicine, Xiangyang No.1 People's Hospital, Hubei University of Medicine, Xiangyang 441000, Hubei, China" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.27.20220830", @@ -1125104,27 +1124698,27 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.10.30.352914", - "rel_title": "Evidence for adaptive evolution in the receptor-binding domain of seasonal coronaviruses", - "rel_date": "2020-10-30", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.30.352914", - "rel_abs": "Seasonal coronaviruses (OC43, 229E, NL63 and HKU1) are endemic to the human population, regularly infecting and reinfecting humans while typically causing asymptomatic to mild respiratory infections. It is not known to what extent reinfection by these viruses is due to waning immune memory or antigenic drift of the viruses. Here, we address the influence of antigenic drift on immune evasion of seasonal coronaviruses. We provide evidence that at least two of these viruses, OC43 and 229E, are undergoing adaptive evolution in regions of the viral spike protein that are exposed to human humoral immunity. This suggests that reinfection may be due, in part, to positively-selected genetic changes in these viruses that enable them to escape recognition by the immune system. It is possible that, as with seasonal influenza, these adaptive changes in antigenic regions of the virus would necessitate continual reformulation of a vaccine made against them.", + "rel_doi": "10.1101/2020.10.27.20221085", + "rel_title": "How Emergency Care Congestion Increases Covid-19 Mortality: Evidence from Lombardy, Italy", + "rel_date": "2020-10-29", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20221085", + "rel_abs": "BackgroundThe Covid-19 pandemic has caused generous and well-developed healthcare systems to collapse. This paper quantifies how much system congestion may have increased mortality rates, using distance to the ICU as a proxy for access to emergency care.\n\nMethodsWe match daily death registry data for almost 1,500 municipalities in Lombardy, Italy, to data on geographical location of all ICU beds in the region. We then analyze how system congestion increases mortality in municipalities that are far from the ICU through a differences-in-differences regression model.\n\nFindingsWe find that Covid-19 mortality is up to 60% higher in the average municipality - which is 15 minutes driving away from the closest ICU - than in a municipality with an ICU in town. This difference is larger in areas and in days characterized by an abnormal number of calls to the emergency line.\n\nInterpretationWe interpret these results as suggesting that a sudden surge of critical patients may have congested the healthcare system, forcing emergency medical services to prioritize patients in the most proximate communities in order to maximize the number of lives saved. Through some back-of-the-envelope calculations, we estimate that Lombardys death toll from the first Covid-19 outbreak could have been 25% lower had all municipalities had ready access to the ICU. Drawing a lesson from Lombardys tale, governments should strengthen the emergency care response and palliate geographical inequalities to ensure that everyone in need can receive critical care on time during new outbreaks.\n\nFundingNo funding.", "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Kathryn Kistler", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Gabriele Ciminelli", + "author_inst": "Asia School of Business in collaboration with MIT Sloan Management" }, { - "author_name": "Trevor Bedford", - "author_inst": "Fred Hutchinson Cancer Research Center" + "author_name": "Silvia Garcia-Mandico", + "author_inst": "Organisation for Economic Co-operation and Development" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "evolutionary biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "health policy" }, { "rel_doi": "10.1101/2020.10.28.20221176", @@ -1127898,195 +1127492,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.27.20219436", - "rel_title": "Childhood asthma outcomes during the COVID-19 pandemic: Findings from the PeARL multi-national cohort.", + "rel_doi": "10.1101/2020.10.27.20219618", + "rel_title": "Modelling trachoma post 2020: Opportunities for mitigating the impact of COVID-19 and accelerating progress towards elimination.", "rel_date": "2020-10-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20219436", - "rel_abs": "ImportanceImportance: The interplay between COVID-19 pandemic and asthma in children is still unclear.\n\nObjectiveWe evaluated the impact of COVID-19 pandemic on childhood asthma outcomes.\n\nDesignThe PeARL multinational cohort included children with asthma and non-asthmatic controls recruited during the COVID-19 pandemic and compared current disease activity with data available from the previous year.\n\nSettingPediatric outpatient clinics.\n\nParticipantsThe study included 1,054 children with asthma and 505 non-asthmatic controls, aged between 4-18 years, from 25 pediatric departments, from 15 countries globally.\n\nExposuresCOVID-19 pandemic first wave, starting from the date of the first fatality in the respective country.\n\nMain outcomes and measuresWe assessed the pandemics impact on the frequency of respiratory infections, emergency presentations and hospital admissions in asthmatic versus non-asthmatic participants, controlling for confounding factors including the pandemics duration and the frequency of such acute events during 2019. Using paired analyses, we evaluated the impact of the pandemic on the annualized frequency of asthma attacks and the previously mentioned acute events, asthma control, and pulmonary function in children with asthma, compared to their baseline disease activity, during the preceding year.\n\nResultsDuring the pandemic, children with asthma experienced fewer upper respiratory tract infections, episodes of pyrexia, emergency visits, hospital admissions, asthma attacks and hospitalizations due to asthma, in comparison to the preceding year. Sixty-six percent of asthmatic children had improved asthma control while in 33% the improvement exceeded the minimally clinically important difference. Pre-bronchodilatation FEV1 and peak expiratory flow rate were also improved during the pandemic.\n\nWhen compared to non-asthmatic controls, children with asthma were not found to be at increased risk of LRTIs, episodes of pyrexia, emergency visits or hospitalizations during the pandemic. However, an increased risk of URTIs emerged.\n\nConclusions and relevanceChildhood asthma outcomes, including control, were improved during the first wave of the COVID-19 pandemic, probably because of reduced exposure to asthma triggers and increased treatment adherence. The decreased frequency of acute episodes does not support the notion that childhood asthma may be a risk factor for COVID-19. Furthermore, the potential for improving childhood asthma outcomes through environmental control becomes apparent.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat was the impact of COVID-19 pandemic on childhood asthma outcomes?\n\nFindingsDuring the first wave of the pandemic, children with asthma have experienced improved outcomes, as evidenced by fewer asthma attachks, hospitalizations, improved scores in validated asthma control measures and improved pulmonary function.\n\nMeaningThis is the first study to show a positive impact of COVID-19 pandemic on childhood asthma activity. This is probably the result of reduced exposure to asthma triggers and increased treatment adherence. The decreased frequency of acute episodes does not support the hypothesis that childhood asthma may be a risk factor for COVID-19.", - "rel_num_authors": 44, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20219618", + "rel_abs": "BackgroundThe COVID-19 pandemic has disrupted planned annual antibiotic mass drug administration (MDA) activities which have formed the cornerstone of the largely successful global efforts to eliminate trachoma as a public health problem.\n\nMethodsUsing a mathematical model we investigate the impact of interruption to MDA in trachoma-endemic settings. We evaluate potential measures to mitigate this impact and consider alternative strategies for accelerating progress in those areas where the trachoma elimination targets may not be achievable otherwise.\n\nResultsWe demonstrate that for districts which were hyperendemic at baseline, or where the trachoma elimination thresholds have not already been achieved after 3 rounds of MDA, the interruption to planned MDA could lead to a delay greater than the duration of interruption. We also show that an additional round of MDA in the year following MDA resumption could effectively mitigate this delay. For districts where probability of elimination under annual MDA was already very low, we demonstrate that more intensive MDA schedules are needed to achieve agreed targets.\n\nConclusionThrough appropriate use of additional MDA, the impact of COVID-19 in terms of delay to reaching trachoma elimination targets can be effectively mitigated. Additionally, more frequent MDA may accelerate progress towards 2030 goals.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Nikolaos G. Papadopoulos", - "author_inst": "Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester, UK. Allergy Department, 2nd " - }, - { - "author_name": "Alexander G. Mathioudakis", - "author_inst": "Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester, UK. North West Lung Centre, W" - }, - { - "author_name": "Adnan Custovic", - "author_inst": "Imperial College London, London, UK." - }, - { - "author_name": "Antoine Deschildre", - "author_inst": "Univ. Lille, INSERM Unit 1019, CNRS UMR 8204, Institut Pasteur de Lille, Center for infection and immunity of Lille, 59019 Lille cedex, France." - }, - { - "author_name": "Wanda Phipatanakul", - "author_inst": "Department of Allergy and Immunology, Boston Children Hospital, Boston, Massachusetts, USA." - }, - { - "author_name": "Gary Wong", - "author_inst": "Department of Pediatrics, Faculty of Medicine, The Chinese University of Hong Kong, Sha Tin, Hong Kong." - }, - { - "author_name": "Paraskevi Xepapadaki", - "author_inst": "Allergy Department, 2nd Paediatric Clinic, National and Kapodistrian University of Athens, Athens, Greece" - }, - { - "author_name": "Rola Abou-Taam", - "author_inst": "Pediatric Pulmonology and Allergy Department Hospital Necker-Enfants Malades, Paris, France." - }, - { - "author_name": "Ioana Agache", - "author_inst": "Allergy & Clinical Immunology, Transylvania University, Brasov, Romania." - }, - { - "author_name": "Jose A. Castro-Rodriguez", - "author_inst": "Department of Pediatric Pulmonology, School of Medicine, Pontificia Universidad Catolica de Chile, Santiago, Chile." - }, - { - "author_name": "Zhimin Chen", - "author_inst": "Department of pulmonology, the children hospital, Zhejiang University school of medicine, national clinical research center for child health, Hangzhou, Zhejiang" - }, - { - "author_name": "Pierrick Cros", - "author_inst": "Department of Pediatrics, University Hospital Morvan, Brest, France." - }, - { - "author_name": "Jean-Christop Dubus", - "author_inst": "Centre de Ressources et de Competences pour la Mucoviscidose Pneumo-Allergologie, Ventilation, Maladies Respiratoires Rares de l Enfant CHU Timone-Enfants, Mars" - }, - { - "author_name": "Zeinab Awad El-Sayed", - "author_inst": "Pediatric Allergy and Immunology Unit, Children's Hospital, Ain Shams University, Cairo, Egypt." - }, - { - "author_name": "Rasha El-Owaidy", - "author_inst": "Pediatric Allergy and Immunology Unit, Children's Hospital, Ain Shams University, Cairo, Egypt." - }, - { - "author_name": "Wojciech Feleszko", - "author_inst": "Department of Pediatric Pneumonology and Allergy, The Medical University of Warsaw, Warsaw, Poland." - }, - { - "author_name": "Vincenzo Fierro", - "author_inst": "Allergy Department, Bambino Gesu Children Hospital IRCCS, Roma, Italy." - }, - { - "author_name": "Alessandro Fiocchi", - "author_inst": "Allergy Department, Bambino Gesu Children Hospital IRCCS, Roma, Italy." - }, - { - "author_name": "Luis Garcia-Marcos", - "author_inst": "Pediatric Respiratory and Allergy Units, Virgen de la Arrixaca Children University Clinical Hospital, University of Murcia, Murcia, Spain. Institute for Biomed" - }, - { - "author_name": "Anne Goh", - "author_inst": "Department of Internal Medicine, Rush Medical College, Chicago." - }, - { - "author_name": "Elham M. Hossny", - "author_inst": "Pediatric Allergy and Immunology Unit, Children's Hospital, Ain Shams University, Cairo, Egypt" - }, - { - "author_name": "Yunuen R. Huerta Villalobos", - "author_inst": "Hospital General Regional 1 Dr. Carlos Mac Gregor Sanchez Navarro IMSS, Mexico." - }, - { - "author_name": "Tuomas Jartti", - "author_inst": "Department of Pediatrics and Adolescent Medicine, Oulu University Hospital and University of Oulu, Oulu, Finland." - }, - { - "author_name": "Pascal Le Roux", - "author_inst": "Department of pediatrics, Groupe hospitalier Le Havre, France." - }, - { - "author_name": "Julia Levina", - "author_inst": "Pediatric and Child Health Research Institute of the Central Clinical Hospital of the Russian Academy of Sciences, Russia." - }, - { - "author_name": "Aida Ines Lopez Garcia", - "author_inst": "Allergy and Clinical Immunology Service of the University Hospital of Puebla, Mexico." - }, - { - "author_name": "Angel Mazon Ramos", - "author_inst": "Pediatric Pulmonology & Allergy Unit Children Hospital la Fe, Valencia, Spain." - }, - { - "author_name": "Mario Morais Almeida", - "author_inst": "Allergy Center, CUF Descobertas Hospital, Lisbon, Portugal." - }, - { - "author_name": "Clare Murray", - "author_inst": "Division of Infection, Immunity and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester, UK." - }, - { - "author_name": "Karthik Nagaraju", - "author_inst": "VN Allergy & Asthma Research Centre, Chennai, Tamilnadu, India." - }, - { - "author_name": "Major K. Nagaraju", - "author_inst": "Professor & Head, Department of Allergy & Clinical Immunology, Saveetha Medical College, Chennai, India." - }, - { - "author_name": "Elsy Maureen Navarrete Rodriguez", - "author_inst": "Pediatric Allergy and Clinical Immunology Service, Hospital Infantil, til de Mexico Federico Gomez, Mexico." - }, - { - "author_name": "Leyla Namazova-Baranova", - "author_inst": "Pediatric and Child Health Research Institute of the Central Clinical Hospital of the Russian Academy of Sciences, Russia. Pirogov Russian National Research Med" - }, - { - "author_name": "Antonio Nieto Garcia", - "author_inst": "Pediatric Pulmonology & Allergy Unit Children Hospital la Fe, Valencia, Spain." - }, - { - "author_name": "Cesar Fireth Pozo Beltran", - "author_inst": "Teaching and Research Department and Paediatric Allergy department, Hospital with Specialties Juan Maria de Salvatierra, La Paz, Baja California Sur Mexico. Al" + "author_name": "Anna Borlase", + "author_inst": "University of Oxford" }, { - "author_name": "Thanaporn Ratchataswan", - "author_inst": "Department of Allergy and Immunology, Boston Children Hospital, Boston, Massachusetts, USA." + "author_name": "Seth Blumberg", + "author_inst": "Francis Proctor Foundation, UCSF" }, { - "author_name": "Daniela Rivero Yeverino", - "author_inst": "Allergy and Clinical Immunology Department, Hospital Universitario de Puebla, Puebla, Mexico." + "author_name": "E Kelly Callahan", + "author_inst": "Trachoma Control Program, The Carter Center, Atlanta, Georgia, USA." }, { - "author_name": "Erendira Rodriguez Zagal", - "author_inst": "Hospital General Regional 1 Dr. Carlos Mac Gregor Sanchez Navarro IMSS, Mexico." + "author_name": "Michael S. Deiner", + "author_inst": "University of California, San Francisco" }, { - "author_name": "Cyril E Schweitzer", - "author_inst": "CHRU de Nancy, Hopital d Enfants, Rue du Morvan, 54511 Vandoeuvre, France." + "author_name": "Scott D Nash", + "author_inst": "Trachoma Control Program, The Carter Center, Atlanta, Georgia, USA." }, { - "author_name": "Marleena Tulkki", - "author_inst": "Department of Pediatrics and Adolescent Medicine, Turku University Hospital and University of Turku, Turku, Finland." + "author_name": "Travis C Porco", + "author_inst": "Francis I Proctor Foundation, UCSF, USA." }, { - "author_name": "Katarzyna Wasilczuk", - "author_inst": "Department of Pediatric Pneumonology and Allergy, The Medical University of Warsaw, Warsaw, Poland" + "author_name": "Anthony W Solomon", + "author_inst": "Department of Control of Neglected Tropical Diseases, World Health Organisation, Geneva, Switzerland" }, { - "author_name": "Dan XU", - "author_inst": "Department of pulmonology, the children hospital, Zhejiang University school of medicine, national clinical research center for child health, Hangzhou, Zhejiang" + "author_name": "Thomas M Lietman", + "author_inst": "Francis I Proctor Foundation, UCSF, USA." }, { - "author_name": "- PeARL Collaborators", - "author_inst": "" + "author_name": "Joaquin M Prada", + "author_inst": "Faculty of Health and Medical Sciences, University of Surrey, UK" }, { - "author_name": "- PeARL Think Tank", - "author_inst": "" + "author_name": "T Deirdre Hollingsworth", + "author_inst": "University of Oxford" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.10.27.20220558", @@ -1129372,61 +1128830,29 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.10.24.20218727", - "rel_title": "DNA methylation and gene expression pattern of ACE2 and TMPRSS2 genes in saliva samples of patients with SARS-CoV-2 infection", + "rel_doi": "10.1101/2020.10.23.20218511", + "rel_title": "Large-scale population analysis of SARS-CoV2 whole genome sequences reveals host-mediated viral evolution with emergence of mutations in the viral Spike protein associated with elevated mortality rates", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.24.20218727", - "rel_abs": "COVID-19 caused by SARS-CoV-2 became a pandemic affecting the health and economy of the world. Although it was known that this virus uses ACE2 protein along with TMPRSS2 to enter the host cell, the methylation pattern and gene expression of ACE2 and TMPRSS2 genes are not explored in saliva samples of patients infected with COVID-19. The study aimed to quantify promoter methylation of ACE2 and TMPRSS2 along with its mRNA expression in saliva samples of COVID-19 patients in order to understand the regulatory mechanism of these genes in SARS-CoV-2 infection. Saliva samples were collected from thirty male patients with SARS-CoV-2 infection and thirty age-matched healthy control male subjects. Q MS PCR and qRT PCR was performed to quantify the promoter DNA methylation and mRNA expression of ACE2 and TMPRSS2 respectively. Our study didnt find any significant difference between methylation and expression of these two genes in cases compared to control subjects. However there was significant positive correlation between DNA methylation of ACE2 and its gene expression. Among cases, the sample collected [≥]7 days after appearance of symptoms showed higher amount of methylation in both ACE2 and TMPRSS2 genes when compared to sample collected before 7 days. In conclusion, we found that ACE2 and TMPRSS2 methylation plays a role in COVID-19.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.23.20218511", + "rel_abs": "BackgroundWe aimed to further characterize and analyze in depth intra-host variation and founder variants of SARS-CoV-2 worldwide up until August 2020, by examining in excess of 94,000 SARS-CoV-2 viral sequences in order to understand SARS-CoV-2 variant evolution, how these variants arose and identify any increased mortality associated with these variants.\n\nMethods and FindingsWe combined worldwide sequencing data from GISAID and Sequence Read Archive (SRA) repositories and discovered SARS-CoV-2 hypermutation occurring in less than 2% of COVID19 patients, likely caused by host mechanisms involved APOBEC3G complexes and intra-host microdiversity. Most of this intra-host variation occurring in SARS-CoV-2 are predicted to change viral proteins with defined variant signatures, demonstrating that SARS-CoV-2 can be actively shaped by the host immune system to varying degrees. At the global population level, several SARS-CoV-2 proteins such as Nsp2, 3C-like proteinase, ORF3a and ORF8 are under active evolution, as evidenced by their increased {pi}N/ {pi}S ratios per geographical region. Importantly, two emergent variants: V1176F in co-occurrence with D614G mutation in the viral Spike protein, and S477N, located in the Receptor Binding Domain (RBD) of the Spike protein, are associated with high fatality rates and are increasingly spreading throughout the world. The S477N variant arose quickly in Australia and experimental data support that this variant increases Spike protein fitness and its binding to ACE2.\n\nConclusionsSARS-CoV-2 is evolving non-randomly, and human hosts shape emergent variants with positive fitness that can easily spread into the population. We propose that V1776F and S477N variants occurring in the Spike protein are two novel mutations occurring in SARS-CoV-2 and may pose significant public health concerns in the future.\n\nAuthor SummaryWe have developed an efficient bioinformatics pipeline that has allowed us obtain the most complete picture to date of how the SARS-CoV-2 virus has changed during the last eight month global pandemic and will continue to change in the near future. We characterized the importance of the host immune response in shaping viral variants at different degrees, evidenced by hypermutation responses on SARS-CoV-2 in less than 2% of infections and positive selection of several viral proteins by geographical region. We underscore how human hosts are shaping emergent variants with positive fitness that can easily spread into the population, evidenced by variants V1176F and S477N, located in the stalk and receptor binding domains of the Spike protein, respectively. Variant V1176 is associated with increased mortality rates in Brazil and variant S477N is associated with increased mortality rates over the world. In addition, it has been experimentally demonstrated that S477N variant increase fitness of Spike protein and its binding with ACE2, thus predicting to increase virulence of SARS-CoV-2. This limits the concept of herd immunity proposals and re-emphasize the need to limit the spread of the virus to avoid emergence of more virulent forms of SARS-CoV-2 that can spread worldwide.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Pratibha Misra", - "author_inst": "AFMC, Pune" - }, - { - "author_name": "Bhasker Mukherjee", - "author_inst": "AFMC, Pune" - }, - { - "author_name": "Rakhi Negi", - "author_inst": "AFMC, Pune" - }, - { - "author_name": "Vikas Marwah", - "author_inst": "Army Institute of Cardio thoracic sciences, Pune" - }, - { - "author_name": "Arijit Kumar Ghosh", - "author_inst": "Army Institute of Cardio thoracic sciences, Pune" - }, - { - "author_name": "Prashant Jindamwar", - "author_inst": "Army Institute of Cardio thoracic sciences, Pune" - }, - { - "author_name": "Mukesh U Singh", - "author_inst": "AFMC, Pune" - }, - { - "author_name": "Yaongamphi Vashum", - "author_inst": "AFMC, Pune" - }, - { - "author_name": "Syamraj R", - "author_inst": "AFMC, Pune" + "author_name": "Carlos Farkas", + "author_inst": "Research Institute in Oncology and Hematology (RIOH), CancerCare Manitoba, Winnipeg, MB, Canada" }, { - "author_name": "Bala Chandra G", - "author_inst": "AFMC, Pune" + "author_name": "Andy Mella", + "author_inst": "Departamento de Fisica, Facultad de Ciencias Fisicas y Matematicas, Universidad de Chile, Blanco Encalada 2008, Santiago, Casilla 487-3, Chile" }, { - "author_name": "Sibin M K", - "author_inst": "Armed forces medical college" + "author_name": "Jody J Haigh", + "author_inst": "Research Institute in Oncology and Hematology (RIOH), CancerCare Manitoba, Winnipeg, MB, Canada" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1130922,35 +1130348,99 @@ "category": "otolaryngology" }, { - "rel_doi": "10.1101/2020.10.25.20219212", - "rel_title": "Economic Losses Associated with COVID-19 Deaths in the United States", + "rel_doi": "10.1101/2020.10.25.20219337", + "rel_title": "Efficacy of Convalescent Plasma Therapy compared to Fresh Frozen Plasma in Severely ill COVID-19 Patients: A Pilot Randomized Controlled Trial", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.25.20219212", - "rel_abs": "In addition to the overwhelming health effects of COVID-19, the disease has inflicted unprecedented economic damage. Vast resources have been directed at COVID-19 testing and health care while economic activity has been substantially curtailed due to disruptions resulting from individual choices and government policies. This study estimates the economic loss associated with COVID-19 deaths in the U.S. from February 1, 2020 through July 11, 2020. We use estimates of years of life lost that are based on the age and gender of decedents. Using a value of life year estimate of $66,759, we calculate economic losses of roughly $66 billion. The losses are concentrated in New York and New Jersey, which account for 17.5% of the total losses. Our analysis of per capita losses by state indicates that the highest values are located in the northeastern region of the country, while the values in the western states are relatively low. While economic losses associate with COVID-19 deaths is just one aspect of the pandemic, our estimates can provide context to the value of prevention and mitigation efforts.\n\nJEL codesI12, I18, J17", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.25.20219337", + "rel_abs": "BackgroundThe role of convalescent plasma (COPLA) for the treatment of severely ill Corona Virus Disease-2019 is under investigation. We compared the efficacy and safety of convalescent plasma with fresh frozen plasma (FFP) in severe COVID-19 patients.\n\nMethods and findingsThis was an open-label, single-centre phase II RCT on 29 patients with severe COVID-19 from India. One group received COPLA with standard medical care (SMC) (n=14), and another group received FFP with SMC (n=15). A total of 29 patients were randomized in the two treatment groups. Eleven out of 14 (78.5%) patients remained free of ventilation at day seven in the intervention arm while the proportion was 14 out of 15 (93.3 %) in the control arm (p= 0.258). The median reductions in RR per min at 48-hours in COPLA-group and FFP group were -6.5 and -3 respectively [p=0.004] and at day seven were -14.5 and -10 respectively (p=0.008). The median improvements in percentage O2 saturation at 48-hours were 6.5 and 2 respectively [p=0.001] and at day seven were 10 and 7.5 respectively (p=0.026). In the COPLA-group, the median improvement in PaO2/FiO2 was significantly superior to FFP at 48-hours [41.94 and 231.15, p=0.009], and also at day-7 [5.55 and 77.01 p<0.001]. We did not find significant differences in hospitalization duration between the groups (0.08).\n\nConclusionCOPLA therapy resulted in rapid improvement in respiratory parameters and shortened time to clinical recovery, although no significant reduction in mortality was observed in this pilot trial. We need larger trials to draw conclusive evidence on the use of Convalescent plasma in COVID-19. This trial is registered with ClinicalTrial.gov (identifier: NCT04346446).", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Troy Quast", - "author_inst": "University of South Florida, College of Public Health" + "author_name": "Meenu Bajpai", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" }, { - "author_name": "Ross Andel", - "author_inst": "University of South Florida, School of Aging" + "author_name": "Suresh kumar", + "author_inst": "Maulana Azad Medical College" }, { - "author_name": "Sean Gregory", - "author_inst": "Northern Arizona University, Department of Politics & International Affairs" + "author_name": "Ashish Maheshwari", + "author_inst": "Institute of Liver and Biliary Sciences" }, { - "author_name": "Eric A. Storch", - "author_inst": "Baylor College of Medicine, Menninger Department of Psychiatry & Behavioral Sciences" + "author_name": "Karan Chabra", + "author_inst": "Maulana Azad Medical College" + }, + { + "author_name": "Pratibha Kale", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Amita Gupta", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "ashad Narayanan", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Ekta Gupta", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Nirupama Ttrehanpati", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Chhagan Bihari", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Reshu Agarwal", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Kamini Gupta", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Upendra kumar Gupta", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Ankit Bhardwaj", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Guresh Kumar", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Mojahidul Islam", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Ravinder Singh", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Pushpa Yadav", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "RAKHI MAIWALL", + "author_inst": "INSTITUTE OF LIVER AND BILIARY SCIENCES" + }, + { + "author_name": "Shiv K Sarin", + "author_inst": "Institute of Liver and Biliary Sciences (ILBS)" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.26.20219345", @@ -1132560,97 +1132050,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.27.20220541", - "rel_title": "A Scalable Saliva-based, Extraction-free RT-LAMP Protocol for SARS-Cov-2 Diagnosis", + "rel_doi": "10.1101/2020.10.26.20220244", + "rel_title": "Age-adjusted Charlson comorbidity index score is the best predictor for severe clinical outcome in the hospitalized patients with COVID-19 infection: a result from nationwide database of 5,621 Korean patients", "rel_date": "2020-10-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.27.20220541", - "rel_abs": "I.Scalable, cost-effective screening methods are an essential tool to control SARS-CoV-2 spread. We have developed a straight saliva-based, RNA extraction-free, RT-LAMP test that is comparable to current nasopharyngeal swab RT-PCR tests in both sensitivity and specificity. Using a 2-step readout of fluorescence and melting-point curve analysis, the test is scalable to more than 30,000 tests per day with average turnaround time of less than 3 hours. The test was validated using samples from 244 symptomatic patients, and showed sensitivity of 78.9% (vs. 85.5% for nasopharyngeal swabs RT-PCR) and specificity of 100% (vs. 100% for nasopharyngeal swabs RT-PCR). Our method is therefore accurate, robust, time and cost effective and therefore can be used for screening of SARS-CoV-2.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.26.20220244", + "rel_abs": "Aged population with comorbidities demonstrated high mortality rate and severe clinical outcome in the patients with coronavirus disease 2019 (COVID-19). However, whether age-adjusted Charlson comorbidity index score (CCIS) predict fatal outcomes remains uncertain. This retrospective, nationwide cohort study was performed to evaluate patient mortality and clinical outcome according to CCIS among the hospitalized patients with COVID-19 infection. We included 5,621 patients who had been discharged from isolation or had died from COVID-19 by April 30, 2020. The primary outcome was composites of death, admission to intensive care unit (ICU), use of mechanical ventilator or extracorporeal membrane oxygenation. The secondary outcome was mortality. Multivariate Cox proportional hazard model was used to evaluate CCIS as the independent risk factor for death. Among 5,621 patients, the high CCIS ([≥]3) group showed higher proportion of elderly population and lower plasma hemoglobin and lower lymphocyte and platelet counts. The high CCIS group was an independent risk factor for composite outcome (HR 3.63, 95% CI 2.45-5.37, P < 0.001) and patient mortality (HR 22.96, 95% CI 7.20-73.24, P < 0.001). The nomogram demonstrated that the CCIS was the most potent predictive factor for patient mortality. The predictive nomogram using CCIS for the hospitalized patients with COVID-19 may help clinicians to triage the high-risk population and to concentrate limited resources to manage them.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Paula Asprino", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" - }, - { - "author_name": "Fabiana Bettoni", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" - }, - { - "author_name": "Anamaria Camargo", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" - }, - { - "author_name": "Diego Coelho", - "author_inst": "Mendelics Analise Genomica, Sao Paulo, Brazil" - }, - { - "author_name": "Guilherme Coppini", - "author_inst": "Mendelics Analise Genomica, Sao Paulo, Brazil" - }, - { - "author_name": "Igor Correa", - "author_inst": "Mendelics Analise Genomica, Sao Paulo, Brazil" - }, - { - "author_name": "Erika Freitas", - "author_inst": "Mendelics Analise Genomica, Sao Paulo, Brazil" - }, - { - "author_name": "Lilian Inoue", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" - }, - { - "author_name": "Joao Paulo Kitajima", - "author_inst": "Mendelics Analise Genomica, Sao Paulo, Brazil" - }, - { - "author_name": "Mayra Kuroki", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" - }, - { - "author_name": "Cibele Masotti", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" - }, - { - "author_name": "Tatiana Marques", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" - }, - { - "author_name": "Alice Reis", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" - }, - { - "author_name": "Luiz Fernando Reis", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" + "author_name": "Do Hyoung Kim", + "author_inst": "Kangnam Sacred Heart Hospital" }, { - "author_name": "Bibiana Santos", - "author_inst": "Mendelics Analise Genomica, Sao Paulo, Brazil" + "author_name": "Hayne Cho Park", + "author_inst": "Kangnam Sacred Heart Hospital" }, { - "author_name": "Ernande dos Santos", - "author_inst": "Hospital Sirio-Libanes, Sao Paulo, Brazil" + "author_name": "AJin Cho", + "author_inst": "Kangnam Sacred Heart Hospital" }, { - "author_name": "David Schlesinger", - "author_inst": "Mendelics" + "author_name": "Juhee Kim", + "author_inst": "Kangnam Sacred Heart Hospital" }, { - "author_name": "Cecilia Sena", - "author_inst": "Mendelics Analise Genomica, Sao Paulo, Brazil" + "author_name": "Kyu-sang Yun", + "author_inst": "Kangnam Sacred Heart Hospital" }, { - "author_name": "Talita Spadaccini", - "author_inst": "Mendelics Analise Genomica, Sao Paulo, Brazil" + "author_name": "Jinseog Kim", + "author_inst": "Dongguk University" }, { - "author_name": "Lucas Taniguti", - "author_inst": "Mendelics Analise Genomica, Sao Paulo, Brazil" + "author_name": "Young-Ki Lee", + "author_inst": "Kangnam Sacred Heart Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1134786,27 +1134224,67 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.10.22.20217430", - "rel_title": "Covid-19 and Socioeconomic Factors: Cross-country Evidence", + "rel_doi": "10.1101/2020.10.22.20215749", + "rel_title": "An ultra-sensitive, ultra-fast whole blood monocyte CD169 assay for COVID-19 screening", "rel_date": "2020-10-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.22.20217430", - "rel_abs": "BackgroundCOVID-19 pandemic has affected all countries across the globe in varying intensity resulting in varied numbers for total cases and deaths.\n\nObjectivesThe paper aims to understand if different socioeconomic factors have a role to play in determining the intensity of COVID-19 impact.\n\nMethodsThe study uses a country-wise number of corona cases and deaths and analyse them in a cross-country multivariate regression framework. It uses gross domestic product per capita, average temperature, population density, and median age as independent variables. The study uses testing data as a control variable.\n\nResultsIn absence of the testing variable, higher-income countries have experienced a higher number of COVID cases. The population density, median age, climate do not have significant impact. The countries with higher population density have lower deaths. Each region shows different patterns of correlation between socioeconomic factors and COVID intensity.\n\nConclusionThe majority of the cross-country variation can be attributed to the number of tests done by a country. The countries with high population density would have applied strict lockdowns and proactive testing to curb the deaths. The study essentially refutes claims around corona being a high-income group disease, cold-climate disease, or a disease impacting old-age patients more.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.22.20215749", + "rel_abs": "CoVID-19 is an unprecedented epidemic, globally challenging health systems, societies, and economy. Its diagnosis relies on molecular methods, with drawbacks revealed by current use as mass screening. Monocyte CD169 upregulation has been reported as a marker of viral infections, we evaluated a flow cytometry three-color rapid assay of whole blood monocyte CD169 for CoVID-19 screening.\n\nOutpatients (n=177) with confirmed CoVID-19 infection, comprising 80 early-stage ([≤]14 days after symptom onset), 71 late-stage ([≥]15 days), and 26 asymptomatic patients received whole blood CD169 testing in parallel with SARS-CoV-2 RT-PCR. Upregulation of monocyte CD169 without polymorphonuclear neutrophil CD64 changes was the primary endpoint. Sensitivity was 98% and 100% in early-stage and asymptomatic patients respectively, specificity was 50% and 84%. Rapid whole blood monocyte CD169 evaluation was highly sensitive when compared with RT-PCR, especially in early-stage, asymptomatic patients whose RT-PCR tests were not yet positive.\n\nDiagnostic accuracy, easy finger prick sampling and minimal time-to-result (15-30 minutes) rank whole blood monocyte CD169 upregulation as a potential screening and diagnostic support for CoVID-19. Secondary endpoints were neutrophil CD64 upregulation as a marker of bacterial infections and monocyte HLA-DR downregulation as a surrogate of immune fitness, both assisting with adequate and rapid management of non-CoVID cases.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Vishalkumar J Jani", - "author_inst": "Indian Institute of Public Health Gandhinagar" + "author_name": "Moise Michel", + "author_inst": "Assistance Publique - Hopitaux de Marseille" }, { - "author_name": "Dileep V Mavalankar", - "author_inst": "Indian Institute of Public Health Gandhinagar" + "author_name": "Fabrice Malergue", + "author_inst": "Beckman Coulter, Marseille, France" + }, + { + "author_name": "Ines Ait-Belkacem", + "author_inst": "Beckman Coulter, Marseille, France" + }, + { + "author_name": "Penelope Bourgoin", + "author_inst": "Beckman Coulter, Marseille, France" + }, + { + "author_name": "Pierre-Emmanuel Morange", + "author_inst": "Aix-Marseille University" + }, + { + "author_name": "Isabelle Arnoux", + "author_inst": "C2VN Aix Marseille Univ INSERM, INRAE, APHM Hopitaux Universitaires de Marseille, Hematology unit, Marseille, France" + }, + { + "author_name": "Tewfik Miloud", + "author_inst": "Beckman Coulter, Marseille, France" + }, + { + "author_name": "Matthieu Million", + "author_inst": "IHU Mediterranee Infection" + }, + { + "author_name": "Herve Tissot-Dupont", + "author_inst": "IHU Mediterranee Infection" + }, + { + "author_name": "Jean-Louis Mege", + "author_inst": "Aix-Marseille Univ, IRD, APHM, MEPHI, Marseille, France" + }, + { + "author_name": "Jean-Marc Busnel", + "author_inst": "Beckman Coulter, Marseille, France" + }, + { + "author_name": "Joana Vitte", + "author_inst": "Aix-Marseille University" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.22.20217695", @@ -1136160,39 +1135638,67 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.10.21.20217406", - "rel_title": "Social and Psychiatric Effects of COVID-19 Pandemic and Distance Learning On High School Students: A Cross-Sectional Web-Based Survey Comparing Turkey and Denmark", + "rel_doi": "10.1101/2020.10.21.20217380", + "rel_title": "Development of a predictive risk model for severe COVID-19 disease using population-based administrative data", "rel_date": "2020-10-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20217406", - "rel_abs": "ObjectiveIn this study we investigated the socio-psychological effects of both the pandemic and distance learning on high school students in Turkey and Denmark. We aimed to assess whether there were any differences a) between students attending public or private schools in Turkey and b) between two countries having different approaches to pandemic and considerable socio-cultural and economic differences.\n\nMethodsWe conducted a web-based questionnaire study in a cross-sectional design using Survey Monkey platform and sent out via social media to high school students from Turkey and Denmark. The survey collected socio-demographic data, several variables associated with pandemic and distance education and their effects on social life and psychological status. Additionally, emotional status was assessed using positive (PA) and negative affects (NA) schedule (PANAS). The survey ran from July 3 and August 31 2020.\n\nResultsWe studied 565 (mean age: 16.5 {+/-} 1.0) Turkish and 92 (mean age:17.7 {+/-} 1.0) Danish students, of whom the majority were female adolescents (63% vs 76%). Students educated in public (47.6%) and private high schools (52.4%) were nearly similar in number in Turkish group, whereas in the Danish sample almost all students were from public school (98.9%). Turkish students were significantly more likely to be compliant with the pandemic related restrictions. Besides that, there were significant socio-economic disparities between Turkish and Danish students and also within Turkey between public and private school students. Turkish online education system was significantly less adequate and satisfactory compared to the Danish system. These were even worse for those who were attending public schools in Turkey. Regardless of the socio-economic differences, the majority of the students in both countries has been negatively affected by the pandemic and related restrictions and had a negative opinion about distance education. This was also true for the PANAS scores. The total scores of PANAS were similar between Turkish and Danish students (PA: 27.0 {+/-} 7.6 versus 25.8 {+/-} 5.6; NA: 24.8{+/-} 7.5 versus 24.5{+/-} 7.3) and also within Turkey between public and private school students (PA: 26.8 {+/-} 7.5 versus 27.1 {+/-} 7.6; NA: 24.7{+/-} 7.2 versus 25.0{+/-} 7.8). While female students were significantly more severely affected in the Turkish group, no such gender differences were observed in the Danish group. Additionally, considerable portion of the students in Turkey and Denmark expressed loneliness (55.2% vs 59.8%, p<0.706), boredom (71.2% vs 58.7%, p=0.019) and anxiety towards the future (61.4% vs 22.8%, p<0.001). Decreased physical activity, sleep problems, eating disorders and domestic abuse were other complaints.\n\nConclusionsAdolescents from both countries have been severely affected by the pandemic and its related restrictions and expressed negative views about distance education. Turkish online education system seemed to be less satisfactory when compared to Danish system and within Turkey, public school students had significantly more disadvantages compared to those attending private schools. Despite the fact that there were several socio-economic inequalities among students, in general, there were no robust significant differences regarding psychological status and opinion about distance learning, indicating a global worsening of emotional status during pandemic.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20217380", + "rel_abs": "BackgroundRecent studies have reported numerous significant predictors for adverse outcomes in COVID-19 disease. However, there have been few simple clinical risk score for prompt risk stratification. The objective is to develop a simple risk score for severe COVID-19 disease using territory-wide healthcare data based on simple clinical and laboratory variables.\n\nMethodsConsecutive patients admitted to Hong Kongs public hospitals between 1st January and 22nd August 2020 diagnosed with COVID-19, as confirmed by RT-PCR, were included. The primary outcome was composite intensive care unit admission, need for intubation or death with follow-up until 8th September 2020.\n\nResultsCOVID-19 testing was performed in 237493 patients and 4445 patients (median age 44.8 years old, 95% CI: [28.9, 60.8]); 50% male) were tested positive. Of these, 212 patients (4.8%) met the primary outcome. A risk score including the following components was derived from Cox regression: gender, age, hypertension, stroke, diabetes mellitus, ischemic heart disease/heart failure, respiratory disease, renal disease, increases in neutrophil count, monocyte count, sodium, potassium, urea, alanine transaminase, alkaline phosphatase, high sensitive troponin-I, prothrombin time, activated partial thromboplastin time, D-dimer and C-reactive protein, as well as decreases in lymphocyte count, base excess and bicarbonate levels. The model based on test results taken on the day of admission demonstrated an excellent predictive value. Incorporation of test results on successive time points did not further improve risk prediction.\n\nConclusionsA simple clinical score accurately predicted severe COVID-19 disease, even without including symptoms, blood pressure or oxygen status on presentation, or chest radiograph results.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Lara Selin Seyahi", - "author_inst": "Robert college, Istanbul, Turkey" + "author_name": "Jiandong Zhou", + "author_inst": "City University of Hong Kong" }, { - "author_name": "Seyda Gul Ozcan", - "author_inst": "Cerrahpasa Medical Faculty, Department of Internal Medicine, Cerrahpasa Medical School, Istanbul University-Cerrahpasa, Istanbul, Turkey" + "author_name": "Sharen Lee", + "author_inst": "Laboratory of Cardiovascular Physiology, Li Ka Shing Institute of Health Sciences" }, { - "author_name": "Necdet Sut", - "author_inst": "Department of Biostatistics and Medical Informatics, Trakya University Medical Faculty, Edirne, Turkey" + "author_name": "Xiansong Wang", + "author_inst": "The Chinese University of Hong Kong" }, { - "author_name": "Ayumi Mayer", - "author_inst": "Aurehoj High School, Copenhagen, Denmark" + "author_name": "Yi Li", + "author_inst": "Wuhan Asia Heart Hospital" }, { - "author_name": "Burc Cagri Poyraz", - "author_inst": "Department of Psychiatry, Division of Geriatric Psychiatry, Cerrahpasa Medical Faculty, Istanbul University-Cerrahpasa, Istanbul, Turkey" + "author_name": "William KK Wu", + "author_inst": "The Chinese University of Hong Kong" + }, + { + "author_name": "Tong Liu", + "author_inst": "Tianjin Medical University" + }, + { + "author_name": "Zhidong Cao", + "author_inst": "Chinese Academy of Sciences" + }, + { + "author_name": "Daniel Dajun Zeng", + "author_inst": "Chinese Academy of Sciences" + }, + { + "author_name": "Ian CK Wong", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Bernard MY Cheung", + "author_inst": "The University of Hong Kong" + }, + { + "author_name": "Qingpeng Zhang", + "author_inst": "City University of Hong Kong" + }, + { + "author_name": "Gary Tse", + "author_inst": "Tianjin Medical University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.21.20217083", @@ -1137722,29 +1137228,89 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.21.20216895", - "rel_title": "Superspreading Events Without Superspreaders: Using High Attack Rate Events to Estimate N o forAirborne Transmission of COVID-19", + "rel_doi": "10.1101/2020.10.21.20217042", + "rel_title": "Viral dynamics of SARS-CoV-2 infection and the predictive value of repeat testing", "rel_date": "2020-10-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20216895", - "rel_abs": "We study transmission of COVID-19 using five well-documented case studies - a Washington state church choir, a Korean call center, a Korean exercise class, and two different Chinese bus trips. In all cases the likely index patients were pre-symptomatic or mildly symptomatic, which is when infective patients are most likely to interact with large groups of people. An estimate of N0, the characteristic number of COVID-19 virions needed to induce infection in each case, is found using a simple physical model of airborne transmission. We find that the N0 values are similar for five COVID-19 superspreading cases ([~]300-2,000 viral copies) and of the same order as influenza A. Consistent with the recent results of Goyal et al, these results suggest that viral loads relevant to infection from presymptomatic or mildly symptomatic individuals may fall into a narrow range, and that exceptionally high viral loads are not required to induce a superspreading event [1,2]. Rather, the accumulation of infective aerosols exhaled by a typical pre-symptomatic or mildly symptomatic patient in a confined, crowded space (amplified by poor ventilation, particularly activity like exercise or singing, or lack of masks) for exposure times as short as one hour are sufficient. We calculate that talking and breathing release [~]460N0 and [~]10N0 (quanta)/hour, respectively, providing a basis to estimate the risks of everyday activities. Finally, we provide a calculation which motivates the observation that fomites appear to account for a small percentage of total COVID-19 infection events.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.21.20217042", + "rel_abs": "BackgroundSARS-CoV-2 infections are characterized by viral proliferation and clearance phases and can be followed by low-level persistent viral RNA shedding. The dynamics of viral RNA concentration, particularly in the early stages of infection, can inform clinical measures and interventions such as test-based screening.\n\nMethodsWe used prospective longitudinal RT-qPCR testing to measure the viral RNA trajectories for 68 individuals during the resumption of the 2019-20 National Basketball Association season. For 46 individuals with acute infections, we inferred the peak viral concentration and the duration of the viral proliferation and clearance phases.\n\nFindingsAccording to our mathematical model, we found that viral RNA concentrations peaked an average of 3.3 days (95% credible interval [2.5, 4.2]) after first possible detectability at a cycle threshold value of 22.3 [20.5, 23.9]. The viral clearance phase lasted longer for symptomatic individuals (10.9 days [7.9, 14.4]) than for asymptomatic individuals (7.8 days [6.1, 9.7]). A second test within 2 days after an initial positive PCR substantially improves certainty about a patients infection phase. The effective sensitivity of a test intended to identify infectious individuals declines substantially with test turnaround time.\n\nConclusionsSARS-CoV-2 viral concentrations peak rapidly regardless of symptoms. Sequential tests can help reveal a patients progress through infection stages. Frequent rapid-turnaround testing is needed to effectively screen individuals before they become infectious.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "MARA G. PRENTISS", - "author_inst": "Harvard University" + "author_name": "Stephen M Kissler", + "author_inst": "Harvard T.H. Chan School of Public Health" }, { - "author_name": "Arthur Chu", - "author_inst": "QVT Family Office" + "author_name": "Joseph R. Fauver", + "author_inst": "Yale School of Public Health" }, { - "author_name": "Karl K. Berggren", - "author_inst": "MIT" + "author_name": "Christina Mack", + "author_inst": "IQVIA, Real World Solutions" + }, + { + "author_name": "Scott W. Olesen", + "author_inst": "Harvard T.H. Chan School of Public Health" + }, + { + "author_name": "Caroline Tai", + "author_inst": "IQVIA, Real World Solutions" + }, + { + "author_name": "Kristin Y. Shiue", + "author_inst": "IQVIA, Real World Solutions" + }, + { + "author_name": "Chaney Kalinich", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Sarah Jednak", + "author_inst": "University of Michigan School of Public Health" + }, + { + "author_name": "Isabel Ott", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Chantal Vogels", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Jay Wohlgemuth", + "author_inst": "Quest Diagnostics" + }, + { + "author_name": "James Weisberger", + "author_inst": "Bioreference Laboratories" + }, + { + "author_name": "John DiFiori", + "author_inst": "Hospital for Special Surgery, and the National Basketball Association" + }, + { + "author_name": "Deverick J. Anderson", + "author_inst": "Duke Center for Antimicrobial Stewardship and Infection Prevention" + }, + { + "author_name": "Jimmie Mancell", + "author_inst": "Department of Medicine, University of Tennessee Health Science Center" + }, + { + "author_name": "David Ho", + "author_inst": "Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons" + }, + { + "author_name": "Nathan D. Grubaugh", + "author_inst": "Yale School of Public Health" + }, + { + "author_name": "Yonatan H. Grad", + "author_inst": "Harvard T.H. Chan School of Public Health" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1139208,47 +1138774,111 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.10.22.349522", - "rel_title": "Analysis of SARS-CoV-2 ORF3a structure reveals chloride binding sites", + "rel_doi": "10.1101/2020.10.22.349951", + "rel_title": "Immunogenicity of a new gorilla adenovirus vaccine candidate for COVID-19", "rel_date": "2020-10-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.22.349522", - "rel_abs": "SARS-CoV-2 ORF3a is believed to form ion channels, which may be involved in the modulation of virus release, and has been implicated in various cellular processes like the up-regulation of fibrinogen expression in lung epithelial cells, downregulation of type 1 interferon receptor, caspase-dependent apoptosis, and increasing IFNAR1 ubiquitination. ORF3a assemblies as homotetramers, which are stabilized by residue C133. A recent cryoEM structure of a homodimeric complex of ORF3a has been released. A lower-resolution cryoEM map of the tetramer suggests two dimers form it, arranged side by side. The dimers cryoEM structure revealed that each protomer contains three transmembrane helices arranged in a clockwise configuration forming a six helices transmembrane domain. This domains potential permeation pathway has six constrictions narrowing to about 1 [A] in radius, suggesting the structure solved is in a closed or inactivated state. At the cytosol end, the permeation pathway encounters a large and polar cavity formed by multiple beta strands from both protomers, which opens to the cytosolic milieu. We modeled the tetramer following the arrangement suggested by the low-resolution tetramer cryoEM map. Molecular dynamics simulations of the tetramer embedded in a membrane and solvated with 0.5 M of KCl were performed. Our simulations show the cytosolic cavity is quickly populated by both K+ and Cl-, yet with different dynamics. K+ ions moved relatively free inside the cavity without forming proper coordination sites. In contrast, Cl- ions enter the cavity, and three of them can become stably coordinated near the intracellular entrance of the potential permeation pathway by an inter-subunit network of positively charged amino acids. Consequently, the central cavitys electrostatic potential changed from being entirely positive at the beginning of the simulation to more electronegative at the end.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.22.349951", + "rel_abs": "The COVID-19 pandemic caused by the emergent SARS-CoV-2 coronavirus threatens global public health and there is an urgent need to develop safe and effective vaccines. Here we report the generation and the preclinical evaluation of a novel replication-defective gorilla adenovirus-vectored vaccine encoding the pre-fusion stabilized Spike (S) protein of SARS-CoV2. We show that our vaccine candidate, GRAd- COV2, is highly immunogenic both in mice and macaques, eliciting both functional antibodies which neutralize SARS-CoV-2 infection and block Spike protein binding to the ACE2 receptor, and a robust, Th1- dominated cellular response in the periphery and in the lung. We show here that the pre-fusion stabilized Spike antigen is superior to the wild type in inducing ACE2-interfering, SARS-CoV2 neutralizing antibodies. To face the unprecedented need for vaccine manufacturing at massive scale, different GRAd genome deletions were compared to select the vector backbone showing the highest productivity in stirred tank bioreactors. This preliminary dataset identified GRAd-COV2 as a potential COVID-19 vaccine candidate, supporting the translation of GRAd-COV2 vaccine in a currently ongoing Phase I clinical trial (NCT04528641).", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Valeria Marquez-Miranda", - "author_inst": "Interdisciplinary Center of Neuroscience of Valparaiso, Faculty of Sciences, University of Valparaiso, Chile" + "author_name": "Alessandra Vitelli Sr.", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Stefania Capone Sr.", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Angelo Raggioli", + "author_inst": "ReiThera Srl" }, { - "author_name": "Maximiliano Rojas", - "author_inst": "Center for Bioinformatics and Integrative Biology, Universidad Andres Bello, Avenida Republica 330, Santiago, Chile" + "author_name": "Michela Gentile", + "author_inst": "ReiThera Srl" }, { - "author_name": "Yorley Duarte", - "author_inst": "Center for Bioinformatics and Integrative Biology, Universidad Andres Bello, Avenida Republica 330, Santiago, Chile" + "author_name": "Simone Battella", + "author_inst": "ReiThera Srl" }, { - "author_name": "Ignacio Diaz-Franulic", - "author_inst": "Center for Bioinformatics and Integrative Biology, Universidad Andres Bello, Avenida Republica 330, Santiago, Chile" + "author_name": "Armin Lahm", + "author_inst": "ReiThera Srl" }, { - "author_name": "Miguel Holmgren", - "author_inst": "Molecular Neurophysiology Section, National Institute of Neurological Disorders and Stroke, National Institutes of Health, MD, USA" + "author_name": "Andrea Sommella", + "author_inst": "ReiThera Srl" }, { - "author_name": "Raul Cachau", - "author_inst": "Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA" + "author_name": "Alessandra Maria Contino", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Richard A Urbanowicz", + "author_inst": "University of Nottingham" + }, + { + "author_name": "Romina Scala", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Federica Barra", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Adriano Leuzzi", + "author_inst": "ReiThera Srl" }, { - "author_name": "Fernando Danilo Gonzalez-Nilo", - "author_inst": "Center for Bioinformatics and Integrative Biology, Universidad Andres Bello, Avenida Republica 330, Santiago, Chile" + "author_name": "Eleonora Lilli", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Giuseppina Miselli", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Alessia Noto", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Maria Ferraiuolo", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Francesco Talotta", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Theocharis Tsoleridis", + "author_inst": "University of Nottingham" + }, + { + "author_name": "Silvia Meschi", + "author_inst": "National Institute for Infectious Diseases L. Spallanzani" + }, + { + "author_name": "Marco Soriani", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Antonella Folgori", + "author_inst": "ReiThera Srl" + }, + { + "author_name": "Jonathan K Ball", + "author_inst": "the University of Nottingham" + }, + { + "author_name": "Stefano Colloca", + "author_inst": "ReiThera Srl" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "biophysics" + "category": "immunology" }, { "rel_doi": "10.1101/2020.10.22.350207", @@ -1140825,63 +1140455,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.20.20215863", - "rel_title": "Cognitive deficits in people who have recovered from COVID-19 relative to controls: An N=84,285 online study", + "rel_doi": "10.1101/2020.10.19.20215079", + "rel_title": "Epidemic Curve of Contamination in a Hospital That Served as Sentinel of the Spread of the SARS-Cov-2 Epidemic in the City of Rio de Janeiro", "rel_date": "2020-10-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.20.20215863", - "rel_abs": "Case studies have revealed neurological problems in severely affected COVID-19 patients. However, there is little information regarding the nature and broader prevalence of cognitive problems post-infection or across the full spread of severity. We analysed cognitive test data from 84,285 Great British Intelligence Test participants who completed a questionnaire regarding suspected and biologically confirmed COVID-19 infection. People who had recovered, including those no longer reporting symptoms, exhibited significant cognitive deficits when controlling for age, gender, education level, income, racial-ethnic group and pre-existing medical disorders. They were of substantial effect size for people who had been hospitalised, but also for mild but biologically confirmed cases who reported no breathing difficulty. Finer grained analyses of performance support the hypothesis that COVID-19 has a multi-system impact on human cognition.\n\nSignificance statementThere is evidence that COVID-19 may cause long term health changes past acute symptoms, termed long COVID. Our analyses of detailed cognitive assessment and questionnaire data from tens thousands of datasets, collected in collaboration with BBC2 Horizon, align with the view that there are chronic cognitive consequences of having COVID-19. Individuals who recovered from suspected or confirmed COVID-19 perform worse on cognitive tests in multiple domains than would be expected given their detailed age and demographic profiles. This deficit scales with symptom severity and is evident amongst those without hospital treatment. These results should act as a clarion call for more detailed research investigating the basis of cognitive deficits in people who have survived SARS-COV-2 infection.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.19.20215079", + "rel_abs": "The COVID-19 pandemic had a profound impact on the operation of Brazilian hospital units, even those dedicated to non-infectious diseases. This study aims to describe the Covid-19 epidemic curve from a cardiovascular specialized nosocomial unit. All symptomatic employees were submitted to RT-qPCR. A total of 613 tests were performed on 548 employees between March 23, 2020, and June 4, 2020; with 45.7% positivity from the samples, representing 11.9% of the total employees. The epidemic curve showed a profound drop after first week of May. The data showed a high contamination rate despite widespread availability of personal protective equipment and employees training.", "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Adam Hampshire", - "author_inst": "Imperial College London" + "author_name": "Marisa Santos", + "author_inst": "Instituto Nacional de Cardiologia" }, { - "author_name": "William Trender", - "author_inst": "Imperial College London" + "author_name": "Tereza Fellipe Guimaraes", + "author_inst": "Instituto Nacional de Cardiologia" }, { - "author_name": "Samuel Chamberlain", - "author_inst": "University of Cambridge" + "author_name": "Helena Cramer Rey", + "author_inst": "Instituto Nacional de Cardiologia" }, { - "author_name": "Amy Jolly", - "author_inst": "Imperial College London" + "author_name": "Fabiana Mucillo", + "author_inst": "Instituto Nacional de Cardiologia" }, { - "author_name": "Jon E Grant", - "author_inst": "University of Chicago" + "author_name": "Adriana Carvalho", + "author_inst": "Instituto Nacional de Cardiologia" }, { - "author_name": "Fiona Patrick", - "author_inst": "King's College London" + "author_name": "Izabella Bezerra", + "author_inst": "Instituto de Biofisica Carlos Chagas Filho UFRJ" }, { - "author_name": "Ndaba Mazibuko", - "author_inst": "King's College London" + "author_name": "Raiana Barbosa", + "author_inst": "Instituto de Biofisica Carlos Chagas Filho UFRJ" }, { - "author_name": "Steve Williams", - "author_inst": "King's College London" + "author_name": "Tais Hanae Kasai Brunswick", + "author_inst": "Centro Nacional de Biologia Estrutural e Bioimagem/ CENABIO-UFRJ" }, { - "author_name": "Joe M Barnby", - "author_inst": "King's College London" + "author_name": "Glauber Monteiro Dias", + "author_inst": "Instituto Nacional de Cardiologia" }, { - "author_name": "Peter Hellyer", - "author_inst": "King's College London" + "author_name": "Aurora Issa", + "author_inst": "Instituto Nacional de Cardiologia" }, { - "author_name": "Mitul A Mehta", - "author_inst": "King's College London" + "author_name": "Antonio Carlos Campos de Carvalho", + "author_inst": "Instituto de Biofisica Carlos Chagas Filho UFRJ" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.10.20.20215970", @@ -1142339,93 +1141969,105 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.15.20213512", - "rel_title": "COVID-19 neutralizing antibodies predict disease severity and survival", + "rel_doi": "10.1101/2020.10.15.20213108", + "rel_title": "FebriDx point-of-care test in patients with suspected COVID-19: a pooled diagnostic accuracy study", "rel_date": "2020-10-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.15.20213512", - "rel_abs": "COVID-19 exhibits variable symptom severity ranging from asymptomatic to life-threatening, yet the relationship between severity and the humoral immune response is poorly understood. We examined antibody responses in 113 COVID-19 patients and found that severe cases resulting in intubation or death exhibited increased inflammatory markers, lymphopenia, and high anti-RBD antibody levels. While anti-RBD IgG levels generally correlated with neutralization titer, quantitation of neutralization potency revealed that high potency was a predictor of survival. In addition to neutralization of wild-type SARS-CoV-2, patient sera were also able to neutralize the recently emerged SARS-CoV-2 mutant D614G, suggesting protection from reinfection by this strain. However, SARS-CoV-2 sera was unable to cross-neutralize a highly-homologous pre-emergent bat coronavirus, WIV1-CoV, that has not yet crossed the species barrier. These results highlight the importance of neutralizing humoral immunity on disease progression and the need to develop broadly protective interventions to prevent future coronavirus pandemics.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.15.20213108", + "rel_abs": "BackgroundWe conducted a systematic review and individual patient data (IPD) meta-analysis to evaluate the diagnostic accuracy of a commercial point-of-care test, the FebriDx lateral flow device (LFD), in adult patients with suspected COVID-19. The FebriDx LFD is designed to distinguish between viral and bacterial respiratory infection.\n\nMethodsWe searched MEDLINE, EMBASE, PubMed, Google Scholar, LitCovid, ClinicalTrials.gov and preprint servers on the 13th of January 2021 to identify studies reporting diagnostic accuracy of FebriDx (myxovirus resistance protein A component) versus real time reverse transcriptase polymerase chain reaction (RT-PCR) testing for SARS-CoV-2 in adult patients suspected of COVID-19. IPD were sought from studies meeting the eligibility criteria. Studies were screened for risk of bias using the QUADAS-2 tool. A bivariate linear mixed model was fitted to the data to obtain a pooled estimate of sensitivity and specificity with 95% confidence intervals (95% CIs). A summary receiver operating characteristic (SROC) curve of the model was constructed. A sub-group analysis was performed by meta-regression using the same modelling approach to compare pooled estimates of sensitivity and specificity between patients with a symptom duration of 0 to 7 days and >7 days, and patients aged between 16 to 73 years and >73 years.\n\nResultsTen studies were screened, and three studies with a total of 1481 patients receiving hospital care were included. FebriDx produced an estimated pooled sensitivity of 0.911 (95% CI: 0.855-0.946) and specificity of 0.868 (95% CI: 0.802-0.915) compared to RT-PCR. There were no significant differences between the sub-groups of 0 to 7 days and >7 days in estimated pooled sensitivity (p = 0.473) or specificity (p = 0.853). There were also no significant differences between the sub-groups of 16 to 73 years of age and >73 years of age in estimated pooled sensitivity (p = 0.946) or specificity (p = 0.486).\n\nConclusionsBased on the results of three studies, the FebriDx LFD had high diagnostic accuracy for COVID-19 in a hospital setting, however, the pooled estimates of sensitivity and specificity should be interpreted with caution due to the small number of studies included, risk of bias, and inconsistent reference standards. Further research is required to confirm these findings, and determine how FebriDx would perform in different healthcare settings and patient populations.\n\nTrial registrationThis study was conducted at pace as part of the COVID-19 National Diagnostic Research and Evaluation Platform (CONDOR) national test evaluation programme (https://www.condor-platform.org), and as a result, no protocol was developed, and the study was not registered.\n\nLay summaryTests to diagnose COVID-19 are crucial to help control the spread of the disease and to guide treatment. Over the last few months, tests have been developed to diagnose COVID-19 either by detecting the presence of the virus or by detecting specific markers linked to the virus being active in the body. These tests use complex machines in laboratories accepting samples from large geographical areas. Sometimes it takes days for test results to come back. So, to reduce the wait for results, new portable tests are being developed. These point-of-care (POC) tests are designed to work close to where patients require assessment and care such as hospital emergency departments, GP surgeries or care homes. For these new POC tests to be useful, they should ideally be as good as standard laboratory tests.\n\nIn this study we looked at published research into a new test called FebriDx. FebriDx is a POC test that detects the bodys response to infection, and is claimed to be able to detect the presence of any viral infection, including infections due to the SARS-CoV-2 virus which causes COVID-19, as well as bacterial infections which can have similar symptoms. The FebriDx result was compared with standard laboratory tests for COVID-19 performed on the same patients throat and nose swab sample. We were able to analyse data from three studies with a total of 1481 adult patients who were receiving hospital care with symptoms of COVID-19 during the UK pandemic. Approximately one fifth of the patients were diagnosed as positive for SARS-CoV-2 virus using standard laboratory tests for COVID-19.\n\nOur analysis demonstrated that FebriDx correctly identified 91 out of 100 patients who had COVID-19 according to the standard laboratory test. FebriDx also correctly identified 87 out of 100 patients who did not have COVID-19 according to the standard laboratory test. These results have important implications for how these tests could be used. As there were slightly fewer FebriDx false results when the results of the standard laboratory test were positive (9 out of 100) than when the results of the standard laboratory test were negative (13 out of 100), we can have slightly more confidence in a positive test result using FebriDx than a negative FebriDx result.\n\nOverall, we have shown that the FebriDx POC test performed well during the UK COVID-19 pandemic when compared with laboratory tests, especially when COVID-19 was indicated. For the future, this means that the FebriDx POC test might be helpful in making a quick clinical decision on whether to isolate a patient with COVID-19-like symptoms arriving in a busy emergency department. However, our results indicate it would not completely replace the need to conduct a laboratory test in certain cases to confirm COVID-19.\n\nThere are limitations to our findings. For example, we do not know if FebriDx will work in a similar way with patients in different settings such as in the community or care homes. Similarly, we do not know whether other viral and bacterial infections which cause similar COVID-19 symptoms, and are more common in the autumn and winter months, could influence the FebriDx test accuracy. Our findings are also only based on three studies.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Wilfredo F Garcia-Beltran", - "author_inst": "Massachusetts General Hospital, Department of Pathology" + "author_name": "Samuel G Urwin", + "author_inst": "NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne Hospitals Foundation Trust, Newcastle-upon-Tyne, UK" }, { - "author_name": "Evan C Lam", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "B Clare Lendrem", + "author_inst": "NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK" }, { - "author_name": "Michael G Astudillo", - "author_inst": "Massachusetts General Hospital, Department of Pathology" + "author_name": "Jana Suklan", + "author_inst": "NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK" }, { - "author_name": "Diane Yang", - "author_inst": "Massachusetts General Hospital, Department of Pathology" + "author_name": "Kile Green", + "author_inst": "NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK" }, { - "author_name": "Tyler E Miller", - "author_inst": "Massachusetts General Hospital, Department of Pathology" + "author_name": "Sara Graziadio", + "author_inst": "NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne Hospitals Foundation Trust, Newcastle-upon-Tyne, UK" }, { - "author_name": "Jared Feldman", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Peter Buckle", + "author_inst": "Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, UK" }, { - "author_name": "Blake M Hauser", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Paul M Dark", + "author_inst": "Division of Infection, Immunity & Respiratory Medicine, University of Manchester, UK" }, { - "author_name": "Timothy M Caradonna", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Adam L Gordon", + "author_inst": "School of Medicine, University of Nottingham, UK; NIHR Applied Research Collaboration East Midlands (ARC-EM), Nottingham, UK" }, { - "author_name": "Kiera L Clayton", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Daniel S Lasserson", + "author_inst": "NIHR Community Healthcare MedTech and In Vitro Diagnostics Cooperative, Oxford Health NHS Foundation Trust, Oxford, UK; Division of Health Sciences, University " }, { - "author_name": "Adam D Nitido", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Brian Nicholson", + "author_inst": "Nuffield Department of Primary Care Health Sciences, University of Oxford, Oxford, UK" }, { - "author_name": "Mandakolathur R Murali", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "D Ashley Price", + "author_inst": "NIHR Newcastle In Vitro Diagnostics Co-operative, Newcastle-upon-Tyne Hospitals Foundation Trust, Newcastle-upon-Tyne, UK" }, { - "author_name": "Galit Alter", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Charles Reynard", + "author_inst": "NIHR Doctoral Research Fellowship Programme, UK; Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK" }, { - "author_name": "Richelle C Charles", - "author_inst": "Massachusetts General Hospital, Infectious Disease Unit" + "author_name": "Mark H Wilcox", + "author_inst": "Healthcare Associated Infections Research Group, NIHR Leeds In Vitro Diagnostics Co-operative, Leeds Teaching Hospitals NHS Trust and University of Leeds, Leeds" }, { - "author_name": "Anand Dighe", - "author_inst": "Massachusetts General Hospital, Department of Pathology" + "author_name": "Gail Hayward", + "author_inst": "NIHR Community Healthcare MedTech and In Vitro Diagnostics Co-operative, Oxford Health NHS Foundation Trust, Oxford, UK; Nuffield Department of Primary Care Hea" }, { - "author_name": "John A Branda", - "author_inst": "Massachusetts General Hospital, Department of Pathology" + "author_name": "Graham Prestwich", + "author_inst": "Yorkshire and Humber Academic Health Science Network, Wakefield, UK" }, { - "author_name": "Jochen K Lennerz", - "author_inst": "Massachusetts General Hospital, Department of Pathology" + "author_name": "Valerie Tate", + "author_inst": "Patient Public Involvement (PPI) Member, Precision Antimicrobial Prescribing PPI Group, NIHR Community Healthcare MedTech and In Vitro Diagnostics Cooperative, " }, { - "author_name": "Daniel Lingwood", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Tristan W Clark", + "author_inst": "School of Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; Department of Infection, University Hospital Sout" }, { - "author_name": "Aaron G Schmidt", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Raja V Reddy", + "author_inst": "Department of Respiratory Medicine, Kettering General Hospital NHS Foundation Trust, Kettering, UK" }, { - "author_name": "A. John Iafrate", - "author_inst": "Massassachusetts General Hospital, Department of Pathology" + "author_name": "Hamish Houston", + "author_inst": "Northwick Park Hospital, London North West University Healthcare NHS Trust, Harrow, UK" }, { - "author_name": "Alejandro B Balazs", - "author_inst": "Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Ankur Gupta-Wright", + "author_inst": "Institute for Global Health, University College London, London, UK; Ealing Hospital, London North West University Healthcare NHS Trust, London, UK; Clinical Res" + }, + { + "author_name": "Laurence John", + "author_inst": "Northwick Park Hospital, London North West University Healthcare NHS Trust, Harrow, UK" + }, + { + "author_name": "Richard Body", + "author_inst": "Division of Cardiovascular Sciences, Faculty of Biology, Medicine and Health, University of Manchester, UK; Emergency Department, Manchester Royal Infirmary, Ma" + }, + { + "author_name": "A Joy Allen", + "author_inst": "NIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research Institute, Newcastle University, Newcastle-upon-Tyne, UK" } ], "version": "1", @@ -1144025,43 +1143667,27 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2020.10.17.20214429", - "rel_title": "SARS-CoV-2 infection among patients with multiple sclerosis; A cross-sectional study", + "rel_doi": "10.1101/2020.10.18.20213942", + "rel_title": "LOCKDOWN FATIGUE AMONG COLLEGE STUDENTS DURING THE COVID-19 PANDEMIC: PREDICTIVE ROLE OF PERSONAL RESILIENCE, COPING BEHAVIOURS, AND HEALTH", "rel_date": "2020-10-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.17.20214429", - "rel_abs": "BackgroundNeurological disability associated with multiple sclerosis and immunosuppressive or immunomodulatory therapy which is administered for it may increases the risk of SARS-CoV-2 infection and its morbidity/mortality.\n\nObjectiveIn this study, we evaluated the infection rate and the severity of SARS-CoV-2 infection in patients with multiple sclerosis (MS)\n\nMethodsOne thousand and three hundred and sixty one MS patients from Fars province, south of Iran, were interviewed by phone from April 3 to June 20, 2020. Basic demographic data, information about MS disease and any symptoms or laboratory results relevant to COVID-19 were gathered and reviewed by treating neurologist and MS nurses. SPSS version 22 was used for data analysis.\n\nResults68 (5%) of MS patients were suspected cases and 8 (0.58%) of all patients with positive real-time reverse transcription polymerase chain reaction (RT-PCR) or chest CT were in the confirmed group. 5 cases of the confirmed group needed hospitalization. Two patients died while both of them had PPMS and were taking rituximab. The frequency rate of suspected cases with RRMS was 57 (87.7%), followed by PPMS 5 (7.7%) and CIS 2(3.1%). In the confirmed group 37.5% had RRMS, 50% had PPMS, 25% use corticosteroid drug, and 50% were on rituximab. 62.5% of confirmed cases had high disability level and need assistance to walk. 36.8% of suspected and 25% of the confirmed cases were on IFN-{beta}1; eventually all of them recovered well from COVID-19 infection.\n\nConclusionThe present study showed that rate of developing COVID-19 in MS patients are similar to the general population and the frequency of PPMS phenotype, rituximab therapy and corticosteroid therapy were higher in the confirmed group.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.18.20213942", + "rel_abs": "BackgroundThe lockdown measures imposed by many countries since the onset of the COVID-19 pandemic have been useful in slowing the transmission of the disease; however, there is growing concern regarding their adverse consequences on overall health and well-being, particularly among young people. To date, most studies have focused on the mental health consequences of the lockdown measures, while studies assessing how this disease control measure influences the occurrence of fatigue are largely absent.\n\nAimThe aims of this study are two-fold: (a) to examine the levels of lockdown fatigue, and (2) to determine the role of coping behaviours, personal resilience, psychological well-being and perceived health in fatigue associated to the lockdown measure.\n\nMethodsThis is an online cross-sectional study involving 243 college students in the Central Philippines during the sixth month of the lockdown measure implemented due to the COVID-19 pandemic. Five standardised scales were used to collect the data.\n\nResultsOverall, college students reported moderate levels of lockdown fatigue, with a mean score of 31.54 (out of 50). Physical exhaustion or tiredness, headaches and body pain, decreased motivation and increased worry were the most pronounced manifestations of fatigue reported. Gender and college year were identified as important predictors of fatigue. Increased personal resilience and coping skills were associated with lower levels of lockdown fatigue.\n\nConclusionCollege students experience moderate levels of fatigue during the mandatory lockdown or home confinement period. Resilient students and those who perceive higher social support experience lower levels of fatigue during the lockdown period compared to students with low resilience and social support. Lockdown fatigue may be addressed by formulating and implementing interventions to enhance personal resilience and social support among college students.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Mahnaz Bayat", - "author_inst": "Shiraz University of Medical Sciences" - }, - { - "author_name": "Alireza Fayyazpoor", - "author_inst": "Shiraz Medical School, Shiraz University of Medical Sciences" - }, - { - "author_name": "Afshin Borhani Haghighi", - "author_inst": "Shiraz University of Medical Sciences" - }, - { - "author_name": "Daniyal Salehi", - "author_inst": "Shiraz University of Medical Sciences" - }, - { - "author_name": "Hossein Molavi Vardanjan", - "author_inst": "Shiraz University of Medical Sciences" + "author_name": "Leodoro Labrague", + "author_inst": "Sultan Qaboos University" }, { - "author_name": "Maryam Poursadeghfard", - "author_inst": "Shiraz University of Medical Sciences" + "author_name": "Cherry Ann Ballad", + "author_inst": "Sultan Qaboos University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "nursing" }, { "rel_doi": "10.1101/2020.10.18.20214692", @@ -1145743,75 +1145369,59 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.10.19.343954", - "rel_title": "Single cell resolution of SARS-CoV-2 tropism, antiviral responses, and susceptibility to therapies in primary human airway epithelium", - "rel_date": "2020-10-19", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.19.343954", - "rel_abs": "The human airway epithelium is the initial site of SARS-CoV-2 infection. We used flow cytometry and single cell RNA-sequencing to understand how the heterogeneity of this diverse cell population contributes to elements of viral tropism and pathogenesis, antiviral immunity, and treatment response to remdesivir. We found that, while a variety of epithelial cell types are susceptible to infection, ciliated cells are the predominant cell target of SARS-CoV-2. The host protease TMPRSS2 was required for infection of these cells. Importantly, remdesivir treatment effectively inhibited viral replication across cell types, and blunted hyperinflammatory responses. Induction of interferon responses within infected cells was rare and there was significant heterogeneity in the antiviral gene signatures, varying with the burden of infection in each cell. We also found that heavily infected secretory cells expressed abundant IL-6, a potential mediator of COVID-19 pathogenesis.", - "rel_num_authors": 14, + "rel_doi": "10.1101/2020.10.15.20213348", + "rel_title": "COVID-19 In a Rural Health System in New York - Case Series and an Approach to Management", + "rel_date": "2020-10-18", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.15.20213348", + "rel_abs": "BackgroundMany rural hospitals and health systems in the U.S. lack sufficient resources to treat COVID-19. We developed a system for managing inpatient COVID-19 hospital admissions in St. Lawrence County, an underserved rural county which is the largest county in New York State.\n\nMethodsWe used a hub and spoke system to route COVID-19 patients in the St. Lawrence Health System to its flagship hospital. We assembled a small clinical team to manage admitted COVID-19 patients and to stay abreast of a quickly changing body of literature and standard of care. We subsequently completed a review of clinical data for patients who were treated by our inpatient COVID-19 treatment team between March 20 and May 22, 2020.\n\nResultsTwenty COVID-19 patients were identified. Sixteen patients (80%) met NIH criteria for severe or critical disease. One patient died. No patients were transferred to other hospitals.\n\nConclusionsDuring the first two months of the pandemic, we were able to manage hospitalized COVID-19 patients in our rural community. Development of similar treatment models in other rural areas should be considered.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Jessica K. Fiege", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Joshua M. Thiede", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Hezkiel Nanda", - "author_inst": "University of Minnesota" - }, - { - "author_name": "William E Matchett", - "author_inst": "University of Minnesota" + "author_name": "Eyal Kedar", + "author_inst": "St. Lawrence Health System, Department of Internal Medicine, Division of Rheumatology" }, { - "author_name": "Patrick J. Moore", - "author_inst": "University of Minnesota" + "author_name": "Regina Scott", + "author_inst": "St. Lawrence Health System, Department of Pharmacy" }, { - "author_name": "Noe Rico Montanari", - "author_inst": "University of Minnesota" + "author_name": "Daniel Soule", + "author_inst": "St. Lawrence Health System, Department of Internal Medicine, Division of Infectious Diseases" }, { - "author_name": "Beth K Thielen", - "author_inst": "University of Minnesota" + "author_name": "Carly Lovelett", + "author_inst": "St. Lawrence Health System, Department of Clinical and Rural Health Research" }, { - "author_name": "Jerry Daniel", - "author_inst": "University of Minnesota" + "author_name": "Kyle Tower", + "author_inst": "St. Lawrence Health System, Department of Clinical and Rural Health Research" }, { - "author_name": "Emma Stanley", - "author_inst": "University of Minnesota" + "author_name": "Kylie Broughal", + "author_inst": "St. Lawrence Health System, Department of Internal Medicine, Division of Infectious Diseases" }, { - "author_name": "Ryan C Hunter", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Vineet D Menachery", - "author_inst": "University of Texas Medical Branch" + "author_name": "Daniel Jaremczuk", + "author_inst": "St. Lawrence Health System, Department of Clinical and Rural Health Research" }, { - "author_name": "Steven S. Shen", - "author_inst": "University of Minnesota" + "author_name": "Sara Mohaddes", + "author_inst": "St. Lawrence Health System, Department of Hospital Medicine" }, { - "author_name": "Tyler D. Bold", - "author_inst": "University of Minnesota" + "author_name": "Imre Rainey-Spence", + "author_inst": "St. Lawrence Health System, Department of Hospital Medicine" }, { - "author_name": "Ryan A. Langlois", - "author_inst": "University of Minnesota" + "author_name": "Timothy Atkinson", + "author_inst": "St. Lawrence Health System, Department of Hospital Medicine" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.15.20205054", @@ -1147348,55 +1146958,111 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.10.14.20212555", - "rel_title": "Multi-organ impairment in low-risk individuals with long COVID", + "rel_doi": "10.1101/2020.10.14.20207050", + "rel_title": "A betacoronavirus multiplex microsphere immunoassay detects early SARS-CoV-2 seroconversion and controls for pre-existing seasonal human coronavirus antibody cross-reactivity", "rel_date": "2020-10-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.14.20212555", - "rel_abs": "BackgroundSevere acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) infection has disproportionately affected older individuals and those with underlying medical conditions. Research has focused on short-term outcomes in hospital, and single organ involvement. Consequently, impact of long COVID (persistent symptoms three months post-infection) across multiple organs in low-risk individuals is yet to be assessed.\n\nMethodsAn ongoing prospective, longitudinal, two-centre, observational study was performed in individuals symptomatic after recovery from acute SARS-CoV-2 infection. Symptoms and organ function (heart, lungs, kidneys, liver, pancreas, spleen) were assessed by standardised questionnaires (EQ-5D-5L, Dyspnoea-12), blood investigations and quantitative magnetic resonance imaging, defining single and multi-organ impairment by consensus definitions.\n\nFindingsBetween April and September 2020, 201 individuals (mean age 44 (SD 11.0) years, 70% female, 87% white, 31% healthcare workers) completed assessments following SARS-CoV-2 infection (median 140, IQR 105-160 days after initial symptoms). The prevalence of pre-existing conditions (obesity: 20%, hypertension: 6%; diabetes: 2%; heart disease: 4%) was low, and only 18% of individuals had been hospitalised with COVID-19. Fatigue (98%), muscle aches (88%), breathlessness (87%), and headaches (83%) were the most frequently reported symptoms. Ongoing cardiorespiratory (92%) and gastrointestinal (73%) symptoms were common, and 42% of individuals had ten or more symptoms.\n\nThere was evidence of mild organ impairment in heart (32%), lungs (33%), kidneys (12%), liver (10%), pancreas (17%), and spleen (6%). Single (66%) and multi-organ (25%) impairment was observed, and was significantly associated with risk of prior COVID-19 hospitalisation (p<0.05).\n\nInterpretationIn a young, low-risk population with ongoing symptoms, almost 70% of individuals have impairment in one or more organs four months after initial symptoms of SARS-CoV-2 infection. There are implications not only for burden of long COVID but also public health approaches which have assumed low risk in young people with no comorbidities.\n\nFundingThis work was supported by the UKs National Consortium of Intelligent Medical Imaging through the Industry Strategy Challenge Fund, Innovate UK Grant 104688, and also through the European Unions Horizon 2020 research and innovation programme under grant agreement No 719445.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.14.20207050", + "rel_abs": "With growing concern of persistent or multiple waves of SARS-CoV-2 in the United States, sensitive and specific SARS-CoV-2 antibody assays remain critical for community and hospital-based SARS-CoV-2 surveillance. Here, we describe the development and application of a multiplex microsphere-based immunoassay (MMIA) for COVD-19 antibody studies, utilizing serum samples from non-human primate SARS-CoV-2 infection models, an archived human sera bank and subjects enrolled at five U.S. military hospitals. The MMIA incorporates prefusion stabilized spike glycoprotein trimers of SARS-CoV-2, SARS-CoV-1, MERS-CoV, and the seasonal human coronaviruses HCoV-HKU1 and HCoV-OC43, into a multiplexing system that enables simultaneous measurement of off-target pre-existing cross-reactive antibodies. We report the sensitivity and specificity performances for this assay strategy at 98% sensitivity and 100% specificity for subject samples collected as early as 10 days after the onset of symptoms. In archival sera collected prior to 2019 and serum samples from subjects PCR negative for SARS-CoV-2, we detected seroprevalence of 72% and 98% for HCoV-HKU1 and HCoV-0C43, respectively. Requiring only 1.25 {micro}L of sera, this approach permitted the simultaneous identification of SARS-CoV-2 seroconversion and polyclonal SARS-CoV-2 IgG antibody responses to SARS-CoV-1 and MERS-CoV, further demonstrating the presence of conserved epitopes in the spike glycoprotein of zoonotic betacoronaviruses. Application of this serology assay in observational studies with serum samples collected from subjects before and after SARS-CoV-2 infection will permit an investigation of the influences of HCoV-induced antibodies on COVID-19 clinical outcomes.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Andrea Dennis", - "author_inst": "Perspectum" + "author_name": "Eric D. Laing", + "author_inst": "Department of Microbiology and Immunology, Uniformed Services University" }, { - "author_name": "Malgorzata Wamil", - "author_inst": "Great Western Hospitals NHS Foundation Trust" + "author_name": "Spencer L. Sterling", + "author_inst": "Department of Microbiology and Immunology, Uniformed Services University; Henry M. Jackson Foundation for the Advancement of Military Medicine" }, { - "author_name": "Sandeep Kapur", - "author_inst": "Mayo Clinic Healthcare" + "author_name": "Stephanie A. Richard", + "author_inst": "Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University; Henry M. Jackson Foundation f" }, { - "author_name": "Johann Alberts", - "author_inst": "Alliance Medical" + "author_name": "Shreshta Phogat", + "author_inst": "Department of Microbiology and Immunology, Uniformed Services University; Henry M. Jackson Foundation for the Advancement of Military Medicine" }, { - "author_name": "Andrew Badley", - "author_inst": "Mayo Clinic" + "author_name": "Emily C. Samuels", + "author_inst": "Department of Microbiology and Immunology, Uniformed Services University; Henry M. Jackson Foundation for the Advancement of Military Medicine" }, { - "author_name": "Gustav Anton Decker", - "author_inst": "Mayo Clinic International" + "author_name": "Nusrat J. Epsi", + "author_inst": "Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University; Henry M. Jackson Foundation f" }, { - "author_name": "Stacey A Rizza", - "author_inst": "Mayo Clinic" + "author_name": "Lianying Yan", + "author_inst": "Department of Microbiology and Immunology, Uniformed Services University; Henry M. Jackson Foundation for the Advancement of Military Medicine" }, { - "author_name": "Rajarshi Banerjee", - "author_inst": "Perspectum" + "author_name": "Nicole Moreno", + "author_inst": "Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University; Henry M. Jackson Foundation f" }, { - "author_name": "Amitava Banerjee", - "author_inst": "University College London" + "author_name": "Christian Coles", + "author_inst": "Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University; Henry M. Jackson Foundation f" + }, + { + "author_name": "Jennifer Mehalko", + "author_inst": "Protein Expression Laboratory, National Cancer Institute RAS Initiative, Frederick National Laboratory for Cancer Research" + }, + { + "author_name": "Matthew Drew", + "author_inst": "Protein Expression Laboratory, National Cancer Institute RAS Initiative, Frederick National Laboratory for Cancer Research" + }, + { + "author_name": "Caroline English", + "author_inst": "Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University; Henry M. Jackson Foundation f" + }, + { + "author_name": "Kevin K. Chung", + "author_inst": "Department of Medicine, Uniformed Services University" + }, + { + "author_name": "G. Travis Clifton", + "author_inst": "Brooke Army Medical Center, JBSA Fort Sam Houston" + }, + { + "author_name": "Vincent Munster", + "author_inst": "NIAID" + }, + { + "author_name": "Emmie de Wit", + "author_inst": "NIAID, NIH" + }, + { + "author_name": "David Tribble", + "author_inst": "Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University" + }, + { + "author_name": "Brian Agan", + "author_inst": "Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University; Henry M. Jackson Foundation f" + }, + { + "author_name": "Dominic Esposito", + "author_inst": "Protein Expression Laboratory, National Cancer Institute RAS Initiative, Frederick National Laboratory for Cancer Research" + }, + { + "author_name": "Charlotte Lanteri", + "author_inst": "Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University" + }, + { + "author_name": "Edward Mitre", + "author_inst": "Department of Microbiology and Immunology, Uniformed Services University" + }, + { + "author_name": "Timothy H. Burgess", + "author_inst": "Infectious Diseases Clinical Research Program, Department of Preventive Medicine and Biostatistics, Uniformed Services University" + }, + { + "author_name": "Christopher C. Broder", + "author_inst": "Department of Microbiology and Immunology, Uniformed Services University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.10.14.20212498", @@ -1149010,67 +1148676,51 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.10.14.339952", - "rel_title": "Multiplexed proteomics and imaging of resolving and lethal SARS-CoV-2 infection in the lung", + "rel_doi": "10.1101/2020.10.15.325050", + "rel_title": "The Strand-biased Transcription of SARS-CoV-2 and Unbalanced Inhibition by Remdesivir", "rel_date": "2020-10-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.14.339952", - "rel_abs": "Normal tissue physiology and repair depends on communication with the immune system. Understanding this communication at the molecular level in intact tissue requires new methods. The consequences of SARS-CoV-2 infection, which can result in acute respiratory distress, thrombosis and death, has been studied primarily in accessible liquid specimens such as blood, sputum and bronchoalveolar lavage, all of which are peripheral to the primary site of infection in the lung. Here, we describe the combined use of multiplexed deep proteomics with multiplexed imaging to profile infection and its sequelae directly in fixed lung tissue specimens obtained from necropsy of infected animals and autopsy of human decedents. We characterize multiple steps in disease response from cytokine accumulation and protein phosphorylation to activation of receptors, changes in signaling pathways, and crosslinking of fibrin to form clots. Our data reveal significant differences between naturally resolving SARS-CoV-2 infection in rhesus macaques and lethal COVID-19 in humans. The approach we describe is broadly applicable to other tissues and diseases.\n\nSummaryProteomics of infected tissue reveals differences in inflammatory and thrombotic responses between resolving and lethal COVID-19.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.15.325050", + "rel_abs": "SARS-CoV-2, a positive single-stranded RNA virus, caused the COVID-19 pandemic. During the viral replication and transcription, the RNA dependent RNA polymerase (RdRp) \"jumps\" along the genome template, resulting in discontinuous negative-stranded transcripts. In other coronaviruses, the negative strand RNA was found functionally relevant to the activation of host innate immune responses. Although the sense-mRNA architectures of SARS-CoV-2 were reported, its negative strand was unexplored. Here, we deeply sequenced both strands of RNA and found SARS-CoV-2 transcription is strongly biased to form the sense strand. During negative strand synthesis, apart from canonical sub-genomic ORFs, numerous non-canonical fusion transcripts are formed, driven by 3-15 nt sequence homology scattered along the genome but more prone to be inhibited by SARS-CoV-2 RNA polymerase inhibitor Remdesivir. The drug also represses more of the negative than the positive strand synthesis as supported by a mathematic simulation model and experimental quantifications. Overall, this study opens new sights into SARS-CoV-2 biogenesis and may facilitate the anti-viral vaccine development and drug design.\n\nOne Sentence SummaryStrand-biased transcription of SARS-CoV-2.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Marian Kalocsay", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Zoltan Maliga", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Ajit J Nirmal", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Robyn J Eisert", - "author_inst": "Harvard Medical School" - }, - { - "author_name": "Gary A Bradshaw", - "author_inst": "Harvard Medical School" + "author_name": "Yan Zhao", + "author_inst": "Southern University of Science and Technology" }, { - "author_name": "Yu-An Chen", - "author_inst": "Harvard Medical School" + "author_name": "Jing Sun", + "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff" }, { - "author_name": "Roxanne J Pelletier", - "author_inst": "Harvard Medical School" + "author_name": "Yunfei Li", + "author_inst": "Department of Biology, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China." }, { - "author_name": "Connor A Jacobson", - "author_inst": "Harvard Medical School" + "author_name": "Zhengxuan Li", + "author_inst": "Department of Biology, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China." }, { - "author_name": "Julian Mintseris", - "author_inst": "Harvard Medical School" + "author_name": "Yu Xie", + "author_inst": "Department of Biology, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China." }, { - "author_name": "Amanda J Martinot", - "author_inst": "Tufts University" + "author_name": "Ruoqing Feng", + "author_inst": "Department of Biology, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China." }, { - "author_name": "Dan H Barouch", - "author_inst": "Beth Israel Deaconess Medical Center, Ragon Institute of MGH, MIT, and Harvard" + "author_name": "Jincun Zhao", + "author_inst": "State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, the First Aff" }, { - "author_name": "Peter Sorger", - "author_inst": "Harvard University" + "author_name": "Yuhui Hu", + "author_inst": "Department of Biology, Southern University of Science and Technology, Shenzhen 518055, Guangdong, China" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "new results", - "category": "pathology" + "category": "systems biology" }, { "rel_doi": "10.1101/2020.10.14.339465", @@ -1150412,53 +1150062,37 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2020.10.13.20178483", - "rel_title": "Automated chest radiograph diagnosis: A Twofer for tuberculosis and Covid-19", + "rel_doi": "10.1101/2020.10.12.20211565", + "rel_title": "Funding and COVID-19 Research Priorities - Are the research needs for Africa being met?", "rel_date": "2020-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.13.20178483", - "rel_abs": "Coronavirus disease (Covid 19) and Tuberculosis (TB) are two challenges the world is facing. TB is a pandemic which has challenged mankind for ages and Covid 19 is a recent onset fast spreading pandemic. We study these two conditions with focus on Artificial Intelligence (AI) based imaging, the role of digital chest x-ray and utility of end to end platform to improve turnaround times. Using artificial intelligence assisted technology for triage and creation of structured radiology reports using an end to end platform can ensure quick diagnosis. Changing dynamics of TB screening in the times of Covid 19 pandemic have resulted in bottlenecks for TB diagnosis. The paper tries to outline two types of use cases, one is COVID-19 screening in a hospital-based scenario and the other is TB screening project in mobile van setting and discusses the learning of these models which have both used AI for prescreening and generating structured radiology reports.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.12.20211565", + "rel_abs": "IntroductionEmerging data from Africa indicates remarkably low numbers of reported COVID-19 deaths despite high levels of disease transmission. However evolution of these trends as the pandemic progresses remains unknown. More certain are the devastating long-term impacts of the pandemic on health and development evident globally. Research tailored to the unique needs of African countries is crucial.\n\nUKCDR and GloPID-R have launched a tracker of funded COVID-19 projects mapped to the WHO research priorities and research priorities of Africa and less-resourced countries and published a baseline analysis of a Living Systematic Review (LSR) of these projects.\n\nMethodsIn-depth analyses of the baseline LSR for COVID-19 funded research projects in Africa (as of 15th July 2020) to determine the funding landscape and alignment of the projects to research priorities of relevance to Africa.\n\nResultsThe limited COVID-19 related research across Africa appears to be supported mainly by international funding, especially from Europe, although with notably limited funding from United States-based funders. At the time of this analysis no research projects funded by an African-based funder were identified in the tracker although there are several active funding calls geared at research in Africa and there may be funding data which has not been made publicly available.\n\nMany projects mapped to the WHO research priorities and 5 particular gaps in research funding were identified namely: investigating the role of children in COVID-19 transmission; effective modes of community engagement; health systems research; communication of uncertainties surrounding mother-to-child transmission of COVID-19; and identifying ways to promote international cooperation. Capacity strengthening was identified as a dominant theme in funded research project plans.\n\nConclusionsWe found significantly lower funding investments in COVID-19 research in Africa compared to High-Income Countries, seven months into the pandemic, indicating a paucity of research targeting the research priorities of relevance to Africa.\n\nSummary Box\n\nWhat is already known?O_LIThere has been a swift global research response to the COVID-19 pandemic guided by priorities outlined in the WHO Research Roadmap and hundreds of research activities have rapidly been commissioned.\nC_LIO_LIThe research priorities for Africa are likely to be influenced by unique contextual factors which could worsen the prognosis of infections and influence measures for disease prevention and control and indirect long-term disease impacts.\nC_LIO_LIRemarkably, there has been a low number of reported COVID-19 mortalities despite emerging evidence of high levels of transmission in Africa.\nC_LI\n\nWhat are the new findings?O_LIWe present the most comprehensive assessment of COVID-19 research investments in Africa seven months into this pandemic and found significantly less research investments in Africa, given that only 84 out of 1858 research projects identified globally involved at least one African country.\nC_LIO_LISeveral important gaps in funded research in Africa were identified indicating some areas requiring greater research focus.\nC_LIO_LIThe dominant capacity strengthening theme in funded research projects highlights insufficient pandemic research preparedness of African countries.\nC_LI\n\nWhat do the new findings imply?O_LIAn assessment of the alignment of funded research projects in Africa to important global and regional research priorities is imperative for gaining key insights into the trends of disease, guiding research funding investments, prevention and control strategies and learning lessons for future pandemics.\nC_LIO_LIIn this context of limited resources, investments in research in Africa must be targeted at the most pressing research needs for effective control of this pandemic.\nC_LI", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Mitusha Verma", - "author_inst": "Nanavati Hospital" - }, - { - "author_name": "Deepak Patkar", - "author_inst": "Nanavati Hospital" - }, - { - "author_name": "Madhura Ingalhalikar", - "author_inst": "Symbiosis Center for Medical Image Analysis, Symbiosis International University" - }, - { - "author_name": "Amit Kharat", - "author_inst": "DeepTek Inc" - }, - { - "author_name": "Pranav Ajmera", - "author_inst": "Dr D Y Patil Hospital and Medical College, D Y Patil University, Pune" + "author_name": "Emilia Antonio", + "author_inst": "University of Oxford" }, { - "author_name": "Viraj Kulkarni", - "author_inst": "Deeptek Inc" + "author_name": "Moses Alobo", + "author_inst": "African Academy of Sciences" }, { - "author_name": "Aniruddha Pant", - "author_inst": "Deeptek Inc" + "author_name": "Marta Tufet-Bayona", + "author_inst": "United Kingdom Collaborative for Development Research" }, { - "author_name": "Vaishnavi Thakker", - "author_inst": "Dr D Y Patil Medical College, Hospital and Research Centre, Dr D Y Patil University, Pune" + "author_name": "Kevin Marsh", + "author_inst": "University of Oxford" }, { - "author_name": "Gunjan Naik", - "author_inst": "Deeptek Inc" + "author_name": "Alice Norton", + "author_inst": "United Kingdom Collaborative for Development Research" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1152290,39 +1151924,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.10.13.20211904", - "rel_title": "Background and concurrent factors predicting non-adherence to public health preventive measures during the chronic phase of the COVID-19 pandemic", + "rel_doi": "10.1101/2020.10.11.20210849", + "rel_title": "Post mortem pathological findings in COVID-19 cases: A Systematic Review", "rel_date": "2020-10-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.13.20211904", - "rel_abs": "To determine factors that predict non-adherence to preventive measures for COVID-19 during the chronic phase of the pandemic, a cross-sectional, general population survey was conducted in Israel. Sociodemographic, health-related, behavioral, and COVID-19-related characteristics were collected. Among 2055 participants, non-adherence was associated with male gender, young age, bachelorhood, being employed, lower decrease in income, low physical activity, psychological distress, ADHD symptoms, past risk-taking and anti-social behavior, low pro-sociality, perceived social norms favoring non-adherence, low perceived risk of COVID-19, low perceived efficacy of the preventive measures, and high perceived costs of adherence to the preventive measures. There appears to be a need for setting out and communicating preventive measures to specifically targeted at-risk populations.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.11.20210849", + "rel_abs": "BackgroundThe current COVID-19 pandemic is considered one of the most serious public health crisis over the last few decades. Although the disease can result in diverse, multiorgan pathology, there have been very few studies addressing the postmortem pathological findings of the cases. Active autopsy amid this pandemic could be an essential tool for diagnosis, surveillance, and research.\n\nObjectiveTo provide a total picture of the SARS-CoV-2 histopathological features of different body organs through a systematic search of the published literature.\n\nMethodsA systematic search of electronic databases (PubMed, ScienceDirect, Google scholar, Medrxiv & Biorxiv) was carried out from December 2019 to August, 15th 2020, for journal articles of different study designs reporting postmortem pathological findings in COVID-19 cases. PRISMA guidelines were used for reporting the review.\n\nResultsA total of 50 articles reporting 430 cases were included in our analysis. Postmortem pathological findings were reported for different body organs, pulmonary system (42 articles), cardiovascular system ( 23 articles), hepatobiliary system (22 articles), kidney (16 articles), spleen, and lymph nodes (12 articles), and central nervous system (7 articles). In lung samples, diffuse alveolar damage (DAD) was the most commonly reported findings in 239 cases (84.4%). Myocardial hypertrophy (87 cases by 51.2%), arteriosclerosis (121 cases by 62%), and steatosis ( 118 cases by 59.3%) were the most commonly reported pathological findings in the heart, kidney, and hepatobiliary system respectively.\n\nConclusionAutopsy examination as an investigation tool could help in a better understanding of SARS-CoV-2 pathophysiology, diagnosis, management, and subsequently improving patient care.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Yehuda Pollak", - "author_inst": "The Hebrew University of Jerusalem" - }, - { - "author_name": "Rachel Shoham", - "author_inst": "Talpiot College" + "author_name": "Hamed Hammoud", + "author_inst": "Community Medicine Residency Program, Department of Medical Education, Hamad Medical Corporation, Doha, Qatar." }, { - "author_name": "Haym Dayan", - "author_inst": "The Hebrew University of Jerusalem" + "author_name": "Ahmed Bendari", + "author_inst": "Department of Pathology, Research Institute of Ophthalmology, Giza, Egypt." }, { - "author_name": "Ortal Gabrieli Seri", - "author_inst": "The Hebrew University of Jerusalem" + "author_name": "Tasneem Bendari", + "author_inst": "Faculty of Medicine, Zagazig University, Zagazig, Egypt." }, { - "author_name": "Itai Berger", - "author_inst": "The Hebrew University of Jerusalem" + "author_name": "Iheb Bougmiza", + "author_inst": "Community Medicine Residency Program, Community Medicine Department, Primary Health Care Corporation, Doha, Qatar." } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "pathology" }, { "rel_doi": "10.1101/2020.10.13.20172957", @@ -1153871,25 +1153501,49 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.10.20210427", - "rel_title": "Mathematical Modeling of COVID-19 pandemic in the African continent", + "rel_doi": "10.1101/2020.10.09.20209429", + "rel_title": "Robust test and trace strategies can prevent COVID-19 resurgences: a case study from New South Wales, Australia", "rel_date": "2020-10-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.10.20210427", - "rel_abs": "The present work aims to give a contribution to the understanding of the highly infectious pandemic caused by the COVID-19 in the African continent. The study focuses on the modelling and the forecasting of COVID-19 spread in the most affected African continent, namely: Morocco, Algeria, Tunisia, Egypt and South Africa and for the sake of comparison two of the most affected European country are also considered, namely: France and Italy. To this end, an epidemiological SEIQRDP model is presented, which is an adaptation of the classic SIR model widely used in mathematical epidemiology. In order to better coincide with the preventive measures taken by the governments to deal with the spread of COVID-19, this model considers the quarantine. For the identification of the models parameters, official data of the pandemic up to August 1st, 2020 are considered. The results show that the number of infections due to the use of quarantine is expected to be very low provided the isolation is effective. However, it is increasing in some countries with the early lifting of containment. Finally, the information provided by the SEIQRDP model could help to establish a realistic assessment of the short-term pandemic situation. Moreover, this will help maintain the most appropriate and necessary public health measures after the lockdown lifting.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.09.20209429", + "rel_abs": "ObjectivesThe early stages of the COVID-19 pandemic illustrated that SARS-CoV-2, the virus that causes the disease, has the potential to spread exponentially. Therefore, as long as a substantial proportion of the population remains susceptible to infection, the potential for new epidemic waves persists even in settings with low numbers of active COVID-19 infections, unless sufficient countermeasures are in place. We aim to quantify vulnerability to resurgences in COVID-19 transmission under variations in the levels of testing, tracing, and mask usage.\n\nSettingThe Australian state of New South Wales, a setting with prolonged low transmission, high mobility, non-universal mask usage, and a well-functioning test-and-trace system.\n\nParticipantsNone (simulation study)\n\nResultsWe find that the relative impact of masks is greatest when testing and tracing rates are lower (and vice versa). Scenarios with very high testing rates (90% of people with symptoms, plus 90% of people with a known history of contact with a confirmed case) were estimated to lead to a robustly controlled epidemic, with a median of [~]180 infections in total over October 1 - December 31 under high mask uptake scenarios, or 260-1,200 without masks, depending on the efficacy of community contact tracing. However, across comparable levels of mask uptake and contact tracing, the number of infections over this period were projected to be 2-3 times higher if the testing rate was 80% instead of 90%, 8-12 times higher if the testing rate was 65%, or 30-50 times higher with a 50% testing rate. In reality, NSW diagnosed 254 locally-acquired cases over this period, an outcome that had a low probability in the model (4-7%) under the best-case scenarios of extremely high testing (90%), near-perfect community contact tracing (75-100%), and high mask usage (50-75%), but a far higher probability if any of these were at lower levels.\n\nConclusionsOur work suggests that testing, tracing and masks can all be effective means of controlling transmission. A multifaceted strategy that combines all three, alongside continued hygiene and distancing protocols, is likely to be the most robust means of controlling transmission of SARS-CoV-2.\n\nStrengths and limitations of this studyO_LIA key methodological strength of this study is the level of detail in the model that we use, which allows us to capture many of the finer details of the extent to which controlling COVID-19 transmission relies on the balance between testing, contact tracing, and mask usage.\nC_LIO_LIAnother key strength is that our model is stochastic, so we are able to quantify the probability of different epidemiological outcomes under different policy settings.\nC_LIO_LIA key limitation is the shortage of publicly-available data on the efficacy of contact tracing programs, including data on how many people were contacted for each confirmed index case of COVID-19.\nC_LI", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Nawel ARIES", - "author_inst": "Centre de Developpement des Energies Renouvelables" + "author_name": "Robyn M Stuart", + "author_inst": "Department of Mathematical Sciences, University of Copenhagen, Copenhagen, Denmark" + }, + { + "author_name": "Romesh G Abeysuriya", + "author_inst": "Disease Elimination Program, Burnet Institute, Melbourne, Victoria, Australia" + }, + { + "author_name": "Cliff C Kerr", + "author_inst": "Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, USA" + }, + { + "author_name": "Dina Mistry", + "author_inst": "Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, USA" + }, + { + "author_name": "Daniel J Klein", + "author_inst": "Institute for Disease Modeling, Global Health Division, Bill & Melinda Gates Foundation, Seattle, USA" }, { - "author_name": "Houdayfa OUNIS", - "author_inst": "Institut de Recherche Dupuy de Lome,CNRS UMR 6027, IRDL, Lorient F-56100, France" + "author_name": "Richard Gray", + "author_inst": "The Kirby Institute, UNSW Sydney, Sydney, New South Wales, Australia" + }, + { + "author_name": "Margaret Hellard", + "author_inst": "Disease Elimination Program, Burnet Institute, Melbourne, Victoria, Australia" + }, + { + "author_name": "Nick Scott", + "author_inst": "Disease Elimination Program, Burnet Institute, Melbourne, Victoria, Australia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1156197,25 +1155851,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.08.20208991", - "rel_title": "Covid Pandemic Analysis using Regression", + "rel_doi": "10.1101/2020.10.09.20209981", + "rel_title": "The risk for a new COVID-19 wave -- and how it depends on $R_0$, the current immunity level and current restrictions", "rel_date": "2020-10-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.08.20208991", - "rel_abs": "Covid-19 is a pandemic which has affected all parts of the world. Covid-19 is a pandemic which can be controlled only by maintaining social distancing, proper hygiene, wearing mask, hand sanitation and to a extend by wearing face shield. Even though each state has followed their own ways of controlling the infection, awareness among citizens and behaving as responsible citizens is very important in controlling this disease. Contact tracing plays an important role in controlling this pandemic. This paper deals with the effect of Covid-19 in various states of India and also forecasts its effect using machine learning techniques. Regression analysis like Linear and polynomial have been used for analysis of Covid-19, where Kaggle dataset has been used. This helps in understanding the much-affected states in India and helps to understand the infrastructure requirements to handle this pandemic efficiently.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.09.20209981", + "rel_abs": "The COVID-19 pandemic has hit different parts of the world differently: some regions are still in the rise of the first wave, other regions are now facing a decline after a first wave, and yet other regions have started to see a second wave. The current immunity level i in a region is closely related to the cumulative fraction infected, which primarily depends on two factors: a) the initial potential for COVID-19 in the region (often quantified by the basic reproduction number R0), and b) the timing, amount and effectiveness of preventive measures put in place. By means of a mathematical model including heterogeneities owing to age, social activity and susceptibility, and allowing for time-varying preventive measures, the risk for a new epidemic wave and its doubling time, and how they depend on R0, i and the overall effect of the current preventive measures, are investigated. Focus lies on quantifying the minimal overall effect of preventive measures pMin needed to prevent a future outbreak. The first result shows that the current immunity level i plays a more influential roll than when immunity is obtained from vaccination. Secondly, by comparing regions with different R0 and i it is shown that regions with lower R0 and low i may now need higher preventive measures (pMin) compared with other regions having higher R0 but also higher i, even when such immunity levels are far from herd immunity.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Raji P", - "author_inst": "NMIT" + "author_name": "Tom Britton", + "author_inst": "Stockholm University" + }, + { + "author_name": "Pieter Trapman", + "author_inst": "Stockholm University" }, { - "author_name": "Deeba Lakshmi G R", - "author_inst": "NMIT" + "author_name": "Frank G Ball", + "author_inst": "University of Nottingham" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1157638,199 +1157296,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.10.20210492", - "rel_title": "Transmission of SARS-CoV-2 from Children and Adolescents", + "rel_doi": "10.1101/2020.10.11.20210773", + "rel_title": "Summer School Holidays and the Growth Rate in Sars-CoV-2 Infections Across German Districts", "rel_date": "2020-10-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.10.20210492", - "rel_abs": "A better understanding of SARS-CoV-2 transmission from children and adolescents is crucial for informing public health mitigation strategies. We conducted a retrospective cohort study among household contacts of primary cases defined as children and adolescents aged 719 years with laboratory evidence of SARS-CoV-2 infection acquired during an overnight camp outbreak. Among household contacts, we defined secondary cases using the Council of State and Territorial Epidemiologists definition. Among 526 household contacts of 224 primary cases, 48 secondary cases were identified, corresponding to a secondary attack rate of 9% (95% confidence interval [CI], 7%-12%). Our findings show that children and adolescents can transmit SARS-CoV-2 to adult contacts and other children in a household setting.", - "rel_num_authors": 45, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.11.20210773", + "rel_abs": "ObjectivesTo estimate the effect that summer school holidays had on the growth rate in Sars-CoV-2 infections across German districts. The Robert-Koch-Institute reports that during the summer holiday period a foreign country is stated as the most likely place of infection for an average of 27 and a maximum of 49 percent of new Sars-CoV-2 infections in Germany. Yet, infection may have taken place elsewhere, not all international travel is holiday-related and any impact of holiday-related travel will not be restricted to holidays abroad.\n\nDesignCross-sectional study on observational data. In Germany, summer school holidays are coordinated between states and spread out over 13 weeks. We analyse the association between these holidays and the weekly infection growth rate in SARS-CoV-2 infections across 401 German districts. Employing a dynamic model with district fixed effects, we test whether the holiday season results in a statistically significantly higher infection growth rate than the period of two weeks before holidays start, our presumed counterfactual.\n\nResultsWe find effects of the holiday period equal in size to almost 50 percent of the average district growth rate in new infections in Germany during their respective final week of holidays and the two weeks after holidays end. States in the West of Germany tend to experience stronger effects than those in the East. This is consistent with another result, namely that we find statistically significant interaction effects of school holidays with per capita taxable income and the share of foreign residents in a districts population, with both factors hypothesised to increase holiday-related travels.\n\nConclusionsOur results suggest that changed behaviour during the holiday season accelerated the pandemic and made it considerably more difficult for public health authorities to contain the spread of the virus by means of contact tracing. Governments did not prepare adequately or timely for this acceleration.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Victoria T. Chu", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Anna R. Yousaf", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Karen Chang", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Noah Schwartz", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Clinton McDaniel", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Christine Szablewski", - "author_inst": "Georgia Department of Public Health" - }, - { - "author_name": "Marie Brown", - "author_inst": "Georgia Department of Public Health" - }, - { - "author_name": "Kathryn Winglee", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Scott Lee", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Zhaohui Cui", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Adebola Adebayo", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Tiffiany Aholou", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Minal Amin", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Peter Aryee", - "author_inst": "Georgia Department of Public Health" - }, - { - "author_name": "Cindy Castaneda", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Trudy Chambers", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Amy Fleshman", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Christin Goodman", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Tony Holmes", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Asha Ivey-Stephenson", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Emiko Kamitani", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Susan Katz", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jennifer Knapp", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Maureen Kolasa", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Maranda Lumsden", - "author_inst": "Georgia Department of Public Health" - }, - { - "author_name": "Erin Mayweather", - "author_inst": "Georgia Department of Public Health" - }, - { - "author_name": "Asfia Mohammed", - "author_inst": "Georgia Department of Public Health" - }, - { - "author_name": "Anne Moorman", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Alpa Patel-Larson", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Lara Perinet", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Mark Pilgard", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Deirdre Pratt", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Shanica Railey", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jaina Shah", - "author_inst": "Georgia Department of Public Health" - }, - { - "author_name": "Dawn Tuckey", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Emilio Dirlikov", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Dale Rose", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Julie Villanueva", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Alicia Fry", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Aron Hall", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Hannah Kirking", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Jacqueline Tate", - "author_inst": "Centers for Disease Control and Prevention" - }, - { - "author_name": "Cherie Drenzek", - "author_inst": "Georgia Department of Public Health" - }, - { - "author_name": "Tatiana Lanzieri", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Thomas Pluemper", + "author_inst": "Vienna University of Economics and Business" }, { - "author_name": "Rebekah Stewart", - "author_inst": "Centers for Disease Control and Prevention" + "author_name": "Eric Neumayer", + "author_inst": "London School of Economics and Political Science" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.10.12.335083", @@ -1159572,49 +1159058,49 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.06.20208025", - "rel_title": "Enoxaparin is associated with lower rates of thrombosis, kidney injury, and mortality than Unfractionated Heparin in hospitalized COVID patients", + "rel_doi": "10.1101/2020.10.09.20210302", + "rel_title": "Polyester Nasal Swabs Collected in a Dry Tube are a Robust and Inexpensive, Minimal Self-Collection Kit for SARS-CoV-2 Testing", "rel_date": "2020-10-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.06.20208025", - "rel_abs": "Although anticoagulants such as unfractionated heparin and low molecular weight heparin (LMWH, e.g. enoxaparin) are both being used for therapeutic mitigation of COVID associated coagulopathy (CAC), differences in their clinical outcomes remain to be investigated. Here, we employ automated neural networks supplemented with expert curation ( augmented curation) for retrospectively analyzing the complete electronic health records (EHRs) of 671 hospitalized COVID-19 patients administered either enoxaparin or unfractionated heparin, but not both. We find that COVID-19 patients administered unfractionated heparin but not enoxaparin have higher rates of mortality (risk ratio: 2.6; 95% C.I.: [1.2-5.4]; p-value: 0.02; BH adjusted p-value: 0.09), thrombotic events (risk ratio: 5.7, 95% C.I.: [2.1, 33.9], p-value: 0.024), acute kidney injury (risk ratio: 5.5; 95% C.I.: [1.2-17.7]; p-value: 0.02; BH adjusted p-value: 0.10), and bacterial pneumonia (risk ratio undefined; 95% C.I.: [1.0, 292]; p-value:0.02; BH adjusted p-value:0.10), compared to patients administered enoxaparin but not unfractionated heparin. Notably, even after controlling for potential confounding factors such as demographics, comorbidities, admission diagnosis, initial ICU status, and initial level of oxygen support, the above differences between the enoxaparin and unfractionated heparin patient cohorts remain statistically significant. This study emphasizes the need for mechanistically investigating differential modulation of the COVID-associated coagulation cascades by enoxaparin versus unfractionated heparin.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.09.20210302", + "rel_abs": "BackgroundPolyester nasal swabs stored in saline or in a dry tube were evaluated as an alternative to foam nasal swabs for SARS-CoV-2 testing by reverse transcription quantitative polymerase chain reaction (RT-qPCR) since they may be inexpensively manufactured at high capacity.\n\nMethodsSurrogate clinical specimens were prepared by inoculating foam and polyester nasal swabs with residual SARS-CoV-2 positive clinical specimens diluted in porcine or human matrix. Dry swab elution with phosphate buffered saline (PBS) was evaluated by vortex, swab swirling, and passive methodologies. Surrogate and clinical nasal specimen stability were evaluated at refrigerated (4{degrees}C) and elevated temperatures (40{degrees}C for 12 hours, 32{degrees}C hold) through 72 hours.\n\nResultsPolyester swabs demonstrated equivalent performance to foam swabs for detection of low and high SARS-CoV-2 viral loads. Dry swab elution performed with PBS and mechanical disruption by vortex resulted in nearly complete quantitative recovery of virus. Dry polyester and foam surrogate specimens were stable through 72 hours both when refrigerated and after high temperature excursion, which simulated specimen transport without cold chain. Similarly, clinical specimens collected with polyester swabs and stored dry were stable through 72 hours in the presence and absence of cold chain. Polyester surrogate specimens stored in saline were stable through 72 hours refrigerated but only through 48 hours at elevated temperatures.\n\nConclusionsPolyester nasal swabs stored in dry collection tubes comprise a robust and inexpensive self-collection method for SARS-CoV-2 viral load testing, which is stable under conditions required for home collection and shipment to the laboratory.", "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Colin Pawlowski", - "author_inst": "nference" + "author_name": "James Douglas Rains", + "author_inst": "Quantigen Biosciences" }, { - "author_name": "AJ Venkatakrishnan", - "author_inst": "nference" + "author_name": "Leah R Padgett", + "author_inst": "Quantigen Biosciences" }, { - "author_name": "Christian Kirkup", - "author_inst": "nference" + "author_name": "Charlotte L Ahls", + "author_inst": "Quantigen Biosciences" }, { - "author_name": "Gabriela Berner", - "author_inst": "nference" + "author_name": "Delini K Samarasinghe", + "author_inst": "Quantigen Biosciences" }, { - "author_name": "Arjun Puranik", - "author_inst": "nference" + "author_name": "Michelle L Wallander", + "author_inst": "Sciest LLC" }, { - "author_name": "John C O'Horo", - "author_inst": "Mayo Clinic" + "author_name": "Lauren A Kennington", + "author_inst": "Quantigen Biosciences" }, { - "author_name": "Andrew D Badley", - "author_inst": "Mayo Clinic" + "author_name": "Yuan-Po Tu", + "author_inst": "The Everett Clinic --Part of Optum" }, { - "author_name": "Venky Soundararajan", - "author_inst": "nference" + "author_name": "James S Elliott", + "author_inst": "Quantigen Biosciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1161246,59 +1160732,99 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.10.07.20208280", - "rel_title": "A high-throughput microfluidic nano-immunoassay for detecting anti-SARS-CoV-2 antibodies in serum or ultra-low volume dried blood samples", + "rel_doi": "10.1101/2020.10.09.333278", + "rel_title": "Major role of IgM in the neutralizing activity of convalescent plasma against SARS-CoV-2", "rel_date": "2020-10-09", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.07.20208280", - "rel_abs": "Novel technologies are needed to facilitate large-scale detection and quantification of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) specific antibodies in human blood samples. Such technologies are essential to support seroprevalence studies, vaccine clinical trials, and to monitor quality and duration of immunity. We developed a microfluidic nano-immunnoassay for the detection of anti-SARS-CoV-2 IgG antibodies in 1024 samples per device. The method achieved a specificity of 100% and a sensitivity of 98% based on the analysis of 289 human serum samples. To eliminate the need for venipuncture, we developed low-cost, ultra-low volume whole blood sampling methods based on two commercial devices and repurposed a blood glucose test strip. The glucose test strip permits the collection, shipment, and analysis of 0.6 {micro}L whole blood easily obtainable from a simple fingerprick. The nano-immunoassay platform achieves high-throughput, high sensitivity and specificity, negligible reagent consumption, and a decentralized and simple approach to blood sample collection. We expect this technology to be immediately applicable to current and future SARS-CoV-2 related serological studies and to protein biomarker diagnostics in general.", - "rel_num_authors": 10, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.10.09.333278", + "rel_abs": "Characterization of the humoral response to SARS-CoV-2, the etiological agent of Covid-19, is essential to help control the infection. In this regard, we and others recently reported that the neutralization activity of plasma from COVID-19 patients decreases rapidly during the first weeks after recovery. However, the specific role of each immunoglobulin isotype in the overall neutralizing capacity is still not well understood. In this study, we selected plasma from a cohort of Covid-19 convalescent patients and selectively depleted immunoglobulin A, M or G before testing the remaining neutralizing capacity of the depleted plasma. We found that depletion of immunoglobulin M was associated with the most substantial loss of virus neutralization, followed by immunoglobulin G. This observation may help design efficient antibody-based COVID-19 therapies and may also explain the increased susceptibility to SARS-CoV-2 of autoimmune patients receiving therapies that impair the production of IgM.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Zoe Swank", - "author_inst": "Ecole Polytechnique Federale de Lausanne" + "author_name": "Romain Gasser", + "author_inst": "Universite de Montreal" }, { - "author_name": "Gr\u00e9goire Michielin", - "author_inst": "Ecole Polytechnique Federale de Lausanne" + "author_name": "Marc Cloutier", + "author_inst": "Hema-Quebec" }, { - "author_name": "Hon Ming Yip", - "author_inst": "Ecole Polytechnique Federale de Lausanne" + "author_name": "Jeremie Prevost", + "author_inst": "Universite de Montreal" }, { - "author_name": "Patrick Cohen", - "author_inst": "University of Geneva Hospitals" + "author_name": "Corby Fink", + "author_inst": "University of Western Ontario" }, { - "author_name": "Diego O. Andrey", - "author_inst": "University of Geneva Hospitals" + "author_name": "Eric Ducas", + "author_inst": "Hema-Quebec" }, { - "author_name": "Nicolas Vuilleumier", - "author_inst": "University of Geneva Hospitals" + "author_name": "Shilei Ding", + "author_inst": "CRCHUM" }, { - "author_name": "Laurent Kaiser", - "author_inst": "University of Geneva Hospitals" + "author_name": "Nathalie Dussault", + "author_inst": "Hema-Quebec" }, { - "author_name": "Isabella Eckerle", - "author_inst": "University of Geneva Hospitals" + "author_name": "Patricia Landry", + "author_inst": "Hema-Quebec" }, { - "author_name": "Benjamin Meyer", - "author_inst": "University of Geneva" + "author_name": "Tony Tremblay", + "author_inst": "Hema-Quebec" }, { - "author_name": "Sebastian J. Maerkl", - "author_inst": "Ecole Polytechnique Federale de Lausanne" + "author_name": "Audrey Laforce-Lavoie", + "author_inst": "Hema-Quebec" + }, + { + "author_name": "Antoine Lewin", + "author_inst": "Hema-Quebec" + }, + { + "author_name": "Guillaume Beaudoin-Bussieres", + "author_inst": "Universite de Montreal" + }, + { + "author_name": "Annemarie Laumaea", + "author_inst": "Universite de Montreal" + }, + { + "author_name": "Halima Medjahed", + "author_inst": "CRCHUM" + }, + { + "author_name": "Catherine Larochelle", + "author_inst": "Universite de Montreal" + }, + { + "author_name": "Jonathan Richard", + "author_inst": "Centre de Recherche du CHUM" + }, + { + "author_name": "Gregory A Dekaban", + "author_inst": "University of Western Ontario" + }, + { + "author_name": "Jimmy D Dikeakos", + "author_inst": "University of Western Ontario" + }, + { + "author_name": "Renee Bazin", + "author_inst": "Hema-Quebec" + }, + { + "author_name": "Andres Finzi", + "author_inst": "Universite de Montreal" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.10.09.332692", @@ -1162803,57 +1162329,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.10.02.20205674", - "rel_title": "Mental health symptoms in a cohort of hospital healthcare workers following the first peak of the Covid-19 pandemic in the United Kingdom.", + "rel_doi": "10.1101/2020.10.05.20207423", + "rel_title": "Psychiatric side effects induced by chloroquine and hydroxychloroquine: a systematic review of case reports and population studies", "rel_date": "2020-10-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.02.20205674", - "rel_abs": "BackgroundThe Covid-19 pandemic is likely to lead to a significant increase in mental health disorders amongst healthcare workers (HCW).\n\nAimsWe evaluated the prevalence of anxiety, depressive and post-traumatic stress disorder (PTSD) symptoms in a HCW population in the United Kingdom (UK), to identify subgroups most at risk.\n\nMethodsAn electronic survey was conducted between the 05/06/2020 and 31/07/2020 of all hospital HCW in the West Midlands, UK using clinically validated questionnaires: Patient Health Questionnaire-4 (PHQ-4) and the Impact of Event Scale-Revised (IES-R). Univariate analyses and adjusted logistic regression analyses were performed to estimate the strengths in associations.\n\nResultsThere were 2638 eligible participants who completed the survey (female: 79.5%, median age: 42 [IQR: 32-51] years). The prevalence rates of clinically significant symptoms of anxiety, depression and PTSD were 34.3%, 31.2% and 24.5% respectively. In adjusted analysis a history of mental health conditions was associated with clinically significant symptoms of anxiety (odds ratio 2.3 [95% CI 1.9-2.7]; p<0.001), depression (2.5 [2.1-3.0]; p<0.001) and PTSD (2.1 [1.7-2.5]; p<0.001). The availability of adequate personal protective equipment (PPE), wellbeing support and lower exposure to moral dilemmas at work demonstrated significant negative associations with former symptoms (p[≤]0.001).\n\nConclusionsWe report a high prevalence of clinically significant symptoms of anxiety, depression and PTSD in hospital HCW following the initial Covid-19 pandemic peak in the UK. Those with a history of mental health conditions were most at risk. Adequate PPE availability, access to wellbeing support and reduced exposure to moral dilemmas may protect hospital HCW from mental health symptoms.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.05.20207423", + "rel_abs": "Chloroquine and hydroxychloroquine are commonly used drugs in the treatment of malaria as well as chronic diseases, such as rheumatoid arthritis, and systemic lupus erythematosus. Although various reports on possible psychiatric side effects of these drugs exist, the nature and extent of these effects remain poorly understood. Moreover, the relevance of these drugs in the treatment of early stages of COVID-19 necessitates a careful estimation of their side effects. Here, we provide a systematic review of the psychiatric side effects associated with chloroquine and hydroxychloroquine. We used PubMed, Scopus, and Web of Science platforms to identify relevant literature published between 1962 and 2020. Search terms included chloroquine, hydroxychloroquine, psychiatry, psychosis, depression, anxiety, bipolar disorder, delirium, and psychotic disorders. Only case reports and clinical trials were included. All studies included records of psychiatric side effects induced by either chloroquine or hydroxychloroquine or both. Both retrospective and prospective, randomized as well as non-randomized population studies were included. Overall, the psychiatric side effects are dose- and sex-independent. The most common psychiatric side effects reported are increased speech output/ excessive talking, increased psychomotor activity, irritable mood, auditory hallucinations, delusion of grandiosity, and suicide attempts, likely due to brain intoxicationbe of chloroquine or hydroxychloroquine. The symptoms can develop in a few hours to 11 weeks after drug intake and are normally reversed within a week after the drug withdrawal. We conclude that CQ and HCQ have the potential to induce psychiatric side effects. This study calls for further investigation of psychiatric symptoms induced by these drugs in the short and long term.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Kasun Wanigasooriya", - "author_inst": "University of Birmingham" + "author_name": "Fernanda Talarico", + "author_inst": "Department of Psychiatry, University of Alberta" }, { - "author_name": "Priyanka Palimar", - "author_inst": "Forward Thinking Birmingham" + "author_name": "Sucheta Chakravarty", + "author_inst": "Department of Psychology, University of Alberta" }, { - "author_name": "David Naumann", - "author_inst": "University Hospitals Birmingham NHS Foundation Trust" - }, - { - "author_name": "Khalida Ismail", - "author_inst": "King's College London" - }, - { - "author_name": "Jodie L. Fellows", - "author_inst": "University Hospitals Birmingham NHS Foundation Trust" - }, - { - "author_name": "Peter Logan", - "author_inst": "Walsall Healthcare NHS Trust" - }, - { - "author_name": "Christopher V. Thompson", - "author_inst": "Sandwell and West Birmingham Hospitals NHS Trust" + "author_name": "Yang Liu", + "author_inst": "Department of Psychiatry, University of Alberta" }, { - "author_name": "Helen Bermingham", - "author_inst": "University Hospitals Birmingham NHS Foundation Trust" + "author_name": "Angrew Greenshaw", + "author_inst": "Department of Psychiatry, University of Alberta" }, { - "author_name": "Andrew D. Beggs", - "author_inst": "University of Birmingham" + "author_name": "Ives Passos", + "author_inst": "Programa de Pos-Graduacao em Psiquiatria e Ciencias do Comportamento, Laboratory of Molecular Psychiatry and Bipolar Disorder Program, Hospital de Clinicas de P" }, { - "author_name": "Tariq Ismail", - "author_inst": "University Hospitals Birmingham NHS Foundation Trust" + "author_name": "Bo Cao", + "author_inst": "Department of Psychiatry, University of Alberta" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "psychiatry and clinical psychology" }, @@ -1164489,33 +1163999,37 @@ "category": "health economics" }, { - "rel_doi": "10.1101/2020.10.05.20206920", - "rel_title": "Development of a customised data management system for a COVID-19-adapted colorectal cancer pathway", + "rel_doi": "10.1101/2020.10.04.20206516", + "rel_title": "Rationale and prognosis of repurposed drugs with risk stratification of patients in oxygen support in COVID-19: A systematic review and meta-analysis", "rel_date": "2020-10-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.05.20206920", - "rel_abs": "PurposeThe COVID-19 pandemic posed an unprecedented challenge to healthcare systems around the world. To mitigate the risks of those referred with possible colorectal cancer during the pandemic we implemented a clinical pathway which required a customised data management system for robust operation. Here, we describe the principal concepts and evaluation of the performance of a spreadsheet-based data management system.\n\nMethodsA system was developed using Microsoft Excel(R) 2007 aiming to retain the spreadsheets inherent intuitiveness of direct data entry. Data was itemised limiting entry errors. Visual Basic for Applications (VBA) was used to construct a user-friendly interface to enhance efficiency of data entry and segregate the data required for operational tasks. This was done with built-in loop-back data entry. Finally data derivation and analysis was performed to facilitate pathway monitoring.\n\nResultsFor a pathway which required rapid implementation and development of a customised data management system, the use of a spreadsheet was advantageous due to its user-friendly direct data entry capability. Its function was enhanced by UserForm and large data handling by data segregation using VBA macros. Data validation and conditional formatting minimised data entry errors. Computation by the COUNT function facilitated live data monitoring on a dashboard. During the three months the pathway ran for, the system processed 36 nodal data points for each of the included 837 patients. Data monitoring confirmed its accuracy.\n\nConclusionLarge volume data management using a spreadsheet system is possible with appropriate data definition and VBA programmed data segregation. Clinicians regular input and optimisation made the system adaptable for rapid implementation.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.04.20206516", + "rel_abs": "BackgroundThe rising number of trials on repurposed dugs in COVID-19 has led to duplication and a need for curation of available outcomes from treatments that have been followed across the world. We have conducted a systematic review and meta-analysis that focus on evaluating the clinical outcomes of repurposed interventions against COVID-19.\n\nMethodsRandom effects model was adopted to estimate overall treatment effect and heterogeneity. Meta- regression was performed to study the correlation between comorbid conditions and non- invasive or invasive ventilation requirement.\n\nResultsTwenty-nine articles met our eligibility criteria. In subgroup analysis, Tocilizumab was highly significant with lower mortality rate (OR 27.50; 95%CI [5.39-140.24]) of severe COVID-19 patients. Hydroxychloroquine and Lopinavir-ritonavir was found to be inefficacious in severe patients (OR 0.64; 95%CI [0.47-0.86] and 1.40 [0.71-2.76]). Dexamethasone had marginal effect on overall mortality rate (OR 1.19; 95%CI [1.05-1.35]). The meta-regression shows a positive correlation between prevalence of patients on Tocilizumab in non invasive support and hypertension condition (P = 0.02), whereas a negative correlation was identified with patients having lung disease (P = 0.03).\n\nConclusionOverall, our study confirmed that tocilizumab may probably reduce the mortality rate (<10%) of severe COVID-19 patients than other interventions. Further, reduce the risk of requiring non- invasive ventilator support in patients with comorbid condition of lung disease. Hydroxychloroquine and Lopinavir-ritonavir has no clinical benefits in severe COVID-19. A high quality evidence is required to evaluate the usage of Serpin + Favipiravir combination in severe or critical COVID-19.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Frances Gunn", - "author_inst": "1.\tDepartment of Colorectal Surgery, Western General Hospital, Edinburgh, United Kingdom" + "author_name": "Esther Jebarani Elangovan", + "author_inst": "Anna University" }, { - "author_name": "Janice Miller", - "author_inst": "1.\tDepartment of Colorectal Surgery, Western General Hospital, Edinburgh, United Kingdom, 2. Clinical Surgery, University of Edinburgh, Edinburgh, United Kingdo" + "author_name": "Vanitha Shyamili Kumar", + "author_inst": "IIT Madras" }, { - "author_name": "Malcolm G Dunlop", - "author_inst": "Institute of Genetics and Molecular Medicine" + "author_name": "Adhithyan Kathiravan", + "author_inst": "IIT-Madras" }, { - "author_name": "Farhat V N Din", - "author_inst": "1.\tDepartment of Colorectal Surgery, Western General Hospital, Edinburgh, United Kingdom 2.\tClinical Surgery, University of Edinburgh, Edinburgh, United Kingdo" + "author_name": "Raghav Mallampalli", + "author_inst": "IIT-Madras" }, { - "author_name": "Yasuko Maeda", - "author_inst": "Western General Hospital and University of Edinburgh" + "author_name": "Tiju Thomas", + "author_inst": "Indian Institute of Technology Madras" + }, + { + "author_name": "Gnanasambandam Subramaniyam", + "author_inst": "Madras medical college" } ], "version": "1", @@ -1165859,39 +1165373,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.10.06.20207662", - "rel_title": "Which factors should be included in triage? An online survey of the attitudes of the UK general public to pandemic triagedilemmas", + "rel_doi": "10.1101/2020.09.25.20199562", + "rel_title": "Pathogenesis-based pre-exposure prophylaxis associated with low risk of SARS-CoV-2 infection in healthcare workers at a designated Covid-19 hospital", "rel_date": "2020-10-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.06.20207662", - "rel_abs": "ObjectiveAs cases of COVID-19 infections surge, concerns have renewed about intensive care units (ICU) being overwhelmed and the need for specific triage protocols over winter. This study aimed to help inform triage guidance by exploring the view of lay people about factors to include in triage decisions.\n\nDesign, setting and participantsOnline survey between 29th May and 22nd June 2020 based on hypothetical triage dilemmas. Participants recruited from existing market research panels, representative of the UK general population. Scenarios were presented in which a single ventilator is available, and two patients require ICU admission and ventilation. Patients differed in one of: chance of survival, life expectancy, age, expected length of treatment, disability, and degree of frailty. Respondents were given the option of choosing one patient to treat, or tossing a coin to decide.\n\nResultsSeven hundred and sixty-three participated. A majority of respondents prioritized patients who would have a higher chance of survival (72-93%), longer life expectancy (78-83%), required shorter duration of treatment (88-94%), were younger (71-79%), or had a lesser degree of frailty (60-69% all p< .001). Where there was a small difference between two patients, a larger proportion elected to toss a coin to decide which patient to treat. A majority (58-86%) were prepared to withdraw treatment from a patient in intensive care who had a lower chance of survival than another patient currently presenting with COVID-19. Respondents also indicated a willingness to give higher priority to healthcare workers and to patients with young children.\n\nConclusionMembers of the UK general public potentially support a broadly utilitarian approach to ICU triage in the face of overwhelming need. Survey respondents endorsed the relevance of patient factors currently included in triage guidance, but also factors not currently included. They supported the permissibility of reallocating treatment in a pandemic.\n\nBMJI, the Submitting Author has the right to grant and does grant on behalf of all authors of the Work (as defined in the below author licence), an exclusive licence and/or a non-exclusive licence for contributions from authors who are: i) UK Crown employees; ii) where BMJ has agreed a CC-BY licence shall apply, and/or iii) in accordance with the terms applicable for US Federal Government officers or employees acting as part of their official duties; on a worldwide, perpetual, irrevocable, royalty-free basis to BMJ Publishing Group Ltd (\"BMJ\") its licensees and where the relevant Journal is co-owned by BMJ to the co-owners of the Journal, to publish the Work in this journal and any other BMJ products and to exploit all rights, as set out in our licence.\n\nThe Submitting Author accepts and understands that any supply made under these terms is made by BMJ to the Submitting Author unless you are acting as an employee on behalf of your employer or a postgraduate student of an affiliated institution which is paying any applicable article publishing charge (\"APC\") for Open Access articles. Where the Submitting Author wishes to make the Work available on an Open Access basis (and intends to pay the relevant APC), the terms of reuse of such Open Access shall be governed by a Creative Commons licence - details of these licences and which Creative Commons licence will apply to this Work are set out in our licence referred to above.\n\nOther than as permitted in any relevant BMJ Authors Self Archiving Policies, I confirm this Work has not been accepted for publication elsewhere, is not being considered for publication elsewhere and does not duplicate material already published. I confirm all authors consent to publication of this Work and authorise the granting of this licence.\n\nArticle SummaryO_ST_ABSStrengths and Limitations of this studyC_ST_ABSO_LIFirst UK survey to investigate public attitudes to pandemic triage dilemmas\nC_LIO_LILarge survey, representative of the UK general population\nC_LIO_LIEnables comparison of ethical arguments and existing guidance with the views of the public\nC_LIO_LIIdentifies relevance of specific patient factors in concrete forced choice dilemmas: may be helpful in development or revision of triage policies\nC_LIO_LISurvey findings do not allow assessment of relative weight of different factors\nC_LI", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.25.20199562", + "rel_abs": "At present, no agents are known to be effective in preventing Covid-19. Based on current knowledge of the pathogenesis of this disease, we suggest that SARS-CoV-2 infection might be attenuated by directly maintaining innate pulmonary redox, metabolic and dilation functions using well-tolerated medications that are known to serve these functions, specifically, using a low dose aerosolized combination of glutathione, inosine and potassium. From June 1 to July 10, 2020, we conducted a low-intervention open-label single-centre study to evaluate safety and efficacy of pre-exposure prophylaxis (PrEP) with the aerosolized combination medications (ACM) on SARS-CoV-2 incidence in 99 healthcare workers (HCWs) at a hospital that was designated to treat Covid-19 patients. We also retrospectively compared SARS-CoV-2 incidence in the ACM users to that in 268 untreated HCWs at the same hospital. Eligible participants received an aerosolized combination of 21.3 mg/ml glutathione, 8.7 mg/ml inosine in 107 mM potassium solution for 14 days. The main outcome was the frequency of laboratory confirmed SARS-CoV-2 cases, defined as individuals with positive genetic or immunological tests within 28 days of the study period. During the PrEP period, solicited adverse events occurred in five participants; all were mild and transient reactions. SARS-CoV-2 was detected in 2 ACM users (2%, 95% CI: 0.3% to 7.1%), which was significantly less than the incidence in 24 nonusers (9%, 95% CI: 5.8% to 13.0%; P = 0.02). Our findings might be used either to prevent SARS-CoV-2 infection, or to support ongoing and new research into more effective treatments for Covid-19. The study was registered with rosrid.ru, AAAA-A20-120061690058-2, and isrctn.com, ISRCTN34160010.", "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Dominic Wilkinson", - "author_inst": "University of Oxford" + "author_name": "Michael V. Dubina", + "author_inst": "State Research Institute of Highly Pure Bioprepartions" }, { - "author_name": "Hazem Zohny", - "author_inst": "University of Oxford" + "author_name": "Veronika V. Gomonova", + "author_inst": "North-Western State Medical University named after I.I. Mechnikov" }, { - "author_name": "Andreas Kappes", - "author_inst": "City, University of London" + "author_name": "Anastasia E. Taraskina", + "author_inst": "North-Western State Medical University named after I.I. Mechnikov" }, { - "author_name": "Walter Sinnott-Armstrong", - "author_inst": "Duke University" + "author_name": "Natalia V. Vasilyeva", + "author_inst": "North-Western State Medical University named after I.I. Mechnikov" }, { - "author_name": "Julian Savulescu", - "author_inst": "University of Oxford" + "author_name": "Sergey A. Sayganov", + "author_inst": "North-Western State Medical University named after I.I. Mechnikov" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "medical ethics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.09.29.20204164", @@ -1167365,57 +1166879,45 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.10.03.20205278", - "rel_title": "Validation of self-collected buccal swab and saliva as a diagnostic tool for COVID-19", + "rel_doi": "10.1101/2020.10.02.20205724", + "rel_title": "COVID-19 severity in asthma patients: A multi-center matched cohort study", "rel_date": "2020-10-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.03.20205278", - "rel_abs": "BackgroundEffective management of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) requires large-scale testing. Collection of nasopharyngeal swab (NPS) by healthcare workers (HCW) is currently used to diagnose SARS-CoV-2, which increases the risk of transmission to HCWs. Self-administered saliva and buccal swabs are convenient, painless and safe alternative sample collection methods.\n\nMethodsA cross-sectional single centre study was conducted on 42 participants who were tested positive for SARS-CoV-2 via NPS within the past 7 days. A self-collected saliva and buccal swab and a HCW-collected NPS were obtained. Real-time polymerase chain reaction (RT-PCR) was performed and cycle threshold (CT) values were obtained. Positive percent agreement (PPA), negative percent agreement (NPA) and overall agreement (OA) were calculated for saliva and buccal swabs, as compared with NPS.\n\nResultsAmong the 42 participants, 73.8% (31/42) tested positive via any one of the 3 tests. With reference to NPS, the saliva test had PPA 66.7%, NPA 91.7% and OA 69.0%. The buccal swab had PPA 56.7%, NPA 100% and OA 73.8%. Presence of symptoms improved diagnostic accuracy. There was no statistically significant association between CT values and duration of symptom onset within the first 12 days of symptoms for all three modalities.\n\nConclusionSelf-collected saliva tests and buccal swabs have only moderate agreement with HCW-collected NPS swabs. Primary screening for SARS-CoV-2 may be performed with a saliva test or buccal swab, with a negative test warranting a confirmatory NPS to avoid false negatives. This combined strategy minimizes discomfort and reduces the risk of spread to the community and HCWs.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.02.20205724", + "rel_abs": "ObjectiveThe evidence pertaining to the effects of asthma on Coronavirus disease 2019 outcomes has been unclear. To improve our understanding of the clinically important association of asthma and Coronavirus disease 2019.\n\nMethodsA matched cohort study was performed using data from the Mass General Brigham Health Care System (Boston, MA). Adult (age [≥] 18 years) patients with confirmed Coronavirus disease 2019 and without chronic obstructive pulmonary disease, cystic fibrosis, or interstitial lung disease between March 4, 2020 and July 2, 2020 were analyzed. Up to 5 non-asthma comparators were matched to each asthma patient based on age (within 5 years), sex, and date of positive test (within 7 days). The primary outcomes were hospitalization, mechanical ventilation, and death, using multivariable Cox-proportional hazards models accounting for competing risk of death, when appropriate. Patients were followed for these outcomes from diagnosis of Coronavirus disease 2019 until July 2, 2020.\n\nResultsAmong 562 asthma patients, 199 (21%) were hospitalized, 15 (3%) received mechanical ventilation, and 7 (1%) died. Among the 2686 matched comparators, 487 (18%) were hospitalized, 107 (4%) received mechanical ventilation, and 69 (3%) died. The adjusted Hazard Ratios among asthma patients were 0.99 (95% Confidence Internal 0.80, 1.22) for hospitalization, 0.69 (95% Confidence Internal 0.36, 1.29) for mechanical ventilation, and 0.30 (95% Confidence Internal 0.11, 0.80) for death.\n\nConclusionsIn this matched cohort study from a large Boston-based healthcare system, asthma was associated with comparable risk of hospitalization and mechanical ventilation but a lower risk of mortality.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Chee Wai Ku", - "author_inst": "KK Women's and Children's Hospital" - }, - { - "author_name": "Shivani Durai", - "author_inst": "KK Women's and Children's Hospital" - }, - { - "author_name": "Jacqueline Q T Kwan", - "author_inst": "National University Singapore" - }, - { - "author_name": "See Ling Loy", - "author_inst": "Duke-NUS Medical School" + "author_name": "Lacey B. Robinson", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Christina Erwin", - "author_inst": "Duke-NUS Medical School" + "author_name": "Liqin Wang", + "author_inst": "Brigham and Womens Hospital" }, { - "author_name": "Karrie K K Ko", - "author_inst": "Singapore General Hospital" + "author_name": "Xiaoqing Fu", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Xiang Wen Ng", - "author_inst": "KK Womens and Childrens Hospital" + "author_name": "Zachary S. Wallace", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Lynette Oon", - "author_inst": "Singapore General Hospital" + "author_name": "Aidan A. Long", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Koh Cheng Thoon", - "author_inst": "KK Women's and Children's Hospital" + "author_name": "Yuqing Zhang", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Shirin Kalimuddin", - "author_inst": "Singapore General Hospital" + "author_name": "Carlso A. Camargo Jr.", + "author_inst": "Massachusetts General Hospital" }, { - "author_name": "Jerry KY Chan", - "author_inst": "KK Women's and Children's Hospital" + "author_name": "Kimberly G. Blumenthal", + "author_inst": "Massachusetts General Hospital" } ], "version": "1", @@ -1169315,77 +1168817,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.30.20204719", - "rel_title": "Corticosteroid pulses for hospitalized patients with COVID-19. Effects on mortality and in-hospital stay.", - "rel_date": "2020-10-04", + "rel_doi": "10.1101/2020.10.02.20199083", + "rel_title": "Performance of a rapid SARS-COV-2 serology test in whole blood and separated plasma", + "rel_date": "2020-10-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.30.20204719", - "rel_abs": "Background: COVID-19 has high mortality in hospitalized patients, and we need effective treatments. Our objective was to assess corticosteroid pulses influence on 60-days mortality in hospitalized patients with severe COVID-19, intensive care admission, and hospital stay. Methods: We designed a multicenter retrospective cohort study in three teaching hospitals of Castilla y Leon, Spain (865.096 people). We selected patients with confirmed COVID-19 and lung involvement with a pO2/FiO2 < 300, excluding those exposed to immunosuppressors before or during hospitalization, patients terminally ill at admission, or died the first 24 hours. We performed a propensity score matching (PSM) adjusting covariates that modify the probability of being treated. Then we used a Cox regression model in the PSM group to consider factors affecting mortality. Findings: From 2933 patients, 257 fulfilled the inclusion and exclusion criteria. One hundred and twenty-four patients were on corticosteroid pulses, and 133 were not. 30{middle dot}3% (37/122) of patients died in the corticosteroid pulses group and 42{middle dot}9% (57/133) in the non-exposed cohort. These differences (12{middle dot}6% CI95% [8{middle dot}54-16{middle dot}65]) were statically significant (log-rank 4{middle dot}72, p=0{middle dot}03). We performed PSM using the exact method. Mortality differences remained in the PSM group (log-rank 5{middle dot}31, p=0{middle dot}021) and were still significant after a Cox regression model (HR for corticosteroid pulses 0{middle dot}561, p= 0{middle dot}039). There were no significant differences in intensive care admission rate (p=0{middle dot}173). The hospital stay was longer in the corticosteroid group (p<0,001). Interpretation: This study provides evidence about treatment with corticosteroid pulses in severe COVID-19 that might significantly reduce mortality. Strict inclusion and exclusion criteria with that selection process set a reliable frame to compare mortality in both exposed and non-exposed groups. Funding: There was no funding provided.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.10.02.20199083", + "rel_abs": "Rapid SARS-COV-2 related serology testing can help identify and manage the spread of infection in decentralized testing environments but the limitation in performance of existing tests in blood has restricted implementation of testing at the point-of-care. Optimization of existing rapid tests in whole blood will require significant effort in the short-term and there is a need for solutions to help bridge the gap in performance between plasma and whole blood. We demonstrate here the implementation of the H.E.R.M.E.S platform, a portable plasma separation system that can enhance the performance of blood-based diagnostic testing, with a commercially available SARS-COV-2 IgG/IgM serology rapid diagnostic test (RDT) in a blinded study with 61 human samples. We compare the performance of the RDT in whole blood and separated plasma and highlight that plasma yields a 39% increase in positivity agreement with PCR in samples collected from patients with early infections. We further legitimize the increase in positivity agreement rate with the help of an independent evaluation by 10 previously untrained users. The H.E.R.M.E.S plasma separation system circumvents the need for assay optimization in whole blood and furthers the legitimacy of incorporating SARS-COV-2 serology RDTs at the point-of-care. The data highlighted in this work makes a compelling case for the incorporation of the H.E.R.M.E.S system in large scale efforts to perform SARS-COV-2 serology testing in decentralized testing environments.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Ivan Cusacovich", - "author_inst": "Hospital Clinico Universitario de Valladolid" - }, - { - "author_name": "Alvaro Aparisi", - "author_inst": "Hospital Clinico de Valladolid. Spain" - }, - { - "author_name": "Miguel Marcos", - "author_inst": "University Hospital of Salamanca-IBSAL, University of Salamanca" - }, - { - "author_name": "Cristina Ybarra-Falcon", - "author_inst": "Hospital Clinico de Valladolid" - }, - { - "author_name": "Carolina Iglesias-Echevarria", - "author_inst": "Hospital Clinico de Valladolid" - }, - { - "author_name": "Maria Lopez-Veloso", - "author_inst": "Hospital Universitario de Burgos" - }, - { - "author_name": "Julio Barraza-Vengoechea", - "author_inst": "Hospital Universitario de Burgos" - }, - { - "author_name": "carlos Duenas", - "author_inst": "Hospital Clinico de Valladolid" - }, - { - "author_name": "Santiago Antonio Juarros Martinez", - "author_inst": "Hospital Clinico de Valladolid" - }, - { - "author_name": "Beatriz Rodriguez-Alonso", - "author_inst": "Hospital Universitario de Salamanca" - }, - { - "author_name": "Jose-Angel Martin-Oterino", - "author_inst": "Hospital Universitario de Salamanca" - }, - { - "author_name": "Miguel Montero-Baladia", - "author_inst": "Hospital Universitario de Burgos" - }, - { - "author_name": "Leticia Moralejo", - "author_inst": "Hospital Universitario de Salamanca" - }, - { - "author_name": "David Andaluz-Ojeda", - "author_inst": "Hospital Clinico de Valladolid" - }, - { - "author_name": "Roberto Gonzalez-Fuentes", - "author_inst": "Hospital Clinico de Valladolid" + "author_name": "Sasank Vemulapati", + "author_inst": "Hermes Life Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1171089,45 +1170535,57 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.09.30.320903", - "rel_title": "SARS-CoV-2 viral budding and entry can be modeled using virus-like particles", + "rel_doi": "10.1101/2020.09.30.319863", + "rel_title": "Thiopurines activate an antiviral unfolded protein response that blocks viral glycoprotein accumulation in cell culture infection model", "rel_date": "2020-10-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.30.320903", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first discovered in December 2019 in Wuhan, China and expeditiously spread across the globe causing a global pandemic. While a select agent designation has not been made for SARS-CoV-2, closely related SARS-CoV-1 and MERS coronaviruses are classified as Risk Group 3 select agents, which restricts use of the live viruses to BSL-3 facilities. Such BSL-3 classification make SARS-CoV-2 research inaccessible to the majority of functioning research laboratories in the US; this becomes problematic when the collective scientific effort needs to be focused on such in the face of a pandemic. In this work, we assessed the four structural proteins from SARS-CoV-2 for their ability to form viruslike particles (VLPs) from human cells to form a competent system for BSL-2 studies of SARS-CoV-2. Herein, we provide methods and resources of producing, purifying, fluorescently and APEX2-labeling of SARS-CoV-2 VLPs for the evaluation of mechanisms of viral budding and entry as well as assessment of drug inhibitors under BSL-2 conditions.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.30.319863", + "rel_abs": "Enveloped viruses, including influenza A viruses (IAVs) and coronaviruses (CoVs), utilize the host cell secretory pathway to synthesize viral glycoproteins and direct them to sites of assembly. Using an image-based high-content screen, we identified two thiopurines, 6-thioguanine (6-TG) and 6-thioguanosine (6-TGo), that selectively disrupted the processing and accumulation of IAV glycoproteins hemagglutinin (HA) and neuraminidase (NA). Selective disruption of IAV glycoprotein processing and accumulation by 6-TG and 6-TGo correlated with unfolded protein response (UPR) activation and HA accumulation could be partially restored by the chemical chaperone 4-phenylbutyrate (4PBA). Chemical inhibition of the integrated stress response (ISR) restored accumulation of NA monomers in the presence of 6-TG or 6-TGo, but did not restore NA glycosylation or oligomerization. Thiopurines inhibited replication of the human coronavirus OC43 (HCoV-OC43), which also correlated with UPR/ISR activation and diminished accumulation of ORF1ab and nucleocapsid (N) mRNAs and N protein, which suggests broader disruption of coronavirus gene expression in ER-derived cytoplasmic compartments. The chemically similar thiopurine 6-mercaptopurine (6-MP) had little effect on the UPR and did not affect IAV or HCoV-OC43 replication. Consistent with reports on other CoV Spike (S) proteins, ectopic expression of SARS-CoV-2 S protein caused UPR activation. 6-TG treatment inhibited accumulation of full length S0 or furin-cleaved S2 fusion proteins, but spared the S1 ectodomain. DBeQ, which inhibits the p97 AAA-ATPase required for retrotranslocation of ubiquitinated misfolded proteins during ER-associated degradation (ERAD) restored accumulation of S0 and S2 proteins in the presence of 6-TG, suggesting that 6-TG induced UPR accelerates ERAD-mediated turnover of membrane-anchored S0 and S2 glycoproteins. Taken together, these data indicate that 6-TG and 6-TGo are effective host-targeted antivirals that trigger the UPR and disrupt accumulation of viral glycoproteins. Importantly, our data demonstrate for the first time the efficacy of these thiopurines in limiting IAV and HCoV-OC43 replication in cell culture models.\n\nIMPORTANCESecreted and transmembrane proteins are synthesized in the endoplasmic reticulum (ER), where they are folded and modified prior to transport. During infection, many viruses burden the ER with the task of creating and processing viral glycoproteins that will ultimately be incorporated into viral envelopes. Some viruses refashion the ER into replication compartments where viral gene expression and genome replication take place. This viral burden on the ER can trigger the cellular unfolded protein response (UPR), which attempts to increase the protein folding and processing capacity of the ER to match the protein load. Much remains to be learned about how viruses co-opt the UPR to ensure efficient synthesis of viral glycoproteins. Here, we show that two FDA-approved thiopurine drugs, 6-TG and 6-TGo, induce the UPR in a manner that impedes viral glycoprotein accumulation for enveloped influenza viruses and coronaviruses. These drugs may impede the replication of viruses that require precise tuning of the UPR to support viral glycoprotein synthesis for the successful completion of a replication cycle.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Caroline B. Plescia", - "author_inst": "Purdue University" + "author_name": "Patrick D Slaine", + "author_inst": "Dalhousie University" }, { - "author_name": "Emily A. David", - "author_inst": "Purdue University" + "author_name": "Mariel Kleer", + "author_inst": "University of Calgary" }, { - "author_name": "Dhabaleswar Patra", - "author_inst": "Purdue University" + "author_name": "Brett Duguay", + "author_inst": "Dalhousie University" }, { - "author_name": "Ranjan Sengupta", - "author_inst": "Purdue University" + "author_name": "Eric Stanley Pringle", + "author_inst": "Dalhousie University" }, { - "author_name": "Souad Amiar", - "author_inst": "Purdue University" + "author_name": "Eileigh Kadijk", + "author_inst": "Dalhousie University" }, { - "author_name": "Yuan Su", - "author_inst": "Purdue University" + "author_name": "Shan Ying", + "author_inst": "Dalhousie University" }, { - "author_name": "Robert V. Stahelin", - "author_inst": "Purdue University" + "author_name": "Aruna D Balgi", + "author_inst": "University of British Columbia" + }, + { + "author_name": "Michel Roberge", + "author_inst": "University of British Columbia" + }, + { + "author_name": "Craig McCormick", + "author_inst": "Dalhousie University" + }, + { + "author_name": "Denys A Khaperskyy", + "author_inst": "Dalhousie University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -1172791,41 +1172249,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.30.20201830", - "rel_title": "Geospatial Analysis of Individual and Community-Level Socioeconomic Factors Impacting SARS-CoV-2 Prevalence and Outcomes", + "rel_doi": "10.1101/2020.09.29.20201368", + "rel_title": "Seroprevalence of SARS-CoV-2 IgG antibodies, in Corsica (France), April and June 2020.", "rel_date": "2020-09-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.30.20201830", - "rel_abs": "BackgroundThe SARS-CoV-2 pandemic has disproportionately affected racial and ethnic minority communities across the United States. We sought to disentangle individual and census tract-level sociodemographic and economic factors associated with these disparities.\n\nMethods and FindingsAll adults tested for SARS-CoV-2 between February 1 and June 21, 2020 were geocoded to a census tract based on their address; hospital employees and individuals with invalid addresses were excluded. Individual (age, sex, race/ethnicity, preferred language, insurance) and census tract-level (demographics, insurance, income, education, employment, occupation, household crowding and occupancy, built home environment, and transportation) variables were analyzed using linear mixed models predicting infection, hospitalization, and death from SARS-CoV-2.\n\nAmong 57,865 individuals, per capita testing rates, individual (older age, male sex, non-White race, non-English preferred language, and non-private insurance), and census tract-level (increased population density, higher household occupancy, and lower education) measures were associated with likelihood of infection. Among those infected, individual age, sex, race, language, and insurance, and census tract-level measures of lower education, more multi-family homes, and extreme household crowding were associated with increased likelihood of hospitalization, while higher per capita testing rates were associated with decreased likelihood. Only individual-level variables (older age, male sex, Medicare insurance) were associated with increased mortality among those hospitalized.\n\nConclusionsThis study of the first wave of the SARS-CoV-2 pandemic in a major U.S. city presents the cascade of outcomes following SARS-CoV-2 infection within a large, multi-ethnic cohort. SARS-CoV-2 infection and hospitalization rates, but not death rates among those hospitalized, are related to census tract-level socioeconomic characteristics including lower educational attainment and higher household crowding and occupancy, but not neighborhood measures of race, independent of individual factors.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.29.20201368", + "rel_abs": "Our aim was to assess the seroprevalence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection after the lockdown in a sample of the Corsican population. Between 16th April and 15th June 2020, 2,312 residual sera were collected from patients having carried out a blood analysis in one of the participating laboratories. Residual sera obtained from persons of all ages were tested for the presence of anti-SARS-CoV-2 IgG using the EUROIMMUN enzyme immunoassay kit for semiquantitative detection of IgG antibodies against S1 domain of viral spike protein (ELISA-S). Borderline and positive samples in ELISA-S were also tested with an in-house virus neutralization test (VNT). Prevalence values were adjusted for sex and age. A total of 1,973 residual sera samples were included in the study. The overall seroprevalence based on ELISA-S was 5.27% [95% confidence interval (CI) 4.33-6.35] and 5.46% [4.51-6.57] after adjustment. Gender was not associated with IgG detection. However, significant differences were observed between age groups (p-value = 1 E-5) and particularly for people being younger than 50 years of age (Odd ratio (OR) = 2.86 95% CI [1.80-4.53]; p-value <0.000001*). The prevalence of neutralizing antibody titers [≥]40 was of 3% [2.28-3.84]. In conclusion the present study showed that a low seroprevalence for COVID-19 in Corsica in accordance with values reported for other French regions in which the impact of the pandemic was low.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Sara J Cromer", - "author_inst": "Massachusetts General Hospital" + "author_name": "Lisandru Capai", + "author_inst": "UR 7310, Laboratoire de Virologie, Universite de Corse, Corte, France" }, { - "author_name": "Chirag M Lakhani", - "author_inst": "Harvard Medical School" + "author_name": "Nazli Ayhan", + "author_inst": "UR 7310, Laboratoire de Virologie, Universite de Corse, Corte, France AND UnitE des Virus emergents (UVE): Aix Marseille Univ, IRD 190, INSERM 1207, IHU Mediter" }, { - "author_name": "Deborah J Wexler", - "author_inst": "Massachusetts General Hospital" + "author_name": "Shirley Masse", + "author_inst": "UR 7310, Laboratoire de Virologie, Universite de Corse, Corte, France" }, { - "author_name": "Sherri-Ann M Burnett-Bowie", - "author_inst": "Massachusetts General Hospital" + "author_name": "Jean Canarelli", + "author_inst": "Laboratoire de biologie medicale, CCF, Ajaccio, France" }, { - "author_name": "Miriam Udler", - "author_inst": "Massachusetts General Hospital" + "author_name": "Stephane Priet", + "author_inst": "Unite des Virus Emergents (UVE): Aix Marseille Univ, IRD 190, INSERM 1207, IHU Mediterranee Infection," }, { - "author_name": "Chirag J Patel", - "author_inst": "Harvard Medical School" + "author_name": "Marie-Helene Simeoni", + "author_inst": "Laboratoire de Biologie medicale 2A2B, 20250, Corte, France." + }, + { + "author_name": "Remi N Charrel", + "author_inst": "Aix Marseille Univ." + }, + { + "author_name": "Xavier de Lamballerie", + "author_inst": "Ai-Marseille univ -Inserm - IRD" + }, + { + "author_name": "Alessandra Falchi", + "author_inst": "UR 7310, Laboratoire de Virologie, Universite de Corse, Corte, France" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1174813,21 +1174283,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.29.20203760", - "rel_title": "Which early indicator allows for a better understanding of the evolution of the COVID-19 epidemic in France?", + "rel_doi": "10.1101/2020.09.29.20203885", + "rel_title": "Estimation of the Basic Reproduction Number of SARS-CoV-2 in Bangladesh Using Exponential Growth Method", "rel_date": "2020-09-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.29.20203760", - "rel_abs": "We provide an explanation for the apparent discrepancy between the dynamic of the positive COVID-19 test rates and of the numbers of COVID-19-related hospital and intensive care admissions and deaths in France. We highlight the existence of a latency period of around 5 weeks between the infections of young individual (generally asymptomatic) to older individuals that may have a severe form of the disease and may be hospitalized. If the overall positive detection rate provided relevant information until the end of August, since the beginning of September the overall positive detection rate has reached a plateau and no longer provides relevant information on the current state of the epidemic. We show that the positive detection rate in the 70+ age group is a relevant and early indicator of the epidemic. Furthermore, we have shown an identical doubling time of around 16 days for the following indicators: the positive tests rate for the 70+ age group, the number of new admissions to hospital, intensive care unit admissions and deaths.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.29.20203885", + "rel_abs": "ObjectivesIn December 2019, a novel coronavirus (SARS-CoV-2) outbreak emerged in Wuhan, Hubei Province, China. Soon, it has spread out across the world and become an ongoing pandemic. In Bangladesh, the first case of novel coronavirus (SARS-CoV-2) was detected on March 8, 2020. Since then, not many significant studies have been conducted to understand the transmission dynamics of novel coronavirus (SARS-CoV-2) in Bangladesh. In this study, we estimated the basic reproduction number R0 of novel coronavirus (SARS-CoV-2) in Bangladesh.\n\nMethodsThe data of daily confirmed cases of novel coronavirus (SARS-CoV-2) in Bangladesh and the reported values of generation time of novel coronavirus (SARS-CoV-2) for Singapore and Tianjin, China, were collected. We calculated the basic reproduction number R0 by applying the exponential growth (EG) method. Epidemic data of the first 76 days and different values of generation time were used for the calculation.\n\nResultsThe basic reproduction number R0 of novel coronavirus (SARS-CoV-2) in Bangladesh is estimated to be 2.66 [95% CI: 2.58-2.75], optimized R0 is 2.78 [95% CI: 2.69-2.88] using generation time 5.20 with a standard deviation of 1.72 for Singapore. Using generation time 3.95 with a standard deviation of 1.51 for Tianjin, China, R0 is estimated to be 2.15 [95% CI: 2.09-2.20], optimized R0 is 2.22 [95% CI: 2.16-2.29].\n\nConclusionsThe calculated basic reproduction number R0 of novel coronavirus (SARS-CoV-2) in Bangladesh is significantly higher than 1, which indicates its high transmissibility and contagiousness.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Patrice Loisel", - "author_inst": "INRAE" + "author_name": "Riaz Mahmud", + "author_inst": "Department of Mathematics, Faculty of Mathematics and Computer Science, South Asian University, New Delhi-110021, India." + }, + { + "author_name": "H. M. Abrar Fahim Patwari", + "author_inst": "Department of Applied Mathematics, Faculty of Science, Noakhali Science and Technology University, Noakhali-3814, Bangladesh." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1176283,33 +1175757,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.26.20201814", - "rel_title": "Evolution of COVID-19 cases in selected low- and middle-income countries: past the herd immunity peak?", + "rel_doi": "10.1101/2020.09.26.20202325", + "rel_title": "An optimal control policy for COVID-19 pandemic until a vaccine deployment", "rel_date": "2020-09-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.26.20201814", - "rel_abs": "We have studied the evolution of COVID-19 in 12 low- and middle-income countries in which reported cases have peaked and declined rapidly in the past 2-3 months. In most of these countries the declines happened while control measures were consistent or even relaxing, and without signs of significant increases in cases that might indicate second waves. For the 12 countries we studied, the hypothesis that these countries have reached herd immunity warrants serious consideration. The Reed-Frost model, perhaps the simplest description for the evolution of cases in an epidemic, with only a few constant parameters, fits the observed case data remarkably well, and yields parameter values that are reasonable. The best-fitting curves suggest that the effective basic reproduction numberin these countries ranged between 1.5 and 2.0, indicating that the curve was \"flattened \"in some countries but not \"suppressed \"by pushing the reproduction number below 1. The results suggest that between 51 and 80% of the population in these countries have been infected, and that between 0.05% and 2.50% of cases have been detected - values which are consistent with findings from serological and T-cell immunity studies. The infection rates, combined with data and estimates for deaths from COVID-19, allow us to estimate overall infection fatality rates for three of the countries. The values are lower than expected from reported infection fatality rates by age, based on data from several high-income countries, and the countries populations by age. COVID-19 may have a lower mortality risk in these three countries (to differing degrees in each country) than in high-income countries, due to differences in immune-response, prior exposure to coronaviruses, disease characteristics or other factors. We find that the herd immunity hypothesis would not have fit the evolution of reported cases in several European countries, even just after the initial peaks - and subsequent resurgences of cases obviously prove that those countries have infection rates well below herd immunity levels. Our hypothesis that the 12 countries we studied have reached herd immunity should now be tested further, through serological and T-cell-immunity studies.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.26.20202325", + "rel_abs": "When an outbreak starts spreading, policy makers have to make decisions that affects health of their citizens and the economic. Some might induce harsh measures, such as lockdown. Following a long harsh lockdown, economical declines force policy makers to rethink reopening. But what is the most effective reopening strategy? In order to provide an effective strategy, here we propose a control strategy model. Our model assesses the trade-off between social performance and limited medical resources by determining individuals propensities. The proposed strategy also helps decision makers to find optimal lockdown and exit strategy for each region. Moreover, the financial loss is minimized. In addition, a study of a COVID-19 dataset for Los Angeles County is performed to validate our model and its results.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Axel S Lexmond", - "author_inst": "University of Pretoria" - }, - { - "author_name": "Carlijn JA Nouwen", - "author_inst": "Personal capacity" - }, - { - "author_name": "Othmane Fourtassi", - "author_inst": "Personal capacity" - }, - { - "author_name": "John Paul Callan", - "author_inst": "Personal capacity" + "author_name": "Hamid R. Sayarshad", + "author_inst": "Cornell University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1177929,43 +1177391,59 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.09.25.20201616", - "rel_title": "COVID-19 in Youth Soccer", + "rel_doi": "10.1101/2020.09.24.20200196", + "rel_title": "Cost-effectiveness of remdesivir and dexamethasone for COVID-19 treatment in South Africa", "rel_date": "2020-09-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.25.20201616", - "rel_abs": "PurposeThe purpose of this study was to determine the case and incidence rates of COVID-19 among youth soccer players and evaluate the relationship with background COVID-19 risk and phase of return to play.\n\nMethodsSurveys were distributed to soccer clubs throughout the country regarding their phase of return to soccer (individual only, group non-contact, group contact) and date of reinitiation, number of players, cases of COVID-19, and risk reduction procedures that were being implemented. Overall case and incidence rates were compared to national pediatric data and county data from the prior 10 weeks where available. Finally, a negative binomial regression model was developed to predict club COVID-19 cases with local incidence rate and phase of return as covariates and the log of club player-days as an offset.\n\nResults129 clubs responded, of whom 124 had reinitiated soccer, representing 91,007 players with a median duration of 73 days (IQR: 53-83 days) since restarting. Of the 119 that had progressed to group activities, 218 cases of COVID-19 were reported among 85,861 players. Youth soccer players had a lower case rate and incidence rate than the national rate for children in the US (254 v. 477 cases per 100,000; IRR = 0.511, 95% CI = [0.40-0.57], p<0.001) and the general population from the counties in which soccer clubs were based where data was available (268 v. 864 cases per 100,000; IRR = 0.202 [0.19-0.21], p<0.001). After adjusting for local COVID-19 incidence, there was no relationship between club COVID-19 incidence and phase of return (non-contact: {beta}=0.35{+/-}0.67, p=0.61; contact: {beta}=0.18{+/-}0.67, p=0.79). No cases were reported to have resulted in hospitalization or death. 100% of clubs reported having a plan in place to reduce the risk of COVID-19 and utilizing multiple different risk reduction procedures (median 8, IQR 6-10).\n\nConclusionsThe incidence of COVID-19 among youth soccer athletes is relatively low when compared to the background incidence among children in the United States and the local general population. No relationship was identified between club COVID-19 incidence and phase of return to soccer. Youth soccer clubs universally report implementing a number of risk reduction procedures.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.24.20200196", + "rel_abs": "BackgroundSouth Africa recently experienced a first peak in COVID-19 cases and mortality. Dexamethasone and remdesivir both have the potential to reduce COVID-related mortality, but their cost-effectiveness in a resource-limited setting with scant intensive care resources is unknown.\n\nMethodsWe projected intensive care unit (ICU) needs and capacity from August 2020 to January 2021 using the South African National COVID-19 Epi Model. We assessed cost-effectiveness of 1) administration of dexamethasone to ventilated patients and remdesivir to non-ventilated patients, 2) dexamethasone alone to both non-ventilated and ventilated patients, 3) remdesivir to non-ventilated patients only, and 4) dexamethasone to ventilated patients only; all relative to a scenario of standard care. We estimated costs from the healthcare system perspective in 2020 USD, deaths averted, and the incremental cost effectiveness ratios of each scenario.\n\nResultsRemdesivir for non-ventilated patients and dexamethasone for ventilated patients was estimated to result in 1,111 deaths averted (assuming a 0-30% efficacy of remdesivir) compared to standard care, and save $11.5 million. The result was driven by the efficacy of the drugs, and the reduction of ICU-time required for patients treated with remdesivir. The scenario of dexamethasone alone to ventilated and non-ventilated patients requires additional $159,000 and averts 1,146 deaths, resulting in $139 per death averted, relative to standard care.\n\nConclusionsThe use of dexamethasone for ventilated and remdesivir for non-ventilated patients is likely to be cost-saving compared to standard care. Given the economic and health benefits of both drugs, efforts to ensure access to these medications is paramount.\n\n40-word summary of articles main pointThe use of remdesivir and dexamethasone for treatment of severe COVID-19 in South Africa is likely to be cost-saving relative to standard care. Enabling access to these medications should be prioritize to improve patient outcomes and reduce total costs.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Andrew Watson", - "author_inst": "University of Wisconsin School of Medicine and Public Health" + "author_name": "Youngji Jo", + "author_inst": "Boston Medical Center" }, { - "author_name": "Kristin Haraldsdottir", - "author_inst": "University of Wisconsin School of Medicine and Public Health" + "author_name": "Lise Jamieson", + "author_inst": "Health Economics and Epidemiology Research Office" }, { - "author_name": "Kevin Biese", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Ijeoma Edoka", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "Leslie Goodavish", - "author_inst": "University of Wisconsin School of Medicine and Public Health" + "author_name": "Lawrence Long", + "author_inst": "Boston University School of Public Health" }, { - "author_name": "Bethany Stevens", - "author_inst": "University of Wisconsin-Madison" + "author_name": "Sheetal Silal", + "author_inst": "University of Cape Town" }, { - "author_name": "Timothy McGuine", - "author_inst": "University of Wisconsin School of Medicine and Public Health" + "author_name": "Juliet R.C. Pulliam", + "author_inst": "Stellenbosch University" + }, + { + "author_name": "Harry Moultrie", + "author_inst": "National Institute for Communicable Diseases" + }, + { + "author_name": "Ian Sanne", + "author_inst": "Health Economics and Epidemiology Research Office" + }, + { + "author_name": "Gesine Meyer-Rath", + "author_inst": "Health Economics and Epidemiology Research Office" + }, + { + "author_name": "Brooke E Nichols", + "author_inst": "Boston University School of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "sports medicine" + "category": "health economics" }, { "rel_doi": "10.1101/2020.09.25.20201905", @@ -1179491,79 +1178969,255 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.23.20198713", - "rel_title": "Suitability of Two Rapid Lateral Flow Immunochromatographic Assays for Predicting SARS-CoV-2 Neutralizing Activity of Sera", + "rel_doi": "10.1101/2020.09.24.20200048", + "rel_title": "Genetic mechanisms of critical illness in Covid-19", "rel_date": "2020-09-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.23.20198713", - "rel_abs": "PurposeAssessment of commercial SARS-CoV-2 immunoassays for their capacity to provide reliable information on sera neutralizing activity is an emerging need. We evaluated the performance of two commercially-available lateral flow immunochromatographic assays (LFIC) (Wondfo SARS-CoV-2 Antibody test and the INNOVITA 2019-nCoV Ab test) in comparison with a SARS-CoV-2 neutralization pseudotyped assay for COVID-19 diagnosis in hospitalized patients, and investigate whether the intensity of the test band in LFIC associates with neutralizing antibody (NtAb) titers.\n\nPatients and MethodsNinety sera were included from 51 patients with moderate to severe COVID-19. A green fluorescent protein (GFP) reporter-based pseudotyped neutralization assay (vesicular stomatitis virus coated with SARS-CoV-2 spike protein) was used. Test line intensity was scored using a 4-level scale (0 to 3+).\n\nResultsOverall sensitivity of LFIC assays was 91.1% for the Wondfo SARS-CoV-2 Antibody test, 72.2% for the INNOVITA 2019-nCoV IgG, 85.6% for the INNOVITA 2019-nCoV IgM and 92.2% for the NtAb assay. Sensitivity increased for all assays in sera collected beyond day 14 after symptoms onset (93.9%, 79.6%,93.9% and 93.9%, respectively). Reactivities equal to or more intense than the positive control line ([≥]2+) in the Wondfo assay had a negative predictive value of 100% and a positive predictive value of 96.4% for high NtAb50 titers ([≥]1/160).\n\nConclusionsOur findings support the use of LFIC assays evaluated herein, particularly the Wondfo test, for COVID-19 diagnosis. We also find evidence that these rapid immunoassays can be used to predict high SARS-CoV-2-S NtAb50 titers.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.24.20200048", + "rel_abs": "The subset of patients who develop critical illness in Covid-19 have extensive inflammation affecting the lungs1 and are strikingly different from other patients: immunosuppressive therapy benefits critically-ill patients, but may harm some non-critical cases.2 Since susceptibility to life-threatening infections and immune-mediated diseases are both strongly heritable traits, we reasoned that host genetic variation may identify mechanistic targets for therapeutic development in Covid-19.3\n\nGenOMICC (Genetics Of Mortality In Critical Care, genomicc.org) is a global collaborative study to understand the genetic basis of critical illness. Here we report the results of a genome-wide association study (GWAS) in 2244 critically-ill Covid-19 patients from 208 UK intensive care units (ICUs), representing >95% of all ICU beds. Ancestry-matched controls were drawn from the UK Biobank population study and results were confirmed in GWAS comparisons with two other population control groups: the 100,000 genomes project and Generation Scotland.\n\nWe identify and replicate three novel genome-wide significant associations, at chr19p13.3 (rs2109069, p = 3.98 x 10-12), within the gene encoding dipeptidyl peptidase 9 (DPP9), at chr12q24.13 (rs10735079, p =1.65 x 10-8) in a gene cluster encoding antiviral restriction enzyme activators (OAS1, OAS2, OAS3), and at chr21q22.1 (rs2236757, p = 4.99 x 10-8) in the interferon receptor gene IFNAR2. Consistent with our focus on extreme disease in younger patients with less comorbidity, we detect a stronger signal at the known 3p21.31 locus than previous studies (rs73064425, p = 4.77 x 10-30).\n\nWe identify potential targets for repurposing of licensed medications. Using Mendelian randomisation we found evidence in support of a causal link from low expression of IFNAR2, and high expression of TYK2, to life-threatening disease. Transcriptome-wide association in lung tissue revealed that high expression of the monocyte/macrophage chemotactic receptor CCR2 is associated with severe Covid-19.\n\nOur results identify robust genetic signals relating to key host antiviral defence mechanisms, and mediators of inflammatory organ damage in Covid-19. Both mechanisms may be amenable to targeted treatment with existing drugs. Large-scale randomised clinical trials will be essential before any change to clinical practice.", + "rel_num_authors": 59, "rel_authors": [ { - "author_name": "Arantxa Valdivia", - "author_inst": "Clinic University Hospital, Valencia, Spain." + "author_name": "Erola Pairo-Castineira", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Ignacio Torres", - "author_inst": "Clinic University Hospital, Valencia, Spain." + "author_name": "Sara Clohisey", + "author_inst": "The Roslin Institute" }, { - "author_name": "Victor Latorre", - "author_inst": "Institute for Integrative System Biology, I2sysBio, Univeristat de Valencia-CSIC." + "author_name": "Lucija Klaric", + "author_inst": "MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK." }, { - "author_name": "Clara Frances-Gomez", - "author_inst": "Institute for Integrative System Biology, I2sysBio, Univeristat de Valencia-CSIC." + "author_name": "Andrew Bretherick", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Josep Ferrer", - "author_inst": "Clinic University Hospital, Valencia, Spain." + "author_name": "Konrad Rawlik", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Lorena Forque", - "author_inst": "Clinic University Hospital, Valencia, Spain." + "author_name": "Nicholas Parkinson", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Rosa Costa", - "author_inst": "Clinic University Hospital, Valencia, Spain." + "author_name": "Dorota Pasko", + "author_inst": "Genomics England" }, { - "author_name": "Carlos Solano de la Asuncion", - "author_inst": "Clinic University Hospital, Valencia, Spain." + "author_name": "Susan Walker", + "author_inst": "Genomics England" }, { - "author_name": "Dixie Huntley", - "author_inst": "Clinic University Hospital, Valencia, Spain." + "author_name": "Anne Richmond", + "author_inst": "MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK." }, { - "author_name": "Roberto Gozalbo-Rovira", - "author_inst": "Department of Microbiology, School of Medicine, University of Valencia, Valencia, Spain" + "author_name": "Max Head Fourman", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Javier Buesa", - "author_inst": "Department of Microbiology, School of Medicine, University of Valencia, Valencia, Spain" + "author_name": "Andy Law", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Estela Gimenez", - "author_inst": "Clinic University Hospital, Valencia, Spain." + "author_name": "James Furniss", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." }, { - "author_name": "Jesus Rodriguez-Diaz", - "author_inst": "Department of Microbiology, School of Medicine, University of Valencia, Valencia, Spain" + "author_name": "Elvina Gountouna", + "author_inst": "Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb" }, { - "author_name": "Ron Geller", - "author_inst": "Institute for Integrative System Biology, I2sysBio, Univeristat de Valencia-CSIC." + "author_name": "Nicola Wrobel", + "author_inst": "Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK." }, { - "author_name": "David Navarro", - "author_inst": "Clinic University Hospital, INCLIVA Health Research Institute, Valencia, Spain." + "author_name": "Clark D Russell", + "author_inst": "University of Edinburgh Centre for Inflammation Research, The Queen's Medical Research Institute, Edinburgh, UK" + }, + { + "author_name": "Loukas Moutsianas", + "author_inst": "Genomics England" + }, + { + "author_name": "Bo Wang", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK" + }, + { + "author_name": "Alison Meynert", + "author_inst": "MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK." + }, + { + "author_name": "Zhijian Yang", + "author_inst": "Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China." + }, + { + "author_name": "Ranran Zhai", + "author_inst": "Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China." + }, + { + "author_name": "Chenqing Zheng", + "author_inst": "Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China." + }, + { + "author_name": "Fiona Griffith", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." + }, + { + "author_name": "Wilna Oosthuyzen", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." + }, + { + "author_name": "Barbara Shih", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." + }, + { + "author_name": "Se\u00e1n Keating", + "author_inst": "Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK." + }, + { + "author_name": "Marie Zechner", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." + }, + { + "author_name": "Chris Haley", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." + }, + { + "author_name": "David J Porteous", + "author_inst": "Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb" + }, + { + "author_name": "Caroline Hayward", + "author_inst": "Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinb" + }, + { + "author_name": "Julian Knight", + "author_inst": "Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK." + }, + { + "author_name": "Charlotte Summers", + "author_inst": "Department of Medicine, University of Cambridge, Cambridge, UK." + }, + { + "author_name": "Manu Shankar-Hari", + "author_inst": "Department of Intensive Care Medicine, Guy's and St. Thomas NHS Foundation Trust, London, UK; School of Immunology and Microbial Sciences, King's College London" + }, + { + "author_name": "Lance Turtle", + "author_inst": "NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences University of Liverpool, L" + }, + { + "author_name": "Antonia Ho", + "author_inst": "MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, Univer" + }, + { + "author_name": "Charles Hinds", + "author_inst": "William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK." + }, + { + "author_name": "Peter Horby", + "author_inst": "Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Old Road Campus, Roosevelt Drive, Oxford, OX3 7FZ, UK." + }, + { + "author_name": "Alistair Nichol", + "author_inst": "Clinical Research Centre at St Vincent's University Hospital, University College Dublin, Dublin, Ireland; Australian and New Zealand Intensive Care Research Cen" + }, + { + "author_name": "David Maslove", + "author_inst": "Department of Critical Care Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, ON, Canada." + }, + { + "author_name": "Lowell Ling", + "author_inst": "Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China." + }, + { + "author_name": "Paul Klenerman", + "author_inst": "University of Oxford" + }, + { + "author_name": "Danny McAuley", + "author_inst": "Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, Northern Ireland, UK; Department of Intensive Care Medicine, Royal Vi" + }, + { + "author_name": "Hugh Montgomery", + "author_inst": "UCL Centre for Human Health and Performance, London, W1T 7HA, UK." + }, + { + "author_name": "Timothy Walsh", + "author_inst": "Intenstive Care Unit, Royal Infirmary of Edinburgh, 54 Little France Drive, Edinburgh, EH16 5SA, UK." + }, + { + "author_name": "- The GenOMICC Investigators", + "author_inst": "-" + }, + { + "author_name": "- The ISARIC4C Investigators", + "author_inst": "-" + }, + { + "author_name": "- The Covid-19 Human Genetics Initiative", + "author_inst": "-" + }, + { + "author_name": "Xia Shen", + "author_inst": "Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK." + }, + { + "author_name": "Kathy Rowan", + "author_inst": "Intensive Care National Audit & Research Centre, London, UK." + }, + { + "author_name": "Angie Fawkes", + "author_inst": "Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK." + }, + { + "author_name": "Lee Murphy", + "author_inst": "Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, EH4 2XU, UK." + }, + { + "author_name": "Chris P Ponting", + "author_inst": "MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK." + }, + { + "author_name": "Albert Tenesa", + "author_inst": "Roslin Institute, University of Edinburgh, Easter Bush, Edinburgh, EH25 9RG, UK." + }, + { + "author_name": "Mark Caulfield", + "author_inst": "Genomics England; William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK" + }, + { + "author_name": "Richard Scott", + "author_inst": "Genomics England" + }, + { + "author_name": "Peter JM Openshaw", + "author_inst": "National Heart & Lung Institute, Imperial College London (St Mary's Campus), Norfolk Place, Paddington, London W2 1PG, UK." + }, + { + "author_name": "Malcolm G Semple", + "author_inst": "University of Liverpool, Liverpool, UK." + }, + { + "author_name": "Veronique Vitart", + "author_inst": "MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK." + }, + { + "author_name": "James F Wilson", + "author_inst": "MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK; Ce" + }, + { + "author_name": "J Kenneth Baillie", + "author_inst": "Roslin Institute, University of Edinburgh" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.09.24.20200576", @@ -1180981,69 +1180635,137 @@ "category": "nursing" }, { - "rel_doi": "10.1101/2020.09.24.20201228", - "rel_title": "Outcomes associated with SARS-CoV-2 viral clades in COVID-19", + "rel_doi": "10.1101/2020.09.22.20192443", + "rel_title": "Reinfection with SARS-CoV-2 and Failure of Humoral Immunity: a case report.", "rel_date": "2020-09-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.24.20201228", - "rel_abs": "BackgroundThe COVID-19 epidemic of 2019-20 is due to the novel coronavirus SARS-CoV-2. Following first case description in December, 2019 this virus has infected over 10 million individuals and resulted in at least 500,000 deaths world-wide. The virus is undergoing rapid mutation, with two major clades of sequence variants emerging. This study sought to determine whether SARS-CoV-2 sequence variants are associated with differing outcomes among COVID-19 patients in a single medical system.\n\nMethodsWhole genome SARS-CoV-2 RNA sequence was obtained from isolates collected from patients registered in the University of Washington Medicine health system between March 1 and April 15, 2020. Demographic and baseline medical data along with outcomes of hospitalization and death were collected. Statistical and machine learning models were applied to determine if viral genetic variants were associated with specific outcomes of hospitalization or death.\n\nFindingsFull length SARS-CoV-2 sequence was obtained 190 subjects with clinical outcome data. 35 (18.4%) were hospitalized and 14 (7.4%) died from complications of infection. A total of 289 single nucleotide variants were identified. Clustering methods demonstrated two major viral clades, which could be readily distinguished by 12 polymorphisms in 5 genes. A trend toward higher rates of hospitalization of patients with Clade 2 was observed (p=0.06). Machine learning models utilizing patient demographics and co-morbidities achieved area-under-the-curve (AUC) values of 0.93 for predicting hospitalization. Addition of viral clade or sequence information did not significantly improve models for outcome prediction.\n\nConclusionSARS-CoV-2 shows substantial sequence diversity in a community-based sample. Two dominant clades of virus are in circulation. Among patients sufficiently ill to warrant testing for virus, no significant difference in outcomes of hospitalization or death could be discerned between clades in this sample. Major risk factors for hospitalization and death for either major clade of virus include patient age and comorbid conditions.\n\nFundingSupported by NIH P30EY001730, the Mark J. Daily, MD Research Fund (RVG), the Alida and Christopher Latham Research Fund (RVG, AYL, CSL), NIH K23EY029246 (AYL), US Food and Drug Administration (QYL)", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20192443", + "rel_abs": "Recovery from COVID-19 is associated with production of anti-SARS-CoV-2 antibodies, but it is uncertain whether these confer immunity. We describe viral RNA shedding duration in hospitalized patients and identify patients with recurrent shedding. We sequenced viruses from two distinct episodes of symptomatic COVID-19 separated by 144 days in a single patient, to conclusively describe reinfection with a new strain harboring the spike variant D614G. With antibody and B cell analytics, we show correlates of adaptive immunity, including a differential response to D614G. Finally, we discuss implications for vaccine programs and begin to define benchmarks for protection against reinfection from SARS-CoV-2.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Kenji Nakamichi", - "author_inst": "University of Washington" + "author_name": "Jason D. Goldman", + "author_inst": "Division of Infectious Diseases, Swedish Medical Center, Providence St. Joseph Health, and Division of Allergy and Infectious Diseases, University of Washington" }, { - "author_name": "Jolie Zhu Shen", - "author_inst": "University of Washington" + "author_name": "Kai Wang", + "author_inst": "Institute for Systems Biology, Seattle, WA, USA" }, { - "author_name": "Cecilia S Lee", - "author_inst": "University of Washington" + "author_name": "Katharina Roltgen", + "author_inst": "Department of Pathology, Stanford University, Stanford, CA, USA" }, { - "author_name": "Aaron Y Lee", - "author_inst": "University of Washington" + "author_name": "Sandra C. A. Nielsen", + "author_inst": "Department of Pathology, Stanford University, Stanford, CA, USA" }, { - "author_name": "Emma Adaline Roberts", - "author_inst": "University of Washington" + "author_name": "Jared C. Roach", + "author_inst": "Institute for Systems Biology, Seattle, WA USA" }, { - "author_name": "Paul D Simonson", - "author_inst": "University of Washington" + "author_name": "Samia N. Naccache", + "author_inst": "Department of Microbiology, LabCorp, Seattle, WA, USA" }, { - "author_name": "Pavitra Roychoudhury", - "author_inst": "University of Washington" + "author_name": "Fan Yang", + "author_inst": "Department of Pathology, Stanford University, Stanford, CA, USA" + }, + { + "author_name": "Oliver F. Wirz", + "author_inst": "Department of Pathology, Stanford University, Stanford, CA, USA" }, { - "author_name": "Jessica G Andriesen", - "author_inst": "jandries@fredhutch.org" + "author_name": "Kathryn E. Yost", + "author_inst": "Department of Pathology, Stanford University, Stanford, CA, USA" }, { - "author_name": "April K Randhawa", - "author_inst": "arandhaw@fredhutch.org" + "author_name": "Ji-Yeun Lee", + "author_inst": "Department of Pathology, Stanford University, Stanford, CA, USA" }, { - "author_name": "Patrick C Mathias", - "author_inst": "University of Washington School of Medicine" + "author_name": "Kelly Chun", + "author_inst": "LabCorp Esoterix, Calabasas, CA, USA" }, { - "author_name": "Alex Greninger", - "author_inst": "University of Washington" + "author_name": "Terri Wrin", + "author_inst": "Monogram Biosciences, South San Francisco, CA, USA" }, { - "author_name": "Keith R Jerome", - "author_inst": "University of Washington" + "author_name": "Christos J. Petropoulos", + "author_inst": "Monogram Biosciences, South San Francisco, CA, USA" }, { - "author_name": "Russell N Van Gelder", - "author_inst": "University of Washington" + "author_name": "Inyou Lee", + "author_inst": "Institute for Systems Biology, Seattle, WA USA" + }, + { + "author_name": "Shannon Fallen", + "author_inst": "Institute for Systems Biology, Seattle, WA, USA" + }, + { + "author_name": "Paula M. Manner", + "author_inst": "Swedish Center for Research and Innovation, Swedish Medical Center, Providence St. Joseph Health, Seattle, WA, USA" + }, + { + "author_name": "Julie A. Wallick", + "author_inst": "Swedish Center for Research and Innovation, Swedish Medical Center, Providence St. Joseph Health, Seattle, WA, USA" + }, + { + "author_name": "Heather A. Algren", + "author_inst": "Swedish Center for Research and Innovation, Swedish Medical Center, Providence St. Joseph Health, Seattle, WA, USA" + }, + { + "author_name": "Kim M. Murray", + "author_inst": "Institute for Systems Biology, Seattle, WA USA" + }, + { + "author_name": "Yapeng Su", + "author_inst": "Institute for Systems Biology, Seattle, WA, USA" + }, + { + "author_name": "Jennifer Hadlock", + "author_inst": "Institute for Systems Biology, Seattle, WA, USA; and Providence St. Joseph Health, Renton, WA, USA" + }, + { + "author_name": "Joshua Jeharajah", + "author_inst": "Division of Infectious Diseases, Polyclinic, Seattle, WA, USA" + }, + { + "author_name": "William R. Berrington", + "author_inst": "Division of Infectious Diseases, Swedish Medical Center, Providence St. Joseph Health, Seattle, WA, USA" + }, + { + "author_name": "George P. Pappas", + "author_inst": "Division of Pulmonology and Critical Care Medicine, Swedish Medical Center, Providence St. Joseph Health, Seattle, WA, USA" + }, + { + "author_name": "Sonam T. Nyatsatsang", + "author_inst": "Division of Infectious Diseases, Swedish Medical Center, Providence St. Joseph Health, Seattle, WA, USA" + }, + { + "author_name": "Alexander L. Greninger", + "author_inst": "Department of Laboratory Medicine and Pathology, University of Washington School of Medicine; Vaccine and Infectious Disease Division, Fred Hutch, Seattle, WA, " + }, + { + "author_name": "Ansuman T. Satpathy", + "author_inst": "Department of Pathology, Stanford University, Stanford, CA, USA" + }, + { + "author_name": "John S Pauk", + "author_inst": "Division of Infectious Diseases, Swedish Medical Center, Providence St. Joseph Health, Seattle, WA, USA" + }, + { + "author_name": "Scott D. Boyd", + "author_inst": "Department of Pathology, Stanford University, and Sean N. Parker Center for Allergy and Asthma Research, Stanford, CA, USA" + }, + { + "author_name": "James R. Heath", + "author_inst": "Institute for Systems Biology, Seattle, WA, USA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1182747,97 +1182469,57 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.09.23.309948", - "rel_title": "Respiratory disease in cats associated with human-to-cat transmission of SARS-CoV-2 in the UK", + "rel_doi": "10.1101/2020.09.23.309849", + "rel_title": "Establishment of a reverse genetics system for SARS-CoV-2 using circular polymerase extension reaction", "rel_date": "2020-09-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.23.309948", - "rel_abs": "Two cats from different COVID-19-infected households in the UK were found to be infected with SARS-CoV-2 from humans, demonstrated by immunofluorescence, in situ hybridisation, reverse transcriptase quantitative PCR and viral genome sequencing. Lung tissue collected post-mortem from cat 1 displayed pathological and histological findings consistent with viral pneumonia and tested positive for SARS-CoV-2 antigens and RNA. SARS-CoV-2 RNA was detected in an oropharyngeal swab collected from cat 2 that presented with rhinitis and conjunctivitis. High throughput sequencing of the virus from cat 2 revealed that the feline viral genome contained five single nucleotide polymorphisms (SNPs) compared to the nearest UK human SARS-CoV-2 sequence. An analysis of cat 2s viral genome together with nine other feline-derived SARS-CoV-2 sequences from around the world revealed no shared catspecific mutations. These findings indicate that human-to-cat transmission of SARS-CoV-2 occurred during the COVID-19 pandemic in the UK, with the infected cats developing mild or severe respiratory disease. Given the versatility of the new coronavirus, it will be important to monitor for human-to-cat, cat-to-cat and cat-to-human transmission.", - "rel_num_authors": 20, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.23.309849", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been identified as the causative agent of coronavirus disease 2019 (COVID-19). While the development of specific treatments and a vaccine is urgently needed, functional analyses of SARS-CoV-2 have been limited by the lack of convenient mutagenesis methods. In this study, we established a PCR-based, bacterium-free method to generate SARS-CoV-2 infectious clones. Recombinant SARS-CoV-2 could be rescued at high titer with high accuracy after assembling 10 SARS-CoV-2 cDNA fragments by circular polymerase extension reaction (CPER) and transfection of the resulting circular genome into susceptible cells. Notably, the construction of infectious clones for reporter viruses and mutant viruses could be completed in two simple steps: introduction of reporter genes or mutations into the desirable DNA fragments (~5,000 base pairs) by PCR and assembly of the DNA fragments by CPER. We hope that our reverse genetics system will contribute to the further understanding of SARS-CoV-2.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Margaret J Hosie", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Ilaria Epifano", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Vanessa Herder", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Richard Orton", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Andrew Stevenson", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Natasha Johnson", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Emma MacDonald", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Dawn Dunbar", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Michael McDonald", - "author_inst": "University of Glasgow" - }, - { - "author_name": "Fiona Howie", - "author_inst": "SRUC Veterinary Services" - }, - { - "author_name": "Bryn Tennant", - "author_inst": "SRUC Veterinary Services" + "author_name": "Shiho Torii", + "author_inst": "Department of Molecular Virology, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Darcy Herrity", - "author_inst": "Fareham Creek Veterinary Surgery" + "author_name": "Chikako Ono", + "author_inst": "Department of Molecular Virology, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Ana C Filipe", - "author_inst": "University of Glasgow" + "author_name": "Rigel Suzuki", + "author_inst": "Department of Molecular Virology, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "Daniel G Streicker", - "author_inst": "University of Glasgow" + "author_name": "Yuhei Morioka", + "author_inst": "Osaka University" }, { - "author_name": "Brian J Willett", - "author_inst": "University of Glasgow" + "author_name": "Itsuki Anzai", + "author_inst": "Osaka University" }, { - "author_name": "Pablo R Murcia", - "author_inst": "University of Glasgow" + "author_name": "Yuzy Fauzyah", + "author_inst": "Osaka University" }, { - "author_name": "Ruth F Jarrett", - "author_inst": "University of Glasgow" + "author_name": "Yusuke Maeda", + "author_inst": "Department of Molecular Virology, Research Institute for Microbial Diseases, Osaka University" }, { - "author_name": "David L Robertson", - "author_inst": "University of Glasgow" + "author_name": "Wataru Kamitani", + "author_inst": "Gunma University Graduate School of Medicine" }, { - "author_name": "William Weir", - "author_inst": "University of Glasgow" + "author_name": "Takasuke Fukuhara", + "author_inst": "Hokkaido University" }, { - "author_name": "- COVID-19 Genomics UK Consortium", - "author_inst": "-" + "author_name": "Yoshiharu Matsuura", + "author_inst": "Osaka University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "microbiology" }, @@ -1184465,37 +1184147,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.22.20198275", - "rel_title": "Knowledge, Attitude and Practice towards COVID-19 among people in Bangladesh during the pandemic: a cross-sectional study.", + "rel_doi": "10.1101/2020.09.22.20199802", + "rel_title": "Smoking is associated with worse outcomes of COVID-19 particularly among younger adults: A systematic review and meta-analysis", "rel_date": "2020-09-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20198275", - "rel_abs": "The world is grappling with Covid-19, a dire public health crisis. Preventive and control measures are adopted to reduce the spread of COVID-19. It is important to know the knowledge, attitude, and practice (KAP) of people towards this pandemic to suggest appropriate coping strategies. The aim of this study was to assess the KAP of Bangladeshi people towards Covid-19 and determinants of those KAPs. We conducted a cross-sectional survey of 492 Bangladeshi people aged above 18 years from May 7 to 29, 2020 throughout the country. Simple and multiple logistic regression analyses were conducted to identify the factors associated with KAP on COVID-19. About 45% of respondents had good knowledge, 49% of respondents expressed positive attitude towards controlling of COVID-19 and 24% of respondents had favorable practice towards COVID-19. Almost three fourths of the respondents went outside home during the lockdown period. Furthermore, the study found that good knowledge and attitude were associated with better practice of COVID-19 health measures. An evidence informed and context specific risk communication and community engagement, and a social and behavior change communication strategy against COVID-19 should be developed in Bangladesh, based on the findings of this study, targeting different socio-economic groups.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.22.20199802", + "rel_abs": "Background: Smoking impairs lung immune functions and damages upper airways, increasing risks of contracting and severity of infectious diseases. Methods: We searched PubMed and Embase for studies published from January 1-May 25, 2020. We included studies reporting smoking behavior of COVID-19 patients and progression of disease, including death. We used a random effects meta-analysis and used meta-regression and lowess regressions to examine relationships in the data. Results: We identified 47 peer-reviewed papers with a total of 31,871 COVID-19 patients, 5,759 (18.1%) experienced disease progression and 5,734 (18.0%) with a history of smoking. Among smokers, 29.2% experienced disease progression, compared with 21.1% of non-smokers. The meta-analysis confirmed an association between smoking and COVID-19 progression (OR 1.56, 95% CI 1.32-1.83, p=0.001). Smoking was associated with increased risk of death from COVID-19 (OR 1.19, 95% CI 1.05-1.34, p=0.007). We found no significant difference (p=0.432) between the effects of smoking on COVID-19 disease progression between adjusted and unadjusted analyses, suggesting that smoking is an independent risk factor for COVID-19 disease progression. We also found the risk of having COVID-19 progression among younger adults (p=0.023), with the effect most pronounced among people under about 45 years old. Conclusions: Smoking is an independent risk for having severe progression of COVID-19, including mortality. The effects seem to be higher among young people. Smoking prevention and cessation should remain a priority for the public, physicians, and public health professionals during the COVID-19 pandemic.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Md. Golam Rabbani", - "author_inst": "Public Health Foundation, Bangladesh" - }, - { - "author_name": "Orin Akter", - "author_inst": "icddr,b" - }, - { - "author_name": "Md. Zahid Hasan", - "author_inst": "icddr,b" - }, - { - "author_name": "Nandeeta Samad", - "author_inst": "North South University, Dhaka, Bangladesh" - }, - { - "author_name": "Shehrin Shaila Mahmood", - "author_inst": "icddr,b" + "author_name": "ROENGRUDEE PATANAVANICH", + "author_inst": "Faculty of Medicine Ramathibodi Hospital, Mahidol University" }, { - "author_name": "Taufique Joarder", - "author_inst": "Public Health Foundation, Bangladesh; Johns Hopkins Bloomberg School of Public Health" + "author_name": "STANTON A GLANTZ", + "author_inst": "University of California San Francisco" } ], "version": "1", @@ -1186571,31 +1186237,27 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.09.18.20197582", - "rel_title": "Ruling In and Ruling Out COVID-19: Computing SARS-CoV-2 Infection Risk From Symptoms, Imaging and Test Data.", + "rel_doi": "10.1101/2020.09.20.20198150", + "rel_title": "Forecasting daily COVID-19 confirmed, deaths and recovered cases using univariate time series models: A case of Pakistan study", "rel_date": "2020-09-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.18.20197582", - "rel_abs": "BackgroundAssigning meaningful probabilities of SARS-CoV-2 infection risk presents a diagnostic challenge across the continuum of care.\n\nMethodsWe integrated patient symptom and test data using machine learning and Bayesian inference to quantify individual patient risk of SARS-CoV-2 infection. We trained models with 100,000 simulated patient profiles based on thirteen symptoms, estimated local prevalence, imaging, and molecular diagnostic performance from published reports. We tested these models with consecutive patients who presented with a COVID-19 compatible illness at the University of California San Diego Medical Center over 14 days starting in March 2020.\n\nResultsWe included 55 consecutive patients with fever (78%) or cough (77%) presenting for ambulatory (n=11) or hospital care (n=44). 51% (n=28) were female, 49% were age <60. Common comorbidities included diabetes (22%), hypertension (27%), cancer (16%) and cardiovascular disease (13%). 69% of these (n=38) were RT-PCR confirmed positive for SARS-CoV-2 infection, 11 had repeated negative nucleic acid testing and an alternate diagnosis. Bayesian inference network, distance metric-learning, and ensemble models discriminated between patients with SARS-CoV-2 infection and alternate diagnoses with sensitivities of 81.6 - 84.2%, specificities of 58.8 - 70.6%, and accuracies of 61.4 - 71.8%. After integrating imaging and laboratory test statistics with the predictions of the Bayesian inference network, changes in diagnostic uncertainty at each step in the simulated clinical evaluation process were highly sensitive to location, symptom, and diagnostic test choices.\n\nConclusionsDecision support models that incorporate symptoms and available test results can help providers diagnose SARS-CoV-2 infection in real world settings.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.20.20198150", + "rel_abs": "The increasing confirmed cases and death counts of Coronavirus disease 2019 (COVID-19) in Pakistan has disturbed not only the health sector, but also all other sectors of the country. For precise policy making, accurate and efficient forecasts of confirmed cases and death counts are important. In this work, we used five different univariate time series models including; Autoregressive (AR), Moving Average (MA), Autoregressive Moving Average (ARMA), Nonparametric Autoregressive (NPAR) and Simple Exponential Smoothing (SES) models for forecasting confirmed, death and recovered cases. These models were applied to Pakistan COVID-19 data, covering the period from 10, March to 3, July 2020. To evaluate models accuracy, computed two standard mean errors such as Mean Absolute Error (MAE) and Root Mean Square Error (RMSE). The findings show that the time series models are useful in predicting COVID-19 confirmed, deaths and recovered cases. Furthermore, MA model outperformed the rest of all models for confirmed and deaths counts prediction, while ARMA is second best model. The SES model seems superior to other models for prediction of recovered counts, however MA is competitive. On the basis of best selected models, we forecast form 4th July to 14th August, 2020, which will be helpful for decision making of public health and other sectors of Pakistan.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Chistopher D'Ambrosia", - "author_inst": "University of California San Diego, Department of Computer Science and Engineering" + "author_name": "Hasnain Iftikhar", + "author_inst": "Quaid-i-Azam University Islamabad, Pakistan" }, { - "author_name": "Henrik Christensen", - "author_inst": "University of California San Diego, Department of Computer Science and Engineering" - }, - { - "author_name": "Eliah Aronoff-Spencer", - "author_inst": "UC San Diego" + "author_name": "Moeeba Iftikhar", + "author_inst": "Department of Psychology, University of Peshawar, Pakistan." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "health policy" }, { "rel_doi": "10.1101/2020.09.19.20197855", @@ -1188153,65 +1187815,77 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.09.22.308023", - "rel_title": "Humoral response to SARS-CoV-2 by healthy and sick dogs during COVID-19 pandemic in Spain.", + "rel_doi": "10.1101/2020.09.22.307751", + "rel_title": "High prevalence of SARS-CoV-2 antibodies in pets from COVID-19+ households", "rel_date": "2020-09-22", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.22.308023", - "rel_abs": "COVID-19 is a zoonotic disease originated by SARS-CoV-2. Infection of animals with SARS-CoV-2 are being reported during last months, and also an increase of severe lung pathologies in domestic dogs has been detected by veterinarians in Spain. Therefore it is necessary to describe the pathological processes in those animals that show symptoms similar to those described in humans affected by COVID-19. The potential for companion animals contributing to the continued human-to-human disease, infectivity, and community spread is an urgent issue to be considered.\n\nForty animals with pulmonary pathologies were studied by chest X-ray, ultrasound study, and computed tomography. Nasopharyngeal and rectal swab were analyzed to detect canine pathogens, including SARS-CoV-2. Twenty healthy dogs living in SARS-CoV-2 positive households were included. Immunoglobulin detection by different immunoassays was performed. Our findings show that sick dogs presented severe alveolar or interstitial pattern, with pulmonary opacity, parenchymal abnormalities, and bilateral lesions. Forty dogs were negative for SARS-CoV-2 but Mycoplasma spp. was detected in 26 of 33 dogs. Five healthy and one pathological dog presented IgG against SARS-CoV-2.\n\nHere we report that despite detecting dogs with IgG -SARS-CoV-2, we never obtained a positive RT-qPCR, not even in dogs with severe pulmonary disease; suggesting that even in the case of a canine infection transmission would be unlikely. Moreover, dogs living in COVID-19 positive households could have been more exposed to be infected during outbreaks.", - "rel_num_authors": 12, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.22.307751", + "rel_abs": "In a survey of household cats and dogs of laboratory-confirmed COVID-19 patients, we found a high seroprevalence of SARS-CoV-2 antibodies, ranging from 21% to 53%, depending on the positivity criteria chosen. Seropositivity was significantly greater among pets from COVID-19+ households compared to those with owners of unknown status. Our results highlight the potential role of pets in the spread of the epidemic.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Ana Judith Perise-Barrios", - "author_inst": "Universidad Alfonso X el Sabio" + "author_name": "Matthieu Fritz", + "author_inst": "Institut de Recherche pour le Developpement" }, { - "author_name": "Beatriz Davinia Tomeo-Martin", - "author_inst": "Universidad Alfonso X el Sabio" + "author_name": "Beatrice Rosolen", + "author_inst": "CHRU hopital Jean-Minjoz" }, { - "author_name": "Pablo Gomez-Ochoa", - "author_inst": "Vetcorner" + "author_name": "Emilie Krafft", + "author_inst": "VetAgro Sup" }, { - "author_name": "Pablo Delgado-Bonet", - "author_inst": "Universidad Alfonso X el Sabio" + "author_name": "Pierre Becquart", + "author_inst": "Institut de Recherche pour le Developpement" }, { - "author_name": "Pedro Plaza", - "author_inst": "ERVET-DIEZ BRU" + "author_name": "Eric Elguero", + "author_inst": "Institut de Recherche pour le Developpement" }, { - "author_name": "Paula Palau-Concejo", - "author_inst": "Universidad Alfonso X el Sabio" + "author_name": "Oxana Vratskikh", + "author_inst": "Institut Pasteur Paris" }, { - "author_name": "Jorge Gonzalez", - "author_inst": "Micros Veterinaria SL" + "author_name": "Solene Denolly", + "author_inst": "Centre International de Recherche en Infectiologie" }, { - "author_name": "Gustavo Ortiz-Diez", - "author_inst": "Universidad Alfonso X el Sabio" + "author_name": "Bertrand Boson", + "author_inst": "Centre International de Recherche en Infectiologie" }, { - "author_name": "Antonio Melendez-Lazo", - "author_inst": "Laboklin GmbH & Co. KG" + "author_name": "Jessica Vanhomwegen", + "author_inst": "Institut Pasteur Paris" }, { - "author_name": "Michaela Gentil", - "author_inst": "Laboklin GmbH & Co. KG" + "author_name": "Meriadeg Ar Gouilh", + "author_inst": "Normandie Universite/Centre Hospitalo-Universitaire Cean" }, { - "author_name": "Javier Garcia-Castro", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Angeli Kodjo", + "author_inst": "VetAgro Sup" + }, + { + "author_name": "Catherine Chirouze", + "author_inst": "CHRU hopital Jean-Minjoz/Universite de Bourgogne Franche-Comte" + }, + { + "author_name": "Serge Rosolen", + "author_inst": "Sorbonne Universite Institut de la Vision/Clinique Veterinaire Voltaire" + }, + { + "author_name": "Vincent Legros", + "author_inst": "Centre International de Recherche en Infectiologie/VetAgro Sup" }, { - "author_name": "Alicia Barbero-Fernandez", - "author_inst": "Universidad Alfonso X el Sabio" + "author_name": "Eric M. Leroy", + "author_inst": "Institut de Recherche pour le Developpement" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -1189714,27 +1189388,87 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2020.09.18.304493", - "rel_title": "An immunodominance hierarchy exists in CD8+ T cell responses to HLA-A*02:01-restricted epitopes identified from the non-structural polyprotein 1a of SARS-CoV-2.", + "rel_doi": "10.1101/2020.09.18.304139", + "rel_title": "Antisense oligonucleotides target a nearly invariant structural element from the SARS-CoV-2 genome and drive RNA degradation", "rel_date": "2020-09-19", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.18.304493", - "rel_abs": "COVID-19 vaccines are being rapidly developed and human trials are underway. Almost all of these vaccines have been designed to induce antibodies targeting spike protein of SARS-CoV-2 in expectation of neutralizing activities. However, non-neutralizing antibodies are at risk of causing antibody-dependent enhancement. Further, the longevity of SARS-CoV-2-specific antibodies is very short. Therefore, in addition to antibody-induced vaccines, novel vaccines on the basis of SARS-CoV-2-specific cytotoxic T lymphocytes (CTLs) should be considered in the vaccine development. Here, we attempted to identify HLA-A*02:01-restricted CTL epitopes derived from the non-structural polyprotein 1a of SARS-CoV-2. Eighty-two peptides were firstly predicted as epitope candidates on bioinformatics. Fifty-four in 82 peptides showed high or medium binding affinities to HLA-A*02:01. HLA-A*02:01 transgenic mice were then immunized with each of the 54 peptides encapsulated into liposomes. The intracellular cytokine staining assay revealed that 18 out of 54 peptides were CTL epitopes because of the induction of IFN-{gamma}-producing CD8+ T cells. In the 18 peptides, 10 peptides were chosen for the following analyses because of their high responses. To identify dominant CTL epitopes, mice were immunized with liposomes containing the mixture of the 10 peptides. Some peptides were shown to be statistically predominant over the other peptides. Surprisingly, all mice immunized with the liposomal 10 peptide mixture did not show the same reaction pattern to the 10 peptides. There were three pattern types that varied sequentially, suggesting the existence of an immunodominance hierarchy, which may provide us more variations in the epitope selection for designing CTL-based COVID-19 vaccines.\n\nImportanceFor the development of vaccines based on SARS-CoV-2-specific cytotoxic T lymphocytes (CTLs), we attempted to identify HLA-A*02:01-restricted CTL epitopes derived from the non-structural polyprotein 1a of SARS-CoV-2. Out of 82 peptides predicted on bioinformatics, 54 peptides showed good binding affinities to HLA-A*02:01. Using HLA-A*02:01 transgenic mice, 18 in 54 peptides were found to be CTL epitopes in the intracellular cytokine staining assay. Out of 18 peptides, 10 peptides were chosen for the following analyses because of their high responses. To identify dominant epitopes, mice were immunized with liposomes containing the mixture of the 10 peptides. Some peptides were shown to be statistically predominant. Surprisingly, all immunized mice did not show the same reaction pattern to the 10 peptides. There were three pattern types that varied sequentially, suggesting the existence of an immunodominance hierarchy, which may provide us more variations in the epitope selection for designing CTL-based COVID-19 vaccines.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.18.304139", + "rel_abs": "RNA structural elements occur in numerous single stranded (+)-sense RNA viruses. The stemloop 2 motif (s2m) is one such element with an unusually high degree of sequence conservation, being found in the 3 UTR in the genomes of many astroviruses, some picornaviruses and noroviruses, and a variety of coronaviruses, including SARS-CoV and SARS-CoV-2. The evolutionary conservation and its occurrence in all viral subgenomic transcripts implicates a key role of s2m in the viral infection cycle. Our findings indicate that the element, while stably folded, can nonetheless be invaded and remodelled spontaneously by antisense oligonucleotides (ASOs) that initiate pairing in exposed loops and trigger efficient sequence-specific RNA cleavage in reporter assays. ASOs also act to inhibit replication in an astrovirus replicon model system in a sequence-specific, dose-dependent manner and inhibit SARS-CoV-2 infection in cell culture. Our results thus permit us to suggest that the s2m element is a site of vulnerability readily targeted by ASOs, which show promise as anti-viral agents.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Akira Takagi", - "author_inst": "Saitama Medical University" + "author_name": "Valeria Lulla", + "author_inst": "University of Cambridge" }, { - "author_name": "Masanori Matsui", - "author_inst": "Saitama Medical University" + "author_name": "Michal P Wandel", + "author_inst": "MRC LMB" + }, + { + "author_name": "Katarzyna J Bandyra", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Tom Dendooven", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Xiaofei Yang", + "author_inst": "John Ines Centre" + }, + { + "author_name": "Nicole Doyle", + "author_inst": "Pirbright Institute" + }, + { + "author_name": "Stephanie Oerum", + "author_inst": "CNRS/Univ Paris Diderot" + }, + { + "author_name": "Felix Randow", + "author_inst": "MRC LMB" + }, + { + "author_name": "Helena J Maier", + "author_inst": "The Pirbright Institute" + }, + { + "author_name": "William Scott", + "author_inst": "University of California Santa Cruz" + }, + { + "author_name": "Yiliang Ding", + "author_inst": "John Innes Centre" + }, + { + "author_name": "Andrew Firth", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Kotryna Bloznelyte", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Ben Luisi", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Rachel Ulferts", + "author_inst": "The Francis Crick Institute" + }, + { + "author_name": "Mary Wu", + "author_inst": "Crick Institute" + }, + { + "author_name": "Rupert Beale", + "author_inst": "Crick Institute" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "immunology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.09.16.300970", @@ -1191152,43 +1190886,39 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.09.15.20191957", - "rel_title": "Adherence to the test, trace and isolate system: results from a time series of 21 nationally representative surveys in the UK (the COVID-19 Rapid Survey of Adherence to Interventions and Responses study)", + "rel_doi": "10.1101/2020.09.15.20195222", + "rel_title": "Demand for Self-Managed Online Telemedicine Abortion in Eight European Countries During the COVID-19 Pandemic: A Regression Discontinuity Analysis", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.15.20191957", - "rel_abs": "Objectives: To investigate rates of adherence to the UKs test, trace and isolate system over time. Design: Time series of cross-sectional online surveys. Setting: Data were collected between 2 March and 5 August 2020. Participants: 42,127 responses from 31,787 people living in the UK, aged 16 years or over, are presented (21 survey waves, n{approx}2,000 per wave). Main outcome measures: Identification of the key symptoms of COVID-19 (cough, high temperature / fever, and loss of sense of smell or taste), self-reported adherence to self-isolation if symptomatic, requesting an antigen test if symptomatic, intention to share details of close contacts, self-reported adherence to quarantine if alerted that you had been in contact with a confirmed COVID-19 case. Results: Only 48.9% of participants (95% CI 48.2% to 49.7%) identified key symptoms of COVID-19. Self-reported adherence to test, trace and isolate behaviours was low (self-isolation 18.2%, 95% CI 16.4% to 19.9%; requesting an antigen test 11.9%, 95% CI 10.1% to 13.8%; intention to share details of close contacts 76.1%, 95% CI 75.4% to 76.8%; quarantining 10.9%, 95% CI 7.8% to 13.9%) and largely stable over time. By contrast, intention to adhere to protective measures was much higher. Non-adherence was associated with: men, younger age groups, having a dependent child in the household, lower socio-economic grade, greater hardship during the pandemic, and working in a key sector. Conclusions: Practical support and financial reimbursement is likely to improve adherence. Targeting messaging and policies to men, younger age groups, and key workers may also be necessary.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.15.20195222", + "rel_abs": "ObjectivesIn most European countries, patients seeking medication abortion during the COVID-19 pandemic are still expected to attend healthcare settings in person despite lockdown measures and infection risk. We assessed whether demand for self-managed medication abortion provided by a fully remote online telemedicine service increased following the emergence of COVID-19.\n\nDesignWe used regression discontinuity to compare the number of requests to online telemedicine service Women on Web in eight European countries before and after they implemented lockdown measures to slow COVID-19 transmission. We examined the number deaths due to COVID-19, the degree of government-provided economic support, the severity of lockdown travel restrictions, and the medication abortion service provision model in countries with and without significant changes in requests.\n\nSettingEight European countries served by Women on Web.\n\nParticipants3,915 people who made requests for self-managed abortion to Women on Web between January 1st, 2019 and June 1st, 2020.\n\nMain Outcome MeasuresPercent change in requests to Women on Web before and after the emergence of COVID-19 and associated lockdown measures.\n\nResultsFive countries showed significant increases in requests, ranging from 28% in Northern Ireland (p=0.001) to 139% in Portugal (p<0.001). Two countries showed no significant change in requests, and one country, Great Britain, showed an 88% decrease in requests (p<0.001). Countries with significant increases in requests were either countries where abortion services are mainly provided in hospitals or where no abortion services are available and international travel was prohibited during lockdown. By contrast, Great Britain authorized teleconsultation for medication abortion and provision of medications by mail during the pandemic.\n\nConclusionThese marked changes in requests for self-managed medication abortion during COVID-19 demonstrate demand for fully remote models of abortion care and an urgent need for policymakers to expand access to medication abortion by telemedicine.\n\nO_TEXTBOXO_TEXTBOXNOWhat this paper addsC_TEXTBOXNO What is already know on this subjectO_LIThe COVID-19 pandemic has presented challenges to patients seeking medication abortion, including lockdown travel restrictions and infection risk during in-person clinic visits.\nC_LIO_LIYet in most European countries, medication abortion must still be provided through in-person models of care. The sole exception is Great Britain, where a fully remote medication abortion service was introduced in response to the pandemic.\nC_LIO_LIAnecdotal reports suggest that patients are struggling to access in-person abortion services and may turn to self-managed abortion as a result. However, to date there has been no systematic assessment of this possibility.\nC_LI\n\nWhat this study addsO_LIOur study provides the best evidence to date that demand for self-managed medication abortion provided using online telemedicine increased following the emergence of the COVID-19 pandemic.\nC_LIO_LIThe largest increases were observed in countries where medication abortion is provided mainly in hospitals and where travel restrictions were most stringent. By contrast, in the one country that implemented fully remote services, demand for self-managed abortion declined almost to zero.\nC_LIO_LIOur findings demonstrate the urgent need for policymakers to expand access to telemedicine models of medication abortion within the formal healthcare setting.\nC_LI\n\nC_TEXTBOX", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Louise E. Smith", - "author_inst": "King's College London" - }, - { - "author_name": "Henry W. W. Potts", - "author_inst": "University College London" + "author_name": "Abigail R.A. Aiken", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Richard Amlot", - "author_inst": "Public Health England" + "author_name": "Jennifer E Starling", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Nicola T. Fear", - "author_inst": "King's College London" + "author_name": "Rebecca Gomperts", + "author_inst": "Women on Web" }, { - "author_name": "Susan Michie", - "author_inst": "University College London" + "author_name": "James G Scott", + "author_inst": "University of Texas at Austin" }, { - "author_name": "James Rubin", - "author_inst": "King's College London" + "author_name": "Catherine Aiken", + "author_inst": "University of Cambridge" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "sexual and reproductive health" }, { "rel_doi": "10.1101/2020.09.14.20193177", @@ -1193206,97 +1192936,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.16.20195446", - "rel_title": "High-throughput quantitation of SARS-CoV-2 antibodies in a single-dilution homogeneous assay", + "rel_doi": "10.1101/2020.09.16.20193466", + "rel_title": "Inexpensive, versatile and open-source methods for SARS-CoV-2 detection", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20195446", - "rel_abs": "SARS-CoV-2 emerged in late 2019 and has since spread around the world, causing a pandemic of the respiratory disease COVID-19. Detecting antibodies against the virus is an essential tool for tracking infections and developing vaccines. Such tests, primarily utilizing the enzyme-linked immunosorbent assay (ELISA) principle, can be either qualitative (reporting positive/negative results) or quantitative (reporting a value representing the quantity of specific antibodies). Quantitation is vital for determining stability or decline of antibody titers in convalescence, efficacy of different vaccination regimens, and detection of asymptomatic infections. Quantitation typically requires two-step ELISA testing, in which samples are first screened in a qualitative assay and positive samples are subsequently analyzed as a dilution series. To overcome the throughput limitations of this approach, we developed a simpler and faster system that is highly automatable and achieves quantitation in a single-dilution screening format with sensitivity and specificity comparable to those of ELISA.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20193466", + "rel_abs": "Re-opening of communities in the midst of the ongoing COVID-19 pandemic has ignited a second wave of infections in many places around the world. Mitigating the risk of reopening will require widespread SARS-CoV-2 testing, which would be greatly facilitated by simple, rapid, and inexpensive testing methods. To this end, we evaluated several protocols for RNA extraction and RT-qPCR that are simpler and less expensive than prevailing methods. First, we show that isopropanol precipitation provides an effective means of RNA extraction from nasopharyngeal (NP) swab samples. Second, we evaluate direct addition of NP swab samples to RT-qPCR reactions without an RNA extraction step. We describe a simple, inexpensive swab collection solution suitable for direct addition, which we validate using contrived swab samples. Third, we describe an open-source master mix for RT-qPCR and show that it permits detection of viral RNA in NP swab samples. Lastly, we show that an end-point fluorescence measurement provides an accurate diagnostic readout without requiring a qPCR thermocycler. Adoption of these simple, inexpensive methods has the potential to significantly reduce the time and expense of COVID-19 testing.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Markus H Kainulainen", - "author_inst": "Viral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, GA, USA" - }, - { - "author_name": "Eric Bergeron", - "author_inst": "Viral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, GA, USA" - }, - { - "author_name": "Payel Chatterjee", - "author_inst": "Viral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, GA, USA" - }, - { - "author_name": "Asheley P Chapman", - "author_inst": "School of Chemistry and Biochemistry, School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA" - }, - { - "author_name": "Joo Lee", - "author_inst": "Reagent and Diagnostic Services Branch, Division of Scientific Resources, Centers for Disease Control and Prevention, Atlanta, GA, USA" - }, - { - "author_name": "Asiya Chida", - "author_inst": "Reagent and Diagnostic Services Branch, Division of Scientific Resources, Centers for Disease Control and Prevention, Atlanta, GA, USA" - }, - { - "author_name": "Xiaoling Tang", - "author_inst": "Reagent and Diagnostic Services Branch, Division of Scientific Resources, Centers for Disease Control and Prevention, Atlanta, GA, USA" - }, - { - "author_name": "Rebekah E Wharton", - "author_inst": "Emergency Response Branch, Division of Laboratory Sciences, Centers for Disease Control and Prevention, Atlanta, GA, USA" - }, - { - "author_name": "Kristina B Mercer", - "author_inst": "Newborn Screening & Molecular Biology Branch, Division of Laboratory Sciences, Centers for Disease Control and Prevention, Atlanta, GA, USA" - }, - { - "author_name": "Marla Petway", - "author_inst": "Reagent and Diagnostic Services Branch, Division of Scientific Resources, Centers for Disease Control and Prevention, Atlanta, GA, USA" - }, - { - "author_name": "Harley M Jenks", - "author_inst": "Viral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Thomas G.W. Graham", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Timothy D Flietstra", - "author_inst": "Viral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Claire Dugast-Darzacq", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Amy J Schuh", - "author_inst": "Viral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Gina M. Dailey", + "author_inst": "University of California Berkeley" }, { - "author_name": "Panayampalli S Satheshkumar", - "author_inst": "Poxvirus and Rabies Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Xammy Huu Nguyenla", + "author_inst": "University of California Berkeley" }, { - "author_name": "Jasmine M Chaitram", - "author_inst": "Division of Laboratory Systems, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Erik Van Dis", + "author_inst": "University of California Berkeley" }, { - "author_name": "S Michele Owen", - "author_inst": "National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Meagan N. Esbin", + "author_inst": "University of California Berkeley" }, { - "author_name": "M G Finn", - "author_inst": "School of Chemistry and Biochemistry, School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA, USA" + "author_name": "Abrar Abidi", + "author_inst": "University of California Berkeley" }, { - "author_name": "Jason M Goldstein", - "author_inst": "Reagent and Diagnostic Services Branch, Division of Scientific Resources, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Sarah A Stanley", + "author_inst": "University of California Berkeley" }, { - "author_name": "Joel M Montgomery", - "author_inst": "Viral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Xavier Darzacq", + "author_inst": "UC Berkeley" }, { - "author_name": "Christina F Spiropoulou", - "author_inst": "Viral Special Pathogens Branch, Division of High-Consequence Pathogens and Pathology, Centers for Disease Control and Prevention, Atlanta, GA, USA" + "author_name": "Robert Tjian", + "author_inst": "University of California Berkeley" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1194876,41 +1194566,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.18.20195669", - "rel_title": "How do the general population behave with facemasks to prevent COVID-19 in the community?", + "rel_doi": "10.1101/2020.09.16.20195750", + "rel_title": "Association between corticosteroids and intubation or death among patients with COVID-19 pneumonia in non-ICU settings: an observational study using of real-world data from 51 hospitals in France and Luxembourg", "rel_date": "2020-09-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.18.20195669", - "rel_abs": "IMPORTANCE The appropriate use of facemasks, recommended or mandated by authorities, is critical to protect the community and prevent the spread of COVID-19. OBJECTIVE To evaluate the frequency and quality of facemask use in general populations of different socio-spatial backgrounds. DESIGN A multi-site observational study carried out from 25 June 2020 to 21 July 2020. SETTING The observations were carried out in 43 different locations in a region in the west of France, representing various areas: rural and urban, indoor and outdoor, and in areas where masks were mandated or not. An observer was positioned at a predetermined place, facing a landmark, and collected information about the use of facemasks and socio-demographic data. PARTICIPANTS All individual passing between the observer and the landmark were included. EXPOSURE The observer collected information on whether a mask was worn, the type of mask used, the quality of the positioning, gender, and the age category of each individual. MAIN OUTCOMES AND MEASURES The main outcomes were the use of a facemask and the quality of the positioning. Factors associated with these outcomes were identified. RESULTS A total of 3354 observations were recorded. A facemask was worn by 56.4% (n=1892) of individuals, varying from 49% (n=1359) in non-mandatory areas and 91.7% (n=533) in mandatory areas, including surgical facemasks (56.8%, n=1075) and cloth masks (43.2%, n=817). The facemask was correctly positioned in 75.2% (n=1422) of cases. The factors independently associated with wearing a facemask were being indoors (adjusted odds ratio [aOR], 0.37; 95% confidence interval [CI], 0.31-0.44), being in a mandatory area (aOR, 0.14; 95%CI, 0.10-0.20), female gender (aOR, 0.57; 95%CI, 0.49-0.66), and age >40 years (aOR, 0.54; 95%CI, 0.46-0.63). The factors independently associated with correct mask position were rural location (aOR, 0.76; 95%CI, 0.97-0.98), being in an indoor area (aOR, 0.49; 95%CI, 0.38-0.65), use of a cloth mask (aOR, 0.65; 95%CI, 0.52-0.81), and age >40 years (aOR, 0.61; 95%CI 0.49-0.76). CONCLUSIONS AND RELEVANCE Information campaigns should promote the use of cloth masks. Young people in general and men in particular are the priority targets. Simplifying the rules to require universal mandatory masking seems to be the best approach for health authorities.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.16.20195750", + "rel_abs": "Objective To assess the effectiveness of corticosteroids on outcomes of patients with mild COVID-19 pneumonia. Methods We used routine care data from 51 hospitals in France and Luxembourg to assess the effectiveness of corticosteroids at 0.8 mg/kg/day eq. prednisone (CTC group) vs standard of care (no-CTC group) among patients [≤] 80 years old with COVID-19 pneumonia requiring oxygen without mechanical ventilation. The primary outcome was intubation or death at Day 28. Baseline characteristics of patients were balanced using propensity score inverse probability of treatment weighting. Results Among the 891 patients included in the analysis, 203 were assigned to the CTC group. At day 28, corticosteroids did not reduce the rate of the primary outcome (wHR 0.92, 95% CI 0.61 to 1.39) nor the cumulative death rate (wHR 1.03, 95% CI 0.54 to 1.98). Corticosteroids significantly reduced the rate of the primary outcome for patients requiring oxygen [≥] at 3L/min (wHR 0.50, 95% CI 0.30 to 0.85) or C-Reactive Protein (CRP) [≥] 100mg/L (wHR 0.44, 95%CI 0.23 to 0.85). We found a higher number of hyperglycaemia events among patients who received corticosteroids, but number of infections were similar across the two groups. Conclusions We found no association between the use of corticosteroids and intubation or death in the broad population of patients [≤]80 years old with COVID-19 hospitalized in non-ICU settings. However, the treatment was beneficial for patients with [≥] 3L/min oxygen or CRP [≥] 100mg/L at baseline. These data support the need to confirm the right timing of corticosteroids for patients with mild COVID.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Colin DESCHANVRES", - "author_inst": "CHU de Nantes" + "author_name": "Viet-Thi Tran", + "author_inst": "Universite de Paris" }, { - "author_name": "Thomas HAUDEBOURG", - "author_inst": "CHU de Nantes" + "author_name": "Matthieu Mahevas", + "author_inst": "APHP" }, { - "author_name": "Nathan PEIFFER-SMADJA", - "author_inst": "Hopital Bichat Claude Bernard" + "author_name": "Firouze Bani Sadr", + "author_inst": "CHU Reims" }, { - "author_name": "Karine BLANCKAERT", - "author_inst": "CHU de Nantes" + "author_name": "Olivier Robineau", + "author_inst": "CHU Tourcoing" }, { - "author_name": "David BOUTOILLE", - "author_inst": "CHU de Nantes" + "author_name": "Thomas Perpoint", + "author_inst": "CHU Lyon" }, { - "author_name": "Jean-Christophe LUCET", - "author_inst": "Hopital Bichat Claude Bernard" + "author_name": "Elodie Perrodeau", + "author_inst": "APHP" }, { - "author_name": "Gabriel BIRGAND", - "author_inst": "CHU de Nantes" + "author_name": "Laure Gallay", + "author_inst": "CHU Lyon" + }, + { + "author_name": "Philippe Ravaud", + "author_inst": "APHP" + }, + { + "author_name": "Francois Goehringer", + "author_inst": "CHU Nancy" + }, + { + "author_name": "Xavier Lescure", + "author_inst": "APHP" + }, + { + "author_name": "- COCORICO", + "author_inst": "" } ], "version": "1", @@ -1196966,63 +1196672,95 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.09.16.299537", - "rel_title": "Mouse model for testing SARS-CoV-2 antivirals: Pharmacokinetics", + "rel_doi": "10.1101/2020.09.16.297945", + "rel_title": "Characterisation of protease activity during SARS-CoV-2 infection identifies novel viral cleavage sites and cellular targets for drug repurposing", "rel_date": "2020-09-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.16.299537", - "rel_abs": "Background and ObjectivesRemdesivir and hydroxychloroquine are or were among the most promising therapeutic options to tackle the current SARS-CoV-2 pandemic. Besides the use of the prodrug remdesivir itself, the direct administration of GS-441 524, the resulting main metabolite of remdesivir, could be advantageous and even more effective. All substances were not originally developed for the treatment of COVID-19 and especially for GS-441 524 little is known about its pharmacokinetic and physical-chemical properties. To justify the application of new or repurposed drugs in humans, pre-clinical in vivo animal models are mandatory to investigate relevant PK and PD properties and their relationship to each other. In this study, an adapted mouse model was chosen to demonstrate its suitability to provide sufficient information on the model substances GS-441 524 and HCQ regarding plasma concentration and distribution into relevant tissues a prerequisite for treatment effectiveness.\n\nMethodsGS-441 524 and HCQ were administered intravenously as a single injection to male mice. Blood and organ samples were taken at several time points and drug concentrations were quantified in plasma and tissue homogenates by two liquid chromatography/tandem mass spectrometry methods. In vitro experiments were conducted to investigate the degradation of remdesivir in human plasma and blood. All pharmacokinetic analyses were performed with R Studio using non-compartmental analysis.\n\nResultsHigh tissue to plasma ratios for GS-441 524 and HCQ were found, indicating a significant distribution into the examined tissue, except for the central nervous system and fat. For GS-441 524, measured tissue concentrations exceeded the reported in vitro EC50 values by more than 10-fold and in consideration of its high efficacy against feline infectious peritonitis, GS-441 524 could indeed be effective against SARS-CoV-2 in vivo. For HCQ, relatively high in vitro EC50 values are reported, which were not reached in all tissues. Facing its slow tissue distribution, HCQ might not lead to sufficient tissue saturation for a reliable antiviral effect.\n\nConclusionThe mouse model was able to characterise the PK and tissue distribution of both model substances and is a suitable tool to investigate early drug candidates against SARS-CoV-2. Furthermore, we could demonstrate a high tissue distribution of GS-441 524 even if not administered as the prodrug remdesivir.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.16.297945", + "rel_abs": "SARS-CoV-2 is the causative agent behind the COVID-19 pandemic, and responsible for over 170 million infections, and over 3.7 million deaths worldwide. Efforts to test, treat and vaccinate against this pathogen all benefit from an improved understanding of the basic biology of SARS-CoV-2. Both viral and cellular proteases play a crucial role in SARS-CoV-2 replication, and inhibitors targeting proteases have already shown success at inhibiting SARS-CoV-2 in cell culture models. Here, we study proteolytic cleavage of viral and cellular proteins in two cell line models of SARS-CoV-2 replication using mass spectrometry to identify protein neo-N-termini generated through protease activity. We identify previously unknown cleavage sites in multiple viral proteins, including major antigenic proteins S and N, which are the main targets for vaccine and antibody testing efforts. We discovered significant increases in cellular cleavage events consistent with cleavage by SARS-CoV-2 main protease, and identify 14 potential high-confidence substrates of the main and papain-like proteases, validating a subset with in vitro assays. We showed that siRNA depletion of these cellular proteins inhibits SARS-CoV-2 replication, and that drugs targeting two of these proteins: the tyrosine kinase SRC and Ser/Thr kinase MYLK, showed a dose-dependent reduction in SARS-CoV-2 titres. Overall, our study provides a powerful resource to understand proteolysis in the context of viral infection, and to inform the development of targeted strategies to inhibit SARS-CoV-2 and treat COVID-19.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Oliver Scherf-Clavel", - "author_inst": "University of Wuerzburg" + "author_name": "Bjoern Meyer", + "author_inst": "Institut Pasteur" }, { - "author_name": "Edith Kaczmarek", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Jeanne Chiaravalli", + "author_inst": "Institut Pasteur" }, { - "author_name": "Martina Kinzig", - "author_inst": "Institute for Biomedical and Pharmaceutical Research" + "author_name": "Stacy Gellenoncourt", + "author_inst": "Institut Pasteur" }, { - "author_name": "Bettina Friedl", - "author_inst": "University of Wuerzburg" + "author_name": "Philip Brownridge", + "author_inst": "University of Liverpool" }, { - "author_name": "Malte Feja", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Dominic P. Bryne", + "author_inst": "University of Liverpool" }, { - "author_name": "Rainer Hoehl", - "author_inst": "Paracelsus Medical Private University" + "author_name": "Leonard A. Daly", + "author_inst": "University of Liverpool" }, { - "author_name": "Roland Nau", - "author_inst": "University Medical Center Goettingen" + "author_name": "Arturas Grauslys", + "author_inst": "University of Liverpool" }, { - "author_name": "Ulrike Holzgrabe", - "author_inst": "University of Wuerzburg" + "author_name": "Marius Walter", + "author_inst": "Buck Institute for Aging" }, { - "author_name": "Manuela Gernert", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Fabrice Agou", + "author_inst": "Institut Pasteur" }, { - "author_name": "Franziska Richter", - "author_inst": "University of Veterinary Medicine Hannover" + "author_name": "Lisa A. Chakrabarti", + "author_inst": "Institut Pasteur" }, { - "author_name": "Fritz Soergel", - "author_inst": "Institute for Biomedical and Pharmaceutical Research, Paul-Ehrlich-Strasse 19, D-90562 Nuernberg-Heroldsberg" + "author_name": "Charles S. Craik", + "author_inst": "UCSF" + }, + { + "author_name": "Claire E. Eyers", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Patrick A. Eyers", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Yann Gambin", + "author_inst": "UNSW" + }, + { + "author_name": "Andrew R Jones", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Emma Sierecki", + "author_inst": "UNSW" + }, + { + "author_name": "Eric Verdin", + "author_inst": "Buck Institute for Aging" + }, + { + "author_name": "Marco Vignuzzi", + "author_inst": "Institut Pasteur" + }, + { + "author_name": "Edward Emmott", + "author_inst": "University of Liverpool" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", - "category": "systems biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.09.16.298992", @@ -1198648,95 +1198386,67 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.14.20191759", - "rel_title": "SARS-CoV-2 N-antigenemia: A new alternative to nucleic acid amplification techniques", + "rel_doi": "10.1101/2020.09.14.20194001", + "rel_title": "Predictors of characteristics associated with negative SARS-CoV-2 PCR test despite proven disease and association with treatment and outcomes.The COVID-19 RT-PCR Study.", "rel_date": "2020-09-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.14.20191759", - "rel_abs": "Background. Molecular assays on nasopharyngeal swabs remain the cornerstone of COVID-19 diagnostic. Despite massive worldwide efforts, the high technicalities of nasopharyngeal sampling and molecular assays, as well as scarce resources of reagents, limit our testing capabilities. Several strategies failed, to date, to fully alleviate this testing process (e.g. saliva sampling or antigen testing on nasopharyngeal samples). We assessed the performances of a new ELISA microplate assay quantifying SARS-CoV-2 nucleocapsid antigen (N-antigen) in serum or plasma. Methods. The specificity of the assay, determined on 63 non-COVID patients, was 98.4% (95% confidence interval [CI], 85.3 to 100). Performances were determined on 227 serum samples from 165 patients with RT-PCR confirmed SARS-CoV-2 infection included in the French COVID and CoV-CONTACT cohorts. Findings. Sensitivity was 132/142, 93.0% (95% CI, 84.7 to 100), within the first two weeks after symptoms onset. A subset of 73 COVID-19 patients had a serum collected within 24 hours following or preceding a positive nasopharyngeal swab. Among patients with high nasopharyngeal viral loads, Ct value below 30 and 33, only 1/50 and 4/67 tested negative for N-antigenemia, respectively. Among patients with a negative nasopharyngeal RT-PCR, 8/12 presented positive N-antigenemia. The lower respiratory tract was explored for 6/8 patients, showing positive PCR in 5 cases. Interpretation. This is the first demonstration of the N-antigen antigenemia during COVID-19. Its detection presented a robust sensitivity, especially within the first 14 days after symptoms onset and high nasopharyngeal viral loads. These findings have to be confirmed with higher representation of outpatients. This approach could provide a valuable new option for COVID-19 diagnosis, only requiring a blood draw and easily scalable in all clinical laboratories.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.14.20194001", + "rel_abs": "Background: Reverse transcriptase-polymerase chain reaction (RT PCR) testing is an important tool for the diagnosis of coronavirus disease 2019 (COVID19). However, performance concerns have recently emerged, especially about its sensitivity.. We hypothesized that clinical, biological and radiological characteristics of patients with false negative first RT-PCR testing, despite final diagnosis of COVID19, might differ from patients with positive first RT PCR. Methods: Case / control, multicenter study in which COVID19 patients with negative first RT PCR testing were matched to patients with positive first RT PCR on age, gender and initial admission unit (ward or intensive care). Results: Between March 30, and June 22, 2020, 80 cases and 80 controls were included. Neither proportion of death at hospital discharge, nor duration of hospital length stay differed between case and control patients (P=0.80 and P=0.54, respectively). In multivariate analysis, headache (adjusted OR: 0.07 [0.01 ; 0.49]; P=0.007) and fatigue/malaise (aOR: 0.16 [0.03 ; 0.81]; P=0.027) were associated with lower risk of false negative, whereas platelets > 207.103.mm-3 (aOR: 3.81 [1.10 ; 13.16]; P=0.034) and CRP > 79.8 mg.L-1 (aOR: 4.00 [1.21 ; 13.19]; P=0.023) were associated with higher risk of false negative. Interpretation: Patients with suspected COVID19 and higher inflammatory biological signs expected higher risk of false negative RT PCR testing. Strategy of serial RT PCR testings must be rigorously evaluated before adoption by clinicians.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Quentin Le Hingrat", - "author_inst": "Universite de Paris, Virology, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" - }, - { - "author_name": "Benoit Visseaux", - "author_inst": "Universite de Paris, Virology, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" - }, - { - "author_name": "Cedric Laouenan", - "author_inst": "Universite de Paris, Center for Clinical Investigation, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" - }, - { - "author_name": "Sarah Tubiana", - "author_inst": "Universite de Paris, Center for Clinical Investigation, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" - }, - { - "author_name": "Lila Bouadma", - "author_inst": "Universite de Paris, Medical and Infectious Diseases Intensive Care Unit, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Pari" - }, - { - "author_name": "Yazdan Yazdanpanah", - "author_inst": "Universite de Paris, Tropical and infectious diseases Department, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, Franc" - }, - { - "author_name": "Xavier Duval", - "author_inst": "Universite de Paris, Center for Clinical Investigation, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" - }, - { - "author_name": "Houria Ichou", - "author_inst": "Virology, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" + "author_name": "Jean Baptiste Lascarrou", + "author_inst": "CHU Nantes" }, { - "author_name": "Florence Damond", - "author_inst": "Virology, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" + "author_name": "Gwenhael Colin", + "author_inst": "CHD Vendee" }, { - "author_name": "Melanie Bertine", - "author_inst": "Virology, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" + "author_name": "Aurelie Le Thuaut", + "author_inst": "CHU Nantes" }, { - "author_name": "Nabil Benmalek", - "author_inst": "Virology, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" + "author_name": "Nicolas Serck", + "author_inst": "Clinique Saint Pierre" }, { - "author_name": "- French COVID cohort management committee", - "author_inst": "" + "author_name": "Mickael Ohana", + "author_inst": "CHRU Strasbourg" }, { - "author_name": "- CoV-CONTACT study group", - "author_inst": "" + "author_name": "Bertrand Sauneuf", + "author_inst": "CH Cherbourg En Contentin" }, { - "author_name": "Christophe Choquet", - "author_inst": "Emergency Department, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital Paris, France" + "author_name": "Guillaume Geri", + "author_inst": "CHU Ambroise Pare" }, { - "author_name": "Jean-Francois Timsit", - "author_inst": "Universite de Paris, Medical and Infectious Diseases Intensive Care Unit, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Pari" + "author_name": "Jean Baptiste Mesland", + "author_inst": "Hopital Jolimont" }, { - "author_name": "Jade Ghosn", - "author_inst": "Universite de Paris, Tropical and infectious diseases Department, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, Franc" + "author_name": "Gaetane Ribeyre", + "author_inst": "Centre de Soins" }, { - "author_name": "Charlotte Charpentier", - "author_inst": "Universite de Paris, Virology, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" + "author_name": "Claire Hussenet", + "author_inst": "Groupe Confluent" }, { - "author_name": "Diane Descamps", - "author_inst": "Universite de Paris, Virology, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" + "author_name": "Anne Sophie Boureau", + "author_inst": "CHU Nantes" }, { - "author_name": "Nadhira Houhou-Fidouh", - "author_inst": "Virology, Assistance Publique-Hopitaux de Paris, Bichat-Claude Bernard University Hospital, Paris, France" + "author_name": "Thomas Gille", + "author_inst": "Hopital Avicenne" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.09.15.298547", @@ -1200326,45 +1200036,89 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2020.09.13.20193722", - "rel_title": "Sensing of COVID-19 Antibodies in Seconds via Aerosol Jet Printed Three Dimensional Electrodes", + "rel_doi": "10.1101/2020.09.13.20193805", + "rel_title": "Genome sequencing of sewage detects regionally prevalent SARS-CoV-2 variants", "rel_date": "2020-09-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.13.20193722", - "rel_abs": "Rapid diagnosis is critical for the treatment and prevention of diseases. In this research, we report sensing of antibodies specific to SARS-CoV-2 virus in seconds via an electrochemical platform consisting of gold micropillar array electrodes decorated with reduced graphene oxide and functionalized with recombinant viral antigens. The array electrodes are fabricated by Aerosol Jet (AJ) nanoparticle 3D printing, where gold nanoparticles (3-5nm) are assembled in 3D space, sintered, and integrated with a microfluidic device. The device is shown to detect antibodies to SARS-CoV-2 spike S1 protein and its receptor-binding-domain (RBD) at concentrations down to 1pM via electrochemical impedance spectroscopy and read by a smartphone-based user interface. In addition, the sensor can be regenerated within a minute by introducing a low-pH chemistry that elutes the antibodies from the antigens, allowing successive testing of multiple antibody samples using the same sensor. The detection time for the two antibodies tested in this work is 11.5 seconds. S1 protein sensing of its antibodies is specific, which cross-reacts neither with other antibodies nor with proteins such as Nucleocapsid antibody and Interleukin-6 protein. The proposed sensing platform is generic and can also be used for the rapid detection of biomarkers for other infectious agents such as Ebola, HIV, and Zika, which will benefit the public health.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.13.20193805", + "rel_abs": "Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from nasopharyngeal swabs of individual patients to track viral spread. Recently, RT-qPCR of municipal wastewater has been used to quantify the abundance of SARS-CoV-2 in several regions globally. However, metatranscriptomic sequencing of wastewater can be used to profile the viral genetic diversity across infected communities. Here, we sequenced RNA directly from sewage collected by municipal utility districts in the San Francisco Bay Area to generate complete and near-complete SARS-CoV-2 genomes. The major consensus SARS-CoV-2 genotypes detected in the sewage were identical to clinical genomes from the region. Using a pipeline for single nucleotide variant (SNV) calling in a metagenomic context, we characterized minor SARS-CoV-2 alleles in the wastewater and detected viral genotypes which were also found within clinical genomes throughout California. Observed wastewater variants were more similar to local California patient-derived genotypes than they were to those from other regions within the US or globally. Additional variants detected in wastewater have only been identified in genomes from patients sampled outside of CA, indicating that wastewater sequencing can provide evidence for recent introductions of viral lineages before they are detected by local clinical sequencing. These results demonstrate that epidemiological surveillance through wastewater sequencing can aid in tracking exact viral strains in an epidemic context.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Md Azahar Ali", - "author_inst": "Carnegie Mellon University" + "author_name": "Alexander Crits-Christoph", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Chunshan Hu", - "author_inst": "Carnegie Mellon University" + "author_name": "Rose S Kantor", + "author_inst": "Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA" }, { - "author_name": "Sanjida Jahan", - "author_inst": "Carnegie Mellon University" + "author_name": "Matthew R Olm", + "author_inst": "Department of Microbiology and Immunology, Stanford University, CA, USA" }, { - "author_name": "Bin Yuan", - "author_inst": "Carnegie Mellon University" + "author_name": "Oscar N Whitney", + "author_inst": "Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA" }, { - "author_name": "Mohammad Sadeq Saleh", - "author_inst": "Carnegie Mellon University" + "author_name": "Basem Al-Shayeb", + "author_inst": "Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA" }, { - "author_name": "Enguo Ju", - "author_inst": "University of Pittsburgh Medical Center" + "author_name": "Yue C Lou", + "author_inst": "Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA" }, { - "author_name": "Shou-Jiang Gao", - "author_inst": "University of Pittsburgh Medical Center" + "author_name": "Avi Flamholz", + "author_inst": "Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA" }, { - "author_name": "Rahul P Panat", - "author_inst": "Carnegie Mellon University" + "author_name": "Lauren C Kennedy", + "author_inst": "Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA" + }, + { + "author_name": "Hannah Greenwald", + "author_inst": "Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA" + }, + { + "author_name": "Adrian Hinkle", + "author_inst": "Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA" + }, + { + "author_name": "Jonathan Hetzel", + "author_inst": "Illumina, San Diego, CA, USA" + }, + { + "author_name": "Sara Spitzer", + "author_inst": "Illumina, San Diego, CA, USA" + }, + { + "author_name": "Jeffery Koble", + "author_inst": "Illumina, San Diego, CA, USA" + }, + { + "author_name": "Asako Tan", + "author_inst": "Illumina, San Diego, CA, USA" + }, + { + "author_name": "Fred Hyde", + "author_inst": "Illumina, San Diego, CA, USA" + }, + { + "author_name": "Gary Schroth", + "author_inst": "Illumina, San Diego, CA, USA" + }, + { + "author_name": "Scott Kuersten", + "author_inst": "Illumina, San Diego, CA, USA" + }, + { + "author_name": "Jillian F Banfield", + "author_inst": "Innovative Genomics Institute, Berkeley, CA, 94704, USA" + }, + { + "author_name": "Kara L Nelson", + "author_inst": "Department of Civil and Environmental Engineering, University of California, Berkeley, CA, USA" } ], "version": "1", @@ -1201720,75 +1201474,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.11.20192401", - "rel_title": "Anakinra and Intravenous IgG versus Tocilizumab in the Treatment of COVID-19 Pneumonia", + "rel_doi": "10.1101/2020.09.11.20193011", + "rel_title": "Clinical effectiveness of drugs in hospitalized patients with COVID-19 infection: a systematic review and meta-analysis.", "rel_date": "2020-09-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.11.20192401", - "rel_abs": "Background: COVID-19 can lead to acute respiratory failure and an exaggerated inflammatory response. Studies have suggested promising outcomes using monoclonal antibodies targeting IL-1{beta} (Anakinra) or IL6 (Tocilizumab), however no head to head comparison was done between the two treatments. Herein, we report our experience in treating COVID-19 pneumonia associated with cytokine storm with either subcutaneous Anakinra given concomitantly with intravenous immunoglobulin (IVIG), or intravenous Tocilizumab. Methods: Comprehensive clinical and laboratory data from patients with COVID-19 pneumonia admitted at our hospital between March and May 2020 were collected. Patients who received either Anakinra/ IVIG or Tocilizumab were selected. Baseline characteristics including oxygen therapy, respiratory status evaluation using ROX index, clinical assessment using NEWS score and laboratory data were collected. Outcomes included mortality, intubation, ICU admission and length of stay. In addition, we compared the change in ROX index, NEWS score and inflammatory markers at days 7 and 14 post initiation of therapy. Results: 84 consecutive patients who received either treatment (51 in the Anakinra/ IVIG group and 33 in the Tocilizumab group) were retrospectively studied. Baseline inflammatory markers were similar in both groups. There was no significant difference regarding to death (21.6% vs 15.2%, p 0.464), intubation (15.7% vs 24.2%, p 0.329), ICU need (57.1% vs 48.5%, p 0.475) or length of stay (13+9.6 vs 14.9+11.6, p 0.512) in the Anakinra/IVIG and Tocilizumab, respectively. Additionally, the rate of improvement in ROX index, NEWS score and inflammatory markers was similar in both groups at days 7 and 14. Furthermore, there was no difference in the incidence of superinfection in both groups. Conclusion: Treating COVID-19 pneumonia associated with cytokine storm features with either subcutaneous Anakinra/IVIG or intravenous Tocilizumab is associated with improved clinical outcomes in most subjects. The choice of treatment does not appear to affect morbidity or mortality. Randomized controlled trials are needed to confirm our study findings. Funding: None.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.11.20193011", + "rel_abs": "Objective. The aim was to assess the clinical effectiveness of drugs used in hospitalized patients with COVID-19 infection. Method. We conducted a systematic review of randomized clinical trials assessing treatment with remdesivir, chloroquine, hydroxychloroquine, lopinavir, ritonavir, dexamethasone, and convalescent plasma, for hospitalized patients with a diagnosis of SARS-CoV-2 infection. The outcomes were mortality, clinical improvement, duration of ventilation, duration of oxygen support, duration of hospitalization), virological clearance, and severe adverse events. Results. A total of 48 studies were retrieved from the databases. Ten articles were finally included in the data extraction and qualitative synthesis of results. The meta-analysis suggests a benefit of dexamethasone versus standard care in the reduction of risk of mortality at day 28; and the clinical improvement at days 14 and 28 in patients treated with remdesivir. Conclusions. Dexamethasone would have a better result in hospitalized patients, especially in low-resources settings. Significance of results. The analysis of the main treatments proposed for hospitalized patients is of vital importance to reduce mortality in low-income countries; since the COVID-19 pandemic had an economic impact worldwide with the loss of jobs and economic decline in countries with scarce resources. Keywords: Drugs; Antivirals; Clinical improvement; Mortality; COVID-19; SARS-CoV2.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Massa Zantah", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Eduardo Dominguez Castillo", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Andrew J. Gangemi", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Maulin Patel", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Junad Chowdhury", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Steven Verga", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Osheen Abramian", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Mattew Zheng", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Kevin Lu", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Arthur Lau", - "author_inst": "Lewis Katz School of Medicine at Temple University" - }, - { - "author_name": "Justin Levinson", - "author_inst": "Lewis Katz School of Medicine at Temple University" + "author_name": "Roberto Ariel Abeldano Zuniga", + "author_inst": "University of Sierra Sur" }, { - "author_name": "Hauquing Zhao", - "author_inst": "Lewis Katz School of Medicine at Temple University" + "author_name": "Silvia Coca", + "author_inst": "University of Sierra Sur" }, { - "author_name": "Gerard J. Criner", - "author_inst": "Lewis Katz School of Medicine at Temple University" + "author_name": "Giuliana Abeldano", + "author_inst": "University of Sierra Sur" }, { - "author_name": "Roberto Caricchio", - "author_inst": "Lewis Katz School of Medicine at Temple University" + "author_name": "Ruth Ana Maria Gonzalez Villoria", + "author_inst": "University of Sierra Sur" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.09.11.20192229", @@ -1203486,49 +1203200,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.10.20191841", - "rel_title": "The King's College London Coronavirus Health and Experiences of Colleagues at King's Study: SARS-CoV-2 antibody response in an occupational sample", + "rel_doi": "10.1101/2020.09.09.20191643", + "rel_title": "Spatial and temporal trends in social vulnerability and COVID-19 incidence and death rates in the United States", "rel_date": "2020-09-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.10.20191841", - "rel_abs": "We report test results for SARS-CoV-2 antibodies in an occupational group of postgraduate research students and current members of staff at Kings College London. Between June and July 2020, antibody testing kits were sent to n=2296 participants; n=2004 (86.3%) responded, of whom n=1882 (93.9%) returned valid test results. Of those that returned valid results, n=124 (6.6%) tested positive for SARS-CoV-2 antibodies, with initial comparisons showing variation by age group and clinical exposure.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20191643", + "rel_abs": "BackgroundEmerging evidence suggests that socially vulnerable communities are at higher risk for coronavirus disease 2019 (COVID-19) outbreaks in the United States. However, no prior studies have examined temporal trends and differential effects of social vulnerability on COVID-19 incidence and death rates. The purpose of this study was to examine temporal trends among counties with high and low social vulnerability and to quantify disparities in these trends over time. We hypothesized that highly vulnerable counties would have higher incidence and death rates compared to less vulnerable counties and that this disparity would widen as the pandemic progressed.\n\nMethodsWe conducted a retrospective longitudinal analysis examining COVID-19 incidence and death rates from March 1 to August 31, 2020 for each county in the US. We obtained daily COVID-19 incident case and death data from USAFacts and the Johns Hopkins Center for Systems Science and Engineering. We classified counties using the Social Vulnerability Index (SVI), a percentile-based measure from the Centers for Disease Control and Prevention in which higher scores represent more vulnerability. Using a Bayesian hierarchical negative binomial model, we estimated daily risk ratios (RRs) comparing counties in the first (lower) and fourth (upper) SVI quartiles. We adjusted for percentage of the county designated as rural, percentage in poor or fair health, percentage of adult smokers, county average daily fine particulate matter (PM2.5), percentage of primary care physicians per 100,000 residents, and the proportion tested for COVID-19 in the state.\n\nResultsIn unadjusted analyses, we found that for most of March 2020, counties in the upper SVI quartile had significantly fewer cases per 100,000 than lower SVI quartile counties. However, on March 30, we observed a \"crossover effect\" in which the RR became significantly greater than 1.00 (RR = 1.10, 95% PI: 1.03, 1.18), indicating that the most vulnerable counties had, on average, higher COVID-19 incidence rates compared to least vulnerable counties. Upper SVI quartile counties had higher death rates on average starting on March 30 (RR = 1.17, 95% PI: 1.01,1.36). The death rate RR achieved a maximum value on July 29 (RR = 3.22, 95% PI: 2.91, 3.58), indicating that most vulnerable counties had, on average, 3.22 times more deaths per million than the least vulnerable counties. However, by late August, the lower quartile started to catch up to the upper quartile. In adjusted models, the RRs were attenuated for both incidence cases and deaths, indicating that the adjustment variables partially explained the associations. We also found positive associations between COVID-19 cases and deaths and percentage of the county designated as rural, percentage of resident in fair or poor health, and average daily PM2.5.\n\nConclusionsResults indicate that the impact of COVID-19 is not static but can migrate from less vulnerable counties to more vulnerable counties over time. This highlights the importance of protecting vulnerable populations as the pandemic unfolds.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Daniel Leightley", - "author_inst": "Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London." - }, - { - "author_name": "Valentina Vitiello", - "author_inst": "The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London, London, UK." - }, - { - "author_name": "Gabriella Bergin-Cartwright", - "author_inst": "Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London." - }, - { - "author_name": "Alice Wickersham", - "author_inst": "Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London" - }, - { - "author_name": "Katrina A S Davis", - "author_inst": "Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London." + "author_name": "Brian Neelon", + "author_inst": "Medical University of South Carolina" }, { - "author_name": "Sharon Stevelink", - "author_inst": "Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London" + "author_name": "Fedelis Mutiso", + "author_inst": "Medical University of South Carolina" }, { - "author_name": "Matthew Hotopf", - "author_inst": "Department of Psychological Medicine, Institute of Psychiatry Psychology and Neuroscience, King's College London" + "author_name": "Noel T Mueller", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" }, { - "author_name": "Reza Razavi", - "author_inst": "The School of Biomedical Engineering and Imaging Sciences, Faculty of Life Sciences and Medicine, King's College London" + "author_name": "John L Pearce", + "author_inst": "Medical University of South Carolina" }, { - "author_name": "- On behalf of the KCL CHECK research team", - "author_inst": "" + "author_name": "Sara E Benjamin-Neelon", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" } ], "version": "1", @@ -1205168,89 +1204866,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.10.20192260", - "rel_title": "Evaluating ten commercially-available SARS-CoV-2 rapid serological tests using the STARD (Standards for Reporting of Diagnostic Accuracy Studies) method.", + "rel_doi": "10.1101/2020.09.10.20189696", + "rel_title": "High COVID-19 transmission potential associated with re-opening universities can be mitigated with layered interventions", "rel_date": "2020-09-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.10.20192260", - "rel_abs": "Numerous SARS-CoV-2 rapid serological tests have been developed, but their accuracy has usually been assessed using very few samples, and rigorous comparisons between these tests are scarce. In this study, we evaluated and compared 10 commercially-available SARS-CoV-2 rapid serological tests using the STARD methodology (Standards for Reporting of Diagnostic Accuracy Studies). 250 sera from 159 PCR-confirmed SARS-CoV-2 patients (collected from 0 to 32 days after onset of symptoms) were tested with rapid serological tests. Control sera (N=254) were retrieved from pre-COVID periods from patients with other coronavirus infections (N=11), positive rheumatoid factors (N=3), IgG/IgM hyperglobulinemia (N=9), malaria (n=5), or no documented viral infection (N=226). All samples were tested using rapid lateral flow immunoassays (LFIA) from ten manufacturers. Only four tests achieved [≥]98% specificity, with other tests ranging from 75.7%-99.2%. Sensitivities varied by the day of sample collection, from 31.7%-55.4% (Days 0-9), 65.9%-92.9% (Days 10-14), and 81.0%-95.2% (>14 days) after the onset of symptoms, respectively. Only three tests evaluated met French Health Authorities' thresholds for SARS-CoV-2 serological tests ([≥]90% sensitivity + [≥]98% specificity). Overall, the performances between tests varied greatly, with only a third meeting acceptable specificity and sensitivity thresholds. Knowing the analytical performance of these tests will allow clinicians to use them with more confidence, could help determine the general population's immunological status, and may diagnose some patients with false-negative RT-PCR results.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.10.20189696", + "rel_abs": "Background: Re-opening universities while controlling COVID-19 transmission poses unique challenges. UK universities typically host 20,000 to 40,000 undergraduate students, with the majority moving away from home to attend. In the absence of realistic mixing patterns, previous models suggest that outbreaks associated with universities re-opening are an eventuality. Methods: We developed a stochastic transmission model based on realistic mixing patterns between students. We evaluated alternative mitigation interventions for a representative university. Results: Our model predicts, for a set of plausible parameter values, that if asymptomatic cases are half as infectious as symptomatic cases then 5,760 (3,940 - 7,430) out of 28,000 students, 20% (14% - 26%), could be infected during the first term, with 950 (656 - 1,209) cases infectious on the last day of term. If asymptomatic cases are as infectious as symptomatic cases then three times as many cases could occur, with 94% (93% - 94%) of the student population getting infected during the first term. We predict that one third of infected students are likely to be in their first year, and first year students are the main drivers of transmission due to high numbers of contacts in communal residences. We find that reducing face-to-face teaching is likely to be the single most effective intervention, and this conclusion is robust to varying assumptions about asymptomatic transmission. Supplementing reduced face-to-face testing with COVID-secure interactions and reduced living circles could reduce the percentage of infected students by 75%. Mass testing of students would need to occur at least fortnightly, is not the most effective option considered, and comes at a cost of high numbers of students requiring self-isolation. When transmission is controlled in the student population, limiting imported infection from the community is important. Conclusions: Priority should be given to understanding the role of asymptomatic transmission in the spread of COVID-19. Irrespective of assumptions about asymptomatic transmission, our findings suggest that additional outbreak control measures should be considered for the university setting. These might include reduced face-to-face teaching, management of student mixing and enhanced testing. Onward transmission to family members at the end of term is likely without interventions.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Laurent Dortet", - "author_inst": "Hopital de Bicetre" - }, - { - "author_name": "Jean-Baptiste Ronat", - "author_inst": "MSF France" - }, - { - "author_name": "Christelle Vauloup-Fellous", - "author_inst": "Service de Virologie, H\u00f4pital Paul-Brousse, Inserm U 1193 ; Universit\u00e9 Paris-Saclay Villejuif, APHP Paris-Saclay" - }, - { - "author_name": "C\u00e9line Langendorf", - "author_inst": "Epicentre (South Africa)" - }, - { - "author_name": "David-Alexis Mendels", - "author_inst": "xrapid-group" - }, - { - "author_name": "C\u00e9cile Emeraud", - "author_inst": "Hopital de Bicetre" - }, - { - "author_name": "Saoussen Oueslati", - "author_inst": "INSERM U914" - }, - { - "author_name": "Delphine Girlich", - "author_inst": "Service de Bacteriologie" + "author_name": "Ellen Brooks-Pollock", + "author_inst": "University of Bristol" }, { - "author_name": "Anthony Chauvin", - "author_inst": "APHP, H\u00f4pitaux universitaires Lariboisi\u00e8re-Saint Louis-Fernand-WIdal" + "author_name": "Hannah Christensen", + "author_inst": "University of Bristol" }, { - "author_name": "Ali Afdjei", - "author_inst": "Emergency Department, H\u00f4pital Parly-2," + "author_name": "Adam Trickey", + "author_inst": "University of Bristol" }, { - "author_name": "Sandrine Bernabeu", - "author_inst": "Paris-Sud University, LabEx Lermit, Faculty of Medecine" + "author_name": "Gibran Hemani", + "author_inst": "University of Bristol" }, { - "author_name": "Samuel Le Pape", - "author_inst": "Service de Virologie, H\u00f4pital Paul-Brousse, Inserm U 1193 ; Universit\u00e9 Paris-Saclay Villejuif, APHP Paris-Saclay" + "author_name": "Emily Nixon", + "author_inst": "University of Bristol" }, { - "author_name": "Rim Kallala", - "author_inst": "Service de Virologie, H\u00f4pital Paul-Brousse" + "author_name": "Amy Thomas", + "author_inst": "University of Bristol" }, { - "author_name": "Alice Rochard", - "author_inst": "APHP, Hopital de Bicetre" + "author_name": "Katy Turner", + "author_inst": "University of Bristol" }, { - "author_name": "Celine Verstuyft", - "author_inst": "Facult\u00e9 de M\u00e9decine Paris-Sud, Univ Paris-Sud, Universit\u00e9 Paris-Saclay; INSERM U1184; Service de G\u00e9n\u00e9tique mol\u00e9culaire, Pharmacog\u00e9n\u00e9tique et H" + "author_name": "Adam Finn", + "author_inst": "University of Bristol" }, { - "author_name": "Nicolas Fortineau", - "author_inst": "APHP" + "author_name": "Matt Hickman", + "author_inst": "University of Bristol" }, { - "author_name": "Anne-Marie Roque-Afonso", - "author_inst": "Service de Virologie, H\u00f4pital Paul-Brousse, Inserm U 1193 ; Universit\u00e9 Paris-Saclay Villejuif, APHP Paris-Saclay" + "author_name": "Caroline Relton", + "author_inst": "University of Bristol" }, { - "author_name": "Thierry Naas", - "author_inst": "APHP" + "author_name": "Leon Danon", + "author_inst": "University of Exeter" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1206678,35 +1206348,39 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.09.09.20188482", - "rel_title": "Adherence to COVID-19 pandemic prescribed recommendations, source of information and lockdown psychological impact of Nigeria social media users", + "rel_doi": "10.1101/2020.09.09.20182592", + "rel_title": "Is there a correlation between pulmonary inflammation index with COVID-19 disease severity and outcome?", "rel_date": "2020-09-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20188482", - "rel_abs": "BackgroundCOVID-19 is a highly infectious viral disease that has spread to over one hundred and eight countries, including Nigeria. Countries across the globe have been implementing preventive measures towards curbing the spread and impact of the virus. Thus, the present study was aimed at assessing compliance to prescribe preventive recommendations, the psychological effect of lockdown, and the source of information among Nigeria social media users.\n\nMethodsThis research implemented an online cross-sectional survey using an unidentified online Google based questionnaire to elicit required information from potential respondents via social media channels such as WhatsApp, Twitter, Instagram, Telegram and Facebook. On these forums, an external link with google based questionnaire was shared with Nigerians social media users to participate from 1st to 31st April 2020 and we had 1,131 respondents who participated in the survey.\n\nResultsAge and respondents scientific or non-scientific backgrounds were the socio-demographic variables associated with respondents having psychological challenges as P<0.05. However, none of the socio-demographic variables of the respondents were associated with compliance with the recommendations as P>0.05. Also, most (63.4%) of the respondents were stressed by the feelings associated with the COVID-19 pandemic, as the expected majority (80.1%) sources information about the epidemics through social media platforms.\n\nConclusionGiven numerous uncertainties surrounding the global COVID-19 pandemics, there is a need to continuously increase awareness through various media and ensure that people are highly complying with the preventive measures being put in place by relevant authorities. Also, palliative measures should be put in place to reduce the psychological impact of the pandemic.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20182592", + "rel_abs": "Rationalthe radiologic pulmonary inflammatory index (PII) may be used as early predictor of inflammation as laboratory assessments in COVID-19 cases. The purpose of this study was to compare the clinical and radiological features between the cases of COVID-19 necessitating admittance to the intensive care unit (ICU) and those who did not, and to correlate the radiological pulmonary inflammation index (PII) with other inflammatory markers and outcome.\n\nPatients and methodsThis study included 72 patients consecutively admitted with confirmed COVID-19. Their electronic records of were retrospectively revised and the demographic, clinical, laboratory (complete blood count, C reactive protein, D dimer and serum ferritin), HRCT data, pulmonary inflammation index (PII) and the outcomes of the patients (ICU admission, death, recovery, and referral) were analyzed.\n\nResultsThey were 50/50% males/females, mean age was 47.1 {+/-} 16.8 (median 47 years). During their stay, 15.3% necessitated ICU admittance, 49 (68%) cured and discharged, 9 cases referred and five cases (6.9%) died. The baseline lesions identified were ground glass opacification recognized in (93%), higher PII and >3 lobes affection were considerably recorded in those who required ICU admittance (P= 0.041 and 0.013). There were moderate positive correlations between PII with age (r=0.264, P=0.031) and other prognostic inflammatory indicators as ferritin (r=0.225, P=0.048), D Dimer (r=0.271, P=0.043) and serum creatinine.\n\nConclusionsThe use of PII together with clinical and laboratory data may be valuable in defining the inflammatory state of COVID-19. It was correlated with other inflammatory indices as D dimer, ferritin even before clinical deterioration. This may allow clinicians to avoid the progression of the illness and improve cure rates by proper early intervention.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Obasanjo Afolabi Bolarinwa", - "author_inst": "University of Kwazulu-Natal, Durban, South Africa; Obafemi Awolowo University, Nigeria" + "author_name": "Aliae Mohamed-Hussein", + "author_inst": "Faculty of medicine, Assiut University" }, { - "author_name": "Olalekan Seun Olagunju", - "author_inst": "Obafemi Awolowo University, Nigeria" + "author_name": "Islam Galal", + "author_inst": "Chest Department, Aswan Iniversity" }, { - "author_name": "Tesleem Babalola", - "author_inst": "University of KwaZulu-Natal, South Africa" + "author_name": "Mohammed Mustafa Abdel Rasik Mohamed", + "author_inst": "Public Health, Kasr Alainy, Cairo University" }, { - "author_name": "Balsam Qubais", - "author_inst": "University of Sharjah" + "author_name": "Howaida Abd Elaal", + "author_inst": "Faculty of Nursing, Aswan University" + }, + { + "author_name": "Karim ME Aly", + "author_inst": "Cardiology, Assiut University" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.09.09.20191676", @@ -1208488,49 +1208162,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.07.20189597", - "rel_title": "COVID-19 control across urban-rural gradients", + "rel_doi": "10.1101/2020.09.07.20184887", + "rel_title": "Age-structured SIR model and resource growth dynamics: A preliminary COVID-19 study", "rel_date": "2020-09-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.07.20189597", - "rel_abs": "Controlling the regional re-emergence of SARS-CoV-2 after its initial spread in ever-changing personal contact networks and disease landscapes is a challenging task. In a landscape context, contact opportunities within and between populations are changing rapidly as lockdown measures are relaxed and a number of social activities re-activated. Using an individual-based metapopulation model, we explored the efficacy of different control strategies across an urban-rural gradient in Wales, UK. Our model shows that isolation of symptomatic cases, or regional lockdowns in response to local outbreaks, have limited efficacy unless the overall transmission rate is kept persistently low. Additional isolation of non-symptomatic infected individuals, who may be detected by effective test and trace strategies, is pivotal to reduce the overall epidemic size over a wider range of transmission scenarios. We define an urban-rural gradient in epidemic size as a correlation between regional epidemic size and connectivity within the region, with more highly connected urban populations experiencing relatively larger outbreaks. For interventions focused on regional lockdowns, the strength of such gradients in epidemic size increased with higher travel frequencies, indicating a reduced efficacy of the control measure in the urban regions under these conditions. When both non-symptomatic and symptomatic individuals are isolated or regional lockdown strategies are enforced, we further found the strongest urban-rural epidemic gradients at high transmission rates. This effect was reversed for strategies targeted at symptomatics only. Our results emphasise the importance of test-and-tracing strategies and maintaining low transmission rates for efficiently controlling COVID19 spread, both at landscape scale and in urban areas.\n\nAuthor summaryThe spread of infectious diseases is the outcome of contact patterns and involves source-sink dynamics of how infectious individuals spread the disease through pools of susceptible individuals. Control strategies that aim to reduce disease spread often need to accept ongoing transmission chains and therefore, may not work equally well in different scenarios of how individuals and populations are connected to each other. To understand the efficacy of different control strategies to contain the spread of COVID19 across gradients of urban and rural populations, we simulated a large range of different control strategies in response to regional COVID19 outbreaks, involving regional lockdown and the isolation individuals that express symptoms and those that developed not symptoms but may contribute to disease transmission. Our results suggest that isolation of asymptomatic individuals through intensive test-and-tracing is important for efficiently reducing the epidemic size. Regional lockdowns and the isolation of symptomatic cases only are of limited efficacy for reducing the epidemic size, unless overall transmission rate is kept persistently low. Moreover, we found high overall transmission rates to result in relatively larger epidemics in urban than in rural communities for these control strategies, emphasising the importance of keeping transmission rates constantly low in addition to regional measures to avoid the disease spread at large scale.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.07.20184887", + "rel_abs": "In this paper, we discuss three different response strategies to a disease outbreak and their economic implications in an age-structured population. We have utilized the classical age structured SIR-model, thus assuming that recovered people will not be infected again. Available resource dynamics is governed by the well-known logistic growth model, in which the reproduction coefficient depends on the disease outbreak spreading dynamics. We further investigate the feedback interaction of the disease spread dynamics and resource growth dynamics with the premise that the quality of treatment depends on the current economic situation. The very inclusion of mortality rates and economic considerations in the same model may be incongruous under certain positions, but in this model, we take a realpolitik approach by exploring all of these factors together as it is done in reality.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Konstans Wells", - "author_inst": "Swansea University" - }, - { - "author_name": "Miguel Lurgi", - "author_inst": "Swansea University" - }, - { - "author_name": "Brendan Collins", - "author_inst": "Department of Public Health and Policy, University of Liverpool, Liverpool L69 3GB, UK" - }, - { - "author_name": "Biagio Lucini", - "author_inst": "Department of Mathematics, Swansea University, Swansea SA2 8PP, Wales, UK" - }, - { - "author_name": "Rowland Raymond Kao", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Alun L. Lloyd", - "author_inst": "Biomathematics Graduate Program and Department of Mathematics, North Carolina State University, Raleigh, NC 27695, USA" - }, - { - "author_name": "Simon D.W. Frost", - "author_inst": "Microsoft Research Lab, Redmond, Washington, WA 98052, USA and London School of Hygiene and Tropical Medicine, London, WC1E 7HT" + "author_name": "S. G. Babajanyan", + "author_inst": "Singapore University of Technology and Design" }, { - "author_name": "Mike B. Gravenor", - "author_inst": "Swansea University Medical School, Swansea University, Swansea SA2 8PP, Wales, UK" + "author_name": "Kang Hao Cheong", + "author_inst": "Singapore University of Technology and Design" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1209982,51 +1209632,27 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.09.20191239", - "rel_title": "COVID-19 Transmission Within Danish Households: A Nationwide Study from Lockdown to Reopening", + "rel_doi": "10.1101/2020.09.09.20188961", + "rel_title": "Effect of Screen time on Glycaemic control of Type 2 Diabetes patients during COVID-19 Outbreak: A Survey based Study", "rel_date": "2020-09-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20191239", - "rel_abs": "BackgroundThe Covid-19 pandemic is one of the most serious global public health threats in recent times. Understanding transmission of SARS-CoV-2 is of utmost importance to be able to respond to outbreaks and take action against spread of the disease. Transmission within the household is a concern, especially because infection control is difficult to apply within the household domain.\n\nMethodsWe used comprehensive administrative register data from Denmark, comprising the full population and all COVID-19 tests, to estimate household transmission risk and attack rate.\n\nResultsWe studied the testing dynamics for COVID-19 and found that the day after receiving a positive test result within the household, 35% of potential secondary cases were tested and 13% of these were positive. After a primary case in 6,782 households, 82% of potential secondary cases were tested within 14 days, of which 17% tested positive as secondary cases, implying an attack rate of 17%. Among primary cases, those aged 0-24 were underrepresented when compared with the total population. We found an approximately linearly increasing relationship between attack rate and age. We investigated the transmission risk from primary cases by age, and found an increasing risk with age of primary cases for adults, while the risk seems to decrease with age for children.\n\nConclusionsAlthough there is an increasing attack rate and transmission risk of SARS-CoV-2 with age, children are also able to transmit SARS-CoV-2 within the household.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.09.20188961", + "rel_abs": "IntroductionDecreased workout during coronavirus disease 2019 (COVID-19) is a serious issue for the patients with type 2 diabetes (T2DM), since their glycaemic control is very much related to that. COVID-19 has posed a severe health issue that is playing havoc on the aged patients with existing comorbidities. Studies have shown mixed reports of social media on T2DM, with some showing positive results due to increased use of apps and adherence to lifestyle, while others have shown adiposity and glycaemic control related to hours spent on-screen time in children. Data on adult T2DM patients screen time activity and prevailing glycosylated haemoglobin (HbA1c), fasting blood sugar (FBS) and, post-prandial blood sugar (PPBS) is sparse.\n\nAimTo study the effect of screen-time spent on social media per day on glycaemic parameters of T2DM patients.\n\nMaterials and methodsData was collected for T2DM patients giving informed written consent and meeting a set of pre-specified inclusion criteria. Through two rounds of surveys done from May 15 to June 26, the authors collected the answers to a set of questionnaires from a total of 344 patients sent via email. Due to the non-availability of data from a few patients, a total of 229 patients data were finally analyzed. SPSS software version V21 (R) was used to perform Binary logistic regression for calculating the odds ratio (OR) of the categorical variables. The outcomes, looked for in the analysis, were poor control of glycaemic parameters like HbA1c (defined by >7%), FBS (defined by >150 mg/dL) and, PPBS (defined by >200 mg/dL) and the exposure variables were Screen time spent by the person per day for all the three glycaemic parameters and, doctors visit and, daily exercise for HbA1c outcome.\n\nResultsA total of 173 patients had a screen time (henceforth, it means time spent on social media) of less than 2 hours/day in the study sample. Among the 173 patients, 73 (42.2%) had achieved HbA1c less than 7%, whereas the remaining 100 (57.8%) had HbA1c more than 7%. On the other hand, 56 patients had a screen time of more than 2 hours, of which 44 (72.73%) had HbA1c more than 7%. Among the 173 patients, only 89 (51.44%) had an FBS value of more than 150 mg/dL as compared to 46 (82.12%) with a screen time of more than 2 hours. Out of these 173 patients, only 43 (24.86%) had a PPBS value of more than 200 mg/dL as compared to 41 (73.21%) with a screen time of more than 2 hours. It was found that the odds of having a poor glycaemic control as per HbA1c, FBS and PPBS is 2.67 times higher (95%CI: 1.91-6.95), 4.34 times higher (95%CI: 1.52-4.76) and, 8.26 times higher (95%CI: 4.26-11.83) in the cohort with a screen time of more than 2 hours as compared to the cohort with a screen time of less than 2 hours, respectively.\n\nConclusionThere seems to be an increased risk of uncontrolled glycaemic indices with increased screen time and, decreased work out. This is a small study and the findings need to be corroborated with larger sample size.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Frederik Plesner Lyngse", - "author_inst": "University of Copenhagen" - }, - { - "author_name": "Carsten Thure Kirkeby", - "author_inst": "University of Copenhagen" - }, - { - "author_name": "Tariq Halasa", - "author_inst": "University of Copenhagen" - }, - { - "author_name": "Viggo Andreasen", - "author_inst": "Roskilde University" - }, - { - "author_name": "Robert Leo Skov", - "author_inst": "Statens Serum Institut" - }, - { - "author_name": "Frederik Trier M\u00f8ller", - "author_inst": "Statens Serum Institut" - }, - { - "author_name": "Tyra Grove Krause", - "author_inst": "Statens Serum Institut" + "author_name": "Sayak Roy", + "author_inst": "Medica Superspeciality Hospital" }, { - "author_name": "K\u00e5re M\u00f8lbak", - "author_inst": "Statens Serum Institut" + "author_name": "Kingshuk Bhattacharjee", + "author_inst": "Medwes Pvt LTD, Kolkata, Wb, India" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "endocrinology" }, { "rel_doi": "10.1101/2020.09.08.20190421", @@ -1211884,25 +1211510,49 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.04.20188110", - "rel_title": "Modelling the transmission of infectious diseases inside hospital bays: implications for Covid-19", + "rel_doi": "10.1101/2020.09.05.20189142", + "rel_title": "Development and Validation of the Patient History COVID-19 (PH-Covid19) Scoring System: A Multivariable Prediction Model of Death in Mexican Patients with COVID-19", "rel_date": "2020-09-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20188110", - "rel_abs": "Healthcare associated transmission of viral infections is a major problem that has significant economic costs and can lead to loss of life. Infections with the highly contagious SARS-CoV-2 virus have been shown to have a high prevalence in hospitals around the world. The spread of this virus might be impacted by the density of patients inside hospital bays. To investigate this aspect, in this study we consider a mathematical modelling and computational approach to describe the spread of SARS-CoV-2 among hospitalised patients. We focus on 4-bed bays and 6-bed bays, which are commonly used to accommodate various non-Covid-19 patients in many hospitals across UK. We use this mathematical model to investigate the spread of SARS-CoV-2 infections among patients in non-Covid bays, in the context of various scenarios: changes in the number of contacts with infected patients and staff, having symptomatic vs. asymptomatic patients, removing infected individuals from these hospital bays once they are known to be infected, and the role of periodic testing of hospitalised patients. Our results show that 4-bed bays reduce the spread of SARS-CoV-2 compared to 6-bed bays. Moreover, we show that the position of a new (not infected) patient in specific beds in a 6-bed bay might also slow the spread of the disease. Finally, we propose that regular SARS-CoV-2 testing of hospitalised patients would allow appropriate placement of infected patients in specific (Covid-only) hospital bays.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.05.20189142", + "rel_abs": "We sought to develop and validate a multivariable prediction model of death in Mexican patients with COVID-19, by using demographic and patient history predictors. We conducted a national retrospective cohort in two different sets of patients from the Mexican COVID-19 Epidemiologic Surveillance Study. To develop the model, we included 264,026 patients tested for SARS-CoV-2 between February 28 and May 30, 2020. To validate the model, 592,160 patients studied between June 1 and July 23, 2020 were included. Patients with a positive RT-PCR for SARS-CoV-2 and complete unduplicated data were eligible. Demographic and patient history variables were analyzed through Multivariable Cox regression models to evaluate predictors to be included in the prognostic scoring system called PH-Covid19. 83,779 patients were included to develop the model; 100,000, to validate the model. Eight predictors (age, sex, diabetes, COPD, immunosuppression, hypertension, obesity, and CKD) were included in the PH-Covid19 scoring system (range of values: -2 to 25 points). The predictive model has a discrimination of death of 0.8 (95%CI:0.796-0.804). The PH-Covid19 scoring system was developed and validated in Mexican patients to aid clinicians to stratify patients with COVID-19 at risk of fatal outcomes, allowing for better and efficient use of resources.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "David Moreno Martos", - "author_inst": "University of Dundee" + "author_name": "Javier Mancilla-Galindo", + "author_inst": "Instituto Nacional de Cardiologia" }, { - "author_name": "Benjamin Parcell", - "author_inst": "NHS Tayside" + "author_name": "Juan Mauricio Vera-Zertuche", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Slavador Zubiran" }, { - "author_name": "Raluca Eftimie", - "author_inst": "University of Dundee" + "author_name": "Addi Rhode Navarro-Cruz", + "author_inst": "Benemerita Universidad Autonoma de Puebla" + }, + { + "author_name": "Orietta Segura-Badilla", + "author_inst": "Universidad del Bio-Bio" + }, + { + "author_name": "Gerardo Reyez-Velazquez", + "author_inst": "Instituto Mexicano del Seguro Social" + }, + { + "author_name": "Francisco Javier Tepepa-Lopez", + "author_inst": "Instituto Politecnico Nacional" + }, + { + "author_name": "Patricia Aguilar-Alonso", + "author_inst": "Benemerita Universidad Autonoma de Puebla" + }, + { + "author_name": "Jose de Jesus Vidal-Mayo", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" + }, + { + "author_name": "Ashuin Kammar-Garcia", + "author_inst": "Instituto Nacional de Ciencias Medicas y Nutricion Salvador Zubiran" } ], "version": "1", @@ -1214814,25 +1214464,49 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.04.20188359", - "rel_title": "COVID-19 superspreading in cities versus the countryside", + "rel_doi": "10.1101/2020.09.04.20188680", + "rel_title": "CAN EDUCATIONAL INSTITUTIONS REOPEN FOR IN-PERSON CLASSES SAFELY AMID THE COVID-19 PANDEMIC?", "rel_date": "2020-09-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20188359", - "rel_abs": "So far, the COVID-19 pandemic has been characterised by an initial rapid rise in new cases followed by a peak and a more erratic behaviour that varies between regions. This is not easy to reproduce with traditional SIR models, which predict a more symmetric epidemic. Here, we argue that superspreaders and population heterogeneity are the core factors explaining this discrepancy. We do so through an agent-based lattice model of a disease spreading in a heterogeneous population. We predict that an epidemic driven by superspreaders will spread rapidly in cities, but not in the countryside where the sparse population limits the maximal number of secondary infections. This suggests that mitigation strategies should include restrictions on venues where people meet a large number of strangers. Furthermore, mitigating the epidemic in cities and in the countryside may require different levels of restrictions.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.04.20188680", + "rel_abs": "Can educational institutions open up safely amid COVID-19? We build an epidemiological model to investigate the strategies necessary for institutions to reopen. The four measures that are most relevant for in-person opening are: (i) wide-spread rapid testing, possibly saliva-based, (ii) enforcement of mask wearing, (iii) social distancing, and (iv) contact tracing. We demonstrate that institutions need to test at a relatively high level (e.g., at least once every week) in the initial phases of reopening. Contact tracing is relatively more important when the positivity rate from random testing is relatively low, which is likely during the initial phases. A Bayesian adaptive testing strategy based on positivity rates can help institutions optimally manage the costs and risks of reopening. This paper contributes to the nascent literature on combating the COVID-19 pandemic and is especially relevant for large-scale organizations. This work is motivated and guided by the SHIELD program of UIUC.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Andreas Eilersen", - "author_inst": "University of Copenhagen" + "author_name": "Ujjal K Mukherjee", + "author_inst": "University of Illinois at Urbana-Champaign" }, { - "author_name": "Kim Sneppen", - "author_inst": "University of Copenhagen" + "author_name": "Subhonmesh Bose", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Anton Ivanov", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Sebastian Souyris", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Sridhar Seshadri", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Padmavati Sridhar", + "author_inst": "University of California Berkeley" + }, + { + "author_name": "Ronald Watkins", + "author_inst": "University of Illinois at Urbana-Champaign" + }, + { + "author_name": "Yuqian Yu", + "author_inst": "University of Illinois at Urbana-Champaign" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1216404,43 +1216078,127 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.09.03.20187336", - "rel_title": "Household Secondary Attack Rate in Gandhinagar district of Gujarat state from Western India", + "rel_doi": "10.1101/2020.09.03.20183947", + "rel_title": "SARS-CoV-2-specific IgA and limited inflammatory cytokines are present in the stool of select patients with acute COVID-19", "rel_date": "2020-09-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.03.20187336", - "rel_abs": "Objectives: Current retrospective study aims to evaluate household Secondary Attack Rate (SAR) of COVID-19 in Gandhinagar (rural) district of Gujarat, India. Methods: Line-listing of 486 laboratory-confirmed patients, tested between 28th March to 2nd July was collected, out of them 80 (15% of overall sample) cases were randomly selected. Demographic, clinical and household details of cases were collected through telephonic interview. During interview 28 more patients were identified from the same household and were added accordingly. So, study included 74 unrelated cluster of households with 74 primary cases and 386 close contacts. Results: SAR in household contacts of COVID-19 in Gandhinagar was 8.8%. Out of 108, 8 patients expired (7.4%), where higher mortality was observed in primary cases (9.5%) as compared to secondary cases (3%). Occupational analysis showed that majority of the secondary cases (88%) were not working and hence had higher contact time with patient. No out-of-pocket expenditure occurred in 94% of the patients, in remaining 6% average expenditure of 1,49,633INR (2027 USD) was recorded. Conclusions: Key observations from the study are 1) SAR of 8.8% is relatively low and hence home isolation of the cases can be continued 2) Primary case is more susceptible to fatal outcome as compared to secondary cases 3) Government has covered huge population of the COVID-19 patients under cost protection. However, more robust studies with larger datasets are needed to further validate the findings.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.03.20183947", + "rel_abs": "Background and aimsImmune dysregulation caused by SARS-CoV-2 infection is thought to play a pathogenic role in COVID-19. SARS-CoV-2 can infect a variety of host cells, including intestinal epithelial cells. We sought to characterize the role of the gastrointestinal immune system in the pathogenesis of the inflammatory response associated with COVID-19.\n\nMethodsWe measured cytokines, inflammatory markers, viral RNA, microbiome composition and antibody responses in stool and serum samples from a prospectively enrolled cohort of 44 hospitalized COVID-19 patients.\n\nResultsSARS-CoV-2 RNA was detected in stool of 41% of patients and was found more frequently in patients with diarrhea than those without (16[44%] vs 5[19%], p=0.06). Patients who survived had lower median viral genome copies than those who did not (p=0.021). Compared to uninfected controls, COVID-19 patients had higher median fecal levels of IL-8 (166.5 vs 286.5 pg/mg; p=0.05) and lower levels of fecal IL-10 (678 vs 194 pg/mg; p<0.001) compared to uninfected controls. Stool IL-23 was higher in patients with more severe COVID-19 disease (223.8 vs 86.6 pg/mg; p=0.03) and we find evidence of intestinal virus-specific IgA responses, which was associated with more severe disease. Fecal cytokines and calprotectin levels were not correlated with gastrointestinal symptoms or with the level of virus detected.\n\nConclusionsAlthough SARS-CoV-2 RNA was detectable in the stools of COVID-19 patients and select individuals had evidence for a specific mucosal IgA response, intestinal inflammation was limited, even in patients presenting with gastrointestinal symptoms.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Komal Shah", - "author_inst": "Indian Institute of Public Health Gandhinagar" + "author_name": "Graham J Britton", + "author_inst": "Icahn School of Medicine at Mount Sinai (co-first author)" }, { - "author_name": "Nupur Desai", - "author_inst": "New York University, USA" + "author_name": "Alice Chen-Liaw", + "author_inst": "Icahn School of Medicine at Mount Sinai (co-first author)" }, { - "author_name": "Deepak Saxena", - "author_inst": "Indian Institute of Public Health Gandhinagar" + "author_name": "Francesca Cossarini", + "author_inst": "Icahn School of Medicine at Mount Sinai (co-first author)" }, { - "author_name": "Dileep Mavalankar", - "author_inst": "Indian Institute of Public Health Gandhinagar" + "author_name": "Alexandra E Livanos", + "author_inst": "Icahn School of Medicine at Mount Sinai (co-first author)" + }, + { + "author_name": "Matthew P Spindler", + "author_inst": "Icahn School of Medicine at Mount Sinai (co-first author)" + }, + { + "author_name": "Tamar Plitt", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Joseph Eggers", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Ilaria Mogno", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Ana Gonzalez-Reiche", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Sophia Siu", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Michael Tankelevich", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Lauren Grinspan", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Rebekah E Dixon", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Divya Jha", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Adriana van de Guchte", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Zenab Khan", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Gustavo Martinez-Delgado", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Fatima Amanat", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Daisy A Hoagland", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Umang Mishra", - "author_inst": "Epidemic, Commissioner (Health, Medical Services and Medical Education), Gandhinagar" + "author_name": "Benjamin tenOever", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "G C Patel", - "author_inst": "Epidemic Branch, Commissionerate of Health, Gandhinagar, Gujarat" + "author_name": "Marla C Dubinsky", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Miriam Merad", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Harm van Bakel", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Florian Krammer", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Gerold Bongers", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Saurabh Mehandru", + "author_inst": "Icahn School of Medicine at Mount Sinai (co-senior author)" + }, + { + "author_name": "Jeremiah J Faith", + "author_inst": "Icahn School of Medicine at Mount Sinai (co-senior author)" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "gastroenterology" }, { "rel_doi": "10.1101/2020.09.03.20187823", @@ -1217902,69 +1217660,57 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.09.01.20185280", - "rel_title": "SARS-CoV-2 Protein in Wastewater Mirrors COVID-19 Prevalence.", + "rel_doi": "10.1101/2020.09.01.20186049", + "rel_title": "App-based symptom tracking to optimize SARS-CoV-2 testing strategy using machine learning", "rel_date": "2020-09-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20185280", - "rel_abs": "The COVID-19 pandemic has given rise to diverse approaches to track infections. The causative agent, SARS-CoV-2, is a fecally-shed RNA virus, and many groups have assayed wastewater for viral RNA fragments by quantitative reverse transcription polymerase chain reaction (qRT-PCR) as a proxy for COVID-19 prevalence in the community. Most groups report low levels of viral RNA that often skirt the methods theoretical limits of detection and quantitation. Here, we demonstrate the presence of SARS-CoV-2 structural proteins in wastewater using traditional immunoblotting and quantitate them from wastewater solids using an immuno-linked PCR method called Multiplex Paired-antibody Amplified Detection (MPAD). MPAD demonstrated facile detection of SARS-CoV-2 proteins compared with SARS-CoV-2 RNA via qRT-PCR in wastewater. In this longitudinal study, we corrected for stochastic variability inherent to wastewater-based epidemiology using multiple fecal content protein biomarkers. These normalized SARS-CoV-2 protein data correlated well with public health metrics. Our method of assaying SARS-CoV-2 protein from wastewater represents a promising and sensitive epidemiological tool to assess prevalence of fecally-shed pathogens in the community.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20186049", + "rel_abs": "BackgroundTests are scarce resources, especially in low and middle-income countries, and the optimization of testing programs during a pandemic is critical for the effectiveness of the disease control. Hence, we aim to use the combination of symptoms to build a regression model as a screening tool to identify people and areas with a higher risk of SARS-CoV-2 infection to be prioritized for testing.\n\nMaterials and MethodsWe applied machine learning techniques and provided a visualization of potential regions with high densities of COVID-19 as a risk map. We performed a retrospective analysis of individuals registered in \"Dados do Bem\", an app-based symptom tracker in use in Brazil.\n\nResultsFrom April 28 to July 16, 2020, 337,435 individuals registered their symptoms through the app. Of these, 49,721 participants were tested for SARS-CoV-2 infection, being 5,888 (11.8%) positive. Among self-reported symptoms, loss of smell (OR[95%CI]: 4.6 [4.4 - 4.9]), fever (2.6 [2.5 - 2.8]), and shortness of breath (2.1 [1.6-2.7]) were associated with SARS-CoV-2 infection. Our final model obtained a competitive performance, with only 7% of false-negative users among the predicted as negatives (NPV = 0.93). From the 287,714 users still not tested, our model estimated that only 34.5% are potentially infected, thus reducing the need for extensive testing of all registered users. The model was incorporated by the \"Dados do Bem\" app aiming to prioritize users for testing. We developed an external validation in the state of Goias and found that of the 465 users selected, 52% tested positive.\n\nConclusionsOur results showed that the combination of symptoms might predict SARS-Cov-2 infection and, therefore, can be used as a tool by decision-makers to refine testing and disease control strategies.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Nafisa Neault", - "author_inst": "Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada, K1H 8L1" + "author_name": "LEILA F. DANTAS", + "author_inst": "Pontifical Catholic University of Rio de Janeiro" }, { - "author_name": "Aiman T. Baig", - "author_inst": "Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada, K1H 8L1" + "author_name": "IGOR T. PERES", + "author_inst": "Pontifical Catholic University of Rio de Janeiro" }, { - "author_name": "Tyson E. Graber", - "author_inst": "Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada, K1H 8L1" - }, - { - "author_name": "Patrick M. D'Aoust", - "author_inst": "Department of Civil Engineering, University of Ottawa, Ottawa, Canada, K1N 6N5" + "author_name": "LEONARDO S.L. BASTOS", + "author_inst": "Pontifical Catholic University of Rio de Janeiro" }, { - "author_name": "Elisabeth Mercier", - "author_inst": "Department of Civil Engineering, University of Ottawa, Ottawa, Canada, K1N 6N5" + "author_name": "JANAINA F. MARCHESI", + "author_inst": "Instituto Tecgraf, Pontifical Catholic University of Rio de Janeiro" }, { - "author_name": "Ilya Alexandrov", - "author_inst": "ActivSignal LLC., Natick, MA, United States, 01760" + "author_name": "GUILHERME F.G. DE SOUZA", + "author_inst": "Pontifical Catholic University of Rio de Janeiro" }, { - "author_name": "Daniel Crosby", - "author_inst": "ActivSignal LLC., Natick, MA, United States, 01760" + "author_name": "JOAO GABRIEL M. GELLI", + "author_inst": "Pontifical Catholic University of Rio de Janeiro" }, { - "author_name": "Janice Mayne", - "author_inst": "Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Canada, K1H 8M5" + "author_name": "FERNANDA A. BAIAO", + "author_inst": "Pontifical Catholic University of Rio de Janeiro" }, { - "author_name": "Thomas Pounds", - "author_inst": "ActivSignal LLC., Natick, MA, United States, 01760" + "author_name": "PAULA MACAIRA", + "author_inst": "Pontifical Catholic University of Rio de Janeiro" }, { - "author_name": "Malcolm MacKenzie", - "author_inst": "ActivSignal LLC., Natick, MA, United States, 01760" + "author_name": "SILVIO HAMACHER", + "author_inst": "Pontifical Catholic University of Rio de Janeiro" }, { - "author_name": "Daniel Figeys", - "author_inst": "Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, Canada, K1H 8M5; Department of Chemistry and Biomolecular Sciences, Unive" - }, - { - "author_name": "Alex E. MacKenzie", - "author_inst": "Children's Hospital of Eastern Ontario Research Institute, Ottawa, Canada, K1H 8L1" - }, - { - "author_name": "Robert Delatolla", - "author_inst": "Department of Civil Engineering, University of Ottawa, Ottawa, Canada, K1N 6N5" + "author_name": "FERNANDO A. BOZZA", + "author_inst": "National Institute of Infectious Diseases Evandro Chagas (INI), Oswaldo Cruz Foundation (FIOCRUZ)" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1219448,57 +1219194,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.09.01.20182873", - "rel_title": "Effects of Public Health Interventions on the Epidemiological Spread During the First Wave of the COVID-19 Outbreak in Thailand", + "rel_doi": "10.1101/2020.09.02.20186577", + "rel_title": "COVID-19: Impact on the health and wellbeing of ex-serving personnel (Veterans-CHECK) protocol paper", "rel_date": "2020-09-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.01.20182873", - "rel_abs": "A novel infectious respiratory disease was recognized in Wuhan (Hubei Province, China) in December 2019. In February 2020, the disease was named \"coronavirus disease 2019\" (COVID-19). COVID-19 became a pandemic in March 2020, and, since then, different countries have implemented a broad spectrum of policies. Thailand is considered to be among the top countries in handling its first wave of the outbreak -- 12 January to 31 July 2020. Here, we illustrate how Thailand tackled the COVID-19 outbreak, particularly the effects of public health interventions on the epidemiologic spread. This study shows how the available data from the outbreak can be analyzed and visualized to quantify the severity of the outbreak, the effectiveness of the interventions, and the level of risk of allowed activities during an easing of a \"lockdown.\" This study shows how a well-organized governmental apparatus can overcome the havoc caused by a pandemic.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.09.02.20186577", + "rel_abs": "IntroductionWe will use a sub-sample of a current longitudinal study to investigate the impact of COVID-19 on the health and wellbeing of ex-service personnel in the UK. The study will provide evidence for the UK Office of Veterans Affairs (OVA), UK stakeholders supporting the ex-service community, and evidence to inform our international counterparts working with ex-service communities in allied countries regarding the impact of COVID-19 on the health and wellbeing of ex-service personnel.\n\nMethods and analysisParticipants were eligible to participate if they lived in the UK, had Regular service history from the UK Armed Forces and had previously completed the Kings Centre for Military Health Research (KCMHR) Health and Wellbeing survey between 2014-2016. Participants who met these criteria were recruited through email to take part in an online questionnaire. The study provides additional quantitative longitudinal data on this sub-sample. Data are being collected June 2020-September 2020. Specific measures are used to capture participants COVID-19 experiences, health and wellbeing status and lifestyle behaviours. Other key topics will include questions regarding the impact of COVID-19 pandemic on employment, finances, volunteering, charitable giving, accommodation and living arrangements, help-seeking behaviours, as well as any potential positive changes during this period.\n\nEthics and DisseminationEthical approval has been gained from Kings College London Research Ethics Committee (Ref: HR-19/20-18626). Participants were provided with information and agreed to a series of consent statements before enrolment. Data are kept on secure servers with access to personally identifiable information limited. Findings will be disseminated to the OVA, UK ex-service stakeholders and international research institutions through stakeholder meetings, project reports and scientific publications.\n\nStrengths and limitations of this studyO_LIStrengths include recruitment from a population where underlying characteristics are known, and longitudinal data is held on their health and wellbeing.\nC_LIO_LIThere has been rapid roll-out of the survey to ensure relevance for participants COVID-19 experiences and use of validated measures for mental health and wellbeing outcomes.\nC_LIO_LIStudy limitations include recruitment from a specific cohort; hence the study cannot comment on the impact of COVID-19 in other veteran populations.\nC_LI", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Sipat Dr. Triukose", - "author_inst": "Research group on Applied Digital Technology in Medicine (ATM) and Chulalongkorn University Big Data Analytics and IoT Center (CUBIC), Chulalongkorn University" - }, - { - "author_name": "Sirin Dr. Nitinawarat", - "author_inst": "International School of Engineering, Faculty of Engineering and Research group on Applied Digital Technology in Medicine (ATM), Chulalongkorn University" + "author_name": "Marie-Louise Sharp", + "author_inst": "King's College London" }, { - "author_name": "Ponlapat Satian", - "author_inst": "Lansaka Hospital, Office of the permanent secretary, Ministry of Public Health, Thailand" + "author_name": "Danai Serfioti", + "author_inst": "King's College London" }, { - "author_name": "Anupap Dr. Somboonsavatdee", - "author_inst": "Greater Data Science Lab, Department of Statistics, Chulalongkorn Business School, 15 Chulalongkorn University, Bangkok, Thailand" + "author_name": "Margaret Jones", + "author_inst": "King's College London" }, { - "author_name": "Ponlachart Dr. Chotikarn", - "author_inst": "Marine and Coastal Resources Institute, Faculty of Environmental Management, Coastal Oceanography and Climate Change Research Center, Prince of Songkla Universi" + "author_name": "Howard Burdett", + "author_inst": "King's College London" }, { - "author_name": "Thunchanok Thammasanya", - "author_inst": "TrueEye Company Limited, Bangkok, Thailand" + "author_name": "David Pernet", + "author_inst": "King's College London" }, { - "author_name": "Nasamon Wanlapakorn", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, 22 Chulalongkorn University, Bangkok, Thailand" + "author_name": "Lisa Hull", + "author_inst": "King's College London" }, { - "author_name": "Natthinee Dr. Sudhinaraset", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand" + "author_name": "Dominic Murphy", + "author_inst": "Combat Stress" }, { - "author_name": "Pitakpol Dr. Boonyamalik", - "author_inst": "Office of the Permanent Secretary, Ministry of Public Health, Bangkok, Thailand" + "author_name": "Sharon Stevelink", + "author_inst": "King's College London" }, { - "author_name": "Bancha Kakhong", - "author_inst": "Department of Health, Ministry of Public Health, Bangkok, Thailand" + "author_name": "Simon Wessely", + "author_inst": "King's College London" }, { - "author_name": "Yong Poovorawan", - "author_inst": "Center of Excellence in Clinical Virology, Department of Pediatrics, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand" + "author_name": "Nicola Fear", + "author_inst": "King's College London" } ], "version": "1", @@ -1220942,81 +1220684,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.29.20184135", - "rel_title": "Modeling the combined effect of digital exposure notification and non-pharmaceutical interventions on the COVID-19 epidemic in Washington state", + "rel_doi": "10.1101/2020.08.29.20184465", + "rel_title": "One Study of COVID-19 Spreading at The United States - Brazil - Colombia", "rel_date": "2020-09-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.29.20184135", - "rel_abs": "Contact tracing is increasingly being used to combat COVID-19, and digital implementations are now being deployed, many of them based on Apple and Googles Exposure Notification System. These systems are new and are based on smartphone technology that has not traditionally been used for this purpose, presenting challenges in understanding possible outcomes. In this work, we use individual-based computational models to explore how digital exposure notifications can be used in conjunction with non-pharmaceutical interventions, such as traditional contact tracing and social distancing, to influence COVID-19 disease spread in a population. Specifically, we use a representative model of the household and occupational structure of three counties in the state of Washington together with a proposed digital exposure notifications deployment to quantify impacts under a range of scenarios of adoption, compliance, and mobility. In a model in which 15% of the population participated, we found that digital exposure notification systems could reduce infections and deaths by approximately 8% and 6%, effectively complementing traditional contact tracing. We believe this can serve as guidance to health authorities in Washington state and beyond on how exposure notification systems can complement traditional public health interventions to suppress the spread of COVID-19.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.29.20184465", + "rel_abs": "The present work concerns the COVID-19s spread over The United States, Brazil and Colombia. Although countries show differences in economic development, but similarities such as continental dimension or social interaction, the spread of COVID-19 in them has some similarities. At the moment, the countries are living the disease with temporal delay. Thus, we used a database on WHO Coronavirus, Mathematical Modeling and Numerical Simulations to describe the most recent COVID-19 development patterns in these countries, which we saw.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Matthew Abueg", - "author_inst": "Google Research" - }, - { - "author_name": "Robert Hinch", - "author_inst": "Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Neo Wu", - "author_inst": "Google Research" - }, - { - "author_name": "Luyang Liu", - "author_inst": "Google Research" - }, - { - "author_name": "William J M Probert", - "author_inst": "University of Oxford" - }, - { - "author_name": "Austin Wu", - "author_inst": "Google LLC" - }, - { - "author_name": "Paul Eastham", - "author_inst": "Google Research" - }, - { - "author_name": "Yusef Shafi", - "author_inst": "Google Research" - }, - { - "author_name": "Matt Rosencrantz", - "author_inst": "Google Research" - }, - { - "author_name": "Michael Dikovsky", - "author_inst": "Google Research" - }, - { - "author_name": "Zhao Cheng", - "author_inst": "Google Research" - }, - { - "author_name": "Anel Nurtay", - "author_inst": "Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Lucie Abeler-D\u00f6rner", - "author_inst": "Nuffield Department of Medicine, University of Oxford" + "author_name": "Eliandro Rodrigues Cirilo", + "author_inst": "Universidade Estadual de Londrina" }, { - "author_name": "David G Bonsall", - "author_inst": "Big Data Institute" + "author_name": "Miguel Candezano", + "author_inst": "Universidad del Atlantico" }, { - "author_name": "Michael V McConnell", - "author_inst": "Google LLC" + "author_name": "Paulo Natti", + "author_inst": "Universidade Estadual de Londrina" }, { - "author_name": "Shawn O'Banion", - "author_inst": "Google Research" + "author_name": "Neyva Romeiro", + "author_inst": "Universidade Estadual de Londrina" }, { - "author_name": "Christophe Fraser", - "author_inst": "University of Oxford" + "author_name": "Jeinny Polo", + "author_inst": "Universidad Nacional Abierta y a Distancia" } ], "version": "1", @@ -1222844,41 +1222538,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.31.20185587", - "rel_title": "Health and economic effects of COVID-19 control in Australia: Modelling and quantifying the payoffs of hard versus soft lockdown", + "rel_doi": "10.1101/2020.08.31.20185033", + "rel_title": "Asymptomatic cases and limited transmission of SARS-CoV-2 in residents and healthcare workers in three Dutch nursing homes", "rel_date": "2020-09-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.31.20185587", - "rel_abs": "Objective(s)Australia requires high quality evidence to optimise likely health and economy outcomes to effectively manage the current resurgence of COVID-19. We hypothesise that the most stringent social distancing (SD) measures (100% of level in Australia in April 2020) deliver better public health and economy outcomes.\n\nDesign Fit-for-purpose (individual-based and compartment) models were used to simulate the effects of different SD and detection strategies on Australian COVID-19 infections and the economy from March to July 2020. Public reported COVID-19 data were used to estimate model parameters.\n\nMain outcome measuresPublic health and economy outcomes for multiple social distancing levels were evaluated, assessing \"hard\" versus \"soft\" lockdowns, and for early versus later relaxation of social distancing. Outcomes included costs and the timing and magnitude of observed COVID-19 cases and cumulative deaths in Australia from March to June 2020.\n\nResultsHigher levels of social distancing achieve zero community transmission with 100% probability and lower economy cost while low levels of social distancing result in uncontrolled outbreaks and higher economy costs. High social distancing total economy costs were $17.4B versus $41.2B for 0.7 social distancing. Early relaxation of suppression results in worse public health outcomes and higher economy costs.\n\nConclusion(s)Better public health outcomes (reduced COVID-19 fatalities) are positively associated with lower economy costs and higher levels of social distancing; achieving zero community transmission lowers both public health and economy costs compared to allowing community transmission to continue; and early relaxation of social distancing increases both public health and economy costs.\n\nSignificanceThe known is that COVID-19 infections can be suppressed with social distancing (SD) measures of sufficient stringency and duration.\n\nThe new is we find highest levels of SD (100% SD that prevailed in April 2020) generate much lower COVID-9 deaths; reduced SD days; increased economic activity; and much higher probability of elimination over a subsequent 12-month period than lower levels of SD.\n\nThe implications are that greater levels of SD are preferred to lower SD because they deliver both better public health and lower economy costs.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.31.20185033", + "rel_abs": "PurposeMany nursing homes worldwide have been hit by outbreaks of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We aimed to assess the contribution of a- and presymptomatic residents and healthcare workers in transmission of SARS-CoV-2 in three nursing homes.\n\nMethodsTwo serial point-prevalence surveys, 1 week apart, among residents and healthcare workers of three Dutch nursing homes with recent SARS-CoV-2 introduction. Nasopharyngeal and oropharyngeal testing for SARS-CoV-2, including reverse-transcriptase polymerase chain reaction (rRT-PCR) was presymptomatic or asymptomatic with standardized symptom assessment.\n\nResultsIn total, 297 residents and 542 healthcare workers participated in the study. At the first point-prevalence survey, 15 residents tested positive of which one was presymptomatic (Ct value>35) and three remained asymptomatic (Ct value of 23, 30 and 32). At the second point-prevalence survey one resident and one healthcare worker tested SARS-CoV-2 positive (Ct value >35 and 24, respectively) and both remained asymptomatic.\n\nConclusionThis study confirms a-and presymptomatic occurrence of Covid-19 among residents and health care workers. Ct values below 25 suggested that these cases have the potential to contribute to viral spread. However, very limited transmission impeded the ability to answer the research question. We describe factors that may contribute to the prevention of transmission and argue that the necessity of large-scale preemptive testing in nursing homes may be dependent of the local situation regarding prevalence of cases in the surrounding community and infection control opportunities.\n\nKEY SUMMARY POINTSO_ST_ABSAimC_ST_ABSTo assess the contribution of a- and presymptomatic residents and healthcare workers in transmission of SARS-CoV-2 in three nursing homes by facility wide preemptive testing.\n\nFindingsOccurrence of a-and presymptomatic residents and healthcare workers with Ct values below 25 was confirmed. However, evaluation of contribution to transmission of the virus was not possible because of limited positive cases in the follow-up.\n\nMessageNecessity of large-scale preemptive testing for a- and presymptomatic SARS-CoV-2 cases in nursing homes may be dependent on prevalence of cases in the surrounding community and infection control opportunities.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Quentin Grafton", - "author_inst": "Australian National University" - }, - { - "author_name": "Tom Kompas", - "author_inst": "University of Melbourne" + "author_name": "Laura W van Buul", + "author_inst": "Amsterdam University Medical Center" }, { - "author_name": "John Parslow", - "author_inst": "CSIRO" + "author_name": "Judith Henriette van den Besselaar", + "author_inst": "Amsterdam Universitair Medische Centra" }, { - "author_name": "Kathryn Glass", - "author_inst": "Australian National University" + "author_name": "Fleur M.H.P.H. Koene", + "author_inst": "Amsterdam University Medical Center" }, { - "author_name": "Emily Banks", - "author_inst": "Australian National University" + "author_name": "Bianca M. Buurman", + "author_inst": "Amsterdam University Medical Center" }, { - "author_name": "Kamalini Lokuge", - "author_inst": "Australian National University" + "author_name": "Cees M.P.M. Hertogh", + "author_inst": "Amsterdam University Medical Center" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1224654,31 +1224344,59 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.09.01.278366", - "rel_title": "An intestinal cell type in zebrafish is the nexus for the SARS-CoV-2 receptor and the Renin-Angiotensin-Aldosterone System that contributes to COVID-19 comorbidities", + "rel_doi": "10.1101/2020.09.01.278952", + "rel_title": "Structural Variants in SARS-CoV-2 Occur at Template-Switching Hotspots", "rel_date": "2020-09-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.01.278366", - "rel_abs": "People with underlying conditions, including hypertension, obesity, and diabetes, are especially susceptible to negative outcomes after infection with the coronavirus SARS-CoV-2. These COVID-19 comorbidities are exacerbated by the Renin-Angiotensin-Aldosterone System (RAAS), which normally protects from rapidly dropping blood pressure or dehydration via the peptide Angiotensin II (Ang II) produced by the enzyme Ace. The Ace paralog Ace2 degrades Ang II, thus counteracting its chronic effects. Ace2 is also the SARS-CoV-2 receptor. Ace, the coronavirus, and COVID-19 comorbidities all regulate Ace2, but we dont yet understand how. To exploit zebrafish (Danio rerio) as a disease model to understand mechanisms regulating the RAAS and its relationship to COVID-19 comorbidities, we must first identify zebrafish orthologs and co-orthologs of human RAAS genes, and second, understand where and when these genes are expressed in specific cells in zebrafish development. To achieve these goals, we conducted genomic analyses and investigated single cell transcriptomes. Results showed that most human RAAS genes have an ortholog in zebrafish and some have two or more co-orthologs. Results further identified a specific intestinal cell type in zebrafish larvae as the site of expression for key RAAS components, including Ace, Ace2, the coronavirus co-receptor Slc6a19, and the Angiotensin-related peptide cleaving enzymes Anpep and Enpep. Results also identified specific vascular cell subtypes as expressing Ang II receptors, apelin, and apelin receptor genes. These results identify specific genes and cell types to exploit zebrafish as a disease model for understanding the mechanisms leading to COVID-19 comorbidities.\n\nSUMMARY STATEMENTGenomic analyses identify zebrafish orthologs of the Renin-Angiotensin-Aldosterone System that contribute to COVID-19 comorbidities and single-cell transcriptomics show that they act in a specialized intestinal cell type.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.09.01.278952", + "rel_abs": "The evolutionary dynamics of SARS-CoV-2 have been carefully monitored since the COVID-19 pandemic began in December 2019, however, analysis has focused primarily on single nucleotide polymorphisms and largely ignored the role of structural variants (SVs) as well as recombination in SARS-CoV-2 evolution. Using sequences from the GISAID database, we catalogue over 100 insertions and deletions in the SARS-CoV-2 consensus sequences. We hypothesize that these indels are artifacts of imperfect homologous recombination between SARS-CoV-2 replicates, and provide four independent pieces of evidence. (1) The SVs from the GISAID consensus sequences are clustered at specific regions of the genome. (2) These regions are also enriched for 5 and 3 breakpoints in the transcription regulatory site (TRS) independent transcriptome, presumably sites of RNA-dependent RNA polymerase (RdRp) template-switching. (3) Within raw reads, these structural variant hotspots have cases of both high intra-host heterogeneity and intra-host homogeneity, suggesting that these structural variants are both consequences of de novo recombination events within a host and artifacts of previous recombination. (4) Within the RNA secondary structure, the indels occur in \"arms\" of the predicted folded RNA, suggesting that secondary structure may be a mechanism for TRS-independent template-switching in SARS-CoV-2 or other coronaviruses. These insights into the relationship between structural variation and recombination in SARS-CoV-2 can improve our reconstructions of the SARS-CoV-2 evolutionary history as well as our understanding of the process of RdRp template-switching in RNA viruses.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "John Postlethwait", - "author_inst": "University of Oregon" + "author_name": "Brianna Chrisman", + "author_inst": "Stanford University" }, { - "author_name": "Dylan R Farnsworth", - "author_inst": "University of Oregon" + "author_name": "Kelley Paskov", + "author_inst": "Stanford University" }, { - "author_name": "Adam C Miller", - "author_inst": "University of Oregon" + "author_name": "Nate Stockham", + "author_inst": "Stanford University" + }, + { + "author_name": "Kevin Tabatabaei", + "author_inst": "McMaster University" + }, + { + "author_name": "Jae-Yoon Jung", + "author_inst": "Stanford University" + }, + { + "author_name": "Peter Washington", + "author_inst": "Stanford University" + }, + { + "author_name": "Maya Varma", + "author_inst": "Stanford University" + }, + { + "author_name": "Min Woo Sun", + "author_inst": "Stanford University" + }, + { + "author_name": "Sepideh Maleki", + "author_inst": "University of Texas Austin" + }, + { + "author_name": "Dennis Paul Wall", + "author_inst": "Stanford University School of Medicine" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "developmental biology" + "category": "genetics" }, { "rel_doi": "10.1101/2020.09.01.277780", @@ -1226572,43 +1226290,63 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.26.20182584", - "rel_title": "A multipurpose machine learning approach to predict COVID-19 negative prognosis in Sao Paulo, Brazil", + "rel_doi": "10.1101/2020.08.26.20182618", + "rel_title": "Post-COVID-19 Functional Status: Relation to age, smoking, hospitalization and comorbidities", "rel_date": "2020-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.26.20182584", - "rel_abs": "IntroductionThe new coronavirus disease (COVID-19) is a challenge for clinical decision-making and the effective allocation of healthcare resources. An accurate prognostic assessment is necessary to improve survival of patients, especially in developing countries. This study proposes to predict the risk of developing critical conditions in COVID-19 patients by training multipurpose algorithms.\n\nMethodsA total of 1,040 patients with a positive RT-PCR diagnosis for COVID-19 from a large hospital from Sao Paulo, Brazil, were followed from March to June 2020, of which 288 (28%) presented a severe prognosis, i.e. Intensive Care Unit (ICU) admission, use of mechanical ventilation or death. Routinely-collected laboratory, clinical and demographic data was used to train five machine learning algorithms (artificial neural networks, extra trees, random forests, catboost, and extreme gradient boosting). A random sample of 70% of patients was used to train the algorithms and 30% were left for performance assessment, simulating new unseen data. In order to assess if the algorithms could capture general severe prognostic patterns, each model was trained by combining two out of three outcomes to predict the other.\n\nResultsAll algorithms presented very high predictive performance (average AUROC of 0.92, sensitivity of 0.92, and specificity of 0.82). The three most important variables for the multipurpose algorithms were ratio of lymphocyte per C-reactive protein, C-reactive protein and Braden Scale.\n\nConclusionThe results highlight the possibility that machine learning algorithms are able to predict unspecific negative COVID-19 outcomes from routinely-collected data.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.26.20182618", + "rel_abs": "RationalRecently, a new \"Post-COVID-19 Functional Status (PCFS) scale\" is recommended in the current COVID-19 pandemic. It is proposed that it could be used to display direct retrieval and the functional sequelae of COVID-19.\n\nAim of the studyTo assess the Post COVID-19 functional status in Egypt and to evaluate if age, gender, comorbidities have any effect on functional limitations in recovered COVID-19 patients.\n\nPatients and methodsA total of 444 registered confirmed COVID-19 patients were included. They were interviewed in our follow-up clinics or by calls and filled an Arabic translated PCFS scale in paper or online forms as well as their demographic and clinical data.\n\nResults80% of COVID-19 recovered cases have diverse degrees of functional restrictions ranging from negligible (63.1%), slight (14.4%), moderate (2%) to severe (0.5%) based on PCFS. Furthermore, there was a substantial variance between the score of PCFS with age (P= 0.003), gender (P= 0.014), the duration since the onset of the symptoms of COVID-19 (P <0.001), need for oxygen supplementation (P<0.001), need for ICU admittance (P= 0.003), previous periodic influenza vaccination (P<0.001), smoking status (P < 0.001) and lastly the presence of any comorbid disorder (P <0.001).\n\nConclusionsMost of the COVID-19 recovered cases have diverse degrees of functional restrictions ranging from negligible to severe based on PCFS. These restrictions were affected by age, gender, periodic influenza vaccination, smoking, duration since symptoms onset, need for oxygen or ICU admittance, and lastly the presence of coexisting comorbidity.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Fernando Timoteo Fernandes", - "author_inst": "Fundacentro" + "author_name": "Aliae Mohamed-Hussein", + "author_inst": "Faculty of medicine, Assiut University" }, { - "author_name": "Tiago Almeida de Oliveira", - "author_inst": "Paraiba State University" + "author_name": "Islam Galal", + "author_inst": "Chest Department, Aswan University" }, { - "author_name": "Cristiane Esteves Teixeira", - "author_inst": "National Cancer Institute" + "author_name": "Mahmoud Saad", + "author_inst": "Faculty of Medicine, Assiut University" }, { - "author_name": "Andre Filipe de Moraes Batista", - "author_inst": "University of Sao Paulo" + "author_name": "Hossam Eldeen Zayan", + "author_inst": "Assiut University Hospitals" }, { - "author_name": "Gabriel Dalla Costa", - "author_inst": "BP - A Beneficencia Portuguesa de Sao Paulo" + "author_name": "Moustafa Abdelsayed", + "author_inst": "Assiut University Hospitals" }, { - "author_name": "Alexandre Chiavegatto Filho", - "author_inst": "University of Sao Paulo" + "author_name": "Mohamed Moustafa", + "author_inst": "Chest Department, Assiut University" + }, + { + "author_name": "Abdel Rahman Ezzat", + "author_inst": "Assiut University" + }, + { + "author_name": "Radwa Helmy", + "author_inst": "Assiut Unicersity" + }, + { + "author_name": "Howaida Abd Elaal", + "author_inst": "Faculty of Nursing, Aswan University" + }, + { + "author_name": "Karim Aly", + "author_inst": "Cardiology, Assiut University" + }, + { + "author_name": "Shaimaa Abderheem", + "author_inst": "Public Health, Aswan University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.08.26.20181644", @@ -1227974,25 +1227712,53 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2020.08.27.20183277", - "rel_title": "DeepSOCIAL: Social Distancing Monitoring and Infection Risk Assessment in COVID-19 Pandemic", + "rel_doi": "10.1101/2020.08.28.20183863", + "rel_title": "Unmasking the conversation on masks: Natural language processing for topical sentiment analysis of COVID-19 Twitter discourse", "rel_date": "2020-09-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.27.20183277", - "rel_abs": "Social distancing is a recommended solution by the World Health Organisation (WHO) to minimise the spread of COVID-19 in public places. The majority of governments and national health authorities have set the 2-meter physical distancing as a mandatory safety measure in shopping centres, schools and other covered areas. In this research, we develop a generic Deep Neural Network-Based model for automated people detection, tracking, and inter-people distances estimation in the crowd, using common CCTV security cameras. The proposed model includes a YOLOv4-based framework and inverse perspective mapping for accurate people detection and social distancing monitoring in challenging conditions, including people occlusion, partial visibility, and lighting variations. We also provide an online risk assessment scheme by statistical analysis of the Spatio-temporal data from the moving trajectories and the rate of social distancing violations. We identify high-risk zones with the highest possibility of virus spread and infections. This may help authorities to redesign the layout of a public place or to take precaution actions to mitigate high-risk zones. The efficiency of the proposed methodology is evaluated on the Oxford Town Centre dataset, with superior performance in terms of accuracy and speed compared to three state-of-the-art methods.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.28.20183863", + "rel_abs": "In this exploratory study, we scrutinize a database of over one million tweets collected from March to July 2020 to illustrate public attitudes towards mask usage during the COVID-19 pandemic. We employ natural language processing, clustering and sentiment analysis techniques to organize tweets relating to mask-wearing into high-level themes, then relay narratives for each theme using automatic text summarization. In recent months, a body of literature has highlighted the robustness of trends in online activity as proxies for the sociological impact of COVID-19. We find that topic clustering based on mask-related Twitter data offers revealing insights into societal perceptions of COVID-19 and techniques for its prevention. We observe that the volume and polarity of mask-related tweets has greatly increased. Importantly, the analysis pipeline presented may be leveraged by the health community for qualitative assessment of public response to health intervention techniques in real time.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Mahdi Rezaei", - "author_inst": "The University of Leeds" + "author_name": "Abraham C. Sanders", + "author_inst": "Rensselaer Polytechnic Institute" + }, + { + "author_name": "Rachael C. White", + "author_inst": "Rensselaer Polytechnic Institute" }, { - "author_name": "Mohsen Azarmi", - "author_inst": "Qazvin Azad University" + "author_name": "Lauren S. Severson", + "author_inst": "Rensselaer Polytechnic Institute" + }, + { + "author_name": "Rufeng Ma", + "author_inst": "Rensselaer Polytechnic Institute" + }, + { + "author_name": "Richard McQueen", + "author_inst": "Rensselaer Polytechnic Institute" + }, + { + "author_name": "Haniel C. Alc\u00e2ntara Paulo", + "author_inst": "Rensselaer Polytechnic Institute" + }, + { + "author_name": "Yucheng Zhang", + "author_inst": "Rensselaer Polytechnic Institute" + }, + { + "author_name": "John S. Erickson", + "author_inst": "Rensselaer Polytechnic Institute" + }, + { + "author_name": "Kristin P. Bennett", + "author_inst": "Rensselaer Polytechnic Institute" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "health informatics" }, @@ -1229920,21 +1229686,37 @@ "category": "scientific communication and education" }, { - "rel_doi": "10.1101/2020.08.25.20181347", - "rel_title": "Correction of Daily Positivity Rates for contribution of various test protocols being used in a pandemic.", + "rel_doi": "10.1101/2020.08.24.20180752", + "rel_title": "Disease-dependent interaction policies to support health and economic outcomes during the COVID-19 epidemic", "rel_date": "2020-08-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.25.20181347", - "rel_abs": "Daily positivity rate (DPR) is a popular metric to judge the prevalence of an infection in the population and the testing response to it as a single number. It has been widely implicated in predicting future course of the SARS CoV-2 pandemic in India. With increasing use of multiple testing protocols with varying sensitivity and specificity in various proportions, the naive calculation loses meaning particularly during comparison between states/countries with large daily variations in contribution of different testing protocols to the testing response. We propose an adjustment to the naive DPR based on the testing parameters and the relative proportional use of each such protocol. Such a correction has become essential for comparing testing response of Indian states from Jun 2020 - Aug 2020 because of steep variations in testing protocol in certain states.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20180752", + "rel_abs": "Lockdowns and stay-at-home orders have partially mitigated the spread of Covid-19. However, the indiscriminate nature of mitigation -- applying to all individuals irrespective of disease status -- has come with substantial socioeconomic costs. Here, we explore how to leverage the increasing reliability and scale of both molecular and serological tests to balance transmission risks with economic costs involved in responding to Covid-19 epidemics. First, we introduce an optimal control approach that identifies personalized interaction rates according to an individuals test status; such that infected individuals isolate, recovered individuals can elevate their interactions, and activity of susceptible individuals varies over time. Critically, the extent to which susceptible individuals can return to work depends strongly on isolation efficiency. As we show, optimal control policies can yield mitigation policies with similar infection rates to total shutdown but lower socioeconomic costs. However, optimal control policies can be fragile given mis-specification of parameters or mis-estimation of the current disease state. Hence, we leverage insights from the optimal control solutions and propose a feedback control approach based on monitoring of the epidemic state. We utilize genetic algorithms to identify a switching policy such that susceptible individuals (both PCR and serological test negative) return to work after lockdowns insofar as recovered fraction is much higher than the circulating infected prevalence. This feedback control policy exhibits similar performance results to optimal control, but with greater robustness to uncertainty. Overall, our analysis shows that test-driven improvements in isolation efficiency of infectious individuals can inform disease-dependent interaction policies that mitigate transmission while enhancing the return of individuals to pre-pandemic economic activity.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Bhavik Bansal", - "author_inst": "All India Institute of Medical Sciences, New Delhi" + "author_name": "Guanlin Li", + "author_inst": "Georgia Institute of Technology" + }, + { + "author_name": "Shashwat Shivam", + "author_inst": "Georgia Institute of Technology" + }, + { + "author_name": "Michael E. Hochberg", + "author_inst": "University of Montpellier" + }, + { + "author_name": "Yorai Wardi", + "author_inst": "Georgia Institute of Technology" + }, + { + "author_name": "Joshua S Weitz", + "author_inst": "Georgia Institute of Technology" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1231866,59 +1231648,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.25.20182113", - "rel_title": "Post-infection depression, anxiety and PTSD: a retrospective cohort study with mild COVID-19 patients", + "rel_doi": "10.1101/2020.08.25.20181420", + "rel_title": "The Role of Air Conditioning in the Diffusion of Sars-CoV-2 in Indoor Environments: a First Computational Fluid Dynamic Model, based on Investigations performed at the Vatican State Childrens Hospital.", "rel_date": "2020-08-31", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.25.20182113", - "rel_abs": "BackgroundIt remains unclear whether COVID-19 is associated with psychiatric symptoms during or after the acute illness phase. Being affected by the disease exposes the individual to an uncertain prognosis and a state of quarantine. These factors can predispose individuals to the development of mental symptoms during or after the acute phase of the disease. There is a need for prospective studies assessing mental health symptoms in COVID-19 patients in the post-infection period.\n\nMethodsIn this retrospective cohort study, nasopharyngeal swabs for COVID-19 tests were collected at patients homes under the supervision of trained healthcare personnel. Patients who tested positive for COVID-19 and were classified as mild cases (N=895) at treatment intake were further assessed for the presence of mental health disorders (on average, 56.6 days after the intake). We investigated the association between the number of COVID-19 symptoms at intake and depression, anxiety and PTSD, adjusting for previous mental health status, time between baseline and outcome, and other confounders. Multivariate logistic regression and generalized linear models were employed for categorical and continuous outcomes, respectively.\n\nFindingsDepression, anxiety and PTSD were reported by 26.2% (N=235), 22.4% (N=201), and 17.3% (N=155) of the sample. Reporting an increased number of COVID-related symptoms was associated with depression (aOR=1.059;95%CI=1.002-1.119), anxiety (aOR=1.072;95%CI=1.012-1.134), and PTSD (aOR=1.092;95%CI=1.024-1.166). Sensitivity analyses supported findings for both continuous and categorical measures.\n\nInterpretationExposure to an increased number of COVID-19 symptoms may predispose individuals to depression, anxiety and PTSD after the acute phase of the disease. These patients should be monitored for the development of mental health disorders after COVID-19 treatment discharge. Early interventions, such as brief interventions of psychoeducation on coping strategies, could benefit these individuals.\n\nFundingThe city health department of Sao Caetano do Sul (Secretaria Municipal de Saude da Prefeitura de Sao Caetano do Sul) funded the establishment and implementation of the COVID-19 platform.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.25.20181420", + "rel_abs": "BackgroundAbout 15 million people worldwide were affected by the Sars-Cov-2 infection, which already caused 600,000 deaths. This virus is mainly transmitted through exhalations from the airways of infected persons, so that Heating, Ventilation and Air Conditioning (HVAC) systems might play a role in increasing or reducing the spreading of the infection in indoor environments.\n\nMethodsWe modelled the role of HVAC systems in the diffusion of the contagion through Computational Fluid Dynamics (CFD) simulations of cough at the \"Bambino Gesu\" Vatican State Childrens Hospital.\n\nBoth waiting and hospital rooms were modeled as indoor scenarios. A specific Infection-Index ({eta}) parameter was used to estimate the amount of contaminated air inhaled by each person present in the simulated indoor scenarios. The potential role of exhaust air ventilation systems placed above the coughing patients mouth was also assessed.\n\nResultsOur CFD-based simulations of the waiting room show that HVAC air-flow remarkably enhances infected droplets diffusion in the whole indoor environment within 25 seconds from the cough event, despite the observed dilution of saliva particles containing the virus. At the same time also their number is reduced due to removal through the HVAC system or deposition on the surfaces. The proper use of Local Exhaust Ventilation systems (LEV) simulated in the hospital room was associated to a complete reduction of infected droplets spreading from the patients mouth in the first 0.5 seconds following the cough event. In the hospital room, the use of LEV system completely reduced the {eta} index computed for the patient hospitalized at the bed next to the spreader, with a decreased possibility of contagion.\n\nConclusionsCFD-based simulations for indoor environment can be useful to optimize air conditioning flow and to predict the contagion risk both in hospitals/ambulatories and in other public/private settings.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Flavia Ismael", - "author_inst": "Universidade Municipal de Sao Caetano do Sul, Sao Caetano do Sul, SP, Brazil" - }, - { - "author_name": "Joao C. S. Bizario", - "author_inst": "Faculdade de Medicina de Olinda, Olinda, PE, Brazil" + "author_name": "Luca Borro", + "author_inst": "Department of Imaging, Advanced Cardiovascular Imaging Unit, Bambino Gesu Childrens Hospital, IRCCS, Rome, Italy" }, { - "author_name": "Tatiane Battagin", - "author_inst": "Universidade Municipal de Sao Caetano do Sul, Sao Caetano do Sul, SP, Brazil" - }, - { - "author_name": "Beatriz Zaramella", - "author_inst": "Universidade Municipal de Sao Caetano do Sul, Sao Caetano do Sul, SP, Brazil" - }, - { - "author_name": "Fabio E Leal", - "author_inst": "Universidade Municipal de Sao Caetano do Sul, Sao Caetano do Sul, SP, Brazil" - }, - { - "author_name": "Julio Torales", - "author_inst": "Department of Psychiatry, School of Medical Sciences, National University of Asuncion, Asuncion, Paraguay" + "author_name": "Lorenzo Mazzei", + "author_inst": "Ergon Research, CFD Consultant, Florence, Italy" }, { - "author_name": "Antonio Ventriglio", - "author_inst": "Department of Clinical and Experimental Medicine, University of Foggia, Foggia, Italy" + "author_name": "Massimiliano Raponi", + "author_inst": "Hospital Directorate, Bambino Gesu Childrens Hospital, IRCCS, Rome, Italy;" }, { - "author_name": "Megan E. Marziali", - "author_inst": "Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, U.S." + "author_name": "Prisco Piscitelli", + "author_inst": "Italian Society of Environmental Medicine, SIMA, Milan, Italy; - Staff UNESCO Chair on Health Education and Sustainable Development, Federico II University, Nap" }, { - "author_name": "Silvia S. Martins", - "author_inst": "Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, U.S." + "author_name": "Alessandro Miani", + "author_inst": "Italian Society of Environmental Medicine - Department of Environmental Sciences and Policy, University of Milan, Milan, Italy;" }, { - "author_name": "Joao M. Castaldelli-Maia", - "author_inst": "Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, U.S." + "author_name": "Aurelio Secinaro", + "author_inst": "Department of Imaging, Advanced Cardiovascular Imaging Unit, Bambino Gesu Childrens Hospital, IRCCS, Rome, Italy" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.08.25.20182162", @@ -1233944,21 +1233710,21 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.08.26.269118", - "rel_title": "Fractal signatures of SARS-CoV2 coronavirus, the indicator matrix, the fractal dimension and the 2D directional wavelet transform: A comparative study with SARS-CoV, MERS-CoV and SARS-like coronavirus.", + "rel_doi": "10.1101/2020.08.27.270835", + "rel_title": "Secondary analysis of transcriptomes of SARS-CoV-2 infection models to characterize COVID-19", "rel_date": "2020-08-28", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.26.269118", - "rel_abs": "The main goal of this paper is to show the 2D fractal signatures of SARS-CoV2 coronavirus, indicator matrixes maps showing the concentration of nucleotide acids are built form the RNA sequences, and then the fractal dimension and 2D Directional Wavelet Transform (DCWT) are calculated. Analysis of 21 RNA sequences downloaded from NCBI database shows that indicator matrixes and 2D DCWT exhibit the same patterns with different positions, while the fractal dimensions are oscillating around 1.60. A comparison with SARS-CoV, MERS-CoV and SARS-like Coronavirus shows slightly different fractal dimensions, however the indicator matrix and 2D DCWT exhibit the same patterns for the couple (SARS-CoV2, SARS-CoV) and (MERS-CoV, SARS-like) Coronavirus. Obtained results show that SARS-CoV2 is probably a result of SARS-CoV mutation process.", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.27.270835", + "rel_abs": "Knowledge about the molecular mechanisms driving COVID-19 pathophysiology and outcomes is still limited. To learn more about COVID-19 pathophysiology we performed secondary analyses of transcriptomic data from two in vitro (Calu-3 and Vero E6 cells) and one in vivo (Ad5-hACE2-sensitized mice) models of SARS-CoV-2 infection. We found 1467 conserved differentially expressed host genes (differentially expressed in at least two of the three model system transcriptomes compared) in SARS-CoV-2 infection. To find potential genetic factors associated with COVID-19, we analyzed these conserved differentially expressed genes using known human genotype-phenotype associations. Genome-wide association study enrichment analysis showed evidence of enrichment for GWA loci associated with platelet functions, blood pressure, body mass index, respiratory functions, and neurodegenerative and neuropsychiatric diseases, among others. Since human protein complexes are known to be directly related to viral infection, we combined and analyzed the conserved transcriptomic signature with SARS-CoV-2-host protein-protein interaction data and found more than 150 gene clusters. Of these, 29 clusters (with 5 or more genes in each cluster) had at least one gene encoding protein that interacts with SARS-CoV-2 proteome. These clusters were enriched for different cell types in lung including epithelial, endothelial, and immune cell types suggesting their pathophysiological relevancy to COVID-19. Finally, pathway analysis on the conserved differentially expressed genes and gene clusters showed alterations in several pathways and biological processes that could enable in understanding or hypothesizing molecular signatures inducing pathophysiological changes, risks, or sequelae of COVID-19.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Sid-Ali Ouadfeul", - "author_inst": "Algerian Petroleum Institute" + "author_name": "Anil G Jegga", + "author_inst": "Cincinnati Childrens Hospital Medical Center" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "new results", "category": "genomics" }, @@ -1235441,57 +1235207,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.24.20170175", - "rel_title": "Evidence of SARS-CoV-2 transcriptional activity in cardiomyocytes of COVID-19 patients without clinical signs of cardiac involvement", + "rel_doi": "10.1101/2020.08.24.20174367", + "rel_title": "COVID-19 and heart medications: What's the connection?", "rel_date": "2020-08-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20170175", - "rel_abs": "BackgroundCardiovascular complication in patients affected by novel Coronavirus respiratory disease (COVID-19) are increasingly recognized. However, although a cardiac tropism of SARS-CoV-2 for inflammatory cells in autopsy heart samples of COVID-19 patients has been reported, the presence of the virus in cardiomyocytes has not been documented yet.\n\nMethodsWe investigated for SARS-CoV-2 presence in heart tissue autopsies of 6 consecutive COVID-19 patients deceased for respiratory failure showing no signs of cardiac involvement and with no history of heart disease. Cardiac autopsy samples were analysed by digital PCR, Western blot, immunohistochemistry, immunofluorescence, RNAScope, and transmission electron microscopy assays.\n\nResultsThe presence of SARS-CoV-2 into cardiomyocytes was invariably detected. A variable pattern of cardiomyocytes injury was observed, spanning from the absence of cell death and subcellular alterations hallmarks to the intracellular oedema and sarcomere ruptures. In addition, we found active viral transcription in cardiomyocytes, by detecting both sense and antisense SARS-CoV-2 spike RNA.\n\nConclusionsIn this analysis of autopsy cases, the presence of SARS-CoV-2 into cardiomyocytes, determining variable patterns of intracellular involvement, has been documented. All these findings suggest the need of a cardiologic surveillance even in survived COVID-19 patients not displaying a cardiac phenotype, in order to monitor potential long-term cardiac sequelae.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20174367", + "rel_abs": "AimTo determine association between clinical outcome of COVID-19 and prior usage of cardiovascular and metabolic drugs, including, Aspirin, ACEIs, ARBs, Clopidogrel, metformin, and Statins.\n\nMethodsStatistical examination of the demographic, clinical, laboratory and imaging features of 353 patients with SARS-CoV-2 disease admitted from February to April 2020.\n\nResultMinor discrepancies were observed in the clinical presentations, radiologic involvement and laboratory results across groups of patients under treatment with specific drugs. Aspirin-users had better clinical outcome with lower need of ventilation support, whereas, metformin- users had increased chance of intubation and of mortality.\n\nConclusionAlthough not being conclusive, our findings suggest the possibility of the effect of previous drug usages on the various presentations and clinical course of COVID-19 infection.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Gaetano Pietro Bulfamante", - "author_inst": "University of Milan" + "author_name": "Nafiseh Saleknezhad", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Gianluca Lorenzo Perrucci", - "author_inst": "Centro Cardiologico Monzino-IRRCS" + "author_name": "Bardia Khosravi", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Monica Falleni", - "author_inst": "University of Milan" + "author_name": "Amir Anushiravani", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Elena Sommariva", - "author_inst": "Centro Cardiologico Monzino-IRCCS" + "author_name": "Masoud Eslahi", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Delfina Tosi", - "author_inst": "University of Milan" + "author_name": "Amir Reza Radmard", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Carla Martinelli", - "author_inst": "University of Milan" + "author_name": "Azin Sirusbakht", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Paola Songia", - "author_inst": "Centro Cardiologico Monzino-IRCCS" + "author_name": "Seyed Mohammad Pourabbas", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Paolo Poggio", - "author_inst": "Centro Cardiologico Monzino-IRCCS" + "author_name": "Mohammad Abdollahi", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Stefano Carugo", - "author_inst": "University of Milan" + "author_name": "Amir Kasaeian", + "author_inst": "Tehran University of Medical Sciences" }, { - "author_name": "Giulio Pompilio", - "author_inst": "Centro Cardiologico Monzino-IRCCS" + "author_name": "Majid Sorouri", + "author_inst": "Tehran University of Medical Sciences" + }, + { + "author_name": "Ali Reza Sima", + "author_inst": "Tehran University of Medical Sciences" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "cardiovascular medicine" }, @@ -1237335,95 +1237105,63 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.08.22.20179754", - "rel_title": "Monitoring COVID-19 transmission risks by RT-PCR tracing of droplets in hospital and living environments", + "rel_doi": "10.1101/2020.08.22.20179960", + "rel_title": "Impacts of K-12 school reopening on the COVID-19 epidemic in Indiana, USA", "rel_date": "2020-08-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.22.20179754", - "rel_abs": "SARS-CoV-2 environmental contamination occurs through droplets and biological fluids released in the surroundings from patients or asymptomatic carriers. Surfaces and objects contaminated by saliva or nose secretions represent a risk for indirect transmission of COVID-19. We assayed surfaces from hospital and living spaces to identify the presence of viral RNA and the spread of fomites in the environment. Anthropic contamination by droplets and biological fluids was monitored by detecting the microbiota signature using multiplex RT-PCR on selected species and massive sequencing on 16S-amplicons.\n\nA total of 92 samples (flocked swab) were collected from critical areas during the pandemic, including indoor (3 hospitals and 3 public buildings) and outdoor surfaces exposed to anthropic contamination (handles and handrails, playgrounds). Traces of biological fluids were frequently detected in spaces open to the public and on objects that are touched with the hands (>80%). However, viral RNA was not detected in hospital wards or other indoor and outdoor surfaces either in the air system of a COVID-hospital, but only in the surroundings of an infected patient, in consistent association with droplets traces and fomites. Handled objects accumulated the highest level of multiple contaminations by saliva, nose secretions and faecal traces, further supporting the priority role of handwashing in prevention.\n\nIn conclusion, anthropic contamination by droplets and biological fluids is widespread in spaces open to the public and can be traced by RT-PCR. Monitoring fomites can support evaluation of indirect transmission risks for Coronavirus or other flu-like viruses in the environment.\n\nImportanceSeveral studies searched for SARS-CoV-2 in the environment because saliva and nasopharyngeal droplets can land on objects and surfaces creating fomites. However, the ideal indicator would be the detection of the biofluid. This approach was not yet considered, but follows a traditional principle in hygiene, using indicators rather than pathogens. We searched for viral RNA but also for droplets on surfaces at risk. For the first time, we propose to monitor droplets thorugh their microbiota, by RT-PCR or NGS.\n\nEven if performed during the pandemic, SARS-CoV-2 wasnt largely spread on surfaces, unless in proximity of an infectious patient. However, anthropic contamination was frequently at high level, suggesting a putative marker for indirect transmission and risk assessment. Moreover, all SARS-CoV-2-contaminated surfaces showed the droplets microbiota.\n\nFomites detection may have an impact on public health, supporting prevention of indirect transmission also for other communicable diseases such as Flu and Flu-like infections.\n\nGRAPHICAL ABSTRACT\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC=\"FIGDIR/small/20179754v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (30K):\norg.highwire.dtl.DTLVardef@b15c11org.highwire.dtl.DTLVardef@1398ddorg.highwire.dtl.DTLVardef@98f501org.highwire.dtl.DTLVardef@1fd5282_HPS_FORMAT_FIGEXP M_FIG C_FIG", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.22.20179960", + "rel_abs": "In the United States, schools closed in March 2020 due to COVID-19 and began reopening in August 2020, despite continuing transmission of SARS-CoV-2. In states where in-person instruction resumed at that time, two major unknowns were the capacity at which schools would operate, which depended on the proportion of families opting for remote instruction, and adherence to face-mask requirements in schools, which depended on cooperation from students and enforcement by schools. To determine the impact of these conditions on the statewide burden of COVID-19 in Indiana, we used an agent-based model calibrated to and validated against multiple data types. Using this model, we quantified the burden of COVID-19 on K-12 students, teachers, their families, and the general population under alternative scenarios spanning three levels of school operating capacity (50%, 75%, and 100%) and three levels of face-mask adherence in schools (50%, 75%, and 100%). Under a scenario in which schools operated remotely, we projected 45,579 (95% CrI: 14,109-132,546) infections and 790 (95% CrI: 176-1680) deaths statewide between August 24 and December 31. Reopening at 100% capacity with 50% face-mask adherence in schools resulted in a proportional increase of 42.9 (95% CrI: 41.3-44.3) and 9.2 (95% CrI: 8.9-9.5) times that number of infections and deaths, respectively. In contrast, our results showed that at 50% capacity with 100% face-mask adherence, the number of infections and deaths were 22% (95% CrI: 16%-28%) and 11% (95% CrI: 5%-18%) higher than the scenario in which schools operated remotely. Within this range of possibilities, we found that high levels of school operating capacity (80-95%) and intermediate levels of face-mask adherence (40-70%) resulted in model behavior most consistent with observed data. Together, these results underscore the importance of precautions taken in schools for the benefit of their communities.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Andrea Piana", - "author_inst": "Department of Medical, Surgical and Experimental Sciences, University of Sassari" - }, - { - "author_name": "Maria Eugenia Colucci", - "author_inst": "Department of Medicine and Surgery, University Hospital, University of Parma" - }, - { - "author_name": "Federica Valeriani", - "author_inst": "Department of Movement, Human and Health Sciences, Unit of Public Health-Laboratory of Epidemiology and Biotechnologies, University of Rome Foro Italico" - }, - { - "author_name": "Adriano Marcolongo", - "author_inst": "Sant Andrea Hospital, Sapienza University of Rome" - }, - { - "author_name": "Giovanni Sotgiu", - "author_inst": "Department of Medical, Surgical and Experimental Sciences, University of Sassari" - }, - { - "author_name": "Cesira Pasquarella", - "author_inst": "Department of Medicine and Surgery, University Hospital, University of Parma" - }, - { - "author_name": "Lory Marika Margarucci", - "author_inst": "Department of Movement, Human and Health Sciences, Unit of Public Health-Laboratory of Epidemiology and Biotechnologies, University of Rome Foro Italico" - }, - { - "author_name": "Andrea Petrucca", - "author_inst": "Sant Andrea Hospital, Sapienza University of Rome" - }, - { - "author_name": "Gianluca Gianfranceschi", - "author_inst": "Department of Movement, Human and Health Sciences, Unit of Public Health-Laboratory of Epidemiology and Biotechnologies, University of Rome Foro Italico" + "author_name": "Guido Espana", + "author_inst": "University of Notre Dame" }, { - "author_name": "Sergio Babudieri", - "author_inst": "Department of Medical, Surgical and Experimental Sciences, University of Sassari" + "author_name": "Sean Cavany", + "author_inst": "University of Notre Dame" }, { - "author_name": "Pietro Vitali", - "author_inst": "Department of Medicine and Surgery, University Hospital, University of Parma" + "author_name": "Rachel J Oidtman", + "author_inst": "University of Notre Dame" }, { - "author_name": "Giuseppe D'Ermo", - "author_inst": "Department of Surgery, Sapienza University of Rome" + "author_name": "Carly Barbera", + "author_inst": "University of Notre Dame" }, { - "author_name": "Assunta Bizzarro", - "author_inst": "Department of Medicine and Surgery, University Hospital, University of Parma" + "author_name": "Alan Costello", + "author_inst": "University of Notre Dame" }, { - "author_name": "Flavio De Maio", - "author_inst": "Dipartimento di Scienze biotecnologiche di base, cliniche intensivologiche e perioperatorie-Sezione di Microbiologia, Universita Cattolica del Sacro Cuore" + "author_name": "Anita Lerch", + "author_inst": "University of Notre Dame" }, { - "author_name": "Matteo Vitali", - "author_inst": "Department of Public Health and Infectious Diseases, University of Rome La Sapienza" + "author_name": "Marya Poterek", + "author_inst": "University of Notre Dame" }, { - "author_name": "Antonio Azara", - "author_inst": "Department of Medical, Surgical and Experimental Sciences, University of Sassari" + "author_name": "Quan Tran", + "author_inst": "University of Notre Dame" }, { - "author_name": "Ferdinando Romano", - "author_inst": "Department of Public Health and Infectious Diseases, University of Rome La Sapienza" + "author_name": "Annaliese Wieler", + "author_inst": "University of Notre Dame" }, { - "author_name": "Maurizio Simmaco", - "author_inst": "Sant Andrea Hospital, Sapienza University of Rome" + "author_name": "Sean M Moore", + "author_inst": "University of Notre Dame" }, { - "author_name": "Vincenzo Romano Spica", - "author_inst": "University of Rome \"Foro Italico\"" + "author_name": "Alex Perkins", + "author_inst": "University of Notre Dame" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.23.20180158", @@ -1238957,57 +1238695,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.23.20177501", - "rel_title": "Therapeutic Prospects for Th-17 Cell Immune Storm Syndrome and Neurological Symptoms in COVID-19: Thiamine Efficacy and Safety, In-vitro Evidence and Pharmacokinetic Profile", + "rel_doi": "10.1101/2020.08.24.20176792", + "rel_title": "Temporal increase in D614G mutation of SARS-CoV-2 in the Middle East and North Africa: Phylogenetic and mutation analysis study", "rel_date": "2020-08-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.23.20177501", - "rel_abs": "IntroductionEmerging infectious diseases, especially the coronavirus disease identified in 2019 (COVID-19), can be complicated by a severe exacerbation in the Th17 cell-mediated IL-17 proinflammatory immune storm. This enhanced immune response plays a major role in mortality and morbidity, including neurological symptoms. We hypothesized that countering the cytokine storm with thiamine may have therapeutic efficacy in lowering the Th17 cell proinflammatory response. We used an in vitro study and corroborated those results in disease controls (DC). We developed an effective dose range and model for key pharmacokinetic measures with the potential of targeting the cytokine storm and neurological symptoms of COVID-19.\n\nStudy Participants and MethodsWe investigated the effect of a three-week 200 mg dose of thiamine in lowering the Th17 response in sixteen DC (proinflammatory origin due to heavy alcohol drinking) patients; and eight healthy control/volunteers (HV) as a pilot clinical-translational investigation. To further investigate, we performed an in vitro study evaluating the effectiveness of thiamine treatment in lowering the Th17 proinflammatory response in a mouse macrophage cell line (RAW264.7) treated with ethanol. In this in vitro study, 100 mg/day equivalent (0.01 {micro}g/ml) thiamine was used. Based on recent publications, we compared the results of the IL-17 response from our clinical and in vitro study to those found in other proinflammatory disease conditions (metabolic conditions, septic shock, viral infections and COVID-19), including symptoms, and dose ranges of effective and safe administration of thiamine. We developed a dose range and pharmacokinetic profile for thiamine as a novel intervention strategy in COVID-19 to alleviate the effects of the cytokine storm and neurological symptoms.\n\nResultsThe DC group showed significantly elevated proinflammatory cytokines compared to HV. Three-week of 200 mg daily thiamine treatment significantly lowered the baseline IL-17 levels while increased IL-22 levels (anti-inflammatory response). This was validated by an in vitro macrophage response using a lower thiamine dose equivalent (100 mg), which resulted in attenuation of IL-17 and elevation of IL-22 at the mRNA level compared to the ethanol-only treated group. In humans, a range of 79-474 mg daily of thiamine was estimated to be effective and safe as an intervention for the COVID-19 cytokine storm. A literature review showed that several neurological symptoms of COVID-19 (which exist in 45.5% of the severe cases) occur in other viral infections and neuroinflammatory states that may also respond to thiamine treatment.\n\nDiscussionThe Th17 mediated IL-17 proinflammatory response can potentially be attenuated by thiamine. Thiamine, a very safe drug even at very high doses, could be repurposed for treating the cytokine/immune storm of COVID-19 and the subsequent neurological symptoms observed in COVID-19 patients. Further studies using thiamine as an interventional/prevention strategy in severe COVID-19 patients could identify its precise anti-inflammatory role.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.24.20176792", + "rel_abs": "Phylogeny construction can help to reveal evolutionary relatedness among molecular sequences. The spike (S) gene of SARS-CoV-2 is the subject of an immune selective pressure which increases the variability in such region. This study aimed to identify mutations in the S gene among SARS-CoV-2 sequences collected in the Middle East and North Africa (MENA), focusing on the D614G mutation, that has a presumed fitness advantage. Another aim was to analyze the S gene sequences phylogenetically. The SARS-CoV-2 S gene sequences collected in the MENA were retrieved from the GISAID public database, together with its metadata. Mutation analysis was conducted in Molecular Evolutionary Genetics Analysis software. Phylogenetic analysis was done using maximum likelihood (ML) and Bayesian methods. A total of 553 MENA sequences were analyzed and the most frequent S gene mutations included: D614G = 435, Q677H = 8, and V6F = 5. A significant increase in the proportion of D614G was noticed from (63.0%) in February 2020, to (98.5%) in June 2020 (p< 0.001). Two large phylogenetic clusters were identified via ML analysis, which showed an evidence of inter-country mixing of sequences, which dated back to February 8, 2020 and March 15, 2020 (median estimates). The mean evolutionary rate for SARS-CoV-2 was about 6.5 x 10-3 substitutions/site/year based on large clusters Bayesian analyses. The D614G mutation appeared to be taking over the COVID-19 infections in the MENA. Bayesian analysis suggested that SARS-CoV-2 might have been circulating in MENA earlier than previously reported.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Vatsalya Vatsalya", - "author_inst": "University of Louisville" - }, - { - "author_name": "Fengyuan Li", - "author_inst": "University of Louisville" - }, - { - "author_name": "Jane C Frimodig", - "author_inst": "University of Louisville" - }, - { - "author_name": "Khushboo S Gala", - "author_inst": "University of Louisville" - }, - { - "author_name": "Shweta Srivastava", - "author_inst": "University of Louisville" - }, - { - "author_name": "Maiying Kong", - "author_inst": "University of Louisville" + "author_name": "Malik Sallam", + "author_inst": "University of Jordan" }, { - "author_name": "Vijay A Ramchandani", - "author_inst": "National Institute on Alcohol Abuse and Alcoholism" + "author_name": "Nidaa Ababneh", + "author_inst": "University of Jordan" }, { - "author_name": "Wenke Feng", - "author_inst": "University of Louisville" + "author_name": "Deema Dababseh", + "author_inst": "University of Jordan" }, { - "author_name": "Xiang Zhang", - "author_inst": "University of Louisville" + "author_name": "Faris Bakri", + "author_inst": "University of Jordan" }, { - "author_name": "Craig J McClain", - "author_inst": "University of Louisville" + "author_name": "Azmi Mahafzah", + "author_inst": "University of Jordan" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1240938,53 +1240656,65 @@ "category": "hematology" }, { - "rel_doi": "10.1101/2020.08.21.20177923", - "rel_title": "Prevalence and outcome of Covid-19 infection in cancer patients: a national VA study", + "rel_doi": "10.1101/2020.08.21.20178863", + "rel_title": "Next generation sequencing of SARS-CoV-2 from patient specimens of Nevada reveals occurrence of specific nucleotide variants at high frequency", "rel_date": "2020-08-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.21.20177923", - "rel_abs": "BackgroundEmerging data suggest variability in susceptibility and outcome to Covid-19 infection. Identifying the risk-factors associated with infection and outcomes in cancer patients is necessary to develop healthcare recommendations.\n\nMethodsWe analyzed electronic health records of the US National Veterans Administration healthcare system and assessed the prevalence of Covid-19 infection in cancer patients. We evaluated the proportion of cancer patients tested for Covid-19 and their confirmed positivity, with clinical characteristics, and outcome, and stratified by demographics, comorbidities, cancer treatment and cancer type.\n\nResultsOf 22914 cancer patients tested for Covid-19, 1794 (7.8%) were positive. The prevalence of Covid-19 was similar across all ages. Higher prevalence was observed in African-American (AA) (15%) compared to white (5.5%; P<.001), in Hispanic vs non-Hispanic population and in patients with hematologic malignancy compared to those with solid tumors (10.9% vs 7.7%; P<.001). Conversely, prevalence was lower in current smoker patients, patients with other co-morbidities and having recently received cancer therapy (< 6 months). The Covid-19 attributable mortality was 10.9%. Highest mortality rates were observed in older patients, those with renal dysfunction, higher Charlson co-morbidity score and with certain cancer types. Recent (< 6 months) or past treatment did not influence mortality. Importantly, AA patients had 3.5-fold higher Covid-19 attributable hospitalization, however had similar mortality rate as white patients.\n\nConclusionPre-existence of cancer affects both susceptibility to Covid-19 infection and eventual outcome. The overall Covid-19 attributable mortality in cancer patients is affected by age, co-morbidity and specific cancer types, however, race or recent treatment including immunotherapy does not impact outcome.\n\nFundingsVA Office of Research and Development and National Institutes of Health.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.21.20178863", + "rel_abs": "Patients with signs of COVID-19 were tested with CDC approved diagnostic RT-PCR for SARS-CoV-2 using RNA extracted from nasopharyngeal/nasal swabs. In order to determine the variants of SARS-CoV-2 circulating in the state of Nevada, 200 patient specimens from positively identified cases were sequenced through our robust protocol for sequencing SARS-CoV-2 genomes from the nasopharyngeal or nasal swabs. This protocol enabled the identification of specific nucleotide variants including those coding for D614G and clades defining mutations. Additionally, these sequences were used for determining the phylogenetic relationships of SARS-CoV-2 genomes of public health importance occurring in the state of Nevada. Our study reports the occurrence of a novel variant in the nsp12 (RdRp-RNA dependent RNA Polymerase) protein at residue 323 (314aa of orf1b) to Phenylalanine (F) from Proline (P), present in the original isolate of SARS-CoV-2 (Wuhan-Hu-1). This 323F variant is found at a very high frequency (46% of the tested specimen) in Northern Nevada, possibly because the virus accumulated this mutation while circulating in the community and the shelter in place orders restricted the introduction and spread of other variants into this region. Structural modeling of the RdRp with P323F variant did not show any significant difference in protein conformation, but the phenotypic effect is unknown and an area of active investigation. In conclusion, our results highlight the introduction and spread of specific SARS-CoV-2 variants at very high frequency within a distinct geographic location that is important for clinical and public health perspectives in understanding the evolution and transmission of SARS-CoV-2.\n\nIMPORTANCESARS-COV-2 genomes accumulate nucleotide mutations while passing in the human population and these mutations may confer phenotypic differences including altered immune response and anti-viral drug resistance. We developed a robust workflow to sequence SARS-CoV-2 directly from the nasal/nasopharyngeal swabs containing even a very low viral loads (>35 Ct value samples). Our protocol does not rely on amplicon based sequencing strategies nor the need of passing the virus into tissue culture thus reduces the possibility of an introduction of laboratory-adapted mutations. Sequences of SARS-CoV-2 from the patients of the state of Nevada during early months of the pandemic identified a rare mutation in the RdRp protein (P323F). This mutation occurred at a very high frequency in the variants of SARS-CoV-2 circulating Northern Nevada. Identification of such variants is important for clinical and public health perspectives in understanding transmission mediated evolution of SARS-CoV-2 variants and their implications on therapeutics and diagnostics.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Nathanael R Fillmore", - "author_inst": "VA Boston Healthcare System, Harvard Medical School, Dana-Farber Cancer Institute" + "author_name": "Paul Hartley", + "author_inst": "Nevada Genomics Center, University of Nevada, Reno" }, { - "author_name": "Jennifer La", - "author_inst": "VA Boston Healthcare System" + "author_name": "Richard L Tillett", + "author_inst": "Nevada Institute of Personalized Medicine, University of Nevada, Las Vegas" }, { - "author_name": "Raphael E Szalat", - "author_inst": "VA Boston Healthcare System, Dana-Farber Cancer Institute, Boston University School of Medicine" + "author_name": "Yanji Xu", + "author_inst": "Nevada Center for Bioinformatics, University of Nevada, Reno" }, { - "author_name": "David P Tuck", - "author_inst": "VA Boston Healthcare System, Boston University School of Medicine" + "author_name": "David P AuCoin", + "author_inst": "Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine" }, { - "author_name": "Vinh Nguyen", - "author_inst": "VA Boston Healthcare System" + "author_name": "Joel R Sevinsky", + "author_inst": "Theiagen Consulting, LLC" }, { - "author_name": "Cenk Yildirim", - "author_inst": "VA Boston Healthcare System" + "author_name": "Andrew Gorzalski", + "author_inst": "Nevada State Public Health Laboratory, University of Nevada, Reno" }, { - "author_name": "Nhan V Do", - "author_inst": "VA Boston Healthcare System, Boston University School of Medicine" + "author_name": "Mark C Pandori", + "author_inst": "Nevada State Public Health Laboratory, Pathology & Lab Medicine, University of Nevada, Reno School of Medicine" }, { - "author_name": "Mary T Brophy", - "author_inst": "VA Boston Healthcare System, Boston University School of Medicine" + "author_name": "Erin Buttery", + "author_inst": "Southern Nevada Public Health Laboratory of the Southern Nevada Health District, Las Vegas" }, { - "author_name": "Nikhil C Munshi", - "author_inst": "VA Boston Healthcare System, Harvard Medical School, Dana-Farber Cancer Institute" + "author_name": "Holly Hansen", + "author_inst": "Southern Nevada Public Health Laboratory of the Southern Nevada Health District, Las Vegas" + }, + { + "author_name": "Michael Picker", + "author_inst": "Southern Nevada Public Health Laboratory of the Southern Nevada Health District, Las Vegas" + }, + { + "author_name": "Cyprian C Rossetto", + "author_inst": "Department of Microbiology & Immunology, University of Nevada, Reno School of Medicine" + }, + { + "author_name": "Subhash C Verma", + "author_inst": "Department of Microbiology and Immunology, University of Nevada, Reno School of Medicine" } ], "version": "1", - "license": "cc0", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1242380,99 +1242110,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.20.20178970", - "rel_title": "Poor knowledge of COVID-19 and unfavourable perception of the response to the pandemic by healthcare workers at the Bafoussam Regional Hospital (West Region - Cameroon)", + "rel_doi": "10.1101/2020.08.20.20178889", + "rel_title": "Impact of Duration of Cessation of Mass BCG Vaccination Programs on Covid -19 Mortality", "rel_date": "2020-08-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.20.20178970", - "rel_abs": "BackgroundThe World Health Organization has warned against a dramatic impact of COVID-19 in sub-Saharan Africa unless adequate response strategies are implemented. Whatever the strategy, the role of health care workers is pivotal. We undertook this study to assess knowledge of COVID-19 and perception of the response to the pandemic among the staff of a regional hospital in charge of COVID-19 patients in West Cameroon.\n\nMethodsWe used a convenience non probabilistic sampling method to carry out a survey with a self-administered questionnaire from April 14, 2020 to April 29, 2020 at the Bafoussam Regional Hospital (BRH). All the staff was invited to participate. Statistical analyses were done using Microsoft Excel 2010 and Epi-lnfo version 7.1.5.2 software.\n\nResultsResponse rate was 76.1% (464/610). Mean age (SD) and average work experience (SD) were 35.0 (8.9) and 8.4 (7.4) years respectively. Sex ratio (M/F) was 101/356. Nursing and midwifery staff (56.8%) and in-patients units (49.94%) were predominant. Knowledge on origin and transmission of SARS-CoV-2 was poor but knowledge of clinical signs and the role of laboratory tests were good. 53.2% of respondents said all therapeutic regimens are only supportive and only a third of them trusted drugs recommended by health authorities. For 36.9% of respondents, herbal remedies can prevent/cure COVID-19. 70% of staffs felt they were not knowledgeable enough to handle COVID-19 cases. 85.6% of respondents thought the BRH had insufficient resources to adequately respond to COVID-19 and 55.6% were dissatisfied with its response to the pandemic (weaknesses: medicines/technologies (74.5%), service delivery (28.1%), human resource (10.9%)). 68% of staff felt insufficiently protected on duty and 76.5% reported that the pandemic significantly reduced non-COVID-19 services. 85.5% said they complied with preventive measures while in the community. For 44% of respondents Cameroonian regulations on COVID-19 corpses should be made more culture-sensitive. 51.2% of respondents were against vaccine trial in their community.\n\nConclusionKnowledge of COVID-19 was poor and perception of the response to the pandemic was unfavorable.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.20.20178889", + "rel_abs": "Back groundBCG have heterogeneous immunity to certain pathogens other than Mycobacterium tuberculosis effect. At early times during COVID-19 pandemic heterogeneous immunity towards (SARS-CoV-2), was hypothesized and statistical correlation between of BCG vaccination practices and COVID-19 mortality variances among countries was statistically proved. These studies were criticized because of low evidence of such studies and possible confounding factors. For that reason, this study was designed to look for impact of duration of cessation of BCG programs on COVID-19 mortality looking for the hypotheses by different design and looking forward to support previous studies.\n\nMethodsTotal number of studied group is 14 countries which had stopped BCG vaccination programs.\n\nThrough applying stem-leaf plot for exploring data screening behavior concerning COVID-19Mortality for obsolescence duration of cessation of mass BCG vaccination programs, as well as (nonlinear regression of compound model) for predicted shape behavior for that group.\n\nResultsSlope value shows highly significant effectiveness of obsolescence of cessation of mass BCG vaccination programs on COVID-19 mortality at P-value<0.000. Obsolescence of duration of cessation of mass BCG vaccination programs has strong negative association with COVID-19 mortality in countries which stopped BCG vaccination programs.\n\nConclusiaonThe longer the cessation duration of BCG programs, the higher the COVID-19mortality is, and vice versa.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "JOVANNY TSUALA FOUOGUE", - "author_inst": "Faculty of Medicine and pharmaceutical sciences_ university of Dschang" - }, - { - "author_name": "MICHEL NOUBOM", - "author_inst": "Faculty of Medicine and Pharmaceutical sciences _ University of Dschang" - }, - { - "author_name": "BRUNO KENFACK", - "author_inst": "Faculty of Medicine and Pharmaceutical Sciences _ University of Dschang" - }, - { - "author_name": "NORBERT TANKE DONGMO", - "author_inst": "Cameroon Society of Epidemiology" - }, - { - "author_name": "MAXIME TABEU", - "author_inst": "Bafoussam Regional Hospital" - }, - { - "author_name": "LINDA MEGOZEU", - "author_inst": "Bafoussam Regional Hospital" - }, - { - "author_name": "JEAN MARIE ALIMA", - "author_inst": "Bafoussam Regional Hospital" - }, - { - "author_name": "YANNICK FOGOUM FOGANG", - "author_inst": "Faculty of Medicine and Pharmaceutical Sciences_ University of Dschang" - }, - { - "author_name": "LANDRY CHARLES A NYAM RIM", - "author_inst": "Bafoussam Regional Hospital" - }, - { - "author_name": "FLORENT YMELE FOUELIFACK", - "author_inst": "Institut Superieur de Technologies Medicales, Yaounde" - }, - { - "author_name": "JEANNE HORTENCE FOUEDJIO", - "author_inst": "Faculty of Medicine and Biomedical Sciences, University of Yaounde 1" - }, - { - "author_name": "PAMELA LEONIE NZOGNING FOUOGUE MANEBOU", - "author_inst": "Freelance translator, Bafoussam, Cameroon" - }, - { - "author_name": "CLOTAIRE DAMIEN BIBOU ZE", - "author_inst": "Yagoua Health District, Yagoua" - }, - { - "author_name": "BRICE FOUBI KOUAM", - "author_inst": "Bafoussam Regional Hospital" - }, - { - "author_name": "LAURIANE NOMENE FOMETE", - "author_inst": "Agence Nationale de Recherche sur le Sida et les Hepatite virales - Site Cameroun," - }, - { - "author_name": "PIERRE MARIE TEBEU", - "author_inst": "Faculty of Medicine and Biomedical Sciences, University of Yaounde 1" - }, - { - "author_name": "JEAN DUPONT NGOWA KEMFANG", - "author_inst": "Faculty of Medicine and Biomedical Sciences, University of Yaounde 1" - }, - { - "author_name": "PASCAL FOUMANE", - "author_inst": "Faculty of Medicine and Biomedical Sciences, University of Yaounde 1" - }, - { - "author_name": "ZACHARIE SANDO", - "author_inst": "Faculty of Medicine and Biomedical Sciences, University of Yaounde 1" - }, - { - "author_name": "GEORGE ENOW ENOWNCHONG OROCK", - "author_inst": "Bafoussam Regional Hospital" + "author_name": "Tareef Fadhil Raham", + "author_inst": "MOH Iraq" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health systems and quality improvement" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.08.22.262733", @@ -1244018,33 +1243672,89 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.20.20176529", - "rel_title": "Preventing within household transmission of COVID-19: Is self-isolation outside the home feasible and acceptable?", + "rel_doi": "10.1101/2020.08.19.20178186", + "rel_title": "Self assessment overestimates historical COVID-19 disease relative to sensitive serological assays: cross sectional study in UK key workers", "rel_date": "2020-08-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.20.20176529", - "rel_abs": "BackgroundWithin-household transmission of COVID-19 is responsible for a significant number of infections. The risk of within-household infection is greatly increased among those from Black Asian and minority ethnic (BAME) and low income communities. Efforts to protect these communities are urgently needed. The aim of this study is to explore the acceptability of the availability of accommodation to support isolation among at risk populations.\n\nMethodsOur study used a mixed methods design structured in two phases. In phase 1, we conducted a survey study of a sample of volunteers from our existing database of 300 individuals who had provided consent to be contacted about ongoing research projects into infection control. In phase 2, we conducted semi-structured interviews with 19 participants from BAME communities and low income communities recruited through social media.\n\nResultsParticipants from the survey and interview phase of the study viewed the provision of accommodation as important and necessary. Factors influencing likely uptake of accommodation included perceived 1) vulnerability of household 2) exposure to the virus and 3) options for isolation at home. Barriers to accepting the offer of accommodation included 1) being able to isolate at home 2) wanting to be with family 3) caring responsibilities 4) concerns about mental wellbeing 5) upheaval of moving when ill and 6) concerns about infection control. Participants raised a series of issues that should be addressed before accommodation is offered. These included questions regarding who should use temporary accommodation and at what stage to effectively reduce transmission in the home, and how infection control in temporary accommodation would be managed.\n\nConclusionThis research provides evidence that the provision of accommodation to prevent within household transmission of the virus is viewed as acceptable, feasible and necessary by many people who are concerned about infection transmission in the home. We explore ways in which accommodation might be offered. In particular, vulnerable members of the household could be protected if accommodation is offered to individuals who are informed through test trace and isolate that they have been in contact with the virus.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.19.20178186", + "rel_abs": "ObjectiveTo measure the association between self-reported signs and symptoms and SARS-CoV-2 seropositivity.\n\nDesignCross-sectional study of three key worker groups.\n\nSettingSix acute NHS hospitals and two Police and Fire and Rescue sites in England.\n\nParticipantsIndividuals were recruited from three streams: (A) Police and Fire and Rescue services (n = 1147), (B) healthcare workers (n = 1546) and (C) healthcare workers with previously positive virus detection (n = 154).\n\nMain outcome measuresDetection of anti-SARS-CoV-2 antibodies in plasma.\n\nResults943 of the 2847 participants (33%) reported belief they had had COVID-19, having experienced compatible symptoms (including 152 from Stream C). Among individuals reporting COVID-19 compatible symptoms, 466 (49%) were seronegative on both Nucleoprotein (Roche) and Spike-protein (EUROIMMUN) antibody assays. However, among the 268 individuals with prior positive SARS-CoV-2 tests, of whom 96% reported symptoms with onset a median of 63 days (IQR 52 - 75 days) prior to venesection, Roche and EUROIMMUN assays had 96.6% (95% CI 93.7% - 98.2%) and 93.3% (95% CI 89.6% - 95.7%) sensitivity respectively. Symptomatic but seronegative individuals had significantly earlier symptom onset dates than the symptomatic seropositive individuals, shorter illness duration and a much lower anosmia reporting frequency.\n\nConclusionsSelf-reported belief of COVID-19 was common among our frontline worker cohort. About half of these individuals were seronegative, despite a high sensitivity of serology in this cohort, at least in individuals with previous positive PCR results. This is compatible with non-COVID-19 respiratory disease during the COVID-19 outbreak having been commonly mistaken for COVID-19 within the key worker cohort studied.\n\nWhat is already known on this topicScreening for SARS-CoV-2 antibodies is under way in some key worker groups; however, how this adds to self-reported COVID-19 illness is unclear. There are limited studies that investigate the association between self-reported belief of COVID-19 illness and seropositivity.\n\nWhat this study addsAbout one third of a large cohort of key frontline workers believed they had had COVID-19 infection. In around half of these there was no serological evidence of infection. Individuals who believed they had previous infection, but were seronegative, differed systematically from the seropositive individuals: disordered sense of taste and smell was less common, illness duration was shorter, and reported onset of illness commonly predated the main COVID-19 epidemic in the UK.\n\nAlthough some individuals with previous COVID-19 may be seronegative, among symptomatic individuals who had PCR-confirmed SARS-CoV-2 within our cohort, sensitivity of the two immunoassays used (Roche Elecsys (R) and EUROIMMUN) exceeded 90%. Together, these data indicate that many key workers may falsely believe, based on symptomatic illness experienced during 2020, that they have had COVID-19. Further research investigating the relationship between antibody detection and protection from future infection, with and without a history of COVID-19 disease, will help define the role serological testing can play in clinical practice.", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Sarah Denford", + "author_name": "Ranya Mulchandani", + "author_inst": "Public Health England" + }, + { + "author_name": "Sian Taylor-Phillips", + "author_inst": "University of Warwick" + }, + { + "author_name": "Hayley Jones", "author_inst": "University of Bristol" }, { - "author_name": "Kate S Morton", - "author_inst": "University of Southampton" + "author_name": "Tony Ades", + "author_inst": "University of Bristol" }, { - "author_name": "Jeremy Horwood", + "author_name": "Ray Borrow", + "author_inst": "Public Health England" + }, + { + "author_name": "Ezra Linley", + "author_inst": "Public Health England" + }, + { + "author_name": "Peter Kirwan", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Richard Stewart", + "author_inst": "Milton Keynes University NHS Hospital" + }, + { + "author_name": "Philippa Moore", + "author_inst": "Gloucestershire Hospitals NHS Foundation Trust" + }, + { + "author_name": "John Boyes", + "author_inst": "Gloucestershire Hospitals NHS Foundation Trust" + }, + { + "author_name": "Anil Hormis", + "author_inst": "The Rotherham NHS Foundation Trust" + }, + { + "author_name": "Neil Todd", + "author_inst": "York Teaching Hospitals NHS Foundation Trust" + }, + { + "author_name": "Antoanela Colda", + "author_inst": "Milton Keynes University NHS Hospital" + }, + { + "author_name": "Ian Reckless", + "author_inst": "Milton Keynes University NHS Hospital" + }, + { + "author_name": "Tim Brooks", + "author_inst": "Public Health England" + }, + { + "author_name": "Andre Charlett", + "author_inst": "Public Health England" + }, + { + "author_name": "Matthew Hickman", "author_inst": "University of Bristol" }, { - "author_name": "Rachel de Garang", - "author_inst": "Public Contributor" + "author_name": "Isabel Oliver", + "author_inst": "Public Health England" }, { - "author_name": "Lucy Yardley", - "author_inst": "University of Bristol, University of Southampton" + "author_name": "David Wyllie", + "author_inst": "Public Health England" } ], "version": "1", @@ -1245700,117 +1245410,89 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.18.20174623", - "rel_title": "Retrospective screening of routine respiratory samples revealed undetected community transmission and missed intervention opportunities for SARS-CoV-2 in the United Kingdom", + "rel_doi": "10.1101/2020.08.18.20159608", + "rel_title": "Severity-stratified and longitudinal analysis of VWF/ADAMTS13 imbalance, altered fibrin crosslinking and inhibition of fibrinolysis as contributors to COVID-19 coagulopathy", "rel_date": "2020-08-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.18.20174623", - "rel_abs": "In the early phases of the SARS coronavirus type 2 (SARS-CoV-2) pandemic, testing focused on individuals fitting a strict case definition involving a limited set of symptoms together with an identified epidemiological risk, such as contact with an infected individual or travel to a high-risk area. To assess whether this impaired our ability to detect and control early introductions of the virus into the UK, we PCR-tested archival specimens collected on admission to a large UK teaching hospital who retrospectively were identified as having a clinical presentation compatible with COVID-19. In addition, we screened available archival specimens submitted for respiratory virus diagnosis, and dating back to early January 2020, for the presence of SARS-CoV-2 RNA. Our data provides evidence for widespread community circulation of SARS-CoV2 in early February 2020 and into March that was undetected at the time due to restrictive case definitions informing testing policy. Genome sequence data showed that many of these early cases were infected with a distinct lineage of the virus. Sequences obtained from the first officially recorded case in Nottinghamshire - a traveller returning from Daegu, South Korea - also clustered with these early UK sequences suggesting acquisition of the virus occurred in the UK and not Daegu. Analysis of a larger sample of sequences obtained in the Nottinghamshire area revealed multiple viral introductions, mainly in late February and through March. These data highlight the importance of timely and extensive community testing to prevent future widespread transmission of the virus.", - "rel_num_authors": 25, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.18.20159608", + "rel_abs": "BackgroundEarly clinical reports have suggested that the prevalence of thrombotic complications in the pathogenesis of COVID-19 may be as high as 30% in intensive care unit (ICU)-admitted patients and could be a major factor contributing to mortality. However, mechanisms underlying COVID-19-associated thrombo-coagulopathy, and its impact on patient morbidity and mortality, are still poorly understood.\n\nMethodsWe performed a comprehensive analysis of coagulation and thromboinflammatory factors in plasma from COVID-19 patients with varying degrees of disease severity. Furthermore, we assessed the functional impact of these factors on clot formation and clot lysis.\n\nResultsAcross all COVID-19 disease severities (mild, moderate and severe) we observed a significant increase (6-fold) in the concentration of ultra-large von Willebrand factor (UL-VWF) multimers compared to healthy controls. This is likely the result of an interleukin (IL)-6 driven imbalance of VWF and the regulatory protease ADAMTS13 (a disintegrin and metalloproteinase with thrombospondin type 1 motifs, member 13). Upregulation of this key pro-coagulant pathway may also be influenced by the observed increase (~6-fold) in plasma -defensins, a consequence of increased numbers of neutrophils and neutrophil activation. Markers of endothelial, platelet and leukocyte activation were accompanied by increased plasma concentrations of Factor XIII (FXIII) and plasminogen activator inhibitor (PAI)-1. In patients with high FXIII we observed alteration of the fibrin network structure in in vitro assays of clot formation, which coupled with increased PAI-1, prolonged the time to clot lysis by the t-PA/plasmin fibrinolytic pathway by 52% across all COVID-19 patients (n=23).\n\nConclusionsWe show that an imbalance in the VWF/ADAMTS13 axis causing increased VWF reactivity may contribute to the formation of platelet-rich thrombi in the pulmonary vasculature of COVID-19 patients. Through immune and inflammatory responses, COVID-19 also alters the balance of factors involved in fibrin generation and fibrinolysis which accounts for the persistent fibrin deposition previously observed in post-mortem lung tissue.\n\nWhat is new?O_LIIn all COVID-19 patients, even mild cases, UL-VWF is present in plasma due to the alteration of VWF and ADAMTS13 concentrations, likely driven by increased IL-6 and -defensins.\nC_LIO_LIIncreased plasma FXIII alters fibrin structure and enhances incorporation of VWF into fibrin clusters.\nC_LIO_LIDefective fibrin structure, coupled with increased plasma PAI-1 and 2-antiplasmin, inhibits fibrinolysis by t-PA/plasmin.\nC_LI\n\nWhat are the clinical implications?O_LIProphylactic anticoagulation and management of thrombotic complications in COVID-19 patients are ongoing challenges requiring a better understanding of the coagulopathic mechanisms involved.\nC_LIO_LIWe have identified FXIII and VWF as potential therapeutic targets for treating fibrin formation defects in COVID-19 patients.\nC_LIO_LIWe have identified a multifaceted fibrinolytic resistance in COVID-19 patient plasma with potential implications in the treatment of secondary thrombotic events such as acute ischaemic stroke or massive pulmonary embolism.\nC_LI", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Joseph G Chappell", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Theocharis Tsoleridis", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Gemma Clark", - "author_inst": "Nottingham University Hospitals" - }, - { - "author_name": "Louise Berry", - "author_inst": "Nottingham University Hospitals" - }, - { - "author_name": "Nadine Holmes", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Christopher Moore", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Matthew Carlile", - "author_inst": "University of Nottingham" - }, - { - "author_name": "Fei Sang", - "author_inst": "University of Nottingham" + "author_name": "Kieron South", + "author_inst": "University of Manchester" }, { - "author_name": "Johnny Debebe", - "author_inst": "University of Nottingham" + "author_name": "Lucy Roberts", + "author_inst": "University of Manchester" }, { - "author_name": "Victoria Wright", - "author_inst": "University of Nottingham" + "author_name": "Lucy Victoria Morris", + "author_inst": "University of Manchester" }, { - "author_name": "William Irving", - "author_inst": "University of Nottingham" + "author_name": "Elizabeth Mann", + "author_inst": "University of Manchester" }, { - "author_name": "Brian J Thomson", - "author_inst": "Nottingham University Hospitals" + "author_name": "Madhvi Menon", + "author_inst": "University of Manchester" }, { - "author_name": "Timothy C.J. Boswell", - "author_inst": "Nottingham University Hospitals" + "author_name": "Sean Knight", + "author_inst": "University of Manchester" }, { - "author_name": "Iona Willingham", - "author_inst": "Nottingham University Hospitals" + "author_name": "Joanne E Konkel", + "author_inst": "University of Manchester" }, { - "author_name": "Amelia Joseph", - "author_inst": "Nottingham University Hospitals" + "author_name": "Andrew Ustianowsk", + "author_inst": "Regional Infectious Diseases Unit, North Manchester General Hospital" }, { - "author_name": "Wendy Smith", - "author_inst": "Nottingham University Hopsitals" + "author_name": "Nawar D Bakerly", + "author_inst": "Respiratory Department, Salford Royal NHS Foundation Trust" }, { - "author_name": "Manjinder Khakh", - "author_inst": "Nottingham University Hospitals" + "author_name": "Paul M Dark", + "author_inst": "University of Manchester" }, { - "author_name": "Vicki M. Fleming", - "author_inst": "Nottingham University Hospitals" + "author_name": "Angela Simpson", + "author_inst": "University of Manchester" }, { - "author_name": "Michelle M. Lister", - "author_inst": "Nottingham University Hospitals" + "author_name": "Timothy Felton", + "author_inst": "University of Manchester" }, { - "author_name": "Hannah C. Howson-Wells", - "author_inst": "Nottingham University Hospitals" + "author_name": "Alexander Horsley", + "author_inst": "University of Manchester" }, { - "author_name": "Edward C Holmes", - "author_inst": "University of Sydney" + "author_name": "- CIRCO", + "author_inst": "" }, { - "author_name": "Matthew W. Loose", - "author_inst": "University of Nottingham" + "author_name": "Tracy Hussell", + "author_inst": "University of Manchester" }, { - "author_name": "Jonathan K. Ball", - "author_inst": "University of Nottingham" + "author_name": "John R. Grainger", + "author_inst": "University of Manchester" }, { - "author_name": "C. Patrick McClure", - "author_inst": "University of Nottingham" + "author_name": "Craig J Smith", + "author_inst": "University of Manchester" }, { - "author_name": "- The COVID-19 Genomics UK consortium study group", - "author_inst": "" + "author_name": "Stuart M Allan", + "author_inst": "University of Manchester" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1247286,67 +1246968,75 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2020.08.17.20177022", - "rel_title": "Decontaminating N95 respirators during the Covid-19 pandemic: simple and practical approaches to increase decontamination capacity, speed, safety and ease of use.", + "rel_doi": "10.1101/2020.08.18.20171074", + "rel_title": "Bayesian Spatio-Temporal Modeling of COVID-19: Inequalities on Case-Fatality Risk", "rel_date": "2020-08-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.17.20177022", - "rel_abs": "BackgroundThe COVID-19 pandemic has caused a severe shortage of personal protective equipment (PPE), especially N95 respirators. Efficient, effective and economically feasible methods for large-scale PPE decontamination are urgently needed.\n\nAims(1) to develop protocols for effectively decontaminating PPE using vaporized hydrogen peroxide (VHP); (2) to develop novel approaches that decrease set up and take down time while also increasing decontamination capacity (3) to test decontamination efficiency for N95 respirators heavily contaminated by makeup or moisturizers.\n\nMethodsWe converted a decommissioned Biosafety Level 3 laboratory into a facility that could be used to decontaminate N95 respirators. N95 respirators were hung on metal racks, stacked in piles, placed in paper bags or covered with makeup or moisturizer. A VHP(R)VICTORYTM unit from STERIS was used to inject VHP into the facility. Biological and chemical indicators were used to validate the decontamination process.\n\nFindingsN95 respirators individually hung on metal racks were successfully decontaminated using VHP. N95 respirators were also successfully decontaminated when placed in closed paper bags or if stacked in piles of up to six. Stacking reduced the time needed to arrange N95 respirators for decontamination by approximately two-thirds while almost tripling facility capacity. Makeup and moisturizer creams did not interfere with the decontamination process.\n\nConclusionsRespirator stacking can reduce the hands-on time and increase decontamination capacity. When personalization is needed, respirators can be decontaminated in labeled paper bags. Make up or moisturizers do not appear to interfere with VHP decontamination.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.18.20171074", + "rel_abs": "The ongoing outbreak of COVID-19 challenges health systems and epidemiological responses of all countries worldwide. Although mitigation measures have been globally considered, the spatial heterogeneity of its effectiveness is evident, underscoring global health inequalities. Using Bayesian-based Markov chain Monte Carlo simulations, we evidenced that factors contributing to poverty are also risk factors for COVID-19 case-fatality, and unexpectedly, their impact on the case-fatality risk is comparable to that produced by health factors. Additionally, we confirm that both case-fatality risk and multidimensional poverty index have a heterogeneous spatial distribution, where the lastest consists of health, educational, dwelling, and employment dimensions. Spatio-temporal analysis reveals that the spatial heterogeneity in case-fatalities is associated with the percentage contribution of the health (RR 1.89 95%CI=1.43-2.48) and dwelling (RR 2.01 95%CI=1.37-2.63) dimensions to the multidimensional poverty, but also with the educational (RR 1.21 95%CI=1.03-1.49), and employment (RR 1.23 95%CI=1.02-1.47) dimensions. This spatial correlation indicates that the case-fatality risk increase by 189% and 201% in regions with a higher contribution of the health dimension (i.e., lack of health insurance and self-reporting) and dwelling dimension (i.e., lack of access to safe water, inadequate disposal of human feces, poor housing construction, and critical overcrowding), respectively. Furthermore, although a temporal decrease is evident, the relative risk of dying by COVID-19 in Colombia is still 200% higher than the established case-fatality risk based on the COVID-19 dynamics in Italy and China. These findings assist policy-makers in the spatial and temporal planning of strategies focused on mitigating the case-fatality risk in most vulnerable communities and preparing for future pandemics by progressively reducing the factors that generate health inequality.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "RICCARDO RUSSO", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Gina Polo", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Carly Levine", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Carlos Mera Acosta", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Courtney Veilleux", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Diego Soler-Tovar", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Blas Peixoto", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Juli\u00e1n Felipe Porras Villamil", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Jessica McCormick-Ell", - "author_inst": "National Institutes of Health" + "author_name": "Natalia Polanco Palencia", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Thomas Block", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Marco Penagos", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Anthony Gresko", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Juan Meza Martinez", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Guillaume Delmas", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Juan Nicol\u00e1s Bobadilla", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Poonam Chitale", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Laura Victoria Martin", + "author_inst": "Grupo de Investigaci\u00f3n en Cuidado Primario Visual y Ocular. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Alexis Frees", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Sandra Dur\u00e1n", + "author_inst": "Grupo de Investigaci\u00f3n en Cuidado Primario Visual y Ocular. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "Alejandro Ruiz", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Martha Rodriguez \u00c1lvarez", + "author_inst": "Grupo de Investigaci\u00f3n en Cuidado Primario Visual y Ocular. Universidad de La Salle. Bogot\u00e1, Colombia." }, { - "author_name": "David Alland", - "author_inst": "Rutgers, The State University of New Jersey" + "author_name": "Carlos Meza Carvajalino", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." + }, + { + "author_name": "Luis Carlos Villamil", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." + }, + { + "author_name": "Efrain Benavides Ortiz", + "author_inst": "Grupo de Investigaci\u00f3n en Epidemiolog\u00eda y SaludP\u00fablica. Universidad de La Salle. Bogot\u00e1, Colombia." } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.18.20176354", @@ -1249132,31 +1248822,223 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.08.20.258772", - "rel_title": "What if we perceive SARS-CoV-2 genomes as documents? Topic modelling using Latent Dirichlet Allocation to identify mutation signatures and classify SARS-CoV-2 genomes", - "rel_date": "2020-08-20", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.20.258772", - "rel_abs": "Topic modeling is frequently employed for discovering structures (or patterns) in a corpus of documents. Its utility in text-mining and document retrieval tasks in various fields of scientific research is rather well known. An unsupervised machine learning approach, Latent Dirichlet Allocation (LDA) has particularly been utilized for identifying latent (or hidden) topics in document collections and for deciphering the words that define one or more topics using a generative statistical model. Here we describe how SARS-CoV-2 genomic mutation profiles can be structured into a Bag of Words to enable identification of signatures (topics) and their probabilistic distribution across various genomes using LDA. Topic models were generated using ~47000 novel corona virus genomes (considered as documents), leading to identification of 16 amino acid mutation signatures and 18 nucleotide mutation signatures (equivalent to topics) in the corpus of chosen genomes through coherence optimization. The document assumption for genomes also helped in identification of contextual nucleotide mutation signatures in the form of conventional N-grams (e.g. bi-grams and tri-grams). We validated the signatures obtained using LDA driven method against the previously reported recurrent mutations and phylogenetic clades for genomes. Additionally, we report the geographical distribution of the identified mutation signatures in SARS-CoV-2 genomes on the global map. Use of the non-phylogenetic albeit classical approaches like topic modeling and other data centric pattern mining algorithms is therefore proposed for supplementing the efforts towards understanding the genomic diversity of the evolving SARS-CoV-2 genomes (and other pathogens/microbes).", - "rel_num_authors": 3, + "rel_doi": "10.1101/2020.08.16.20176065", + "rel_title": "Multi-organ Proteomic Landscape of COVID-19 Autopsies", + "rel_date": "2020-08-19", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.16.20176065", + "rel_abs": "The molecular pathology of multi-organ injuries in COVID-19 patients remains unclear, preventing effective therapeutics development. Here, we report an in-depth multi-organ proteomic landscape of COVID-19 patient autopsy samples. By integrative analysis of proteomes of seven organs, namely lung, spleen, liver, heart, kidney, thyroid and testis, we characterized 11,394 proteins, in which 5336 were perturbed in COVID-19 patients compared to controls. Our data showed that CTSL, rather than ACE2, was significantly upregulated in the lung from COVID-19 patients. Dysregulation of protein translation, glucose metabolism, fatty acid metabolism was detected in multiple organs. Our data suggested upon SARS-CoV-2 infection, hyperinflammation might be triggered which in turn induces damage of gas exchange barrier in the lung, leading to hypoxia, angiogenesis, coagulation and fibrosis in the lung, kidney, spleen, liver, heart and thyroid. Evidence for testicular injuries included reduced Leydig cells, suppressed cholesterol biosynthesis and sperm mobility. In summary, this study depicts the multi-organ proteomic landscape of COVID-19 autopsies, and uncovered dysregulated proteins and biological processes, offering novel therapeutic clues.\n\nHIGHLIGHTSO_LICharacterization of 5336 regulated proteins out of 11,394 quantified proteins in the lung, spleen, liver, kidney, heart, thyroid and testis autopsies from 19 patients died from COVID-19.\nC_LIO_LICTSL, rather than ACE2, was significantly upregulated in the lung from COVID-19 patients.\nC_LIO_LIEvidence for suppression of glucose metabolism in the spleen, liver and kidney; suppression of fatty acid metabolism in the kidney; enhanced fatty acid metabolism in the lung, spleen, liver, heart and thyroid from COVID-19 patients; enhanced protein translation initiation in the lung, liver, renal medulla and thyroid.\nC_LIO_LITentative model for multi-organ injuries in patients died from COVID-19: SARS-CoV-2 infection triggers hyperinflammatory which in turn induces damage of gas exchange barrier in the lung, leading to hypoxia, angiogenesis, coagulation and fibrosis in the lung, kidney, spleen, liver, heart, kidney and thyroid.\nC_LIO_LITesticular injuries in COVID-19 patients included reduced Leydig cells, suppressed cholesterol biosynthesis and sperm mobility.\nC_LI", + "rel_num_authors": 51, "rel_authors": [ { - "author_name": "Sunil Nagpal", - "author_inst": "BioSciences R&D, TCS Research, Tata Consultancy Services Ltd. Pune, India" + "author_name": "Xiu Nie", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China." }, { - "author_name": "Divyanshu Srivastava", - "author_inst": "BioSciences R&D, TCS Research, Tata Consultancy Services Ltd, Pune, India." + "author_name": "Liujia Qian", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" }, { - "author_name": "Sharmila S Mande", - "author_inst": "BioSciences R&D, TCS Research, Tata Consultancy Services Ltd, Pune, India." + "author_name": "Rui Sun", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Bo Huang", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Xiaochuan Dong", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Qi Xiao", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Qiushi Zhang", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Tian Lu", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Liang Yue", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Shuo Chen", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Xiang Li", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Yaoting Sun", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Lu Li", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Luang Xu", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Yan Li", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Ming Yang", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Zhangzhi Xue", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Shuang Liang", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Xuan Ding", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Chunhui Yuan", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Li Peng", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Wei Liu", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Xiao Yi", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Mengge Lyu", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Guixiang Xiao", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Xia Xu", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Weigang Ge", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Jiale He", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Jun Fan", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Junhua Wu", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Meng Luo", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Xiaona Chang", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Huaxiong Pan", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Xue Cai", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Junjie Zhou", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Jing Yu", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Huanhuan Gao", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Mingxing Xie", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Sihua Wang", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Guan Ruan", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Hao Chen", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Hua Su", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Heng Mei", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Danju Luo", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Dashi Zhao", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Fei Xu", + "author_inst": "College of Basic Medical Sciences, Dalian Medical University" + }, + { + "author_name": "Yan Li", + "author_inst": "College of Basic Medical Sciences, Shanghai Jiao Tong University" + }, + { + "author_name": "Yi Zhu", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" + }, + { + "author_name": "Jiahong Xia", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Yu Hu", + "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430022, China" + }, + { + "author_name": "Tiannan Guo", + "author_inst": "School of Life Sciences, Westlake University, Hangzhou 310024, China" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "confirmatory results", - "category": "bioinformatics" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.08.16.20167536", @@ -1250750,35 +1250632,31 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.08.16.20176073", - "rel_title": "Impacts on Surgery Resident Education at a first wave COVID-19 epicenter", + "rel_doi": "10.1101/2020.08.16.20176057", + "rel_title": "On the use of growth models for forecasting epidemic outbreaks with application to COVID-19 data", "rel_date": "2020-08-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.16.20176073", - "rel_abs": "BackgroundThis study aims to identify the effects of the COVID-19 pandemic on surgical resident training and education at Danbury Hospital.\n\nMethodsWe conducted an observational study at a Western Connecticut hospital heavily affected by the first wave of the COVID-19 pandemic to assess its effects on surgical residents, focusing on surgical education, clinical experience, and operative skills development. Objective data was available through recorded work hours, case logs, and formal didactics. In addition, we created an anonymous survey to assess resident perception of their residency experience during the pandemic.\n\nResultsThere are 22 surgical residents at our institution; all were included in the study. Resident weekly duty hours decreased by 23.9 hours with the majority of clinical time redirected to caring for COVID-19 patients. Independent studying increased by 1.6 hours (26.2%) while weekly didactics decreased by 2.1 hours (35.6%). The operative volume per resident decreased by 65.7% from 35.0 to 12.0 cases for the period of interest, with a disproportionately high effect on junior residents, who experienced a 76.2% decrease. Unsurprisingly, 70% of residents reported a negative effect of the pandemic on their surgical skills.\n\nConclusionsDuring the first wave of the COVID-19 pandemic, surgical residents usual workflows changed dramatically, as much of their time was dedicated to the critical care of patients with COVID-19. However, the consequent opportunity cost was to surgery-specific training; there was a significant decrease in operative cases and time spent in surgical didactics, along with elevated concern about overall preparedness for their intended career.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.16.20176057", + "rel_abs": "The initial phase dynamics of an epidemic without containment measures is commonly well modeled using exponential growth models. However, in the presence of containment measures, the exponential model becomes less appropriate. Under the implementation of an isolation measure for detected infectives, we propose to model epidemic dynamics by fitting a flexible growth model curve to reported positive cases and to infer the overall epidemic dynamics by introducing information on the detection/testing effort and recovery and death rates. The resulting modeling approach is close to the SIQR (Susceptible-Infectious-Quarantined-Recovered) model framework. We focused on predicting the peaks (time and size) in positive cases, actives cases and new infections. We applied the approach to data from the COVID-19 outbreak in Italy. Fits on limited data before the observed peaks illustrate the ability of the flexible growth model to approach the estimates from the whole data.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Alexander Ostapenko", - "author_inst": "Danbury Hospital" - }, - { - "author_name": "Samantha McPeck", - "author_inst": "University of Connecticut" + "author_name": "Chenangnon F. TOVISSODE", + "author_inst": "Laboratoire de Biomathematiques et d'Estimations Forestieres, University of Abomey-Calavi, Calavi, Benin" }, { - "author_name": "Shawn Liechty", - "author_inst": "Danbury Hospital" + "author_name": "Bruno E. LOKONON", + "author_inst": "Laboratoire de Biomathematiques et d'Estimations Forestieres, University of Abomey-Calavi, Calavi, Benin" }, { - "author_name": "Daniel Kleiner", - "author_inst": "Danbury Hospital" + "author_name": "Romain GLELE KAKA\u00cf", + "author_inst": "Laboratoire de Biomathematiques et d'Estimations Forestieres, University of Abomey-Calavi, Calavi, Benin" } ], "version": "1", "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "surgery" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.16.20175992", @@ -1252612,35 +1252490,55 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.08.14.20170290", - "rel_title": "Efficient Deep Network Architecture for COVID-19 Detection Using Computed Tomography Images", + "rel_doi": "10.1101/2020.08.15.20175869", + "rel_title": "Pulmonary cavitation; an under-recognized late complication of severe COVID-19 lung disease", "rel_date": "2020-08-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.14.20170290", - "rel_abs": "Globally the devastating consequence of COVID-19 or Severe Acute Respiratory Syndrome-Coronavirus (SARS-CoV-2) has posed danger on the life of living beings. Doctors and scientists throughout the world are working day and night to combat the proliferation or transmission of this deadly disease in terms of technology, finances, data repositories, protective equipment, and many other services. Rapid and efficient detection of COVID-19 reduces the rate of spreading this deadly disease and early treatment improve the recovery rate. In this paper, we proposed a new framework to exploit powerful features extracted from the autoencoder and Gray Level Co-occurence Matrix (GLCM), combined with random forest algorithm for the efficient and fast detection of COVID-19 using computed tomographic images. The models performance is evident from its 97.78% accuracy, 96.78% recall, and 98.77% specificity.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.15.20175869", + "rel_abs": "BackgroundRadiological findings of the novel coronavirus disease 2019 (COVID-19) pulmonary disease have been well documented and range from scattered ground-glass infiltrates in milder cases to confluent ground-glass change, dense consolidation, and crazy paving in the critically ill, however, lung cavitation has not been described in these patients.\n\nObjectivesTo assess the incidence of pulmonary cavitation and describe its characteristics and evolution.\n\nMethodsA retrospective review of all patients admitted to our institution with COVID-19 was undertaken and imaging reviewed to identify patients who developed pulmonary cavitation.\n\nResultsTwelve out of 689 (1.7%) patients admitted to our institution with COVID-19 developed pulmonary cavitation, comprising 3.3% (n = 12/359) of those with COVID-19 pneumonia, and 11% (n = 12/110) of those admitted to the intensive care unit. We describe the imaging characteristics of the cavitation and present the clinical, pharmacological, laboratory, and microbiological parameters for these patients. In this cohort six patients have died while another remains critically ill and unlikely to survive.\n\nConclusionCavitary lung disease in patients with severe COVID-19 disease is not uncommon, and is associated with a high level of morbidity and mortality.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Chirag Goel", - "author_inst": "Thapar Institute of Engineering and Technology" + "author_name": "Zaid Zoumot", + "author_inst": "Cleveland Clinic Abu Dhabi" }, { - "author_name": "Abhimanyu Kumar", - "author_inst": "Thapar Institute of Engineering and Technology" + "author_name": "Maria-Fernanda Bonilla", + "author_inst": "Cleveland Clinic Abu Dhabi" }, { - "author_name": "Satish Kumar Dubey", - "author_inst": "Indian Institute of Technology Delhi" + "author_name": "Ali Saeed Wahla", + "author_inst": "Cleveland Clinic Abu Dhabi" + }, + { + "author_name": "Irfan Shafiq", + "author_inst": "Cleveland Clinic Abu Dhabi" + }, + { + "author_name": "Mateen Uzbeck", + "author_inst": "Cleveland Clinic Abu Dhabi" + }, + { + "author_name": "Rania M El-Lababidi", + "author_inst": "Cleveland Clinic Abu Dhabi" }, { - "author_name": "Vishal Srivastava", - "author_inst": "Thapar Institute of Engineering and Technology" + "author_name": "Fadi Hamed", + "author_inst": "Cleveland Clinic Abu Dhabi" + }, + { + "author_name": "Mohamed Abuzakouk", + "author_inst": "Cleveland Clinic Abu Dhabi" + }, + { + "author_name": "Mahmoud El-Kaissi", + "author_inst": "Cleveland Clinic Abu Dhabi" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.08.15.20102699", @@ -1254406,73 +1254304,105 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.08.15.252395", - "rel_title": "Susceptibility of swine cells and domestic pigs to SARS-CoV-2", + "rel_doi": "10.1101/2020.08.15.252353", + "rel_title": "High titers of multiple antibody isotypes against the SARS-CoV-2 spike receptor-binding domain and nucleoprotein associate with better neutralization.", "rel_date": "2020-08-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.15.252395", - "rel_abs": "The emergence of SARS-CoV-2 has resulted in an ongoing global pandemic with significant morbidity, mortality, and economic consequences. The susceptibility of different animal species to SARS-CoV-2 is of concern due to the potential for interspecies transmission, and the requirement for pre-clinical animal models to develop effective countermeasures. In the current study, we determined the ability of SARS-CoV-2 to (i) replicate in porcine cell lines, (ii) establish infection in domestic pigs via experimental oral/intranasal/intratracheal inoculation, and (iii) transmit to co-housed naive sentinel pigs. SARS-CoV-2 was able to replicate in two different porcine cell lines with cytopathic effects. Interestingly, none of the SARS-CoV-2-inoculated pigs showed evidence of clinical signs, viral replication or SARS-CoV-2-specific antibody responses. Moreover, none of the sentinel pigs displayed markers of SARS-CoV-2 infection. These data indicate that although different porcine cell lines are permissive to SARS-CoV-2, five-week old pigs are not susceptible to infection via oral/intranasal/intratracheal challenge. Pigs are therefore unlikely to be significant carriers of SARS-CoV-2 and are not a suitable pre-clinical animal model to study SARS-CoV-2 pathogenesis or efficacy of respective vaccines or therapeutics.", - "rel_num_authors": 15, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.15.252353", + "rel_abs": "Understanding antibody responses to SARS-CoV-2 is indispensable for the development of containment measures to overcome the current COVID-19 pandemic. Here, we determine the ability of sera from 101 recovered healthcare workers to neutralize both authentic SARS-CoV-2 and SARS-CoV-2 pseudotyped virus and address their antibody titers against SARS-CoV-2 nucleoprotein and spike receptor-binding domain. Interestingly, the majority of individuals have low neutralization capacity and only 6% of the healthcare workers showed high neutralizing titers against both authentic SARS-CoV-2 virus and the pseudotyped virus. We found the antibody response to SARS-CoV-2 infection generates antigen-specific isotypes as well as a diverse combination of antibody isotypes, with high titers of IgG, IgM and IgA against both antigens correlating with neutralization capacity. Importantly, we found that neutralization correlated with antibody titers as quantified by ELISA. This suggests that an ELISA assay can be used to determine seroneutralization potential. Altogether, our work provides a snapshot of the SARS-CoV-2 neutralizing antibody response in recovered healthcare workers and provides evidence that possessing multiple antibody isotypes may play an important role in SARS-CoV-2 neutralization.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "David A Meekins", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Maria G Noval", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Igor Morozov", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Maria E Kaczmarek", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Jessie D Trujillo", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Akiko Koide", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Natasha N Gaudreault", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Bruno A Rodriguez-Rodriguez", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Dashzeveg Bold", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Ping Louie", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Bianca L Artiaga", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Takuya Tada", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Sabarish V Indran", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Takamitsu Hattori", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Taeyong Kwon", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Tatyana Panchenko", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Velmurugan Balaraman", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Larizbeth A Romero", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Daniel W Madden", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Kai Wen Teng", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Heinz Feldmann", - "author_inst": "Laboratory of Virology, Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Hamilton, MT, USA" + "author_name": "Andrew Bazley", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Jamie Henningson", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Maren de Vries", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Wenjun Ma", - "author_inst": "Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA and Department of Veterinary Pathobi" + "author_name": "Marie I Samanovic", + "author_inst": "New York University School of Medicine" }, { - "author_name": "Udeni B.R. Balasuriya", - "author_inst": "Louisiana Animal Disease Diagnostic Laboratory and Department of Pathobiological Sciences, School of Veterinary Medicine, Louisiana State University, Baton Roug" + "author_name": "Jeffrey N Weiser", + "author_inst": "NYU Langone Health" }, { - "author_name": "Juergen A Richt", - "author_inst": "Center of Excellence for Emerging and Zoonotic Animal Diseases, Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State Uni" + "author_name": "Ioannis Aifantis", + "author_inst": "New York University School of Medicine" + }, + { + "author_name": "Joan Cangiarella", + "author_inst": "New York University School of Medicine" + }, + { + "author_name": "Mark J Mulligan", + "author_inst": "New York University School of Medicine" + }, + { + "author_name": "Ludovic Desvignes", + "author_inst": "New York University School of Medicine" + }, + { + "author_name": "Meike Dittmann", + "author_inst": "New York University School of Medicine" + }, + { + "author_name": "Nathaniel R Landau", + "author_inst": "New York University School of Medicine" + }, + { + "author_name": "Maria E Aguero-Rosenfeld", + "author_inst": "New York University" + }, + { + "author_name": "Shohei Koide", + "author_inst": "New York University School of Medicine" + }, + { + "author_name": "Kenneth A Stapleford Jr.", + "author_inst": "New York University School of Medicine" } ], "version": "1", @@ -1256136,55 +1256066,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.13.249847", - "rel_title": "Open Science Saves Lives: Lessons from the COVID-19 Pandemic", + "rel_doi": "10.1101/2020.08.11.245415", + "rel_title": "Extensive Genetic Diversity and Host Range of Rodent-borne Coronaviruses", "rel_date": "2020-08-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.13.249847", - "rel_abs": "In the last decade Open Science principles have been successfully advocated for and are being slowly adopted in different research communities. In response to the COVID-19 pandemic many publishers and researchers have sped up their adoption of Open Science practices, sometimes embracing them fully and sometimes partially or in a sub-optimal manner. In this article, we express concerns about the violation of some of the Open Science principles and its potential impact on the quality of research output. We provide evidence of the misuses of these principles at different stages of the scientific process. We call for a wider adoption of Open Science practices in the hope that this work will encourage a broader endorsement of Open Science principles and serve as a reminder that science should always be a rigorous process, reliable and transparent, especially in the context of a pandemic where research findings are being translated into practice even more rapidly. We provide all data and scripts at https://osf.io/renxy/.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.11.245415", + "rel_abs": "To better understand the genetic diversity, host association and evolution of coronaviruses (CoVs) in China we analyzed a total of 696 rodents encompassing 16 different species sampled from Zhejiang and Yunnan provinces. Based on the reverse transcriptase PCR-based CoV screening CoVs of fecal samples and subsequent sequence analysis of the RdRp gene, we identified CoVs in diverse rodent species, comprising Apodemus agrarius, Apodemus latronum, Bandicota indica, Eothenomys miletus, E. eleusis, Rattus andamanesis, Rattus norvegicus, and R. tanezumi. Apodemus chevrieri was a particularly rich host, harboring 25 rodent CoVs. Genetic and phylogenetic analysis revealed the presence of three groups of CoVs carried by a range of rodents that were closely related to the Lucheng Rn rat coronavirus (LRNV), China Rattus coronavirus HKU24 (ChRCoV_HKU24) and Longquan Rl rat coronavirus (LRLV) identified previously. One newly identified A. chevrieri-associated virus closely related to LRNV lacked an NS2 gene. This virus had a similar genetic organization to AcCoV-JC34, recently discovered in the same rodent species in Yunnan, suggesting that it represents a new viral subtype. Notably, additional variants of LRNV were identified that contained putative nonstructural NS2b genes located downstream of the NS2 gene that were likely derived from the host genome. Recombination events were also identified in the ORF1a gene of Lijiang-71. In sum, these data reveal the substantial genetic diversity and genomic complexity of rodent-borne CoVs, and greatly extend our knowledge of these major wildlife virus reservoirs.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Lonni Besan\u00e7on", - "author_inst": "Faculty of Information Technology, Monash University, Melbourne, Australia" - }, - { - "author_name": "Nathan Peiffer-Smadja", - "author_inst": "Universite de Paris, IAME, INSERM, F-75018 Paris, France" - }, - { - "author_name": "Corentin Segalas", - "author_inst": "Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom" + "author_name": "Wen Wang", + "author_inst": "Department of Zoonosis, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention" }, { - "author_name": "Haiting Jiang", - "author_inst": "School of Health Policy and Management, Nanjing Medical University, No.101 Longmian Avenue, Nanjing 211166, P.R.China" + "author_name": "Xian-Dan Lin", + "author_inst": "Wenzhou Center for Disease Control and Prevention" }, { - "author_name": "Paola Masuzzo", - "author_inst": "IGDORE, Institute for Globally Distributed Open Research and Education" + "author_name": "Hai-Lin Zhang", + "author_inst": "Yunnan Institute of Endemic Diseases Control and Prevention" }, { - "author_name": "Cooper A Smout", - "author_inst": "The University of Queensland" + "author_name": "Miao-Ruo Wang", + "author_inst": "Longquan Center for Disease Control and Prevention" }, { - "author_name": "Eric Billy", - "author_inst": "Immuno-oncology researcher, Strasbourg, France" + "author_name": "Xiao-Qing Guan", + "author_inst": "National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention" }, { - "author_name": "Maxime Deforet", - "author_inst": "Sorbonne Universite, CNRS, Institut de Biologie Paris-Seine (IBPS), Laboratoire Jean Perrin (LJP), F-75005, Paris, France" + "author_name": "Edward C Holmes", + "author_inst": "University of Sydney" }, { - "author_name": "Cl\u00e9mence Leyrat", - "author_inst": "Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, United Kingdom" + "author_name": "Yong-Zhen Zhang", + "author_inst": "Shanghai Public Health Clinical Center & School of Public Health, Fudan University, Shanghai, China." } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", - "category": "scientific communication and education" + "category": "genetics" }, { "rel_doi": "10.1101/2020.08.13.248575", @@ -1257770,109 +1257692,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.11.20171843", - "rel_title": "Functional SARS-CoV-2-specific immune memory persists after mild COVID-19", + "rel_doi": "10.1101/2020.08.12.20156257", + "rel_title": "Obesity, old age and frailty are the true risk factors for COVID-19 mortality and not chronic disease or ethnicity in Croydon.", "rel_date": "2020-08-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20171843", - "rel_abs": "The recently emerged SARS-CoV-2 virus is currently causing a global pandemic and cases continue to rise. The majority of infected individuals experience mildly symptomatic coronavirus disease 2019 (COVID-19), but it is unknown whether this can induce persistent immune memory that might contribute to herd immunity. Thus, we performed a longitudinal assessment of individuals recovered from mildly symptomatic COVID-19 to determine if they develop and sustain immunological memory against the virus. We found that recovered individuals developed SARS-CoV-2-specific IgG antibody and neutralizing plasma, as well as virus-specific memory B and T cells that not only persisted, but in some cases increased numerically over three months following symptom onset. Furthermore, the SARS-CoV-2-specific memory lymphocytes exhibited characteristics associated with potent antiviral immunity: memory T cells secreted IFN-{gamma} and expanded upon antigen re-encounter, while memory B cells expressed receptors capable of neutralizing virus when expressed as antibodies. These findings demonstrate that mild COVID-19 elicits memory lymphocytes that persist and display functional hallmarks associated with antiviral protective immunity.", - "rel_num_authors": 23, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.12.20156257", + "rel_abs": "BackgroundCoronavirus-19 (COVID-19) mortality in hospitalised patients is strongly associated with old age, nursing home residence, male sex and obesity, with a more controversial association with ethnicity and chronic diseases, in particular diabetes mellitus. Further complicating the evaluation of the independent impacts of these risk factors is the failure to control for frailty in the published studies thus far.\n\nAimTo determine the true risk factors for mortality in patients confirmed to have COVID-19 in Croydon needing hospital admission and to evaluate the independence of these risk factors in this group after adjusting for body mass index (BMI) and frailty.\n\nMethodsThis observational study retrospectively reviewed hospital electronic medical records of 466 consecutive patients who were admitted to Croydon University Hospital confirmed positive by rapid PCR test from 11th March 2020 to 9th April 2020. Statistical analysis was performed by multiple unconditional and univariate logistic regression.\n\nResultsAfter multivariate analysis, male sex [OR 1.44 (CI 0.92-2.40)], age (per year) [OR 1.07 (CI 1.05-1.09)], morbid obesity (BMI > 40 kg/m2 vs reference BMI 18.5-24.9 kg/m2) [OR 14.8 (CI 5.25-41.8)], and nursing home residence (OR 3.01 (CI 1.56-5.79) were independently associated with COVID-19 mortality with no statistically significant association found with chronic diseases or ethnicity. In the non-nursing home population, after adjusting for age and sex, the odds ratio for type 2 diabetes mellitus (T2DM) as a risk factor was 1.64 (CI 1.03-2.61, p = 0.03) and was and was attenuated to 1.30 (CI 0.78-2.18)) after controlling for BMI; the association of mortality with male sex was strengthened [OR 1.66 (CI 0.96-2.87)] and that for ethnic minority patients was weakened [South Asians [from OR 1.30 (CI 0.67-2.53)) to OR 1.21 (CI 0.60-2.46)]; African Caribbeans [from OR 1.24 (CI 0.65-2.34) to OR 1.16 (CI 0.58-2.30)]. There was a borderline but potentially large protective effect (p= 0.09) in patients who were on anticoagulation drugs prior to admission [OR 0.56 (CI 0.28-1.11)].\n\nConclusionOur study found no significant effect of ethnicity and chronic diseases as independent risk factors on COVID-19 mortality in Croydon population whereas male sex, high BMI, old age and frailty were found to be independent risk factors. Routine prophylactic treatment with anticoagulant drugs in the high-risk COVID-19 population warrants further prompt investigation.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Lauren B Rodda", - "author_inst": "University of Washington" + "author_name": "Zinu Philipose", + "author_inst": "Croydon University Hospital" }, { - "author_name": "Jason Netland", - "author_inst": "University of Washington" + "author_name": "Nadia Smati", + "author_inst": "Croydon University Hospital" }, { - "author_name": "Laila Shehata", - "author_inst": "University of Washington" + "author_name": "Chun Shing Jefferson Wong", + "author_inst": "Croydon University Hospital" }, { - "author_name": "Kurt B Pruner", - "author_inst": "University of Washington" + "author_name": "Karen Aspey", + "author_inst": "Croydon University Hospital" }, { - "author_name": "Peter M Morawski", - "author_inst": "Benaroya Research Institute" - }, - { - "author_name": "Christopher Thouvenel", - "author_inst": "Seattle Children's Research Institute" - }, - { - "author_name": "Kennidy K Takehara", - "author_inst": "University of Washington" - }, - { - "author_name": "Julie Eggenberger", - "author_inst": "University of Washington" - }, - { - "author_name": "Emily A Hemann", - "author_inst": "University of Washington" - }, - { - "author_name": "Hayley R Waterman", - "author_inst": "Benaroya Research Institute" - }, - { - "author_name": "Mitchell L Fahning", - "author_inst": "Benaroya Research Institute" - }, - { - "author_name": "Yu Chen", - "author_inst": "Seattle Children's Research Institute" - }, - { - "author_name": "Jennifer Rathe", - "author_inst": "University of Washington" - }, - { - "author_name": "Caleb Stokes", - "author_inst": "University of Washington" - }, - { - "author_name": "Samuel Wrenn", - "author_inst": "University of Washington" - }, - { - "author_name": "Brooke Fiala", - "author_inst": "University of Washington" - }, - { - "author_name": "Lauren P Carter", - "author_inst": "University of Washington" - }, - { - "author_name": "Jessica A Hamerman", - "author_inst": "Benaroya Research Institute" - }, - { - "author_name": "Neil P King", - "author_inst": "University of Washington" - }, - { - "author_name": "Michael Gale", - "author_inst": "University of Washington" - }, - { - "author_name": "Daniel J Campbell", - "author_inst": "Benaroya Research Institute" - }, - { - "author_name": "David Rawlings", - "author_inst": "Seattle Children's Research Institute" - }, - { - "author_name": "Marion Pepper", - "author_inst": "University of Washington" + "author_name": "Michael Anthony Mendall", + "author_inst": "Croydon University Hospital" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1259372,35 +1259222,51 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.13.20173997", - "rel_title": "Deep Learning for Automated Recognition of Covid-19 from Chest X-ray Images", + "rel_doi": "10.1101/2020.08.11.20172551", + "rel_title": "Results and Impact of Intensive SARS-CoV-2 Testing in a High Volume, Outpatient Radiation Oncology Clinic in a Pandemic Hotspot", "rel_date": "2020-08-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.13.20173997", - "rel_abs": "BackgroundThe pandemic caused by coronavirus in recent months is having a devastating global effect, which puts the world under the most ever unprecedented emergency. Currently, since there are not effective antiviral treatments for Covid-19 yet, it is crucial to early detect and monitor the progression of the disease, thus helping to reduce mortality. While a corresponding vaccine is being developed, and different measures are being used to combat the virus, medical imaging techniques have also been investigated to assist doctors in diagnosing this disease.\n\nObjectiveThis paper presents a practical solution for the detection of Covid-19 from chest X-ray (CXR) images, exploiting cutting-edge Machine Learning techniques.\n\nMethodsWe employ EfficientNet and MixNet, two recently developed families of deep neural networks, as the main classification engine. Furthermore, we also apply different transfer learning strategies, aiming at making the training process more accurate and efficient. The proposed approach has been validated by means of two real datasets, the former consists of 13,511 training images and 1,489 testing images, the latter has 14,324 and 3,581 images for training and testing, respectively.\n\nResultsThe results are promising: by all the experimental configurations considered in the evaluation, our approach always yields an accuracy larger than 95.0%, with the maximum accuracy obtained being 96.64%.\n\nConclusionsAs a comparison with various existing studies, we can thus conclude that our performance improvement is significant.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.11.20172551", + "rel_abs": "BackgroundIn an attempt to reduce interruptions in radiation treatment, our department implemented universal SARS-CoV-2 PCR testing during the peak of the New York City COVID-19 epidemic.\n\nMethodsStarting 4/18/20, outpatients coming into the Department of Radiation Oncology for either simulation or brachytherapy were required to undergo PCR testing for SARS-CoV-2. Starting on 5/6/20, patients were offered simultaneous SARS CoV-2 IgG antibody testing.\n\nResultsBetween 4/18/20-6/25/20, 1360 patients underwent 1,401 outpatient screening visits (Table 1). Of the patients screened, 411 were screened between 4/18/20 and 5/6/20 (Phase 1) with PCR testing: 13 (3.1%) patients were PCR positive. From 5/7/20 to 6/25/20, 990 patients were scheduled for both PCR and antibody testing (Phase 2), including 41 previously screened in Phase 1. Of those with known antibody status (n=952), 5.5% were seropositive. After 5/21/20, no screened patient (n=605) tested PCR positive. In the month prior to screening (3/17/20-4/19/20), 24 of 625 patients initiating external radiation had treatment interrupted due to COVID-19 infection (3.8%) vs 7 of 600 patients (1.1%) in the month post screening (4/20/20-5/24/20) (p=0.002).\n\nO_TBL View this table:\norg.highwire.dtl.DTLVardef@1fd270aorg.highwire.dtl.DTLVardef@10e1f44org.highwire.dtl.DTLVardef@26b73corg.highwire.dtl.DTLVardef@1c7e2feorg.highwire.dtl.DTLVardef@79ad0_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1:C_FLOATNO O_TABLECAPTIONDemographic and Disease Data\n\nC_TABLECAPTION C_TBL ConclusionsState-wide mitigation efforts, coupled with intensive departmental screening, helped prevent interruptions in radiation during the COVID-19 epidemic that could have compromised treatment efficacy.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Phuong Nguyen", - "author_inst": "University of L'Aquila" + "author_name": "Sean M McBride", + "author_inst": "Memorial Sloan Kettering Cancer Center" }, { - "author_name": "Ludovico Iovino", - "author_inst": "Gran Sasso Science Institute, Italy" + "author_name": "Kimberly Bundick", + "author_inst": "Memorial Sloan Kettering Cancer Center" }, { - "author_name": "Michele Flammini", - "author_inst": "Gran Sasso Science Institute, Italy" + "author_name": "Harper Hubbeling", + "author_inst": "Memorial Sloan Kettering Cancer Center" }, { - "author_name": "Linh Tuan Linh", - "author_inst": "Duy Tan University" + "author_name": "Morgan Freret", + "author_inst": "Memorial Sloan Kettering Cancer Center" + }, + { + "author_name": "Leslie Modlin", + "author_inst": "Memorial Sloan Kettering Cancer Center" + }, + { + "author_name": "Mini Kamboj", + "author_inst": "Memorial Sloan Kettering Cancer Center" + }, + { + "author_name": "Oren Cahlon", + "author_inst": "Memorial Sloan Kettering Cancer Center" + }, + { + "author_name": "Daniel Gomez", + "author_inst": "Memorial Sloan Kettering Cancer Center" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "oncology" }, { "rel_doi": "10.1101/2020.08.13.20174417", @@ -1260898,25 +1260764,37 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.08.13.250076", - "rel_title": "In Silico Design of siRNAs Targeting Existing and Future Respiratory Viruses with VirusSi", + "rel_doi": "10.1101/2020.08.14.251496", + "rel_title": "Rational Design of SARS-CoV-2 Spike Glycoproteins To Increase Immunogenicity By T Cell Epitope Engineering", "rel_date": "2020-08-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.13.250076", - "rel_abs": "The COVID-19 pandemic has exposed global inadequacies in therapeutic options against both the COVID-19-causing SARS-CoV-2 virus and other newly emerged respiratory viruses. In this study, we present the VirusSi computational pipeline, which facilitates the rational design of siRNAs to target existing and future respiratory viruses. Mode A of VirusSi designs siRNAs against an existing virus, incorporating considerations on siRNA properties, off-target effects, viral RNA structure and viral mutations. It designs multiple siRNAs out of which the top candidate targets >99% of SARS-CoV-2 strains, and the combination of the top four siRNAs is predicted to target all SARS-CoV-2 strains. Additionally, we develop Greedy Algorithm with Redundancy (GAR) and Similarity-weighted Greedy Algorithm with Redundancy (SGAR) to support the Mode B of VirusSi, which pre-designs siRNAs against future emerging viruses based on existing viral sequences. Time-simulations using known coronavirus genomes as early as 10 years prior to the COVID-19 outbreak show that at least three SARS-CoV-2-targeting siRNAs are among the top 30 pre-designed siRNAs. Before-the-outbreak pre-design is also possible against the MERS-CoV virus and the 2009-H1N1 swine flu virus. Our data support the feasibility of pre-designing anti-viral siRNA therapeutics prior to viral outbreaks. We propose the development of a collection of pre-designed, safety-tested, and off-the-shelf siRNAs that could accelerate responses toward future viral diseases.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.14.251496", + "rel_abs": "The current COVID-19 pandemic caused by SARS-CoV-2 has resulted in millions of confirmed cases and thousands of deaths globally. Extensive efforts and progress have been made to develop effective and safe vaccines against COVID-19. A primary target of these vaccines is the SARS-CoV-2 spike (S) protein, and many studies utilized structural vaccinology techniques to either stabilize the protein or fix the receptor-binding domain at certain states. In this study, we extended an evolutionary protein design algorithm, EvoDesign, to create thousands of stable S protein variants without perturbing the surface conformation and B cell epitopes of the S protein. We then evaluated the mutated S protein candidates based on predicted MHC-II T cell promiscuous epitopes as well as the epitopes similarity to human peptides. The presented strategy aims to improve the S proteins immunogenicity and antigenicity by inducing stronger CD4 T cell response while maintaining the proteins native structure and function. The top EvoDesign S protein candidate (Design-10705) recovered 31 out of 32 MHC-II T cell promiscuous epitopes in the native S protein, in which two epitopes were present in all seven human coronaviruses. This newly designed S protein also introduced nine new MHC-II T cell promiscuous epitopes and showed high structural similarity to its native conformation. The proposed structural vaccinology method provides an avenue to rationally design the antigens structure with increased immunogenicity, which could be applied to the rational design of new COVID-19 vaccine candidates.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Dingyao Zhang", - "author_inst": "Yale University" + "author_name": "Edison Ong", + "author_inst": "University of Michigan Medical School, Ann Arbor, MI 48109, USA" }, { - "author_name": "Jun Lu", - "author_inst": "Yale University" + "author_name": "Xiaoqiang Huang", + "author_inst": "University of Michigan Medical School, Ann Arbor, MI 48109, USA" + }, + { + "author_name": "Robin Pearce", + "author_inst": "University of Michigan Medical School, Ann Arbor, MI 48109, USA" + }, + { + "author_name": "Yang Zhang", + "author_inst": "University of Michigan" + }, + { + "author_name": "Yongqun He", + "author_inst": "University of Michigan" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", "category": "bioinformatics" }, @@ -1262636,43 +1262514,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.10.20171629", - "rel_title": "Risk of fomite-mediated transmission of SARS-CoV-2 in child daycares, schools, and offices: a modeling study", + "rel_doi": "10.1101/2020.08.10.20169649", + "rel_title": "The COVID-19 Pandemic Vulnerability Index (PVI) Dashboard: monitoring county level vulnerability", "rel_date": "2020-08-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171629", - "rel_abs": "SARS-CoV-2 can persist on surfaces, suggesting that surface-based transmission might be important for this pathogen. We find that fomites may be a substantial source of risk, particularly in schools and child daycares. Combining surface cleaning and decontamination with strategies to reduce pathogen shedding on surfaces can help mitigate this risk.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20169649", + "rel_abs": "While the COVID-19 pandemic presents a global challenge, the U.S. response places substantial responsibility for both decision-making and communication on local health authorities. To better support counties and municipalities, we integrated baseline data on relevant community vulnerabilities with dynamic data on local infection rates and interventions into a Pandemic Vulnerability Index (PVI). The PVI presents a visual synthesis of county-level vulnerability indicators that can be compared in a regional, state, or nationwide context. We describe use of the PVI, supporting epidemiological modeling and machine-learning forecasts, and deployment of an interactive, web Dashboard. The Dashboard facilitates decision-making and communication among government officials, scientists, community leaders, and the public to enable more effective and coordinated action to combat the pandemic.\n\nOne Sentence SummaryThe COVID-19 Pandemic Vulnerability Index Dashboard monitors multiple data streams to communicate county-level trends and vulnerabilities and support local decision-making to combat the pandemic.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Alicia Nicole Mullis Kraay", - "author_inst": "Emory University" + "author_name": "Skylar W Marvel", + "author_inst": "North Carolina State University" }, { - "author_name": "Michael A L Hayashi", - "author_inst": "University of Michigan, Ann Arbor" + "author_name": "John S House", + "author_inst": "National Institute of Environmental Health Sciences" }, { - "author_name": "David M Berendes", - "author_inst": "Division of Foodborne, Waterborne, and Environmental Diseases, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Pr" + "author_name": "Matthew Wheeler", + "author_inst": "National Institute of Environmental Health Sciences" }, { - "author_name": "Julia S Sobolik", - "author_inst": "Emory University" + "author_name": "Kuncheng Song", + "author_inst": "North Carolina State University" }, { - "author_name": "Juan S Leon", - "author_inst": "Emory University" + "author_name": "Yihui Zhou", + "author_inst": "North Carolina State University" }, { - "author_name": "Benjamin A Lopman", - "author_inst": "Emory University" + "author_name": "Fred A Wright", + "author_inst": "North Carolina State University" + }, + { + "author_name": "Weihsueh A Chiu", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Ivan Rusyn", + "author_inst": "Texas A&M University" + }, + { + "author_name": "Alison Motsinger-Reif", + "author_inst": "National Institute of Environmental Health Sciences" + }, + { + "author_name": "David M Reif", + "author_inst": "North Carolina State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.08.09.20171280", @@ -1264206,177 +1264100,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.11.247395", - "rel_title": "Elicitation of potent neutralizing antibody responses by designed protein nanoparticle vaccines for SARS-CoV-2", + "rel_doi": "10.1101/2020.08.11.247320", + "rel_title": "Efficacy of Targeting SARS-CoV-2 by CAR-NK Cells", "rel_date": "2020-08-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.11.247395", - "rel_abs": "A safe, effective, and scalable vaccine is urgently needed to halt the ongoing SARS-CoV-2 pandemic. Here, we describe the structure-based design of self-assembling protein nanoparticle immunogens that elicit potent and protective antibody responses against SARS-CoV-2 in mice. The nanoparticle vaccines display 60 copies of the SARS-CoV-2 spike (S) glycoprotein receptor-binding domain (RBD) in a highly immunogenic array and induce neutralizing antibody titers roughly ten-fold higher than the prefusion-stabilized S ectodomain trimer despite a more than five-fold lower dose. Antibodies elicited by the nanoparticle immunogens target multiple distinct epitopes on the RBD, suggesting that they may not be easily susceptible to escape mutations, and exhibit a significantly lower binding:neutralizing ratio than convalescent human sera, which may minimize the risk of vaccine-associated enhanced respiratory disease. The high yield and stability of the protein components and assembled nanoparticles, especially compared to the SARS-CoV-2 prefusion-stabilized S trimer, suggest that manufacture of the nanoparticle vaccines will be highly scalable. These results highlight the utility of robust antigen display platforms for inducing potent neutralizing antibody responses and have launched cGMP manufacturing efforts to advance the lead RBD nanoparticle vaccine into the clinic.", - "rel_num_authors": 40, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.11.247320", + "rel_abs": "SARS-CoV-2, which causes COVID-19 disease, is one of greatest global pandemics in history. No effective treatment is currently available for severe COVID-19 disease. One strategy for implementing cell-based immunity involves the use of chimeric antigen receptor (CAR) technology. Unlike CAR T cells, which need to be developed using primary T cells derived from COVID-19 patients with lymphopenia, clinical success of CAR NK cell immunotherapy is possible through the development of allogeneic, universal, and off-the-shelf CAR-NK cells from a third party, which will significantly broaden the application and reduce costs. Here, we develop a novel approach for the generation of CAR-NK cells for targeting SARS-CoV-2. CAR-NK cells were generated using the scFv domain of CR3022 (henceforth, CR3022-CAR-NK), a broadly neutralizing antibody for SARS-CoV-1 and SARS-CoV-2. CR3022-CAR-NK cells can specifically bind to RBD of SARS-CoV-2 and pseudotyped SARS-CoV-2 S protein, and can be activated by pseudotyped SARS-CoV-2-S viral particles in vitro. Further, CR3022-CAR-NK cells can specifically kill pseudo-SARS-CoV-2 infected target cells. Thus, off-the-shelf CR3022-CAR-NK cells may have the potential to treat patients with severe COVID-19 disease.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Alexandra C Walls", - "author_inst": "University of Washington" - }, - { - "author_name": "Brooke Fiala", - "author_inst": "University of Washington" - }, - { - "author_name": "Alexandra Schaefer", - "author_inst": "University of North Carolina Chapel Hill" - }, - { - "author_name": "Samuel Wrenn", - "author_inst": "University of Washington" - }, - { - "author_name": "Minh N Pham", - "author_inst": "University of Washington" - }, - { - "author_name": "Michael Murphy", - "author_inst": "University of Washington" - }, - { - "author_name": "Longping V Tse", - "author_inst": "University of North Carolina Chapel Hill" - }, - { - "author_name": "Laila Shehata", - "author_inst": "University of Washington" - }, - { - "author_name": "Chengbo Chen", - "author_inst": "University of Washington" - }, - { - "author_name": "Mary Jane Navarro", - "author_inst": "University of Washington" - }, - { - "author_name": "Marcos C Miranda", - "author_inst": "University of Washington" - }, - { - "author_name": "Deleah Pettie", - "author_inst": "University of Washington" - }, - { - "author_name": "Rashmi Ravichandran", - "author_inst": "University of Washington" - }, - { - "author_name": "John C Kraft", - "author_inst": "University of Washington" - }, - { - "author_name": "Cassandra Ogohara", - "author_inst": "University of Washington" - }, - { - "author_name": "Anne Palser", - "author_inst": "Kymab Ltd" - }, - { - "author_name": "Sara Chalk", - "author_inst": "Kymab Ltd" - }, - { - "author_name": "E-Chiang Lee", - "author_inst": "Kymab Ltd" - }, - { - "author_name": "Elizabeth Kepl", - "author_inst": "University of Washington" - }, - { - "author_name": "Cameron M Chow", - "author_inst": "University of Washington" - }, - { - "author_name": "Claire Sydeman", - "author_inst": "University of Washington" - }, - { - "author_name": "Edgar A Hodge", - "author_inst": "University of Washington" - }, - { - "author_name": "Brieann Brown", - "author_inst": "University of Washington" - }, - { - "author_name": "Jim T Fuller", - "author_inst": "University of Washington" - }, - { - "author_name": "Kenneth Dinnon III", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Lisa Gralinski", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Sarah R Leist", - "author_inst": "University of North Carolina" - }, - { - "author_name": "Kendra L Gully", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Thomas B Lewis", - "author_inst": "University of Washington" - }, - { - "author_name": "Miklos Guttman", - "author_inst": "University of Washington" - }, - { - "author_name": "Helen Y Chu", - "author_inst": "University of Washington" - }, - { - "author_name": "Kelly K Lee", - "author_inst": "University of Washington" - }, - { - "author_name": "Deborah H Fuller", - "author_inst": "University of Washington" - }, - { - "author_name": "Ralph S. Baric", - "author_inst": "University of North Carolina at Chapel Hill" - }, - { - "author_name": "Paul Kellam", - "author_inst": "University of Washington" - }, - { - "author_name": "Lauren Carter", - "author_inst": "University of Washington" + "author_name": "Minh Tuyet Ma", + "author_inst": "Rutgers-The State University of New Jersey" }, { - "author_name": "Marion Pepper", - "author_inst": "University of Washington" - }, - { - "author_name": "Timothy P Sheahan", - "author_inst": "University of North Carolina at Chapel Hill" + "author_name": "Saiaditya Badeti", + "author_inst": "Rutgers-The State University of New Jersey" }, { - "author_name": "David Veesler", - "author_inst": "University of Washington" + "author_name": "Ke Geng", + "author_inst": "Rutgers-The State University of New Jersey" }, { - "author_name": "Neil P King", - "author_inst": "University of Washington" + "author_name": "Dongfang Liu", + "author_inst": "Rutgers-The State University of New Jersey" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", "category": "immunology" }, @@ -1266064,75 +1265814,79 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.08.07.20170449", - "rel_title": "Outcomes of COVID-19 related hospitalisation among people with HIV in the ISARIC WHO Clinical Characterisation Protocol UK Protocol: prospective observational study", + "rel_doi": "10.1101/2020.08.05.20169060", + "rel_title": "Tocilizumab in hospitalized patients with COVID-19: Clinical outcomes, inflammatory marker kinetics, safety, and a review of the literature", "rel_date": "2020-08-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.07.20170449", - "rel_abs": "Background.There is conflicting evidence about how HIV infection influences COVID-19. We compared the presentation characteristics and outcomes of people with and without HIV hospitalised with COVID-19 at 207 centres across the United Kingdom.\n\nMethods.We analysed data from people with laboratory confirmed or highly likely COVID-19 enrolled into the ISARIC CCP-UK study. The primary endpoint was day-28 mortality after presentation. We used Kaplan-Meier methods and Cox regression to describe the association with HIV status after adjustment for sex, ethnicity, age, indeterminate/probable hospital acquisition of COVID-19 (definite hospital acquisition excluded), presentation date, and presence/absence of ten comorbidities. We additionally adjusted for disease severity at presentation as defined by hypoxia/oxygen therapy.\n\nFindings.Among 47,539 patients, 115 (0{middle dot}24%) had confirmed HIV-positive status and 103/115 (89{middle dot}6%) had a record of antiretroviral therapy. At presentation, relative to the HIV-negative group, HIV-positive people were younger (median 55 versus 74 years; p<0{middle dot}001), had a higher prevalence of obesity and moderate/severe liver disease, higher lymphocyte counts and C-reactive protein, and more systemic symptoms. The cumulative incidence of day-28 mortality was 25{middle dot}2% in the HIV-positive group versus 32{middle dot}1% in the HIV-negative group (p=0{middle dot}12); however, stratification for age revealed a higher mortality among HIV-positive people aged below 60 years. The effect of HIV-positive status was confirmed in adjusted analyses (adjusted hazard ratio [HR] 1{middle dot}49, 95% confidence interval [CI] 0{middle dot}99-2{middle dot}25; p=0{middle dot}06). Following additional adjustment for disease severity at presentation, mortality was higher in HIV-positive people (adjusted HR 1{middle dot}63; 95% CI 1{middle dot}07-2{middle dot}48; p=0{middle dot}02). In the HIV-positive group, mortality was more common among those who were slightly older and among people with obesity and diabetes with complications.\n\nInterpretation.HIV-positive status may be associated with an increased risk of day-28 mortality following a COVID-19 related hospitalisation.\n\nFunding.NIHR, MRC, Wellcome Trust, Department for International Development, Bill and Melinda Gates Foundation.\n\nStudy registrationISRCTN66726260\n\nRESEARCH IN CONTEXTO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for articles in all languages containing the words \"COVID*\", \"coronavirus\", \"SARS CoV-2\" AND \"HIV\". After screening on 23rd July 2020, we found 51 articles reporting outcomes of COVID-19 in HIV-positive people. Of these, 2 were systematic reviews, 24 were single case reports or case series of under 10 participants, and 12 were larger case series or retrospective cohorts without matched controls. There were two cohort studies that matched HIV-positive people diagnosed with COVID-19 to the general population attending for HIV care in the same area, and three studies that matched HIV-positive people diagnosed with COVID-19 to HIV-negative controls. Some of the evidence from the United States and Europe to date suggests that people with HIV experience a similar disease course and outcomes of COVID-19 compared to the general population. However, many of the studies are limited by small sample size, lack of comparator group and lack of adjustment for potential confounding. In contrast, preliminary results from a cohort study of over 20,000 participants in South Africa indicate that HIV-positive status more than doubles the risk of COVID-19 related mortality. Currently, the evidence from the United Kingdom is limited to two case series comprising a total of 21 patients.\n\nAdded value of this studyThis study analysed data collected from 207 sites across the United Kingdom as part of ISARIC CCP, the largest prospective cohort of patients hospitalised with COVID-19, to evaluate the association between HIV-positive status and day-28 mortality. The study has the benefit of a relatively large number of participants with HIV (n=115, almost all receiving antiretroviral therapy) and importantly, the ability to direct compare their presenting characteristics and outcomes to those of 47,424 HIV-negative controls within the same dataset. This includes the ability to assess the influence of gender, ethnicity and age, as well as the effect of key comorbidities including chronic cardiac, pulmonary, renal and haematological disease, diabetes, obesity, chronic neurological disorder, dementia, liver disease, and malignancy. Unlike some of the other evidence to date, but in line with the data from South Africa, this study indicates that HIV-positive status may increase the risk of mortality with COVID-19 compared to the general population, with an effect that was especially evident among people with HIV aged below 60 years and was independent of gender or ethnicity. Although we detected an association between mortality among people with HIV and occurrence of obesity and diabetes with complication, the effect of HIV-positive status persisted after adjusting for comorbidities.\n\nImplications of all the available evidencePeople with HIV may be at increased risk of severe outcomes from COVID-19 compared to the general population. Ongoing data collection is needed to confirm this association. Linkage of hospital outcome data to the HIV history will be paramount to establishing the determinants of the increased risk. COVID-19 related hospitalisation should pursue systematic recording of HIV status to ensure optimal management and gathering of evidence.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.05.20169060", + "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) due to infection with SARS-CoV-2 causes substantial morbidity. Tocilizumab, an interleukin-6 receptor antagonist, might improve outcomes by mitigating inflammation.\n\nMethodsWe conducted a retrospective study of patients admitted to the University of Washington Hospital system with COVID-19 and requiring supplemental oxygen. Outcomes included clinical improvement, defined as a two-point reduction in severity on a 6-point ordinal scale or discharge, and mortality within 28 days. We used Cox proportional-hazards models with propensity score inverse probability weighting to compare outcomes in patients who did and did not receive tocilizumab.\n\nResultsWe evaluated 43 patients who received tocilizumab and 45 who did not. Patients receiving tocilizumab were younger with fewer comorbidities but higher baseline oxygen requirements. Tocilizumab treatment was associated with reduced CRP, fibrinogen, and temperature, but there were no meaningful differences in Cox models of time to clinical improvement (adjusted hazard ratio [aHR], 0.92; 95% CI, 0.38-2.22) or mortality (aHR, 0.57; 95% CI, 0.21-1.52). A numerically higher proportion of tocilizumab-treated patients had subsequent infections, transaminitis, and cytopenias.\n\nConclusionsTocilizumab did not improve outcomes in hospitalized patients with COVID-19. However, this study was not powered to detect small differences, and there remains the possibility for a survival benefit.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Anna Maria Geretti", - "author_inst": "University of Liverpool" + "author_name": "Joshua A Hill", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Alexander Stockdale", - "author_inst": "University of Liverpool" + "author_name": "Manoj P Menon", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Sophie Kelly", - "author_inst": "University of Liverpool" + "author_name": "Shireesha Dhanireddy", + "author_inst": "University of Washington" }, { - "author_name": "Muge Cevik", - "author_inst": "University of St Andrews" + "author_name": "Mark M Wurfel", + "author_inst": "University of Washington" }, { - "author_name": "Simon Collins", - "author_inst": "HIV i-Base" + "author_name": "Margaret Green", + "author_inst": "University of Washington" }, { - "author_name": "Laura Waters", - "author_inst": "Central and North West London NHS Foundation Trust, British HIV Association" + "author_name": "Rupali Jain", + "author_inst": "University of Washington" }, { - "author_name": "Giovanni Villa", - "author_inst": "University of Sussex" + "author_name": "Jeannie D Chan", + "author_inst": "University of Washington" }, { - "author_name": "Annemarie B Docherty", - "author_inst": "University of Edinburgh" + "author_name": "Joanna Huang", + "author_inst": "University of Washington" }, { - "author_name": "Ewen M Harrison", - "author_inst": "University of Edinburgh" + "author_name": "Danika Bethune", + "author_inst": "University of Washington" }, { - "author_name": "Lance Turtle", - "author_inst": "University of Liverpool" + "author_name": "Cameron Turtle", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Peter JM Openshaw", - "author_inst": "Imperial College London" + "author_name": "Christine Johnston", + "author_inst": "University of Washington" }, { - "author_name": "Kenneth Baillie", - "author_inst": "Royal Infirmary Edinburgh, University of Edinburgh" + "author_name": "Hu Xie", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Caroline Sabin", - "author_inst": "University College London" + "author_name": "Wendy M Leisenring", + "author_inst": "Fred Hutchinson Cancer Research Center" }, { - "author_name": "Malcolm Gracie Semple", - "author_inst": "University of Liverpool" + "author_name": "H. Nina Kim", + "author_inst": "University of Washington" + }, + { + "author_name": "Guang-Shing Cheng", + "author_inst": "Fred Hutchinson Cancer Research Center" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "hiv aids" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.08.09.20171249", @@ -1267742,107 +1267496,143 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.10.20171033", - "rel_title": "Post-exertion oxygen saturation as a prognostic factor for adverse outcome in patients attending the emergency department with suspected COVID-19: Observational cohort study", + "rel_doi": "10.1101/2020.08.11.244996", + "rel_title": "Pleiotropic effect of Lactoferrin in the prevention and treatment of COVID-19 infection: in vivo, in silico and in vitro preliminary evidences", "rel_date": "2020-08-11", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.10.20171033", - "rel_abs": "BackgroundMeasurement of post-exertion oxygen saturation has been proposed to assess illness severity in suspected COVID-19 infection. We aimed to determine the accuracy of post-exertional oxygen saturation for predicting adverse outcome in suspected COVID-19.\n\nMethodsWe undertook an observational cohort study across 70 emergency departments during first wave of the COVID-19 pandemic in the United Kingdom. We collected data prospectively, using a standardised assessment form, and retrospectively, using hospital records, from patients with suspected COVID-19, and reviewed hospital records at 30 days for adverse outcome (death or receiving organ support). Patients with post-exertion oxygen saturation recorded were selected for this analysis.\n\nResultsWe analysed data from 817 patients with post-exertion oxygen saturation recorded after excluding 54 in whom measurement appeared unfeasible. The c-statistic for post-exertion change in oxygen saturation was 0.589 (95% confidence interval 0.465 to 0.713), and the positive and negative likelihood ratios of a 3% or more desaturation were respectively 1.78 (1.25 to 2.53) and 0.67 (0.46 to 0.98). Multivariable analysis showed that post-exertion oxygen saturation was not a significant predictor of adverse outcome when baseline clinical assessment was taken into account (p=0.368). Secondary analysis excluding patients in whom post-exertion measurement appeared inappropriate resulted in a c-statistic of 0.699 (0.581 to 0.817), likelihood ratios of 1.98 (1.26 to 3.10) and 0.61 (0.35 to 1.07), and some evidence of additional prognostic value on multivariable analysis (p=0.019).\n\nConclusionsPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19.\n\nRegistrationISRCTN registry, ISRCTN56149622, http://www.isrctn.com/ISRCTN28342533\n\nKey messagesWhat is already known on this subject?\n\nO_LIPost exertional decrease in oxygen saturation can be used to predict prognosis in chronic lung diseases\nC_LIO_LIPost exertional desaturation has been proposed as a way of predicting adverse outcome in people with suspected COVID-19\nC_LI\n\nWhat this study adds:\n\nO_LIPost-exertion oxygen saturation provides modest prognostic information in the assessment of patients attending the emergency department with suspected COVID-19\nC_LI", - "rel_num_authors": 22, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.11.244996", + "rel_abs": "Lactoferrin, a multifunctional cationic glycoprotein, secreted by exocrine glands and neutrophils, possesses an antiviral activity extendable to SARS-CoV-2.\n\nWe performed in vitro assays proving lactoferrin antiviral activity through direct attachment to both virus and cell surface components. This activity varied according to concentration (100/500g/ml), multiplicity of infection (0.1/0.01) and cell type (Vero E6/Caco-2 cells).\n\nInterestingly, the in silico results strongly supported the hypothesis of a direct recognition between the lactoferrin and the Spike S glycoprotein, thus hindering the viral entry into the cells.\n\nHence, we conducted a clinical trial to investigate effect and tolerability of a liposomal lactoferrin formulation as a supplementary nutraceutical agent in mild-to-moderate and asymptomatic COVID-19 patients.\n\nA total of 92 mild-to-moderate (67/92) and asymptomatic (25/92) COVID-19 patients were recruited and divided in 3 groups according to the administered regimen. Thirty-two patients, 14 hospitalised and 18 in home-based insolation received oral and intranasal liposomal bovine lactoferrin (bLf), 32 hospitalised patients were treated with standard of care treatment (hydroxychloroquine, azitromicin and lopinavir/darunavir), and 28, in home-based isolation, did not take any medication. Furthermore, 32 COVID-19 negative, not-treated, healthy subjects were added as a control group for ancillary analysis.\n\nbLf-supplemented COVID-19 patients obtained an earlier and significant (p < 0,0001.) median rRT-PCR SARS-COV-2 RNA negative conversion than standard of care-treated and non-treated COVID-19 patients (14.25 vs 27.13 vs 32.61 days, respectively).\n\nIn addition, bLf-supplemented COVID-19 patients showed significant fast clinical symptoms recovery than standard of care-treated and non-treated COVID-19 patients. Moreover, in bLf-supplemented patients, a significant decrease of either serum ferritin or IL-6 levels or host iron overload, all parameters characterizing inflammatory processes, were observed. Serum D-dimers was also found significantly decreased following bLf supplement. No adverse events were reported.\n\nThese in vitro and in vivo observations led us to speculate a potential and safe supplementary role of Blf in the management of mild-to-moderate and asymptomatic COVID-19 patients.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Steve Goodacre", - "author_inst": "University of Sheffield" + "author_name": "Elena Campione", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Ben Thomas", - "author_inst": "University of Sheffield" + "author_name": "Caterina Lanna", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Ellen Lee", - "author_inst": "University of Sheffield" + "author_name": "Terenzio Cosio", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Laura Sutton", - "author_inst": "University of Sheffield" + "author_name": "Luigi Rosa", + "author_inst": "University La Sapienza" }, { - "author_name": "Katie Biggs", - "author_inst": "University of Sheffield" + "author_name": "Maria Pia Conte", + "author_inst": "University of Rome La Sapienza" }, { - "author_name": "Carl Marincowitz", - "author_inst": "University of Sheffield" + "author_name": "Federico Iacovelli", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Amanda Loban", - "author_inst": "University of Sheffield" + "author_name": "Alice Romeo", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Simon Waterhouse", - "author_inst": "University of Sheffield" + "author_name": "Mattia Falconi", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Richard Simmonds", - "author_inst": "University of Sheffield" + "author_name": "Claudia Del Vecchio", + "author_inst": "University of Padova" }, { - "author_name": "Jose Schutter", - "author_inst": "University of Sheffield" + "author_name": "Elisa Franchin", + "author_inst": "University of Padova" }, { - "author_name": "Sarah Connelly", - "author_inst": "University of Sheffield" + "author_name": "Maria Stella Lia", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Elena Sheldon", - "author_inst": "University of Sheffield" + "author_name": "Marilena Minieri", + "author_inst": "Policlinico Tor Vergata" }, { - "author_name": "Jamie Hall", - "author_inst": "University of Sheffield" + "author_name": "Carlo Chiaramonte", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Emma Young", - "author_inst": "University of Sheffield" + "author_name": "Marco Ciotti", + "author_inst": "Policlinico Tor Vergata" }, { - "author_name": "Andrew Bentley", - "author_inst": "Manchester University NHS Foundation Trust, Wythenshawe Hospital" + "author_name": "Marzia Nuccetelli", + "author_inst": "Policlinico Tor Vergata" }, { - "author_name": "Kirsty Challen", - "author_inst": "Lancashire Teaching Hospitals NHS Foundation Trust" + "author_name": "Alessandro Terrinoni", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Chris Fitzsimmons", - "author_inst": "Sheffield Children's NHS Foundation Trust" + "author_name": "Sergio Bernardini", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Tim Harris", - "author_inst": "Barts Health NHS Trust" + "author_name": "Luca Coppeda", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Fiona Lecky", - "author_inst": "University of Sheffield" + "author_name": "Andrea Magrini", + "author_inst": "University of Rome Tor Vergata" }, { - "author_name": "Andrew Lee", - "author_inst": "University of Sheffield" + "author_name": "Alessandro Miani", + "author_inst": "Department of Environmental Sciences and Policy, University of Milan, Via Celoria 2, 20133 Milan, Italy" }, { - "author_name": "Ian Maconochie", - "author_inst": "Imperial College Healthcare NHS Trust" + "author_name": "Loredana Sarmati", + "author_inst": "Infectious Disease Unit, Tor Vergata University Hospital, Rome, 00133, Italy" }, { - "author_name": "Darren Walter", - "author_inst": "Manchester University NHS Foundation Trust" + "author_name": "Prisco Piscitelli", + "author_inst": "UNESCO Chair on Health Education and Sustainable Development, University of Naples Federico II, 80131 Naples, Italy" + }, + { + "author_name": "Nicola Moricca", + "author_inst": "Villa dei Pini" + }, + { + "author_name": "Stefano Sabatini", + "author_inst": "Villa dei Pini" + }, + { + "author_name": "Andrea Di Lorenzo", + "author_inst": "Infectious Disease Unit, Tor Vergata University Hospital, Rome, 00133, Italy" + }, + { + "author_name": "Ilaria Iannuzzi", + "author_inst": "Occupational Medicine Department, University of Rome \"Tor Vergata\", Rome, 00133, Italy." + }, + { + "author_name": "Felice Rosapepe", + "author_inst": "Pineta Grande Hospital" + }, + { + "author_name": "Pier Luigi Bartoletti", + "author_inst": "Fimmg" + }, + { + "author_name": "Massimo Andreoni", + "author_inst": "University of Rome Tor Vergata" + }, + { + "author_name": "Piera Valenti", + "author_inst": "University of Rome La Sapienza" + }, + { + "author_name": "Luca Bianchi", + "author_inst": "University of Rome Tor Vergata" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.08.11.245100", @@ -1269796,35 +1269586,51 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.06.20155804", - "rel_title": "Characterization of Israeli COVID-19 Outbreak Drivers and Forecasting Using a Versatile Web App", + "rel_doi": "10.1101/2020.07.29.20164558", + "rel_title": "Clinical and intestinal histopathological findings in SARS-CoV-2/COVID-19 patients with hematochezia", "rel_date": "2020-08-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.06.20155804", - "rel_abs": "BackgroundNo versatile web app exists that allows epidemiologists and managers around the world to fully analyze the impacts of COVID-19 mitigation. The NMB-DASA web app presented here fills this gap.\n\nMethodsOur web app uses a model that explicitly identifies a contact class of individuals, symptomatic and asymptomatic classes and a parallel set of response class, subject to lower contact pathogen contact rates. The user inputs a CSV file containing incidence and mortality time series. A default set of parameters is available that can be overwritten through input or online entry, and a subset of these can be fitted to the model using an MLE algorithm. The end of model-fitting and forecasting intervals are specifiable and changes to parameters allows counterfactual and forecasted scenarios to be explored.\n\nFindingsWe illustrate the app in the context of the current COVID-19 outbreak in Israel, which can be divided into four distinct phases: an initial outbreak; a social distancing, a social relaxation, and a second wave mitigation phase. Our projections beyond the relaxation phase indicate that an 85% drop in social relaxation rates are needed just to stabilize the current incidence rate and that at least a 95% drop is needed to quell the outbreak.\n\nInterpretationOur analysis uses only incidence and mortality rates. In the hands of policy makers and health officers, we believe our web app provides an invaluable tool for evaluating the impacts of different outbreak mitigation policies and measures.\n\nFundingThis research was funded by NSF Grant 2032264.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.29.20164558", + "rel_abs": "Gastrointestinal (GI) symptoms of SARS-CoV2/COVID-19 in the form of anorexia, nausea, vomiting, abdominal pain and diarrhea are usually preceeded by respiratory manifestations and are associated with a poor prognosis. Hematochezia is an uncommon clinical presentation of COVID-19 disease and we hypothesize that older patients with significant comorbidites (obesity and cardiovascular) and prolonged hospitalization are suspectible to ischemic injury to the bowel.\n\nWe reviewed the clinical course, key laboratory data including acute phase reactants, drug/medication history in two elderly male patients admitted for COVID-19 respiratory failure. Both patients had a complicated clinical course and suffered from hematochezia and acute blood loss anemia requiring blood transfusion around day 40 of their hospitalization. Colonoscopic impressions were correlated with the histopathological findings in the colonic biopies and changes compatible with ischemia to nonspecific acute inflammation, edema and increased eosinophils in the lamina propria were noted. Both patients were on anticoagulants, multiple antibiotics and antifungal agents due to respiratory infections at the time of lower GI bleeding. Hematochezia resolved spontaneously with supportive care. Both patients eventually recovered and were discharged.\n\nElderly patients with significant comorbid conditions are uniquely at risk for ischemic injury to the bowel. Hypoxic conditions due to COVID-19 pneumonia and respiratory failure, compounded by preexisting cardiovascular complications, and/or cytokine storm orchestrated by the viral infection leading to alteration in coagulation profile and/or drug/medication injury can be difficult to distinguish in these critically ill patients. Presentation of hematochezia may further increase the mortality and morbidity of COVID-19 patients, and prompt consultation and management by gastroenterology is therefore warranted.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Wayne M. Getz", - "author_inst": "University of California, Berkeley" + "author_name": "Margaret Cho", + "author_inst": "NYU Lngone Health" }, { - "author_name": "Richard Salter", - "author_inst": "Oberlin College" + "author_name": "Weiguo Liu", + "author_inst": "NYU Langone Health" }, { - "author_name": "Ludovica Luisa Vissat", - "author_inst": "University of California, Berkeley" + "author_name": "Sophie Balzora", + "author_inst": "NYU Langone Health" }, { - "author_name": "Nir Horvitz", - "author_inst": "University of California, Berkeley" + "author_name": "Yvelisse Suarez", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Deepthi Hoskoppal", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Neil D Theise", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Wenqing Cao", + "author_inst": "NYU Langone Health" + }, + { + "author_name": "Suparna A Sarkar", + "author_inst": "NYU Langone Health" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "gastroenterology" }, { "rel_doi": "10.1101/2020.08.03.20167593", @@ -1271814,99 +1271620,135 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.06.20169722", - "rel_title": "SARS-CoV-2 infection fatality risk in a nationwide seroepidemiological study", + "rel_doi": "10.1101/2020.08.06.20169813", + "rel_title": "Outcome of Conservative Therapy in COVID-19 Patients Presenting with Gastrointestinal Bleeding", "rel_date": "2020-08-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.06.20169722", - "rel_abs": "ObjectiveTo estimate the range of the age- and sex-specific infection fatality risk (IFR) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on confirmed coronavirus disease 2019 (COVID-19) deaths and excess all-cause deaths.\n\nDesignNationwide population-based seroepidemiological study combined with two national surveillance systems.\n\nSetting and participantsNon-institutionalized Spanish population of all ages.\n\nMain outcome measuresThe range of IFR was calculated as the observed number of COVID-19 deaths and excess deaths divided by the estimated number of SARS-CoV-2 infections in the non-institutionalized Spanish population. Laboratory-confirmed COVID-19 deaths were obtained from the National Epidemiological Surveillance Network (RENAVE) and excess all-cause deaths from the Monitoring Mortality System (MoMo) up to July 15, 2020. SARS-CoV-2 infections were derived from the estimated seroprevalence by a chemiluminiscent microparticle immunoassay for IgG antibodies in 61,092 participants in the ENE-COVID nationwide serosurvey between April 27 and June 22, 2020.\n\nResultsThe overall IFR (95% confidence interval) was 0.8% (0.8% to 0.9%) for confirmed COVID-19 deaths and 1.1% (1.0% to 1.2%) for excess deaths. The IFR ranged between 1.1% (1.0% to 1.2%) and 1.4% (1.3% to 1.5%) in men and between 0.6% (0.5% to 0.6%) and 0.8% (0.7% to 0.8%) in women. The IFR increased sharply after age 50, ranging between 11.6% (8.1% to 16.5%) and 16.4% (11.4% to 23.2%) in men [≥]80 years and between 4.6% (3.4% to 6.3%) and 6.5% (4.7% to 8.8%) in women [≥]80 years.\n\nConclusionThe sharp increase in SARS-CoV-2 IFR after age 50 was more marked in men than in women. Fatality from COVID-19 is substantially greater than that reported for other common respiratory diseases such as seasonal influenza.\n\nWHAT IS ALREADY KNOWN ON THIS TOPICInfection fatality risk (IFR) for SARS-CoV-2 is a key indicator for policy decision making, but its magnitude remains under debate. Case fatality risk, which accounts for deaths among confirmed COVID-19 cases, overestimates SARS-CoV-2 fatality as it excludes a large proportion of asymptomatic and mild-symptomatic infections. Population-based seroepidemiological studies are a valuable tool to properly estimate the number of infected individuals, regardless of symptoms. Also, because ascertainment of deaths due to COVID-19 is often incomplete, the calculation of the IFR should be complemented with data on excess all-cause mortality. In addition, data on age- and sex-specific IFR are scarce, even though age and sex are well known modifiers of the clinical evolution of COVID-19.\n\nWHAT THIS STUDY ADDSUsing the ENE-COVID nationwide serosurvey and two national surveillance systems in Spain, this study provides a range of age- and sex-specific IFR estimates for SARS-CoV-2 based on laboratory-confirmed COVID-19 deaths and excess all-cause deaths. The risk of death was very low among infected individuals younger than 50 years, but it increased sharply with age, particularly among men. In the oldest age group ([≥]80 years), it was estimated that 12% to 16% of infected men and 5% to 6% of infected women died during the first epidemic wave.", - "rel_num_authors": 20, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.06.20169813", + "rel_abs": "Background/ObjectiveThere is a paucity of data on the management of gastrointestinal (GI) bleeding in patients with COVID-19 amid concerns about the risk of transmission during endoscopic procedures. We aimed to study the outcomes of conservative treatment for GI bleeding in patients with COVID-19.\n\nMethodsIn this retrospective analysis, 24 of 1342 (1.8%) patients with COVID-19, presenting with GI bleeding from 22 April to 22 July 2020, were included.\n\nResultsThe mean age of patients was 45.8{+/-}12.7 years; 17 (70.8%) were males; upper GI (UGI) bleeding: lower GI (LGI) 23:1. Twenty-two (91.6%) patients had evidence of cirrhosis-21 presented with UGI bleeding while one had bleeding from hemorrhoids. Two patients without cirrhosis were presumed to have non-variceal bleeding. The medical therapy for UGI bleeding included vasoconstrictors-somatostatin in 17 (73.9%) and terlipressin in 4 (17.4%) patients. All patients with UGI bleeding received proton pump inhibitors and antibiotics. Packed red blood cells (PRBCs), fresh frozen plasma and platelets were transfused in 14 (60.9%), 3 (13.0%) and 3 (13.0%), respectively. The median PRBCs transfused was 1 (0-3) unit(s). The initial control of UGI bleeding was achieved in all 23 patients and none required an emergency endoscopy. At 5-day follow-up, none rebled or died. Two patients later rebled, one had intermittent bleed due to gastric antral vascular ectasia, while another had rebleed 19 days after discharge. Three (12.5%) cirrhosis patients succumbed to acute hypoxemic respiratory failure during hospital stay.\n\nConclusionConservative management strategies including pharmacotherapy, restrictive transfusion strategy, and close hemodynamic monitoring can successfully manage GI bleeding in COVID-19 patients and reduce need for urgent endoscopy. The decision for proceeding with endoscopy should be taken by a multidisciplinary team after consideration of the patients condition, response to treatment, resources and the risks involved, on a case to case basis.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Roberto Pastor-Barriuso", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Shalimar", + "author_inst": "All India Institute of Medical Sciences, New Delhi, India" }, { - "author_name": "Beatriz Perez-Gomez", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Manas Vaishnav", + "author_inst": "All India Institute of Medical Sciences" }, { - "author_name": "Miguel A Hernan", - "author_inst": "Chan School of Public Health, Harvard" + "author_name": "Anshuman Elhence", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Mayte Perez-Olmeda", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Ramesh Kumar", + "author_inst": "All India Institute of Medical Sciences, Patna" }, { - "author_name": "Raquel Yotti", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Srikant Mohta", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Jesus Oteo", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Chandan Palle", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Jose Luis Sanmartin", - "author_inst": "Ministerio de Sanidad" + "author_name": "Peeyush Kumar", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Inmaculada Leon-Gomez", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Mukesh Ranjan", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Aurora Fernandez-Garcia", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Tanmay Vajpai", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Pablo Fernandez-Navarro", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Shubham Prasad", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Israel Cruz", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Jatin Yegurla", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Mariano Martin", - "author_inst": "Ministerio de Sanidad" + "author_name": "Anugrah Dhooria", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Concepcion Delgado-Sanz", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Vikas Banyal", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Nerea Fernandez de Larrea", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Samagra Agarwal", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Jose Leon Paniagua", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Rajat Bansal", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Juan Fernando Munoz-Montalvo", - "author_inst": "Ministerio de Sanidad" + "author_name": "Sulagna Bhattacharjee", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Faustino Blanco", - "author_inst": "Ministerio de Sanidad" + "author_name": "Richa Aggarwal", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Amparo Larrauri", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Kapil D Soni", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Marina Pollan", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Swetha Rudravaram", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Marina Pollan", - "author_inst": "Instituto de Salud Carlos III" + "author_name": "Ashutosh K Singh", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Irfan Altaf", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Avinash Choudekar", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Soumya J Mahapatra", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Deepak Gunjan", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Saurabh Kedia", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Govind Makharia", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Anjan Trikha", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Pramod Garg", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Anoop Saraya", + "author_inst": "All India Institute of Medical Sciences, New Delhi" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "gastroenterology" }, { "rel_doi": "10.1101/2020.08.06.20169565", @@ -1273412,81 +1273254,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.08.05.20168948", - "rel_title": "Development of mass spectrometry-based targeted assay for direct detection of novel SARS-CoV-2 coronavirus from clinical specimens", + "rel_doi": "10.1101/2020.08.05.20168146", + "rel_title": "Clinical Mortality Review in a Large COVID-19 Cohort", "rel_date": "2020-08-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.05.20168948", - "rel_abs": "The COVID-19 pandemic caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has overwhelmed health systems worldwide and highlighted limitations of diagnostic testing. Several types of diagnostics including RT-PCR-based assays, antigen detection by lateral flow assays and antibody-based assays have been developed and deployed in a short time. However, many of these assays are lacking in sensitivity and/or specificity. Here, we describe an immunoaffinity purification followed by high resolution mass spectrometry-based targeted assay capable of detecting viral antigen in nasopharyngeal swab samples of SARS-CoV-2 infected individuals. Based on our discovery experiments using purified virus, recombinant viral protein and nasopharyngeal swab samples from COVID-19 positive patients, nucleocapsid protein was selected as a target antigen. We then developed an automated antibody capture-based workflow coupled to targeted high-field asymmetric ion mobility spectrometry (FAIMS) - parallel reaction monitoring (PRM) assays on an Orbitrap Exploris 480 mass spectrometer. An ensemble machine learning-based model for determining COVID-19 positive samples was created using fragment ion intensities in the PRM data. This resulted in 97.8% sensitivity and 100% specificity with RT-PCR-based molecular testing as the gold standard. Our results demonstrate that direct detection of infectious agents from clinical samples by mass spectrometry-based assays have potential to be deployed as diagnostic assays in clinical laboratories.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.05.20168146", + "rel_abs": "BackgroundNorthwell Health (Northwell), an integrated health system in New York, treated more than 15000 inpatients with coronavirus disease (COVID-19) at the US epicenter of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic. We describe the demographic characteristics of COVID-19 mortalities, observation of frequent rapid response teams (RRT)/cardiac arrest (CA) calls for non-intensive care unit (ICU) patients, and factors that contributed to RRT/CA calls.\n\nMethodsA team of registered nurses reviewed medical records of inpatients who tested positive for SARS-CoV-2 via polymerase chain reaction (PCR) before or on admission and died between March 13 (first Northwell inpatient expiration) and April 30, 2020 at 15 Northwell hospitals. Findings for these patients were abstracted into a database and statistically analyzed.\n\nFindingsOf 2634 COVID-19 mortalities, 56.1% had oxygen saturation levels greater than or equal to 90% on presentation and required no respiratory support. At least one RRT/CA was called on 42.2% of patients at a non-ICU level of care. Before the RRT/CA call, the most recent oxygen saturation levels for 76.6% of non-ICU patients were at least 90%. At the time RRT/CA was called, 43.1% had an oxygen saturation less than 80%.\n\nInterpretationThis study represents one of the largest cohorts of reviewed mortalities that also captures data in non-structured fields. Approximately 50% of deaths occurred at a non-ICU level of care, despite admission to the appropriate care setting with normal staffing. The data imply a sudden, unexpected deterioration in respiratory status requiring RRT/CA in a large number of non-ICU patients. Patients admitted to a non-ICU level of care suffer rapid clinical deterioration, often with a sudden decrease in oxygen saturation. These patients could benefit from additional monitoring (eg, continuous central oxygenation saturation), although this approach warrants further study.\n\nFundingNational Institute on Aging and the National Library of Medicine of the National Institutes of Health.\n\nRESEARCH IN CONTEXTO_ST_ABSEvidence before the studyC_ST_ABSThe world first learned of SARS-CoV-2 through a landmark study published by the Lancet in January 2020. Early evidence was limited due to the novel nature of the virus, clinician inexperience in treating COVID-19, small sample size of primarily hospital inpatients in early observational studies, use of structured datasets for data collection, and early and evolving treatment guidelines. We collected evidence from leading medical journals from January 2020 through June 2020 that primarily describe the clinical characteristics of COVID-19 (eg, patient age, sex, and comorbidities) as well as the different approaches to treatment that were being used. Our search consisted of real-time publications as they became available. Analyzing the characteristics of patients who died can help to define the clinical nature of COVID-19 and potentially suggest new care protocols.\n\nAdded value of this studyUnlike prior research, our study represents one of the largest cohorts of COVID-19 mortalities abstracted from both structured and unstructured fields in the medical record using data collected during the surge of infections in the New York metropolitan area in March through April 2020. Our study identified an unusual pattern of respiratory decompensation in patients who presented to the hospital with acceptable oxygen saturation levels and were therefore admitted to a non-ICU setting for care. Through our unique analysis, we identified a cohort of patients who experienced a rapid response team/cardiac arrest call after a sudden and unexpected decrease in their oxygenation saturation levels.\n\nImplications of available evidenceOur findings, based on over 2600 inpatient mortalities, suggest that there is a subpopulation of patients who are admitted to a non-ICU setting where continuous oxygenation saturation monitoring is not a standard, but may be warranted. Further research is needed to understand which patients are at highest risk for mortality, due to age and comorbidities, and the implications of continuous monitoring on mortality rates. This finding is relevant to a wide audience of national and international health care providers.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Santosh Renuse", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Patrick M Vanderboom", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Anthony D. Maus", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Jennifer V. Kemp", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Kari M. Gurtner", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Anil K. Madugundu", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Sandip Chavan", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Jane A. Peterson", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Benjamin J. Madden", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Kiran K. Mangalaparthi", - "author_inst": "Mayo Clinic" + "author_name": "Mark P Jarrett", + "author_inst": "Donald and Barbara Zucker School at Hofstra/Northwell" }, { - "author_name": "Dong-Gi Mun", - "author_inst": "Mayo Clinic" - }, - { - "author_name": "Smrita Singh", - "author_inst": "Mayo Clinic" + "author_name": "Susanne F Schultz", + "author_inst": "Northwell Health" }, { - "author_name": "Benjamin R. Kipp", - "author_inst": "Mayo Clinic" + "author_name": "Julie S Lyall", + "author_inst": "Northwell Health" }, { - "author_name": "Surendra Dasari", - "author_inst": "Mayo Clinic" + "author_name": "Jason J Wang", + "author_inst": "Donald and Barbara Zucker School at Hofstra/Northwell" }, { - "author_name": "Ravinder J. Singh", - "author_inst": "Mayo Clinic" + "author_name": "Lori Stier", + "author_inst": "Northwell Health" }, { - "author_name": "Stefan K. Grebe", - "author_inst": "Mayo Clinic" + "author_name": "Marcella De Geronimo", + "author_inst": "NorthwellHealth" }, { - "author_name": "Akhilesh Pandey", - "author_inst": "Mayo Clinic" + "author_name": "Karen L Nelson", + "author_inst": "Donald and Barbara Zucker School at Hofstra/Northwell" } ], "version": "1", @@ -1275402,31 +1275204,139 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2020.08.05.237404", - "rel_title": "Analysis of single nucleotide polymorphisms between 2019-nCoV genomes and its impact on codon usage", + "rel_doi": "10.1101/2020.08.04.20168112", + "rel_title": "Seroprevalence of COVID-19 in Niger State", "rel_date": "2020-08-05", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.05.237404", - "rel_abs": "The spread of COVID-19 is a global concern that has taken a toll on entire human health. Researchers across the globe has been working in devising the strategies to combat this dreadful disease. Studies focused on genetic variability helps design effective drugs and vaccines. Considering this, the present study entails the information regarding the genome-wide mutations detected in the 108 SARS CoV-2 genomes worldwide. We identified a few hypervariable regions localized in orf1ab, spike, and nucleocapsid gene. These nucleotide polymorphisms demonstrated their effect on both codon usage as well as amino acid usage pattern. Altogether the present study provides valuable information that would be helpful to ongoing research on 2019-nCoV vaccine development.", - "rel_num_authors": 3, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.04.20168112", + "rel_abs": "BackgroundCoronavirus Disease 2019 (COVID-19) Pandemic caused by SARS-CoV-2 is ongoing causing human and socioeconomic losses.\n\nObjectiveTo know how far the virus has spread in Niger State, Nigeria, a pilot study was carried out to determine the SARS-CoV-2 seroprevalence, patterns, dynamics, and risk factors in the state.\n\nMethodsA cross sectional study design and Clustered-Stratified-Random sampling strategy were used to select 185 test participants across the state. SARS-CoV-2 IgG and IgM Rapid Test Kits (Colloidal gold immunochromatography lateral flow system) were used to determine the presence or absence of the antibodies to the virus in the blood of sampled participants across Niger State as from 26th June 2020 to 30th June 2020. The test kits were validated using the blood samples of some of the Nigeria Center for Disease Control (NCDC) confirmed positive and negative COVID-19 cases in the State. SARS-CoV-2 IgG and IgM Test results were entered into the EPIINFO questionnaire administered simultaneously with each test. EPIINFO was then used for to calculate arithmetic mean and percentage, odd ratio, chi-square, and regression at 95% Confidence Interval of the data generated.\n\nResultsThe seroprevalence of SARS-CoV-2 in Niger State was found to be 25.41% and 2.16% for the positive IgG and IgM respectively. Seroprevalence among age groups, gender and by occupation varied widely. COVID-19 asymptomatic rate in the state was found to be 46.81%. The risk analyses showed that the chances of infection are almost the same for both urban and rural dwellers in the state. However, health care workers, those that experienced flu-like symptoms and those that have had contact with person (s) that travelled out of Nigeria in the last six (6) months (February -June 2020) are twice (2 times) at risk of being infected with the virus. More than half (54.59%) of the participants in this study did not practice social distancing at any time since the pandemic started. Discussions about knowledge, practice and attitude of the participants are included.\n\nConclusionThe observed Niger State SARS-CoV-2 seroprevalence and infection patterns means that the virus is widely spread, far more SARS CoV-2 infections occurred than the reported cases and high asymptomatic COVID-19 across the state.", + "rel_num_authors": 30, "rel_authors": [ { - "author_name": "Suruchi Gupta", - "author_inst": "CSIR- Indian Institute of Integrative Medicine" + "author_name": "Hussaini Majiya", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Mohammed Aliyu-Paiko", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Vincent Tochukwu Balogu", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Dickson Achimugu Musa", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Ibrahim Maikudi Salihu", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Abdullahi Abubakar Kawu", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Ishaq Yakubu Bashir", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Aishat Rabiu Sani", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "John Baba", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Amina Tako Muhammad", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Fatima Ladidi Jibril", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Ezekiel Bala", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Nuhu George Obaje", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Yahaya Badeggi Aliyu", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Ramatu Gogo Muhammad", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Hadiza Mohammed", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Usman Naji Gimba", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Abduljaleel Uthman", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Hadiza Muhammad Liman", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Sule Alfa Alhaji", + "author_inst": "General Hospital, Minna, Nigeria" + }, + { + "author_name": "Joseph Kolo James", + "author_inst": "Niger State Ministry of Health, Minna, Nigeria" + }, + { + "author_name": "Muhammad Muhammad Makusidi", + "author_inst": "Niger State Ministry of Health, Minna, Nigeria" + }, + { + "author_name": "Mohammed Danasabe Isah", + "author_inst": "General Hospital, Minna, Nigeria" + }, + { + "author_name": "Ibrahim Abdullahi", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Umar Ndagi", + "author_inst": "IBB Specialised Hospital, Minna, Nigeria" + }, + { + "author_name": "Bala Waziri", + "author_inst": "IBB Specialised Hospital, Minna, Nigeria" + }, + { + "author_name": "Chindo Ibrahim Bisallah", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" + }, + { + "author_name": "Naomi John Dadi-Mamud", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" }, { - "author_name": "Ravail Singh", - "author_inst": "CSIR- Indian Institute of Integrative Medicine" + "author_name": "Kolo Ibrahim", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" }, { - "author_name": "Prosenjit Paul", - "author_inst": "Negenome Bio Solutions" + "author_name": "Abu Kasim Adamu", + "author_inst": "Ibrahim Badamasi Babangida University, Lapai, Nigeria" } ], "version": "1", - "license": "cc_no", - "type": "confirmatory results", - "category": "genomics" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.08.04.20167643", @@ -1277548,47 +1277458,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.31.20165480", - "rel_title": "Clinical course and severity outcome indicators among COVID 19 hospitalized patients in relation to comorbidities distribution Mexican cohort", + "rel_doi": "10.1101/2020.07.31.20166264", + "rel_title": "Risk stratification as a tool to rationalize quarantine among health care workers exposed to COVID-19 cases - Evidence from a tertiary healthcare centre in India", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20165480", - "rel_abs": "IntroductionCOVID-19 affected worldwide, causing to date, around 500,000 deaths. In Mexico, by April 29, the general case fatality was 6.52%, with 11.1% confirmed case mortality and hospital recovery rate around 72%. Once hospitalized, the odds for recovery and hospital death rates depend mainly on the patients comorbidities and age. In Mexico, triage guidelines use algorithms and risk estimation tools for severity assessment and decision-making. The studys objective is to analyze the underlying conditions of patients hospitalized for COVID-19 in Mexico concerning four severity outcomes.\n\nMaterials and MethodsRetrospective cohort based on registries of all laboratory-confirmed patients with the COVID-19 infection that required hospitalization in Mexico. Independent variables were comorbidities and clinical manifestations.\n\nDependent variables were four possible severity outcomes(a) pneumonia, (b) mechanical ventilation (c) intensive care unit, and (d) death; all of them were coded as binary Results: We included 69,334 hospitalizations of laboratory-confirmed and hospitalized patients to June 30, 2020. Patients were 55.29 years, and 62.61% were male. Hospital mortality among patients aged<15 was 9.11%, 51.99% of those aged >65 died. Male gender and increasing age predicted every severity outcome. Diabetes and hypertension predicted every severity outcome significantly. Obesity did not predict mortality, but CKD, respiratory diseases, cardiopathies were significant predictors.\n\nConclusionObesity increased the risk for pneumonia, mechanical ventilation, and intensive care admittance, but it was not a predictor of in-hospital death. Patients with respiratory diseases were less prone to develop pneumonia, to receive mechanical ventilation and intensive care unit assistance, but they were at higher risk of in-hospital death.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20166264", + "rel_abs": "BackgroundQuarantine of healthcare workers (HCWs) exposed to COVID -19 confirmed cases is a well-known strategy for limiting the transmission of infection. However, there is need of evidence-based guidelines for quarantine of HCWs in COVID -19.\n\nMethodsWe describe our experience of contact tracing and risk stratification of 3853 HCWs who were exposed to confirmed COVID-19 cases in a tertiary health care institution in India. We developed an algorithm, on the basis of risk stratification, to rationalize quarantine among HCWs. Risk stratification was based on the duration of exposure, distance from the patient, and appropriateness of personal protection equipment (PPE) usage. Only high-risk contacts were quarantined for 14 days. They underwent testing for COVID-19 after five days of exposure, while low-risk contacts continued their work with adherence to physical distancing, hand hygiene, and appropriate use of PPE. The low-risk contacts were encouraged to monitor for symptoms and report for COVID-19 screening if fever, cough, or shortness of breath occurred. We followed up all contacts for 14 days from the last exposure and observed for symptoms of COVID-19 and test positivity.\n\nResults and interpretationOut of total 3853 contacts, 560 (14.5%) were categorized as high-risk contacts, and 40 of them were detected positive for COVID-19, with a test positivity rate of 7.1% (95% CI = 5.2 - 9.6). Overall, 118 (3.1%) of all contacts tested positive. Our strategy prevented 3215 HCWs from being quarantined and saved 45,010 person-days of health workforce until June 8, 2020, in the institution.\n\nWe conclude that exposure-based risk stratification and quarantine of HCWs is a viable strategy to prevent unnecessary quarantine, in a healthcare institution.\n\nSummaryO_ST_ABSWhat is already known about this subject?C_ST_ABSO_LIQuarantine of HCWs is a well-known strategy for community and HCWs to prevent the transmission of COVID-19.\nC_LIO_LIThough success stories of prompt contact tracing and quarantine to control COVID-19 are available from countries like South Korea, Singapore, and Hong Kong, there is a scarcity of evidence that could guide targeted quarantine of HCWs exposed to COVID -19 in India.\nC_LI\n\nWhat does this study add?O_LIOnly 14.5% HCWs exposed to COVID-19 cases were stratified \"high risk\" contacts, and the most common reason for high-risk contacts was non-formal workplace interactions such as having meals together.\nC_LIO_LIThe overall test positivity rate among the high-risk contacts was 7.1%, while it was higher in symptomatic high-risk contacts as compared to those who were asymptomatic (10.2% vs. 6.3%).\nC_LI\n\nHow might this impact on clinical practice?O_LIContact tracing and risk stratification can be used to minimize unnecessary quarantine of COVID-19 exposed health care workers and prevent the depletion of healthcare workers amidst the pandemic to continue the healthcare services optimally.\nC_LI", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Genny Carrillo", - "author_inst": "Texas A&M University" + "author_name": "Ravneet Kaur", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Shashi Kant", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Mohan Bairwa", + "author_inst": "AIIMS, New Delhi" + }, + { + "author_name": "Arvind Kumar", + "author_inst": "All India Institute of Medical Sciences, New Delhi" + }, + { + "author_name": "Shivram Dhakad", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Nina Mendez Dominguez", - "author_inst": "Universidad Marista, School of Medicina, Merida, Yucatan, Mexico" + "author_name": "Vignesh Dwarakanathan", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Kassandra D Santos Zaldivar", - "author_inst": "Universidad Marista de Merida, Yucatan, Mexico" + "author_name": "Aftab Ahmad", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Andrea Rochel Perez", - "author_inst": "Universidad Marista de Merida, Yucatan, Mexico" + "author_name": "Pooja Pandey", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Mario Azuela Morales", - "author_inst": "Universidad Marista de Merida, Yucatan, Mexico" + "author_name": "Arti Kapil", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Osman Cuevas Koh", - "author_inst": "Universidad Marista de Merida, Yucatan,Mexico" + "author_name": "Rakesh Lodha", + "author_inst": "All India Institute of Medical Sciences, New Delhi" }, { - "author_name": "Alberto Alvarez Baeza", - "author_inst": "Universidad Marista de Merida, Yucatan, Mexico" + "author_name": "Naveet Wig", + "author_inst": "All India Institute of Medical Sciences, New Delhi" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.07.31.20165654", @@ -1278962,45 +1278888,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.03.20167189", - "rel_title": "Evaluating Data-Driven Forecasting Methods for Predicting SARS-CoV2 Cases: Evidence From 173 Countries", + "rel_doi": "10.1101/2020.08.03.20167197", + "rel_title": "Spreading of COVID-19 in Italy as the spreading of a wave packet", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.03.20167189", - "rel_abs": "The WHO announced the epidemic of SARS-CoV2 as a public health emergency of international concern on 30th January 2020. To date, it has spread to more than 200 countries, and has been declared as a global pandemic. For appropriate preparedness, containment, and mitigation response, the stakeholders and policymakers require prior guidance on the propagation of SARS-CoV2. This study aims to provide such guidance by forecasting the cumulative COVID-19 cases up to 4 weeks ahead for 173 countries, using four data-driven methodologies; autoregressive integrated moving average (ARIMA), exponential smoothing model (ETS), random walk forecasts (RWF) with and without drift. We also evaluate the accuracy of these forecasts using the Mean Absolute Percentage Error (MAPE). The results show that the ARIMA and ETS methods outperform the other two forecasting methods. Additionally, using these forecasts, we generated heat maps to provide a pictorial representation of the countries at risk of having an increase in cases in the coming 4 weeks for June. Due to limited data availability during the ongoing pandemic, less data-hungry forecasting models like ARIMA and ETS can help in anticipating the future burden of SARS-CoV2 on healthcare systems.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.03.20167197", + "rel_abs": "We find that the spreading of the COVID-19 pandemic in Italy can be described as the propagation of a wave packet in a dispersive medium where the effect of Lockdown is simulated by the dispersion relation of the medium. We start expanding a previous statistical analysis based on the official data provided by the Italian civil protection during 100 days, from March 2nd to June 9th. As the total number of people infected with the virus is uncertain, we have considered the trend of ICU patients and the sum of hospitalized patients and the deceased. Both the corresponding curves are well approximated by the same function depending on four free parameters. The model allows to predict the short term behavior of the pandemic and to estimate the benefits due to lockdown measures.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Ghufran Ahmad", - "author_inst": "National University of Sciences and Technology (NUST), Islamabad, Pakistan" - }, - { - "author_name": "Furqan Ahmed", - "author_inst": "Leibniz Institute for Prevention Research and Epidemiology, Bremen, Germany" - }, - { - "author_name": "Muhammad Suhail Rizwan", - "author_inst": "National University of Sciences and Technology (NUST), Islamabad, Pakistan" - }, - { - "author_name": "Javed Muhammad", - "author_inst": "University of Swabi, Pakistan" - }, - { - "author_name": "Hira Fatima", - "author_inst": "University of Adelaide, Australia" + "author_name": "Antonio Feoli", + "author_inst": "University of Sannio" }, { - "author_name": "Aamer Ikram", - "author_inst": "National Institute of Health, Pakistan" + "author_name": "Antonella Lucia Iannella", + "author_inst": "University of Sannio" }, { - "author_name": "Hajo Zeeb", - "author_inst": "Leibniz Institute for Prevention Research and Epidemiology, Bremen, Germany" + "author_name": "Elmo Benedetto", + "author_inst": "University of Benevento" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1280620,25 +1280530,145 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.03.20167403", - "rel_title": "The mental health and experiences of discrimination of LGBTQ+ people during the COVID-19 pandemic: Initial findings from the Queerantine Study", + "rel_doi": "10.1101/2020.07.31.20166082", + "rel_title": "Evaluating the effects of SARS-CoV-2 Spike mutation D614G on transmissibility and pathogenicity", "rel_date": "2020-08-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.08.03.20167403", - "rel_abs": "ObjectiveTo assess mental health status and experiences of discrimination amongst a sample of Lesbian, Gay, Bisexual, Transgender, Queer people (LGBTQ+, the \"plus\" including those who dont identify with any such label) during the COVID-19 pandemic.\n\nDesignCross-sectional web-based survey.\n\nSettingResponses were collected during the COVID-19 pandemic between April 27thand July 13th.\n\nParticipants398 LGBTQ+ respondents forming an analytical sample of 310 in the main models.\n\nMethodsWe used a combined measure of gender identity or expression and sexual orientation as the main explanatory variable. We assessed mental health with the 4-item Perceived Stress Scale (PSS-4), and with the 10-item Center for Epidemiological Studies Depression scale (CES-D-10). We measured experiences of discrimination with a battery of questions that asked respondents whether they had experienced a set of discriminatory experiences because of their LGBTQ+ identity during the coronavirus pandemic. Experiences of discrimination was considered a mediating factor and examined both as an outcome as well as an explanatory variable. Models were adjusted for a range of demographic and socioeconomic variables.\n\nResultsThe prevalence of depression and stress were both high, with the majority of the sample exhibiting significant depressive symptomology (69%). Around one-in-six respondents reported some form of discrimination since the start of the pandemic because they were LGBTQ+ (16.7%). In regression models, the average score for perceived stress increased by 1.44 (95% Confidence Interval (CI): 0.517-2.354) for those who had experienced an instance of homophobic or transphobic harassment, compared to respondents who had not. Similarly, the odds of exhibiting significant depressive symptomology (CES-D-10 scores of 10 or more) increased three-fold among those who had experienced harassment based on their gender or sexuality compared to those who had not (OR: 3.251; 95% CI: 1.168-9.052). These marked associations remained after adjustment for a number of socioeconomic and demographic covariates. Cis-female respondents who identify as gay or lesbian had the lowest scores for perceived social or depressive symptoms; conversely transgender and gender diverse individuals had the highest scores.\n\nConclusionsWe found high levels of stress and depressive symptoms, particularly among younger and transgender and gender diverse respondents. These associations were partially explained by experiences of discrimination which had a large, consistent and pernicious impact on stress and mental health.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.31.20166082", + "rel_abs": "Global dispersal and increasing frequency of the SARS-CoV-2 Spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of Spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large data set, well represented by both Spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the Spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant.", + "rel_num_authors": 32, "rel_authors": [ { - "author_name": "Dylan Kneale", - "author_inst": "University College London" + "author_name": "Erik M Volz", + "author_inst": "Imperial College London" }, { - "author_name": "Laia Becares", - "author_inst": "University of Sussex" + "author_name": "Verity Hill", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "John T McCrone", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Anna Price", + "author_inst": "Cardiff University" + }, + { + "author_name": "David Jorgensen", + "author_inst": "Imperial College London" + }, + { + "author_name": "Aine O'Toole", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Joel Alexander Southgate", + "author_inst": "Cardiff University" + }, + { + "author_name": "Robert Johnson", + "author_inst": "Imperial College London" + }, + { + "author_name": "Ben Jackson", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Fabricia F. Nascimento", + "author_inst": "Imperial College London" + }, + { + "author_name": "Sara M. Rey", + "author_inst": "Public Health Wales NHS Trust" + }, + { + "author_name": "Samuel M. Nicholls", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Rachel M. Colquhoun", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Ana da Silva Filipe", + "author_inst": "MRC-University of Glasgow Centre for Virus Research" + }, + { + "author_name": "James G Shepherd", + "author_inst": "University of Glasgow" + }, + { + "author_name": "David J Pascall", + "author_inst": "Institute of Biodiversity, Animal Health and Comparative Medicine, Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, United K" + }, + { + "author_name": "Rajiv Shah", + "author_inst": "MRC-University of Glasgow Centre for Virus Research" + }, + { + "author_name": "Natasha Jesudason", + "author_inst": "MRC-University of Glasgow Centre for Virus Research" + }, + { + "author_name": "Kathy Li", + "author_inst": "MRC-University of Glasgow Centre for Virus Research" + }, + { + "author_name": "Ruth Jarrett", + "author_inst": "MRC-University of Glasgow Centre for Virus Research" + }, + { + "author_name": "Nicole Pacchiarini", + "author_inst": "Public Health Wales NHS Trust" + }, + { + "author_name": "Matthew Bull", + "author_inst": "Public Health Wales NHS Trust" + }, + { + "author_name": "Lily Geidelberg", + "author_inst": "Imperial College London" + }, + { + "author_name": "Igor Siveroni", + "author_inst": "Imperial College London" + }, + { + "author_name": "Ian G. Goodfellow", + "author_inst": "University of Cambridge" + }, + { + "author_name": "Nicholas James Loman", + "author_inst": "University of Birmingham" + }, + { + "author_name": "Oliver Pybus", + "author_inst": "University of Oxford" + }, + { + "author_name": "David L Robertson", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Emma C Thomson", + "author_inst": "University of Glasgow" + }, + { + "author_name": "Andrew Rambaut", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Thomas R Connor", + "author_inst": "Cardiff University" + }, + { + "author_name": "- The COVID-19 Genomics UK Consortium", + "author_inst": "-" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1282389,55 +1282419,103 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.08.02.233510", - "rel_title": "Mechanism of duplex unwinding by coronavirus nsp13 helicases", + "rel_doi": "10.1101/2020.08.02.230839", + "rel_title": "Natural Killer cell activation, reduced ACE2, TMPRSS2, cytokines G-CSF, M-CSF and SARS-CoV-2-S pseudovirus infectivity by MEK inhibitor treatment of human cells", "rel_date": "2020-08-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.02.233510", - "rel_abs": "The current COVID-19 pandemic urges in-depth investigation into proteins encoded with coronavirus (CoV), especially conserved CoV replicases. The nsp13 of highly pathogenic MERS-CoV, SARS-CoV-2, and SARS-CoV exhibit the most conserved CoV replicases. Using single-molecule FRET, we observed that MERS-CoV nsp13 unwound DNA in discrete steps of approximately 9 bp when ATP was used. If another NTP was used, then the steps were only 4 to 5 bp. In dwell time analysis, we detected 3 or 4 hidden steps in each unwinding process, which indicated the hydrolysis of 3 or 4 dTTP. Based on crystallographic and biochemical studies of CoV nsp13 helicases, we modeled an unwinding mechanism similar to the spring-loaded mechanism of HCV NS3 helicase, although our model proposes that flexible 1B and stalk domains, by allowing a lag greater than 4 bp during unwinding, cause the accumulated tension on the nsp13-DNA complex. The hinge region between two RecA-like domains in SARS-CoV-2 nsp13 is intrinsically more flexible than in MERS-CoV nsp13 due to the difference of a single amino acid, which causes the former to induce significantly greater NTP hydrolysis. Our findings thus establish a blueprint for determining the unwinding mechanism of a unique helicase family.\n\nO_LIWhen dTTP was used as the energy source, 4 hidden steps in each individual unwinding step after 3 - 4 NTP hydrolysis were observed.\nC_LIO_LIAn unwinding model of MERS-CoV-nsp13 which is similar to the spring-loaded mechanism of HCV NS3 helicase, except the accumulation of tension on nsp13/DNA complex is caused by the flexible 1B and stalk domains that allow a lag of 4-bp in unwinding.\nC_LIO_LIComparing to MERS-CoV nsp13, the hinge region between two RecA-like domains in SARS-CoV-2 nsp13 is intrinsically more flexible due to a single amino acid difference, which contributes to the significantly higher NTP hydrolysis by SARS-CoV-2 nsp13.\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.08.02.230839", + "rel_abs": "COVID-19 affects vulnerable populations including elderly individuals and patients with cancer. Natural Killer (NK) cells and innate-immune TRAIL suppress transformed and virally-infected cells. ACE2, and TMPRSS2 protease promote SARS-CoV-2 infectivity, while inflammatory cytokines IL-6, or G-CSF worsen COVID-19 severity. We show MEK inhibitors (MEKi) VS-6766, trametinib and selumetinib reduce ACE2 expression in human cells. In some human cells, remdesivir increases ACE2-promoter luciferase-reporter expression, ACE2 mRNA and protein, and ACE2 expression is attenuated by MEKi. In serum-deprived and stimulated cells treated with remdesivir and MEKi we observed correlations between pRB, pERK, and ACE2 expression further supporting role of proliferative state and MAPK pathway in ACE2 regulation. We show elevated cytokines in COVID-19-(+) patient plasma (N=9) versus control (N=11). TMPRSS2, inflammatory cytokines G-CSF, M-CSF, IL-1, IL-6 and MCP-1 are suppressed by MEKi alone or with remdesivir. We observed MEKi stimulation of NK-cell killing of target-cells, without suppressing TRAIL-mediated cytotoxicity. Pseudotyped SARS-CoV-2 virus with a lentiviral core and SARS-CoV-2 D614 or G614 SPIKE (S) protein on its envelope infected human bronchial epithelial cells, small airway epithelial cells, or lung cancer cells and MEKi suppressed infectivity of the pseudovirus. We show a drug class-effect with MEKi to stimulate NK cells, inhibit inflammatory cytokines and block host-factors for SARS-CoV-2 infection leading also to suppression of SARS-CoV-2-S pseudovirus infection of human cells. MEKi may attenuate SARS-CoV-2 infection to allow immune responses and antiviral agents to control disease progression.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Xiao Hu", - "author_inst": "University of Cincinnati College of Medicine" + "author_name": "Lanlan Zhou", + "author_inst": "Brown University" }, { - "author_name": "Wei Hao", - "author_inst": "Chinese Academy of Medical Sciences and Peking Union Medical College" + "author_name": "Kelsey Huntington", + "author_inst": "Brown University" }, { - "author_name": "Bo Qin", - "author_inst": "Chinese Academy of Medical Sciences and Peking Union Medical College" + "author_name": "Shengliang Zhang", + "author_inst": "Brown University" }, { - "author_name": "Zhiqi Tian", - "author_inst": "University of Cincinnati College of Medicine" + "author_name": "Lindsey Carlsen", + "author_inst": "Brown University" }, { - "author_name": "Ziheng Li", - "author_inst": "Chinese Academy of Medical Sciences and Peking Union Medical College" + "author_name": "Eui-Young So", + "author_inst": "Brown University" }, { - "author_name": "Pengjiao Hou", - "author_inst": "Chinese Academy of Medical Sciences and Peking Union Medical College" + "author_name": "Cassandra Parker", + "author_inst": "Brown University" }, { - "author_name": "Rong Zhao", - "author_inst": "Chinese Academy of Medical Sciences and Peking Union Medical College" + "author_name": "Ilyas Sahin", + "author_inst": "Brown University" }, { - "author_name": "Sheng Cui", - "author_inst": "Chinese Academy of Medical Sciences and Peking Union Medical College" + "author_name": "Howard Safran", + "author_inst": "Brown University" }, { - "author_name": "Jiajie Diao", - "author_inst": "University of Cincinnati College of Medicine" + "author_name": "Suchitra Kamle", + "author_inst": "Brown University" + }, + { + "author_name": "Chang-Min Lee", + "author_inst": "Brown University" + }, + { + "author_name": "Chun-Geun Lee", + "author_inst": "Brown University" + }, + { + "author_name": "Jack A. Elias", + "author_inst": "Brown University" + }, + { + "author_name": "Kerry S. Campbell", + "author_inst": "Fox Chase Cancer Center" + }, + { + "author_name": "Mandar T. Naik", + "author_inst": "Brown University" + }, + { + "author_name": "Walter J. Atwood", + "author_inst": "Brown University" + }, + { + "author_name": "Emile Youssef", + "author_inst": "Verastem" + }, + { + "author_name": "Jonathan A. Pachter", + "author_inst": "Verastem" + }, + { + "author_name": "Arunasalam Navaraj", + "author_inst": "Brown University" + }, + { + "author_name": "Attila A. Seyhan", + "author_inst": "Brown University" + }, + { + "author_name": "Olin Liang", + "author_inst": "Brown University" + }, + { + "author_name": "Wafik El-Deiry", + "author_inst": "Brown University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biophysics" + "category": "cell biology" }, { "rel_doi": "10.1101/2020.08.02.233320", @@ -1284507,27 +1284585,39 @@ "category": "endocrinology" }, { - "rel_doi": "10.1101/2020.07.30.20165282", - "rel_title": "A Compartmental Epidemic Model Incorporating Probable Cases to Model COVID-19 Outbreak in Regions with Limited Testing Capacity", - "rel_date": "2020-08-02", + "rel_doi": "10.1101/2020.07.30.20165100", + "rel_title": "Clinical manifestations of patients with Coronavirus Disease 2019 (COVID- 19) attending at hospitals in Bangladesh", + "rel_date": "2020-08-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20165282", - "rel_abs": "We propose a new compartmental epidemic model taking into account people who has symptoms with no confirmatory laboratory testing (probable cases). We prove well-posedness of the model and provide an explicit expression for the basic reproduction number ([R]0). We use the model together with an extended Kalman filter (EKF) to estimate the time-varying effective reproduction number ([R]t) of COVID-19 in West Java province, Indonesia, where laboratory testing capacity is limited. Based on our estimation, the value of [R]t is higher when the probable cases are taken into account. This correction can be used by decision and policy makers when considering re-opening policy and evaluation of measures.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20165100", + "rel_abs": "Bangladesh is in the rising phase of the ongoing pandemic of the coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The scientific literature on clinical manifestations of COVID-19 patients from Bangladesh is scarce. This study aimed to report the sociodemographic and clinical characteristics of patients with COVID-19 in Bangladesh. We conducted a cross-sectional study at three dedicated COVID-19 hospitals. The severity of the COVID-19 cases was assessed based on the WHO interim guidance. Data were collected only from non-critical COVID-19 patients as critical patients required immediate intensive care admission making them unable to respond to the questions. A total of 103 RT-PCR confirmed non-critical COVID-19 patients were enrolled. Most of the patients (71.8%) were male. Mild, moderate and severe illness were assessed in 74.76%, 9.71% and 15.53% of patients respectively. Nearly 52.4% of patients had a co-morbidity, with hypertension being the most common (34%), followed by diabetes mellitus (21.4%) and ischemic heart disease (9.7%). Fever (78.6%), weakness (68%) and cough (44.7%) were the most common clinical manifestations. Other common symptoms included loss of appetite (37.9%), difficulty in breathing (37.9%), altered sensation of taste or smell (35.0%), headache (32%) and body ache (32%). The median time from onset of symptom to attending hospitals was 7 days (IQR 4-10). This study will help both the clinicians and epidemiologists to understand the magnitude and clinical spectrum of COVID-19 patients in Bangladesh.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Agus Hasan", - "author_inst": "University of Southern Denmark" + "author_name": "Md. Shahed Morshed", + "author_inst": "Kurmitola general hospital, Dhaka, Bangladesh" }, { - "author_name": "Yuki Nasution", - "author_inst": "Universitas Mulawarman" + "author_name": "Abdullah Al Mosabbir", + "author_inst": "Biomedical Research Foundation, Dhaka, Bangladesh" + }, + { + "author_name": "Prodipta Chowdhury", + "author_inst": "Keshabpur upazilla health complex, Jessore, Bangladesh" + }, + { + "author_name": "Sheikh Mohammad Ashadullah", + "author_inst": "Shailkupa upazilla health complex, Jhenaidah, Bangladesh" + }, + { + "author_name": "Mohammad Sorowar Hossain", + "author_inst": "Biomedical Research Foundation, Dhaka, Bangladesh" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.07.29.20164459", @@ -1286413,45 +1286503,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.30.20165050", - "rel_title": "Quantification of the association between predisposing health conditions, demographic, and behavioural factors with hospitalisation, intensive care unit admission, and death from COVID-19: a systematic review and meta-analysis", + "rel_doi": "10.1101/2020.07.30.20164608", + "rel_title": "Visualizing and Assessing US County-Level COVID19 Vulnerability", "rel_date": "2020-08-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20165050", - "rel_abs": "BackgroundComprehensive evidence synthesis on the associations between comorbidities and behavioural factors with hospitalisation, Intensive Care Unit (ICU) admission, and death due to COVID-19 is lacking leading to inconsistent national and international recommendations on who should be targeted for non-pharmaceutical interventions and vaccination strategies.\n\nMethodsWe performed a systematic review and meta-analysis on studies and publicly available data to quantify the association between predisposing health conditions, demographics, and behavioural factors with hospitalisation, ICU admission, and death from COVID-19. We provided ranges of reported and calculated effect estimates and pooled relative risks derived from a meta-analysis and meta-regression.\n\nResults75 studies were included into qualitative and 74 into quantitative synthesis, with study populations ranging from 19 - 44,672 COVID-19 cases. The risk of dying from COVID-19 was significantly associated with cerebrovascular [pooled RR 2.7 (95% CI 1.7-4.1)] and cardiovascular [RR 3.2 (CI 2.3-4.5)] diseases, hypertension [RR 2.6 (CI 2.0-3.4)], and renal disease [RR 2.5 (CI 1.8-3.4)]. Health care workers had lower risk for death and severe outcomes of disease (RR 0.1 (CI 0.1-0.3). Our meta-regression showed a decrease of the effect of some comorbidities on severity of disease with higher median age of study populations. Associations between comorbidities and hospitalisation and ICU admission were less strong than for death.\n\nConclusionsWe obtained robust estimates on the magnitude of risk for COVID-19 hospitalisation, ICU admission, and death associated with comorbidities, demographic, and behavioural risk factors. We identified and confirmed population groups that are vulnerable and that require targeted prevention approaches.\n\nSummaryComorbidities such as cardiovascular disease or hypertension are less strongly associated with hospitalization and ICU admission than with death in COVID-19 patients. Increasing age is associated with a lower effect on comorbidities on disease severity.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.30.20164608", + "rel_abs": "ObjectiveLike most of the world, the United States public health and economy are impacted by the COVID19 pandemic. However, discrete pandemic effects may not be fully realized on the macro-scale. With this perspective, our goal is to visualize spread of the pandemic and measure county-level features which may portend vulnerability.\n\nMaterials and MethodsWe accessed the New York Times GitHub repository COVID19 data and 2018 US Census data for all US Counties. The disparate datasets were merged and filtered to allow for visualization and assessments about case fatality rate (CFR%) and associated demographic, ethnic and economic features.\n\nResultsOur results suggest that county-level COVID19 fatality rates are related to advanced population age (p <0.001) and less diversity as evidenced by higher proportion of Caucasians in High CFR% counties (p < 0.001). Also, lower CFR% counties had a greater proportion of the population reporting has having 2 or more races (p <0.001). We noted no significant differences between High and Low CFR% counties with respect to mean income or poverty rate.\n\nConclusionsUnique COVID19 impacts are realized at the county level. Use of public datasets, data science skills and information visualization can yield helpful insights to drive understanding about community-level vulnerability.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Nathalie Veronica Fernandez Villalobos", - "author_inst": "Helmholtz Centre for Infection Research" - }, - { - "author_name": "Joerdis Jennifer Ott", - "author_inst": "Helmholtz Centre for Infection Research, Hannover Medical School, German Centre for Infection Research" + "author_name": "Gina Cahill", + "author_inst": "Baylor College of Medicine, Department of Pediatrics, Houston TX, USA" }, { - "author_name": "Carolina Judith Klett-Tammen", - "author_inst": "Helmholtz Centre for Infection Research" + "author_name": "Carleigh Kutac", + "author_inst": "Baylor St. Luke's Medical Center, Houston TX, USA" }, { - "author_name": "Annabelle Bockey", - "author_inst": "Helmholtz Centre for Infection Research, University Hospital Freiburg" - }, - { - "author_name": "Patrizio Vanella", - "author_inst": "Helmholtz Centre for Infection Research" - }, - { - "author_name": "Gerard Krause", - "author_inst": "Helmholtz Centre for Infection Research, Hannover Medical School, German Centre for Infection Research, Twincore" - }, - { - "author_name": "Berit Lange", - "author_inst": "Helmholtz Centre for Infection Research, German Centre for Infection Research" + "author_name": "Nicholas L Rider", + "author_inst": "BAYLOR COLLEGE OF MEDICINE" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1288015,117 +1288089,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.29.20164293", - "rel_title": "Persistent fatigue following SARS-CoV-2 infection is common and independent of severity of initial infection", + "rel_doi": "10.1101/2020.07.29.20164160", + "rel_title": "Tocilizumab shortens time on mechanical ventilation and length of hospital stay in patients with severe COVID-19: a retrospective cohort study.", "rel_date": "2020-07-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.29.20164293", - "rel_abs": "Fatigue is a common symptom in those presenting with symptomatic COVID-19 infection. However, it is unknown if COVID-19 results in persistent fatigue in those recovered from acute infection. We examined the prevalence of fatigue in individuals recovered from the acute phase of COVID-19 illness using the Chalder Fatigue Score (CFQ-11). We further examined potential predictors of fatigue following COVID-19 infection, evaluating indicators of COVID-19 severity, markers of peripheral immune activation and circulating pro-inflammatory cytokines. Of 128 participants (49.5 {+/-} 15 years; 54% female), more than half reported persistent fatigue (52.3%; 45/128) at 10 weeks (median) after initial COVID-19 symptoms. There was no association between COVID-19 severity (need for inpatient admission, supplemental oxygen or critical care) and fatigue following COVID-19. Additionally, there was no association between routine laboratory markers of inflammation and cell turnover (leukocyte, neutrophil or lymphocyte counts, neutrophil-to-lymphocyte ratio, lactate dehydrogenase, C-reactive protein) or pro-inflammatory molecules (IL-6 or sCD25) and fatigue post COVID-19. Female gender and those with a pre-existing diagnosis of depression/anxiety were over-represented in those with fatigue. Our findings demonstrate a significant burden of post-viral fatigue in individuals with previous SARS-CoV-2 infection after the acute phase of COVID-19 illness. This study highlights the importance of assessing those recovering from COVID-19 for symptoms of severe fatigue, irrespective of severity of initial illness, and may identify a group worthy of further study and early intervention.", - "rel_num_authors": 26, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.29.20164160", + "rel_abs": "BackgroundHyperinflammation is a key feature of the pathogenesis of COVID-19 with a central role of the interleukin-6 pathway. We aimed to study the impact of the IL-6 receptor antagonist tocilizumab on the outcome of patients admitted to the intensive care unit (ICU) with acute respiratory distress syndrome (ARDS) related to COVID-19.\n\nMethodsEighty-seven patients with confirmed SARS-CoV-2 infection and moderate to severe ARDS were included (n tocilizumab = 29, n controls = 58). A matched cohort was created using a propensity score. The primary endpoint was 30-day all-cause mortality, secondary endpoints included ventilation-free days and length of stay.\n\nResultsNo difference was found in 30-day all-cause mortality in patients treated with tocilizumab compared to controls (17.2% vs. 32.8%, p = 0.2; HR = 0.52 [0.19 - 1.39], p = 0.19). Ventilator-free days were 19.0 (IQR 12.5 - 20.0) versus 9 (IQR 0.0 - 18.5; p = 0.04), respectively. A higher rate of freedom from mechanical ventilation at 30 days was achieved in patients receiving tocilizumab (HR 2.83 [1.48 - 5.40], p < 0.002). Median length of stay in ICU and total length of stay were reduced by 8 and 9.5 days in patients treated with tocilizumab. Similar results were obtained in the analysis of the propensity score matched cohort.\n\nConclusionsTreatment of critically ill patients with ARDS due to COVID-19 with tocilizumab was not associated with reduced 30-day all-cause mortality, but shorter duration on ventilatory support as well as shorter overall length of stay in hospital and in ICU.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Liam Townsend", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Adam H Dyer", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Karen Jones", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Jean Dunne", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Rachel Kiersey", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Fiona Gaffney", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Laura O'Connor", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Aoife Mooney", - "author_inst": "St James's Hospital" + "author_name": "Johannes Eimer", + "author_inst": "Karolinska Univeristy Hopsital Huddinge, Sweden, Unit of Infectious Diseases." }, { - "author_name": "Deirdre Leavy", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Katie Ridge", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Catherine King", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Fionnuala Cox", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Kate O'Brien", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Joanne Dowds", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Jamie Sugrue", - "author_inst": "Trinity College Dublin" - }, - { - "author_name": "David Hopkins", - "author_inst": "Trinity College Dublin" - }, - { - "author_name": "Patricia Byrne", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Tara Kingston", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Cliona Ni Cheallaigh", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Parthiban Nadarajan", - "author_inst": "St James's Hospital" - }, - { - "author_name": "Anne Marie McLaughlin", - "author_inst": "St James's Hospital" + "author_name": "Jan Vesterbacka", + "author_inst": "Karolinska University Hospital HUddinge, Sweden, Unit of Infectious Diseases" }, { - "author_name": "Nollaig M Bourke", - "author_inst": "Trinity College Dublin" + "author_name": "Anna-Karin Svensson", + "author_inst": "Karolinska Univeristy Hospital Huddinge, Sweden, Unit of Infectious DIseases" }, { - "author_name": "Colm Bergin", - "author_inst": "St James's Hospital" + "author_name": "Bertil Stojanovic", + "author_inst": "Karolinska University Hospital HUddinge, Sweden, Unit of Infectious Diseases" }, { - "author_name": "Cliona O'Farrelly", - "author_inst": "Trinity College Dublin" + "author_name": "Charlotta Wagrell", + "author_inst": "Karolinska University Hospital, Huddinge, Sweden, Unit of Infectious Diseases" }, { - "author_name": "Ciaran Bannan", - "author_inst": "St James's Hospital" + "author_name": "Anders Sonnerborg", + "author_inst": "Karolinska University Hospital HUddinge, Sweden, Unit of Infectious Diseases" }, { - "author_name": "Niall Conlon", - "author_inst": "St James's Hospital" + "author_name": "Piotr Nowak", + "author_inst": "Karolinska INstitute, Karolinska University Hospital Huddinge, Sweden, Unit of Infectious DIseases" } ], "version": "1", @@ -1289573,53 +1289571,45 @@ "category": "hematology" }, { - "rel_doi": "10.1101/2020.07.29.20159442", - "rel_title": "Early Clinical Factors Predicting the Development of Critical Disease in Japanese Patients with COVID-19: A Single-Center Retrospective, Observational Study", + "rel_doi": "10.1101/2020.07.24.20148262", + "rel_title": "Incidence and outcomes of healthcare-associated COVID-19 infections: significance of delayed diagnosis and correlation with staff absence", "rel_date": "2020-07-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.29.20159442", - "rel_abs": "BackgroundInsufficient evidence of factors predicting the COVID-19 progression from mild to moderate to critical has been established. We retrospectively evaluated risk factors for critical progression in Japanese COVID-19 patients.\n\nMethodSeventy-four laboratory-confirmed COVID-19 patients were hospitalized in our hospital between February 20, 2020, and June 10, 2020. We excluded asymptomatic, non-Japanese, and child patients. We divided patients into the stable group (SG) and the progression group (PG) (patients requiring mechanical ventilation). We compared the clinical factors in both groups. We established the cutoff values (COVs) for significantly different factors via receiver operating characteristic (ROC) curve analysis and evaluated risk factors by univariate regression.\n\nResultsWe enrolled 57 COVID-19 patients (median age 52 years, 56.1% male). The median progression time from symptom onset was eight days. Seven patients developed critical disease (PG: 12.2%), two (3.5%) of whom died; 50 had stable disease. Univariate logistic analysis identified elevated lactate dehydrogenase (LDH) (COV: 309 U/l), decreased estimated glomerular filtration rate (eGFR) (COV: 68 ml/min), lymphocytopenia (COV: 980/l), and statin use as significantly associated with disease progression. However, in Cox proportional hazards analysis, lymphocytopenia at symptom onset was not significant.\n\nConclusionsWe identified three candidate risk factors for adult Japanese patients with mild to moderate COVID-19: statin use, elevated LDH level, and decreased eGFR.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.24.20148262", + "rel_abs": "BackgroundThe sudden increase in COVID-19 admissions in hospitals during the SARS-CoV2 pandemic of 2020 has led to onward transmissions among vulnerable inpatients.\n\nAimsThis study was performed to evaluate the prevalence and clinical outcomes of Healthcare-associated COVID-19 infections (HA-COVID-19) during the 2020 epidemic and study factors which may promote or correlate with its incidence and transmission in a London Teaching Hospital Trust.\n\nMethodsElectronic laboratory, patient and staff self-reported sickness records were interrogated for the period 1st March to 18th April 2020. HA-COVID-19 was defined as symptom onset >14d of admission. Test performance of a single combined throat and nose swab (CTNS) for patient placement and the effect of delayed RNA positivity (DRP, defined as >48h delay) on patient outcomes was evaluated. The incidence of staff self-reported COVID-19 sickness absence, hospital bed occupancy, community incidence and DRP was compared HA-COVID-19. The incidence of other significant hospital-acquired bacterial infections (OHAI) was compared to previous years.\n\nResults58 HA-COVID-19 (7.1%) cases were identified. As compared to community-acquired cases, significant differences were observed in age (p=0.018), ethnicity (p<0.001) and comorbidity burden (p<0.001) but not in 30d mortality. CTNS negative predictive value was 60.3%. DRP was associated with greater mortality (p=0.034) and 34.5% HA-COVID-19 cases could be traced to delayed diagnosis in CA-COVID-19. Incidence of HA-COVID-19 correlated positively with DRP (R=0.7108) and staff sickness absence (R=0.7815). OHAI rates were similar to previous 2 years.\n\nConclusionEarly diagnosis and isolation of COVID-19 would help reduce transmission. A single CTNS has limited value in segregating patients into positive and negative pathways.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Takatoshi Higuchi", - "author_inst": "Toyonaka Municipal Hospital" + "author_name": "Kirstin Khonyongwa", + "author_inst": "Kings College Hospital NHS Foundation Trust, Denmark Hill, London, UK" }, { - "author_name": "Tsutomu Nishida", - "author_inst": "Toyonaka Municipal Hospital" + "author_name": "Surabhi K Taori", + "author_inst": "Kings College Hospital NHS Foundation Trust, Denmark Hill, London, UK" }, { - "author_name": "Hiromi Iwahashi", - "author_inst": "Toyonaka Municipal Hospital" - }, - { - "author_name": "Osamu Morimura", - "author_inst": "Toyonaka Municipal Hospital" - }, - { - "author_name": "Yasushi Otani", - "author_inst": "Toyonaka Municipal Hospital" + "author_name": "Ana Soares", + "author_inst": "Kings College Hospital NHS Foundation Trust, Denmark Hill, London, UK" }, { - "author_name": "Yukiyoshi Okauchi", - "author_inst": "Toyonaka Municipal Hospital" + "author_name": "Nergish Desai", + "author_inst": "Kings College Hospital NHS Foundation Trust, Denmark Hill, London, UK" }, { - "author_name": "Masaru Yokoe", - "author_inst": "Toyonaka Municipal Hospital" + "author_name": "Malur Sudhanva", + "author_inst": "Kings College Hospital NHS Foundation Trust, Denmark Hill, London, UK" }, { - "author_name": "Norihiro Suzuki", - "author_inst": "Toyonaka Municipal Hospital" + "author_name": "William Bernal", + "author_inst": "Kings College Hospital NHS Foundation Trust, Denmark Hill, London, UK" }, { - "author_name": "Masami Inada", - "author_inst": "Toyonaka Municipal Hospital" + "author_name": "Silke Schelenz", + "author_inst": "Kings College Hospital NHS Foundation Trust, Denmark Hill, London, UK" }, { - "author_name": "Kinya Abe", - "author_inst": "Toyonaka Municipal Hospital" + "author_name": "Lisa A Curran", + "author_inst": "Kings College Hospital NHS Foundation Trust, Denmark Hill, London, UK" } ], "version": "1", @@ -1291363,23 +1291353,59 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.07.27.20162743", - "rel_title": "How much reserve capacity is justifiable for hospital pandemic preparedness? A cost-effectiveness analysis for COVID-19 in Germany", + "rel_doi": "10.1101/2020.07.27.20162636", + "rel_title": "The German Corona Consensus Dataset (GECCO): A standardized dataset for COVID-19 research", "rel_date": "2020-07-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.27.20162743", - "rel_abs": "IntroductionIn preparation for a possible second COVID-19 pandemic wave, expanding intensive care unit (ICU) bed capacity is an important consideration. The purpose of this study was to determine the costs and benefits of this strategy in Germany.\n\nMethodsThis study compared the provision of additional capacity to no intervention from a societal perspective. A decision model was developed using, e.g., information on age-specific fatality rates, ICU costs and outcomes, and the herd protection threshold. The net monetary benefit (NMB) was calculated based upon the willingness to pay for new medicines for the treatment of cancer, a condition with a similar disease burden in the near term.\n\nResultsThe marginal cost-effectiveness ratio (MCER) of supplying one additional ICU bed is {euro}24,815 per life year gained and increases with the number of additional beds. The NMB remains positive for utilization rates as low as 1.5% and, assuming full capacity utilization, for multiples of the currently available bed capacity. Expanding the ICU bed capacity by 10,000 beds is projected to result in societal costs of {euro}41 billion and to reduce mortality of ICU candidates by 20% compared with no intervention (assuming full capacity utilization). In a sensitivity analysis, the variables with the highest impact on the MCER were the mortality rates in the ICU and after discharge.\n\nConclusionsIn Germany, the provision of additional ICU bed capacity appears to be cost-effective over a large increase in the number of beds. Nevertheless, bed utilization is constrained by labor supply and possibly other input factors.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.27.20162636", + "rel_abs": "BackgroundThe current COVID-19 pandemic has led to a surge of research activity. While this research provides important insights, the multitude of studies results in an increasing segmentation of information. To ensure comparability across projects and institutions, standard datasets are needed. Here, we introduce the \"German Corona Consensus Dataset\" (GECCO), a uniform dataset that uses international terminologies and health IT standards to improve interoperability of COVID-19 data.\n\nMethodsBased on previous work (e.g., the ISARIC-WHO COVID-19 case report form) and in coordination with experts from university hospitals, professional associations and research initiatives, data elements relevant for COVID-19 research were collected, prioritized and consolidated into a compact core dataset. The dataset was mapped to international terminologies, and the Fast Healthcare Interoperability Resources (FHIR) standard was used to define interoperable, machine-readable data formats.\n\nResultsA core dataset consisting of 81 data elements with 281 response options was defined, including information about, for example, demography, anamnesis, symptoms, therapy, medications or laboratory values of COVID-19 patients. Data elements and response options were mapped to SNOMED CT, LOINC, UCUM, ICD-10-GM and ATC, and FHIR profiles for interoperable data exchange were defined.\n\nConclusionGECCO provides a compact, interoperable dataset that can help to make COVID-19 research data more comparable across studies and institutions. The dataset will be further refined in the future by adding domain-specific extension modules for more specialized use cases.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Afschin Gandjour", - "author_inst": "Frankfurt School of Finance & Management" + "author_name": "Julian Sass", + "author_inst": "Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Alexander Bartschke", + "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Moritz Lehne", + "author_inst": "Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Andrea Essenwanger", + "author_inst": "Berlin Institute of Health (BIH), Berlin, Germany" + }, + { + "author_name": "Eugenia Rinaldi", + "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Stefanie Rudolph", + "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Kai Uwe Heitmann", + "author_inst": "health innovation hub of the Federal Ministry of Health, Berlin, Germany" + }, + { + "author_name": "Joerg Janne Vehreschild", + "author_inst": "Medical Department 2, Hematology / Oncology, University Hospital of Frankfurt, Germany | Department I for Internal Medicine, University Hospital Cologne, German" + }, + { + "author_name": "Christof von Kalle", + "author_inst": "Charite Universitaetsmedizin Berlin, Berlin, Germany" + }, + { + "author_name": "Sylvia Thun", + "author_inst": "Berlin Institute of Health (BIH), Berlin, Germany" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.07.27.20162867", @@ -1293157,27 +1293183,43 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2020.07.28.20163592", - "rel_title": "Evaluation of a SARS-CoV-2 surrogate virus neutralization test for detection of antibody in human, canine, cat and hamster sera", + "rel_doi": "10.1101/2020.07.28.20163543", + "rel_title": "Prevalence of amyloid blood clots in COVID-19 plasma", "rel_date": "2020-07-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20163592", - "rel_abs": "Surrogate neutralization assays for SARS-CoV-2 that can be done without biosafety-level-3 containment and across multiple species are desirable. We evaluate a recently developed surrogate virus neutralization test (sVNT) in comparison to 90% plaque reduction neutralization tests (PRNT90) in human, canine, cat and hamster sera and found excellent concordance between the two assays. Using a panel of immune sera to other coronaviruses, we confirm the lack of cross reactivity in sVNT and PRNT90 assays.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.28.20163543", + "rel_abs": "The rapid detection of COVID-19 uses genotypic testing for the presence of SARS-Cov-2 virus in nasopharyngeal swabs, but it can have a poor sensitivity. A rapid, host-based physiological test that indicated whether the individual was infected or not would be highly desirable. Coagulaopathies are a common accompaniment to COVID-19, especially micro-clots within the lungs. We show here that microclots can be detected in the native plasma of COVID-19 patient, and in particular that such clots are amyloid in nature as judged by a standard fluorogenic stain. This provides a rapid and convenient test (P<0.0001), and suggests that the early detection and prevention of such clotting could have an important role in therapy.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Joseph Sriyal Malik Peiris", - "author_inst": "University of Hong Kong" + "author_name": "Etheresia Pretorius", + "author_inst": "Stellenbosch University" }, { - "author_name": "Ranawaka APM Perera", - "author_inst": "The University of Hong Kong" + "author_name": "Chantelle Venter", + "author_inst": "Stellenbosch University" + }, + { + "author_name": "Gert J Laubscher", + "author_inst": "Stellenbosch MediClinic Private Practice" + }, + { + "author_name": "Petrus J Lourens", + "author_inst": "Stellenbosch MediClinic Private Practice" + }, + { + "author_name": "Janami Steenkamp", + "author_inst": "PathCare Laboratories" + }, + { + "author_name": "Douglas B Kell", + "author_inst": "University of Liverpool" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2020.07.28.20163493", @@ -1294839,45 +1294881,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.25.20162073", - "rel_title": "Effectiveness and Safety of Chloroquine or Hydroxychloroquine as a mono-therapy or in combination with Azithromycin in the treatment of COVID-19 patients: Systematic Review and Meta-Analysis", + "rel_doi": "10.1101/2020.07.27.20161976", + "rel_title": "Exploratory analysis of immunization records highlights decreased SARS-CoV-2 rates in individuals with recent non-COVID-19 vaccinations", "rel_date": "2020-07-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.25.20162073", - "rel_abs": "Many recent studies have investigated the role of either Chloroquine (CQ) alone, Hydroxychloroquine (HCQ) alone, or CQ/HCQ in combination with azithromycin (AZM) in management of the emerging coronavirus. This systematic review and meta-analysis of either published or preprint observational or interventional studies were conducted to assess the cure rate, duration of hospital stay, radiological progression, clinical worsening, need for mechanical ventilation, the occurrence of side effects, and mortality. A search of the online database through June 2020 was performed and examined the reference lists of pertinent articles for in-vivo studies only. Pooled relative risks (RRs), standard mean, of 95 % confidence intervals (CIs) were calculated with the random-effects model.\n\nResultsThe duration of hospital stay was shorter in the standard care in comparison with HCQ group, the standard mean of hospital stay was 0.57, 95% CI, and 0.20-0.94. Overall virological cure, or more specifically at day 4, 10, and 14 among patients exposed to HCQ did not differ significantly from the standard care [(RR=0.92, 95% CI 0.78-1.15), (RR=1.11, 95% CI 0.74-1.65), (RR=1.21, 95%CI 0.70-2.01), and (RR=0.98, 95% CI, 0.76-1.27)] respectively. Radiological improvement or clinical worsening was not statistically different between HCQ and standard care [(RR=1.11, 95% CI 0.64-1.65) and (RR=1.28, 95% CI 0.33-4.99)]. The need for mechanical ventilation (MV) was not significant between the HCQ group and the standard care (RR= 1.5, 95%CI 0.78-2.89). Side effects were more reported in the HCQ group than the standard care (RR=3.14, 95% CI 1.58-6.24). Mortality among HCQ was not affected by receiving HCQ (RR=3.14, 95% CI 1.58-6.24), meta-regression analysis revealed that country is a strong predictor of mortality. The duration of hospital stay among the HCQ and AZM didnt differ significantly from the standard care (standard mean= 0.77, 95% CI 0.46-1.08). Despite virological cure and need for MV did not differ significantly [(RR= 3.23, 95% CI 0.70-14.97) and (RR=1.27, 95%CI 0.7-2.13)] respectively. Mortality among the HCQ+AZM was more significantly higher than among the standard care (RR= 1.8, 95% CI 1.19-2.27).\n\nConclusionDespite the scarcity of published data of good quality, the effectiveness and safety of either HCQ alone or in combination with AZM in treating the pandemic of COVID-19 cant be assured. Future randomized control trials need to be carried out to verify this conclusion.\n\nRegistrationPROSPERO registration number: CRD42020192084", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.27.20161976", + "rel_abs": "Multiple clinical studies are ongoing to assess whether existing vaccines may afford protection against SARS-CoV-2 infection through trained immunity. In this exploratory study, we analyze immunization records from 137,037 individuals who received SARS-CoV-2 PCR tests. We find that polio, Hemophilus influenzae type-B (HIB), measles-mumps-rubella (MMR), varicella, pneumococcal conjugate (PCV13), geriatric flu, and hepatitis A / hepatitis B (HepA-HepB) vaccines administered in the past 1, 2, and 5 years are associated with decreased SARS-CoV-2 infection rates, even after adjusting for geographic SARS-CoV-2 incidence and testing rates, demographics, comorbidities, and number of other vaccinations. Furthermore, age, race/ethnicity, and blood group stratified analyses reveal significantly lower SARS-CoV-2 rate among black individuals who have taken the PCV13 vaccine, with relative risk of 0.45 at the 5 year time horizon (n: 653, 95% CI: (0.32, 0.64), p-value: 6.9e-05). These findings suggest that additional pre-clinical and clinical studies are warranted to assess the protective effects of existing non-COVID-19 vaccines and explore underlying immunologic mechanisms. We note that the findings in this study are preliminary and are subject to change as more data becomes available and as further analysis is conducted.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Ramy Mohamed Ghazy", - "author_inst": "High Institute of Public Health" + "author_name": "Colin Pawlowski", + "author_inst": "nference" }, { - "author_name": "Abdallah Almaghraby", - "author_inst": "Alexandria Faculty of Medicine" + "author_name": "Arjun Puranik", + "author_inst": "nference" }, { - "author_name": "Ramy Shaaban", - "author_inst": "Utah State University" + "author_name": "Hari Bandi", + "author_inst": "nference" }, { - "author_name": "Ahmed Kamal", - "author_inst": "Alexandria Faculty of Medicine" + "author_name": "AJ Venkatakrishnan", + "author_inst": "nference" }, { - "author_name": "Hatem Beshir", - "author_inst": "Mansoura Faculty of Medicine" + "author_name": "Vineet Agarwal", + "author_inst": "nference" }, { - "author_name": "Amr Moursi", - "author_inst": "Ninewells University Hospital" + "author_name": "Richard Kennedy", + "author_inst": "Mayo Clinic" }, { - "author_name": "Sarah Hamed N. Taha", - "author_inst": "Cairo University" + "author_name": "John C O'Horo", + "author_inst": "Mayo Clinic" }, { - "author_name": "Ahmed Ramadan", - "author_inst": "DataClin" + "author_name": "Gregory J Gores", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Amy W Williams", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "John Halamka", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Andrew D Badley", + "author_inst": "Mayo Clinic" + }, + { + "author_name": "Venky Soundararajan", + "author_inst": "nference" } ], "version": "1", @@ -1296585,71 +1296643,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.21.20153650", - "rel_title": "Patient characteristics and predictors of mortality in 470 adults admitted to a district general hospital in England with Covid-19", + "rel_doi": "10.1101/2020.07.18.20155549", + "rel_title": "Trends of in-hospital and 30-day mortality after percutaneous coronary intervention in England before and after the COVID-19 era", "rel_date": "2020-07-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.21.20153650", - "rel_abs": "BackgroundUnderstanding risk factors for death in Covid-19 is key to providing good quality clinical care. Due to a paucity of robust evidence, we sought to assess the presenting characteristics of patients with Covid-19 and investigate factors associated with death.\n\nMethodsRetrospective analysis of adults admitted with Covid-19 to Royal Oldham Hospital, UK. Logistic regression modelling was utilised to explore factors predicting death.\n\nResults470 patients were admitted, of whom 169 (36%) died. The median age was 71 years (IQR 57-82), and 255 (54.3%) were men. The most common comorbidities were hypertension (n=218, 46.4%), diabetes (n=143, 30.4%) and chronic neurological disease (n=123, 26.1%). The most frequent complications were acute kidney injury (n=157, 33.4%) and myocardial injury (n=21, 4.5%). Forty-three (9.1%) patients required intubation and ventilation, and 39 (8.3%) received non-invasive ventilation Independent risk factors for death were increasing age (OR per 10 year increase above 40 years 1.87, 95% CI 1.57-2.27), hypertension (OR 1.72, 1.10-2.70), cancer (OR 2.20, 1.27-3.81), platelets <150x103/{micro}L (OR 1.93, 1.13-3.30), C-reactive protein [≥]100 {micro}g/mL (OR 1.68, 1.05-2.68), >50% chest radiograph infiltrates, (OR 2.09, 1.16-3.77) and acute kidney injury (OR 2.60, 1.64-4.13). There was no independent association between death and gender, ethnicity, deprivation level, fever, SpO2/FiO2 (oxygen saturation index), lymphopenia or other comorbidities.\n\nConclusionsWe characterised the first wave of patients with Covid-19 in one of Englands highest incidence areas, determining which factors predict death. These findings will inform clinical and shared decision making, including the use of respiratory support and therapeutic agents.\n\nSummaryIncreasing age, hypertension, cancer, platelets <150x103/{micro}L, CRP[≥]100 {micro}g/mL, >50% chest radiograph infiltrates, and acute kidney injury predict in-hospital death from Covid-19, whilst gender, ethnicity, deprivation level, fever, SpO2/FiO2 (oxygen saturation index), lymphopenia and other comorbidities do not.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.18.20155549", + "rel_abs": "ObjectivesTo examine short-term primary causes of death after percutaneous coronary intervention (PCI) in a national cohort before and during COVID-19.\n\nBackgroundPublic reporting of PCI outcomes is a performance metric and a requirement in many healthcare systems. There are inconsistent data on the causes of death after PCI, and what proportion of these are attributable to cardiac causes.\n\nMethodsAll patients undergoing PCI in England between 1st January 2017 and 10th May 2020 were retrospectively analysed (n=273,141), according to their outcome from the date of PCI; no death and in-hospital, post-discharge, and 30-day death.\n\nResultsThe overall rates of in-hospital and 30-day death were 1.9% and 2.8%, respectively. The rate of 30-day death declined between 2017 (2.9%) and February 2020 (2.5%), mainly due to lower in-hospital death (2.1% vs. 1.5%), before rising again from 1st March 2020 (3.2%) due to higher rates of post-discharge mortality. Only 59.6% of 30-day deaths were due to cardiac causes, the most common being acute coronary syndrome, cardiogenic shock and heart failure, and this persisted throughout the study period. 10.4% of 30-day deaths after 1st March 2020 were due to confirmed COVID-19.\n\nConclusionsIn this nationwide study, we show that 40% of 30-day deaths are due to non-cardiac causes. Non-cardiac deaths have increased even more from the start of the COVID-19 pandemic, with one in ten deaths from March 2020 being COVID-19 related. These findings raise a question of whether public reporting of PCI outcomes should be cause-specific.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Joseph V Thompson", - "author_inst": "Royal Oldham Hospital" - }, - { - "author_name": "Nevan Meghani", - "author_inst": "Royal Oldham Hospital" - }, - { - "author_name": "Bethan M Powell", - "author_inst": "Royal Oldham Hospital" + "author_name": "Mohamed O Mohamed", + "author_inst": "Keele Cardiovascular Research Group, Keele University, United Kingdom" }, { - "author_name": "Ian Newell", - "author_inst": "Royal Oldham Hospital" + "author_name": "Tim Kinnaird", + "author_inst": "University hospital of Wales, Cardiff, Wales, UK" }, { - "author_name": "Roanna Craven", - "author_inst": "Royal Oldham Hospital" + "author_name": "Nick Curzen", + "author_inst": "Wessex Cardiothoracic Unit, Southampton University Hospital Southampton & Faculty of Medicine University of Southampton, UK" }, { - "author_name": "Gemma Skilton", - "author_inst": "Royal Oldham Hospital" + "author_name": "Peter Ludman", + "author_inst": "Institute of Cardiovascular Sciences, University of Birmingham, Birmingham, UK" }, { - "author_name": "Lydia J Bagg", - "author_inst": "Royal Oldham Hospital" + "author_name": "Jianhua Wu", + "author_inst": "University of Leeds" }, { - "author_name": "Irha Yaqoob", - "author_inst": "Royal Oldham Hospital" + "author_name": "Muhammad Rashid", + "author_inst": "Keele Cardiovascular Research Group, Centre for Prognosis Research, Keele University, United Kingdom" }, { - "author_name": "Michael J Dixon", - "author_inst": "Royal Oldham Hospital" + "author_name": "Ahmad Shoaib", + "author_inst": "Keele Cardiovascular Research Group, Centre for Prognosis Research, Keele University, United Kingdom" }, { - "author_name": "Eleanor J Evans", - "author_inst": "Royal Oldham Hospital" + "author_name": "Mark de Belder", + "author_inst": "National Institute for Cardiovascular Outcomes Research, Barts Health NHS Trust, London, UK" }, { - "author_name": "Belina Kambele", - "author_inst": "Royal Oldham Hospital" + "author_name": "John Deanfield", + "author_inst": "Institute of Cardiovascular Sciences, University College London, UK" }, { - "author_name": "Asif Rehman", - "author_inst": "Royal Oldham Hospital" + "author_name": "Chris Gale", + "author_inst": "Leeds Institute for Data analytics, University of Leeds, Leeds, UK" }, { - "author_name": "Georges Ng Man Kwong", - "author_inst": "Royal Oldham Hospital" + "author_name": "Mamas A Mamas", + "author_inst": "Keele Cardiovascular Research Group, Centre for Prognosis Research, Keele University, United Kingdom" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2020.07.25.20161661", @@ -1298355,43 +1298405,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.07.27.222901", - "rel_title": "Evolution And Genetic Diversity Of SARSCoV-2 In Africa Using Whole Genome Sequences", + "rel_doi": "10.1101/2020.07.26.222117", + "rel_title": "Predicting the Emergence of SARS-CoV-2 Clades", "rel_date": "2020-07-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.27.222901", - "rel_abs": "The ongoing SARSCoV-2 pandemic was introduced into Africa on 14th February 2020 and has rapidly spread across the continent causing severe public health crisis and mortality. We investigated the genetic diversity and evolution of this virus during the early outbreak months using whole genome sequences. We performed; recombination analysis against closely related CoV, Bayesian time scaled phylogeny and investigated spike protein amino acid mutations. Results from our analysis showed recombination signals between the AfrSARSCoV-2 sequences and reference sequences within the N and S genes. The evolutionary rate of the AfrSARSCoV-2 was 4.133 x 10-4 high posterior density HPD (4.132 x 10-4 to 4.134 x 10-4) substitutions/site/year. The time to most recent common ancestor TMRCA of the African strains was December 7th 2019. The AfrSARCoV-2 sequences diversified into two lineages A and B with B being more diverse with multiple sub-lineages confirmed by both maximum clade credibility MCC tree and PANGOLIN software. There was a high prevalence of the D614-G spike protein amino acid mutation (82.61%) among the African strains. Our study has revealed a rapidly diversifying viral population with the G614 spike protein variant dominating, we advocate for up scaling NGS sequencing platforms across Africa to enhance surveillance and aid control effort of SARSCoV-2 in Africa.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.26.222117", + "rel_abs": "Evolution is a process of change where mutations in the viral RNA are selected based on their fitness for replication and survival. Given that current phylogenetic analysis of SARS-CoV-2 identifies new viral clades after they exhibit evolutionary selections, one wonders whether we can identify the viral selection and predict the emergence of new viral clades? Inspired by the Kolmogorov complexity concept, we propose a generative complexity (algorithmic) framework capable to analyze the viral RNA sequences by mapping the multiscale nucleotide dependencies onto a state machine, where states represent subsequences of nucleotides and state-transition probabilities encode the higher order interactions between these states. We apply computational learning and classification techniques to identify the active state-transitions and use those as features in clade classifiers to decipher the transient mutations (still evolving within a clade) and stable mutations (typical to a clade). As opposed to current analysis tools that rely on the edit distance between sequences and require sequence alignment, our method is computationally local, does not require sequence alignment and is robust to random errors (substitution, insertions and deletions). Relying on the GISAID viral sequence database, we demonstrate that our method can predict clade emergence, potentially aiding with the design of medications and vaccines.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Babatunde Olanrewaju Motayo", - "author_inst": "Federal Medical Center, Abeokuta" - }, - { - "author_name": "Olukunle O Oluwasemowo", - "author_inst": "University of Ibadan" - }, - { - "author_name": "Paul A Akinduti", - "author_inst": "Covenant University, Otta, Nigeria" + "author_name": "Siddharth Jain", + "author_inst": "California Institute of Technology" }, { - "author_name": "Babatunde A Olusola", - "author_inst": "University of Ibadan, Nigeria" + "author_name": "Xiongye Xiao", + "author_inst": "University of Southern California" }, { - "author_name": "Olumide T Arege", - "author_inst": "University of Ibadan, Nigeria" + "author_name": "Paul Bogdan", + "author_inst": "University of Southern California" }, { - "author_name": "Adedayo O Faneye", - "author_inst": "University of Ibadan, Nigeria" + "author_name": "Jehoshua Bruck", + "author_inst": "Caltech" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.07.27.223578", @@ -1300837,153 +1300879,49 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.21.20125138", - "rel_title": "Viral RNA level, serum antibody responses, and transmission risk in discharged COVID-19 patients with recurrent positive SARS-CoV-2 RNA test results: a population-based observational cohort study", + "rel_doi": "10.1101/2020.07.23.20154369", + "rel_title": "Potential impact of individual exposure histories to endemic human coronaviruses on age-dependence in severity of COVID-19", "rel_date": "2020-07-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.21.20125138", - "rel_abs": "SummaryO_ST_ABSBackgroundC_ST_ABSManaging discharged COVID-19 (DC) patients with recurrent positive (RP) SARS-CoV-2 RNA test results is challenging. We aimed to comprehensively characterize the viral RNA level and serum antibody responses in RP-DC patients and evaluate their viral transmission risk.\n\nMethodsA population-based observational cohort study was performed on 479 DC patients discharged from February 1 to May 5, 2020 in Shenzhen, China. We conducted RT-qPCR, antibody assays, neutralisation assays, virus isolation, whole genome sequencing (WGS), and epidemiological investigation of close contacts.\n\nFindingsOf 479 DC patients, the 93 (19%) RP individuals, including 36 with multiple RP results, were characterised by young age (median age: 34 years, 95% confidence interval [CI]: 29-38 years). The median discharge-to-RP length was 8 days (95% CI: 7-14 days; maximum: 90 days). After readmission, RP-DC patients exhibited mild (28%) or absent (72%) symptoms, with no disease progression. The viral RNA level in RP-DC patients ranged from 1{middle dot}9-5{middle dot}7 log10 copies/mL (median: 3{middle dot}2, 95% CI: 3{middle dot}1-3{middle dot}5). At RP detection, the IgM, IgG, IgA, total antibody, and neutralising antibody (NAb) seropositivity rates in RP-DC patients were 38% (18/48), 98% (47/48), 63% (30/48), 100% (48/48), and 91% (39/43), respectively. Regarding antibody levels, there was no significant difference between RP-DC and non-RP-DC patients. The antibody level remained constant in RP-DC patients pre- and post-RP detection. Virus isolation of nine representative specimens returned negative results. WGS of six specimens yielded only genomic fragments. No clinical symptoms were exhibited by 96 close contacts of 23 RP-DC patients; their viral RNA (96/96) and antibody (20/20) test results were negative. After full recovery, 60% of patients (n=162, 78 no longer RP RP-DC and 84 non-RP-DC) had NAb titres of [≥]1:32.\n\nInterpretationRP may occur in DC patients following intermittent and non-stable excretion of low viral RNA levels. RP-DC patients pose a low risk of transmitting SARS-CoV-2. An NAb titre of [≥] 1:32 may provide a reference indicator for evaluating humoral responses in COVID-19 vaccine clinical trials.\n\nFundingSanming Project of Medicine in Shenzhen, China National Science and Technology Major Projects Foundation, Special Foundation of Science and Technology Innovation Strategy of Guangdong Province of China, and Shenzhen Committee of Scientific and Technical Innovation grants.", - "rel_num_authors": 35, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20154369", + "rel_abs": "Cross-reactivity to SARS-CoV-2 from previous exposure to endemic coronaviruses (eHCoV) is gaining increasing attention as a possible driver of both protection against infection and severity of COVID-19 disease. Here, we use a stochastic individual-based model to show that heterogeneities in individual exposure histories to endemic coronaviruses are able to explain observed age patterns of hospitalisation due to COVID-19 in EU/EEA countries and the UK, provided there is (i) a decrease in cross-protection to SARS-CoV-2 with the number of eHCoV exposures and (ii) an increase in potential disease severity with number of eHCoV exposures or as a result of immune senescence. We also show that variation in health care capacity and testing efforts is compatible with country-specific differences in hospitalisation rates. Our findings call for further research on the role of cross-reactivity to endemic coronaviruses and highlight potential challenges arising from heterogeneous health care capacity and testing.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Chao Yang", - "author_inst": "Shenzhen Centre for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Min Jiang", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Xiaohui Wang", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Xiujuan Tang", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Shisong Fang", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Hao Li", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Le Zuo", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Yixiang Jiang", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Yifan Zhong", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Qiongcheng Chen", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Chenli Zheng", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Lei Wang", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Shuang Wu", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Weihua Wu", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Hui Liu", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Jing Yuan", - "author_inst": "State Key Discipline of Infectious Disease, National Clinical Research Center for infectious disease, Shenzhen Third People's Hospital, Second Hospital Affiliat" - }, - { - "author_name": "Xuejiao Liao", - "author_inst": "State Key Discipline of Infectious Disease, National Clinical Research Center for infectious disease, Shenzhen Third People's Hospital, Second Hospital Affiliat" - }, - { - "author_name": "Zhen Zhang", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Yiman Lin", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Yijie Geng", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Huan Zhang", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangdong, China" - }, - { - "author_name": "Huanying Zheng", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangdong, China" - }, - { - "author_name": "Min Wan", - "author_inst": "Shenzhen LongHua District Maternity and Child Healthcare Hospital, Shenzhen, China" - }, - { - "author_name": "Linying Lu", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Xiaohu Ren", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" - }, - { - "author_name": "Yujun Cui", - "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China" - }, - { - "author_name": "Xuan Zou", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" + "author_name": "Francesco Pinotti", + "author_inst": "University of Oxford" }, { - "author_name": "Tiejian Feng", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" + "author_name": "Paul S Wikramaratna", + "author_inst": "No Affiliation" }, { - "author_name": "Junjie Xia", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" + "author_name": "Uri Obolski", + "author_inst": "Tel Aviv University" }, { - "author_name": "Ruifu Yang", - "author_inst": "State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China" + "author_name": "Robert Paton", + "author_inst": "University of Oxford" }, { - "author_name": "Yingxia Liu", - "author_inst": "State Key Discipline of Infectious Disease, National Clinical Research Center for infectious disease, Shenzhen Third People's Hospital, Second Hospital Affiliat" + "author_name": "Daniel Santa Cruz Damineli", + "author_inst": "Universidade de Sao Paulo" }, { - "author_name": "Shujiang Mei", - "author_inst": "Shenzhen Center for Disease Control and Prevention" + "author_name": "Luiz Carlos Junior Alcantara", + "author_inst": "Oswaldo Cruz Foundation" }, { - "author_name": "Baisheng Li", - "author_inst": "Guangdong Provincial Center for Disease Control and Prevention, Guangdong, China" + "author_name": "Marta Giovanetti", + "author_inst": "Fundacao Oswaldo Cruz" }, { - "author_name": "Zhengrong Yang", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" + "author_name": "Sunetra Gupta", + "author_inst": "University of Oxford" }, { - "author_name": "Qinghua Hu", - "author_inst": "Shenzhen Center for Disease Control and Prevention, Shenzhen, China" + "author_name": "Jos\u00e9 Louren\u00e7o", + "author_inst": "University of Oxford" } ], "version": "1", @@ -1302443,127 +1302381,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.21.20159053", - "rel_title": "Prospective Observational Study of Screening Asymptomatic Healthcare Workers for SARS-CoV-2 at a Canadian Tertiary Care Center", + "rel_doi": "10.1101/2020.07.22.20158352", + "rel_title": "Anatomy of digital contact tracing: role of age, transmission setting, adoption and case detection", "rel_date": "2020-07-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.21.20159053", - "rel_abs": "We screened three separate cohorts of healthcare workers for SARS-CoV-2 via nasopharyngeal swab PCR. A seroprevalence analysis using multiple assays was performed in a subgroup. The asymptomatic health care worker cohorts had a combined swap positivity rate of 29/5776 (0.50%, 95%CI 0.32-0.75) compared to the symptomatic cohort rate of 54/1597 (3.4%) (ratio of symptomatic to asymptomatic 6.8:1). Sequencing demonstrated several variants. The seroprevalence (n=996) was 1.4-3.4% depending on assay. Protein microarray analysis showed differing SARS-CoV-2 protein reactivities and helped define likely true positives vs. suspected false positives. Routine screening of asymptomatic health care workers helps identify a significant proportion of infections.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.22.20158352", + "rel_abs": "The efficacy of digital contact tracing against COVID-19 epidemic is debated: smartphone penetration is limited in many countries, non-uniform across age groups, with low coverage among elderly, the most vulnerable to SARS-CoV-2. We developed an agent-based model to precise the impact of digital contact tracing and household isolation on COVID-19 transmission. The model, calibrated on French population, integrates demographic, contact-survey and epidemiological information to describe the risk factors for exposure and transmission of COVID-19. We explored realistic levels of case detection, app adoption, population immunity and transmissibility. Assuming a reproductive ratio R = 2.6 and 50% detection of clinical cases, a ~20% app adoption reduces peak incidence by ~35%. With R = 1.7, >30% app adoption lowers the epidemic to manageable levels. Higher coverage among adults, playing a central role in COVID-19 transmission, yields an indirect benefit for elderly. These results may inform the inclusion of digital contact tracing within a COVID-19 response plan.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Deepali Kumar", - "author_inst": "University Health Network" + "author_name": "Jes\u00fas A. Moreno L\u00f3pez", + "author_inst": "INSERM, Sorbonne Universit\u00e9; Instituto de F\u00edsica Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB)" }, { - "author_name": "Victor H Ferreira", - "author_inst": "University Health Network, Toronto, Canada" + "author_name": "Beatriz Arregui-Garc\u013aa", + "author_inst": "INSERM, Sorbonne Universit\u00e9; Instituto de F\u00edsica Interdisciplinar y Sistemas Complejos IFISC (CSIC-UIB)" }, { - "author_name": "Andrzej Chruscinski", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Vathany Kulasingam", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Trevor J Pugh", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Tamara Dus", - "author_inst": "University Health Network, Toronto, Canada" + "author_name": "Piotr Bentkowski", + "author_inst": "INSERM, Sorbonne Universit\u00e9" }, { - "author_name": "Brad Wouters", - "author_inst": "University Health Network, Toronto, Canada" + "author_name": "Livio Bioglio", + "author_inst": "Department of Computer Science, University of Turin" }, { - "author_name": "Amit Oza", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Matthew Ierullo", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Terrance J.Y. Ku", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Beata Majchrzak-Kita", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Sonika Humar", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Ilona Bahinskaya", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Natalia Pinzon", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Jianhua Zhang", - "author_inst": "University Health Network, Toronto, Canada" - }, - { - "author_name": "Lawrence E Heisler", - "author_inst": "Ontario Institute for Cancer Research, Toronto, Canada" - }, - { - "author_name": "Paul M Krzyzanowski", - "author_inst": "Ontario Institute for Cancer Research, Toronto, Canada" - }, - { - "author_name": "Bernard Lam", - "author_inst": "Ontario Institute for Cancer Research, Toronto, Canada" - }, - { - "author_name": "Ilinca M Lungu", - "author_inst": "Ontario Institute for Cancer Research, Toronto, Canada" - }, - { - "author_name": "Dorin Manase", - "author_inst": "University Health Network Digital Department, Toronto, Canada" - }, - { - "author_name": "Krista M Pace", - "author_inst": "University Health Network Digital Department, Toronto, Canada" - }, - { - "author_name": "Pouria Mashouri", - "author_inst": "University Health Network Digital Department,Toronto, Canada" - }, - { - "author_name": "Michael Brudno", - "author_inst": "University Health Network Digital Department, Toronto, Canada" + "author_name": "Francesco Pinotti", + "author_inst": "INSERM, Sorbonne Universit\u00e9" }, { - "author_name": "Michael Garrels", - "author_inst": "University Health Network, Toronto, Canada" + "author_name": "Pierre-Yves Bo\u00eblle", + "author_inst": "INSERM, Sorbonne Universit\u00e9" }, { - "author_name": "Tony Mazzulli", - "author_inst": "Sinai Health System, Toronto, Canada" + "author_name": "Alain Barrat", + "author_inst": "Aix Marseille Univ, Universite de Toulon, CNRS, CPT, Turing Center for Living Systems" }, { - "author_name": "Myron Cybulsky", - "author_inst": "University Health Network, Toronto, Canada" + "author_name": "Vittoria Colizza", + "author_inst": "INSERM, Sorbonne Universit\u00e9" }, { - "author_name": "Atul Humar", - "author_inst": "University Health Network, Toronto, Canada" + "author_name": "Chiara Poletto", + "author_inst": "INSERM, Sorbonne Universit\u00e9" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.07.20.20158238", @@ -1303989,35 +1303855,71 @@ "category": "neurology" }, { - "rel_doi": "10.1101/2020.07.21.20159327", - "rel_title": "COVID-19 Vulnerability of Transgender Women With and Without HIV Infection in the Eastern and Southern U.S.", + "rel_doi": "10.1101/2020.07.21.20159392", + "rel_title": "Development of a quantum-dot lateral flow immunoassay strip based portable fluorescence smart-phone system for ultrasensitive detection of IgM/IgG to SARS-CoV-2", "rel_date": "2020-07-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.21.20159327", - "rel_abs": "BackgroundCOVID-19 is a new global pandemic and people with HIV may be particularly vulnerable. Gender identity is not reported, therefore data are absent on the impact of COVID-19 on transgender people, including transgender people with HIV. Baseline data from the American Cohort to Study HIV Acquisition Among Transgender Women in High Risk Areas (LITE) Study provide an opportunity to examine pre-COVID vulnerability among transgender women.\n\nSettingAtlanta, Baltimore, Boston, Miami, New York City, Washington, DC\n\nMethodsBaseline data from LITE were analysed for demographic, psychosocial, and material factors that may affect risk for COVID-related harms.\n\nResultsThe 1020 participants had high rates of poverty, unemployment, food insecurity, homelessness, and sex work. Transgender women with HIV (n=273) were older, more likely to be Black, had lower educational attainment, and were more likely to experience material hardship. Mental and behavioural health symptoms were common and did not differ by HIV status. Barriers to healthcare included being mistreated mistreatment, uncomfortable providers, and past negative experiences; as well as material hardships, such as cost and transportation. However, most reported access to material and social support - demonstrating resilience.\n\nConclusionsTransgender women with HIV may be particularly vulnerable to pandemic harms. Mitigating this harm would have positive effects for everyone, given the highly infectious nature of this coronavirus. Collecting gender identity in COVID-19 data is crucial to inform an effective public health response. Transgender-led organizations response to this crisis serve as an important model for effective community-led interventions.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.21.20159392", + "rel_abs": "BackgroundSince December 2019, the outbreak of coronavirus disease (COVID-19) has been occurred by novel coronavirus (SARS-CoV-2). The rapid and sensitive immunoassays are urgently demanded for detecting specific antibodies as assistant diagnosis for primary screening of asymptomatic individuals, close contacts, suspected or recovered patients of COIVD-19 during the pandemic period.\n\nMethodsThe recombinant receptor binding domain of SARS-CoV-2 spike protein (S-RBD) was used as the antigen to detect specific IgM and the mixture of recombinant nucleocapsid phosphoprotein (NP) and S-RBD were used to detect specific IgG by the newly designed quantum-dot lateral flow immunoassay strip (QD-LFIA), respectively.\n\nResultsA rapid and sensitive QD-LFIA based portable fluorescence smart-phone system was developed for detecting specific IgM/IgG to SARS-CoV-2 from 100 serum samples of COVID-19 patients and 450 plasma samples from healthy blood donors. Among 100 COVID-19 patients diagnosed with NAT previously, 3 were severe, 35 mild and 62 recovered cases. By using QD-LFIA, 78 (78%) and 99 (99%) samples from 100 COVID-19 patients serum were detected positive for anti-SARS-CoV-2 IgM or IgG, respectively, but only one sample (0.22%) was cross-reactive with S-RBD from 450 healthy blood donor plasmas that were collected from different areas of China.\n\nConclusionAn ultrasensitive and specific QD-LFIA based portable fluorescence smart-phone system was developed fo r detection of specific IgM and IgG to SARS-CoV-2 infection, which could be used for investigating the prevalence or assistant diagnosis of COVID-19 in humans.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Tonia Poteat", - "author_inst": "Department of Social Medicine, University of North Carolina at Chapel Hill" + "author_name": "Bochao Liu", + "author_inst": "Southern Medical University" }, { - "author_name": "Sari Reisner", - "author_inst": "Department of Medicine, Harvard Medical School; Department of Epidemiology, Harvard T.H. Chan School of Public Health" + "author_name": "Jinfeng Li", + "author_inst": "Shenzhen Center for Disease Control and Prevention" }, { - "author_name": "Marissa Miller", - "author_inst": "TransSolutions LLC" + "author_name": "Xi Tang", + "author_inst": "The First People Hospital of Foshan" }, { - "author_name": "Andrea Wirtz", - "author_inst": "Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health" + "author_name": "Ze Wu", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Jinhui Lu", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Chaolan Liang", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Shuiping Hou", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Ling Zhang", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Tingting Li", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Wei Zhao", + "author_inst": "Southern Medical University" + }, + { + "author_name": "Yongshui Fu", + "author_inst": "Guangzhou Blood Center" + }, + { + "author_name": "Yuebin Ke", + "author_inst": "Shenzhen Center for Disease Control and Prevention" + }, + { + "author_name": "Chengyao Li", + "author_inst": "Southern medical university" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "hiv aids" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.07.21.20159244", @@ -1305395,27 +1305297,39 @@ "category": "gastroenterology" }, { - "rel_doi": "10.1101/2020.07.23.20160879", - "rel_title": "Factors associated with psychological distress in health-care workers during an infectious disease outbreak: A rapid living systematic review", + "rel_doi": "10.1101/2020.07.24.20161422", + "rel_title": "Adherence to protective measures among health care workers in the UK; a cross-sectional study", "rel_date": "2020-07-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20160879", - "rel_abs": "BackgroundHealth-care workers (HCW) are at risk for psychological distress during an infectious disease outbreak due to the demands of dealing with a public health emergency.\n\nAimsTo examine the factors associated with psychological distress among HCW during an outbreak.\n\nMethodWe systematically reviewed literature on the factors associated with psychological distress (demographic characteristics, occupational, social, psychological, and infection-related factors) in HCW during an outbreak (COVID-19, SARS, MERS, H1N1, H7N9, Ebola). Four electronic databases were searched (2000 to 10 July 2020) for relevant peer-reviewed research according to a pre-registered protocol. A narrative synthesis was conducted to identify fixed, modifiable, and infection-related factors.\n\nResultsFrom the 3335 records identified, 52 with data from 54,800 HCW were included. All but two studies were cross-sectional. Consistent evidence indicated that being female, a nurse, experiencing stigma, maladaptive coping, having contact or risk for contact with infected patients, and being quarantined, were risk factors for psychological distress among HCW. Personal and organisational social support, perceiving control, positive work attitudes, sufficient information about the outbreak and proper protection, training and resources, were associated with less psychological distress.\n\nConclusionsHCW who may be most at risk for psychological distress during an outbreak require early intervention and ongoing monitoring as there is some evidence that HCW distress can persist for years after an outbreak. Further research is needed to track the associations of risk factors with distress over time and the extent to which certain factors are inter-related and linked to sustained or transient distress.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.24.20161422", + "rel_abs": "Healthcare workers (HCWs) are frontline responders to emergency infectious disease outbreaks such as COVID-19. We investigated factors associated with adherence to personal protective behaviours in UK HCWs during the COVID-19 pandemic using an online cross-sectional survey of 1035 healthcare professionals in the UK. Data were collected between 12th and 16th June 2020. Adjusted logistic regressions were used to separately investigate factors associated with adherence to use of personal protective equipment, maintaining good hand hygiene, and physical distancing from colleagues. Adherence to personal protective measures was suboptimal (PPE use: 80.0%, 95% CI [77.3 to 82.8], hand hygiene: 67.8%, 95% CI [64.6 to 71.0], coming into close contact with colleagues: 74.7%, 95% CI [71.7 to 77.7]). Adherence to PPE use was associated with having adequate PPE resources, receiving training during the pandemic, lower perceived fatalism from COVID-19, higher perceived social norms and higher perceived effectiveness of PPE. Adherence to physical distancing was associated with ones workplace being designed, using markings to facilitate physical distancing and receiving training during the pandemic. There were few associations with adherence to hand hygiene. Findings indicate HCWs should receive training on personal protective behaviours to decrease fatalism over contracting COVID-19 and increase perceived effectiveness of protective measures.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Fuschia M Sirois", - "author_inst": "University of Sheffield" + "author_name": "Louise E. Smith", + "author_inst": "King's College London" }, { - "author_name": "Janine Owens", - "author_inst": "University of Sheffield" + "author_name": "Danai Serfioti", + "author_inst": "King's College London" + }, + { + "author_name": "Dale Weston", + "author_inst": "Public Health England" + }, + { + "author_name": "Neil Greenberg", + "author_inst": "King's College London" + }, + { + "author_name": "G James Rubin", + "author_inst": "King's College London" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.07.24.20161364", @@ -1306849,59 +1306763,67 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.22.20160283", - "rel_title": "Heat-based Decontamination of N95 Masks Using a Commercial Laundry Dryer", + "rel_doi": "10.1101/2020.07.23.20159871", + "rel_title": "Geographic reconstruction of the SARS-CoV-2 outbreak in Lombardy (Italy) during the early phase", "rel_date": "2020-07-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.22.20160283", - "rel_abs": "We propose a dry heat method for decontaminating N95 masks of SARS-CoV-2, designed around placing them in resealable plastic bags, packed in large cardboard boxes installed at the rear end of commercial laundry dryers. Our protocol rests on data collected in collaboration with Alliance Laundry Systems (ALS) and the CDC/NIOSH laboratories, under the \"NPPTL Respirator Assessments to Support the COVID-19 Response\" initiative. We test the two most widely available ALS tumbler models, the UTF75N and UT075N, and show that if our procedure is carefully followed, the masks will be subject to suitably high and stable temperatures for decontamination; in particular the masks will be heated to at least 80 {degrees}C for at least 65 min. For the mask models 3M 1860, 3M 8511, and Halyard 62126, we establish that they pass quantitative fit tests and retain sufficient filtration performance after three cycles of our decontamination procedure. All masks used in this study were new and uncontaminated: the evidence for the levels of biological inactivation of SARS-CoV-2 is provided by [1]. While the protocol outlined here is currently specific to certain tested dryer models, this equipment is widely available, with machines estimated to be within 15 minutes of most US hospitals. Models from other manufacturers may also be appropriate for this decontamination method, though we stress the need for explicit testing on alternative models before use.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.23.20159871", + "rel_abs": "The circulation of SARS-CoV-2 in Italy has been dominated by two large clusters of outbreaks in Northern part of the peninsula, source of alarming and prolonged infections in Lombardy region, in Codogno and Bergamo areas especially.\n\nThe aim of the study was to expand understanding on the circulation of SARS-CoV-2 in the affected Lombardy areas. To this purpose, twenty full length genomes were collected from patients addressing to several Lombard hospitals from February 20th to April 4th, 2020.\n\nThe obtained genome assemblies, available on the GISAD database and performed at the Referral Center for COVID-19 diagnosis, identified 2 main monophyletic clades, containing 9 and 52 isolates, respectively.\n\nThe molecular clock analysis estimated a clusters divergence approximately one month before the first patient identification, supporting the hypothesis that different SARS-CoV-2 strains spread all over the world at different time, but their presence became evident only in late February along with Italian epidemic emergence.\n\nTherefore, the epidemiological reconstruction carried out by this work highlights multiple inputs of the virus into its initial circulation in Lombardy Region.\n\nHowever, a phylogenetic reconstruction robustness will be improved when other genomic sequences will be available, in order to guarantee a complete epidemiological surveillance.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Yuri D. Lensky", - "author_inst": "Stanford University" + "author_name": "Valeria Micheli", + "author_inst": "ASST Fatebenefratelli Sacco, L.Sacco Hospital" }, { - "author_name": "Edward Mazenc", - "author_inst": "Stanford University" + "author_name": "Sara Giordana Rimoldi", + "author_inst": "ASST Fatebenefratelli Sacco, L.Sacco Hospital" }, { - "author_name": "Daniel Ranard", - "author_inst": "Stanford University" + "author_name": "Francesca Romeri", + "author_inst": "ASST Fatebenefratelli Sacco, L.Sacco Hospital" }, { - "author_name": "Matthew Vilim", - "author_inst": "Stanford University" + "author_name": "Francesco Comandatore", + "author_inst": "University of Milan" }, { - "author_name": "Manu Prakash", - "author_inst": "Stanford University" + "author_name": "Alessandro Mancon", + "author_inst": "ASST Fatebenefratelli Sacco, L.Sacco Hospital" }, { - "author_name": "Bill Brooks", - "author_inst": "Alliance Laundry Systems" + "author_name": "Anna Gigantiello", + "author_inst": "ASST Fatebenefratelli Sacco, L.Sacco Hospital" }, { - "author_name": "Amanda Bradley", - "author_inst": "Alliance Laundry Systems" + "author_name": "Matteo Brilli", + "author_inst": "University of Milan" + }, + { + "author_name": "Davide Mileto", + "author_inst": "ASST Fatebenefratelli Sacco, L.Sacco Hospital" + }, + { + "author_name": "Cristina Pagani", + "author_inst": "ASST Fatebenefratelli Sacco, L.Sacco Hospital" }, { - "author_name": "Alain Engelschenschilt", - "author_inst": "Alliance Laundry Systems" + "author_name": "Alessandra Lombardi", + "author_inst": "ASST Fatebenefratelli Sacco, L.Sacco Hospital" }, { - "author_name": "Jason Plutz", - "author_inst": "Alliance Laundry Systems" + "author_name": "Maria Rita Gismondo", + "author_inst": "ASST Fatebenefratelli Sacco, L.Sacco Hospital" }, { - "author_name": "Todd Zellmer", - "author_inst": "Alliance Laundry Systems" + "author_name": "- Laboratory of Clinical Microbiology, Virology and Diagnostic of Bioemergencies Group", + "author_inst": "" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.07.22.20159905", @@ -1308355,59 +1308277,123 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.07.23.212357", - "rel_title": "Single-dose intranasal vaccination elicits systemic and mucosal immunity against SARS-CoV-2", + "rel_doi": "10.1101/2020.07.23.217430", + "rel_title": "SARS-CoV2 genome analysis of Indian isolates and molecular modelling of D614G mutated spike protein with TMPRSS2 depicted its enhanced interaction and virus infectivity", "rel_date": "2020-07-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.23.212357", - "rel_abs": "A safe and durable vaccine is urgently needed to tackle the COVID19 pandemic that has infected >15 million people and caused >620,000 deaths worldwide. As with other respiratory pathogens, the nasal compartment is the first barrier that needs to be breached by the SARS-CoV-2 virus before dissemination to the lung. Despite progress at remarkable speed, current intramuscular vaccines are designed to elicit systemic immunity without conferring mucosal immunity. We report the development of an intranasal subunit vaccine that contains the trimeric or monomeric spike protein and liposomal STING agonist as adjuvant. This vaccine induces systemic neutralizing antibodies, mucosal IgA responses in the lung and nasal compartments, and T-cell responses in the lung of mice. Single-cell RNA-sequencing confirmed the concomitant activation of T and B cell responses in a germinal center-like manner within the nasal-associated lymphoid tissues (NALT), confirming its role as an inductive site that can lead to long-lasting immunity. The ability to elicit immunity in the respiratory tract has can prevent the initial establishment of infection in individuals and prevent disease transmission across humans.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.23.217430", + "rel_abs": "COVID-19 that emerged as a global pandemic is caused by SARS-CoV-2 virus. The virus genome analysis during disease spread reveals about its evolution and transmission. We did whole genome sequencing of 225 clinical strains from the state of Odisha in eastern India using ARTIC protocol-based amplicon sequencing. Phylogenetic analysis identified the presence of all five reported clades 19A, 19B, 20A, 20B and 20C in the population. The analyses revealed two major routes for the introduction of the disease in India i.e. Europe and South-east Asia followed by local transmission. Interestingly, 19B clade was found to be much more prevalent in our sequenced genomes (17%) as compared to other genomes reported so far from India. The haplogroup analysis for clades showed evolution of 19A and 19B in parallel whereas the 20B and 20C appeared to evolve from 20A. Majority of the 19A and 19B clades were present in cases that migrated from Gujarat state in India suggesting it to be one of the major initial points of disease transmission in India during month of March and April. We found that with the time 20A and 20B clades evolved drastically that originated from central Europe. At the same time, it has been observed that 20A and 20B clades depicted selection of four common mutations i.e. 241 C>T (5UTR), P323L in RdRP, F942F in NSP3 and D614G in the spike protein. We found an increase in the concordance of G614 mutation evolution with the viral load in clinical samples as evident from decreased Ct value of spike and Orf1ab gene in qPCR. Molecular modelling and docking analysis identified that D614G mutation enhanced interaction of spike with TMPRSS2 protease, which could impact the shedding of S1 domain and infectivity of the virus in host cells.", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Xingyue An", - "author_inst": "University of Houston" + "author_name": "Sunil Raghav", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" }, { - "author_name": "Melisa Paniagua Martinez", - "author_inst": "University of Houston" + "author_name": "Arup Ghosh", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" }, { - "author_name": "Ali Rezvan", - "author_inst": "University of Houston" + "author_name": "Jyotirmayee Turuk", + "author_inst": "Regional Medical Research Centre (RMRC), Bhubaneswar" }, { - "author_name": "Mohsen Fathi", - "author_inst": "University of Houston" + "author_name": "Sugandh Kumar", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" }, { - "author_name": "Shailbala Singh", - "author_inst": "University of Texas M.D. Anderson Cancer Center" + "author_name": "Atimukta Jha", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" }, { - "author_name": "Sujit Biswas", - "author_inst": "University of Houston" + "author_name": "Swati Madhulika", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" }, { - "author_name": "Melissa Pourpak", - "author_inst": "BD Biosciences" + "author_name": "Manasi Priyadarshini", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" }, { - "author_name": "Cassian Yee", - "author_inst": "University of Texas M.D. Anderson Cancer Center" + "author_name": "Viplov K Biswas", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" }, { - "author_name": "Xinli Liu", - "author_inst": "University of Houston" + "author_name": "P. Sushree Shyamli", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" }, { - "author_name": "Navin Varadarajan", - "author_inst": "University of Houston" + "author_name": "Bharati Singh", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Neha Singh", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Deepika Singh", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Avula Kiran", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Shuchi Smita", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Jyotsnamayee Sabat", + "author_inst": "Regional Medical Research Centre (RMRC), Bhubaneswar" + }, + { + "author_name": "Debdutta Bhattacharya", + "author_inst": "Regional Medical Research Centre (RMRC), Bhubaneswar" + }, + { + "author_name": "Rupesh Dash", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Shantibhushan Senapati", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Tushar K Beuria", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Rajeeb Swain", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Soma Chattopadhyay", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Gulam Hussain Syed", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Anshuman Dixit", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Punit Prasad", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" + }, + { + "author_name": "Sanghamitra Pati", + "author_inst": "Regional Medical Research Centre (RMRC), Bhubaneswar" + }, + { + "author_name": "Ajay Parida", + "author_inst": "Institute of Life Sciences (ILS), Bhubaneswar" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "genomics" }, { "rel_doi": "10.1101/2020.07.23.217174", @@ -1310125,31 +1310111,39 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.07.22.215590", - "rel_title": "Inadequate level of knowledge, mixed outlook and poor adherence to COVID-19 prevention guideline among Ethiopians", - "rel_date": "2020-07-22", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.22.215590", - "rel_abs": "COVID-19 has a potential to cause chaos in Ethiopia due to the countrys already daunting economic and social challenges. Living and working conditions are highly conducive for transmission, as people live in crowded inter-generational households that often lack running water and other basic sanitary facilities. Thus, the aim of this study was to investigate the knowledge, attitudes and practices (KAP) of Ethiopians toward COVID-19 following the introduction of state of emergency by the Ethiopian government to curb the spread of the disease. A cross-sectional study design was conducted in nine reginal states and two chartered cities. Data for demographic, Knowledge, attitude and practice toward COVID-19 were collected through telephone interview from 1570 participants. Descriptive and bivariate analyses using chi-square test, t-test or analysis of variance were performed as appropriate. Binary and multiple logistic regression analysis were used to measure the relationship between the categorical dependent variables and one or more socio-demographic independent variables with two-tailed at =0.05 significance level and 95% of confidence interval. The level of good knowledge, favourable attitude and good practice among the respondents were 42%, 53.8% and 24.3% respectively. Being rural resident, older than 50 years, having at least primary education, being resident of Amhara and Oromia regions were independent predictors of knowledge level. While being rural resident, married, employed, having at least basic education, being residents of Afar, Amhara, Gambela, Oromia and Somali regions were found to be the best predictors of the attitude, being rural resident, government employee, having at least basic education, and living outside of the capital were the independent predictors of practice level of the respondents. The finding revealed that Ethiopians have inadequate level of knowledge and are generally have a mixed outlook on overcoming the pandemic with poor adherence to COVID-19 prevention practice. reinforcing preventive measures and intensifying sensitization campaigns to fill the knowledge gap and persuading people to follow the preventive measures set by the government with concurrent evaluation of the impacts of these measures on knowledge and practice is highly recommended to mitigate the disease.", - "rel_num_authors": 3, + "rel_doi": "10.1101/2020.07.18.20156794", + "rel_title": "Statistical analysis of national & municipal corporation level database of COVID-19 cases In India", + "rel_date": "2020-07-21", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.18.20156794", + "rel_abs": "Since its origin in December 2019, Novel Coronavirus or COVID-19 has caused massive panic in the word by infecting millions of people with a varying fatality rate. The main objective of Governments worldwide is to control the extent of the outbreak until a vaccine or cure has been devised. Machine learning has been an efficient mechanism to train, map, analyze, and predict datasets. This paper aims to utilize regression, a supervised machine learning algorithm to assess time-series datasets of COVID-19 pandemic by performing comparative analysis on datasets of India and two Municipal Corporations of Maharashtra, namely, Mira-Bhayander and Akola. Current study is an attempt towards drawing attention to the dynamics and nature of the pandemic in a controlled locality such as Municipal Corporation; which differs from the exponential nature observed nationally. However, for limited area like the one considered the nature of curve is observed to be cubic for total cases and multi-peak Gaussian for active cases. In conclusion, Government should empower district/ corporations/local authorities to adopt their own methodology and decision-making policy to contain the pandemic at regional-level like the case study discussed herein.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Edessa Negera", - "author_inst": "Hawassa University and London School of Hygiene and Tropical Medicine" + "author_name": "Naman S. Bajaj", + "author_inst": "College Of Engineering Pune" }, { - "author_name": "Tesfaye Moti Demissie", - "author_inst": "University of Oxford" + "author_name": "Sujit S Pardeshi", + "author_inst": "College Of Engineering Pune" }, { - "author_name": "Ketema Tafess", - "author_inst": "Arsi University" + "author_name": "Abhishek D Patange", + "author_inst": "College Of Engineering Pune" + }, + { + "author_name": "Disha Kotecha", + "author_inst": "College Of Engineering Pune" + }, + { + "author_name": "Kavidas K Mate", + "author_inst": "Pimpri Chinchwad College of Engineering & Research, Ravet, Pune" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "animal behavior and cognition" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "health informatics" }, { "rel_doi": "10.1101/2020.07.19.20157164", @@ -1311579,91 +1311573,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.21.213777", - "rel_title": "Cellular events of acute, resolving or progressive COVID-19 in SARS-CoV-2 infected non-human primates", + "rel_doi": "10.1101/2020.07.20.213082", + "rel_title": "Discovery of potential imaging and therapeutic targets for severe inflammation in COVID-19 patients", "rel_date": "2020-07-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.21.213777", - "rel_abs": "We investigated the immune events following SARS-CoV-2 infection, from the acute inflammatory state up to four weeks post infection, in non-human primates (NHP) with heterogeneous pulmonary pathology. The acute phase was characterized by a robust and rapid migration of monocytes expressing CD16 from the blood and concomitant increase in CD16+ macrophages in the lungs. We identified two subsets of interstitial macrophages (HLA-DR+ CD206-), a transitional CD11c+ CD16+ cell population that was directly associated with IL-6 levels in plasma, and one long lasting CD11b+ CD16+ cell population. Strikingly, levels of monocytes were a correlate of viral replication in bronchial brushes and we discovered TARC (CCL17) as a new potential mediator of myeloid recruitment to the lungs. Worse disease outcomes were associated with high levels of cell infiltration in lungs including CD11b+ CD16hi macrophages and CD11b+ neutrophils. Accumulation of macrophages was long-lasting and detectable even in animals with mild or no signs of disease. Interestingly, animals with anti-inflammatory responses including high IL-10:IL-6 and kynurenine to tryptophan ratios had less signs of disease. Our results unravel cellular mechanisms of COVID-19 and suggest that NHP may be appropriate models to test immune therapies.", - "rel_num_authors": 18, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.20.213082", + "rel_abs": "The COVID-19 pandemic has caused more than 540,000 deaths globally. Hyperinflammation mediated by dysregulated monocyte/macrophage function is considered to be the key factor that triggers severe illness in COVID-19. However, no specific targeting molecule has been identified for detecting or treating hyperinflammation related to dysregulated macrophages in severe COVID-19. Herein, we suggest candidate targets for imaging and therapy in severe COVID-19 by analyzing single-cell RNA-sequencing data based on bronchoalveolar lavage fluid of COVID-19 patients. We found that expression of SLC2A3, which can be imaged by [18F]fluorodeoxyglucose, was higher in macrophages from severe COVID-19 patients. Furthermore, by integrating the surface target database and drug-target binding database with RNA-sequencing data of severe COVID-19, we identified CCR1 and FPR1 as surface and druggable targets for drug delivery as well as molecular imaging. Our results provide a resource for candidate targets in the development of specific imaging and therapy for COVID-19-related hyperinflammation.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Marissa D Fahlberg", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Robert V Blair", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Lara A Doyle-Meyers", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Cecily C Midkiff", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Giorgio Zenere", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Kasi E Russell-Lodrigue", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Christopher J Monjure", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Toni P Penney", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Gabrielle Lehmicke", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Brienna M Threeton", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Nadia Golden", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Presan K Datta", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Chad J Roy", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Rudolph P Bohm", - "author_inst": "Tulane National Primate Research Center, Covington, LA" - }, - { - "author_name": "Nicholas J Maness", - "author_inst": "Tulane National Primate Research Center, Covington, LA" + "author_name": "Hyunjong Lee", + "author_inst": "Seoul National University" }, { - "author_name": "Tracy Fischer", - "author_inst": "Tulane National Primate Research Center, Covington, LA" + "author_name": "Hyung-Jun Im", + "author_inst": "Seoul National University" }, { - "author_name": "Jay Rappaport", - "author_inst": "Tulane National Primate Research Center, Covington, LA" + "author_name": "Kwon Joong Na", + "author_inst": "Seoul National University Hospital" }, { - "author_name": "Monica Vaccari", - "author_inst": "Tulane National Primate Research Center, Covington, LA" + "author_name": "Hongyoon Choi", + "author_inst": "Seoul National University Hospital" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.07.21.213405", @@ -1313485,43 +1313423,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.18.210120", - "rel_title": "High expression of angiotensin-converting enzyme-2 (ACE2) on tissue macrophages that may be targeted by virus SARS-CoV-2 in COVID-19 patients", + "rel_doi": "10.1101/2020.07.12.20151878", + "rel_title": "Inverted covariate effects for mutated 2nd vs 1st waveCovid-19: high temperature spread biased for young", "rel_date": "2020-07-20", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.18.210120", - "rel_abs": "Angiotensin-converting enzyme-2 (ACE2) has been recognized as the binding receptor for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that infects host cells, causing the development of the new coronavirus infectious disease (COVID-19). To better understand the pathogenesis of COVID-19 and build up the host anti-viral immunity, we examined the levels of ACE2 expression on different types of immune cells including tissue macrophages. Flow cytometry demonstrated that there was little to no expression of ACE2 on most of the human peripheral blood-derived immune cells including CD4+ T, CD8+ T, activated CD4+ T, activated CD8+ T, CD4+CD25+CD127low/- regulatory T cells (Tregs), Th17 cells, NKT cells, B cells, NK cells, monocytes, dendritic cells (DCs), and granulocytes. Additionally, there was no ACE2 expression (< 1%) found on platelets. Compared with interleukin-4-treated type 2 macrophages (M2), the ACE2 expression was markedly increased on the activated type 1 macrophages (M1) after the stimulation with lipopolysaccharide (LPS). Immunohistochemistry demonstrated that high expressions of ACE2 were colocalized with tissue macrophages, such as alveolar macrophages found within the lungs and Kupffer cells within livers of mice. Flow cytometry confirmed the very low level of ACE2 expression on human primary pulmonary alveolar epithelial cells. These data indicate that alveolar macrophages, as the frontline immune cells, may be directly targeted by the SARS-CoV-2 infection and therefore need to be considered for the prevention and treatment of COVID-19.", - "rel_num_authors": 6, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.12.20151878", + "rel_abs": "(1) BackgroundHere, we characterize COVID-19 2nd waves, following a study presenting negative associations between 1st wave COVID-19 spread parameters and temperature;\n\n(2) MethodsVisual examinations of daily increase in confirmed COVID-19 cases in 124 countries, determined 1st and 2ndwaves in 28 countries;\n\n(3) Results1st wave spread rate increases with country mean elevation, temperature, time since wave onset, and median age. Spread rates decrease above 1000m, indicating high UV decrease spread rate. For 2nd waves, associations are opposite: viruses adapted to high temperature and to infect young populations. Earliest 2nd waves started April 5-7 at mutagenic high elevations (Armenia, Algeria). 2nd waves occurred also at warm-to-cold season transition (Argentina, Chile). Spread decreases in most (77%) countries. Death-to-total case ratios decrease during the 2ndwave, also when comparing with the same period for countries where the 1st wave is ongoing. In countries with late 1st wave onset, spread rates fit better 2nd than 1st wave-temperature patterns; In countries with ageing populations (examples: Japan, Sweden, Ukraine), 2nd waves only adapted to spread at higher temperatures, not to infect children.\n\n(4) Conclusions1st wave viruses evolved towards lower spread and mortality. 2nd wave mutant COVID-19 strain(s) adapted to higher temperature, infecting children and replace (also in cold conditions) 1st wave COVID-19 strains. Counterintuitively, low spread strains replace high spread strains, rendering prognostics and extrapolations uncertain.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Xiang Song", - "author_inst": "Center for Discovery and Innovation, Hackensack Meridian Health" - }, - { - "author_name": "Wei Hu", - "author_inst": "Center for Discovery and Innovation, Hackensack Meridian Health" + "author_name": "Herv\u00e9 Seligmann", + "author_inst": "University Grenoble Alpes and The Hebrew University of Jerusalem" }, { - "author_name": "Haibo Yu", - "author_inst": "Center for Discovery and Innovation, Hackensack Meridian Health" + "author_name": "Siham Iggui", + "author_inst": "University Grenoble Alpes" }, { - "author_name": "Laura Zhao", - "author_inst": "Tianhe Stem Cell Biotechnologies Inc" + "author_name": "Mustapha Rachdi", + "author_inst": "University Grenoble Alpes" }, { - "author_name": "Yeqian Zhao", - "author_inst": "Tianhe Stem Cell Biotechnologies Inc" + "author_name": "Nicolas Vuillerme", + "author_inst": "University Grenoble Alpes" }, { - "author_name": "Yong Zhao", - "author_inst": "Center for Discovery and Innovation, Hackensack Meridian Health" + "author_name": "Jacques Demongeot", + "author_inst": "University Grenoble Alpes" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "immunology" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.07.17.20156109", @@ -1314871,31 +1314805,187 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.17.20155242", - "rel_title": "Genetic inhibition of interleukin-6 receptor signaling and Covid-19", + "rel_doi": "10.1101/2020.07.18.210179", + "rel_title": "Lethality of SARS-CoV-2 infection in K18 human angiotensin converting enzyme 2 transgenic mice", "rel_date": "2020-07-19", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20155242", - "rel_abs": "There are few effective therapeutic options for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Early evidence has suggested that IL-6R blockers may confer benefit, particularly in severe coronavirus disease 2019 (Covid-19).\n\nWe leveraged large-scale human genetic data to investigate whether IL6-R blockade may confer therapeutic benefit in Covid-19. A genetic instrument consisting of seven genetic variants in or close to IL6R was recently shown to be linked to altered levels of c-reactive protein (CRP), fibrinogen, circulating IL-6 and soluble IL-6R, concordant to known effects of pharmacological IL- 6R blockade. We investigated the effect of these IL6R variants on risk of hospitalization for Covid- 19 and other SARS-CoV-2-related outcomes using data from The Covid-19 Host Genetics Initiative.\n\nThe IL6R variants were strongly associated with serum CRP levels in UK Biobank. Meta-analysis of scaled estimates revealed a lower risk of rheumatoid arthritis (OR 0.93 per 0.1 SD lower CRP, 95% CI, 0.90-0.96, P = 9.5 x 10-7), recapitulating this established indication for IL-6R blockers (e.g. tocilizumab and sarilumab). The IL-6R instrument was associated with lower risk of hospitalization for Covid-19 (OR 0.88 per 0.1 SD lower CRP, 95% CI, 0.78-0.99, P = 0.03). We found a consistent association when using a population-based control group (i.e. all non-cases; OR 0.91 per 0.1 SD lower CRP, 95% CI, 0.87-0.96, P = 4.9 x 10-4). Evaluation of further SARS- CoV-2-related outcomes suggested association with risk of SARS-CoV-2 infection, with no evidence of association with Covid-19 complicated by death or requiring respiratory support. We performed several sensitivity analyses to evaluate the robustness of our findings.\n\nOur results serve as genetic evidence for the potential efficacy of IL-6R blockade in Covid-19. Ongoing large-scale RCTs of IL-6R blockers will be instrumental in identifying the settings, including stage of disease, in which these agents may be effective.", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.18.210179", + "rel_abs": "ABSTRACTVaccine and antiviral development against SARS-CoV-2 infection or COVID-19 disease currently lacks a validated small animal model. Here, we show that transgenic mice expressing human angiotensin converting enzyme 2 (hACE2) by the human cytokeratin 18 promoter (K18 hACE2) represent a susceptible rodent model. K18 hACE2-transgenic mice succumbed to SARS-CoV-2 infection by day 6, with virus detected in lung airway epithelium and brain. K18 ACE2-transgenic mice produced a modest TH1/2/17 cytokine storm in the lung and spleen that peaked by day 2, and an extended chemokine storm that was detected in both lungs and brain. This chemokine storm was also detected in the brain at day 4. K18 hACE2-transgenic mice are, therefore, highly susceptible to SARS-CoV-2 infection and represent a suitable animal model for the study of viral pathogenesis, and for identification and characterization of vaccines (prophylactic) and antivirals (therapeutics) for SARS-CoV-2 infection and associated severe COVID-19 disease.", + "rel_num_authors": 42, "rel_authors": [ { - "author_name": "Jonas Bovijn", - "author_inst": "University of Oxford" + "author_name": "Fatai Oladunni", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Cecilia M. Lindgren", - "author_inst": "University of Oxford" + "author_name": "Jun-Gyu Park", + "author_inst": "Texas Biomedical Research Institute" }, { - "author_name": "Michael V. Holmes", - "author_inst": "University of Oxford" + "author_name": "Paula Pino Tamayo", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Olga Gonzalez", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Anwari Ahkter", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Anna Allue Guardia", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Angelica Olmo-Fontanez", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Shalini Gautam", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Andreu Garcia Vilanova", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Chengjin Ye", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Kevin Chiem", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Colwyn Headley", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Varun Dwivedi", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Laura Parodi", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Kendra Alfson", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Hilary Staples", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Alyssa Schami", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Juan Garcia", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Alison Whigham", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Roy Neal Platt", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Michal Gazi", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Jesse C Martinez", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Colin Chuba", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Stephanie Earley", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Oscar Rodriguez", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Stephanie Davis Mdaki", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Katrina Kavelish", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Renee Escalona", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Cory Hallam", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Corbett Christie", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Jean Patterson", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Tim Anderson", + "author_inst": "Texas Biomedical research institute" + }, + { + "author_name": "Ricardo Carrion Jr.", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Edward Dick Jr.", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Shannan Hall-Ursone", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Larry S Schlesinger", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Deepak Kaushal", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Luis D Giavedoni", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Xavier Alvarez", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Joanne Turner", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Luis Martinez-Sobrido", + "author_inst": "Texas Biomedical Research Institute" + }, + { + "author_name": "Jordi B Torrelles", + "author_inst": "Texas Biomedical Research Institute" } ], "version": "1", - "license": "cc_by", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_no", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.07.18.210161", @@ -1316605,171 +1316695,35 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.07.15.204339", - "rel_title": "Mutational dynamics and transmission properties of SARS-CoV-2 superspreading events in Austria", + "rel_doi": "10.1101/2020.07.15.205567", + "rel_title": "COVID-19 Detection on Chest X-Ray and CT Scan Images Using Multi-image Augmented Deep Learning Model", "rel_date": "2020-07-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.15.204339", - "rel_abs": "Superspreading events shape the COVID-19 pandemic. Here we provide a national-scale analysis of SARS-CoV-2 outbreaks in Austria, a country that played a major role for virus transmission across Europe and beyond. Capitalizing on a national epidemiological surveillance system, we performed deep whole-genome sequencing of virus isolates from 576 samples to cover major Austrian SARS-CoV-2 clusters. Our data chart a map of early viral spreading in Europe, including the path from low-frequency mutations to fixation. Detailed epidemiological surveys enabled us to calculate the effective SARS-CoV-2 population bottlenecks during transmission and unveil time-resolved intra-patient viral quasispecies dynamics. This study demonstrates the power of integrating deep viral genome sequencing and epidemiological data to better understand how SARS-CoV-2 spreads through populations.\n\nGraphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY", - "rel_num_authors": 38, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.15.205567", + "rel_abs": "COVID-19 is posed as very infectious and deadly pneumonia type disease until recent time. Despite having lengthy testing time, RT-PCR is a proven testing methodology to detect coronavirus infection. Sometimes, it might give more false positive and false negative results than the desired rates. Therefore, to assist the traditional RT-PCR methodology for accurate clinical diagnosis, COVID-19 screening can be adopted with X-Ray and CT scan images of lung of an individual. This image based diagnosis will bring radical change in detecting coronavirus infection in human body with ease and having zero or near to zero false positives and false negatives rates. This paper reports a convolutional neural network (CNN) based multi-image augmentation technique for detecting COVID-19 in chest X-Ray and chest CT scan images of coronavirus suspected individuals. Multi-image augmentation makes use of discontinuity information obtained in the filtered images for increasing the number of effective examples for training the CNN model. With this approach, the proposed model exhibits higher classification accuracy around 95.38% and 98.97% for CT scan and X-Ray images respectively. CT scan images with multi-image augmentation achieves sensitivity of 94.78% and specificity of 95.98%, whereas X-Ray images with multi-image augmentation achieves sensitivity of 99.07% and specificity of 98.88%. Evaluation has been done on publicly available databases containing both chest X-Ray and CT scan images and the experimental results are also compared with ResNet-50 and VGG-16 models.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Alexandra Popa", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Jakob-Wendelin Genger", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Michael Nicholson", - "author_inst": "Department of Data Sciences, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health" - }, - { - "author_name": "Thomas Penz", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Daniela Schmid", - "author_inst": "Austrian Agency for Health and Food Safety" - }, - { - "author_name": "Stephan W Aberle", - "author_inst": "Center for Virology, Medical University of Vienna" - }, - { - "author_name": "Benedikt Agerer", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Alexander Lercher", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Lukas Endler", - "author_inst": "Department of Biomedical Sciences, University of Veterinary Medicine" - }, - { - "author_name": "Henrique Colaco", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Mark Smyth", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Michael Schuster", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Miguel Grau", - "author_inst": "Institute for Research in Biomedicine" - }, - { - "author_name": "Francisco Martinez Jimenez", - "author_inst": "IRB" - }, - { - "author_name": "Oriol Pich", - "author_inst": "Institute for Research in Biomedicine" - }, - { - "author_name": "Wegene Tamire Borena", - "author_inst": "Institute of Virology, Medical University Innsbruck" + "author_name": "Kiran Purohit", + "author_inst": "NIT Durgapur" }, { - "author_name": "Erich Pawelka", - "author_inst": "Department of Medicine IV, Kaiser Franz Josef Hospital" - }, - { - "author_name": "Zsofia Keszei", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Martin Senekowitsch", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" + "author_name": "Abhishek Kesarwani", + "author_inst": "NIT Durgapur" }, { - "author_name": "Jan Laine", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Judith Aberle", - "author_inst": "Center for Virology, Medical University of Vienna" - }, - { - "author_name": "Monika Redlberger-Fritz", - "author_inst": "Center for Virology, Medical University of Vienna" - }, - { - "author_name": "Mario Karolyi", - "author_inst": "Department of Medicine IV, Kaiser Franz Josef Hospital" - }, - { - "author_name": "Alexander Zoufaly", - "author_inst": "Department of Medicine IV, Kaiser Franz Josef Hospital" - }, - { - "author_name": "Sabine Maritschnik", - "author_inst": "Austrian Agency for Health and Food Safety" - }, - { - "author_name": "Martin Borkovec", - "author_inst": "Austrian Agency for Health and Food Safety" - }, - { - "author_name": "Peter Hufnagl", - "author_inst": "Austrian Agency for Health and Food Safety" - }, - { - "author_name": "Manfred Nairz", - "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck" - }, - { - "author_name": "Guenter Weiss", - "author_inst": "Department of Internal Medicine II, Medical University of Innsbruck" - }, - { - "author_name": "Michael T. Wolfinger", - "author_inst": "University of Vienna, Austria" - }, - { - "author_name": "Dorothee von Laer", - "author_inst": "Institute of Virology, Medical University Innsbruck" - }, - { - "author_name": "Giulio Superti-Furga", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" - }, - { - "author_name": "Nuria Lopez-Bigas", - "author_inst": "Barcelona Institute for Research in Biomedicine" - }, - { - "author_name": "Elisabeth Puchhammer-Stoeckl", - "author_inst": "Medical University of Vienna" - }, - { - "author_name": "Franz Allerberger", - "author_inst": "Austrian Agency for Health and Food Safety" - }, - { - "author_name": "Franziska Michor", - "author_inst": "Dana-Farber Cancer Institute" - }, - { - "author_name": "Christoph Bock", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" + "author_name": "Dakshina Ranjan Kisku", + "author_inst": "National Institute of Technology Durgapur" }, { - "author_name": "Andreas Bergthaler", - "author_inst": "CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences" + "author_name": "Mamata Dalui", + "author_inst": "NIT Durgapur" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "new results", - "category": "microbiology" + "category": "bioengineering" }, { "rel_doi": "10.1101/2020.07.12.20152017", @@ -1318863,25 +1318817,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.15.20140095", - "rel_title": "Preparedness, Perceived Impact and Concerns of health Care Workers in a Teaching Hospital during Coronavirus Disease 2019 (COVID-19)", + "rel_doi": "10.1101/2020.07.17.20152389", + "rel_title": "Mapping physical access to healthcare for older adults in sub-Saharan Africa: A cross-sectional analysis with implications for the COVID-19 response", "rel_date": "2020-07-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.15.20140095", - "rel_abs": "ObjectiveCoronavirus Disease 2019 is a new threat to human lives worldwide. Preparedness of institutions during epidemic outbreak has a pivotal role in saving lives and preventing further spread. At the same time, these pandemics impact badly on professional and personal life of Health care workers. The objective of this study is to find the opinion of Health care workers regarding their level of preparedness, concerns and perceived impact related to this pandemic outbreak.\n\nMaterials and Methodsin this study, random samples of doctors and nurses was provided with a self-administered questionnaire regarding their preparedness, work and non-work related concerns and impact on their lives during Covid-19 outbreak.\n\nResultsMost of the Health Care Workers believed that their institute preparation to fight Covid-19 pandemic is better than prior to onset of this crisis (p0.001). Work related stress was seen more commonly in nurses whereas higher frequency of non-work related stress was observed among doctors. Nurses (75.55%) faith in their employer was more than doctors faith (46.66%) regarding their medical needs. There was more acceptance of hydroxychloroquine as a prophylactic drug for Covid-19 in doctors compared to nurses (p 0.01).\n\nConclusionsThough this institute was more prepared at the time of pandemic spread, substantial opportunity of improvement remains. The consistency of work and non work related anxiety and stress in health care workers is very high in present study group. Concerns and risks of Health Care Workers should be addressed ethically and adequately by strengthening safety measures and building trust in the system they work.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20152389", + "rel_abs": "BackgroundSARS-CoV-2, the virus causing coronavirus disease 2019 (COVID-19), is rapidly spreading across sub-Saharan Africa (SSA). Hospital-based care for COVID-19 is particularly often needed among older adults. However, a key barrier to accessing hospital care in SSA is travel time to the healthcare facility. To inform the geographic targeting of additional healthcare resources, this study aimed to determine the estimated travel time at a 1km x 1km resolution to the nearest hospital and to the nearest healthcare facility of any type for adults aged 60 years and older in SSA.\n\nMethodsWe assembled a unique dataset on healthcare facilities geolocation, separately for hospitals and any type of healthcare facility (including primary care facilities) and including both private- and public-sector facilities, using data from the OpenStreetMap project and the KEMRI Wellcome Trust Programme. Population data at a 1km x 1km resolution was obtained from WorldPop. We estimated travel time to the nearest healthcare facility for each 1km x 1km grid using a cost-distance algorithm.\n\nFindings9.6% (95% CI: 5.2% - 16.9%) of adults aged [≥]60 years had an estimated travel time to the nearest hospital of longer than six hours, varying from 0.0% (95% CI: 0.0% - 3.7%) in Burundi and The Gambia, to 40.9% (95% CI: 31.8% - 50.7%) in Sudan. 11.2% (95% CI: 6.4% - 18.9%) of adults aged [≥]60 years had an estimated travel time to the nearest healthcare facility of any type (whether primary or secondary/tertiary care) of longer than three hours, with a range of 0.1% (95% CI: 0.0% - 3.8%) in Burundi to 55.5% (95% CI: 52.8% - 64.9%) in Sudan. Most countries in SSA contained populated areas in which adults aged 60 years and older had a travel time to the nearest hospital of more than 12 hours and to the nearest healthcare facility of any type of more than six hours. The median travel time to the nearest hospital for the fifth of adults aged [≥]60 years with the longest travel times was 348 minutes (equal to 5.8 hours; IQR: 240 - 576 minutes) for the entire SSA population, ranging from 41 minutes (IQR: 34 - 54 minutes) in Burundi to 1,655 minutes (equal to 27.6 hours; IQR: 1065 - 2440 minutes) in Gabon.\n\nInterpretationOur high-resolution maps of estimated travel times to both hospitals and healthcare facilities of any type can be used by policymakers and non-governmental organizations to help target additional healthcare resources, such as new make-shift hospitals or transport programs to existing healthcare facilities, to older adults with the least physical access to care. In addition, this analysis shows precisely where population groups are located that are particularly likely to under-report COVID-19 symptoms because of low physical access to healthcare facilities. Beyond the COVID-19 response, this study can inform countries efforts to improve care for conditions that are common among older adults, such as chronic non-communicable diseases.\n\nFundingBill & Melinda Gates Foundation\n\nResearch in context\n\nEvidence before this studyWe searched MEDLINE from January 1966 until May 2020 for studies with variations of the words physical access, distance, travel time, hospital, and healthcare facility in the title or abstract. To date, the only studies to systematically map physical access to healthcare facilities in sub-Saharan Africa at a high resolution examined access to emergency hospital care (with a focus on women of child-bearing age), access to care for children with fever, travel time to the nearest healthcare facility for specific populations at risk of viral haemorrhagic fevers, and travel time to the nearest regional- or district-level hospital.\n\nAdded value of this studyThe added value of this study is threefold. First, we assembled a new dataset of GPS-tagged healthcare facilities, which combines two unique data sources for the geolocation of healthcare facilities across sub-Saharan Africa: one-based on crowd-sourced data from OpenStreetMap and one based on information from ministries of health, health management information systems, government statistical agencies, and international organizations. Second, this is the first study to comprehensively map both hospitals and primary healthcare facilities, and including both public- and private-sector facilities, across sub-Saharan Africa. Third, because the COVID-19 epidemic causes a far higher need for hospital services among older than younger population groups, we focus on physical access to healthcare for the population aged 60 years and older, which is a population group that is rarely studied in investigations of healthcare demand and supply in the region. As such, our maps can inform not only the health system response to COVID-19, but more generally to conditions that are common among older adults in the region, particularly chronic non-communicable diseases and their sequelae.\n\nImplications of all the available evidenceLow physical access to healthcare in sub-Saharan Africa will be a major barrier to receiving care for adults aged 60 years and older with COVID-19. However, there is a wide degree of variation in physical access to healthcare facilities for older adults in the region both between and within countries, which likely has an important bearing on the extent to which different population groups within countries are able to access care for COVID-19. Likewise, in those areas with a long travel time to the nearest healthcare facility of any type (which exist in most countries), symptomatic cases of COVID-19 are particularly unlikely to be reported to the healthcare system. Our high-resolution maps for each region and country in sub-Saharan Africa provide precise information about this geographic variation for local, national, and regional policymakers as well as non-governmental organizations.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Kumar Saurabh", - "author_inst": "Government Medical College, Bettiah" + "author_name": "Pascal Geldsetzer", + "author_inst": "Division of Primary Care and Population Health, Department of Medicine, Stanford University; Heidelberg Institute of Global Health, Heidelberg University" + }, + { + "author_name": "Marcel Reinmuth", + "author_inst": "Institute of Geography, Heidelberg University; HeiGIT at Heidelberg University" + }, + { + "author_name": "Paul O Ouma", + "author_inst": "Population Health Unit, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme" + }, + { + "author_name": "Sven Lautenbach", + "author_inst": "HeiGIT at Heidelberg University" }, { - "author_name": "Shilpi Ranjan", - "author_inst": "Nalanda Medical College,Patna" + "author_name": "Emelda A Okiro", + "author_inst": "Population Health Unit, Kenya Medical Research Institute (KEMRI)-Wellcome Trust Research Programme; Centre for Tropical Medicine and Global Health, Nuffield Dep" + }, + { + "author_name": "Till Baernighausen", + "author_inst": "Heidelberg Institute of Global Health, Heidelberg University; Department of Global Health and Population, Harvard T.H. Chan School of Public Health; Africa Heal" + }, + { + "author_name": "Alexander Zipf", + "author_inst": "Institute of Geography, Heidelberg University; HeiGIT at Heidelberg University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1320773,127 +1320747,39 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.07.17.20155937", - "rel_title": "Disease-associated antibody phenotypes and probabilistic seroprevalence estimates during the emergence of SARS-CoV-2", + "rel_doi": "10.1101/2020.07.16.20138354", + "rel_title": "Joint CBC-ICT Interpretation for the pre-surgical screening of COVID 19 asymptomatic cases: A cross-sectional study", "rel_date": "2020-07-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.17.20155937", - "rel_abs": "Serological studies are critical for understanding pathogen-specific immune responses and informing public health measures1,2. Here, we evaluate tandem IgM, IgG and IgA responses in a cohort of individuals PCR+ for SARS-CoV-2 RNA (n=105) representing different categories of disease severity, including mild and asymptomatic infections. All PCR+ individuals surveyed were IgG-positive against the virus spike (S) glycoprotein. Elevated Ab levels were associated with hospitalization, with IgA titers, increased circulating IL-6 and strong neutralizing responses indicative of intensive care status. Additional studies of healthy blood donors (n=1,000) and pregnant women (n=900), sampled weekly during the initial outbreak in Stockholm, Sweden (weeks 14-25, 2020), demonstrated that anti-viral IgG titers differed over 1,000-fold between seroconverters, highlighting the need for careful evaluation of assay cut-offs for individual measurements and accurate estimates of seroprevalence (SP). To provide a solution to this, we developed probabilistic machine learning approaches to assign likelihood of past infection without setting an assay cut-off, allowing for more quantitative individual and population-level Ab measures. Using these tools, that considered responses against both S and RBD, we report SARS-CoV-2 S-specific IgG in 6.8% of blood donors and pregnant women two months after the peak of spring COVID-19 deaths, with the SP curve and country death rate following similar trajectories.", - "rel_num_authors": 27, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.16.20138354", + "rel_abs": "BackgroundOn 26th, February 2020, first cases of COVID 19 were confirmed in Pakistan. Since then, surgeries were halted in a bid to prevent transmission. However, since such a long halt is infeasible, a general protocol of screening the carriers, especially asymptomatic carries, is a dire need of time. The objective of our study is to propose an economically feasible protocol of COVID 19 screening. Simple but effective screening strategies can help to restore the workings of hospital surgical departments.\n\nMethodsWe analyzed the clinical data of patients turning up for elective surgeries at the Rawal General Hospital (RGH), Islamabad from the 24th of March to the 15th of May, 2020. Asymptomatic patients with negative COVID 19 contact and travel histories were screened with COVID 19 Immunochromatography (ICT) IgM / IgG Ab Test. Complete blood count (CBC) was done and interpreted in conjunction with the ICT results.\n\nResults39 patients with a mean age of 49 years were studied. The result of ICT for COVID-19 was positive in 9 cases (23%). The entire positive ICT patients population expressed significantly lower lymphocyte count (p<0.01); 8 patients had high monocyte count (p<0.05) whereas only 4 patients had a combined high neutrophil and monocyte count (P<0.05). All of these four patients with high neutrophil count were females. The combined interpretation of CBC and ICT IgM / IgG Ab Test had a high accuracy in diagnosing asymptomatic COVID-19 carriers that were later confirmed by real-time reverse transcriptase-polymerase chain reaction (rRT-PCR).\n\nConclusionWe propose that joint CBC-ICT interpretation should be adopted on a large scale to help in the diagnoses of asymptomatic carriers as both tests are simple and inexpensive and thus suit the developing countries limited health budget. Future research projects should be adopted in order to assess the accuracy of the proposed protocol on a large scale.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Xaquin Castro Dopico", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Leo Hanke", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Daniel J Sheward", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Sandra Muschiol", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Soo Aleman", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Nastasiya F Grinberg", - "author_inst": "University of Cambridge" - }, - { - "author_name": "Murray Christian", - "author_inst": "Karolinska Institutet" + "author_name": "Tanzeel Imran", + "author_inst": "Department of Pathology, Rawal General Hospital, Islamabad, Pakistan" }, { - "author_name": "Monika Adori", - "author_inst": "Karolinska Institutet" + "author_name": "Humera Altaf Naz", + "author_inst": "Department of Surgery, Shifa College of Medicine, Islamabad, Pakistan" }, { - "author_name": "Laura Perez Vidakovics", - "author_inst": "Karolinska Institutet" + "author_name": "Hamza Khan", + "author_inst": "Shifa College of Medicine, Islamabad, Pakistan" }, { - "author_name": "Kim Chang Il", - "author_inst": "Karolinska Institutet" + "author_name": "Ali Haider Bangash", + "author_inst": "Shifa College of Medicine, STMU, Islamabad, Pakistan" }, { - "author_name": "Sharesta Khoenkhoen", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Pradeepa Pushparaj", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Ainhoa Moliner Morro", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Marco Mandolesi", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Marcus Ahl", - "author_inst": "Karolinska University Hospital" - }, - { - "author_name": "Mattias Forsell", - "author_inst": "Umea University" - }, - { - "author_name": "Jonathan Coquet", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Martin Corcoran", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Joanna Rorbach", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Joakim Dillner", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Gordana Bogdanovic", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Gerald Mcinerney", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Tobias Allander", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Ben Murrell", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Chris Wallace", - "author_inst": "University of Cambridge & MRC Biostatistics Unit" - }, - { - "author_name": "Jan Albert", - "author_inst": "Karolinska Institutet" - }, - { - "author_name": "Gunilla B Karlsson Hedestam", - "author_inst": "Karolinska Institutet" + "author_name": "Laraib Bakhtiar Khan", + "author_inst": "Roots IVY International College, Islamabad, Pakistan" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "hematology" }, { "rel_doi": "10.1101/2020.07.14.20153585", @@ -1322451,35 +1322337,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.14.20153775", - "rel_title": "Direct-to-Consumer Chat-Based Remote Care Before and During the COVID-19 Outbreak", + "rel_doi": "10.1101/2020.07.14.20153908", + "rel_title": "Application of ARIMA and Holt-Winters forecasting model to predict the spreading of COVID-19 for India and its states", "rel_date": "2020-07-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.14.20153775", - "rel_abs": "ObjectiveTo compare the patient population, common complaints, and physician recommendations in direct-to-consumer chat-based consults, before and during the COVID-19 outbreak.\n\nData sourcesData on patient characteristics, patient complaints, and physician recommendations from 36,864 chat-based telemedicine consults with physicians in an online-clinic by patients from across the United States between April 2019 and April 2020.\n\nStudy DesignWe perform a retrospective analysis comparing patient characteristics, visit characteristics, and physician recommendation before and after the COVID-19 outbreak. We examine patient age and gender, visit time, patient chief complains, and physician medical recommendation (including prescription drugs, reassurance, and referrals).\n\nPrincipal FindingsBefore March 2020, most patients were female (75 percent) and 18-44 years old (89 percent). Common complaints such as abdominal pain, dysuria, or sore throat suggested minor acute conditions. Most cases (67 percent) were resolved remotely, mainly via prescriptions; a minority were referred. Since March 2020, the COVID-19 emergency has led to a sharp (fourfold) increase in case volume, including more males (from 25 to 29 percent), patients aged 45 and older (from 11 to 17 percent), and more cases involving mental health complaints and complaints related to COVID-19. Across all symptoms, significantly more cases (78 percent) have been resolved remotely.\n\nConclusionsThe COVID-19 outbreak in the United States has been associated with a sharp increase in the use of chat-based telemedicine services, including by new patient demographics, an increase in both COVID-19 and mental health complains, and an increase in remote case resolutions.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.14.20153908", + "rel_abs": "The novel Corona-virus (COVID-2019) epidemic has posed a global threat to human life and society. The whole world is working relentlessly to find some solutions to fight against this deadly virus to reduce the number of deaths. Strategic planning with predictive modelling and short term forecasting for analyzing the situations based on the worldwide available data allow us to realize the future exponential behaviour of the COVID-19 disease. Time series forecasting plays a vital role in developing an efficient forecasting model for a future prediction about the spread of this contagious disease. In this paper, the ARIMA (Auto regressive integrated moving average) and Holt-Winters time series exponential smoothing are used to develop an efficient 20-days ahead short-term forecast model to predict the effect of COVID-19 epidemic. The modelling and forecasting are done with the publicly available dataset from Kaggle as a perspective to India and its five states such as Odisha, Delhi, Maharashtra, Andhra Pradesh and West Bengal. The model is assessed with correlogram, ADF test, AIC and RMSE to understand the accuracy of the proposed forecasting model.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Dan Zeltzer", - "author_inst": "Tel Aviv University" - }, - { - "author_name": "Alina Vodonos Zilberg", - "author_inst": "K Health, Tel Aviv" - }, - { - "author_name": "Yehuda Edo Paz", - "author_inst": "K Health, New York" - }, - { - "author_name": "Roy Malka", - "author_inst": "K Health, Tel Aviv" + "author_name": "Mrutyunjaya Panda", + "author_inst": "Utkal University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "primary care research" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.07.15.20154682", @@ -1323985,57 +1323859,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.14.20153304", - "rel_title": "Post lockdown COVID-19 seroprevalence and circulation at the time of delivery, France", + "rel_doi": "10.1101/2020.07.13.20152694", + "rel_title": "COVID-19 misinformation: mere harmless delusions or much more? A knowledge and attitude cross-sectional study among the general public residing in Jordan", "rel_date": "2020-07-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.14.20153304", - "rel_abs": "BackgroundTo fight the COVID-19 pandemic, lockdown has been decreed in many countries worldwide. The impact of pregnancy as a severity risk factor is still debated, but strict lockdown measures have been recommended for pregnant women.\n\nObjectivesTo evaluate the impact of the COVID-19 pandemic and lockdown on the seroprevalence and circulation of SARS-CoV-2 in a maternity ward in an area that has been significantly affected by the virus.\n\nStudy designProspective study at the Antoine Beclere Hospital maternity ward (Paris area, France) from May 4 (one week before the end of lockdown) to May 31, 2020 (three weeks after the end of lockdown). All patients admitted to the delivery room during this period were offered a SARS-CoV-2 serology test as well concomitant SARS-CoV-2 RT-PCR on a nasopharyngeal sample.\n\nResultsA total of 249 women were included. Seroprevalence of SARS-CoV-2 was 8%. The RT-PCR positive rate was 0.5%. 47.4% of the SARS-CoV-2-IgG-positive pregnant women never experienced any symptoms. A history of symptoms during the epidemic, such as fever, myalgia and anosmia, was suggestive of previous infection.\n\nConclusionsThree weeks after the end of lockdown, SARS-CoV-2 infections were scarce in our region. A high proportion of SARS-CoV-2-IgG-negative pregnant women must be taken into consideration in the event of a resurgence of the pandemic in order to adapt public health measures to reduce exposure to the virus, such as social distancing and teleworking for this specific population.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20152694", + "rel_abs": "Since the emergence of the recent coronavirus disease 2019 (COVID-19) and its spread as a pandemic, media was teeming with misinformation that led to psychologic, social and economic consequences among the global public. Probing knowledge and anxiety regarding this novel infectious disease is necessary to identify gaps and sources of misinformation which can help public health efforts to design and implement more focused interventional measures. The aim of this study was to evaluate the knowledge, attitude and effects of misinformation about COVID-19 on anxiety level among the general public residing in Jordan. An online survey was used that targeted people aged 18 and above and residing in Jordan. The questionnaire included items on the following: demographic characteristics of the participants, knowledge about COVID-19, anxiety level and misconceptions regarding the origin of the pandemic. The total number of participants included in final analysis was 3150. The study population was predominantly females (76.0%), with mean age of 31 years. The overall knowledge of COVID-19 was satisfactory. Older age, male gender, lower monthly income and educational levels, smoking and history of chronic disease were associated with perceiving COVID-19 as a very dangerous disease. Variables that were associated with a higher anxiety level during the pandemic included: lower monthly income and educational level, residence outside the capital (Amman) and history of smoking. Misinformation about the origin of the pandemic (being part of a conspiracy, biologic warfare and the 5G networks role) was also associated with higher anxiety and lower knowledge about the disease. Social media platforms, TV and news releases were the most common sources of information about the pandemic. The study showed the potential harmful effects of misinformation on the general public and emphasized the need to meticulously deliver timely and accurate information about the pandemic to lessen the health, social and psychological impact of the disease.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Jeremie Mattern", - "author_inst": "Division of Obstetrics and Gynecology, Antoine Beclere Hospital, Paris Saclay University, AP-HP, Clamart, France" - }, - { - "author_name": "Christelle Vauloup-Fellous", - "author_inst": "Division of Virology, Paul Brousse Hospital, Paris Saclay University, AP-HP, INSERM U1193 Villejuif, France" + "author_name": "Malik Sallam", + "author_inst": "University of Jordan" }, { - "author_name": "Hoda Zakaria", - "author_inst": "Division of Obstetrics and Gynecology, Antoine Beclere Hospital, Paris Saclay University, AP-HP, Clamart, France" + "author_name": "Deema Dababseh", + "author_inst": "University of Jordan" }, { - "author_name": "Alexandra Benachi", - "author_inst": "Division of Obstetrics and Gynecology, Antoine Beclere Hospital, Paris Saclay University, AP-HP, Clamart, France" + "author_name": "Alaa Yaseen", + "author_inst": "University of Jordan" }, { - "author_name": "Julie Carrara", - "author_inst": "Division of Obstetrics and Gynecology, Antoine Beclere Hospital, Paris Saclay University, AP-HP, Clamart, France" + "author_name": "Ayat Al-Haidar", + "author_inst": "University of Jordan" }, { - "author_name": "Alexandra Letourneau", - "author_inst": "Division of Obstetrics and Gynecology, Antoine Beclere Hospital, Paris Saclay University, AP-HP, Clamart, France" + "author_name": "Duaa Taim", + "author_inst": "University of Jordan" }, { - "author_name": "Nadege Bourgeois-Nicolaos", - "author_inst": "Division of Microbiology, Antoine Beclere Hospital, Paris Saclay University, AP-HP, Clamart, France" + "author_name": "Huda Eid", + "author_inst": "University of Jordan" }, { - "author_name": "Daniele De Luca", - "author_inst": "Division of Pediatrics and Neonatal Critical Care, Antoine Beclere Hospital, Paris Saclay University, AP-HP, Clamart, France" + "author_name": "Nidaa A. Ababneh", + "author_inst": "University of Jordan" }, { - "author_name": "Florence Doucet-Populaire", - "author_inst": "Division of Microbiology, Antoine Beclere Hospital, Paris Saclay University, AP-HP, Clamart, France" + "author_name": "Faris G. Bakri", + "author_inst": "University of Jordan" }, { - "author_name": "Alexandre J. Vivanti", - "author_inst": "Division of Obstetrics and Gynecology, Antoine Beclere Hospital, Paris Saclay University, AP-HP, Clamart, France" + "author_name": "Azmi Mahafzah", + "author_inst": "University of Jordan" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1325747,59 +1325617,27 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.07.15.205229", - "rel_title": "The S1 protein of SARS-CoV-2 crosses the blood-brain barrier: Kinetics, distribution, mechanisms, and influence of ApoE genotype, sex, and inflammation", - "rel_date": "2020-07-15", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.15.205229", - "rel_abs": "Evidence strongly suggests that SARS-CoV-2, the cause of COVID-19, can enter the brain. SARS-CoV-2 enters cells via the S1 subunit of its spike protein, and S1 can be used as a proxy for the uptake patterns and mechanisms used by the whole virus; unlike studies based on productive infection, viral proteins can be used to precisely determine pharmacokinetics and biodistribution. Here, we found that radioiodinated S1 (I-S1) readily crossed the murine blood-brain barrier (BBB). I-S1 from two commercial sources crossed the BBB with unidirectional influx constants of 0.287 {+/-} 0.024 L/g-min and 0.294 {+/-} 0.032 L/g-min and was also taken up by lung, spleen, kidney, and liver. I-S1 was uniformly taken up by all regions of the brain and inflammation induced by lipopolysaccharide reduced uptake in the hippocampus and olfactory bulb. I-S1 crossed the BBB completely to enter the parenchymal brain space, with smaller amounts retained by brain endothelial cells and the luminal surface. Studies on the mechanisms of transport indicated that I-S1 crosses the BBB by the mechanism of adsorptive transcytosis and that the murine ACE2 receptor is involved in brain and lung uptake, but not that by kidney, liver, or spleen. I-S1 entered brain after intranasal administration at about 1/10th the amount found after intravenous administration and about 0.66% of the intranasal dose entered blood. ApoE isoform or sex did not affect whole brain uptake, but had variable effects on olfactory bulb, liver, spleen, and kidney uptakes. In summary, I-S1 readily crosses the murine BBB, entering all brain regions and the peripheral tissues studied, likely by the mechanism of adsorptive transcytosis.\n\nGraphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY", - "rel_num_authors": 10, + "rel_doi": "10.1101/2020.07.12.20148387", + "rel_title": "Impact of COVID-19 on 2020 US life expectancy for the Black and Latino populations", + "rel_date": "2020-07-14", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.12.20148387", + "rel_abs": "The Black and Latino populations have experienced a disproportionate burden of COVID-19 morbidity and mortality, reflecting persistent structural inequalities that increase risk of exposure to COVID-19 and risk of death for those infected. According to the National Center for Health Statistics, as of July 4, 2020, deaths to Black and Latino individuals comprised 23% and 17%, respectively, of the approximately 115,000 COVID-19 deaths. COVID-19 mortality is likely to result in a larger decline in life expectancy during 2020 than the US has experienced for decades as well as a particularly large reduction for Black and Latino individuals. We estimate life expectancy at birth and at age 65 for 2020, by race and ethnicity, using four scenarios of deaths - one in which the COVID-19 pandemic had not occurred and three including COVID-19 mortality projections produced by the Institute for Health Metrics and Evaluation. Our most likely estimate indicates a reduction in life expectancy at birth greater than 1.5 years for both the Black and Latino populations, which is one year larger than the reduction for whites. This would imply that the Black-white gap would increase by 30%, from 3.6 to 4.7 years, thereby eliminating progress made in reducing this differential since 2008 and reversing an overall trend of steeper mortality declines among the Black population since the early 1990s. Latinos, who have consistently experienced lower mortality than whites (a phenomenon known as the Latino or Hispanic paradox), would see their survival advantage decline by 36%, equivalent to its magnitude in 2006.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Elizabeth M Rhea", - "author_inst": "VA/UW" - }, - { - "author_name": "Aric F Logsdon", - "author_inst": "VA/UW" - }, - { - "author_name": "Kim M Hansen", - "author_inst": "VA" - }, - { - "author_name": "Lindsey Williams", - "author_inst": "VA" - }, - { - "author_name": "May Reed", - "author_inst": "VA/UW" - }, - { - "author_name": "Kristen Baumann", - "author_inst": "VA" - }, - { - "author_name": "Sarah Holden", - "author_inst": "OHSU" - }, - { - "author_name": "Jacob Raber", - "author_inst": "OHSU" - }, - { - "author_name": "William A Banks", - "author_inst": "VA/UW" + "author_name": "Theresa Andrasfay", + "author_inst": "University of Southern California" }, { - "author_name": "Michelle A Erickson", - "author_inst": "VA/UW" + "author_name": "Noreen Goldman", + "author_inst": "Princeton University" } ], "version": "1", - "license": "cc0", - "type": "new results", - "category": "neuroscience" + "license": "cc_by_nc", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.07.13.20152660", @@ -1327321,51 +1327159,35 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.07.10.20150623", - "rel_title": "Maternal and perinatal characteristics and outcomes of pregnancies complicated with COVID-19 in Kuwait", + "rel_doi": "10.1101/2020.07.11.20151688", + "rel_title": "COVID-19 among people living with HIV: A systematic review", "rel_date": "2020-07-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.10.20150623", - "rel_abs": "BackgroundIn late December of 2019, a novel coronavirus (SARS-CoV-2) was identified in the Chinese city Wuhan among a cluster of pneumonia patients. While it is known that pregnant women have reduced immunity and they are at risk for COVID-19 infection during the current pandemic, it is not clear if the disease manifestation would be different in pregnant women from non-pregnant women.\n\nObjectivesTo describe the maternal and neonatal clinical features as well as outcome of pregnancies complicated with SARS-CoV-2 infection.\n\nMethodsIn this retrospective national-based study, we analyzed the medical records of all SARS-CoV-2 positive pregnant patients and their neonates who were admitted to New-Jahra Hospital, Kuwait, between March 15th 2020 and May 31st 2020. The outcomes of pregnancies were assessed until the end date of follow-up (June 15th 2020).\n\nResultsA total of 185 pregnant women were enrolled with a median age of 31 years (interquartile range, IQR: 27.5-34), and median gestational age at diagnosis was 29 weeks (IQR: 18-34). The majority (88%) of the patients had mild symptoms, with fever (58%) being the most common presenting symptom followed by cough (50.6%). During the study period, 141 (76.2%) patients continued their pregnancy, 3 (1.6%) had a miscarriage, 1 (0.5%) had intrauterine fetal death and only 2 (1.1%) patients developed severe pneumonia and required intensive care. Most of the neonates were asymptomatic, and only 2 (5%) of them tested positive on day 5 by nasopharyngeal swab testing.\n\nConclusionPregnant women do not appear to be at higher risk to the COVID-19 than the general population. The clinical features of pregnant women with SARS-CoV-2 infection were similar to those of the general population having SARS-CoV-2 infection. Favorable maternal and neonatal outcomes reinforce the existing evidence and may guide healthcare professionals in the management of pregnancies complicated with SARS-CoV-2 infection.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.11.20151688", + "rel_abs": "This systematic review summarizes the evidence on the earliest patients with COVID-19-HIV co-infection. We searched PubMed, Scopus, Web of Science, Embase, preprint databases, and Google Scholar from December 01, 2019 to June 1, 2020. From an initial 547 publications and 75 reports, 25 studies provided specific information on COVID-19 patients living with HIV. Studies described 252 patients, 80.9% were male, mean age was 52.7 years, and 98% were on ART. Co-morbidities in addition to HIV and COVID-19 (multimorbidity) included hypertension (39.3%), obesity or hyperlipidemia (19.3%), chronic obstructive pulmonary disease (18.0%), and diabetes (17.2%). Two-thirds (66.5%) had mild to moderate symptoms, the most common being fever (74.0%) and cough (58.3%). Among patients who died, the majority (90.5%) were over 50 years old, male (85.7%), and had multimorbidity (64.3%). Our findings highlight the importance of identifying co-infections, addressing co-morbidities, and ensuring a secure supply of ART for PLHIV during the COVID-19 pandemic.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Amal Ayed", - "author_inst": "Obstetric and Gynaecology Department, Farwaniya Hospital, Kuwait" - }, - { - "author_name": "Alia Embaireeg", - "author_inst": "Paediatric Department, Farwaniya Hospital, Kuwait" - }, - { - "author_name": "Asmaa Benawadth", - "author_inst": "Obstetrics and Gynecology Department, Maternity Hospital, Kuwait" - }, - { - "author_name": "Wadha Al-Fouzan", - "author_inst": "Department of Microbiology, Faculty of Medicine, Kuwait University" - }, - { - "author_name": "Majeda Hammoud", - "author_inst": "Paediatrics Department , Faculty of Medicine, Kuwait University" + "author_name": "Hossein Mirzaei", + "author_inst": "HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical S" }, { - "author_name": "Monif Alhathal", - "author_inst": "Neonatal Department, Maternity Hospital, Kuwait" + "author_name": "Willi McFarland", + "author_inst": "Center for Public Health Research, San Francisco Department of Public Health, San Francisco, CA, USA" }, { - "author_name": "Abeer Alzaydai", - "author_inst": "Obstetrics and Gynaecology Department, Al-Adan Hospital, Kuwait" + "author_name": "Mohammad Karamouzian", + "author_inst": "School of Population and Public Health, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada" }, { - "author_name": "Mariam Ayed", - "author_inst": "Neonatal Department, Farwaniya Hospital, Kuwait" + "author_name": "Hamid Sharifi", + "author_inst": "HIV/STI Surveillance Research Center, and WHO Collaborating Center for HIV Surveillance, Institute for Futures Studies in Health, Kerman University of Medical S" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "obstetrics and gynecology" + "category": "hiv aids" }, { "rel_doi": "10.1101/2020.07.11.20147157", @@ -1329087,45 +1328909,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.13.20152330", - "rel_title": "Discrete simulation analysis of COVID-19 and prediction of isolation bed numbers", + "rel_doi": "10.1101/2020.07.12.20152298", + "rel_title": "The effect of international travel restrictions on internal spread of COVID-19", "rel_date": "2020-07-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.13.20152330", - "rel_abs": "The outbreak of COVID-19 has caused tremendous pressure on medical systems. Adequate isolation facilities are essential to control outbreaks, so this study aims to quickly estimate the demand and number of isolation beds. We established a discrete simulation model for epidemiology. By adjusting or fitting necessary epidemic parameters, the effects of the following indicators on the development of the epidemic and the occupation of medical resources were explained: (1) incubation period, (2) response speed and detection capacity of the hospital, (3) disease cure time, and (4) population mobility. Finally, a method for predicting the reasonable number of isolation beds was summarized through multiple linear regression. The prediction equation can be easily and quickly applied to estimate the demanded number of isolation beds in a COVID-19-affected city. A detailed explanation is given for the specific measurement of each parameter in the article.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.12.20152298", + "rel_abs": "BackgroundCountries have restricted international arrivals to delay the spread of COVID-19. These measures carry a high economic and social cost. They may have little impact on COVID-19 epidemics if there are many more cases resulting from local transmission compared to imported cases.\n\nMethodsTo inform decisions about international travel restrictions, we compared the ratio of expected COVID-19 cases from international travel (assuming no travel restrictions) to the expected COVID-19 cases arising from internal spread on an average day in May 2020 in each country. COVID-19 prevalence and incidence were estimated using a modelling framework that adjusts reported cases for under-ascertainment and asymptomatic infections.\n\nFindingsWith May 2019 travel volumes, imported cases account for <10% of total incidence in 103 (95% credible interval: 76 - 130) out of 142 countries, and <1% in 48 (95% CrI: 9 - 95). If we assume that travel would decrease compared to May 2019 even in the absence of formal restrictions, then imported cases account for <10% of total incidence in 109-123 countries and <1% in 61-88 countries (depending on the assumptions about travel reductions).\n\nInterpretationWhile countries can expect infected travellers to arrive in the absence of travel restrictions, in most countries these imported cases likely contribute little to local COVID-19 epidemics. Stringent travel restrictions may have limited impact on epidemic dynamics except in countries with low COVID-19 incidence and large numbers of arrivals from other countries.\n\nFundingWellcome Trust, UK Department for International Development, European Commission, National Institute for Health Research, Medical Research Council, Bill & Melinda Gates Foundation\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSCountries are at different stages of COVID-19 epidemics, so many have implemented policies to minimise the risk of importing cases via international travel. Such policies include border closures, flight suspensions, quarantine and self-isolation on international arrivals. Searching PubMed and MedRxiv using the search: (\"covid\" OR \"coronavirus\" OR \"SARS-CoV-2\") AND (\"travel\" OR \"restrictions\" OR \"flight\" OR \"flights\" OR \"border\") from 1 January - 10 July 2020 returned 118 and 84 studies respectively, of which 39 were relevant to our study. These studies either concentrated in detail on the risk of importation to specific countries or used a single epidemiological or travel dataset to estimate risk. Most of them focused on the risk of COVID-19 introduction from China or other countries with cases earlier in 2020. No study combined country-specific travel data, prevalence estimates and incidence estimates to assess the global risk of importation relative to current local transmission within countries.\n\nAdded value of this studyWe combined data on airline passengers and flight frequencies with estimates of COVID-19 prevalence and incidence (adjusted for underreporting and asymptomatic cases), to estimate the risk of imported cases, relative to the level of local transmission in each country. This allows decision makers to determine where travel restriction policies make large contributions to slowing local transmission, and where they have very little overall effect.\n\nImplications of all the available evidenceIn most countries, imported cases would make a relatively small contribution to local transmission, so travel restrictions would have very little effect on epidemics. Countries where travel restrictions would have a large effect on local transmission are those with strong travel links to countries with high COVID-19 prevalence and/or countries which have successfully managed to control their local outbreaks.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Xinyu Li", - "author_inst": "Department of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital, Central South University," - }, - { - "author_name": "Yufeng Cai", - "author_inst": "Department of Biomedical Informatics, School of Life Sciences, Central South University, Changsha, Hunan" + "author_name": "Timothy W. Russell", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Yinghe Ding", - "author_inst": "Xiangya School of Medicine, Central South University" + "author_name": "Joesph Wu", + "author_inst": "The University of Hong Kong" }, { - "author_name": "Jia-da Li", - "author_inst": "Department of Biomedical Informatics, School of Life Sciences, Central South University" + "author_name": "Samuel Clifford", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Guoqing Huang", - "author_inst": "Department of Emergency, Xiangya Hospital, Central South University" + "author_name": "John Edmunds", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Ye Liang", - "author_inst": "Department of Oral and Maxillofacial Surgery, Center of Stomatology, Xiangya Hospital, Central South University," + "author_name": "Adam J Kucharski", + "author_inst": "London School of Hygiene & Tropical Medicine" }, { - "author_name": "Linyong Xu", - "author_inst": "Department of Biomedical Informatics, School of Life Sciences, Central South University" + "author_name": "Mark Jit", + "author_inst": "London School of Hygiene & Tropical Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1330757,29 +1330575,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.09.20150219", - "rel_title": "Estimating the time-varying reproduction number of COVID-19 with a state-space method", + "rel_doi": "10.1101/2020.07.09.20150136", + "rel_title": "An exploratory Integrated Moving Average Time Series Model of the initial outbreak of COVID-19 in six (6) significantly impacted Countries", "rel_date": "2020-07-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.09.20150219", - "rel_abs": "After slowing down the spread of the novel coronavirus COVID-19, many countries have started to relax their confinement measures in the face of critical damage to socioeconomic structures. At this stage, it is desirable to monitor the degree to which political measures or social affairs have exerted influence on the spread of disease. Though it is difficult to trace back individual transmission of infections whose incubation periods are long and highly variable, estimating the average spreading rate is possible if a proper mathematical model can be devised to analyze daily event-occurrences. To render an accurate assessment, we have devised a state-space method for fitting the Hawkes process to a given dataset of daily confirmed cases. The proposed method detects changes occurring in each country and assesses the impact of social events in terms of the temporally varying reproduction number, which corresponds to the average number of cases directly caused by a single infected case. Moreover, the proposed method can be used to predict the possible consequences of alternative political measures. This information can serve as a reference for behavioral guidelines that should be adopted according to the varying risk of infection.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.09.20150136", + "rel_abs": "The 2019 Novel Coronavirus SARS-CoV-2 (COVID-19) is a single-stranded RNA virus that has threatened the lives of humans all over the globe. Government officials, policy makers and public health officials have been scrambling and struggling to \"flatten the curve\" to decelerate the prevalence and spread of COVID-19 given the significant economic destruction of the spread of the virus. Most \"flatten the curve\" models are based on Compartmental Models. This preliminary research is based on six (6) selected countries significantly impacted by COVID-19 and endeavors to build a new model based on moving averages lagged at different time periods to better hone in on the time the COVID-19 begins to decelerate using the date of first reported case and date of first reported death. This new model, the Consistent Deceleration Model (CDM) is based on each individual countrys date of Peak Increase in Mortality Rate (PINC MR) and the Moving Average since the peak increase in mortality rate (MA POSTINC). The CDM can be utilized of one of many quantitative tools to determine the strength of the deceleration of an infectious outbreak.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Shinsuke Koyama", - "author_inst": "The Institute of Statistical Mathematics, Tokyo 190-8562, Japan" - }, - { - "author_name": "Taiki Horie", - "author_inst": "Department of Physics, Kyoto University, Kyoto 606-8502, Japan" + "author_name": "Joseph Pascarella", + "author_inst": "Saint Joseph's College - New York" }, { - "author_name": "Shigeru Shinomoto", - "author_inst": "Kyoto University" + "author_name": "Elaina Pascarella", + "author_inst": "University of Virginia" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1332143,85 +1331957,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.09.20149534", - "rel_title": "Saliva offers a sensitive, specific and non-invasive alternative to upper respiratory swabs for SARS-CoV-2 diagnosis.", + "rel_doi": "10.1101/2020.07.10.20150631", + "rel_title": "A comprehensive analysis of R0 with different lockdown phase during covid-19 in India", "rel_date": "2020-07-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.09.20149534", - "rel_abs": "RT-qPCR utilising upper respiratory swabs are the diagnostic gold standard for SARS-CoV-2 despite reported low sensitivity and limited scale up due to global shortages. Saliva is a non-invasive, equipment independent alternative to swabs.\n\nWe collected 145 paired saliva and nasal/throat (NT) swabs at diagnosis (day 0) and repeated on day 2 and day 7 dependent on inpatient care and day 28 for study follow up. Laboratory cultured virus was used to determine the analytical sensitivity of spiked saliva and swabs containing amies preservation media.\n\nSelf-collected saliva samples were found to be consistent, and in some cases superior when compared to healthcare worker collected NT swabs from COVID-19 suspected participants. We report for the first time the analytical limit of detection of 10-2and 100 pfu/ml for saliva and swabs respectively.\n\nSaliva is a easily self-collected, highly sensitive specimen for the detection of SARS-CoV-2.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.10.20150631", + "rel_abs": "BackgroundWorld Health organization declared Covid-19 as an outbreak, hence preventive measure like lockdown should be taken to control the spread of infection. This study offers an exhaustive analysis of the reproductive number (R0) in India with major intervention for COVID-19 outbreaks and analysed the lockdown effects on the Covid-19.\n\nMethodologyCovid-19 data extracted from Ministry of Health and Family Welfare, Government of India. Then, a novel method implemented in the incidence and Optimum function in desolve package to the data of cumulative daily new confirmed cases for robustly estimating the reproduction number in the R software.\n\nResultAnalysis has been seen that the lockdown was really quite as effective, India has already shown a major steady decline. The growth rate has fluctuated about 20 percent with trend line projections in various lockdown. A comparative analysis gives an idea of decline in value of R0 from 1.73 to 1.08. Annotation plot showing the predicted R0 values based on previous lockdown in month of June and July.\n\nConclusionWithout lockdown, the growth might not have been contained in India and may have gone into the exponential zone. We show that, the lockdown in India was fairly successful. The effect partial lifting of the lockdown (unlock) is also seen in the results, in terms of increment in R0 values. Hence this study provides a platform for policy makers and government authorities for implementing the strategies to prevent the spread of infection.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Rachel Louise Byrne", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Grant A Kay", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Konstantina Kontogianni", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Lottie Brown", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Andrea M Collins", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Luis E Cuevas", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Daniela Ferreira", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Alice J Fraser", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Gala Garrod", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Helen Hill", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Stefanie Menzies", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Mayank Chhabra", + "author_inst": "IIHMR UniversityJaipur" }, { - "author_name": "Elena Mitsi", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Sophie I Owen", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Christopher T Williams", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Angela Hyder-Wright", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Emily R Adams", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Ana I Cubas-Atienzar", - "author_inst": "Liverpool School of Tropical Medicine" + "author_name": "Tushant Agrawal", + "author_inst": "Amity University Rajasthan" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1333973,133 +1333727,109 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.07.07.20148478", - "rel_title": "Natural killer cell activation related to clinical outcome of COVID-19", + "rel_doi": "10.1101/2020.07.06.20143719", + "rel_title": "Performance characteristics of a high throughput automated transcription mediated amplification test for SARS-CoV-2 detection", "rel_date": "2020-07-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.07.20148478", - "rel_abs": "Understanding innate immune responses in COVID-19 is important for deciphering mechanisms of host responses and interpreting disease pathogenesis. Natural killer (NK) cells are innate effector lymphocytes that respond to acute viral infections, but might also contribute to immune pathology. Here, using 28-color flow cytometry, we describe a state of strong NK cell activation across distinct subsets in peripheral blood of COVID-19 patients, a pattern mirrored in scRNA-seq signatures of lung NK cells. Unsupervised high-dimensional analysis identified distinct immunophenotypes that were linked to disease severity. Hallmarks of these immunophenotypes were high expression of perforin, NKG2C, and Ksp37, reflecting a high presence of adaptive NK cell expansions in circulation of patients with severe disease. Finally, arming of CD56bright NK cells was observed in course of COVID-19 disease states, driven by a defined protein-protein interaction network of inflammatory soluble factors. This provides a detailed map of the NK cell activation-landscape in COVID-19 disease.", - "rel_num_authors": 29, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20143719", + "rel_abs": "The COVID-19 pandemic caused by the new SARS-CoV-2 coronavirus has imposed severe challenges on laboratories in their effort to achieve sufficient diagnostic testing capability for identifying infected individuals. In this study we report the analytical and clinical performance characteristics of a new, high-throughput, fully automated nucleic acid amplification test system for the detection of SARS-CoV-2. The assay utilizes target capture, transcription mediated amplification, and acridinium ester-labeled probe chemistry on the automated Panther System to directly amplify and detect two separate target sequences in the ORF1ab region of the SARS-CoV-2 RNA genome. The probit 95% limit of detection of the assay was determined to be 0.004 TCID50/ml using inactivated virus, and 25 c/ml using synthetic in vitro transcript RNA targets. Analytical sensitivity (100% detection) was confirmed to be 83 - 194 c/ml using three commercially available SARS-CoV-2 nucleic acid controls. No cross reactivity or interference was observed with testing six related human coronaviruses, as well as 24 other viral, fungal, and bacterial pathogens, at high titer. Clinical nasopharyngeal swab specimen testing (N=140) showed 100%, 98.7%, and 99.3% positive, negative, and overall agreement, respectively, with a validated reverse transcription PCR NAAT for SARS-CoV-2 RNA. These results provide validation evidence for a sensitive and specific method for pandemic-scale automated molecular diagnostic testing for SARS-CoV-2.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Christopher Maucourant", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" - }, - { - "author_name": "Iva Filipovic", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Jimmykim Pham", + "author_inst": "Hologic Inc" }, { - "author_name": "Andrea Ponzetta", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Sarah Meyer", + "author_inst": "Hologic Inc" }, { - "author_name": "Soo Aleman", - "author_inst": "Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden" - }, - { - "author_name": "Martin Cornillet", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" - }, - { - "author_name": "Laura Hertwig", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" - }, - { - "author_name": "Benedikt Strunz", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" - }, - { - "author_name": "Antonio Lentini", - "author_inst": "Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden" - }, - { - "author_name": "Bjorn Reinius", - "author_inst": "Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden" + "author_name": "Catherine Nguyen", + "author_inst": "Hologic Inc" }, { - "author_name": "Demi Brownlie", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Analee Williams", + "author_inst": "Hologic Inc" }, { - "author_name": "Angelica Cuapio Gomez", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Melissa Hunsicker", + "author_inst": "Hologic Inc" }, { - "author_name": "Eivind Heggernes Ask", - "author_inst": "Department of Cancer Immunology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway" + "author_name": "Ian McHardy", + "author_inst": "Scripps Health San Diego" }, { - "author_name": "Ryan M Hull", - "author_inst": "SciLifeLab, Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Solna, Sweden" + "author_name": "Inessa Gendlina", + "author_inst": "Montefiore Medical Center" }, { - "author_name": "Alvaro Haroun-Izquierdo", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "D. Yitzchak Goldstein", + "author_inst": "Montefiore Medical Center" }, { - "author_name": "Marie Schaffer", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Amy S. Fox", + "author_inst": "Montefiore Medical Center" }, { - "author_name": "Jonas Klingstrom", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Angela Hudson", + "author_inst": "Hologic Inc" }, { - "author_name": "Elin Folkesson", - "author_inst": "Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Paul Darby", + "author_inst": "Hologic Inc" }, { - "author_name": "Marcus Buggert", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Paul Hovey", + "author_inst": "Hologic Inc" }, { - "author_name": "Johan K Sandberg", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Jose Morales", + "author_inst": "Hologic Inc" }, { - "author_name": "Lars I Eriksson", - "author_inst": "Function Perioperative Medicine and Intensive Care, Karolinska University Hospital, Stockholm, Sweden." + "author_name": "James Mitchell", + "author_inst": "Hologic Inc" }, { - "author_name": "Olav Rooyackers", - "author_inst": "Function Perioperative Medicine and Intensive Care, Karolinska University Hospital, Stockholm, Sweden." + "author_name": "Karen Harrington", + "author_inst": "Hologic Inc" }, { - "author_name": "Hans-Gustaf Ljunggren", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Mehrdad Majlessi", + "author_inst": "Hologic Inc" }, { - "author_name": "Karl-Johan Malmberg", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Joshua Moberly", + "author_inst": "Hologic Inc" }, { - "author_name": "Jakob Michaelsson", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Ankur Shah", + "author_inst": "Hologic Inc" }, { - "author_name": "Nicole Marquardt", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Andrew Worlock", + "author_inst": "Hologic Inc" }, { - "author_name": "Quirin Hammer", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Marion Walcher", + "author_inst": "Hologic Inc" }, { - "author_name": "Kristoffer Stralin", - "author_inst": "Department of Infectious Diseases, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Barbara Eaton", + "author_inst": "Hologic Inc" }, { - "author_name": "Niklas K Bjorkstrom", - "author_inst": "Center for Infectious Medicine, Department of Medicine Huddinge, Karolinska Institutet, Karolinska University Hospital, Stockholm, Sweden" + "author_name": "Damon Getman", + "author_inst": "Hologic Inc" }, { - "author_name": "- Karolinska COVID-19 Study Group", - "author_inst": "-" + "author_name": "Craig Clark", + "author_inst": "Hologic Inc" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1335751,57 +1335481,77 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.07.09.194027", - "rel_title": "Severely ill COVID-19 patients display augmented functional properties in SARS-CoV-2-reactive CD8+ T cells", + "rel_doi": "10.1101/2020.07.09.196386", + "rel_title": "Replication-competent vesicular stomatitis virus vaccine vector protects against SARS-CoV-2-mediated pathogenesis", "rel_date": "2020-07-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.09.194027", - "rel_abs": "The molecular properties of CD8+ T cells that respond to SARS-CoV-2 infection are not fully known. Here, we report on the single-cell transcriptomes of >80,000 virus-reactive CD8+ T cells from 39 COVID-19 patients and 10 healthy subjects. COVID-19 patients segregated into two groups based on whether the dominant CD8+ T cell response to SARS-CoV-2 was exhausted or not. SARS-CoV-2-reactive cells in the exhausted subset were increased in frequency and displayed lesser cytotoxicity and inflammatory features in COVID-19 patients with mild compared to severe illness. In contrast, SARS-CoV-2-reactive cells in the non-exhausted subsets from patients with severe disease showed enrichment of transcripts linked to co-stimulation, pro-survival NF-{kappa}B signaling, and anti-apoptotic pathways, suggesting the generation of robust CD8+ T cell memory responses in patients with severe COVID-19 illness. CD8+ T cells reactive to influenza and respiratory syncytial virus from healthy subjects displayed polyfunctional features. Cells with such features were mostly absent in SARS-CoV-2 responsive cells from both COVID-19 patients and healthy controls non-exposed to SARS-CoV-2. Overall, our single-cell analysis revealed substantial diversity in the nature of CD8+ T cells responding to SARS-CoV-2.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.09.196386", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused millions of human infections and hundreds of thousands of deaths. Accordingly, an effective vaccine is of critical importance in mitigating coronavirus induced disease 2019 (COVID-19) and curtailing the pandemic. We developed a replication-competent vesicular stomatitis virus (VSV)-based vaccine by introducing a modified form of the SARS-CoV-2 spike gene in place of the native glycoprotein gene (VSV-eGFP-SARS-CoV-2). Immunization of mice with VSV-eGFP-SARS-CoV-2 elicits high titers of antibodies that neutralize SARS-CoV-2 infection and target the receptor binding domain that engages human angiotensin converting enzyme-2 (ACE2). Upon challenge with a human isolate of SARS-CoV-2, mice expressing human ACE2 and immunized with VSV-eGFP-SARS-CoV-2 show profoundly reduced viral infection and inflammation in the lung indicating protection against pneumonia. Finally, passive transfer of sera from VSV-eGFP-SARS-CoV-2-immunized animals protects naive mice from SARS-CoV-2 challenge. These data support development of VSV-eGFP-SARS-CoV-2 as an attenuated, replication-competent vaccine against SARS-CoV-2.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Anthony Kusnadi", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "James Brett Case", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Ciro Ram\u00edrez-Su\u00e1stegui", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Paul Rothlauf", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Vicente Fajardo", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Rita E. Chen", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Serena J Chee", - "author_inst": "University of Southampton" + "author_name": "Natasha Kafai", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Benjamin J Meckiff", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Julie M. Fox", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Hayley Simon", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Swathi Shrihari", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Emanuela Pelosi", - "author_inst": "University Hospital Southampton" + "author_name": "Broc T. McCune", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Gr\u00e9gory Seumois", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Ian B. Harvey", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Ferhat Ay", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Brittany Smith", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Pandurangan Vijayanand", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Shamus Keeler", + "author_inst": "Washington University School of Medicine" }, { - "author_name": "Christian H Ottensmeier", - "author_inst": "La Jolla Institute for Immunology" + "author_name": "Louis-Marie Bloyet", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Emma S Winkler", + "author_inst": "Washington University in St. Louis" + }, + { + "author_name": "Michael J. Holtzman", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Daved H. Fremont", + "author_inst": "Washington University School of Medicine" + }, + { + "author_name": "Sean P. J. Whelan", + "author_inst": "Washington University in Saint Louis" + }, + { + "author_name": "Michael S. Diamond", + "author_inst": "Washington University School of Medicine" } ], "version": "1", @@ -1338064,87 +1337814,31 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.07.09.195230", - "rel_title": "Human angiotensin-converting enzyme 2 transgenic mice infected with SARS-CoV-2 develop severe and fatal respiratory disease", - "rel_date": "2020-07-09", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.09.195230", - "rel_abs": "ABSTRACTThe emergence of SARS-CoV-2 has created an international health crisis. Small animal models mirroring SARS-CoV-2 human disease are essential for medical countermeasure (MCM) development. Mice are refractory to SARS-CoV-2 infection due to low affinity binding to the murine angiotensin-converting enzyme 2 (ACE2) protein. Here we evaluated the pathogenesis of SARS-CoV-2 in male and female mice expressing the human ACE2 gene under the control of the keratin 18 promotor. In contrast to non-transgenic mice, intranasal exposure of K18-hACE2 animals to two different doses of SARS-CoV-2 resulted in acute disease including weight loss, lung injury, brain infection and lethality. Vasculitis was the most prominent finding in the lungs of infected mice. Transcriptomic analysis from lungs of infected animals revealed increases in transcripts involved in lung injury and inflammatory cytokines. In the lower dose challenge groups, there was a survival advantage in the female mice with 60% surviving infection whereas all male mice succumbed to disease. Male mice that succumbed to disease had higher levels of inflammatory transcripts compared to female mice. This is the first highly lethal murine infection model for SARS-CoV-2. The K18-hACE2 murine model will be valuable for the study of SARS-CoV-2 pathogenesis and the assessment of MCMs.Competing Interest StatementThe authors have declared no competing interest.View Full Text", - "rel_num_authors": 17, + "rel_doi": "10.1101/2020.07.07.20148239", + "rel_title": "Rapid Systematic Review Exploring Historical and Present Day National and International Governance during Pandemics", + "rel_date": "2020-07-08", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.07.20148239", + "rel_abs": "IntroductionPandemics have plagued mankind since records began, and while non-communicable disease pandemics are more common in high-income nations, infectious disease pandemics continue to affect all countries worldwide. To mitigate impact, national pandemic preparedness and response policies remain crucial. And in response to emerging pathogens of pandemic potential, public health policies must be both dynamic and adaptive. Yet, this process of policy change and adaptation remains opaque. Accordingly, this rapid systematic review will synthesise and analyse evaluative policy literature to develop a roadmap of policy changes that have occurred after each pandemic event, throughout both the 20th and 21st Century, in order to better inform future policy development.\n\nMethods and AnalysisA rapid systematic review will be conducted to assimilate and synthesise both peer-reviewed articles and grey literature that document the then current pandemic preparedness policy, and the subsequent changes to that policy, across high-, middle- and low-income countries. The rapid review will follow the PRISMA guidelines, and the literature search will be performed across five relevant databases, as well as various government websites to scan for grey literature. Articles will be screen against pre-agreed inclusion/ exclusion criteria, and data will be extracted using a pre-defined charting table.\n\nEthics and DisseminationAll data rely on secondary, publicly available data sources; therefore no ethical clearance is required. Upon completion, the results of this study will be disseminated via the Imperial College London Community and published in an open access, peer-reviewed journal.\n\nArticle SummaryO_ST_ABSStrengths and Limitations of this StudyC_ST_ABSO_LIThis systematic review protocol is the first to focus on a longitudinal analysis of pandemic preparedness policy development across low, middle and high income country settings\nC_LIO_LIThis protocol and subsequent review benefit from increased transparency, a systematised strategy (PRISMA), and a reduction in the risk of bias, through publication in an open access journal\nC_LIO_LIThis review will also capture grey literature - studies published outside peer-reviewed journals\nC_LIO_LIThis review protocol and methodology is not as robust as systematic reviews, therefore will lack some of the robustness often associated will classical systematic reviews\nC_LI\n\nRegistration NumberOpen Science Framework: 10.17605/OSF.IO/VKA39", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Joseph Golden", - "author_inst": "United States Army Medical Research Institute of Infectious Diseases" - }, - { - "author_name": "Curtis Cline", - "author_inst": "USAMRIID" - }, - { - "author_name": "Xiankun Zeng", - "author_inst": "Fort Detrick" - }, - { - "author_name": "Aura Garrison", - "author_inst": "USAMRIID" - }, - { - "author_name": "Brian Carey", - "author_inst": "USAMRIID" - }, - { - "author_name": "Eric Mucker", - "author_inst": "USAMRIID" - }, - { - "author_name": "Lauren White", - "author_inst": "USAMRIID" - }, - { - "author_name": "Joshua Shamblin", - "author_inst": "USAMRIID" - }, - { - "author_name": "Rebecca Brocato", - "author_inst": "USAMRIID" - }, - { - "author_name": "Jun Liu", - "author_inst": "USAMRIID" - }, - { - "author_name": "April Babka", - "author_inst": "USAMRIID" - }, - { - "author_name": "Hypaitia Rauch", - "author_inst": "USAMRIID" - }, - { - "author_name": "Jeffrey M Smith", - "author_inst": "USAMRIID" - }, - { - "author_name": "Bradley Hollidge", - "author_inst": "USAMRIID" - }, - { - "author_name": "Collin Fitzpatrick", - "author_inst": "USAMRIID" + "author_name": "Elizabeth Lowry", + "author_inst": "Imperial College London" }, { - "author_name": "Catherine Badger", - "author_inst": "USAMRIID" + "author_name": "Henock Taddese", + "author_inst": "Imperial College London" }, { - "author_name": "Jay Hooper", - "author_inst": "USAMRIID" + "author_name": "Leigh R Bowman", + "author_inst": "Imperial College London" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "health policy" }, { "rel_doi": "10.1101/2020.07.06.20147678", @@ -1339894,29 +1339588,141 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.07.07.186122", - "rel_title": "Towards the design of multiepitope-based peptide vaccine candidate against SARS-CoV-2", + "rel_doi": "10.1101/2020.07.07.191007", + "rel_title": "SARS-CoV-2 infection induces germinal center responses with robust stimulation of CD4 T follicular helper cells in rhesus macaques", "rel_date": "2020-07-08", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.07.186122", - "rel_abs": "Coronavirus disease 2019 is a current pandemic health threat especially for elderly patients with comorbidities. This respiratory disease is caused by a beta coronavirus known as severe acute respiratory syndrome coronavirus 2. The disease can progress into acute respiratory distress syndrome that can be fatal. Currently, no specific drug or vaccine are available to combat this pandemic outbreak. Social distancing and lockdown have been enforced in many places worldwide. The spike protein of coronavirus 2 is essential for viral entry into host target cells via interaction with angiotensin converting enzyme 2. This viral protein is considered a potential target for design and development of a drug or vaccine. Previously, we have reported several potential epitopes on coronavirus 2 spike protein with high antigenicity, low allergenicity and good stability against specified proteases. In the current study, we have constructed and evaluated a peptide vaccine from these potential epitopes by using in silico approach. This construct is predicted to have a protective immunogenicity, low allergenicity and good stability with minor structural flaws in model build. The population coverage of the used T-cells epitopes is believed to be high according to the employed restricted alleles. The vaccine construct can elicit efficient and long-lasting immune response as appeared through simulation analysis. This multiepitope-based peptide vaccine may represent a potential candidate against coronavirus 2. However, further in vitro and in vivo verification are required.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.07.191007", + "rel_abs": "CD4 T follicular helper (Tfh) cells are important for the generation of long-lasting and specific humoral protection against viral infections. The degree to which SARS-CoV-2 infection generates Tfh cells and stimulates the germinal center response is an important question as we investigate vaccine options for the current pandemic. Here we report that, following infection with SARS-CoV-2, adult rhesus macaques exhibited transient accumulation of activated, proliferating Tfh cells in their peripheral blood on a transitory basis. The CD4 helper cell responses were skewed predominantly toward a Th1 response in blood, lung, and lymph nodes, reflective of the interferon-rich cytokine environment following infection. We also observed the generation of germinal center Tfh cells specific for the SARS-CoV-2 spike (S) and nucleocapsid (N) proteins, and a corresponding early appearance of antiviral serum IgG antibodies but delayed or absent IgA antibodies. Our data suggest that a vaccine promoting Th1-type Tfh responses that target the S protein may lead to protective immunity.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Hasanain Abdulhameed Odhar", - "author_inst": "Al-Zahrawi University College" + "author_name": "Sonny R. Elizaldi", + "author_inst": "UC Davis" + }, + { + "author_name": "Yashavanth Shaan Lakshmanappa", + "author_inst": "UC Davis" + }, + { + "author_name": "Jamin W. Roh", + "author_inst": "UC Davis" + }, + { + "author_name": "Brian A. Schmidt", + "author_inst": "UC Davis" + }, + { + "author_name": "Timothy D. Carroll", + "author_inst": "UC Davis" + }, + { + "author_name": "Kourtney D. Weaver", + "author_inst": "Louisiana State University" + }, + { + "author_name": "Justin C. Smith", + "author_inst": "Louisiana State University" }, { - "author_name": "Salam Waheed Ahjel", - "author_inst": "Al-Zahrawi University College" + "author_name": "Jesse D. Deere", + "author_inst": "UC Davis" }, { - "author_name": "Suhad Sami Humadi", - "author_inst": "Al-Zahrawi University College" + "author_name": "Joseph Dutra", + "author_inst": "UC Davis" + }, + { + "author_name": "Mars Stone", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Rebecca Lee Sammak", + "author_inst": "UC Davis" + }, + { + "author_name": "Katherine J. Olstad", + "author_inst": "UC Davis" + }, + { + "author_name": "J. Rachel Reader", + "author_inst": "UC Davis" + }, + { + "author_name": "Zhong-Min Ma", + "author_inst": "UC Davis" + }, + { + "author_name": "Nancy K. Nguyen", + "author_inst": "UC Davis" + }, + { + "author_name": "Jennifer Watanabe", + "author_inst": "UC Davis" + }, + { + "author_name": "Jodie Usachaenko", + "author_inst": "UC Davis" + }, + { + "author_name": "Ramya Immareddy", + "author_inst": "UC Davis" + }, + { + "author_name": "JoAnn L. Yee", + "author_inst": "UC Davis" + }, + { + "author_name": "Daniela Weiskopf", + "author_inst": "La Jolla Institute for Immunology" + }, + { + "author_name": "Alessandro Sette", + "author_inst": "La Jolla Institute for Immunology" + }, + { + "author_name": "Dennis Hartigan-OConnor", + "author_inst": "UC Davis" + }, + { + "author_name": "Stephen J. McSorley", + "author_inst": "UC Davis" + }, + { + "author_name": "John H. Morrison", + "author_inst": "UC Davis" + }, + { + "author_name": "Nam K. Tran", + "author_inst": "UC Davis" + }, + { + "author_name": "Graham Simmons", + "author_inst": "University of California, San Francisco" + }, + { + "author_name": "Michael P Busch", + "author_inst": "La Jolla Institute for Immunology" + }, + { + "author_name": "Pamela A. Kozlowski", + "author_inst": "Louisiana State University" + }, + { + "author_name": "Koen K.A. Van Rompay", + "author_inst": "UC Davis" + }, + { + "author_name": "Christopher J. Miller", + "author_inst": "UC Davis" + }, + { + "author_name": "Smita S Iyer", + "author_inst": "UC Davis" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "new results", "category": "immunology" }, @@ -1341296,91 +1341102,67 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2020.07.05.20146878", - "rel_title": "Effect of Systemic Inflammatory Response to SARS-CoV-2 on Lopinavir and Hydroxychloroquine Plasma Concentrations", + "rel_doi": "10.1101/2020.07.05.20146779", + "rel_title": "Rats and the COVID-19 pandemic: Early data on the global emergence of rats in response to social distancing", "rel_date": "2020-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.05.20146878", - "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19) leads to inflammatory cytokine release, which can downregulate the expression of metabolizing enzymes. This cascade affects drug concentrations in the plasma. We investigated the association between lopinavir (LPV) and hydroxychloroquine (HCQ) plasma concentrations and the values of acute phase inflammation marker C-reactive protein (CRP).\n\nMethodsLPV plasma concentrations were prospectively collected in 92 patients hospitalized at our institution. Lopinavir/ritonavir was administered 12-hourly, 800/200 mg on day 1, and 400/100 mg on day 2 until day 5 or 7. HCQ was given at 800 mg, followed by 400 mg after 6, 24 and 48 hours. Hematological, liver, kidney, and inflammation laboratory values were analyzed on the day of drug level determination.\n\nResultsThe median age of study participants was 59 (range 24-85) years, and 71% were male. The median duration from symptom onset to hospitalization and treatment initiation was 7 days (IQR 4-10) and 8 days (IQR 5-10), respectively. The median LPV trough concentration on day 3 of treatment was 26.5 g/mL (IQR 18.9-31.5). LPV plasma concentrations positively correlated with CRP values (r=0.37, p<0.001), and were significantly lower when tocilizumab was preadministrated. No correlation was found between HCQ concentrations and CRP values.\n\nConclusionsHigh LPV plasma concentrations were observed in COVID-19 patients. The ratio of calculated unbound drug fraction to published SARS-CoV-2 EC50 values indicated insufficient LPV concentrations in the lung. CRP values significantly correlated with LPV but not HCQ plasma concentrations, implying inhibition of cytochrome P450 3A4 (CYP3A4) metabolism by inflammation.", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.05.20146779", + "rel_abs": "Following widespread closures of food-related businesses due to efforts to curtail the spread of SARS-CoV-2, public health authorities reported increased sightings of rats in close vicinity of people. Because rats vector a number of pathogens transmissible to people, changes in their behavior has consequences for human health risks. To determine the extent of how stay-at-home measures influenced patterns of rat sightings we: 1) examined the number of rat-related public service requests before and during the period of lockdown in New York City (NYC) and Tokyo, Japan; 2) examined reports made in proximity to closed food service establishments in NYC; and 3) surveyed pest control companies in the United States, Canada, Japan, and Poland. During the month following lockdown, the overall number of reports decreased by 30% in NYC, while increasing 24% in Tokyo. However, new hotspots of 311 calls were observed in proximity of closed food service establishments in NYC; and there was a consistent positive association between kernel density estimates of food service establishments and location of 311 calls (r = 0.33 to 0.45). Similarly, more reports were observed in the restaurant-dense eastern side of Tokyo. Changes in clientele for pest control companies varied geographically, with 37% of pest-management companies surveyed in North America reporting 50-100% of their post-lockdown rat-related requests coming from new clients. In Warsaw, where there are no clusters of restaurants in densely-populated areas, there were no changes. In Tokyo, there were no changes in clients. We conclude that changes in public service calls are region-specific and localized, with increases in rat sightings more likely near restaurant-dense regions. Pest control companies surveyed in North America either lost much of their business or shifted clientele from old to new locations. We discuss possible mitigation measures including ramping up pest control during re-opening of food-related establishments and the need for citywide rodent surveillance and disease monitoring.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Catia Marzolini", - "author_inst": "University Hospital Basel" - }, - { - "author_name": "Felix Stader", - "author_inst": "University Hospital Basel" - }, - { - "author_name": "Marcel Stoeckle", - "author_inst": "University Hospital Basel" - }, - { - "author_name": "Fabian Franzeck", - "author_inst": "University Hospital Basel" - }, - { - "author_name": "Adrian Egli", - "author_inst": "University Hospital Basel" - }, - { - "author_name": "Stefano Bassetti", - "author_inst": "University Hospital Basel" - }, - { - "author_name": "Alexa Hollinger", - "author_inst": "University Hospital Basel" + "author_name": "Michael H Parsons", + "author_inst": "Fordham University" }, { - "author_name": "Michael Osthoff", - "author_inst": "University Hospital Basel" + "author_name": "Yasushi Kiyokawa", + "author_inst": "University of Tokyo" }, { - "author_name": "Maja Weisser", - "author_inst": "University Hospital Basel" + "author_name": "Jonathan L Richardson", + "author_inst": "University of Tokyo" }, { - "author_name": "Eva Caroline Gebhard", - "author_inst": "University Hospital Basel" + "author_name": "Rafal Stryjek", + "author_inst": "Polish Academy of Sciences" }, { - "author_name": "Veronika Baettig", - "author_inst": "University Hospital Basel" + "author_name": "Kaylee A. Byers", + "author_inst": "University British Columbia" }, { - "author_name": "Julia Geenen", - "author_inst": "University Hospital Basel" + "author_name": "Chelsea G Himsworth", + "author_inst": "The Animal Health Centre, British Columbia" }, { - "author_name": "Nina Khanna", - "author_inst": "University Hospital Basel" + "author_name": "Robert M Corrigan", + "author_inst": "RMC Pest Management Consulting" }, { - "author_name": "Sarah Tschudin-Sutter", - "author_inst": "University Hospital Basel" + "author_name": "Michael A Deutsch", + "author_inst": "Arrow Exterminating Company, Inc." }, { - "author_name": "Daniel Mueller", - "author_inst": "University Hospital Basel" + "author_name": "Masato Ootaki", + "author_inst": "University of Tokyo" }, { - "author_name": "Hans Hirsch", - "author_inst": "University Hospital Basel" + "author_name": "Tsutomu Tanikawa", + "author_inst": "Tokyo Pest Control Association" }, { - "author_name": "Manuel Battegay", - "author_inst": "University Hospital Basel" + "author_name": "Faith E Parsons", + "author_inst": "CareSet Systems" }, { - "author_name": "Parham Sendi", - "author_inst": "University Hospital Basel" + "author_name": "Jason Munch-South", + "author_inst": "Fordham University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.07.05.20146738", @@ -1342550,21 +1342332,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.05.20146837", - "rel_title": "Change points in the spread of COVID-19 question the effectiveness of nonpharmaceutical interventions in Germany", + "rel_doi": "10.1101/2020.07.06.20147660", + "rel_title": "Predicted effects of summer holidays and seasonality on the SARS-Cov-2 epidemic in France", "rel_date": "2020-07-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.05.20146837", - "rel_abs": "AimsNonpharmaceutical interventions against the spread of SARS-CoV-2 in Germany included the cancellation of mass events (from March 8), closures of schools and child day care facilities (from March 16) as well as a \"lockdown\" (from March 23). This study attempts to assess the effectiveness of these interventions in terms of revealing their impact on infections over time.\n\nMethodsDates of infections were estimated from official German case data by incorporating the incubation period and an empirical reporting delay. Exponential growth models for infections and reproduction numbers were estimated and investigated with respect to change points in the time series.\n\nResultsA significant decline of daily and cumulative infections as well as reproduction numbers is found at March 8 (CI [7, 9]), March 10 (CI [9, 11] and March 3 (CI [2, 4]), respectively. Further declines and stabilizations are found in the end of March. There is also a change point in new infections at April 19 (CI [18, 20]), but daily infections still show a negative growth. From March 19 (CI [18, 20]), the reproduction numbers fluctuate on a level below one.\n\nConclusionsThe decline of infections in early March 2020 can be attributed to relatively small interventions and voluntary behavioural changes. Additional effects of later interventions cannot be detected clearly. Liberalizations of measures did not induce a re-increase of infections. Thus, the effectiveness of most German interventions remains questionable. Moreover, assessing of interventions is impeded by the estimation of true infection dates and the influence of test volume.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.06.20147660", + "rel_abs": "1The SARS-CoV-2 epidemic in France has had a large death toll. It has not affected all regions similarly, since the death rate can vary several folds between regions where the epidemic has remained at a low level and regions where it got an early burst. The epidemic has been slowed down by a lockdown that lasted for almost eight weeks, and individuals can now move between metropolitan French regions without restriction. In this report we investigate the effect on the epidemic of summer holidays, during which millions of individuals will move between French regions. Additionally, we evaluate the effect of strong or weak seasonality and of several values for the reproduction number on the epidemic, in particular on the timing, the height and the spread of a second wave. To do so, we extend a SEIR model to simulate the effect of summer migrations between regions on the number and distribution of new infections. We find that the model predicts little effect of summer migrations on the epidemic, because the number of migrating infectious individuals are low as a consequence of the lockdown. However, all the reproduction numbers above 1.0 and the seasonality parameters we tried result in a second epidemic wave, with a peak date that can vary between October 2020 and April 2021. If the sanitary measures currently in place manage to keep the reproduction number below 1.0, the second wave will be avoided. If they keep the reproduction number at a low value, for instance at 1.1 as in one of our simulations, the second wave is flattened and could be similar to the first wave.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Thomas Wieland", - "author_inst": "Karlsruhe Institute of Technology" + "author_name": "Louis Duchemin", + "author_inst": "Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive UMR 5558, F-69622 Villeurbanne, France" + }, + { + "author_name": "Mathilde Paris", + "author_inst": "IGFL, Institut de Genomique Fonctionnelle de Lyon, Universite de Lyon, Ecole Normale Superieure de Lyon, CNRS, Universite Claude Bernard Lyon 1, UMR 5242, 69364" + }, + { + "author_name": "Bastien Boussau", + "author_inst": "Universite de Lyon, Universite Lyon 1, CNRS, Laboratoire de Biometrie et Biologie Evolutive UMR 5558, F-69622 Villeurbanne, France" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1343960,47 +1343750,31 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.07.03.20145912", - "rel_title": "Ultraviolet A Radiation and COVID-19 Deaths: A Multi Country Study", + "rel_doi": "10.1101/2020.07.05.187344", + "rel_title": "N and O glycosylation of the SARS-CoV-2 spike protein", "rel_date": "2020-07-06", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.03.20145912", - "rel_abs": "ObjectivesTo determine whether UVA exposure might be associated with COVID-19 deaths\n\nDesignEcological regression, with replication in two other countries and pooled estimation\n\nSetting2,474 counties of the contiguous USA, 6,755 municipalities in Italy, 6,274 small areas in England. Only small areas in their Vitamin D winter (monthly mean UVvitd of under 165 KJ/m2) from Jan to April 2020.\n\nParticipants\n\nThe at-risk population is the total small area population, with measures to incorporate spatial infection into the model. The model is adjusted for potential confounders including long-term winter temperature and humidity.\n\nMain outcome measuresWe derive UVA measures for each area from remote sensed data and estimate their relationship with COVID-19 mortality with a random effect for States, in a multilevel zero-inflated negative binomial model. In the USA and England death certificates had to record COVID-19. In Italy excess deaths in 2020 over expected from 2015-19.\n\nData sourcesSatellite derived mean daily UVA dataset from Japan Aerospace Exploration Agency. Data on deaths compiled by Center for Disease Control (USA), Office for National Statistics (England) and Italian Institute of Statistics.\n\nResultsDaily mean UVA (January-April 2020) varied between 450 to 1,000 KJ/m2 across the three countries. Our fully adjusted model showed an inverse correlation between UVA and COVID-19 mortality with a Mortality Risk Ratio (MRR) of 0.71 (0.60 to 0.85) per 100KJ/m2 increase UVA in the USA, 0.81 (0.71 to 0.93) in Italy and 0.49 (0.38 to 0.64) in England. Pooled MRR was 0.68 (0.52 to 0.88).\n\nConclusionsOur analysis, replicated in 3 independent national datasets, suggests ambient UVA exposure is associated with lower COVID-19 specific mortality. This effect is independent of vitamin D, as it occurred at irradiances below that likely to induce significant cutaneous vitamin D3 synthesis. Causal interpretations must be made cautiously in observational studies. Nonetheless this study suggests strategies for reduction of COVID-19 mortality.", - "rel_num_authors": 7, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.07.05.187344", + "rel_abs": "Covid-19 pandemic outbreak is the reason of the current world health crisis. The development of effective antiviral compounds and vaccines requires detailed descriptive studies of the SARS-CoV-2 proteins. The SARS-CoV-2 spike (S) protein mediates virion binding to the human cells through its interaction with the ACE2 cell surface receptor and is one of the prime immunization targets. A functional virion is composed of three S1 and three S2 subunits created by furin cleavage of the spike protein at R682, a polybasic cleavage sites that differs from the SARS-CoV spike protein of 2002. We observe that the spike protein is O-glycosylated on a threonine (T678) near the furin cleavage site occupied by core-1 and core-2 structures. In addition, we have identified eight additional O-glycopeptides on the spike glycoprotein and we confirmed that the spike protein is heavily N-glycosylated. Our recently developed LC-MS/MS methodology allowed us to identify LacdiNAc structural motives on all occupied N-glycopeptides and polyLacNAc structures on six glycopeptides of the spike protein. In conclusion, our study substantially expands the current knowledge of the spike proteins glycosylation and enables the investigation of the influence of the O-glycosylation on its proteolytic activation.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Mark Cherrie", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Tom Clemens", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Claudio Colandrea", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "Zhiqiang Feng", - "author_inst": "University of Edinburgh" - }, - { - "author_name": "David Webb", - "author_inst": "University of Edinburgh" + "author_name": "Miloslav Sanda", + "author_inst": "Georgetown University" }, { - "author_name": "Chris Dibben", - "author_inst": "University of Edinburgh" + "author_name": "Lindsay Morrison", + "author_inst": "Waters Corporation" }, { - "author_name": "Richard B Weller", - "author_inst": "University of Edinburgh" + "author_name": "Radoslav Goldman", + "author_inst": "Georgetown University" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "license": "cc_no", + "type": "new results", + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.07.06.190066", @@ -1345398,27 +1345172,43 @@ "category": "dermatology" }, { - "rel_doi": "10.1101/2020.07.03.20145763", - "rel_title": "Oxygen and mortality in COVID-19 pneumonia: a comparative analysis of supplemental oxygen policies and health outcomes across 26 countries.", + "rel_doi": "10.1101/2020.07.03.20146159", + "rel_title": "Sub-epidemic model forecasts for COVID-19 pandemic spread in the USA and European hotspots, February-May 2020", "rel_date": "2020-07-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.03.20145763", - "rel_abs": "IntroductionHypoxia is the main cause of morbidity and mortality in COVID-19. During the COVID-19 pandemic some countries have reduced access to supplemental oxygen (e.g. oxygen rationing), whereas other nations have maintained and even improved access to supplemental oxygen. We examined whether such variation in the access to supplemental oxygen had any bearing on mortality in COVID-19.\n\nMethodsThree independent investigators searched for, identified and extracted the nationally recommended target oxygen levels for the commencement of oxygen in COVID-19 pneumonia from the 29 worst affected countries. Mortality estimates were calculated from three independent sources. We then applied linear regression analysis to examine for potential association between national targets for the commencement of oxygen and case fatality rates.\n\nResultsOf the 26 nations included, 15 had employed conservative oxygen strategies to manage COVID-19 pneumonia. Of them, Belgium, France, USA, Canada, China, Germany, Mexico, Spain, Sweden and the UK guidelines advised commencing oxygen when oxygen saturations (SpO2) fell to 91% or less. Target SpO2 ranged from 92% to 95% in the other 16 nations. Linear regression analysis demonstrated a strong inverse correlation between the national target for the commencement of oxygen and national case fatality rates (Spearmans Rho = -0.622, p < 0.001).\n\nConclusionOur study highlights the disparity in oxygen provision for COVID-19 patients between the nations analysed, and indicates such disparity in access to supplemental oxygen may represent a modifiable factor associated with mortality during the pandemic.\n\nKey MessagesO_ST_ABSWhat is already known?C_ST_ABSO_LIThere were no prospective clinical trials we could identify relating to COVID-19 and supplemental oxygen, nor any published studies examining access to supplemental oxygen and mortality in COVID-19.\nC_LIO_LIThere are a number of studies identifying an association with low oxygen saturations at presentation and mortality in COVID-19 pneumonia.\nC_LIO_LIThere is good quality evidence that a delay in the correction of hypoxia in pneumonia increases mortality.\nC_LI\n\nWhat are the new findings?O_LIThis study highlights the different thresholds for commencing supplemental oxygen in patients with COVID-19 across 26 nations.\nC_LIO_LIThose countries that provide better access to supplemental oxygen have a statistically significant lower mortality rate.\nC_LIO_LIOur results support the consensus view that improving access to supplemental oxygen in COVID-19 pneumonia is likely to reduce mortality.\nC_LI", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.03.20146159", + "rel_abs": "Mathematical models have been widely used to understand the dynamics of the ongoing coronavirus disease 2019 (COVID-19) pandemic as well as to predict future trends and assess intervention strategies. The asynchronicity of infection patterns during this pandemic illustrates the need for models that can capture dynamics beyond a single-peak trajectory to forecast the worldwide spread and for the spread within nations and within other sub-regions at various geographic scales. Here, we demonstrate a five-parameter sub-epidemic wave modeling framework that provides a simple characterization of unfolding trajectories of COVID-19 epidemics that are progressing across the world at different spatial scales. We calibrate the model to daily reported COVID-19 incidence data to generate six sequential weekly forecasts for five European countries and five hotspot states within the United States. The sub-epidemic approach captures the rise to an initial peak followed by a wide range of post-peak behavior, ranging from a typical decline to a steady incidence level to repeated small waves for sub-epidemic outbreaks. We show that the sub-epidemic model outperforms a three-parameter Richards model, in terms of calibration and forecasting performance, and yields excellent short- and intermediate-term forecasts that are not attainable with other single-peak transmission models of similar complexity. Overall, this approach predicts that a relaxation of social distancing measures would result in continuing sub-epidemics and ongoing endemic transmission. We illustrate how this view of the epidemic could help data scientists and policymakers better understand and predict the underlying transmission dynamics of COVID-19, as early detection of potential sub-epidemics can inform model-based decisions for tighter distancing controls.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "- The Gibraltar COVID-19 Research Group: Health Systems", - "author_inst": "" + "author_name": "Gerardo Chowell", + "author_inst": "Georgia State University" }, { - "author_name": "Daniel Goyal", - "author_inst": "University of Gibraltar, Medicine and Public Health" + "author_name": "Richard Rothenberg", + "author_inst": "Georgia State University" + }, + { + "author_name": "Kimberlyn Roosa", + "author_inst": "Georgia State University" + }, + { + "author_name": "Amna Tariq", + "author_inst": "Georgia State University" + }, + { + "author_name": "James M Hyman", + "author_inst": "Tulane University" + }, + { + "author_name": "Ruiyan Luo", + "author_inst": "Georgia State University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.07.03.20146076", @@ -1346704,27 +1346494,55 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.07.02.20144899", - "rel_title": "Curve-fitting approach for COVID-19 data and its physical background", + "rel_doi": "10.1101/2020.07.02.20144857", + "rel_title": "Metabolic indicators associated with non-communicable diseases deteriorated in COVID-19 outbreak: evidence from a two-center, retrospective study", "rel_date": "2020-07-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20144899", - "rel_abs": "Forecast of the peak-out and settling timing of COVID-19 at an early stage should help the people how to cope with the situation. Curve-fitting method with an asymmetric log-normal function has been applied to daily confirmed cases data in various countries. Most of the curve-fitting could show good forecasts, while the reason has not been clearly shown. The K value has recently been proposed which can provide good reasoning of curve-fitting mechanism by corresponding a long and steep slope on the K curve with fitting stability. Since K can be expressed by a time differential of logarithmic total cases, the physical background of the above correspondence was discussed in terms of the growth rate in epidemic entropy.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.02.20144857", + "rel_abs": "ObjectiveOur study aimed to investigate whether the metabolic indicators associated with non-communicable diseases (NCDs) in the general population have changed during the COVID-19 outbreak.\n\nMETHODSThis retrospective self-controlled study enrolled adult participants with metabolic indicators relate to NCDs followed at Fujian Provincial Hospital and Fujian Provincial Hospital South Branch. The metabolic indicators followed during January 1, 2020 and April 30, 2020, the peak period of the COVID-19 epidemic in China, were compared with the baseline value in the same period last year. Pared-samples T-test and Wilcoxon signed-rank test were performed to analyze the differences between paired data.\n\nResultsThe follow-up total cholesterol was significantly increased than that of the baseline (4.73 (4.05, 5.46) mmol/L vs 4.71 (4.05, 5.43) mmol/L, p=0.019; n=3379). Similar results were observed in triglyceride (1.29 (0.91, 1.88) vs 1.25 (0.87, 1.81) mmol/L, p<0.001; n=3381), uric acid (330.0 (272.0, 397.0) vs 327.0 (271.0, 389.0) umol/L, p<0.001; n=3364), and glycosylated hemoglobin (6.50 (6.10, 7.30) vs 6.50 (6.10, 7.20) %, p=0.013; n=532). No significant difference was observed in low density lipoprotein, body mass index and blood pressure.\n\nConclusionsMetabolic indicators associated with NCDs deteriorated in the COVID-19 outbreak. We should take action to prevent and control NCDs without delay.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Yoshiro Nishimoto", - "author_inst": "Science Research Group" + "author_name": "Ting Xue", + "author_inst": "Fujian Medical University" }, { - "author_name": "Kenichi Inoue", - "author_inst": "KOBELCO Research Institute, Inc." + "author_name": "Lizhen Xu", + "author_inst": "Fujian Medical University" + }, + { + "author_name": "mao yaqian", + "author_inst": "Department of endocrinology, Fujian Provincial Hospital" + }, + { + "author_name": "Wei Lin", + "author_inst": "Fujian Medical University" + }, + { + "author_name": "Jixing Liang", + "author_inst": "Fujian Medical University" + }, + { + "author_name": "Huibin Huang", + "author_inst": "Fujian Medical University" + }, + { + "author_name": "Liantao Li", + "author_inst": "Fujian Medical University" + }, + { + "author_name": "Junping Wen", + "author_inst": "Fujian Medical University" + }, + { + "author_name": "Gang Chen", + "author_inst": "Fujian Provincial Hospital" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2020.07.02.20145003", @@ -1348270,21 +1348088,45 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.30.20143149", - "rel_title": "Orthogonal Functions for Evaluating Social Distancing Impact on CoVID-19 Spread", + "rel_doi": "10.1101/2020.07.01.20144329", + "rel_title": "Low plasma 25(OH) vitamin D3 level is associated with increased risk of COVID-19 infection: an Israeli population-based study", "rel_date": "2020-07-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.30.20143149", - "rel_abs": "Early CoVID-19 growth often obeys: [Formula], with Ko = [(ln 2)/(tdbl)], where tdbl is the pandemic doubling time, prior to society-wide Social Distancing. Previously, we modeled Social Distancing with tdbl as a linear function of time, where N [t] 1 {approx} exp[+KA t/ (1+,{gamma}ot)] is used here. Additional parameters besides {Ko,{gamma} o} are needed to better model different{rho} [t] = dN [t]/dt shapes. Thus, a new Orthogonal Function Model [OFM] is developed here using these orthogonal function series: O_FD O_INLINEFIG[Formula 1]C_INLINEFIGM_FD(1)C_FD where N (Z) and Z[t] form an implicit N [t] N (Z[t]) function, giving: O_FD O_INLINEFIG[Formula 2]C_INLINEFIGM_FD(2)C_FD with Lm(Z) being the Laguerre Polynomials. At large MF values, nearly arbitrary functions for N [t] and{rho} [t] = dN [t]/dt can be accommodated. How to determine {KA,{gamma} o} and the {gm; m = (0, +MF)} constants from any given N (Z) dataset is derived, with{rho} [t] set by: O_FD O_INLINEFIG[Formula 3]C_INLINEFIGM_FD(3)C_FD\n\nThe bing com USA CoVID-19 data was analyzed using MF = (0, 1, 2) in the OFM. All results agreed to within about 10 percent, showing model robustness. Averaging over all these predictions gives the following overall estimates for the number of USA CoVID-19 cases at the pandemic end: O_FD O_INLINEFIG[Formula 4]C_INLINEFIGM_FD(4)C_FD which compares the pre- and post-early May bing com revisions. The CoVID-19 pandemic in Italy was examined next. The MF = 2 limit was inadequate to model the Italy{rho} [t] pandemic tail. Thus, regions with a quick CoVID-19 pandemic shutoff may have additional Social Distancing factors operating, beyond what can be easily modeled by just progressively lengthening pandemic doubling times (with 13 Figures).", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.01.20144329", + "rel_abs": "AimTo evaluate associations of plasma 25(OH)D status with the likelihood of coronavirus disease (COVID-19) infection and hospitalization.\n\nMethodsThe study population included the 14,000 members of Leumit Health Services who were tested for COVID-19 infection from February 1st to April 30th 2020, and who had at least one previous blood test for plasma 25(OH)D level. \"Suboptimal\" or \"low\" plasma 25(OH)D level was defined as plasma 25-hydroxyvitamin D, or 25(OH)D, concentration below 30 ng/mL.\n\nResultsOf 7,807 individuals, 782 (10.1%) were COVID-19-positive, and 7,025 (89.9%) COVID-19-negative. The mean plasma vitamin D level was significantly lower among those who tested positive than negative for COVID-19 [19.00 ng/mL (95% confidence interval [CI] 18.41-19.59) vs. 20.55 (95% CI 20.32-20.78)]. Univariate analysis demonstrated an association between low plasma 25(OH)D level and increased likelihood of COVID-19 infection [crude odds ratio (OR) of 1.58 (95% CI 1.24-2.01, p<0.001)], and of hospitalization due to the SARS-CoV-2 virus [crude OR of 2.09 (95% CI 1.01-4.30, p<0.05)]. In multivariate analyses that controlled for demographic variables, and psychiatric and somatic disorders, the adjusted OR of COVID-19 infection [1.45 (95% CI 1.08-1.95, p<0.001)], and of hospitalization due to the SARS-CoV-2 virus [1.95 (95% CI 0.98-4.845, p=0.061)] were preserved. In the multivariate analyses, age over 50 years, male gender and low-medium socioeconomic status were also positively associated with the risk of COVID-19 infection; age over 50 years was positively associated with the likelihood of hospitalization due to COVID-19.\n\nConclusionLow plasma 25(OH)D level appears to be an independent risk factor for COVID-19 infection and hospitalization.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Genghmun Eng", - "author_inst": "Retired Scientist" + "author_name": "Eugene Merzon", + "author_inst": "Leumit Health Services, Tel-Aviv, Israel; Department of Family Medicine, Sackler School of Medicine, Tel Aviv University, Tel Aviv, Israel;" + }, + { + "author_name": "Dmitry Tworowski", + "author_inst": "Weizmann Institute of Science; Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Israel." + }, + { + "author_name": "Alessandro Gorohovski", + "author_inst": "Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Israel." + }, + { + "author_name": "Shlomo Vinker", + "author_inst": "Leumit Health Services, Tel-Aviv, Israel; Department of Family Medicine, Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel;" + }, + { + "author_name": "Avivit Golan Cohen", + "author_inst": "Leumit Health Services, Tel-Aviv, Israel; Department of Family Medicine, Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel;" + }, + { + "author_name": "Ilan Green", + "author_inst": "Leumit Health Services, Tel-Aviv, Israel; Department of Family Medicine, Sackler School of Medicine, Tel-Aviv University, Tel-Aviv, Israel;" + }, + { + "author_name": "Milana Frenkel Morgenstern", + "author_inst": "Cancer Genomics and BioComputing of Complex Diseases Lab, Azrieli Faculty of Medicine, Bar-Ilan University, Israel." } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1349856,73 +1349698,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.07.01.20144162", - "rel_title": "Mass Screening for SARS-CoV-2 Infection among Residents and Staff in Twenty-eight Long-term Care Facilities in Fulton County, Georgia", + "rel_doi": "10.1101/2020.06.30.20143909", + "rel_title": "Exploring Epidemiological Behavior of Novel Coronavirus Outbreak through the Development and Analysis of COVID-19 Daily Dataset in Bangladesh", "rel_date": "2020-07-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.07.01.20144162", - "rel_abs": "Mass screening for SARS-CoV-2 infection in long-term care facilities revealed significantly higher prevalence of infection in facilities that screened in response to a known infection compared to those that screened as a prevention measure. \"Response\" facilities had a SARS-CoV-2 prevalence of 28.9% while \"preventive\" facilities prevalence was 1.6% (p <0.001).", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.30.20143909", + "rel_abs": "BackgroundGlobally, there is an obvious concern about the fact that the evolving 2019-nCoV coronavirus is a worldwide public health threat. The appearance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in China at the end of 2019 triggered a major global epidemic, which is now a major community health issue. As of April 17, 2020, according to Institute of Epidemiology, Disease Control and Research (IEDCR) Bangladesh has reported 1838 confirmed cases in between 8 March to 17 April 2020, with > 4.08% of mortality rate and >3.15% of recovery rate. COVID-19 outbreak is evolving so rapidly in Bangladesh; therefore, the availability of epidemiological data and its sensible analysis are essential to direct strategies for situational awareness and intervention.\n\nMethodThis article presents an exploratory data analysis approach to collect and analyze COVID-19 data on epidemiological outbreaks based on first publicly available COVID-19 Daily Dataset of Bangladesh. Various publicly open data sources on the outbreak of COVID-19 provided by the IEDCR, World Health Organization (WHO), Directorate General of Health Services (DGHS), and Ministry of Health and Family Welfare (MHFW) of Bangladesh have been used in this research.\n\nResultsA Visual Exploratory Data Analysis (V-EDA) techniques have been followed in this research to understand the epidemiological characteristics of COVID-19 outbreak in different districts of Bangladesh in between 8 March 2020 to 12 April 2020 and these findings were compared with those of other countries.\n\nConclusionsIn all, this is extremely important to promptly spread information to understand the risks of this pandemic and begin containment activities in the country.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Carson Ted Telford", - "author_inst": "Fulton County Board of Health" - }, - { - "author_name": "Udodirim Onwubiko", - "author_inst": "Fulton County Board of Health" - }, - { - "author_name": "David Holland", - "author_inst": "Fulton County Board of Health; Emory University Department of Medicine" - }, - { - "author_name": "Kim Turner", - "author_inst": "Fulton County Board of Health" - }, - { - "author_name": "Juliana Prieto", - "author_inst": "Fulton County Board of Health" - }, - { - "author_name": "Sasha Smith", - "author_inst": "Fulton County Board of Health" - }, - { - "author_name": "Jane Yoon", - "author_inst": "Emory University Department of Medicine" - }, - { - "author_name": "Wecheeta Brown", - "author_inst": "Fulton County Board of Health" - }, - { - "author_name": "Allison Chamberlain", - "author_inst": "Fulton County Board of Health; Emory University Rollins School of Public Health" - }, - { - "author_name": "Neel Gandhi", - "author_inst": "Emory University Department of Medicine; Emory University Rollins School of Public Health" - }, - { - "author_name": "Shamimul Khan", - "author_inst": "Fulton County Board of Health" + "author_name": "Samrat Kumar Dey", + "author_inst": "Dhaka International University (DIU)" }, { - "author_name": "Steve Williams", - "author_inst": "Fulton County Government" + "author_name": "Md. Mahbubur Rahman", + "author_inst": "Military Institute of Science and Technology (MIST)" }, { - "author_name": "Fazle Khan", - "author_inst": "Fulton County Board of Health" + "author_name": "Umme Raihan Siddiqi", + "author_inst": "Shaheed Suhrawardy Medical College (ShSMC)" }, { - "author_name": "Sarita Shah", - "author_inst": "Emory University Department of Medicine; Emory University Rollins School of Public Health" + "author_name": "Arpita Howlader", + "author_inst": "Patuakhali Science and Technology University (PSTU)" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1351610,33 +1351412,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.30.20143255", - "rel_title": "Handyfuge-LAMP: low-cost and electricity-free centrifugation forisothermal SARS-CoV-2 detection in saliva.", + "rel_doi": "10.1101/2020.06.29.20142562", + "rel_title": "Male gender and kidney illness associated with an increased risk of severe laboratory-confirmed coronavirus disease", "rel_date": "2020-07-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.30.20143255", - "rel_abs": "Point of care diagnostics for COVID-19 detection are vital to assess infection quickly and at the source so appropriate measures can be taken. The loop-mediated isothermal amplification (LAMP) assay has proven to be a reliable and simple protocol that can detect small amounts of viral RNA in patient samples (<10 genomes per L) (Nagamine, Hase, and Notomi 2002). Recently, Rabe and Cepko at Harvard published a sensitive and simple protocol for COVID-19 RNA detection in saliva using an optimized LAMP assay (Rabe and Cepko, 2020).\n\nThis LAMP protocol has the benefits of being simple, requiring no specialized equipment; rapid, requiring less than an hour from sample collection to readout; and cheap, costing around $1 per reaction using commercial reagents. The pH based colorimetric readout also leaves little ambiguity and is intuitive. However, a shortfall in many nucleic acid-based methods for detection in saliva samples has been the variability in output due to the presence of inhibitory substances in saliva. Centrifugation to separate the reaction inhibitors from inactivated sample was shown to be an effective way to ensure reliable LAMP amplification. However, a centrifuge capable of safely achieving the necessary speeds of 2000 RPM for several minutes often costs hundreds of dollars and requires a power supply.\n\nWe present here an open hardware solution- Handyfuge - that can be assembled with readily available components for the cost of <5 dollars a unit and could be used together with the LAMP assay for point of care detection of COVID-19 RNA from saliva. The device is then validated using the LAMP protocol from Rabe and Cepko. With the use of insulated coolers for reagent supply chain and delivery, the assay presented can be completed without the need for electricity or any laboratory scale infrastructure.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.29.20142562", + "rel_abs": "ObjectiveTo identify factors predicting severe coronavirus disease 2019 (COVID-19) in adolescent and adult patients with laboratory-positive (quantitative reverse-transcription polymerase chain reaction) infection.\n\nMethodsA retrospective cohort study took place, and data from 740 subjects, from all 32 states of Mexico, were analyzed. The association between the studied factors and severe (dyspnea requiring hospital admission) COVID-19 was evaluated through risk ratios (RRs) and 95% confidence intervals (CIs).\n\nResultsSevere illness was documented in 28% of participants. In multiple analysis, male gender (RR = 1.13, 95% CI 1.06 - 1.20), advanced age ([reference: 15 - 29 years old] 30 - 44, RR = 1.02, 95% CI 0.94 - 1.11; 45 - 59, RR = 1.26, 95% CI 1.15 - 1.38; 60 years or older, RR = 1.44, 95% CI 1.29 - 1.60), chronic kidney disease (RR = 1.31, 95% CI 1.04 - 1.64) and thoracic pain (RR = 1.16, 95% CI 1.10 - 1.24) were associated with an increased risk of severe disease.\n\nConclusionsTo the best of our knowledge, this is the first study evaluating predictors of COVID-19 severity in a large subset of the Latin-American population. It is also the first in documenting gender-related differences regarding the severity of the illness. These results may be useful for health care protocols for the early detection and management of COVID-19 patients that may benefit from opportune and specialized supportive medical treatment.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ethan Li", - "author_inst": "Stanford University" + "author_name": "Efren Murillo-Zamora", + "author_inst": "Instituto Mexicano del Seguro Social" }, { - "author_name": "Adam Larson", - "author_inst": "Stanford University" + "author_name": "Xochitl Trujillo", + "author_inst": "Universidad de Colima" }, { - "author_name": "Anestha Kothari", - "author_inst": "Stanford University" + "author_name": "Miguel Huerta", + "author_inst": "Universidad de Colima" }, { - "author_name": "Manu Prakash", - "author_inst": "Stanford University" + "author_name": "Monica Rios-Silva", + "author_inst": "Universidad de Colima" + }, + { + "author_name": "Oliver Mendoza-Cano", + "author_inst": "Universidad de Colima" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1353504,59 +1353310,95 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.06.30.172833", - "rel_title": "Development of RNA-based assay for rapid detection of SARS-CoV-2 in clinical samples", + "rel_doi": "10.1101/2020.06.30.177097", + "rel_title": "Conformational dynamics of SARS-CoV-2 trimeric spike glycoprotein in complex with receptor ACE2 revealed by cryo-EM", "rel_date": "2020-06-30", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.30.172833", - "rel_abs": "The ongoing spread of pandemic coronavirus disease (COVID-19) is caused by Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2). In the lack of specific drugs or vaccines for SARS-CoV-2, demands rapid diagnosis and management are crucial for controlling the outbreak in the community. Here we report the development of the first rapid-colorimetric assay capable of detecting SARS-CoV-2 in the human nasopharyngeal RNA sample in less than 30 minutes. We utilized a nanomaterial-based optical sensing platform to detect RNA-dependent RNA polymerase (RdRp) gene of SARS-CoV-2, where the formation of oligo probe-target hybrid led to salt-induced aggregation and changes in gold-colloid color from pink to blue in visible range. Accordingly, we found a change in colloid color from pink to blue in assay containing nasopharyngeal RNA sample from the subject with clinically diagnosed COVID-19. The colloid retained pink color when the test includes samples from COVID-19 negative subjects or human papillomavirus (HPV) infected women. The results were validated using nasopharangeal RNA samples from suspected COVID-19 subjects (n=136). Using RT-PCR as gold standard, the assay was found to have 85.29% sensitivity and 94.12% specificity. The optimized method has detection limit as little as 0.5 ng of SARS-CoV-2 RNA. Overall, the developed assay rapidly detects SARS-CoV-2 RNA in clinical samples in a cost-effective manner and would be useful in pandemic management by facilitating mass screening.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.30.177097", + "rel_abs": "The recent outbreaks of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its rapid international spread pose a global health emergency. The trimeric spike (S) glycoprotein interacts with its receptor human ACE2 to mediate viral entry into host-cells. Here we present cryo-EM structures of an uncharacterized tightly closed SARS-CoV-2 S-trimer and the ACE2-bound-S-trimer at 2.7-\u00c5 and 3.8-\u00c5-resolution, respectively. The tightly closed S-trimer with inactivated fusion peptide may represent the ground prefusion state. ACE2 binding to the up receptor-binding domain (RBD) within S-trimer triggers continuous swing-motions of ACE2-RBD, resulting in conformational dynamics of S1 subunits. Noteworthy, SARS-CoV-2 S-trimer appears much more sensitive to ACE2-receptor than SARS-CoV S-trimer in terms of receptor-triggered transformation from the closed prefusion state to the fusion-prone open state, potentially contributing to the superior infectivity of SARS-CoV-2. We defined the RBD T470-T478 loop and residue Y505 as viral determinants for specific recognition of SARS-CoV-2 RBD by ACE2, and provided structural basis of the spike D614G-mutation induced enhanced infectivity. Our findings offer a thorough picture on the mechanism of ACE2-induced conformational transitions of S-trimer from ground prefusion state towards postfusion state, thereby providing important information for development of vaccines and therapeutics aimed to block receptor binding.Competing Interest StatementThe authors have declared no competing interest.View Full Text", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Vinod Kumar", - "author_inst": "Sanjay Gandhi Post Graduate Institute of Medical Science (SGPGIMS), Lucknow, India" + "author_name": "Cong Xu", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" }, { - "author_name": "Suman Mishra", - "author_inst": "Sanjay Gandhi Post Graduate Institute of Medical Science (SGPGIMS), Lucknow, India" + "author_name": "Yanxing Wang", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" }, { - "author_name": "Rajni Sharma", - "author_inst": "Sanjay Gandhi Post Graduate Institute of Medical Science (SGPGIMS), Lucknow, India" + "author_name": "Caixuan Liu", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" }, { - "author_name": "Jyotsna Agarwal", - "author_inst": "Dr. Ram Manohar Lohia Institute of Medical Sciences, Lucknow, India" + "author_name": "Chao Zhang", + "author_inst": "CAS Key Laboratory of Molecular Virology & Immunology, Institute Pasteur of Shanghai, Chinese Academy of Sciences, University of Chinese Academy of Sciences" }, { - "author_name": "Ujjala Ghoshal", - "author_inst": "Sanjay Gandhi Post Graduate Institute of Medical Science (SGPGIMS), Lucknow, India" + "author_name": "Wenyu Han", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" }, { - "author_name": "Tripti Khanna", - "author_inst": "Indian Council of Medical Research, Ramalingaswami Bhawan, New Delhi, India" + "author_name": "Xiaoyu Hong", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" }, { - "author_name": "Lokendra K Sharma", - "author_inst": "Sanjay Gandhi Post Graduate Institute of Medical Science (SGPGIMS), Lucknow, India" + "author_name": "Yifan Wang", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" }, { - "author_name": "Santosh K Verma", - "author_inst": "Sanjay Gandhi Postgraduate Institute of Medical Sciences (SGPGIMS), Lucknow, India" + "author_name": "Qin Hong", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" }, { - "author_name": "Swasti Tiwari", - "author_inst": "Sanjay Gandhi Postgraduate Institute of Medical Sciences, Lucknow, India" + "author_name": "Shutian Wang", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" + }, + { + "author_name": "Qiaoyu Zhao", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" + }, + { + "author_name": "Yalei Wang", + "author_inst": "CAS Key Laboratory of Molecular Virology & Immunology, Institute Pasteur of Shanghai, Chinese Academy of Sciences, University of Chinese Academy of Sciences" + }, + { + "author_name": "Yong Yang", + "author_inst": "CAS Key Laboratory of Molecular Virology & Immunology, Institute Pasteur of Shanghai, Chinese Academy of Sciences, University of Chinese Academy of Sciences" + }, + { + "author_name": "Kaijian Chen", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" + }, + { + "author_name": "Wei Zheng", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" + }, + { + "author_name": "Liangliang Kong", + "author_inst": "The National Facility for Protein Science in Shanghai (NFPS)" }, { - "author_name": "Prabhakar Mishra", - "author_inst": "Department of Biostatistics and Health Informatics, Sanjay Gandhi PGIMS, Raibareli Road, Lucknow -226014, India" + "author_name": "Fangfang Wang", + "author_inst": "The National Facility for Protein Science in Shanghai (NFPS)" + }, + { + "author_name": "Qinyu Zuo", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" + }, + { + "author_name": "Zhong Huang", + "author_inst": "CAS Key Laboratory of Molecular Virology & Immunology, Institute Pasteur of Shanghai, Chinese Academy of Sciences, University of Chinese Academy of Sciences" + }, + { + "author_name": "Yao Cong", + "author_inst": "State Key Laboratory of Molecular Biology, National Center for Protein Science Shanghai, Shanghai Institute of Biochemistry and Cell Biology, Center for Excelle" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.06.30.175695", @@ -1355498,53 +1355340,53 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.24.20131185", - "rel_title": "Sentinel Coronavirus Environmental Monitoring Can Contribute to Detecting Asymptomatic SARS-CoV-2 Virus Spreaders and Can Verify Effectiveness of Workplace COVID-19 Controls", + "rel_doi": "10.1101/2020.06.22.20134957", + "rel_title": "Effects of Anticoagulants and Corticosteroids therapy in patients affected by severe COVID-19 Pneumonia", "rel_date": "2020-06-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20131185", - "rel_abs": "Detecting all workplace asymptomatic COVID-19 virus spreaders would require daily testing of employees, which is not practical. Over a two week period, nine workplace locations were chosen to test employees for SARS-CoV-2 infection (841 tests) and high-frequency-touch point environmental surfaces (5,500 tests) for Coronavirus using Eurofins COVID-19 Sentinel RT-PCR methods. Of the 9 locations, 3 had one or employees infected with SARS-CoV-2, neither of whom had symptoms at the time of testing nor developed symptoms. Locations with Coronavirus contaminated surfaces were 10 times more likely to have clinically positive employees than locations with no or very few positive surfaces. Break room chairs, workbenches, and door handles were the most frequently contaminated surfaces. Coronavirus RNA was detected at very low concentrations (RT-PCR 34 to 38 Cq). Environmental monitoring can be used to validate intervention strategies and be useful to verify the effectiveness of such strategies on a regular basis.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.22.20134957", + "rel_abs": "BackgroundIn the absence of a standard of treatment for COVID-19, the combined use of anti-inflammatory (corticosteroids and Enoxaparin) and antiviral drugs may be more effective than using either modality alone in the treatment of COVID-19.\n\nMethodsPatients hospitalized between April 10th, 2020, through May 10th, 2020, who had confirmed COVID-19 infection with clinical or radiographic evidence of pneumonia, in which 65 patients have moderate COVID-19 pneumonia, and 63 patients have severe COVID-19 pneumonia. All patients received early combination therapy of anti-inflammatory (corticosteroids and Enoxaparin) and antiviral drugs. They assessed for type and duration of treatment, and days need to wean from oxygen therapy, length of stay, virus clearance time, and complication or adverse events. All patients had more than 28 days follow up after discharge from the hospital.\n\nResultsModerate COVID-19 pneumonia group were 65 patients who received Enoxaparin, antiviral drugs, empirical antibiotics for pneumonia, and standard treatment for comorbidity. Male patients were 50 (76.9 %) and female patients were 15 (23.1 %). 34 (52.3 %) patients have comorbidity, 25 (38.5%) patients have Diabetes Mellitus and 2 (3.1 %) pregnant ladies. 19 (29.2 %) patients were on low flow oxygen therapy, 3L oxygen or less to maintain oxygen saturation more than 92%. All patients discharged home with no major or minor bleeding complications or significant complications. Severe COVID-19 pneumonia group were 63 patients who received methylprednisolone, enoxaparin, antiviral drugs, empirical antibiotics for pneumonia, and standard treatment for comorbidity. Male patients were 55 (87.3 %) and female patients were 8 (12.7 %). 37 (58.7 %) patients have comorbidity, and 24 (38.1%) patients have Diabetes Mellitus. 32 (50.8 %) patients were on low flow oxygen therapy, 4-9L oxygen, and 31 (49.2 %) patients were on low flow oxygen therapy, 10L oxygen or more, including 12 patients on a non-rebreathing mask. Patients received methylprednisolone were 37 (58.7 %) for 3 days, 16 (25.4 %) for 5 days and 10 (15.9 %) for more than 5 days. Sixty-two patients discharged home with one patient had a long stay, and the other two transferred to ICU. One long-stay patient transferred to ICU on low flow oxygen therapy.\n\nConclusionEarly use of a combined anti-inflammatory (corticosteroids and Enoxaparin) and antiviral drugs treatment in patients with moderate to severe COVID-19 pneumonia prevent complications of the disease and improve clinical outcomes", "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Douglas Marshall", - "author_inst": "Eurofins Microbiology Laboratories" + "author_name": "Khalid Mohammed Ghalilah", + "author_inst": "Al Madinah Al Munawarah Hospital" }, { - "author_name": "Frederic Bois", - "author_inst": "Eurofins Scientific" + "author_name": "Abdul Momin Sabir", + "author_inst": "Al Madinah Al Munawarah Hospital" }, { - "author_name": "Soren K.S. Jensen", - "author_inst": "Eurofins Steins Laboratorium" + "author_name": "Irshad Ali Alvi", + "author_inst": "Al Madinah Al Munawarah Hospital" }, { - "author_name": "Svend A. Linde", - "author_inst": "Eurofins Steins Laboratorium" + "author_name": "Malak Alharbi", + "author_inst": "Al Madinah Al Munawarah Hospital" }, { - "author_name": "Richard Higby", - "author_inst": "Eurofins Microbiology Laboratories" + "author_name": "Abdulrahman Basabrain", + "author_inst": "Al Madinah Al Munawarah Hospital" }, { - "author_name": "Yvoine Remy-McCort", - "author_inst": "Eurofins Scientific" + "author_name": "Mahmooud Aljundi", + "author_inst": "Al Madinah Al Munawarah Hospital" }, { - "author_name": "Sean Murray", - "author_inst": "Eurofins Microbiology Laboratories" + "author_name": "Ghazi Almohammadi", + "author_inst": "Al Madinah Al Munawarah Hospital" }, { - "author_name": "Bryan Dieckelman", - "author_inst": "Eurofins Microbiology Laboratories" + "author_name": "Zainab Almuairfi", + "author_inst": "Al Madinah Al Munawarah Hospital" }, { - "author_name": "Fitri Sudradjat", - "author_inst": "Eurofins Central Analytical Laboratories" + "author_name": "Raed Alharbi", + "author_inst": "Al Madinah Al Munawarah Hospital" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1357288,41 +1357130,97 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.27.20141739", - "rel_title": "Aligning SARS-CoV-2 Indicators via an Epidemic Model: Application to Hospital Admissions and RNA Detection in Sewage Sludge", + "rel_doi": "10.1101/2020.06.28.20141556", + "rel_title": "Monocyte CD169 expression as a biomarker in the early diagnosis of COVID-19", "rel_date": "2020-06-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.27.20141739", - "rel_abs": "Ascertaining the state of coronavirus outbreaks is crucial for public health decision-making. Absent repeated representative viral test samples in the population, public health officials and researchers alike have relied on lagging indicators of infection to make inferences about the direction of the outbreak and attendant policy decisions. Recently researchers have shown that SARS-CoV-2 RNA can be detected in municipal sewage sludge with measured RNA concentrations rising and falling suggestively in the shape of an epidemic curve while providing an earlier signal of infection than hospital admissions data. The present paper presents a SARS-CoV-2 epidemic model to serve as a basis for estimating the incidence of infection, and shows mathematically how modeled transmission dynamics translate into infection indicators by incorporating probability distributions for indicator-specific time lags from infection. Hospital admissions and SARS-CoV-2 RNA in municipal sewage sludge are simultaneously modeled via maximum likelihood scaling to the underlying transmission model. The results demonstrate that both data series plausibly follow from the transmission model specified, provide a direct estimate of the reproductive number R0 = 2.38, and suggest that the detection of viral RNA in sewage sludge leads hospital admissions by 4.6 days on average.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.28.20141556", + "rel_abs": "We assessed the expression of the cell adhesion molecule Sialoadhesin (CD169), a type I interferon-inducible receptor, on monocytes (mCD169) in 53 adult patients admitted to the hospital during the COVID-19 outbreak for a suspicion of SARS-CoV-2 infection. mCD169 was strongly overexpressed in 30 out of 32 (93.7%) confirmed COVID-19 cases, compared to three out of 21 (14.3%) patients for whom the diagnosis of COVID-19 was finally ruled out. mCD169 was associated with the plasma interferon alpha level and thrombocytopenia. mCD169 testing may be helpful for the rapid triage of suspected COVID-19 patients during an outbreak.", + "rel_num_authors": 20, "rel_authors": [ { - "author_name": "Edward H Kaplan", - "author_inst": "Yale University" + "author_name": "Anne-Sophie Bedin", + "author_inst": "Montpellier University" }, { - "author_name": "Dennis Wang", - "author_inst": "Yale University" + "author_name": "Alain Makinson", + "author_inst": "Montpellier University" }, { - "author_name": "Mike Wang", - "author_inst": "Yale University" + "author_name": "Marie-Christine Picot", + "author_inst": "Montpellier University Hospital" }, { - "author_name": "Amyn A Malik", - "author_inst": "Yale University" + "author_name": "Franck Mennechet", + "author_inst": "Montpellier University" }, { - "author_name": "Alessandro Zulli", - "author_inst": "Yale University" + "author_name": "Fabrice Malergue", + "author_inst": "Immunotech Beckman Coulter" }, { - "author_name": "Jordan H Peccia", - "author_inst": "Yale University" + "author_name": "Amandine Pisoni", + "author_inst": "Montpellier University Hospital" + }, + { + "author_name": "Esperance Nyiramigisha", + "author_inst": "Montpellier University Hospital" + }, + { + "author_name": "Lise Montagnier", + "author_inst": "Montpellier University Hospital" + }, + { + "author_name": "Karine Bollore", + "author_inst": "Montpellier University" + }, + { + "author_name": "Segolene Debiesse", + "author_inst": "INSERM" + }, + { + "author_name": "David Morquin", + "author_inst": "Montpellier University Hospital" + }, + { + "author_name": "Penelope Bourgoin", + "author_inst": "Immunotech Beckman Coulter" + }, + { + "author_name": "Nicolas Veyrenche", + "author_inst": "Montpellier University Hospital" + }, + { + "author_name": "Constance Renault", + "author_inst": "Montpellier University" + }, + { + "author_name": "Vincent Foulongne", + "author_inst": "Montpellier University" + }, + { + "author_name": "Bret Caroline", + "author_inst": "Montpellier University" + }, + { + "author_name": "Bourdin Arnaud", + "author_inst": "Montpellier University" + }, + { + "author_name": "Vincent Le Moing", + "author_inst": "Montpellier University" + }, + { + "author_name": "Philippe Van de Perre", + "author_inst": "Montpellier University" + }, + { + "author_name": "Edouard TUAILLON", + "author_inst": "Montpellier University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1358614,31 +1358512,103 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2020.06.29.177030", - "rel_title": "A mobile genetic element in the SARS-CoV-2 genome is shared with multiple insect species", + "rel_doi": "10.1101/2020.06.29.171173", + "rel_title": "An in vitro assessment of anti-SARS-CoV-2 activity of oral preparations of iodine complexes (RENESSANS)", "rel_date": "2020-06-29", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.29.177030", - "rel_abs": "Unprecedented quantities of sequence data have been generated from the newly emergent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causative agent of COVID-19. We document here the presence of s2m, a highly conserved, mobile genetic element with unknown function, in both the SARS-CoV-2 genome and a large number of insect genomes. Although s2m is not universally present among coronaviruses and appears to undergo horizontal transfer, the high sequence conservation and universal presence of s2m among isolates of SARS-CoV-2 indicate that, when present, the element is essential for viral function.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.29.171173", + "rel_abs": "Since the emergence of CoVID-19 pandemic in China in late 2019, scientists are striving hard to explore non-toxic, viable anti-SARS-CoV-2 compounds or medicines. We determined In Vitro anti-SARS-CoV-2 activity of oral formulations (syrup and capsule) of an Iodine-complex (Renessans). A monolayer of vero cells were exposed to SARS-CoV-2 in the presence and absence of different concentrations (equivalent to 50, 05 and 0.5 g/ml of I2) of Renessans. Anti-SARS-CoV-2 activity of each of the formulation was assessed in the form of cell survival, SARS-CoV-2-specific cytopathic effect (CPE) and genome quantization. With varying concentrations of syrup and capsule, a varying rate of inhibition of CPE, cells survival and virus replication was observed. Compared to 0.5 g/ml concentration of Renessans syrup, 5 and 50 g/ml showed comparable results where there was a 100% cell survival, no CPEs and a negligible viral replication ({Delta}CT= 0.11 and 0.13, respectively). This study indicates that Renessans, containing iodine, may have potential activity against SARS-CoV-2 which needs to be further investigated in human clinical trials.", + "rel_num_authors": 21, "rel_authors": [ { - "author_name": "Torstein Tengs", - "author_inst": "The Norwegian Institute of Public Health" + "author_name": "Imran Altaf", + "author_inst": "Quality Operation Laboratory, University of Veterinary and Animal Sciences, Lahore" }, { - "author_name": "Charles F Delwiche", - "author_inst": "University of Maryland, College Park" + "author_name": "Muhammad Faisal Nadeem", + "author_inst": "Institute of Pharmaceutical Sciences, University of Veterinary and Animal Sciences, Lahore" }, { - "author_name": "Christine M Jonassen", - "author_inst": "Ostfold Hospital Trust" + "author_name": "Nadir Hussain", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Muhammad Nawaz", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Sohail Raza", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Muhammad Asad Ali", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Sohail Hasan", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Nazish Matti", + "author_inst": "Department of Pharmacology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Muhammad Ashraf", + "author_inst": "Department of Pharmacology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Ihsan Ullah", + "author_inst": "Institute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Waqar Aziz", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Sehar Fazal", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Saira Rafique", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Muhammad Adnan", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Nageen Sardar", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Tahir Khan", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore" + }, + { + "author_name": "Muhammad Moavia", + "author_inst": "Department of Microbiology, University of Veterinary and Animal Sciences, Lahore;" + }, + { + "author_name": "Sohaib Ashraf", + "author_inst": "Department of Cardiology, Sheikh Zaid Hospital Lahore" + }, + { + "author_name": "Zarfishan Tahir", + "author_inst": "Institute of Public Health, Lahore" + }, + { + "author_name": "Nadia Mukhtar", + "author_inst": "Institute of Public Health, Lahore" + }, + { + "author_name": "Tahir Yaqub", + "author_inst": "University of Veterinary and Animal Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "genetics" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.06.29.178293", @@ -1360160,37 +1360130,29 @@ "category": "addiction medicine" }, { - "rel_doi": "10.1101/2020.06.26.20138545", - "rel_title": "Prevalence of SARS-CoV-2 among workers returning to Bihar gives snapshot of COVID across India", + "rel_doi": "10.1101/2020.06.26.20140814", + "rel_title": "Predicting the Trajectory of Any COVID19 Epidemic From the Best Straight Line", "rel_date": "2020-06-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20138545", - "rel_abs": "India has reported the fourth highest number of confirmed SARS-CoV-2 cases worldwide. Because there is little community testing for COVID, this case count is likely an underestimate. When India partially exited from lockdown on May 4, 2020, millions of daily laborers left cities for their rural family homes. RNA testing on a near-random sample of laborers returning to the state of Bihar is used to estimate positive testing rate for COVID across India for a 6-week period immediately following the initial lifting of Indias lockdown. Positive testing rates among returning laborers are only moderately correlated with, and 21% higher than, Indian states official reports, which are not based on random sampling. Higher prevalence among returning laborers may also reflect greater COVID spread in crowded poor communities such as slums.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.26.20140814", + "rel_abs": "A pipeline involving data acquisition, curation, carefully chosen graphs and mathematical models, allows analysis of COVID-19 outbreaks at 3,546 locations world-wide (all countries plus smaller administrative divisions with data available). Comparison of locations with over 50 deaths shows all outbreaks have a common feature: H(t) defined as loge(X(t)/X(t-1)) decreases linearly on a log scale, where X(t) is the total number of Cases or Deaths on day, t (we use ln for loge). The downward slopes vary by about a factor of three with time constants (1/slope) of between 1 and 3 weeks; this suggests it may be possible to predict when an outbreak will end. Is it possible to go beyond this and perform early prediction of the outcome in terms of the eventual plateau number of total confirmed cases or deaths?\n\nWe test this hypothesis by showing that the trajectory of cases or deaths in any outbreak can be converted into a straight line. Specifically Y(t) {equiv} -ln(ln(N / X (t)), is a straight line for the correct plateau value N, which is determined by a new method, Best-Line Fitting (BLF). BLF involves a straight-line facilitation extrapolation needed for prediction; it is blindingly fast and amenable to optimization. We find that in some locations that entire trajectory can be predicted early, whereas others take longer to follow this simple functional form. Fortunately, BLF distinguishes predictions that are likely to be correct in that they show a stable plateau of total cases or death (N value). We apply BLF to locations that seem close to a stable predicted N value and then forecast the outcome at some locations that are still growing wildly. Our accompanying web-site will be updated frequently and provide all graphs and data described here.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Anup Malani", - "author_inst": "University of Chicago" - }, - { - "author_name": "Manoj Mohanan", - "author_inst": "Duke University" - }, - { - "author_name": "Chanchal Kumar", - "author_inst": "Government of Bihar" + "author_name": "Michael Levitt", + "author_inst": "Stanford School of Medicine" }, { - "author_name": "Jake Kramer", - "author_inst": "University of Chicago" + "author_name": "Andrea Scaiewicz", + "author_inst": "Stanford School of Medicine" }, { - "author_name": "Vaidehi Tandel", - "author_inst": "IDFC Institute" + "author_name": "Francesco Zonta", + "author_inst": "ShanghaiTech University, Shanghai, China" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1361646,31 +1361608,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.24.20139238", - "rel_title": "A Multi-Task Pipeline with Specialized Streams forClassification and Segmentation of InfectionManifestations in COVID-19 Scans", + "rel_doi": "10.1101/2020.06.24.20139410", + "rel_title": "Determination of Robust Regional CT Radiomics Features for COVID-19", "rel_date": "2020-06-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139238", - "rel_abs": "We are concerned with the challenge of coronavirus disease (COVID-19) detection in chest X-ray and Computed Tomography (CT) scans, and the classification and segmentation of related infection manifestations. Even though it is arguably not an established diagnostic tool, using machine learning-based analysis of COVID-19 medical scans has shown the potential to provide a preliminary digital second opinion. This can help in managing the current pandemic, and thus has been attracting significant research attention. In this research, we propose a multi-task pipeline that takes advantage of the growing advances in deep neural network models. In the first stage, we fine-tuned an Inception-v3 deep model for COVID-19 recognition using multi-modal learning, i.e., using X-ray and CT scans. In addition to outperforming other deep models on the same task in the recent literature, with an attained accuracy of 99.4%, we also present comparative analysis for multi-modal learning against learning from X-ray scans alone. The second and the third stages of the proposed pipeline complement one another in dealing with different types of infection manifestations. The former features a convolutional neural network architecture for recognizing three types of manifestations, while the latter transfers learning from another knowledge domain, namely, pulmonary nodule segmentation in CT scans, to produce binary masks for segmenting the regions corresponding to these manifestations. Our proposed pipeline also features specialized streams in which multiple deep models are trained separately to segment specific types of infection manifestations, and we show the significant impact that this framework has on various performance metrics. We evaluate the proposed models on widely adopted datasets, and we demonstrate an increase of approximately 4% and 7% for dice coefficient and mean intersection-over-union (mIoU), respectively, while achieving 60% reduction in computational time, compared to the recent literature.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.24.20139410", + "rel_abs": "BackgroundThe lung CT images of COVID-19 patients can be characterized by three different regions - Ground Glass Opacity (GGO), consolidation and pleural effusion. GCOs have been shown to precede consolidations. Quantitative characterization of these regions using radiomics can facilitate accurate diagnosis, disease progression and response to treatment. However, according to the knowledge of the author, regional CT radiomics analysis of COVID-19 patients has not been carried out. This study aims to address these by determining the radiomics features that can characterize each of the regions separately and can distinguish the regions from each other.\n\nMethods44 radiomics features were generated with four quantization levels for 23 CT slice of 17 patients. Two approaches were the implemented to determine the features that can differentiate between lung regions - 1) Z-score and correlation heatmaps and 2) one way ANOVA for finding statistically significantly difference (p<0.05) between the regions. Radiomics features that show agreement for all cases (Z-score, correlation and statistical significant test) were selected as suitable features. The features were then tested on 52 CT images.\n\nResults10 radiomics features were found to be the most suitable among 44 features. When applied on the test images, they can differentiate between GCO, consolidation and pleural effusion successfully and the difference provided by these 10 features between three lung regions are statistically significant.\n\nConclusionThe ten robust radiomics features can be useful in extracting quantitative data from CT lung images to characterize the disease in the patient, which in turn can help in more accurate diagnosis, staging the severity of the disease and allow the clinician to plan for more successful personalized treatment for COVID-19 patients. They can also be used for monitoring the progression of COVID-19 and response to therapy for clinical trials.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Shimaa El-bana", - "author_inst": "Alexandria Higher Institute of Engineering and Technology" - }, - { - "author_name": "Ahmad Al-Kabbany", - "author_inst": "Department of Electronics and Communications Engineering, Arab Academy for Science, Technology, and Maritime Transport, Alexandria, Egypt" - }, - { - "author_name": "Maha Sharkas", - "author_inst": "Department of Electronics and Communications Engineering, Arab Academy for Science, Technology, and Maritime Transport, Alexandria, Egypt" + "author_name": "Mahbubunnabi Tamal", + "author_inst": "Imam Abdulrahman Bin Faisal University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "radiology and imaging" }, { "rel_doi": "10.1101/2020.06.24.20139469", @@ -1363236,63 +1363190,83 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.06.26.173872", - "rel_title": "Tipiracil binds to uridine site and inhibits Nsp15 endoribonuclease NendoU from SARS-CoV-2", + "rel_doi": "10.1101/2020.06.25.172403", + "rel_title": "Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor", "rel_date": "2020-06-26", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.26.173872", - "rel_abs": "ABSTRACTSARS-CoV-2 Nsp15 is a uridylate-specific endoribonuclease with C-terminal catalytic domain belonging to the EndoU family. It degrades the polyuridine extensions in (-) sense strand of viral RNA and some non-translated RNA on (+) sense strand. This activity seems to be responsible for the interference with the innate immune response and evasion of host pattern recognition. Nsp15 is highly conserved in coronaviruses suggesting that its activity is important for virus replication. Here we report first structures with bound nucleotides and show that SARS-CoV-2 Nsp15 specifically recognizes U in a pattern previously predicted for EndoU. In the presence of manganese ions, the enzyme cleaves unpaired RNAs. Inhibitors of Nsp15 have been reported but not actively pursued into therapeutics. The current COVID-19 pandemic brought to attention the repurposing of existing drugs and the rapid identification of new antiviral compounds. Tipiracil is an FDA approved drug that is used with trifluridine in the treatment of colorectal cancer. Here, we combine crystallography, biochemical and whole cell assays, and show that this compound inhibits SARS-CoV-2 Nsp15 and interacts with the uridine binding pocket of the enzyme\u2019s active site, providing basis for the uracil scaffold-based drug development.Competing Interest StatementThe authors have declared no competing interest.View Full Text", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.25.172403", + "rel_abs": "The current COVID-19 pandemic is caused by the SARS-CoV-2 betacoronavirus, which utilizes its highly glycosylated trimeric Spike protein to bind to the cell surface receptor ACE2 glycoprotein and facilitate host cell entry. We utilized glycomics-informed glycoproteomics to characterize site-specific microheterogeneity of glycosylation for a recombinant trimer Spike mimetic immunogen and for a soluble version of human ACE2. We combined this information with bioinformatic analyses of natural variants and with existing 3D-structures of both glycoproteins to generate molecular dynamics simulations of each glycoprotein alone and interacting with one another. Our results highlight roles for glycans in sterically masking polypeptide epitopes and directly modulating Spike-ACE2 interactions. Furthermore, our results illustrate the impact of viral evolution and divergence on Spike glycosylation, as well as the influence of natural variants on ACE2 receptor glycosylation that, taken together, can facilitate immunogen design to achieve antibody neutralization and inform therapeutic strategies to inhibit viral infection.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Youngchang Kim", - "author_inst": "Argonne National Laboratory/University of Chicago" + "author_name": "Peng Zhao", + "author_inst": "Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, Georgia, 306" }, { - "author_name": "Jacek Wower", - "author_inst": "Auburn University" + "author_name": "Jeremy L Praissman", + "author_inst": "Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, Georgia, 306" }, { - "author_name": "Natalia Maltseva", - "author_inst": "Argonne National Laboratory/University of Chicago" + "author_name": "Oliver C Grant", + "author_inst": "Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, Georgia, 306" }, { - "author_name": "Changsoo Chang", - "author_inst": "Argonne National Laboratory/University of Chicago" + "author_name": "Yongfei Cai", + "author_inst": "Division of Molecular Medicine, Childrens Hospital and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, 02115, USA" }, { - "author_name": "Robert Jedrzejczak", - "author_inst": "Argonne National Laboratory/University of Chicago" + "author_name": "Tianshu Xiao", + "author_inst": "Division of Molecular Medicine, Childrens Hospital and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, 02115, USA" }, { - "author_name": "Mateusz Wilamowski", - "author_inst": "Argonne National Laboratory/University of Chicago" + "author_name": "Katelyn E Rosenbalm", + "author_inst": "Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, Georgia, 306" }, { - "author_name": "Soowon Kang", - "author_inst": "University of Chicago" + "author_name": "Kazuhiro Aoki", + "author_inst": "Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, Georgia, 306" }, { - "author_name": "Vlad Nicolaescu", - "author_inst": "University of Chicago" + "author_name": "Benjamin P Kellman", + "author_inst": "Departments of Pediatrics and Bioengineering, University of California, San Diego, La Jolla, California, 92093, USA" }, { - "author_name": "Glenn Randall", - "author_inst": "University of Chicago" + "author_name": "Robert Bridger", + "author_inst": "Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, Georgia, 306" }, { - "author_name": "Karolina Michalska", - "author_inst": "Argonne National Laboratory/University of Chicago" + "author_name": "Dan H Barouch", + "author_inst": "Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, 02215, USA" }, { - "author_name": "Andrzej Joachimiak", - "author_inst": "Argonne National Laboratory/University of Chicago" + "author_name": "Melinda A Brindley", + "author_inst": "Department of Infectious Diseases, Department of Population Health, Center for Vaccines and Immunology, College of Veterinary Medicine, University of Georgia, A" + }, + { + "author_name": "Nathan E Lewis", + "author_inst": "Departments of Pediatrics and Bioengineering, University of California, San Diego, La Jolla, California, 92093, USA, Novo Nordisk Foundation Center for Biosusta" + }, + { + "author_name": "Michael Tiemeyer", + "author_inst": "Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, Georgia, 306" + }, + { + "author_name": "Bing Chen", + "author_inst": "Division of Molecular Medicine, Childrens Hospital and Department of Pediatrics, Harvard Medical School, Boston, Massachusetts, 02115, USA" + }, + { + "author_name": "Robert J Woods", + "author_inst": "Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, Georgia, 306" + }, + { + "author_name": "Lance Wells", + "author_inst": "Complex Carbohydrate Research Center, Department of Biochemistry and Molecular Biology, and Department of Chemistry, University of Georgia, Athens, Georgia, 306" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "molecular biology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.06.25.20140061", @@ -1364502,39 +1364476,27 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.06.25.170936", - "rel_title": "Cellular exocytosis gene (EXOC6/6B): a potential molecular link for the susceptibility and mortality of COVID-19 in diabetic patients", + "rel_doi": "10.1101/2020.06.23.167072", + "rel_title": "Molecular features similarities between SARS-CoV-2, SARS, MERS and key human genes could favour the viral infections and trigger collateral effects", "rel_date": "2020-06-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.25.170936", - "rel_abs": "Diabetes is one of the most critical comorbidities linked to an increased risk of severe complications in the current coronavirus disease 2019 (COVID-19) pandemic. A better molecular understanding of COVID-19 in people with type diabetes mellitus (T2D) is mandatory, especially in countries with a high rate of T2D, such as the United Arab Emirates (UAE). Identification of the cellular and molecular mechanisms that make T2D patients prone to aggressive course of the disease can help in the discovery of novel biomarkers and therapeutic targets to improve our response to the disease pandemic. Herein, we employed a system genetics approach to explore potential genomic, transcriptomic alterations in genes specific to lung and pancreas tissues, affected by SARS-CoV-2 infection, and study their association with susceptibility to T2D in Emirati patients. Our results identified the Exocyst complex component, 6 (EXOC6/6B) gene (a component for docks insulin granules to the plasma membrane) with documented INDEL in 3 of 4 whole genome sequenced Emirati diabetic patients. Publically available transcriptomic data showed that lung infected with SARS-CoV-2 showed significantly lower expression of EXOC6/6B compared to healthy lungs.\n\nIn conclusion, our data suggest that EXOC6/6B might be an important molecular link between dysfunctional pancreatic islets and ciliated lung epithelium that makes diabetic patients more susceptible to severe SARS-COV-2 complication.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.23.167072", + "rel_abs": "In December 2019 rising pneumonia cases caused by a novel {beta}-coronavirus (SARS-CoV-2) occurred in Wuhan, China, which has rapidly spread worldwide causing thousands of deaths. The WHO declared the SARS-CoV-2 outbreak as a public health emergency of international concern therefore several scientists are dedicated to the study of the new virus. Since human viruses have codon usage biases that match highly expressed proteins in the tissues they infect and depend on host cell machinery for replication and co-evolution, we selected the genes that are highly expressed in the tissue of human lungs to perform computational studies that permit to compare their molecular features with SARS, SARS-CoV-2 and MERS genes. In our studies, we analysed 91 molecular features for 339 viral genes and 463 human genes that consisted of 677873 codon positions. Hereby, we found that A/T bias in viral genes could propitiate the viral infection favoured by a host dependant specialization using the host cell machinery of only some genes. The envelope protein E, the membrane glycoprotein M and ORF7 could have been further benefited by a high rate of A/T in the third codon position. Thereby, the mistranslation or de-regulation of protein synthesis could produce collateral effects, as a consequence of viral occupancy of the host translation machinery due tomolecular similarities with viral genes. Furthermore, we provided a list of candidate human genes whose molecular features match those of SARS-CoV-2, SARSand MERS genes, which should be considered to be incorporated into genetic population studies to evaluate thesusceptibility to respiratory viral infections caused by these viruses. The results presented here, settle the basis for further research in the field of human genetics associated with the new viral infection, COVID-19, caused by SARS-CoV-2 and for the development of antiviral preventive methods.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Jalal Taneera", - "author_inst": "University of Sharjah" - }, - { - "author_name": "Mahmood Yaseen Hachim", - "author_inst": "Mohammed bin Rashid University of Medicine and Health Sciences" - }, - { - "author_name": "Ibrahim Yaseen Hachim", - "author_inst": "University of Sharjah" + "author_name": "Lucas Maldonado Sr.", + "author_inst": "Instituto de Investigaciones en Microbiologia y Parasitologia Medica IMPAM-UBA-CONICET" }, { - "author_name": "Saba Al Heialy", - "author_inst": "Mohammed bin Rashid University of Medicine and Health Sciences" - }, - { - "author_name": "Nabil Sulaiman", - "author_inst": "University of Sharjah" + "author_name": "Laura Kamenetzky", + "author_inst": "Instituto de Investigaciones en Microbiologia y Parasitologia Medica IMPAM-UBA-CONICET" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "genomics" }, { "rel_doi": "10.1101/2020.06.25.171744", @@ -1366231,55 +1366193,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.23.20137471", - "rel_title": "Initial experience with short-course corticosteroids in a small cohort of adults with severe COVID-19 in a tertiary care hospital in India", + "rel_doi": "10.1101/2020.06.23.20138743", + "rel_title": "Only a combination of social distancing and massive testing can effectively stop COVID-19 progression in densely populated urban areas", "rel_date": "2020-06-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.23.20137471", - "rel_abs": "Severe COVID 19 disease is associated with high morbidity and mortality with limited therapeutic options. The role of glucocorticoids in treatment of COVID 19 has been riddled with controversy. The study site has been using glucocorticoids in patients with severe COVID 19 since the first few patients of COVID 19 that were admitted. In the initial cohort of 7 patients with severe COVID disease, use of methylprednisolone in a dose of 30 mg twice daily was associated with rapid improvement in oxygenation and decline in CRP levels. While six patients made a complete clinical recovery, one patient died. There were no secondary infections.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.23.20138743", + "rel_abs": "We present a simple epidemiological model that includes demographic density, social distancing, and efficacy of massive testing and quarantine as the main parameters to model the progression of COVID-19 pandemics in densely populated urban areas (i.e., above 5,000 inhabitants km2). Our model demonstrates that effective containment of pandemic progression in densely populated cities is achieved only by combining social distancing and widespread testing for quarantining of infected subjects. Our results suggest that extreme social distancing without intensive testing is ineffective in extinguishing COVID-19. This finding has profound epidemiological significance and sheds light on the controversy regarding the relative effectiveness of widespread testing and social distancing. Our simple epidemiological simulator is also useful for assessing the efficacy of governmental/societal responses to an outbreak.\n\nThis study also has relevant implications for the concept of smart cities, as densely populated areas are hotspots that are highly vulnerable to epidemic crises.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Sanjiv Jha", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" - }, - { - "author_name": "Kiran Shetty", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" - }, - { - "author_name": "Sonali Vadi", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" - }, - { - "author_name": "Sourabh Phadtare", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" - }, - { - "author_name": "Vatsal Kothari", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" - }, - { - "author_name": "Abhijit Raut", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" - }, - { - "author_name": "Sweta Shah", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" - }, - { - "author_name": "Pallavi Bhargava", - "author_inst": "Henry Ford Hospital System" + "author_name": "Mario Moises Alvarez", + "author_inst": "Tecnologico de Monterrey" }, { - "author_name": "Tanu Singhal", - "author_inst": "Kokilaben Dhirubhai Ambani Hospital and Medical Research Institute" + "author_name": "Grissel Trujillo-de Santiago", + "author_inst": "Tecnologico de Monterrey" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.06.23.20138677", @@ -1367616,29 +1367550,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.21.20136341", - "rel_title": "Analysis and Prediction of the COVID-19 outbreak in Pakistan", + "rel_doi": "10.1101/2020.06.21.20136606", + "rel_title": "Extension and implementation of a system modelling the COVID-19 pandemic in Chile", "rel_date": "2020-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.21.20136341", - "rel_abs": "In this study we estimate the severity of the COVID-19 outbreak in Pakistan prior to and after lock down restrictions were eased. We also project the epidemic curve considering realistic quarantine, social distancing and possible medication scenarios. We use a deterministic epidemic model that includes asymptomatic, quarantined, isolated and medicated population compartments for our analysis. We calculate the basic reproduction number [R]0 for the pre and post lock down periods, noting that during this time no medication was available.1 The pre-lock down value of [R]0 is estimated to be 1.07 and the post lock down value is estimated to be 1.86. We use this analysis to project the epidemic curve for a variety of lock down, social distancing and medication scenarios. We note that if no substantial efforts are made to contain the epidemic, it will peak in mid of September, with the maximum projected active cases being close to 700,000. In a realistic, best case scenario, we project that the epidemic peaks in early to mid July with the maximum active cases being around 120000.We note that social distancing measures and medication if available will help flatten the curve, however without the reintroduction of further lock down it would be very difficult to bring [R]0 below 1. Our study strongly supports the recent WHO recommendation of reintroducing lock downs to control the epidemic.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.21.20136606", + "rel_abs": "We modelling the dynamics of the COVID-19 epidemic taking into account the role of the unreported cases. In a first section we extend the model recently introduced/ implemented by Liu, Magal, Seydi and Webb, by considering different transmission rates for the infectious and unreported states, and we couple three new states related to hospitalized and fatalities. In addition, we introduce an operator that incorporates the effects of mitigation measures at the different rates considered in the system. Finally, we implemented the extended model in the Chilean context by considering variable the transmission rates and the fraction of unreported cases, the latter through an argument that uses mortality rates. We conclude with several conclusions and lines of future research.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Mohsin Ali", - "author_inst": "Lahore University of Management Sciences Lahore" - }, - { - "author_name": "Mudassar Imran", - "author_inst": "Gulf University for Science & Technology, Mishref, Kuwait;" + "author_name": "Gaston Vergara-Hermosilla", + "author_inst": "Universite de Bordeaux" }, { - "author_name": "Adnan Khan", - "author_inst": "Lahore University of Management Sciences Lahore;" + "author_name": "Andres Navas", + "author_inst": "Universidad de Santiago" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1368882,55 +1368812,87 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2020.06.23.20138032", - "rel_title": "Factors Associated with Mental Health Outcomes in Oman during COVID19: Frontline vs Non-frontline Healthcare Workers", + "rel_doi": "10.1101/2020.06.22.20137406", + "rel_title": "Current infection control behaviour patterns in the UK, and how they can be improved by 'Germ Defence', an online behavioural intervention to reduce the spread of COVID-19 in the home.", "rel_date": "2020-06-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.23.20138032", - "rel_abs": "OBJECTIVEThis study aims to assess and compare demographic and psychological factors and sleep status of frontline HCWs in relation to non-frontline HCWs\n\nDESIGN, SETTINGS, AND PARTICIPANTSThis cross-sectional study was conducted using an online survey from the 8th to the 17th of April 2020 across varied health care settings in Oman accruing 1139 HCWS.\n\nMAIN OUTCOMES AND MEASURESMental health status was assessed using Depression, Anxiety, and Stress Scales (DASS-21), and insomnia was evaluated by the Insomnia Severity Index (ISI). Samples were categorized into the frontline and non-frontline groups. Chi-square, odds ratio, and independent t-tests were used to compare groups by demographic and mental health outcomes.\n\nResultsThis study included 1139 HCWs working in Oman. There was a total of 368 (32.3%), 388 (34.1%), 271 (23.8%), and 211 (18.5%) respondents reported to have depression, anxiety, stress, and insomnia, respectively while working during the pandemic period. HCWs in the frontline group were 1.4 times more likely to have anxiety (OR=1.401, p=0.007) and stress (OR=1.404, p=0.015) as compared to those working in the non-frontline group. On indices of sleep-wake cycles, HCWs in the frontline group were 1.37 times more likely to report insomnia (OR=1.377, p=0.037) when compared to those working in the non-frontline group. No significant differences in depression status between workers in the frontline and non-frontline groups were found (p=0.181).\n\nCONCLUSIONS AND RELEVANCETo our knowledge, this is the first study to explore the differential impacts of the COVID-19 pandemic on different grades of HCWs. This study suggests that frontline HCWs are disproportionally affected compared to non-frontline HCWs. The problem with managing sleep-wake cycles and anxiety symptoms were highly endorsed among frontline HCWs. As psychosocial interventions are likely to be constrained owing to the pandemic, mental health care must first be directed to frontline HCWs.\n\nO_TEXTBOXArticle Summary\n\nMethods\n\nO_LIThe study accrued 1139 participants of which 574 were working as frontline HCWs (565 non-frontline workers) serving patients with COVID-19 in different categories of healthcare settings in Oman.\nC_LIO_LIThe following tools used were used alongside the collection of demographic information: The depression, Anxiety and Stress Scale (DASS-21) and Insomnia Severity Index.\nC_LIO_LIStrengths: This nationally representative study is the first of its kind to investigate the differences in magnitude and the covariates of stress and distress between frontline and non-frontline healthcare workers in Oman.\nC_LIO_LILimitations: The use of an online survey and the use of symptom checklists (DASS, ISI) which are typically no match for the gold-standard interviews.\nC_LIO_LIIt is also not clear whether the observed mental health outcomes constitute adjustment disorders/ acute stress reaction or present a chronic-type and thus irreversible psychological distress.\nC_LI\n\nC_TEXTBOX", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.22.20137406", + "rel_abs": "BackgroundGerm Defence (https://germdefence.org/) is a freely available website providing behavioural advice for infection control within households, using behaviour change techniques. This observational study reports current infection control behaviours in the home in UK and international users of the website, and examine how they might be improved to reduce the spread of COVID-19.\n\nMethod28,285 users sought advice from four website pathways (to protect themselves generally, to protect others if the user was showing symptoms, to protect themselves if household members were showing symptoms, and to protect a household member who is at high risk) and completed outcome measures of current infection control behaviours within the home (self-isolation, social distancing, putting shopping/packages aside, wearing face-covering, cleaning and disinfecting, handwashing), and intentions to change these behaviours.\n\nResultsCurrent user behaviours mean scores varied across all infection control measures but were between sometimes and quite often, except handwashing ( very often). Behaviours were similar regardless of the website pathway used. After using Germ Defence, users recorded intentions to improve infection control behaviour across all website pathways and for all behaviours.\n\nConclusionsSelf-reported infection control behaviours other than handwashing are lower than is optimal for infection prevention, although reported handwashing is much higher. The advice using behaviour change techniques in Germ Defence led to intentions to improve these behaviours. This has been shown previously to reduce the incidence, severity and transmission of infections. These findings suggest that promoting Germ Defence within national and local public health guidance could reduce COVID-19 transmission.\n\nO_TEXTBOXSection 1: What is already known on this topicO_LIUntil a vaccine can prevent COVID-19, protective behaviours (such as social distancing, handwashing, cleaning/disinfecting) must be used to limit the spread.\nC_LIO_LIA digital behaviour change intervention to improve protective behaviours (handwashing) within the home succeeded in reducing infection transmission, healthcare utilisation and infection severity during the H1N1 pandemic (the PRIMIT trial).\nC_LIO_LIWe need to understand current levels of protective behaviour in the UK, and how to improve them, to prevent a second wave.\nC_LI\n\nSection 2: What this study addsO_LIOur study suggests that few people are undertaking sufficient protective infection control behaviours in the home to reduce transmission\nC_LIO_LIProviding targeted digital interventions such as Germ Defence (for example through public health and primary care networks) offers a feasible method of increasing intentions to undertake these behaviours.\nC_LI\n\nC_TEXTBOX", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Muna Alshekaili", - "author_inst": "Al Masarra Hospital, Ministry of Health, Oman" + "author_name": "Ben Ainsworth", + "author_inst": "University of Bath" + }, + { + "author_name": "Sascha Miller", + "author_inst": "University of Southampton" + }, + { + "author_name": "James Denison-Day", + "author_inst": "University of Southampton" + }, + { + "author_name": "Beth Stuart", + "author_inst": "University of Southampton" }, { - "author_name": "Walid Hassan", - "author_inst": "Al Masarra Hospital, Ministry of Health, Oman" + "author_name": "Julia Groot", + "author_inst": "University of Bath" }, { - "author_name": "Nazik Al Said", - "author_inst": "Al Masarra Hospital, Ministry of Health, Oman" + "author_name": "Cathy Rice", + "author_inst": "Public contributor" + }, + { + "author_name": "Jennifer Bostock", + "author_inst": "London School of Hygiene & Tropical Medicine" }, { - "author_name": "Fatima Alsulaimani", - "author_inst": "Al Masarra Hospital, Ministry of Health, Oman" + "author_name": "Xiao-Yang Hu", + "author_inst": "University of Southampton" }, { - "author_name": "Sathish Kumar Jayapal", - "author_inst": "Centre of Studies & Research, Directorate General Planning, and studies, Ministry of Health, Oman" + "author_name": "Kate Morton", + "author_inst": "University of Southampton" }, { - "author_name": "Adhra Al-Mawali", - "author_inst": "Centre of Studies & Research, Directorate General Planning, and studies, Ministry of Health, Oman" + "author_name": "Lauren Towler", + "author_inst": "University of Southampton" }, { - "author_name": "Moon Fai Chan", - "author_inst": "Department of Family Medicine & Public Health, College of Medicine & Health Sciences Sultan Qaboos University" + "author_name": "Michael Moore", + "author_inst": "University of Southampton" }, { - "author_name": "Sangeetha Mahadevan", - "author_inst": "Department of Behavioral Medicine, College of Medicine & Health Sciences, Sultan Qaboos University" + "author_name": "Merlin L Willcox", + "author_inst": "University of Southampton" }, { - "author_name": "Samir Al-Adawi", - "author_inst": "Sultan Qaboos University" + "author_name": "Tim Chadborn", + "author_inst": "Public Health England" + }, + { + "author_name": "Natalie Gold", + "author_inst": "Public Health England" + }, + { + "author_name": "Richard Amlot", + "author_inst": "Public Health England" + }, + { + "author_name": "Paul Little", + "author_inst": "University of Southampton" + }, + { + "author_name": "Lucy Yardley", + "author_inst": "University of Bristol" } ], "version": "1", "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.06.23.20138149", @@ -1370444,31 +1370406,43 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2020.06.22.165787", - "rel_title": "Detailed phylogenetic analysis of SARS-CoV-2 reveals latent capacity to bind human ACE2 receptor", + "rel_doi": "10.1101/2020.06.23.167544", + "rel_title": "An Enzymatic TMPRSS2 Assay for Assessment of Clinical Candidates and Discovery of Inhibitors as Potential Treatment of COVID-19", "rel_date": "2020-06-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.22.165787", - "rel_abs": "SARS-CoV-2 is a unique event, having emerged suddenly as a highly infectious viral pathogen for human populations. Previous phylogenetic analyses show its closest known evolutionary relative to be a virus detected in bats (RaTG13), with a common assumption that SARS-CoV-2 evolved from a zoonotic ancestor via recent genetic changes (likely in the Spike protein receptor binding domain - or RBD) that enabled it to infect humans. We used detailed phylogenetic analysis, ancestral sequence reconstruction, and in situ molecular dynamics simulations to examine the Spike-RBDs functional evolution, finding that the common ancestral virus with RaTG13, dating to at least 2013, possessed high binding affinity to the human ACE2 receptor. This suggests that SARS-CoV-2 likely possessed a latent capacity to bind to human cellular targets (though this may not have been sufficient for successful infection) and emphasizes the importance to expand the cataloging and monitoring of viruses circulating in both human and non-human populations.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.23.167544", + "rel_abs": "SARS-CoV-2 is the viral pathogen causing the COVID19 global pandemic. Consequently, much research has gone into the development of pre-clinical assays for the discovery of new or repurposing of FDA-approved therapies. Preventing viral entry into a host cell would be an effective antiviral strategy. One mechanism for SARS-CoV-2 entry occurs when the spike protein on the surface of SARS-CoV-2 binds to an ACE2 receptor followed by cleavage at two cut sites (\"priming\") that causes a conformational change allowing for viral and host membrane fusion. TMPRSS2 has an extracellular protease domain capable of cleaving the spike protein to initiate membrane fusion. A validated inhibitor of TMPRSS2 protease activity would be a valuable tool for studying the impact TMPRSS2 has in viral entry and potentially be an effective antiviral therapeutic. To enable inhibitor discovery and profiling of FDA-approved therapeutics, we describe an assay for the biochemical screening of recombinant TMPRSS2 suitable for high throughput application. We demonstrate effectiveness to quantify inhibition down to subnanomolar concentrations by assessing the inhibition of camostat, nafamostat and gabexate, clinically approved agents in Japan. Also, we profiled a camostat metabolite, FOY-251, and bromhexine hydrochloride, an FDA-approved mucolytic cough suppressant. The rank order potency for the compounds tested are: nafamostat (IC50 = 0.27 nM), camostat (IC50 = 6.2 nM), FOY-251 (IC50 = 33.3 nM) and gabexate (IC50 = 130 nM). Bromhexine hydrochloride showed no inhibition of TMPRSS2. Further profiling of camostat, nafamostat and gabexate against a panel of recombinant proteases provides insight into selectivity and potency.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Erin Brintnell", - "author_inst": "University of Calgary" + "author_name": "Jonathan H. Shrimp", + "author_inst": "National Center for Advancing Translational Sciences, NIH" }, { - "author_name": "Mehul Gupta", - "author_inst": "University of Calgary" + "author_name": "Stephen C. Kales", + "author_inst": "National Center for Advancing Translational Sciences, NIH" }, { - "author_name": "Dave W Anderson", - "author_inst": "University of Calgary" + "author_name": "Philip E. Sanderson", + "author_inst": "National Center for Advancing Translational Sciences, NIH" + }, + { + "author_name": "Anton Simeonov", + "author_inst": "National Center for Advancing Translational Sciences, NIH" + }, + { + "author_name": "Min Shen", + "author_inst": "National Center for Advancing Translational Sciences, NIH" + }, + { + "author_name": "Matthew D. Hall", + "author_inst": "National Center for Advancing Translational Sciences, NIH" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by", "type": "new results", - "category": "evolutionary biology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.06.22.166033", @@ -1371942,25 +1371916,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.18.20132977", - "rel_title": "Covid19 infection spread in Greece: Ensemble forecasting models with statistically calibrated parameters and stochastic noise", + "rel_doi": "10.1101/2020.06.20.20130476", + "rel_title": "Characterizing super-spreading events and age-specific infectivity of COVID-19 transmission in Georgia, USA", "rel_date": "2020-06-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20132977", - "rel_abs": "Following the outbreak of the novel coronavirus SARS-Cov2 in Europe and the subsequent failure of national healthcare systems to sufficiently respond to the fast spread of the pandemic, extensive statistical analysis and accurate forecasting of the epidemic in local communities is of primary importance in order to better organize the social and healthcare interventions and determine the epidemiological characteristics of the disease. For this purpose, a novel combination of Monte Carlo simulations, wavelet analysis and least squares optimization is applied to a known basis of SEIR compartmental models, resulting in the development of a novel class of stochastic epidemiological models with promising short and medium-range forecasting performance. The models are calibrated with the epidemiological data of Greece, while data from Switzerland and Germany are used as a supplementary background. The developed models are capable of estimating parameters of primary importance such as the reproduction number and the real magnitude of the infection in Greece. A clear demonstration of how the social distancing interventions managed to promptly restrict the epidemic growth in the country is included. The stochastic models are also able to generate robust 30-day and 60-day forecast scenarios in terms of new cases, deaths, active cases and recoveries.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.20.20130476", + "rel_abs": "It is imperative to advance our understanding of heterogeneities in the transmission of SARS-CoV-2 such as age-specific infectiousness and super-spreading. To this end, it is important to exploit multiple data streams that are becoming abundantly available during the pandemic. In this paper, we formulate an individual-level spatio-temporal mechanistic framework to integrate individual surveillance data with geo-location data and aggregate mobility data, enabling a more granular understanding of the transmission dynamics of SARS-CoV-2. We analyze reported cases, between March and early May 2020, in five (urban and rural) counties in the State of Georgia USA. First, our results show that the reproductive number reduced to below 1 in about two weeks after the shelter-in-place order. Super-spreading appears to be widespread across space and time, and it may have a particularly important role in driving the outbreak in rural areas and an increasing importance towards later stages of outbreaks in both urban and rural settings. Overall, about 2% of cases were directly responsible for 20% of all infections. We estimate that the infected non-elderly cases (<60) may be 2.78 [2.10, 4.22] times more infectious than the elderly, and the former tend to be the main driver of super-spreading. Our results improve our understanding of the natural history and transmission dynamics of SARS-CoV-2. More importantly, we reveal the roles of age-specific infectiousness and characterize systematic variations and associated risk factors of super-spreading. These have important implications for the planning of relaxing social distancing and, more generally, designing optimal control measures.\n\nSignificance StatementThere is still considerable scope for advancing our understanding of the epidemiology and ecology of COVID-19. In particular, much is unknown about individual-level transmission heterogeneities such as super-spreading and age-specific infectiousness. We statistically synthesize multiple valuable datastreams, including surveillance data and mobility data, that are available during the current COVID-19 pandemic. We show that age is an important factor in the transmission of the virus. Super-spreading is ubiquitous over space and time, and has particular importance in rural areas and later stages of an outbreak. Our results improve our understanding of the natural history the virus and have important implications for designing optimal control measures.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Georgios Politis Sr.", - "author_inst": "National Technical University of Athens" + "author_name": "Max SY Lau", + "author_inst": "Emory University" + }, + { + "author_name": "Bryan Grenfell", + "author_inst": "Princeton University" }, { - "author_name": "Leontios Hadjileontiadis Sr.", - "author_inst": "KHALIFA UNIVERSITY" + "author_name": "Michael Thomas", + "author_inst": "Georgia Department of Public Health" + }, + { + "author_name": "Michael Bryan", + "author_inst": "Georgia Department of Public Health" + }, + { + "author_name": "Kristin Nelson", + "author_inst": "Emory University" + }, + { + "author_name": "Ben Lopman", + "author_inst": "Emory University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1373659,55 +1373649,27 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.06.20.162826", - "rel_title": "anti-IL-6 versus anti-IL-6R Blocking Antibodies to Treat Acute Ebola Infection in BALB/c Mice with Potential Implications for Treating Patients Presenting with COVID-19", + "rel_doi": "10.1101/2020.06.21.163592", + "rel_title": "RNA-Dependent RNA Polymerase From SARS-CoV-2. Mechanism Of Reaction And Inhibition By Remdesivir.", "rel_date": "2020-06-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.20.162826", - "rel_abs": "Cytokine release syndrome (CRS) is known to be a factor in morbidity and mortality associated with acute viral infections including those caused by filoviruses and coronaviruses. IL-6 has been implicated as a cytokine negatively associated with survival after filovirus and coronavirus infection. However, IL-6 has also been shown to be an important mediator of innate immunity and important for the host response to an acute viral infection. Clinical studies are now being conducted by various researchers to evaluate the possible role of IL-6 blockers to improve outcomes in critically ill patients with CRS. Most of these studies involve the use of anti-IL-6R monoclonal antibodies (-IL-6R mAbs). We present data showing that direct neutralization of IL-6 with an -IL-6 mAb in a BALB/c Ebolavirus (EBOV) challenge model produced a statistically significant improvement in outcome compared with controls when administered within the first 24 hours of challenge and repeated every 72 hours. A similar effect was seen in mice treated with the same dose of -IL-6R mAb when the treatment was delayed 48 hrs post-challenge. These data suggest that direct neutralization of IL-6, early during the course of infection, may provide additional clinical benefits to IL-6 receptor blockade alone during treatment of patients with virus-induced CRS.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.21.163592", + "rel_abs": "We combine sequence analysis, molecular dynamics and hybrid quantum mechanics/molecular mechanics simulations to obtain the first description of the mechanism of reaction of SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) and of the inhibition of the enzyme by Remdesivir. Despite its evolutionary youth, the enzyme is highly optimized to have good fidelity in nucleotide incorporation and a good catalytic efficiency. Our simulations strongly suggest that Remdesivir triphosphate (the active form of drug) is incorporated into the nascent RNA replacing ATP, leading to a duplex RNA which is structurally very similar to an unmodified one. We did not detect any reason to explain the inhibitory activity of Remdesivir at the active site. Displacement of the nascent Remdesivir-containing RNA duplex along the exit channel of the enzyme can occur without evident steric clashes which would justify delayed inhibition. However, after the incorporation of three more nucleotides we found a hydrated Serine which is placed in a perfect arrangement to react through a Pinners reaction with the nitrile group of Remdesivir. Kinetic barriers for crosslinking and polymerization are similar suggesting a competition between polymerization and inhibition. Analysis of SARS-CoV-2 mutational landscape and structural analysis of polymerases across different species support the proposed mechanism and suggest that virus has not explored yet resistance to Remdesivir inhibition.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Reid Martin Rubsamen", - "author_inst": "Flow Pharma, Inc." - }, - { - "author_name": "Scott Burkholz", - "author_inst": "Flow Pharma, Inc." - }, - { - "author_name": "Shane Massey", - "author_inst": "University of Texas Medical Branch" - }, - { - "author_name": "Trevor Brasel", - "author_inst": "University of Texas Medical Branch" - }, - { - "author_name": "Tom Hodge", - "author_inst": "Flow Pharma, Inc." - }, - { - "author_name": "Lu Wang", - "author_inst": "Flow Pharma, Inc." - }, - { - "author_name": "Charles Herst", - "author_inst": "Flow Pharma, Inc." - }, - { - "author_name": "Richard Thomas Carback III", - "author_inst": "Flow Pharma, Inc" + "author_name": "Juan Aranda", + "author_inst": "IRB Barcelona" }, { - "author_name": "Paul Harris", - "author_inst": "Columbia University Medical Center" + "author_name": "Modesto Orozco", + "author_inst": "IRB Barcelona" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "immunology" + "category": "biophysics" }, { "rel_doi": "10.1101/2020.06.21.163410", @@ -1375293,69 +1375255,77 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.19.20135756", - "rel_title": "Sensitivity of RT-PCR testing of upper respiratory tract samples for SARS-CoV-2 in hospitalised patients: a retrospective cohort study.", + "rel_doi": "10.1101/2020.06.18.20135137", + "rel_title": "Epidemiological description and analysis of RdRp, E and N genes dynamic by RT-PCR of SARS-CoV-2 in Moroccan population: Experience of the National Reference Laboratory (LNR)-UM6SS", "rel_date": "2020-06-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.19.20135756", - "rel_abs": "ObjectivesTo determine the sensitivity and specificity of RT-PCR testing of upper respiratory tract (URT) samples from hospitalised patients with COVID-19, compared to the gold standard of a clinical diagnosis.\n\nMethodsAll URT RT-PCR testing for SARS-CoV-2 in NHS Lothian, Scotland, United Kingdom between the 7th of February and 19th April 2020 (inclusive) was reviewed, and hospitalised patients were identified. All URT RT-PCR tests were analysed for each patient to determine the sequence of negative and positive results. For those who were tested twice or more but never received a positive result, case records were reviewed, and a clinical diagnosis of COVID-19 allocated based on clinical features, discharge diagnosis, and radiology and haematology results. For those who had negative URT RT-PCR tests but a clinical diagnosis of COVID-19, respiratory samples were retested using a multiplex respiratory panel, a second SARS-CoV-2 RT-PCR assay, and a human RNase P control.\n\nResultsCompared to the gold standard of a clinical diagnosis of COVID-19, the sensitivity of an initial URT RT-PCR for COVID-19 was 82.2% (95% confidence interval 79.0-85.1%). Two consecutive URT RT-PCR tests increased sensitivity to 90.6% (CI 88.0-92.7%). A further 2.2% and 0.9% of patients who received a clinical diagnosis of COVID-19 were positive on a third and fourth test.\n\nConclusionsThe sensitivity of a single RT-PCR test of an URT sample in hospitalised patients is 82.2%. Sensitivity increases to 90.6% when patients are tested twice. A proportion of cases with clinically defined COVID-19 never test positive on URT RT-PCR despite repeated testing.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20135137", + "rel_abs": "The coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a new infectious disease that first emerged in Hubei province, China, in December 2019. On 2 March 2020, the Moroccan Ministry of Health confirmed the first COVID-19 case in Morocco. The new virus SARS-CoV-2 was identified in the sample of a Moroccan expatriate residing in Italy. Without a therapeutic vaccine or specific antiviral drugs, early detection and isolation become essential against novel Coronavirus.\n\nThis study aims to analyze the epidemiological profile of the SARS-CoV-2 in Moroccan cases and to investigate the dynamic of RdRp, N, and E genes in patients from diagnosis until the recovery.\n\nAmong 859 COVID-19 RT-PCR tests realized for 376 patients, 187 cases had positive results COVID-19. 4% were positive with the 3 genes RdRp, N, and E, 40 % with N and E genes, 3% with RdRp and N genes, 31% with only the RdRp gene and 22% cases are positives with N gene. The analysis of the Covid-19 genes (RdRp, N, and E) dynamic reveal that more than 6% stay positive with detection of the N and E gene, and 14% with the N gene after 12 days of treatment.\n\nThe median period from positive to the first negative Covid-19 RT-PCR tests was 6.8{+/-}2.24 days for 44% cases, 14.31{+/-} 2.4 days for 30%, and 22.67 {+/-} 1.21 days for 4%.\n\nThis a first description of the Moroccan COVID-19 cases and the analysis of the dynamic of the RdRp, N, and E genes. The analysis of our population can help to improve in the care of patients.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Thomas C Williams", - "author_inst": "MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, UK" + "author_name": "Houda Benrahma", + "author_inst": "Faculty of Medicine, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Elizabeth Wastnedge", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Idrissa Diawara", + "author_inst": "Faculty of Science and Health Techniques, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Gina McAllister", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Imane Smyej", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Ramya Bhatia", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Jalila Rahoui", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Kate Cuschieri", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Nida Meskaouni", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Kallirroi Kefala", - "author_inst": "Edinburgh Critical Care Research Group, University of Edinburgh, Edinburgh, UK" + "author_name": "Rachid Benmessaoud", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Fiona J Hamilton", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Khadija Arouro", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Ingolfur Johannessen", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Khadija Jaras", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Ian F Laurenson", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Zahra Adam", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Jill Shepherd", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Salma Nahir", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Alistair Stewart", - "author_inst": "eHealth Directorate, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Zineb Aouzal", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Donal Waters", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Hajar Elguazzar", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Helen Wise", - "author_inst": "Blood Sciences, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Leila Jeddane", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." }, { - "author_name": "Kate Templeton", - "author_inst": "Clinical Microbiology & Virology, Directorate of Laboratory Medicine, Royal Infirmary of Edinburgh, NHS Lothian, Edinburgh, UK" + "author_name": "Fadwa Ousti", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." + }, + { + "author_name": "Jalila Elbakkouri", + "author_inst": "National Reference Laboratory, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." + }, + { + "author_name": "Chakib Nejjari", + "author_inst": "International School of Public Health, Mohammed VI University of Health Sciences (UM6SS), Casablanca, Morocco." } ], "version": "1", @@ -1376671,139 +1376641,199 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.06.18.20134742", - "rel_title": "Racial and ethnic determinants of Covid-19 risk", + "rel_doi": "10.1101/2020.06.17.20134031", + "rel_title": "Prolonged low-dose methylprednisolone in patients with severe COVID-19 pneumonia", "rel_date": "2020-06-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.18.20134742", - "rel_abs": "BackgroundRacial and ethnic minorities have disproportionately high hospitalization rates and mortality related to the novel coronavirus disease 2019 (Covid-19). There are comparatively scant data on race and ethnicity as determinants of infection risk.\n\nMethodsWe used a smartphone application (beginning March 24, 2020 in the United Kingdom [U.K.] and March 29, 2020 in the United States [U.S.]) to recruit 2,414,601 participants who reported their race/ethnicity through May 25, 2020 and employed logistic regression to determine the adjusted odds ratios (aORs) and 95% confidence intervals (CIs) for a positive Covid-19 test among racial and ethnic groups.\n\nResultsWe documented 8,858 self-reported cases of Covid-19 among 2,259,841 non-Hispanic white; 79 among 9,615 Hispanic; 186 among 18,176 Black; 598 among 63,316 Asian; and 347 among 63,653 other racial minority participants. Compared with non-Hispanic white participants, the risk for a positive Covid-19 test was increased across racial minorities (aORs ranging from 1.24 to 3.51). After adjustment for socioeconomic indices and Covid-19 exposure risk factors, the associations (aOR [95% CI]) were attenuated but remained significant for Hispanic (1.58 [1.24-2.02]) and Black participants (2.56 [1.93-3.39]) in the U.S. and South Asian (1.52 [1.38-1.67]) and Middle Eastern participants (1.56 [1.25-1.95]) in the U.K. A higher risk of Covid-19 and seeking or receiving treatment was also observed for several racial/ethnic minority subgroups.\n\nConclusionsOur results demonstrate an increase in Covid-19 risk among racial and ethnic minorities not completely explained by other risk factors for Covid-19, comorbidities, and sociodemographic characteristics. Further research investigating these disparities are needed to inform public health measures.", - "rel_num_authors": 30, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.17.20134031", + "rel_abs": "BackgroundIn hospitalized patients with COVID-19 pneumonia, progression to acute respiratory failure requiring invasive mechanical ventilation (MV) is associated with significant morbidity and mortality. Severe dysregulated systemic inflammation is the putative mechanism. We hypothesize that early prolonged methylprednisolone (MP) treatment could accelerate disease resolution, decreasing the need for ICU and mortality.\n\nMethodsWe conducted a multicenter, observational study to explore the association between exposure to prolonged, low-dose, MP treatment and need for ICU referral, intubation or death within 28 days (composite primary endpoint) in patients with severe COVID-19 pneumonia admitted to Italian respiratory high-dependency units. Secondary outcomes were invasive MV-free days and changes in C-reactive protein (CRP) levels.\n\nResultsFindings are reported as MP (n=83) vs. control (n=90). The composite primary endpoint was met by 19 vs. 40 [adjusted hazard ratio (HR) 0.41; 95% confidence interval (CI): 0.24-0.72]. Transfer to ICU and need for invasive MV was necessary in 15 vs. 27 (p=0.07) and 14 vs. 26 (p=0.10), respectively. By day 28, the MP group had fewer deaths (6 vs. 21, adjusted HR=0.29; 95% CI: 0.12-0.73) and more days off invasive MV (24.0 {+/-} 9.0 vs. 17.5 {+/-} 12.8; p=0.001). Study treatment was associated with rapid improvement in PaO2:FiO2 and CRP levels. The complication rate was similar for the two groups (p=0.84).\n\nConclusionIn patients with severe COVID-19 pneumonia, early administration of prolonged MP treatment was associated with a significantly lower hazard of death (71%) and decreased ventilator dependence. Randomized controlled studies are needed to confirm these findings.\n\nRegistrationClinicalTrials.gov. Identifier: NCT04323592", + "rel_num_authors": 45, "rel_authors": [ { - "author_name": "Chun-Han Lo", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Francesco Salton", + "author_inst": "University of Trieste" }, { - "author_name": "Long H. Nguyen", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Paola Confalonieri", + "author_inst": "University of Trieste" }, { - "author_name": "David A. Drew", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Pierachille Santus", + "author_inst": "University of Milan" }, { - "author_name": "Mark S. Graham", - "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K." + "author_name": "Sergio Harari", + "author_inst": "Ospedale San Giuseppe, Milan, Italy" }, { - "author_name": "Erica T. Warner", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Raffaele Scala", + "author_inst": "Ospedale San Donato, Arezzo, Italy" }, { - "author_name": "Amit D. Joshi", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Simone Lanini", + "author_inst": "Istituto Spallanzani, Rome, Italy" }, { - "author_name": "Christina M. Astley", - "author_inst": "Computational Epidemiology Lab and Division of Endocrinology, Boston Children's Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A" + "author_name": "Valentina Vertui", + "author_inst": "Policlinico San Matteo, Pavia, Italy" }, { - "author_name": "Chuan-Guo Guo", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Tiberio Oggionni", + "author_inst": "Policlinico San Matteo, Pavia, Italy" }, { - "author_name": "Wenjie Ma", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Antonella Caminati", + "author_inst": "San Giuseppe Hospital Multimedica, Milan, Italy" }, { - "author_name": "Raaj S. Mehta", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Vincenzo Patruno", + "author_inst": "Azienda Sanitaria Universitaria Friuli Centrale, Udine, Italy" }, { - "author_name": "Sohee Kwon", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Mario Tamburrini", + "author_inst": "Azienda Sanitaria Friuli Occidentale, Pordenone, Italy" }, { - "author_name": "Mingyang Song", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Alessandro Scartabellati", + "author_inst": "Ospedale Maggiore, Crema, Italy" }, { - "author_name": "Richard Davies", - "author_inst": "Zoe Global Limited, London, U.K." + "author_name": "Mara Parati", + "author_inst": "Ospedale Maggiore di Crema" }, { - "author_name": "Joan Capdevila", - "author_inst": "Zoe Global Limited, London, U.K." + "author_name": "Massimiliano Villani", + "author_inst": "Ospedale Maggiore, Crema, Italy" }, { - "author_name": "Karla A. Lee", - "author_inst": "Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K." + "author_name": "Dejan Radovanovic", + "author_inst": "Ospedale Sacco, Milan, Italy" }, { - "author_name": "Mary Ni Lochlainn", - "author_inst": "Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K." + "author_name": "Sara Tomassetti", + "author_inst": "University of Florence, Italy" }, { - "author_name": "Thomas Varsavsky", - "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K." + "author_name": "Claudia Ravaglia", + "author_inst": "Ospedale Pierantoni, Forli, Italy" }, { - "author_name": "Carole H. Sudre", - "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K." + "author_name": "Venerino Poletti", + "author_inst": "Ospedale Pierantoni, Forli, Italy" }, { - "author_name": "Jonathan Wolf", - "author_inst": "Zoe Global Limited, London, U.K." + "author_name": "Andrea Vianello", + "author_inst": "University of Padua, Italy" }, { - "author_name": "Yvette C. Cozier", - "author_inst": "Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A." + "author_name": "Anna Talia Gaccione", + "author_inst": "General Hospital, Vittorio Veneto, Italy" }, { - "author_name": "Lynn Rosenberg", - "author_inst": "Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A." + "author_name": "Luca Guidelli", + "author_inst": "Ospeadle San Donato, Arezzo, Italy" }, { - "author_name": "Lynne R. Wilkens", - "author_inst": "Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, U.S.A." + "author_name": "Rita Raccanelli", + "author_inst": "Ospedale San Giuseppe, Milan, Italy" }, { - "author_name": "Christopher A. Haiman", - "author_inst": "Department of Preventative Medicine, Keck School of Medicine, University of Southern California, Norris Comprehensive Cancer Center, Los Angeles, California, U." + "author_name": "Donato Lacedonia", + "author_inst": "University of Foggia" }, { - "author_name": "Loic Le Marchand", - "author_inst": "Epidemiology Program, University of Hawaii Cancer Center, Honolulu, Hawaii, U.S.A." + "author_name": "Paolo Lucernoni", + "author_inst": "General Hospital, Vittorio Veneto, Italy" }, { - "author_name": "Julie R. Palmer", - "author_inst": "Slone Epidemiology Center, Boston University, Boston, Massachusetts, U.S.A." + "author_name": "Maria Pia Foschino Barbaro", + "author_inst": "University of Foggia" }, { - "author_name": "Tim D. Spector", - "author_inst": "Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K." + "author_name": "Stefano Centanni", + "author_inst": "Ospedale San Paolo, Milan, Italy" }, { - "author_name": "Sebastien Ourselin", - "author_inst": "School of Biomedical Engineering & Imaging Sciences, King's College London, London, U.K." + "author_name": "Michele Mondoni", + "author_inst": "Ospedale San Paolo, Milan, Italy" }, { - "author_name": "Claire J. Steves", - "author_inst": "Department of Twin Research and Genetic Epidemiology, King's College London, London, U.K." + "author_name": "Matteo Davi", + "author_inst": "University of Milan" }, { - "author_name": "Andrew T. Chan", - "author_inst": "Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School. Boston, Massachusetts, U.S.A." + "author_name": "Alberto Fantin", + "author_inst": "Azienda Sanitaria Universitaria Friuli Centrale, Udin, Italy" }, { - "author_name": "- COPE Consortium", - "author_inst": "" + "author_name": "Xueyuan Cao", + "author_inst": "University of Tennessee, Memphis, USA" + }, + { + "author_name": "Lucio Torelli", + "author_inst": "University of Trieste" + }, + { + "author_name": "Antonella Zucchetto", + "author_inst": "CRO Aviano" + }, + { + "author_name": "Marcella Montico", + "author_inst": "CRO Aviano" + }, + { + "author_name": "Annalisa Casarin", + "author_inst": "University of Hertfordshire, Hatfield UK" + }, + { + "author_name": "Micaela Romagnoli", + "author_inst": "Hospital of Treviso" + }, + { + "author_name": "Stefano Gasparini", + "author_inst": "University of Ancona" + }, + { + "author_name": "Martina Bonifazi", + "author_inst": "University of Ancona" + }, + { + "author_name": "Pierlanfranco D'Agaro", + "author_inst": "University of Trieste" + }, + { + "author_name": "Alessandro Marcello", + "author_inst": "ICGEB" + }, + { + "author_name": "Danilo Licastro", + "author_inst": "Area Science Park, Trieste, Italy" + }, + { + "author_name": "Barbara Ruaro", + "author_inst": "University Hospital of Trieste" + }, + { + "author_name": "Maria Concetta Volpe", + "author_inst": "University of Trieste" + }, + { + "author_name": "Reba Umberger", + "author_inst": "University of Tennessee, Memphis, USA" + }, + { + "author_name": "Gianfranco Umberto Meduri", + "author_inst": "University of Tennessee, Memphis, USA" + }, + { + "author_name": "Marco Confalonieri", + "author_inst": "University of Trieste" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.06.18.20133645", @@ -1379061,73 +1379091,61 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.06.17.20133678", - "rel_title": "FAR AWAY FROM HERD IMMUNITY TO SARS-CoV-2: results from a survey in healthy blood donors in South Eastern Italy", + "rel_doi": "10.1101/2020.06.16.20126714", + "rel_title": "Comparative Survival Analysis of Immunomodulatory Therapy for COVID-19 'Cytokine Storm': A Retrospective Observational Cohort Study", "rel_date": "2020-06-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.17.20133678", - "rel_abs": "Here we present results from a survey on anti-SARS-CoV-2 seroprevalence in healthy blood donors from a low incidence COVID-19 area (Apulia region, South Eastern Italy).\n\nAmong 904 subjects tested, only in 9 cases (0.99%) antibodies against SARS-CoV-2 were demonstrated. All the 9 seropositive patients were negative for the research of viral RNA by RT-PCR in nasopharyngeal swab.\n\nThese data, along with those recently reported from other countries, clearly show that we are very far from herd immunity and that the containment measures are at the moment the only realistic instrument we have to slow the spread of the pandemic.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20126714", + "rel_abs": "BackgroundCytokine storm is a marker of COVID-19 illness severity and increased mortality. Immunomodulatory treatments have been repurposed to improve mortality outcomes.\n\nMethodsWe conducted a retrospective analysis of electronic health records across the Northwell Health system. COVID-19 patients hospitalized between March 1, 2020 and April 15, 2020, were included. Cytokine storm was defined by inflammatory markers: ferritin >700ng/mL, C-reactive protein >30mg/dL, or lactate dehydrogenase >300U/L. Patients were subdivided into six groups -no immunomodulatory treatment (standard of care) and five groups that received either corticosteroids, anti-interleukin 6 (IL-6) antibody (tocilizumab) or anti-IL-1 therapy (anakinra) alone or in combination with corticosteroids. The primary outcome was hospital mortality.\n\nResultsThere were 3,098 patients who met inclusion criteria. The most common comorbidities were hypertension (40-56%), diabetes (32-43%) and cardiovascular disease (2-15%). Patients most frequently met criteria with high lactate dehydrogenase (74.8%) alone, or in combination, followed by ferritin (71.4%) and C-reactive protein (9.4%). More than 80% of patients had an elevated D-dimer. Patients treated with a combination of tocilizumab and corticosteroids (Hazard Ratio [HR]: 0.459, 95% Confidence Interval [CI]: 0.295-0.714; p<0.0001) or corticosteroids alone (HR: 0.696, 95% CI: 0.512-0.946; p=0.01) had improved hospital survival compared to standard of care. Corticosteroids and tocilizumab was associated with increased survival when compared to corticosteroids and anakinra (HR: 0.612, 95% CI: 0.391-0.958; p-value=0.02).\n\nConclusionsWhen compared to standard of care, corticosteroid and tocilizumab used in combination, or corticosteroids alone, was associated with reduced hospital mortality for patients with COVID-19 cytokine storm.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "jose ramon fiore", - "author_inst": "University of Foggia" - }, - { - "author_name": "michele centra", - "author_inst": "Ospedali Riuniti University Hospital Foggia" - }, - { - "author_name": "armando de carlo", - "author_inst": "Ospedali Riuniti University Hospital, Foggia" - }, - { - "author_name": "marco granato", - "author_inst": "Ospedali riuniti University Hospital Foggia" + "author_name": "Sonali Narain", + "author_inst": "Northwell Health" }, { - "author_name": "annamaria rosa", - "author_inst": "Ospedali riuniti University Hospital Foggia" + "author_name": "Dimitre Stefanov", + "author_inst": "Northwell Health" }, { - "author_name": "lucia de feo", - "author_inst": "Ospedali riuniti university hospital foggia" + "author_name": "Alice S Chau", + "author_inst": "Seattle Children's Research Institute" }, { - "author_name": "mariantonietta di stefano", - "author_inst": "University of Foggia" + "author_name": "Andrew G Weber", + "author_inst": "Northwell health" }, { - "author_name": "maria d ' errico", - "author_inst": "university of foggia" + "author_name": "Galina S Marder", + "author_inst": "northwell health" }, { - "author_name": "sergio lo caputo", - "author_inst": "University of foggia" + "author_name": "Blanka Kaplan", + "author_inst": "Northwell Health" }, { - "author_name": "rosella de nittis", - "author_inst": "Ospedali riuniti university hospital foggia" + "author_name": "Prashant Malhotra", + "author_inst": "Northwell Health" }, { - "author_name": "fabio arena", - "author_inst": "university of foggia" + "author_name": "Ona Bloom", + "author_inst": "Northwell Health" }, { - "author_name": "gaetano corso", - "author_inst": "university of foggia" + "author_name": "Audrey Liu", + "author_inst": "Northwell Health" }, { - "author_name": "maurizio MARGAGLIONE", - "author_inst": "UNIVERSITY OF FOGGIA" + "author_name": "Martin Lesser", + "author_inst": "Northwell Health" }, { - "author_name": "TERESA ANTONIA SANTANTONIO", - "author_inst": "UNIVERSITY OF FOGGIA" + "author_name": "Negin Hajizadeh", + "author_inst": "Northwell Health" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1380391,43 +1380409,55 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.16.20133066", - "rel_title": "Effect of hydroxychloroquine on SARS-CoV-2 viral load in patients with COVID-19", + "rel_doi": "10.1101/2020.06.17.20133124", + "rel_title": "The Endothelial Dysfunction and Pyroptosis Driving the SARS-CoV-2 Immune-Thrombosis", "rel_date": "2020-06-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20133066", - "rel_abs": "BackgroundSome studies have shown that hydroxychloroquine (HCQ) is an effective drug in reducing the in vitro replication of SARS-CoV-2. However, the in vivo effect of HCQ still unclear. This study aims to evaluate viral load clearance in patients with COVID-19 who underwent HCQ treatment in comparison with a control group that did not receive the drug.\n\nMethodsThis prospective study comprised consecutive viral load measurements in patients with COVID-19 hospitalized with a moderate illness. Patients received 400 mg of HCQ every 12 hours for 10 days according to the medical decision. Nasal swab samples were collected at the 1st, 7th, and 14th days of the admission.\n\nResults155 samples were collected from 66 patients with COVID-19 (60% female), with a median age of 58 years. The viral load between studied groups, assumed as a semiquantitative measure of cycle threshold (Ct) values, presented no significant difference within the three consecutive measures ({Delta}Ct) (p>0.05). We also analyzed the {Delta}Ct viral load at different intervals of sample collection ({Delta}t <7; 7-12 and >12 days) without significant differences at any {Delta}Ct (p>0.05).\n\nConclusionIn this study, we did not observe any change in viral load in vivo with the use of HCQ.\n\nSummaryWe evaluate viral load clearance in patients with COVID-19 who took hydroxychloroquine (HCQ) for treatment and those who not. Prospective viral load measurements have shown any change in viral load in vivo with the use of HCQ.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.17.20133124", + "rel_abs": "ObjectiveEndothelial cells that are close to the alveolar-capillary exchange membranes can be activated by SARS-CoV-2 infection leading to cytokine release and macrophage activation syndrome. This could trigger endothelial dysfunction, pyroptosis, and immunothrombosis, which are the vascular changes commonly referred to as COVID-19 endotheliopathy. Thus, this study aimed to identify tissue biomarkers associated with endothelial activation/dysfunction and the pyroptosis pathway in the lung and myocardial samples of COVID-19 patients and to compare them to pandemic Influenza A virus H1N1 subtype - 2009 and Control cases.\n\nApproach and ResultsPost-mortem lung (COVID-19 group=6 cases; H1N1 group=10 cases, and Control group=11 cases) and myocardial samples (COVID-19=2 cases and control=1 case) were analyzed using immunohistochemistry and the following monoclonal primary antibodies: anti-CD163, anti-interleukin-6 (IL-6), anti-tumor necrosis factor-alpha (TNF-alpha), anti-intercellular adhesion molecule-1 (ICAM-1), and anti-caspase-1. From the result, IL-6, TNF-alpha, ICAM-1, and caspase-1 showed higher tissue expression in the COVID-19 group than in the H1N1 and control groups.\n\nConclusionOur results demonstrated the presence of endotheliopathy and suggest the participation of the pyroptosis pathway in both the pulmonary and myocardial samples. These conditions might lead to systemic immunothrombotic events that could impair the efforts of clinical staff to avoid fatal outcomes. One of the goals of health professionals should be to identify the high-risk of immunothrombosis patients early to block endotheliopathy and its consequences.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Klinger Soares Faico-Filho", - "author_inst": "Federal University of Sao Paulo" + "author_name": "Seigo Nagashima", + "author_inst": "Pontifical Catholic University of Parana" }, { - "author_name": "Danielle Dias Conte", - "author_inst": "Universidade Federal de Sao Paulo" + "author_name": "Monalisa Castilho Mendes", + "author_inst": "Postgraduation Program in Biotechnology Applied in Health of Children and Adolescent" }, { - "author_name": "Luciano Kleber Souza Luna", - "author_inst": "Universidade Federal de Sao Paulo" + "author_name": "Ana Paula Camargo Martins", + "author_inst": "Pontifical Catholic University of Parana" }, { - "author_name": "Joseane Mayara Almeida Carvalho", - "author_inst": "Universidade Federal de Sao Paulo" + "author_name": "Nicolas Henrique Borges", + "author_inst": "Pontifical Catholic University of Parana" }, { - "author_name": "Ana Helena Sitta Perosa", - "author_inst": "Universidade Federal de Sao Paulo" + "author_name": "Thiago Mateus Godoy", + "author_inst": "Pontifical Catholic University of Parana" }, { - "author_name": "Nancy Bellei", - "author_inst": "Universidade Federal de Sao Paulo" + "author_name": "Anna Flavia Miggiolaro Ribeiro", + "author_inst": "Pontifical Catholic University of Parana" + }, + { + "author_name": "Felipe da Silva Deziderio", + "author_inst": "Pontifical Catholic University of Parana" + }, + { + "author_name": "Lucia de Noronha", + "author_inst": "Pontifical Catholic University of Parana" + }, + { + "author_name": "Cleber Machado-Souza", + "author_inst": "Postgraduation Program in Biotechnology Applied in Health of Children and Adolescent" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "pathology" }, { "rel_doi": "10.1101/2020.06.17.20133876", @@ -1382077,61 +1382107,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.16.20133140", - "rel_title": "COVID-19 outcomes, risk factors and associations by race: a comprehensive analysis using electronic health records data in Michigan Medicine", + "rel_doi": "10.1101/2020.06.16.20133322", + "rel_title": "KNOWLEDGE AND BEHAVIORS RELATED TO THE COVID-19 PANDEMIC IN MALAWI", "rel_date": "2020-06-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20133140", - "rel_abs": "Structured AbstractO_ST_ABSImportanceC_ST_ABSBlacks/African-Americans are overrepresented in the number of COVID-19 infections, hospitalizations and deaths. Reasons for this disparity have not been well-characterized but may be due to underlying comorbidities or sociodemographic factors.\n\nObjectiveTo systematically determine patient characteristics associated with racial/ethnic disparities in COVID-19 outcomes.\n\nDesignA retrospective cohort study with comparative control groups.\n\nSettingPatients tested for COVID-19 at University of Michigan Medicine from March 10, 2020 to April 22, 2020.\n\nParticipants5,698 tested patients and two sets of comparison groups who were not tested for COVID-19: randomly selected unmatched controls (n = 7,211) and frequency-matched controls by race, age, and sex (n = 13,351).\n\nMain Outcomes and MeasuresWe identified factors associated with testing and testing positive for COVID-19, being hospitalized, requiring intensive care unit (ICU) admission, and mortality (in/out-patient during the time frame). Factors included race/ethnicity, age, smoking, alcohol consumption, healthcare utilization, and residential-level socioeconomic characteristics (SES; i.e., education, unemployment, population density, and poverty rate). Medical comorbidities were defined from the International Classification of Diseases (ICD) codes, and were aggregated into a comorbidity score.\n\nResultsOf 5,698 patients, (median age, 47 years; 38% male; mean BMI, 30.1), the majority were non-Hispanic Whites (NHW, 59.2%) and non-Hispanic Black/African-Americans (NHAA, 17.2%). Among 1,119 diagnosed, there were 41.2% NHW and 37.4% NHAA; 44.8% hospitalized, 20.6% admitted to ICU, and 3.8% died. Adjusting for age, sex, and SES, NHAA were 1.66 times more likely to be hospitalized (95% CI, 1.09-2.52; P=.02), 1.52 times more likely to enter ICU (95% CI, 0.92-2.52; P=.10). In addition to older age, male sex and obesity, high population density neighborhood (OR, 1.27 associated with one SD change [95% CI, 1.20-1.76]; P=.02) was associated with hospitalization. Pre-existing kidney disease led to 2.55 times higher risk of hospitalization (95% CI, 1.62-4.02; P<.001) in the overall population and 11.9 times higher mortality risk in NHAA (95% CI, 2.2-64.7, P=.004).\n\nConclusions and RelevancePre-existing type II diabetes/kidney diseases and living in high population density areas were associated with high risk for COVID-19 susceptibility and poor prognosis. Association of risk factors with COVID-19 outcomes differed by race. NHAA patients were disproportionately affected by obesity and kidney disease.\n\nKey PointsO_ST_ABSQuestionC_ST_ABSWhat are the sociodemographic and pre-existing health conditions associated with COVID-19 outcomes and how do they differ by race/ethnicity?\n\nFindingsIn this retrospective cohort of 5,698 patients tested for COVID-19, high population density and comorbidities such as type II diabetes/kidney disease were associated with hospitalization, in addition to older age, male sex and obesity. Adjusting for covariates, non-Hispanic Blacks were 1.66 times more likely to be hospitalized and 1.52 times more likely to be admitted to ICUs than non-Hispanic Whites.\n\nMeaningTargeted interventions to support vulnerable populations are needed. Racial disparities existed in COVID-19 outcomes that cannot be explained after controlling for age, sex, and socioeconomic status.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.16.20133322", + "rel_abs": "BackgroundThere are limited data on knowledge and behaviors related to COVID-19 in African countries.\n\nMethodsBetween April 25th and May 23rd, we contacted 793 individuals aged 18 and older, who previously participated in studies conducted in the Karonga Health and Demographic Surveillance Site in Malawi. During an interview by mobile phone, we ascertained respondents sources of information about COVID-19 and we evaluated their knowledge of the transmission and course/severity of COVID-19. We also asked them to evaluate their own risks of infection and severe illness. Finally, we inquired about the preventive measures they had adopted in response to the pandemic. We described patterns of knowledge and behaviors by area of residence (rural vs. urban).\n\nResultsWe interviewed 630 respondents (79.5% response rate). Four hundred and eighty-nine respondents resided in rural areas (77.6%) and 141 in urban areas (22.4%). Only one respondent had never heard of COVID-19. Misconceptions about the modes of transmission of SARS-CoV-2, and about the course and severity of COVID-19, were common. For example, 33.2% of respondents believed that the novel coronavirus is also waterborne and 50.6% believed that it is also bloodborne. A large percentage of respondents perceived that there was no risk, or only a small risk, that they would become infected (44.4%), but 72% of respondents expected to be severely ill if they became infected with SARS-CoV-2. Increased hand washing and avoiding crowds were the most reported strategies to prevent the spread of SARS-CoV-2. Use of face masks was more common among urban residents (22.5%) than among rural residents (5.0%).\n\nConclusionDespite widespread access to information about the COVID-19 pandemic, gaps in knowledge about COVID-19 persist in this population. The adoption of preventive strategies remains limited, possibly due to low perceived risk of infection among a large fraction of the population.\n\nWhat is already known?O_LISARS-CoV-2 is projected to spread widely in African countries.\nC_LIO_LIThere is limited information about what affected populations know about this new health threat, and how they react to it.\nC_LI\n\nWhat are the new findings?O_LIIn a study in Malawi, respondents lacked knowledge about several aspects of the transmission of SARS-CoV-2, and about the course and severity of COVID-19.\nC_LIO_LIThese knowledge gaps were larger among residents of rural areas than among urban dwellers.\nC_LIO_LIStudy respondents perceived themselves at low risk of infection with SARS-CoV-2, but they over-estimated the likely severity of the disease they would experience if they became infected.\nC_LIO_LIMost respondents reported increased frequency of handwashing, but the adoption of other protective behaviors (e.g., social distancing, use of masks) was limited, particularly in rural areas.\nC_LI\n\nWhat do the new findings imply?O_LIAdditional information campaigns are needed to address knowledge gaps and misperceptions about SARS-CoV-2/COVID-19 in Malawi.\nC_LI", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Tian Gu", - "author_inst": "University of Michigan" - }, - { - "author_name": "Jasmine A. Mack", - "author_inst": "University of Michigan" - }, - { - "author_name": "Maxwell Salvatore", - "author_inst": "University of Michigan" - }, - { - "author_name": "Swaraaj Prabhu Sankar", - "author_inst": "University of Michigan" - }, - { - "author_name": "Thomas S. Valley", - "author_inst": "University of Michigan" + "author_name": "Jethro Banda", + "author_inst": "Malawi Epidemiological and Intervention Research Unit" }, { - "author_name": "Karandeep Singh", - "author_inst": "University of Michigan" + "author_name": "Albert Dube", + "author_inst": "Malawi Epidemiological and Intervention Research Unit" }, { - "author_name": "Brahmajee K. Nallamothu", - "author_inst": "University of Michigan" + "author_name": "Sarah Brumfield", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Sachin Kheterpal", - "author_inst": "University of Michigan" + "author_name": "Abena Amoah", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Lynda Lisabeth", - "author_inst": "University of Michigan" + "author_name": "Amelia Crampin", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Lars G. Fritsche", - "author_inst": "University of Michigan" + "author_name": "Georges Reniers", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Bhramar G. Mukherjee", - "author_inst": "University of Michigan" + "author_name": "St\u00e9phane Helleringer", + "author_inst": "Johns Hopkins University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1383863,23 +1383877,83 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.06.12.20127498", - "rel_title": "Reducing SARS-CoV-2 infectious spreading patterns by removing S and R compartments from SIR model equation", + "rel_doi": "10.1101/2020.06.15.20131680", + "rel_title": "Artificial Intelligence for COVID-19 Risk Classification in Kidney Disease: Can Technology Unmask an Unseen Disease?", "rel_date": "2020-06-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20127498", - "rel_abs": "This research points to the asymptotic instability of SIR model and its variants to predict the behavior of SARS-CoV-2 infection spreading patterns over the population and time aspects. Mainly for the \"S\" and \"R\" terms of the equation, the predictive results fail due to confounding environment of variables that sustain the virus contagion within population complex network basis of analysis. While \"S\" and \"R\" are not homologous data of analysis, thus with improper topological metrics used in many researches, these terms leads to the asymptotic feature of \"I\" term as the most stable point of analysis to achieve proper predictive methods. Having in its basis of formulation the policies adopted by countries, \"I\" therefore presents a stable fixed point orientation in order to be used as a predictive analysis of nearby future patterns of SARS-CoV-2 infection. New metrics using a Weinbull approach for \"I\" are presented and fixed point orientation (sensitivity of the method) are demonstrated empirically by worldwide statistical data.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20131680", + "rel_abs": "BackgroundWe developed two unique machine learning (ML) models that predict risk of: 1) a major COVID-19 outbreak in the service county of a local HD population within following week, and 2) a hemodialysis (HD) patient having an undetected SARS-CoV-2 infection that is identified after following 3 or more days.\n\nMethodsWe used county-level data from United States population (March 2020) and HD patient data from a network of clinics (February-May 2020) to develop two ML models. First was a county-level model that used data from general and HD populations (21 variables); outcome of a COVID-19 outbreak in a dialysis service area was defined as a clinic being located in one of the national counties with the highest growth in COVID-19 positive cases (number and people per million (ppm)) in general population during 22-28 Mar 2020. Second was a patient-level model that used HD patient data (82 variables) to predict an individual having an undetected SARS-CoV-2 infection that is identified in subsequent [≥]3 days.\n\nResultsAmong 1682 counties with dialysis clinics, 82 (4.9%) had a COVID-19 outbreak during 22-28 Mar 2020. Area under the receiver operating characteristic curve (AUROC) for the county-level model was 0.86 in testing dataset. Top predictor of a county experiencing an outbreak was the COVID-19 positive ppm in the general population in the prior week. In a select group (n=11,664) used to build the patient-level model, 28% of patients had COVID-19; prevalence was by design 10% in the testing dataset. AUROC for the patient-level model was 0.71 in the testing dataset. Top predictor of an HD patient having a SARS-CoV-2 infection was mean pre-HD body temperature in the prior week.\n\nConclusionsDeveloped ML models appear suitable for predicting counties at risk of a COVID-19 outbreak and HD patients at risk of having an undetected SARS-CoV-2 infection.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Charles Roberto Telles", - "author_inst": "Secretary of State for Education of Paran" + "author_name": "Caitlin Monaghan", + "author_inst": "Fresenius Medical Care, Global Medical Office" + }, + { + "author_name": "John W Larkin", + "author_inst": "Fresenius Medical Car, Global Medical Office" + }, + { + "author_name": "Sheetal Chaudhuri", + "author_inst": "Fresenius Medical Care, Global Medical Office" + }, + { + "author_name": "Hao Han", + "author_inst": "Fresenius Medical Care, Global Medical Office" + }, + { + "author_name": "Yue Jiao", + "author_inst": "Fresenius Medical Care, Global Medical Office" + }, + { + "author_name": "Kristine Marie Bermudez", + "author_inst": "Fresenius Medical Care North America, Medical Office" + }, + { + "author_name": "Eric D Weinhandl", + "author_inst": "Fresenius Medical Care North America, Medical Office" + }, + { + "author_name": "Ines A Dahne-Steuber", + "author_inst": "Fresenius Medical Care North America, Medical Office" + }, + { + "author_name": "Kathleen Belmonte", + "author_inst": "Fresenius Kidney Care" + }, + { + "author_name": "Luca Neri", + "author_inst": "Fresenius Medical Care Deutschland GmbH, EMEA Medical Office" + }, + { + "author_name": "Peter Kotanko", + "author_inst": "Renal Research Institute" + }, + { + "author_name": "Jeroen P Kooman", + "author_inst": "Maastricht University Medical Center" + }, + { + "author_name": "Jeffrey L Hymes", + "author_inst": "Fresenius Medical Care North America, Medical Office" + }, + { + "author_name": "Robert J Kossmann", + "author_inst": "Fresenius Medical Care North America, Medical Office" + }, + { + "author_name": "Len A Usvyat", + "author_inst": "Fresenius Medical Care, Global Medical Office" + }, + { + "author_name": "Franklin W Maddux", + "author_inst": "Fresenius Medical Care AG & Co. KGaA, Global Medical Office" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "nephrology" }, { "rel_doi": "10.1101/2020.06.15.20131888", @@ -1385605,39 +1385679,35 @@ "category": "systems biology" }, { - "rel_doi": "10.1101/2020.06.17.156679", - "rel_title": "Rapid assessment of ligand binding to the SARS-CoV-2 main protease by saturation transfer difference NMR spectroscopy", - "rel_date": "2020-06-17", + "rel_doi": "10.1101/2020.06.15.152983", + "rel_title": "Virus survival in evaporated saliva microdroplets deposited on inanimate surfaces", + "rel_date": "2020-06-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.17.156679", - "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the etiological cause of the coronavirus disease 2019, for which no effective therapeutics are available. The SARS-CoV-2 main protease (Mpro) is essential for viral replication and constitutes a promising therapeutic target. Many efforts aimed at deriving effective Mpro inhibitors are currently underway, including an international open-science discovery project, codenamed COVID Moonshot. As part of COVID Moonshot, we used saturation transfer difference nuclear magnetic resonance (STD-NMR) spectroscopy to assess the binding of putative Mpro ligands to the viral protease, including molecules identified by crystallographic fragment screening and novel compounds designed as Mpro inhibitors. In this manner, we aimed to complement enzymatic activity assays of Mpro performed by other groups with information on ligand affinity. We have made the Mpro STD-NMR data publicly available. Here, we provide detailed information on the NMR protocols used and challenges faced, thereby placing these data into context. Our goal is to assist the interpretation of Mpro STD-NMR data, thereby accelerating ongoing drug design efforts.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.15.152983", + "rel_abs": "The novel coronavirus respiratory syndrome (COVID-19) has now spread worldwide. The relative contribution of viral transmission via fomites is still unclear. SARS-CoV-2 has been shown to survive on inanimate surfaces for several days, yet the factors that determine its survival on surfaces are not well understood. Here we combine microscopy imaging with virus viability assays to study survival of three bacteriophages suggested as good models for human respiratory pathogens: the enveloped Phi6 (a surrogate for SARS-CoV-2), and the non-enveloped PhiX174 and MS2. We measured virus viability in human saliva microdroplets, SM buffer, and water following deposition on glass surfaces at various relative humidities (RH). Although saliva microdroplets dried out rapidly at all tested RH levels (unlike SM that remained hydrated at RH [≥] 57%), survival of all three viruses in dry saliva microdroplets was significantly higher than in water or SM. Thus, RH and hydration conditions are not sufficient to explain virus survival, indicating that the suspended medium, and association with saliva components in particular, likely affect physicochemical properties that determine virus survival. The observed high virus survival in dry saliva deposited on surfaces, under a wide range of RH levels, can have profound implications for human public health, specifically the COVID-19 pandemic.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Anastassia L. Kantsadi", - "author_inst": "University of Oxford" + "author_name": "Aliza Fedorenko", + "author_inst": "The Hebrew Universtiy of Jerusalem" }, { - "author_name": "Emma Cattermole", - "author_inst": "University of Oxford" - }, - { - "author_name": "Minos-Timotheos Matsoukas", - "author_inst": "University of Patras" + "author_name": "Maor Grinberg", + "author_inst": "The Hebrew Universtiy of Jerusalem" }, { - "author_name": "Georgios A. Spyroulias", - "author_inst": "University of Patras" + "author_name": "Tomer Orevi", + "author_inst": "The Hebrew Universtiy of Jerusalem" }, { - "author_name": "Ioannis Vakonakis", - "author_inst": "University of Oxford" + "author_name": "Nadav Kashtan", + "author_inst": "The Hebrew Universtiy of Jerusalem" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biochemistry" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.06.10.20122465", @@ -1386959,31 +1387029,95 @@ "category": "pathology" }, { - "rel_doi": "10.1101/2020.06.13.20130419", - "rel_title": "Mental health service activity during COVID-19 lockdown: South London and Maudsley data on working age community and home treatment team services and mortality from February to mid-May 2020", + "rel_doi": "10.1101/2020.06.15.20129080", + "rel_title": "What Has Been the Impact of Covid-19 on Safety Culture?", "rel_date": "2020-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.13.20130419", - "rel_abs": "The lockdown and social distancing policy response to the COVID-19 pandemic in the UK has a potentially important impact on provision of mental healthcare; however, there has been relatively little quantification of this. Taking advantage of the Clinical Record Interactive Search (CRIS) data resource with 24-hourly updates of electronic mental health records data, this paper describes daily caseloads and contact numbers (face-to-face and virtual) for home treatment teams (HTTs) and working age adult community mental health teams (CMHTs) from 1st February to 15th May 2020 at the South London and Maudsley NHS Trust (SLaM), a large mental health service provider for 1.2m residents in south London. In addition daily deaths are described for all current and previous SLaM service users over this period and the same dates in 2019. In summary, comparing periods before and after 16th March 2020 the CMHT sector showed relatively stable caseloads and total contact numbers, but a substantial shift from face-to-face to virtual contacts, while HTTs showed the same changeover but reductions in caseloads and total contacts (although potentially an activity rise again during May). Number of deaths for the two months between 16th March and 15th May were 2.4-fold higher in 2020 than 2019, with 958 excess deaths.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20129080", + "rel_abs": "IntroductionCovid-19 has placed an unprecedented demand on healthcare systems worldwide. A positive safety culture is associated with improved patient safety and in turn patient outcomes. To date, no study has evaluated the impact of Covid-19 on safety culture.\n\nMethodsThe Safety Attitudes Questionnaire (SAQ) was used to investigate safety culture at a large UK teaching hospital during Covid-19. Findings were compared with baseline data from 2017. Incident reporting from the year preceding the pandemic was also examined.\n\nResultsSignificant increased were seen in SAQ scores of doctors and other clinical staff, there was no change in the nursing group. During Covid-19, on univariate regression analysis, female gender, age 40-49 years, non-white ethnicity, and nursing job role were all associated with lower SAQ scores. Training and support for redeployment were associated with higher SAQ scores. On multivariate analysis, non-disclosed gender (-0.13), non-disclosed ethnicity (-0.11), nursing role (-0.15), and support (0.29) persisted to significance. A significant decrease (p<0.003) was seen in error reporting after the onset of the Covid-19 pandemic.\n\nDiscussionThis is the first study to report SAQ during Covid-19 and compare with baseline. Differences in SAQ scores were observed during Covid-19 between professional groups and compared to baseline. Reductions in incident reporting were also seen. These changes may reflect perception of risk, changes in volume or nature of work. High-quality support for redeployed staff may be associated with improved safety perception during future pandemics.\n\nWHAT IS ALREADY KNOWN ON THE SUBJECTO_LISafety culture is associated with patient safety and outcomes\nC_LIO_LIThis is the first study to investigate safety culture during the Covid-19 pandemic\nC_LIO_LIThis study uses the Safety Attitudes Questionnaire (SAQ) and Datix incident reporting data to investigate determinants of safety climate during the Covid-19 pandemic.\nC_LIO_LISafety climate is context specific, this study is strengthened by the availability of benchmarking data from before the onset of the Covid-19 pandemic.\nC_LIO_LISignificant differences in SAQ scores between professional groups were observed during Covid-19.\nC_LIO_LIGender, ethnicity and job role were significant determinants of safety attitudes.\nC_LIO_LISupport during redeployment was associated with improved safety attitudes.\nC_LIO_LIThe number of incidents that were reported reduced significantly during Covid-19, although the number of events leading to harm remained constant.\nC_LI", + "rel_num_authors": 19, "rel_authors": [ { - "author_name": "Robert Stewart", - "author_inst": "King's College London" + "author_name": "Max Denning", + "author_inst": "Imperial College London" }, { - "author_name": "Evangelia Martin", - "author_inst": "King's College London" + "author_name": "Ee Teng Goh", + "author_inst": "Imperial College London" }, { - "author_name": "Matthew Broadbent", - "author_inst": "South London and Maudsley NHS Foundation Trust" + "author_name": "Alasdair Scott", + "author_inst": "Imperial College London" + }, + { + "author_name": "Guy Martin", + "author_inst": "Imperial College London" + }, + { + "author_name": "Sheraz Markar", + "author_inst": "Imperial College London" + }, + { + "author_name": "Kelsey Flott", + "author_inst": "Imperial College London" + }, + { + "author_name": "Sam Mason", + "author_inst": "Imperial College London" + }, + { + "author_name": "Jan Przybylowicz", + "author_inst": "Imperial College London" + }, + { + "author_name": "Melanie Almonte", + "author_inst": "Imperial College London" + }, + { + "author_name": "Jonathan Clarke", + "author_inst": "Imperial College London" + }, + { + "author_name": "Jasmine Winter-Beatty", + "author_inst": "Imperial College London" + }, + { + "author_name": "Swathikan Chidambaram", + "author_inst": "Oxford University Hospitals NHS Foundation Trust" + }, + { + "author_name": "Seema Yalamanchili", + "author_inst": "Imperial College London" + }, + { + "author_name": "Benjamin Tan", + "author_inst": "Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore" + }, + { + "author_name": "Abhiram Kanneganti", + "author_inst": "Department of Obstetrics & Gynaecology, National University Hospital (NUH), Singapore" + }, + { + "author_name": "Viknesh Sounderajah", + "author_inst": "Imperial College London" + }, + { + "author_name": "Mary Wells", + "author_inst": "Imperial College London" + }, + { + "author_name": "Sanjay Purkayastha", + "author_inst": "Imperial College London" + }, + { + "author_name": "James Kinross", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2020.06.14.20130815", @@ -1388297,21 +1388431,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.15.20130989", - "rel_title": "Predictive accuracy of a hierarchical logistic model of cumulative SARS-CoV-2 case growth", + "rel_doi": "10.1101/2020.06.12.20127944", + "rel_title": "Evaluation of SARS-CoV-2 in Breastmilk from 18 Infected Women", "rel_date": "2020-06-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.15.20130989", - "rel_abs": "BackgroundInfectious disease predictions models, including virtually all epidemiological models describing the spread of the SARS-CoV-2 pandemic up to June 2020, are rarely evaluated. The aim of the present study was to investigate the predictive accuracy of a prognostic model for forecasting the development of the cumulative number of reported SARS-CoV-2 cases in countries and administrative regions worldwide.\n\nMethodsThe cumulative number of reported SARS-CoV-2 cases was forecasted in 251 regions with a horizon of two weeks, one month, and two months using a previously described hierarchical logistic model at the end of March 2020. Forecasts were compared to actual observations by using a series of evaluation metrics.\n\nResultsOn average, predictive accuracy was very high in nearly all regions at the two weeks forecast, high in most regions at the one month forecast, and notable in the majority of the regions at the two months forecast. Higher accuracy was associated with the availability of more data for estimation and with a more pronounced cumulative case growth from the first case to the date of estimation. In some strongly affected regions, cumulative case counts were considerably underestimated.\n\nConclusionsWith keeping its limitations in mind, the investigated model can be used for the preparation and distribution of resources during the SARS-CoV-2 pandemic. Future research should primarily address the models assumptions and its scope of applicability. In addition, establishing a relationship with known mechanisms and traditional epidemiological models of disease transmission would be desirable.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20127944", + "rel_abs": "To The EditorCurrently, the U.S. Centers for Disease Control and Prevention, American Academy of Pediatrics and the World Health Organization advise that women who are infected with SARS-CoV-2 may choose to breastfeed with appropriate protections to prevent transmission of the virus through respiratory droplets.(1) However, the potential for exposure to SARS-CoV-2 through breastfeeding is currently unknown. To date, case reports on breastmilk samples from a total of 24 SARS-CoV-2-infected women have been published.(2-7) Of those, viral RNA was detected in ten breastmilk samples from four women. In some but not all cases, environmental contamination as the source of the virus or retrograde flow from an infected infant could not be ruled out.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Levente Kriston", - "author_inst": "University Medical Center Hamburg-Eppendorf" + "author_name": "Christina D Chambers", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Paul Krogstad", + "author_inst": "University of California, Los Angeles" + }, + { + "author_name": "Kerri Bertrand", + "author_inst": "University of California, San Diego" + }, + { + "author_name": "Deisy Contreras", + "author_inst": "University of California, Los Angeles" + }, + { + "author_name": "Lars Bode", + "author_inst": "University of California, San Diego" + }, + { + "author_name": "Nicole Tobin", + "author_inst": "University of California, Los Angeles" + }, + { + "author_name": "Grace Aldrovandi", + "author_inst": "University of California, Los Angeles" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1390059,31 +1390217,87 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.06.16.155267", - "rel_title": "Transcriptogram analysis reveals relationship between viral titer and gene sets responses during Corona-virus infection.", + "rel_doi": "10.1101/2020.06.16.154765", + "rel_title": "Machine Learning Models Identify Inhibitors of SARS-CoV-2", "rel_date": "2020-06-16", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.16.155267", - "rel_abs": "To understand the difference between benign and severe outcomes after Coronavirus infection, we urgently need ways to clarify and quantify the time course of tissue and immune responses. Here we re-analyze 72-hour time-series microarrays generated in 2013 by Sims and collaborators for SARS-CoV-1 in vitro infection of a human lung epithelial cell line. Transcriptograms, a Bioinformatics tool to analyze genome-wide gene expression data, allow us to define an appropriate context-dependent threshold for mechanistic relevance of gene differential expression. Without knowing in advance which genes are relevant, classical analyses detect every gene with statistically-significant differential expression, leaving us with too many genes and hypotheses to be useful. Using a Transcriptogram-based top-down approach, we identified three major, differentially-expressed gene sets comprising 219 mainly immune-response-related genes. We identified timescales for alterations in mitochondrial activity, signaling and transcription regulation of the innate and adaptive immune systems and their relationship to viral titer. At the individual-gene level, EGR3 was significantly upregulated in infected cells. Similar activation in T-cells and fibroblasts in infected lung could explain the T-cell anergy and eventual fibrosis seen in SARS-CoV-1 infection. The methods can be applied to RNA data sets for SARS-CoV-2 to investigate the origin of differential responses in different tissue types, or due to immune or preexisting conditions or to compare cell culture, organoid culture, animal models, and human-derived samples.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.16.154765", + "rel_abs": "With the ongoing SARS-CoV-2 pandemic there is an urgent need for the discovery of a treatment for the coronavirus disease (COVID-19). Drug repurposing is one of the most rapid strategies for addressing this need and numerous compounds have been selected for in vitro testing by several groups already. These have led to a growing database of molecules with in vitro activity against the virus. Machine learning models can assist drug discovery through prediction of the best compounds based on previously published data. Herein we have implemented several machine learning methods to develop predictive models from recent SARS-CoV-2 in vitro inhibition data and used them to prioritize additional FDA approved compounds for in vitro testing selected from our in-house compound library. From the compounds predicted with a Bayesian machine learning model, CPI1062 and CPI1155 showed antiviral activity in HeLa-ACE2 cell-based assays and represent potential repurposing opportunities for COVID-19. This approach can be greatly expanded to exhaustively virtually screen available molecules with predicted activity against this virus as well as a prioritization tool for SARS-CoV-2 antiviral drug discovery programs. The very latest model for SARS-CoV-2 is available at www.assaycentral.org.Competing Interest StatementSE is CEO and owner of Collaborations Pharmaceuticals, Inc. DHF, KMZ, TRL, AP are employees of Collaborations Pharmaceuticals, Inc.View Full Text", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Rita M.C. de Almeida", - "author_inst": "Universidade Federal do Rio Grande do Sul" + "author_name": "Victor O Gawriljuk", + "author_inst": "University of Sao Paulo" }, { - "author_name": "Gilberto L Thomas", - "author_inst": "Universidade Federal do Rio Grande do Sul" + "author_name": "Phyo Phyo Kyaw Zin", + "author_inst": "Collaborations Pharmaceuticals, Inc." }, { - "author_name": "James A. Glazier", - "author_inst": "Indiana University" + "author_name": "Daniel H Foil", + "author_inst": "Collaborations Pharmaceuticals, Inc." + }, + { + "author_name": "Jean Bernatchez", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Sungjun Beck", + "author_inst": "University of California, San Diego" + }, + { + "author_name": "Nathan Beutler", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "James Ricketts", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Linlin Yang", + "author_inst": "The Scripps Research Institute" + }, + { + "author_name": "Thomas Rogers", + "author_inst": "Scripps Research" + }, + { + "author_name": "Ana C Puhl", + "author_inst": "Collaborations Pharmaceuticals, Inc." + }, + { + "author_name": "Kimberley M Zorn", + "author_inst": "Collaborations Pharmaceuticals, Inc." + }, + { + "author_name": "Thomas R Lane", + "author_inst": "Collaborations Pharmaceuticals Inc." + }, + { + "author_name": "Andre S Godoy", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Glaucius Olivia", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Jair L Siqueira-Neto", + "author_inst": "University of California San Diego" + }, + { + "author_name": "Peter Madrid", + "author_inst": "SRI International" + }, + { + "author_name": "Sean Ekins", + "author_inst": "Collaborations Pharmaceuticals, Inc." } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2020.06.14.151290", @@ -1391793,27 +1392007,63 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.12.20129114", - "rel_title": "How to better communicate exponential growth of infectious diseases", + "rel_doi": "10.1101/2020.06.14.149153", + "rel_title": "X-206 is a potent and selective inhibitor of SARS-CoV-2 infection in vitro", "rel_date": "2020-06-14", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.12.20129114", - "rel_abs": "Exponential growth bias is the phenomenon that humans underestimate exponential growth. In the context of infectious diseases, this bias may lead to failure to understand the effectiveness of non-pharmaceutical interventions (NPIs). Communicating the same scenario in different ways (framing) has been found to have a large impact on peoples evaluations and behavior in the contexts of social behavior, risk taking and health care. We find that framing matters for peoples assessment of the benefits of NPIs. In two commonly used frames, most subjects in our experiment drastically underestimate the number of cases NPIs avoid. Framing growth in terms of doubling times, rather than growth rates, reduces bias. When the scenario is framed in terms of time gained, rather than cases avoided, the median subject assesses the benefit of NPIs correctly. These findings suggest changes that public health authorities can adopt to better communicate the exponential spread of infectious diseases.", - "rel_num_authors": 2, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.14.149153", + "rel_abs": "Pandemic spread of emerging human pathogenic viruses such as the current SARS-CoV-2, poses both an immediate and future challenge to human health and society. Currently, effective treatment of infection with SARS-CoV-2 is limited and broad spectrum antiviral therapies to meet other emerging pandemics are absent leaving the World population largely unprotected. Here, we have identified distinct members of the family of polyether ionophore antibiotics with potent ability to inhibit SARS-CoV-2 replication and cytopathogenicity in cells. Several compounds from this class displayed more than 100-fold selectivity between viral-induced cytopathogenicity and inhibition of cell viability, however the compound X-206 displayed >500-fold selectivity and was furthermore able to inhibit viral replication even at sub-nM levels. The antiviral mechanism of the polyether ionophores is currently not understood in detail. We demonstrate, through unbiased bioactivity profiling, that their effects on the host cells differ from those of cationic amphiphiles such as hydroxychloroquine. Collectively, our data suggest that polyether ionophore antibiotics should be subject to further investigations as potential broad-spectrum antiviral agents.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Martin Schonger", - "author_inst": "ETH Zurich and HSLU" + "author_name": "Esben B. Svenningsen", + "author_inst": "Aarhus University" + }, + { + "author_name": "Jacob T Jensen", + "author_inst": "Aarhus University" + }, + { + "author_name": "Julia Blay-Cadanet", + "author_inst": "Aarhus University" + }, + { + "author_name": "Han Liu", + "author_inst": "Aarhus University" + }, + { + "author_name": "Shaoquan Lin", + "author_inst": "Aarhus University" + }, + { + "author_name": "Jaime M Villameriel", + "author_inst": "Aarhus University" + }, + { + "author_name": "David Olagnier", + "author_inst": "Aarhus University" + }, + { + "author_name": "Manja Idorn", + "author_inst": "Aarhus University" + }, + { + "author_name": "Soren R. Paludan", + "author_inst": "Aarhus University" + }, + { + "author_name": "Christian K Holm", + "author_inst": "Aarhus University" }, { - "author_name": "Daniela Sele", - "author_inst": "ETH-Bereich Hochschulen" + "author_name": "Thomas B Poulsen", + "author_inst": "Aarhus University" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "type": "new results", + "category": "pharmacology and toxicology" }, { "rel_doi": "10.1101/2020.06.13.149690", @@ -1393379,51 +1393629,35 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.06.13.149880", - "rel_title": "Multi-epitope Based Peptide Vaccine Design Using Three Structural Proteins (S, E, and M) of SARS-CoV-2: An In Silico Approach", + "rel_doi": "10.1101/2020.06.11.146878", + "rel_title": "Colon Cancer and SARS-CoV-2: Impact of ACE2 Expression in Susceptibility to COVID-19", "rel_date": "2020-06-13", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.13.149880", - "rel_abs": "Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is the novel coronavirus responsible for the ongoing pandemic of coronavirus disease (COVID-19). No sustainable treatment option is available so far to tackle such a public health threat. Therefore, designing a suitable vaccine to overcome this hurdle asks for immediate attention. In this study, we targeted for a design of multi-epitope based vaccine using immunoinformatics tools. We considered the structural proteins S, E and, M of SARS-CoV-2, since they facilitate the infection of the virus into host cell and using different bioinformatics tools and servers, we predicted multiple B-cell and T-cell epitopes having potential for the required vaccine design. Phylogenetic analysis provided insight on ancestral molecular changes and molecular evolutionary relationship of S, E, and M proteins. Based on the antigenicity and surface accessibility of these proteins, eight epitopes were selected by various B cell and T cell epitope prediction tools. Molecular docking was executed to interpret the binding interactions of these epitopes and three potential epitopes WTAGAAAYY, YVYSRVKNL, and GTITVEELK were selected for their noticeable higher binding affinity scores -9.1, -7.4, and -7.0 kcal/mol, respectively. Targeted epitopes had 91.09% population coverage worldwide. In summary, we identified three epitopes having the most significant properties of designing the peptide-based vaccine against SARS-CoV-2.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.11.146878", + "rel_abs": "Novel coronavirus disease (COVID-19) pandemic has become a global health emergency. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) interacts with angiotensin-converting enzyme 2 (ACE2) to enter the cells and infects diverse human tissues. It has been reported that a few conditions, including cancer, predispose individuals to SARS-CoV-2 infection and severe form of COVID-19. These findings led us to evaluate the susceptibility of colon adenocarcinoma (COAD) patients to SARS-CoV-2 infection by investigation of ACE2 expression in their tumor tissues. The expression analysis revealed that both mRNA and protein levels of ACE2 had increased in colon cancer samples than normal group. Next, the prognosis analysis has indicated that the upregulation of ACE2 was not correlated with patient survival outcomes. Further assessment displayed the hypomethylation of the ACE2 gene promoter in COAD patients. Surprisingly, this methylation status has a strong negative correlation with ACE2 gene expression. The functional enrichment analysis of the genes that had similar expression patterns with ACE2 in colon cancer tissues demonstrated that they mainly enriched in Vitamin digestion and absorption, Sulfur relay system, and Fat digestion and absorption pathways. Finally, we found that ACE2 gene expression had a significant association with the immune cell infiltration levels in COAD patients. In conclusion, it has plausible that COAD patients are more likely to be infected with SARS-CoV-2 and experience severe injuries. Moreover, COVID-19 would bring unfavorable survival outcomes of patients with colon cancer by the way of immune cell infiltration linked process. The present study highlights the importance of preventive actions for COAD patients during the COVID-19 pandemic.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Arpita Singha Roy", - "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University" - }, - { - "author_name": "Mahafujul Islam Quadery Tonmoy", - "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University" - }, - { - "author_name": "Atqiya Fariha", - "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University" - }, - { - "author_name": "Ithmam Hami", - "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University" - }, - { - "author_name": "Ibrahim Khalil Afif", - "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University" + "author_name": "Mohsen Ahmadi", + "author_inst": "Booali medical diagnostic laboratory" }, { - "author_name": "Md Adnan Munim", - "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University" + "author_name": "Negin Saffarzadeh", + "author_inst": "Department of Medical Genetics, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran" }, { - "author_name": "Mohammad Rahanur Alam", - "author_inst": "Department of Food Technology and Nutrition Science, Noakhali Science and Technology University" + "author_name": "Mohammad Amin Habibi", + "author_inst": "Student Research Committee, Qom University of Medical Sciences, Qom, Iran" }, { - "author_name": "Md. Shahadat Hossain", - "author_inst": "Department of Biotechnology and Genetic Engineering, Noakhali Science and Technology University" + "author_name": "Fatemeh Hajiesmaeili", + "author_inst": "Booali medical diagnostic laboratory" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "bioinformatics" + "category": "genetics" }, { "rel_doi": "10.1101/2020.06.13.149039", @@ -1394689,35 +1394923,67 @@ "category": "emergency medicine" }, { - "rel_doi": "10.1101/2020.06.08.20123786", - "rel_title": "Oscillations in USA COVID-19 Incidence and Mortality Data reflect societal factors", + "rel_doi": "10.1101/2020.06.09.20124008", + "rel_title": "An imperfect tool: COVID-19 'test & trace' success relies on minimising the impact of false negatives and continuation of physical distancing.", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20123786", - "rel_abs": "The COVID-19 pandemic currently in process differs from other infectious disease calamities that have previously plagued humanity in the vast amount of information that is produces each day, which includes daily estimates of the disease incidence and mortality data. Apart from providing actionable information to public health authorities on the trend of the pandemic, the daily incidence reflects the process of disease in a susceptible population and thus reflects the pathogenesis of COVID-19, the public health response and diagnosis and reporting. Both daily new cases and daily mortality data in the US exhibit periodic oscillatory patterns. By analyzing NYC and LA testing data, we demonstrate that this oscillation in the number of cases can be strongly explained by the daily variation in testing. This seems to rule out alternative hypotheses such as increased infections on certain days of the week as driving this oscillation. Similarly, we show that the apparent oscillation in mortality in the US data is mostly an artifact of reporting, which disappears in datasets that record death by episode date, such as the NYC and LA datasets. Periodic oscillations in COVID-19 incidence and mortality data reflect testing and reporting practices and contingencies. Thus, these contingencies should be considered first prior to suggesting social or biological mechanisms.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20124008", + "rel_abs": "Emerging evidence suggests that contact tracing has had limited success in the UK in reducing the R number across the COVID-19 pandemic. We investigate potential pitfalls and areas for improvement by extending an existing branching process contact tracing model, adding diagnostic testing and refining parameter estimates. Our results demonstrate that reporting and adherence are the most important predictors of programme impact but tracing coverage and speed plus diagnostic sensitivity also play an important role. We conclude that well-implemented contact tracing could bring small but potentially important benefits to controlling and preventing outbreaks, providing up to a 15% reduction in R, and reaffirm that contact tracing is not currently appropriate as the sole control measure.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Aviv Bergman", - "author_inst": "Albert Einstein College of Medicine" + "author_name": "Emma L Davis", + "author_inst": "University of Oxford" }, { - "author_name": "Yehonatan Sella", - "author_inst": "Albert Einstein College of Medicine" + "author_name": "Tim C D Lucas", + "author_inst": "University of Oxford" }, { - "author_name": "Peter Agre", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Anna Borlase", + "author_inst": "University of Oxford" }, { - "author_name": "Arturo Casadevall", - "author_inst": "Johns Hopkins School of Public Health" + "author_name": "Timothy M Pollington", + "author_inst": "University of Warwick" + }, + { + "author_name": "Sam Abbott", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Diepreye Ayabina", + "author_inst": "University of Oxford" + }, + { + "author_name": "Thomas Crellen", + "author_inst": "University of Oxford" + }, + { + "author_name": "Joel Hellewell", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Li Pi", + "author_inst": "University of Oxford" + }, + { + "author_name": "Graham F Medley", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "T D\u00e9irdre Hollingsworth", + "author_inst": "University of Oxford" + }, + { + "author_name": "Petra Klepac", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.06.10.20123281", @@ -1396135,53 +1396401,73 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.06.10.20127613", - "rel_title": "On the interplay between mobility and hospitalization capacity during the COVID-19 pandemic: The SEIRHUD model", + "rel_doi": "10.1101/2020.06.10.20127563", + "rel_title": "Multimorbidity, Polypharmacy, and COVID-19 infection within the UK Biobank cohort.", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127613", - "rel_abs": "Measures to reduce the impact of the COVID-19 pandemic require a mix of logistic, political and social capacity. Depending on the country, different approaches to increase hospitalization capacity or to properly apply lock-downs are observed. In order to better understand the impact of these measures we have developed a compartmental model which, on the one hand allows to calibrate the reduction of movement of people within and among different areas, and on the other hand it incorporates a hospitalization dynamics that differentiates the available kinds of treatment that infected people can receive. By bounding the hospitalization capacity, we are able to study in detail the interplay between mobility and hospitalization capacity.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.10.20127563", + "rel_abs": "BACKGROUNDIt is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity ([≥]2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors.\n\nMETHODS AND FINDINGSWe studied data from UK Biobank (428,199 participants; aged 37-73; recruited 2006-2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96-1.30)), whereas those with [≥]2 LTCs had 48% higher risk; RR 1.48 (1.28-1.71). Compared with no cardiometabolic LTCs, having 1 and [≥]2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12-1.46) and 1.77 (1.46-2.15), respectively. Polypharmacy was associated with a dose response increased risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI [≥]40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09-3.78); 2.79 (2.00-3.90); 2.66 (1.88-3.76); 2.13 (1.46-3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population.\n\nCONCLUSIONSIncreasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19.\n\nAuthor summaryO_ST_ABSWhy was this study done?C_ST_ABSO_LIMultimorbidity is a growing global challenge, but thus far LTC prognostic factors for severe COVID-19 primarily involve single conditions and there is a lack of data on the influence of multimorbidity on the risk of COVID-19.\nC_LIO_LIAs countries move from the lockdown phase of COVID-19, clinicians need more information about risk stratification to appropriately advise patients with multimorbidity about risk prevention steps.\nC_LI\n\nWhat did the researchers do and find?O_LIParticipants with multimorbidity ([≥]2 LTCs) had a 48% higher risk of a positive COVID-19 test, those with cardiometabolic multimorbidity had a 77% higher risk, than those without that type of multimorbidity.\nC_LIO_LIThose from non-white ethnicities with multimorbidity had nearly three times the risk of having COVID-19 infection compared to those of white ethnicity\nC_LIO_LIPeople with multimorbidity with the highest risk of COVID-19 infection were the most socioeconomically deprived, those with BMI [≥]40 kg/m2, and those with reduced renal function.\nC_LI\n\nWhat do these findings mean?O_LIIndividuals with [≥]2 LTCs, especially if these are cardiometabolic in nature, should be particularly stringent in adhering to preventive measures, such as physical distancing and hand hygiene.\nC_LIO_LIOur findings have implications for clinicians, occupational health and employers when considering work-place environments, appropriate advice for patients, and adaptations that might be required to protect such staff, identified here, as higher risk.\nC_LI", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Tomas Veloz", - "author_inst": "Fundacion para el Desarrollo Interdisciplinario de la Ciencia la Tecnologia y la Artes" + "author_name": "Ross McQueenie", + "author_inst": "University of Glasgow, Instutute of Health and Wellbeing" }, { - "author_name": "pedro maldonado", - "author_inst": "fundacion para el desarrollo interdisciplinario de la ciencia la tecnologia y las artes" + "author_name": "Hamish Foster", + "author_inst": "University of Glasgow, Instutute of Health and Wellbeing" }, { - "author_name": "samuel ropert", - "author_inst": "fundacion para el desarrollo interdisciplinario de la ciencia la tecnologia y las artes" + "author_name": "Bhautesh D Jani", + "author_inst": "University of Glasgow, Institute of Health and Wellbeing" }, { - "author_name": "cesar ravello", - "author_inst": "Fundacion Ciencia y vida" + "author_name": "Srinivasa Vittal Katikireddi", + "author_inst": "University of Glasgow, Institute of Health and Wellbeing" }, { - "author_name": "alejandra barrios", - "author_inst": "fundacion ciencia y vida" + "author_name": "Naveed Sattar", + "author_inst": "University of Glasgow, Institute of Cardiovascular and Medical Sciences" }, { - "author_name": "soraya mora", - "author_inst": "Fundacion Ciencia y vida" + "author_name": "Jill P Pell", + "author_inst": "University of Glasgow, Institute of Health and Wellbeing" }, { - "author_name": "Cesar Valdenegro", - "author_inst": "Fundacion Ciencia y Vida" + "author_name": "Frederick K Ho", + "author_inst": "University of Glasgow, Institute of Health and Wellbeing" }, { - "author_name": "Tomas Villaseca", - "author_inst": "Fundacion Ciencia y Vida" + "author_name": "Claire L Niedzwiedz", + "author_inst": "University of Glasgow, Institute of Health and Wellbeing" }, { - "author_name": "Tomas Perez-Acle", - "author_inst": "Fundacion Ciencia y Vida" + "author_name": "Claire E Hastie", + "author_inst": "University of Glasgow, Institute of Health and Wellbeing" + }, + { + "author_name": "Jana Anderson", + "author_inst": "University of Glasgow, Institute of Health and Wellbeing" + }, + { + "author_name": "Patrick B Mark", + "author_inst": "University of Glasgow, Institute of Cardiovascular and Medical Sciences" + }, + { + "author_name": "Michael Sullivan", + "author_inst": "University of Glasgow, Institute of Cardiovascular and Medical Sciences" + }, + { + "author_name": "Frances S Mair", + "author_inst": "University of Glasgow, Institute of Health and Wellbeing" + }, + { + "author_name": "Barbara I Nicholl", + "author_inst": "University of Glasgow, Institute of Health and Wellbeing" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1397541,101 +1397827,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.11.20128900", - "rel_title": "Associations between wearing masks, washing hands, and social distancing practices, and risk of COVID-19 infection in public: a cohort-based case-control study in Thailand", + "rel_doi": "10.1101/2020.06.11.20128926", + "rel_title": "Comorbidity and Sociodemographic determinants in COVID-19 Mortality in an US Urban Healthcare System", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128900", - "rel_abs": "We evaluated the effectiveness of personal protective measures, including mask-wearing, handwashing, and social distancing, against COVID-19 infection among contacts of cases. We conducted a case-control study with 211 cases and 839 non-matched controls using all contact tracing records of Thailands national Surveillance and Rapid Response Team. Cases were asymptomatic contacts of COVID-19 patients identified between 1 and 31 March 2020 who were diagnosed with COVID-19 by 21 April 2020; controls were asymptomatic contacts who were not diagnosed with COVID-19. Participants were queried about practices during contact periods with a case. Adjusted odds ratios (aOR) and 95% confidence intervals (CI) were estimated for associations between diagnosis of COVID-19 and covariates using multivariable logistic regression models. Wearing masks all the time during contact was independently associated with lower risk of COVID-19 infection compared to not wearing masks (aOR 0.23, 95% CI 0.09- 0.60), while sometimes wearing masks during contact was not (aOR 0.87, 95% CI 0.41-1.84). Maintaining at least 1 meter distance from a COVID patient (aOR 0.15, 95% CI 0.04-0.63), duration of close contact [≤]15 minutes versus longer (aOR 0.24, 95% CI 0.07-0.90), and handwashing often (aOR 0.34, 95% CI 0.13-0.87) were significantly associated with lower risk of infection. Type of mask was not independently associated with infection. Those who wore masks all the time also were more likely to practice social distancing. Our findings suggest consistent wearing of masks, handwashing, and social distancing in public to protect against COVID-19 infection.", - "rel_num_authors": 21, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128926", + "rel_abs": "BackgroundNew York City is the US epicenter of the coronavirus disease 2019 (COVID-19) pandemic. Early international data indicated that comorbidity contributes significantly to poor prognosis and fatality in patients infected with SARS-CoV-2. It is not known to what degree medical comorbidity and sociodemographic determinants impact COVID-19 mortality in the US.\n\nMethodsEvaluation of de-identified electronic health records of 7,592 COVID-19 patients confirmed by SARS-CoV-2 lab tests in New York City. Medical comorbidites and outcome of mortality, and other covariates, including clinical, sociodemographic, and medication measures were assessed by bivariate and multivariate logistic regression models.\n\nResultsOf common comorbid conditions (hypertension, chronic kidney disease, chronic obstructive pulmonary disease, asthma, obesity, diabetes, HIV, cancer), when adjusted for covariates, chronic kidney disease remained significantly associated with increased odds of mortality. Patients who had more than one comorbidities, former smokers, treated with Azithromycin without Hydroxychloroquine, reside within the boroughs of Brooklyn and Queens Higher had higher odds of death.\n\nConclusionsIncreasing numbers of comorbid factors increase COVID-19 mortality, but several clinical and sociodemographic factors can mitigate risk. Continued evaluation of COVID-19 in large diverse populations is important to characterize individuals at risk and improve clinical outcomes.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Pawinee Doung-ngern", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Rapeepong Suphanchaimat", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Apinya Panjagampatthana", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Chaiwisar Janekrongtham", - "author_inst": "Panjagampatthana" - }, - { - "author_name": "Duangrat Ruampoom", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Nawaporn Daochaeng", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Napatchakorn Eungkanit", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Nichakul Pisitpayat", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Nuengruethai Srisong", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Oiythip Yasopa", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Patchanee Plernprom", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Pitiphon Promduangsi", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Panita Kumphon", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Paphanij Suangtho", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Peeriya Watakulsin", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Sarinya Chaiya", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Somkid Kripattanapong", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Thanawadee Chantian", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." - }, - { - "author_name": "Emily Bloss", - "author_inst": "Thailand Ministry of Public Health - U.S. Centers for Disease Control and Prevention Collaboration" + "author_name": "AN-LI WANG", + "author_inst": "ICAHN SCHOOL OF MEDICINE AT Mount Sinai" }, { - "author_name": "Chawetsan Namwat", - "author_inst": "Department of Disease Control, Ministry of Public Health, Tiwanon Road, Nonthaburi, 11000, Thailand." + "author_name": "Xiaobo Zhong", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Direk Limmathurotsakul", - "author_inst": "Mahidol-Oxford Tropical Medicine Research Unit" + "author_name": "Yasmin Hurd", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1398915,17 +1399129,61 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.11.20128801", - "rel_title": "Early epidemic spread, percolation and Covid-19", + "rel_doi": "10.1101/2020.06.11.20128777", + "rel_title": "An international assessment of the COVID-19 pandemic using ensemble data assimilation", "rel_date": "2020-06-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128801", - "rel_abs": "Human to human transmissible infectious diseases spread in a population using human interactions as its transmission vector. The early stages of such an outbreak can be modeled by a graph whose edges encode these interactions between individuals, the vertices. This article attempts to account for the case when each individual entails in different kinds of interactions which have therefore different probabilities of transmitting the disease. The majority of these results can be also stated in the language of percolation theory.\n\nThe main contributions of the article are: (1) Extend to this setting some results which were previously known in the case when each individual has only one kind of interactions. (2) Find an explicit formula for the basic reproduction number R0 which depends only on the probabilities of transmitting the disease along the different edges and the first two moments of the degree distributions of the associated graphs. (3) Motivated by the recent Covid-19 pandemic, we use the framework developed to compute the R0 of a model disease spreading in populations whose trees and degree distributions are adjusted to several different countries. In this setting, we shall also compute the probability that the outbreak will not lead to an epidemic. In all cases we find such probability to be very low if no interventions are put in place.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.11.20128777", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWThis work shows how one can use iterative ensemble smoothers to effectively estimate parameters of an SEIR model with age-classes and compartments of sick, hospitalized, and dead. The data conditioned on are the daily numbers of accumulated deaths and the number of hospitalized. Also, it is possible to condition on the number of cases obtained from testing. We start from a wide prior distribution for the model parameters; then, the ensemble conditioning leads to a posterior ensemble of estimated parameters leading to model predictions in close agreement with the observations. The updated ensemble of model simulations have predictive capabilities and include uncertainty estimates. In particular, we estimate the effective reproductive number as a function of time, and we can assess the impact of different intervention measures. By starting from the updated set of model parameters, we can make accurate short-term predictions of the epidemic development given knowledge of the future effective reproductive number. Also, the model system allows for the computation of long-term scenarios of the epidemic under different assumptions. We have applied the model system on data sets from several countries with vastly different developments of the epidemic, and we can accurately model the development of the COVID-19 outbreak in these countries. We realize that more complex models, e.g., with regional compartments, may be desirable, and we suggest that the approach used here should be applicable also for these models.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Goncalo Oliveira", - "author_inst": "Universidade Federal Fluminense" + "author_name": "Geir Evensen", + "author_inst": "NORCE" + }, + { + "author_name": "Javier Amezcua", + "author_inst": "University of Reading" + }, + { + "author_name": "Marc Bocquet", + "author_inst": "CEREA, joint laboratory Ecole des Ponts ParisTech and EDF R&D Ecole des Ponts ParisTech, France" + }, + { + "author_name": "Alberto Carrassi", + "author_inst": "University of Reading, Reading, UK" + }, + { + "author_name": "Alban Farchi", + "author_inst": "CEREA, joint laboratory Ecole des Ponts ParisTech and EDF R&D Ecole des Ponts ParisTech, France" + }, + { + "author_name": "Alison Fowler", + "author_inst": "University of Reading, Reading, UK" + }, + { + "author_name": "Peter Houtekamer", + "author_inst": "Environment and Climate Change Canada, Dorval, Quebec, Canada" + }, + { + "author_name": "Christopher K. R. T. Jones", + "author_inst": "University of North Carolina, NC, United States" + }, + { + "author_name": "Rafael de Moraes", + "author_inst": "Delft University of Technology, Delft, Netherlands" + }, + { + "author_name": "Manuel Pulido", + "author_inst": "FaCENA, UNNE and IMIT, CONICET, Corrientes, Argentina" + }, + { + "author_name": "Christian Sampson", + "author_inst": "University of North Carolina, NC, United States" + }, + { + "author_name": "Femke Vossepoel", + "author_inst": "Delft University of Technology, Delft, Netherlands" } ], "version": "1", @@ -1401025,55 +1401283,43 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.09.20127050", - "rel_title": "Plasma from recovered COVID19 subjects inhibits spike protein binding to ACE2 in a microsphere-based inhibition assay", + "rel_doi": "10.1101/2020.06.09.20126508", + "rel_title": "A Novel Approach to Monitoring the COVID-19 Pandemic using Emergency Department Discharge Diagnoses", "rel_date": "2020-06-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20127050", - "rel_abs": "High throughput serological tests that can establish the presence and functional activity of anti-SARS-COV2 antibodies are urgently needed. Here we present microsphere-based Flow Cytometry assays that quantify both anti-spike IgGs in plasma, and the ability of plasma to inhibit the binding of spike protein to angiotensin converting enzyme 2 (ACE2). First, we detected anti-spike-trimer IgGs in 22/24 and anti-spike-receptor-binding-domain (RBD) IgGs in 21/24 COVID+ subjects at a median of 36 (range 14-73) days following documented SARS-CoV-2 RNA (+) secretions. Next, we find that plasma from all 22/24 subjects with anti-trimer IgGs inhibited ACE2-trimer binding to a greater degree than controls, and that the degree of inhibition correlated with anti-trimer IgG levels. Depletion of trimer-reactive Igs from plasma reduced ACE2-trimer inhibitory capacity to a greater degree than depletion of RBD-reactive Igs, suggesting that inhibitory antibodies act by binding both within and outside of the RBD. Amongst the 24 subjects, presence of fever was associated with higher levels of anti-trimer IgG and inhibition of binding to human ACE2. This inhibition assay may be broadly useful to quantify the functional antibody response of recovered COVID19 patients or vaccine recipients in a cell-free assay system.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20126508", + "rel_abs": "IntroductionTracking the COVID-19 pandemic using existing metrics such as confirmed cases and deaths are insufficient for understanding the trajectory of the pandemic and identifying the next wave of cases. In this study, we demonstrate the utility of monitoring the daily number of patients with COVID-like illness (CLI) who present to the Emergency Department (ED) as a tool that can guide local response efforts.\n\nMethodsUsing data from two hospitals in King County, WA, we examined the daily volume of CLI visits, and compare them to confirmed COVID cases and COVID deaths in the County. A linear regression model with varying lags is used to predict the number of daily COVID deaths from the number of CLI visits.\n\nResultsCLI visits appear to rise and peak well in advance of both confirmed COVID cases and deaths in King County. Our regression analysis to predict daily deaths with a lagged count of CLI visits in the ED showed that the R2 value was maximized at 14 days.\n\nConclusionsED CLI visits are a leading indicator of the pandemic. Adopting and scaling up a CLI monitoring approach at the local level will provide needed actionable evidence to policy makers and health officials struggling to confront this health challenge.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Edward P Gniffke", - "author_inst": "Seattle Childrens Research Institute" - }, - { - "author_name": "Whitney E Harrington", - "author_inst": "Seattle Childrens Research Institute" + "author_name": "Herbert C Duber", + "author_inst": "Department of Emergency Medicine and Institute for Health Metrics and Evaluation, University of Washington" }, { - "author_name": "Nicolas Dambrauskas", - "author_inst": "Seattle Childrens Research Institute" + "author_name": "M Kennedy Hall", + "author_inst": "Department of Emergency Medicine, University of Washington" }, { - "author_name": "Yonghou Jiang", - "author_inst": "Seattle Childrens Research Institute" + "author_name": "Karl D Jablonowski", + "author_inst": "Department of Emergency Medicine, University of Washington" }, { - "author_name": "Olesya Trakhimets", - "author_inst": "Seattle Childrens Reserach Institute" + "author_name": "Susan A Stern", + "author_inst": "Department of Emergency Medicine, University of Washington" }, { - "author_name": "Vladimir Vigdorovich", - "author_inst": "Seattle Childrens Research Institute" - }, - { - "author_name": "Lisa Frenkel", - "author_inst": "Seattle Childrens Research Institute" - }, - { - "author_name": "D. Noah Sather", - "author_inst": "Seattle Childrens Research Institute" + "author_name": "Ali H Mokdad", + "author_inst": "Institute for Health Metrics and Evaluation, University of Washington" }, { - "author_name": "Stephen E P Smith", - "author_inst": "Seattle Childrens Research Institute" + "author_name": "Abraham D Flaxman", + "author_inst": "Institute for Health Metrics and Evaluation, University of Washington" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.06.10.20126870", @@ -1402723,62 +1402969,26 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.10.144196", - "rel_title": "Evaluating the efficacy of RT-qPCR SARS-CoV-2 direct approaches in comparison to RNA extraction", + "rel_doi": "10.1101/2020.06.09.142323", + "rel_title": "The impact of viral transport media on PCR assay results for the detection of nucleic acid from SARS-CoV-2 and other viruses", "rel_date": "2020-06-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.10.144196", - "rel_abs": "SARS-CoV-2 genetic identification is based on viral RNA extraction prior to RT-qPCR assay, however recent studies support the elimination of the extraction step. Herein, we assessed the RNA extraction necessity, by comparing RT-qPCR efficacy in several direct approaches vs. the gold standard RNA extraction, in detection of SARS-CoV-2 from laboratory samples as well as clinical Oro-nasopharyngeal SARS-CoV-2 swabs. Our findings show advantage for the extraction procedure, however a direct no-buffer approach might be an alternative, since it identified up to 70% of positive clinical specimens.", - "rel_num_authors": 11, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.09.142323", + "rel_abs": "During the 2020 SARS-Cov-2 pandemic, there has been an acute shortage of viral transport medium. Many different products have been used to meet the demands of large-scale diagnostic and surveillance testing. The stability of SARS-Cov-2 RNA was assessed in several commercially produced transport media and an in-house solution. Coronavirus RNA was rapidly destroyed in the commercial transport media though the deleterious effects on intact virus were limited. Similar results were obtained for a Type A influenza virus. There was reduced detection of both virus and nucleic acid when a herpesvirus sample and purified DNA were tested. Collectively these data showed that the commercial viral transport media contained nucleases or similar substances and may seriously compromise diagnostic and epidemiological investigations.\n\nRecommendations to include foetal bovine serum as a source of protein to enhance the stabilising properties of viral transport media are contraindicated. Almost all commercial batches of foetal bovine serum contain pestiviruses and at times other bovine viruses. In addition to the potential for there to be nucleases in the transport medium, the presence of these viruses and other extraneous nucleic acid in samples may compromise the interpretation of sequence data. The inclusion of foetal bovine serum presents a biosecurity risk for the movement of animal pathogens and renders these transport media unsuitable for animal disease diagnostic applications. While these transport media may be suitable for virus culture purposes, there could be misleading results if used for nucleic acid-based tests. Therefore, these products should be evaluated to ensure fitness for purpose.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Ofir Israeli", - "author_inst": "IIBR" + "author_name": "Peter D Kirkland", + "author_inst": "Elizabeth Macarthur Agriculture Institute" }, { - "author_name": "Adi Beth-Din", - "author_inst": "IIBR" - }, - { - "author_name": "Nir Paran", - "author_inst": "IIBR" - }, - { - "author_name": "Dana Stein", - "author_inst": "IIBR" - }, - { - "author_name": "Shirley Lazar", - "author_inst": "IIBR" - }, - { - "author_name": "Shay Weiss", - "author_inst": "IIBR" - }, - { - "author_name": "Elad Milrot", - "author_inst": "IIBR" - }, - { - "author_name": "Yafit Atiya-Nasagi", - "author_inst": "IIBR" - }, - { - "author_name": "Shmuel Yitzhaki", - "author_inst": "IIBR" - }, - { - "author_name": "Orly Laskar", - "author_inst": "IIBR" - }, - { - "author_name": "Ofir Schuster", - "author_inst": "IIBR" + "author_name": "Melinda J Frost", + "author_inst": "Elizabeth Macarthur Agriculture Institute, Woodbridge Rd, Menangle 2568 NSW Australia" } ], "version": "1", - "license": "cc_no", - "type": "contradictory results", + "license": "cc_by_nc_nd", + "type": "new results", "category": "microbiology" }, { @@ -1404189,75 +1404399,59 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.06.08.20125872", - "rel_title": "Cognitive impairment is a common comorbidity in COVID-19 deceased patients. A hospital-based retrospective cohort study.", + "rel_doi": "10.1101/2020.06.08.20125898", + "rel_title": "Sequence analysis of travel-related SARS-CoV-2 cases in the Greater Geelong region, Australia", "rel_date": "2020-06-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125872", - "rel_abs": "IntroductionLittle is known about the relation of cognitive impairment (CI) to COVID-19 mortality. Here, we analyse the frequency of CI in deceased COVID-19 patients.\n\nMethodsWe included 477 adult cases that died after admission from March 1 to March 31, 2020: 281 with confirmed COVID-19, 58 probable COVID-19, and 138 who died of other causes.\n\nResultsThe number of comorbidities was high in the confirmed COVID-19, and CI was common (30%: 21.1% dementia; 8.9% mild cognitive impairment). Subjects with CI were older, more lived in nursing homes and had shorter times from symptom onset to death than those without CI. COVID-19 patients with CI were rarely admitted to the ICU and fewer received non-invasive mechanical ventilation, but palliative care was provided more often.\n\nConclusionsDementia is a frequent comorbidity in COVID-19 deceased patients. The burden of COVID-19 in the dementia community will be high.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20125898", + "rel_abs": "This study reports the sequence analysis of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) from infected individuals within the Greater Geelong region, Victoria, Australia. All but one individual had recently returned from travelling abroad, and all had clinical signs consistent with SARS-CoV-2 infection. SARS-CoV-2 belonging to three lineages were detected and represent separate introductions of the virus into the region. Sequence data were consistent with the recent travel history of each case. Full virus genome sequencing can play an important role in supporting local epidemiological tracing and monitoring for community transmission. Quality of the SARS-CoV-2 sequences obtained was highly dependent on appropriate sample collection and handling.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Paloma Martin-Jimenez", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Madrid. Spain." - }, - { - "author_name": "Mariana I Munoz-Garcia", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Madrid. Spain" - }, - { - "author_name": "David Seoane", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Madrid. Spain" - }, - { - "author_name": "Lucas Roca-Rodriguez", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Madrid. Spain" - }, - { - "author_name": "Ana Garcia-Reyne", - "author_inst": "Department of Internal Medicine. Hospital Universitario 12 de Octubre. Madrid. Spain" + "author_name": "Tarka Raj Bhatta", + "author_inst": "Deakin University" }, { - "author_name": "Antonio Lalueza", - "author_inst": "Department of Internal Medicine. Hospital Universitario 12 de Octubre. Madrid. Spain." + "author_name": "Anthony Chamings", + "author_inst": "Deakin University" }, { - "author_name": "Guillermo Maestro", - "author_inst": "Department of Internal Medicine. Hospital Universitario 12 de Octubre. Madrid. Spain." + "author_name": "Kwee-Chin Liew", + "author_inst": "Australian Clinical Labs" }, { - "author_name": "Dolores Folgueira", - "author_inst": "Department of Microbiology. Hospital Universitario 12 de Octubre. Madrid. Spain." + "author_name": "Freya Langham", + "author_inst": "Barwon Health" }, { - "author_name": "Victor A Blanco-Palmero", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Group of Neurodegenerative Diseases, Instituto de Investigacion Hospital 12 de Octubre (I+12). CI" + "author_name": "Rudi Gasser", + "author_inst": "Barwon Health" }, { - "author_name": "Alejandro Herrero-San Martin", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Group of Neurodegenerative Diseases, Instituto de Investigacion Hospital 12 de Octubre (I+12). CI" + "author_name": "Owen Harris", + "author_inst": "Australian Clinical Labs" }, { - "author_name": "Sara Llamas-Velasco", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Group of Neurodegenerative Diseases, Instituto de Investigacion Hospital 12 de Octubre (I+12). CI" + "author_name": "Andrew Gador-Whyte", + "author_inst": "Barwon Health" }, { - "author_name": "David A Perez-Martinez", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Group of Neurodegenerative Diseases, Instituto de Investigacion Hospital 12 de Octubre (I+12). CI" + "author_name": "John Stenos", + "author_inst": "Barwon Health" }, { - "author_name": "Marta Gonzalez-Sanchez", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Group of Neurodegenerative Diseases, Instituto de Investigacion Hospital 12 de Octubre (I+12). CI" + "author_name": "Eugene Athan", + "author_inst": "Barwon Health" }, { - "author_name": "Alberto Villarejo-Galende", - "author_inst": "Department of Neurology. Hospital Universitario 12 de Octubre. Group of Neurodegenerative Diseases, Instituto de Investigacion Hospital 12 de Octubre (I+12). CI" + "author_name": "Soren Alexandersen", + "author_inst": "Deakin University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.08.20125823", @@ -1406506,95 +1406700,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.08.20122143", - "rel_title": "Hydroxychloroquine inhibits trained immunity - implications for COVID-19", + "rel_doi": "10.1101/2020.06.06.20124388", + "rel_title": "Protection after Quarantine: Insights from a Q-SEIR Model with Nonlinear Incidence Rates Applied to COVID-19", "rel_date": "2020-06-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.08.20122143", - "rel_abs": "SARS-CoV-2 infection can cause severe disease for which currently no specific therapy is available. The use of hydroxychloroquine to prevent or treat SARS-CoV-2 infection is controversial and its mode of action poorly understood. We demonstrate that hydroxychloroquine inhibits trained immunity at the functional and epigenetic level and is accompanied by profound changes in the cellular lipidome as well as reduced expression of interferon-stimulated genes. Trained immunity comprises a functional adaptation induced by epigenetic reprogramming which facilitates the anti-viral innate immune response. Our findings therefore suggest that hydroxychloroquine may not have a beneficial effect on the anti-viral immune response to SARS-CoV-2.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.06.20124388", + "rel_abs": "Community quarantine has been resorted to by various governments to address the current COVID-19 pandemic; however, this is not the only non-therapeutic method of effectively controlling the spread of the infection. We study an SEIR model with nonlinear incidence rates, and introduce two parameters, and{varepsilon} , which mimics the effect of quarantine (Q). We compare this with the Q-SEIR model, recently developed, and demonstrate the control of COVID-19 without the stringent conditions of community quarantine. We analyzed the sensitivity and elasticity indices of the parameters with respect to the reproduction number. Results suggest that a control strategy that involves maximizing and{varepsilon} is likely to be successful, although quarantine is still more effective in limiting the spread of the virus. Release from quarantine depends on continuance and strict adherence to recommended social and health promoting behaviors. Furthermore, maximizing and{varepsilon} is equivalent to a 50% successful quarantine in disease-free equilibrium (DFE). This model reduced the infectious in Quezon City by 3.45% and Iloilo Province by 3.88%; however, earlier peaking by nine and 17 days, respectively, when compared with the results of Q-SEIR.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Nils Rother", - "author_inst": "Radboudumc" - }, - { - "author_name": "Cansu Yanginlar", - "author_inst": "Radboudumc" - }, - { - "author_name": "Rik G.H. Lindeboom", - "author_inst": "Radboud University" - }, - { - "author_name": "Siroon Bekkering", - "author_inst": "Radboudumc" - }, - { - "author_name": "Mandy M.T. van Leent", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Baranca Buijsers", - "author_inst": "Radboudumc" - }, - { - "author_name": "Inge Jonkman", - "author_inst": "Radboudumc" - }, - { - "author_name": "Mark de Graaf", - "author_inst": "Radboudumc" - }, - { - "author_name": "Marijke Baltissen", - "author_inst": "Radboud University" - }, - { - "author_name": "Lieke A. Lamers", - "author_inst": "Radboud University" - }, - { - "author_name": "Niels P. Riksen", - "author_inst": "Radboudumc" - }, - { - "author_name": "Zahi A. Fayad", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Willem J.M. Mulder", - "author_inst": "Icahn School of Medicine at Mount Sinai" - }, - { - "author_name": "Luuk B. Hilbrands", - "author_inst": "Radboudumc" - }, - { - "author_name": "Leo A.B. Joosten", - "author_inst": "Radboudumc" + "author_name": "Jose Marie Antonio Minoza", + "author_inst": "Department of Computer Science, University of the Philippines Diliman, Philippines" }, { - "author_name": "Mihai G. Netea", - "author_inst": "Radboudumc" + "author_name": "Jesus Emmanuel A. D. Sevilleja", + "author_inst": "National Center for Mental Health, Mandaluyong City, Philippines" }, { - "author_name": "Michiel Vermeulen", - "author_inst": "Radboud University" + "author_name": "Romulo de Castro", + "author_inst": "Center for Informatics, University of San Agustin, Iloilo City, Philippines" }, { - "author_name": "Johan van der Vlag", - "author_inst": "Radboudumc" + "author_name": "Salvador E. Caoili", + "author_inst": "Department of Biochemistry and Molecular Biology, University of the Philippines Manila, Philippines" }, { - "author_name": "Rapha\u00ebl Duivenvoorden", - "author_inst": "Radboudumc" + "author_name": "Vena Pearl Bongolan", + "author_inst": "Department of Computer Science, University of the Philippines Diliman, Philippines" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.06.05.20123604", @@ -1408136,17 +1408274,37 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.06.07.20124933", - "rel_title": "Who dies from COVID-19? Post-hoc explanations of mortality prediction models using coalitional game theory, surrogate trees, and partial dependence plots", + "rel_doi": "10.1101/2020.06.09.20125237", + "rel_title": "COVID-19 related mortality and spread of disease in long-term care: first findings from a living systematic review of emerging evidence", "rel_date": "2020-06-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.07.20124933", - "rel_abs": "As of early June, 2020, approximately 7 million COVID-19 cases and 400,000 deaths have been reported. This paper examines four demographic and clinical factors (age, time to hospital, presence of chronic disease, and sex) and utilizes Shapley values from coalitional game theory and machine learning to evaluate their relative importance in predicting COVID-19 mortality. The analyses suggest that out of the 4 factors studied, age is the most important in predicting COVID-19 mortality, followed by time to hospital. Sex and presence of chronic disease were both found to be relatively unimportant, and the two global interpretation techniques differed in ranking them. Additionally, this paper creates partial dependence plots to determine and visualize the marginal effect of each factor on COVID-19 mortality and demonstrates how local interpretation of COVID-19 mortality prediction can be applicable in a clinical setting. Lastly, this paper derives clinically applicable decision rules about mortality probabilities through a parsimonious 3-split surrogate tree, demonstrating that high-accuracy COVID-19 mortality prediction can be achieved with simple, interpretable models.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.09.20125237", + "rel_abs": "BackgroundPolicy responses to mitigate the impact of the COVID-19 pandemic on long-term care (LTC) require robust and timely evidence on mortality and spread of the disease in these settings. The aim of this living systematic review is to synthesise early international evidence on mortality rates and incidence of COVID-19 among people who use and provide LTC.\n\nMethodsWe report findings of a living systematic review (CRD42020183557), including studies identified through database searches up to 26 June 2020. We searched seven databases (MEDLINE; Embase; CINAHL Plus; Web of Science; Global Health; WHO COVID-19 Research Database; medRxiv) to identify all studies reporting primary data on COVID-19 related mortality and incidence of disease among LTC users and staff. We excluded studies not focusing on LTC. Included studies were critically appraised and results on number of deaths and COVID-19 related mortality rates, case fatality rates, and excess deaths (co-primary outcomes), as well as incidence of disease, hospitalisations, and ICU admissions were synthesised narratively.\n\nFindingsA total of 54 study reports for 49 unique primary studies or outbreak reports were included. Outbreak investigations in LTC facilities found COVID-19 incidence rates of between 0.0% and 71.7% among residents and between 0.4% and 64.0% among staff at affected facilities. Mortality rates varied from 0.0% to 17.1% of all residents at outbreak facilities, with case fatality rates between 0.0% and 33.7%. In included studies of outbreaks, no LTC staff members had died.\n\nStudies of wider LTC populations found that between 0.4% and 40.8% of users, and between 4.0% and 23.8% of staff were infected, although the generalisability of these studies is limited.\n\nThere was limited information on the impact of COVID-19 on LTC in the community.\n\nInterpretationLong-term care users have been particularly vulnerable to the COVID-19 pandemic. However, we found wide variation in spread of disease and mortality rates between outbreaks at individual LTC facilities. Further research into the factors determining successful prevention and containment of COVID-19 outbreaks is needed to protect long-term care users and staff.\n\nFundingThis work was partially conducted as part of the \"Strengthening responses to dementia in developing countries\" (STRiDE) project, supported by the UK Research and Innovations Global Challenges Research Fund (ES/P010938/1). The funders had no role in the design and execution of this study, interpretation of its results, and decision to submit this work to be published.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Russell Yang", - "author_inst": "The Harker School" + "author_name": "Maximilian Salcher-Konrad", + "author_inst": "London School of Economics and Political Science" + }, + { + "author_name": "Arnoupe Jhass", + "author_inst": "University College London" + }, + { + "author_name": "Huseyin Naci", + "author_inst": "London School of Economics and Political Science" + }, + { + "author_name": "Marselia Tan", + "author_inst": "London School of Economics and Political Science" + }, + { + "author_name": "Yousef El-Tawil", + "author_inst": "London School of Economics and Political Science" + }, + { + "author_name": "Adelina Comas-Herrera", + "author_inst": "London School of Economics and Political Science" } ], "version": "1", @@ -1409506,73 +1409664,109 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.06.06.20124123", - "rel_title": "Clinical evaluation of self-collected saliva by RT-qPCR, direct RT-qPCR, RT-LAMP, and a rapid antigen test to diagnose COVID-19", + "rel_doi": "10.1101/2020.06.05.20123554", + "rel_title": "The Role of Vitamin D in The Age of COVID-19: A Systematic Review and Meta-Analysis Along with an Ecological Approach", "rel_date": "2020-06-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.06.20124123", - "rel_abs": "BackgroundThe clinical performance of six molecular diagnostic tests and a rapid antigen test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were clinically evaluated for the diagnosis of coronavirus disease 2019 (COVID-19) in self-collected saliva.\n\nMethodsSaliva samples from 103 patients with laboratory-confirmed COVID-19 (15 asymptomatic and 88 symptomatic) were collected on the day of hospital admission. SARS-CoV-2 RNA in saliva was detected using a quantitative reverse-transcription polymerase chain reaction (RT-qPCR) laboratory-developed tes (LDT), a cobas SARS-CoV-2 high-throughput system, three direct RT-qPCR kits, and reverse-transcription loop mediated isothermal amplification (RT-LAMP). Viral antigen was detected by a rapid antigen immunochromatographic assay.\n\nResultsOf the 103 samples, viral RNA was detected in 50.5-81.6% of the specimens by molecular diagnostic tests and an antigen was detected in 11.7% of the specimens by the rapid antigen test. Viral RNA was detected at a significantly higher percentage (65.6-93.4%) in specimens collected within 9 d of symptom onset compared to that of specimens collected after at least 10 d of symptom onset (22.2-66.7%) and that of asymptomatic patients (40.0-66.7%). Viral RNA was more frequently detected in saliva from males than females.\n\nConclusionsSelf-collected saliva is an alternative specimen diagnosing COVID-19. LDT RT-qPCR, cobas SARS-CoV-2 high-throughput system, direct RT-qPCR except for one commercial kit, and RT-LAMP showed sufficient sensitivity in clinical use to be selectively used according to clinical settings and facilities. The rapid antigen test alone is not recommended for initial COVID-19 diagnosis because of its low sensitivity.\n\nKey pointsSix molecular diagnostic tests showed equivalent and sufficient sensitivity in clinical use in diagnosing COVID-19 in self-collected saliva samples. However, a rapid SARS-CoV-2 antigen test alone is not recommended for use without further study.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20123554", + "rel_abs": "BackgroundEvidence recommends that vitamin D might be a crucial supportive agent for the immune system, mainly in cytokine response regulation against COVID-19. Hence, we carried out a systematic review and meta-analysis in order to maximize the use of everything that exists about the role of vitamin D in the COVID-19.\n\nMethodsA systematic search was performed in PubMed, Scopus, Embase, and Web of Science up to December 18, 2020. Studies focused on the role of vitamin D in confirmed COVID-19 patients were entered into the systematic review.\n\nResultsTwenty-three studies containing 11901participants entered into the meta-analysis. The meta-analysis indicated that 41% of COVID-19 patients were suffering from vitamin D deficiency (95% CI, 29%-55%), and in 42% of patients, levels of vitamin D were insufficient (95% CI, 24%-63%). The serum 25-hydroxyvitamin D concentration was 20.3 ng/mL among all COVID-19 patients (95% CI, 12.1-19.8). The odds of getting infected with SARS-CoV-2 is 3.3 times higher among individuals with vitamin D deficiency (95% CI, 2.5-4.3). The chance of developing severe COVID-19 is about five times higher in patients with vitamin D deficiency (OR: 5.1, 95% CI, 2.6-10.3). There is no significant association between vitamin D status and higher mortality rates (OR: 1.6, 95% CI, 0.5-4.4).\n\nConclusionThis study found that most of the COVID-19 patients were suffering from vitamin D deficiency/insufficiency. Also, there is about three times higher chance of getting infected with SARS-CoV-2 among vitamin D deficient individuals and about 5 times higher probability of developing the severe disease in vitamin D deficient patients. Vitamin D deficiency showed no significant association with mortality rates in this population.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Mayu Ikeda", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Roya Ghasemian", + "author_inst": "Mazandaran University of Medical Sciences" }, { - "author_name": "Kazuo Imai", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Amir Shamshirian", + "author_inst": "Mazandaran University of Medical Sciences" }, { - "author_name": "Sakiko Tabata", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Keyvan Heydari", + "author_inst": "Mazandaran University of Medical Sciences" }, { - "author_name": "Kazuyasu Miyoshi", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Mohammad Malekan", + "author_inst": "Mazandaran University of Medical Sciences" }, { - "author_name": "Tsukasa Mizuno", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Reza Alizadeh-Navaei", + "author_inst": "Mazandaran University of Medical Sciences" }, { - "author_name": "Nami Murahara", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Mohammad Ali Ebrahimzadeh", + "author_inst": "Mazandaran University of Medical Sciences" }, { - "author_name": "Midori Horiuchi", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Hamed Jafarpour", + "author_inst": "Mazandaran University of Medical Sciences" }, { - "author_name": "Kento Kato", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Arash Rezaei Shahmirzadi", + "author_inst": "Golestan University of Medical Sciences" }, { - "author_name": "Yoshitaka Imoto", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Mehrdad Khodabandeh", + "author_inst": "Iran University of Medical Sciences" }, { - "author_name": "Maki Iwata", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Benyamin Seyfari", + "author_inst": "Kashan University of Medical Sciences" }, { - "author_name": "Satoshi Mimura", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Meghdad Sedaghat", + "author_inst": "Shahid Beheshti University of Medical Sciences" }, { - "author_name": "Toshimitsu Ito", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Alireza Motamedzadeh", + "author_inst": "Kashan University of Medical Sciences" }, { - "author_name": "Kaku Tamura", - "author_inst": "Self-Defense Forces Central Hospital" + "author_name": "Ehsan Dadgostar", + "author_inst": "Halal Research Center of IRI" }, { - "author_name": "Yasuyuki Kato", - "author_inst": "International University of Health and Welfare Narita Hospital" + "author_name": "Marzieh Aalinezhad", + "author_inst": "Isfahan University of Medical Sciences" + }, + { + "author_name": "Anahita Asadi", + "author_inst": "Mazandaran University of Medical Sciences" + }, + { + "author_name": "Bahman Zarandi", + "author_inst": "Iran University of Medical Sciences" + }, + { + "author_name": "Nazanin Razzaghi", + "author_inst": "Golestan University of Medical Sciences" + }, + { + "author_name": "Vahid Yaghoubi Naei", + "author_inst": "Mashhad University of Medical Sciences" + }, + { + "author_name": "Reza Beheshti", + "author_inst": "Mazandaran University of Medical Sciences" + }, + { + "author_name": "Amirhossein Hessami", + "author_inst": "Mazandaran University of Medical Sciences" + }, + { + "author_name": "Soheil Azizi", + "author_inst": "Mazandaran University of Medical Sciences" + }, + { + "author_name": "Ali Reza Mohseni", + "author_inst": "Mazandaran University of Medical Sciences" + }, + { + "author_name": "Danial Shamshirian", + "author_inst": "Shahid Beheshti University of Medical Sciences" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1411232,21 +1411426,29 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.06.05.20122903", - "rel_title": "Impact of Governmental interventions on epidemic progression and workplace activity during the COVID-19 outbreak", + "rel_doi": "10.1101/2020.06.05.20123695", + "rel_title": "Non-COVID-19 Deaths After Social Distancing in Norway", "rel_date": "2020-06-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20122903", - "rel_abs": "In the first quarter of 2020, the COVID-19 pandemic brought the world to a state of paralysis. During this period, humanity has seen by far the largest organized travel restrictions and unprecedented efforts and global coordination to contain the spread of the SARS-CoV-2 virus. Using large scale human mobility and fine grained epidemic incidence data, we develop a framework to understand and quantify the effectiveness of the interventions implemented by various countries to control epidemic growth. Our analysis reveals the importance of timing and implementation of strategic policy in controlling the epidemic. Through our analysis, we also unearth significant spatial diffusion of the epidemic before and during the lock-down measures in several countries, casting doubt on the effectiveness or on the implementation quality of the proposed Governmental policies.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.05.20123695", + "rel_abs": "Lay persons and policy makers have speculated on how the imposition of social distancing to reduce SARS CoV-2 (severe acute respiratory syndrome coronavirus 2) infection has affected non-COVID-19 (coronavirus disease of 2019) deaths. No rigorous estimation of the effect appears in the scholarly literature. We use time-series methods to compare non-COVID-19 deaths observed in Norway before and during the epidemic to those expected from non-COVID-19 deaths in Sweden as well as from the history of Norwegian mortality trends. We find that in the first 6 weeks after the divergence between Swedish and Norwegian policies -- the only period for which dependable data can be had - approximately 414 fewer Norwegians died than expected.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Sumit Kumar Ram", - "author_inst": "ETH Zurich" + "author_name": "Ralph Catalano", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Didier Sornette", - "author_inst": "ETH Zurich" + "author_name": "Joan A Casey", + "author_inst": "Columbia University" + }, + { + "author_name": "Tim-Allen Bruckner", + "author_inst": "University of California, Irvine" + }, + { + "author_name": "Alison Gemmill", + "author_inst": "Johns Hopkins Bloomberg School of Public Health" } ], "version": "1", @@ -1412590,27 +1412792,51 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.06.05.136887", - "rel_title": "Protein covariance networks reveal interactions important to the emergence of SARS coronaviruses as human pathogens", + "rel_doi": "10.1101/2020.06.05.137380", + "rel_title": "ScRNA-seq discover cell cluster change under OAB: ACE2 expression reveal possible alternation of 2019-nCoV infectious pathway", "rel_date": "2020-06-06", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.05.136887", - "rel_abs": "SARS-CoV-2 is one of three recognized coronaviruses (CoVs) that have caused epidemics or pandemics in the 21st century and that have likely emerged from animal reservoirs based on genomic similarities to bat and other animal viruses. Here we report the analysis of conserved interactions between amino acid residues in proteins encoded by SARS-CoV-related viruses. We identified pairs and networks of residue variants that exhibited statistically high frequencies of covariance with each other. While these interactions are likely key to both protein structure and other protein-protein interactions, we have also found that they can be used to provide a new computational approach (CoVariance-based Phylogeny Analysis) for understanding viral evolution and adaptation. Our data provide evidence that the evolutionary processes that converted a bat virus into human pathogen occurred through recombination with other viruses in combination with new adaptive mutations important for entry into human cells.", - "rel_num_authors": 2, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.06.05.137380", + "rel_abs": "ObjectivePrevious study indicated that bladder cells which express ACE2 were a potential infection route of 2019-nCov. This study observed some differences of bladder cell cluster and their ACE2 expression between OAB mice and healthy mice, indicating the change of infectious possibility and pathway under overactive bladder (OAB) circumstance.\n\nMaterial and methodPubic dataset acquisition was used to get ACE2 expression in normal human bladder and mice bladder (GSE129845). We built up over OAB model and studied the impact on cell typing and ACE2 expression. By way of using single-cell RNA sequencing (scRNA-seq) technique, bladder cell clustering and ACE2 expression in various cell types were measured respectively.\n\nResultIn pubic database (healthy human and mice bladder), ACE2 expression in humans and mice is concentrated in bladder epithelial cells. The disappearance of umbrella cells, a component of bladder epithelial, was found in our OAB model. In the two mouse bladder samples, ACE2 expression of epithelial cells is 34.1%, also the highest of all cell types.\n\nConclusionThe disappearance of umbrella cell may alternate the infection pathway of 2019-nCov and relate to the onset and progression of OAB.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "William P Robins", - "author_inst": "Harvard Medical School" + "author_name": "Boyu Xiang", + "author_inst": "The fifth brigade, Basic medicine of Army Medical University" }, { - "author_name": "John J Mekalanos", - "author_inst": "Harvard Medical School" + "author_name": "Xiangyu Hu", + "author_inst": "The fourth brigade, Basic medicine of Army Medical University" + }, + { + "author_name": "Haoxuan Li", + "author_inst": "The fourth brigade, Basic medicine of Army Medical University" + }, + { + "author_name": "Li Ma", + "author_inst": "The fifth brigade, Basic medicine of Army Medical University" + }, + { + "author_name": "Hao Zhou", + "author_inst": "Urological Surgery Research Institute, Southwest Hospital, Army Medical" + }, + { + "author_name": "Ling Wei", + "author_inst": "Urological Surgery Research Institute, Southwest Hospital, Army Medical" + }, + { + "author_name": "Jue Fan", + "author_inst": "Singleron Biotechnologies, Yaogu Avenue 11, Nanjing, Jiangsu, China" + }, + { + "author_name": "Ji Zheng", + "author_inst": "Urological Surgery Research Institute, Southwest Hospital, Army Medical" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "cell biology" }, { "rel_doi": "10.1101/2020.06.06.137513", @@ -1414360,79 +1414586,31 @@ "category": "medical education" }, { - "rel_doi": "10.1101/2020.06.02.20120642", - "rel_title": "Estimating excess visual loss in people with neovascular age-related macular degeneration during the COVID-19 pandemic", + "rel_doi": "10.1101/2020.06.03.20121608", + "rel_title": "COVID-19 DYNAMICS CONSIDERING THE INFLUENCE OF HOSPITAL INFRASTRUCTURE: AN INVESTIGATION OF BRAZILIAN SCENARIOS", "rel_date": "2020-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120642", - "rel_abs": "ObjectivesTo report the reduction in new neovascular age-related macular degeneration (nAMD) referrals during the COVID-19 pandemic and estimate the impact of delayed treatment on visual outcomes at one year.\n\nDesignRetrospective clinical audit and simulation model.\n\nSettingMultiple UK NHS ophthalmology centres.\n\nParticipantsData on the reduction in new nAMD referrals was obtained from four NHS Trusts in England comparing April 2020 to April 2019. To estimate the potential impact on one-year visual outcomes, a stratified bootstrap simulation model was developed drawing on an electronic medical records dataset of 20,825 nAMD eyes from 27 NHS Trusts.\n\nMain outcome measuresSimulated mean visual acuity and proportions of eyes with vision [≤]6/60, [≤]6/24 and [≥]6/12 at one year under four hypothetical scenarios: no treatment delay, 3, 6 and 9-month treatment delays. Estimated additional number of eyes with vision [≤]6/60 at one year nationally.\n\nResultsThe number of nAMD referrals at four major eye treatment hospital groups based in England dropped on average by 72% (range 65 to 87%) in April 2020 compared to April 2019. Simulated one-year visual outcomes for 1000 nAMD eyes with a 3-month treatment delay suggested an increase in the proportion of eyes with vision [≤]6/60 from 15.5% (13.2 to 17.9) to 23.3% (20.7 to25.9), and a decrease in the proportion of eyes with vision [≥]6/12 (driving vision) from 35.1% (32.1 to 38.1) to 26.4% (23.8 to29.2). Outcomes worsened incrementally with longer modelled delays. Assuming nAMD referrals are reduced to this level at the national level for only one month, these simulated results suggest an additional 186-365 eyes with vision [≤]6/60 at one-year with even a short treatment delay.\n\nConclusionsWe report a large decrease in nAMD referrals during the first month of COVID-19 lockdown and provide an important public health message regarding the risk of delayed treatment. As a conservative estimate, a treatment delay of 3 months could lead to a >50% relative increase in the number of eyes with vision [≤]6/60 and 25% relative decrease in the number of eyes with driving vision at one year.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.03.20121608", + "rel_abs": "This paper deals with the mathematical modeling and numerical simulations related to the coronavirus dynamics. A description is developed based on the framework of susceptible-exposed-infectious-removed model. Removed population is split into recovered and death populations allowing a better comprehension of real situations. Besides, total population is reduced based on the number of deaths. Hospital infrastructure is also included into the mathematical description allowing the consideration of collapse scenarios. Initially, a model verification is carried out calibrating system parameters with data from China outbreak that is considered a benchmark due the availability of data for the entire cycle. Afterward, numerical simulations are performed to analyze COVID-19 dynamics in Brazil. Results show several scenarios showing the importance of social isolation. System dynamics has a strong sensitivity to transmission rate showing the importance of numerical simulations to guide public health decision strategies.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Darren S Thomas", - "author_inst": "Institute of Health Informatics, University College London, London, UK" - }, - { - "author_name": "Alasdair Warwick", - "author_inst": "Institute of Cardiovascular Science, University College London, London, UK & Moorfields Eye Hospital NHS Foundation Trust, London, UK." - }, - { - "author_name": "Abraham Olvera-Barrios", - "author_inst": "Moorfields Eye Hospital NHS Turst & Institute of Ophthalmology UCL" + "author_name": "Pedro M.C.L. Pacheco", + "author_inst": "Centro Federal de Educacao Tecnologica Celso Suckow da Fonseca - CEFET/RJ" }, { - "author_name": "Catherine Egan", - "author_inst": "Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL" - }, - { - "author_name": "Roy Schwartz", - "author_inst": "Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Health Informatics, University College London, London, UK" - }, - { - "author_name": "Sudeshna Patra", - "author_inst": "Bart's Health NHS Trust, London, UK" - }, - { - "author_name": "Haralabos Eleftheriadis", - "author_inst": "King's College Hospital NHS Trust, London, UK" - }, - { - "author_name": "Anthony P Khawaja", - "author_inst": "Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL" - }, - { - "author_name": "Andrew Lotery", - "author_inst": "Faculty of Medicine, University of Southampton, Southampton, UK" - }, - { - "author_name": "Philipp L Mueller", - "author_inst": "Moorfields Eye Hospital NHS Foundation Trust, London, UK" - }, - { - "author_name": "Robin Hamilton", - "author_inst": "Moorfields Eye Hospital NHS Foundation Trust, London, UK & Institute of Ophthalmology, UCL" - }, - { - "author_name": "Ella Preston", - "author_inst": "Moorfields Eye Hospital NHS Foundation Trust, London, UK" - }, - { - "author_name": "Paul Taylor", - "author_inst": "Institute of Health Informatics, University College London, London, UK" - }, - { - "author_name": "Adnan Tufail", - "author_inst": "Moorfields Eye Hospital NHS Trust & Institute of Ophthalmology UCL" + "author_name": "Marcelo A. Savi", + "author_inst": "Universidade Federal do Rio de Janeiro" }, { - "author_name": "- UK EMR Users Group", - "author_inst": "" + "author_name": "Pedro V. Savi", + "author_inst": "Universidade Federal do Rio de Janeiro" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "ophthalmology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.06.03.20121145", @@ -1415858,51 +1416036,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.06.03.20121442", - "rel_title": "Reduction in preterm births during the COVID-19 lockdown in Ireland: a natural experiment allowing analysis of data from the prior two decades.", + "rel_doi": "10.1101/2020.06.04.20121863", + "rel_title": "COVID-19 and climate: global evidence from 117 countries", "rel_date": "2020-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.03.20121442", - "rel_abs": "BackgroundAetiology of preterm birth (PTB) is heterogeneous and preventive strategies remain elusive. Socio-environmental measures implemented as Irelands prudent response to the SARS-CoV-2 virus (COVID-19) pandemic represented, in effect, a national lockdown and have possibly influenced the health and wellbeing of pregnant women and unborn infants. Cumulative impact of such socio-environmental factors operating contemporaneously on PTB has never been assessed before.\n\nMethodsRegional PTB trends of very low birth weight (VLBW) infants in one designated health area of Ireland over two decades were analysed. Poisson regression and rate ratio analyses with 95% CI were conducted. Observed regional data from January - April 2020 were compared to historical regional and national data and forecasted national figures for 2020.\n\nResultsPoisson regression analysis found that the regional historical VLBW rate per 1000 live births for January to April, 2001-2019 was 8.18 (95% CI: 7.21, 9.29). During January to April 2020, an unusually low VLBW rate of just 2.17 per 1000 live births was observed. The rate ratio of 3.77 (95% CI: 1.21, 11.75), p = 0.022, estimates that for the last two decades there was, on average, 3.77 times the rate of VLBW, compared to the period January to April 2020 during which there is a 73% reduction. National Irish VLBW rate for 2020 is forecasted to be reduced to 400 per 60,000 births compared to the historical 500-600 range.\n\nConclusionAn unprecedented reduction in PTB of VLBW infants was observed in one health region of Ireland during the COVID-19 lockdown. Potential determinants of this unique temporal trend reside in the summative socio-environmental impact of the COVID-19 dictated lockdown. Our findings, if mirrored in other regions that have adopted similar measures to combat the pandemic, demonstrate the potential to evaluate these implicated interdependent behavioural and socio-environmental modifiers to positively influence PTB rates globally.\n\nKey QuestionsO_ST_ABSWhat is already known?C_ST_ABSO_LIPremature birth is an important contributor for under-five mortality globally.\nC_LIO_LICurrently there is no broadly accepted and effective strategy to prevent the birth of premature very low birth weight infants.\nC_LIO_LIImpact of socio-environmental and maternal behavioural modifications on the incidence of preterm birth has not been assessed.\nC_LI\n\nWhat are the new findings?O_LICOVID-19-triggered national lockdown in Ireland created an opportunity to study the cumulative influence of socio-environmental modifications on pregnant mothers.\nC_LIO_LIAn unprecedented 73% reduction in the rate of very low birth weight deliveries was noted in one designated health region of Ireland during January to April of 2020 in comparison to the preceding 20 year timeframe.\nC_LIO_LIOur observations, if nationally mirrored, indicate that birth rate of very low birth weight premature infants in Ireland is forecasted to decrease considerably in 2020.\nC_LI\n\nWhat do the new findings imply?O_LISocially rooted modifiers such as family support, work related stress and commuting, environmental pollution, infection avoidance, sleep and nutritional support, adequate exercise, reduced exposure to tobacco and illicit drugs, avoidance of financial strain, all cumulatively could contribute to reduce preterm birth rate.\nC_LIO_LIOur observations, if reflected in other countries that adopted COVID-19-prompted lockdown measures, would redefine the antecedents that trigger the yet poorly understood pathways leading to preterm births.\nC_LIO_LIPrematurity rate would be the most important curve to bend in the context of reducing infant mortality globally and thus promote the achievement of sustainable development goals for children.\nC_LI", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20121863", + "rel_abs": "Visual inspection of world maps shows that coronavirus disease 2019 (COVID-19) is less prevalent in countries closer to the equator, where heat and humidity tend to be higher. Scientists disagree how to interpret this observation because the relationship between COVID-19 and climatic conditions may be confounded by many factors. We regress confirmed COVID-19 cases per million inhabitants in a country against the countrys distance from the equator, controlling key confounding factors: air travel, distance to Wuhan, testing intensity, cell phone usage, vehicle concentration, urbanization, and income. A one-degree increase in absolute latitude is associated with a 2.6% increase in cases per million inhabitants (p value < 0.001). The Northern hemisphere may see a decline in new COVID-19 cases during summer and a resurgence during winter.\n\nOne Sentence SummaryAn increase in absolute latitude by one degree is associated with a 2.6% increase in COVID-19 cases per million inhabitants after controlling for several important factors.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Roy K Philip", - "author_inst": "Division of Neonatology, Department of Paediatrics, University Maternity Hospital Limerick, Ireland" - }, - { - "author_name": "Helen Purtill", - "author_inst": "Department of Mathematics and Statistics, University of Limerick, Limerick, Ireland" + "author_name": "Simiao Chen", + "author_inst": "Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany." }, { - "author_name": "Elizabeth Reidy", - "author_inst": "Department of Midwifery and Neonatal Nursing, University Maternity Hospital, Limerick, Ireland." + "author_name": "Klaus Prettner", + "author_inst": "University of Hohenheim, Institute of Economics, Stuttgart, Germany." }, { - "author_name": "Mandy Daly", - "author_inst": "Advocacy and Policymaking, Irish Neonatal Health Alliance (INHA), Bray, Wicklow, Ireland." + "author_name": "Michael Kuhn", + "author_inst": "Wittgenstein Centre, Vienna Institute of Demography, Vienna, Austria" }, { - "author_name": "Mendinaro Imcha", - "author_inst": "Department of Obstetrics and Gynaecology, University Maternity Hospital, Limerick, Ireland." + "author_name": "Pascal Geldsetzer", + "author_inst": "Division of Primary Care and Population Health, Department of Medicine, Stanford University, Stanford, CA, USA" }, { - "author_name": "Deirdre McGrath", - "author_inst": "Head of School, School of Medicine University ofLimerick, Limerick, Ireland." + "author_name": "Chen Wang", + "author_inst": "Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China." }, { - "author_name": "Nuala H O'Connell", - "author_inst": "Department of Clinical Microbiology, University Hospital Limerick, Ireland." + "author_name": "Till Baernighausen", + "author_inst": "Heidelberg Institute of Global Health, Heidelberg University, Heidelberg, Germany." }, { - "author_name": "Colum P Dunne", - "author_inst": "Head of Research, School of Medicine and Centre for Interventions in Infection, Inflammation and Immunity (4i), University of Limerick, Ireland." + "author_name": "David E. Bloom", + "author_inst": "Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, USA." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "pediatrics" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.06.04.20119594", @@ -1417907,33 +1418081,21 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.06.04.20122176", - "rel_title": "What variables can better predict the number of infections and deaths worldwide by SARS-CoV-2? Variation through time", + "rel_doi": "10.1101/2020.06.04.20122382", + "rel_title": "Optimal Control Measures to Combat COVID19 Spread in Sri Lanka: A Mathematical ModelConsidering the Heterogeneity of Cases", "rel_date": "2020-06-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20122176", - "rel_abs": "Using data from 50 very different countries (which represent nearly 70% of worlds population) and by means of a regression analysis, we studied the predictive power of different variables (mobility, air pollution, health & research, economic and social & geographic indicators) over the number of infected and dead by SARS-CoV-2. We also studied if the predictive power of these variables changed during a 4 months period (March, April, May and June). We approached data in two different ways, cumulative data and non-cumulative data.\n\nThe number of deaths by Covid-19 can always be predicted with great accuracy from the number of infected, regardless of the characteristics of the country.\n\nInbound tourism emerged as the variable that best predicts the number of infected (and, consequently, the number of deaths) happening in the different countries. Electricity consumption and air pollution of a country (CO2 emissions, nitrous oxide and methane) are also capable of predicting, with great precision, the number of infections and deaths from Covid-19. Characteristics such as the area and population of a country can also predict, although to a lesser extent, the number of infected and dead. All predictive variables remained significant through time.\n\nIn contrast, a series of variables, which in principle would seem to have a greater influence on the evolution of Covid-19 (hospital bed density, Physicians per 1000 people, Researches in R & D, urban population...), turned out to have very little - or none- predictive power.\n\nOur results explain why countries that opted for travel restrictions and social withdrawal policies at a very early stage of the pandemic outbreak, obtained better results. Preventive policies proved to be the key, rather than having large hospital and medical resources.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.04.20122382", + "rel_abs": "The COVID 19 pandemic caused by the novel corona virus (SARS-CoV-2) has been one of the major public health concerns across the globe, currently more than 3.5 million individuals have been infected, and the number of deaths has passed 250,000. The world wide burden of the disease has been massive, and the governments are in dilemma to protect the health system of the country while safeguarding the economy. There is no vaccine or antivirus drug found against this virus while multiple research groups are actively working on a suitable candidate. The only available mode of minimizing the disease burden has been to control its transmission among the population. Since the occurrence of first COVID 19 local case on 11 March 2020, the government of Sri Lanka introduced serious social distancing and public health interventions in its fullest capacity as a developing nation to effectively combat with the disease spread. This study focuses to develop a mathematical model to investigate the dynamic of this novel disease using an extended version of an SEIR compartmental structure considering the heterogeneity of cases such as asymptomatic, symptomatic with mild indications and the cases required intensive care treatments. All the measures and interventions are in progress with a significantly large social and economic cost, thus, optimal control techniques are used to identify the most appropriate strategies to minimize this cost. The results of the simulations prove that optimal control measures can be worked out as the epidemic curves are flattened while delaying the outbreak so that the health system might not be under pressure to treat and care the patients.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Javier Garcia Garcia de Alcaniz", - "author_inst": "Veterinary Faculty Complutense University Madrid Genetics Department" - }, - { - "author_name": "Julia Romero-Lopez", - "author_inst": "Veterinary Faculty Complutense University Madrid Genetics Department" - }, - { - "author_name": "Rocio P. Martinez", - "author_inst": "Veterinary Faculty Complutense University Madrid Genetics Department" - }, - { - "author_name": "Victoria Lopez-Rodas Sr.", - "author_inst": "Veterinary Faculty Complutense University Madrid Genetics Department" + "author_name": "Tharindu Wickramaarachchi Sr.", + "author_inst": "The Open University of sri Lanka" }, { - "author_name": "Eduardo Costas Sr.", - "author_inst": "Veterinary Faculty Complutense University Madrid, Genetics Department" + "author_name": "Sanjeewa Perera Sr.", + "author_inst": "University of Colombo" } ], "version": "1", @@ -1419489,73 +1419651,141 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.06.02.20120014", - "rel_title": "Viral load dynamics in transmissible symptomatic patients with COVID-19", + "rel_doi": "10.1101/2020.06.02.20120345", + "rel_title": "Comparative assessment of multiple COVID-19 serological technologies supports continued evaluation of point-of-care lateral flow assays in hospital and community healthcare settings", "rel_date": "2020-06-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120014", - "rel_abs": "To investigate the relationship between viral load and secondary transmission in novel coronavirus disease 2019 (COVID-19), we reviewed epidemiological and clinical data obtained from immunocompetent laboratory-confirmed patients with COVID-19 at Toyama University Hospital. In total, 28 patients were included in the analysis. Median viral load at the initial sample collection was significantly higher in adults than in children and in symptomatic than in asymptomatic patients. Among symptomatic patients, non-linear regression models showed that the estimated viral load at onset was higher in the index (patients who transmitted the disease to at least one other patient) than in the non-index patients (patients who were not the cause of secondary transmission; median [95% confidence interval]: 6.6 [5.2-8.2] vs. 3.1 [1.5-4.8] log copies/L, respectively). High nasopharyngeal viral loads around onset may contribute to secondary transmission of COVID-19.\n\nArticle Summary LineHigh nasopharyngeal viral load around the onset may contributes to secondary transmission of COVID-19.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.06.02.20120345", + "rel_abs": "There is a clear requirement for an accurate SARS-CoV-2 antibody test, both as a complement to existing diagnostic capabilities and for determining community seroprevalence. We therefore evaluated the performance of a variety of antibody testing technologies and their potential as diagnostic tools. A highly specific in-house ELISA was developed for the detection of anti-spike (S), -receptor binding domain (RBD) and -nucleocapsid (N) antibodies and used for the cross-comparison of ten commercial serological assays - a chemiluminescence-based platform, two ELISAs and seven colloidal gold lateral flow immunoassays (LFIAs) - on an identical panel of 110 SARS-CoV-2-positive samples and 50 pre-pandemic negatives. There was a wide variation in the performance of the different platforms, with specificity ranging from 82% to 100%, and overall sensitivity from 60.9% to 87.3%. However, the head-to-head comparison of multiple sero-diagnostic assays on identical sample sets revealed that performance is highly dependent on the time of sampling, with sensitivities of over 95% seen in several tests when assessing samples from more than 20 days post onset of symptoms. Furthermore, these analyses identified clear outlying samples that were negative in all tests, but were later shown to be from individuals with mildest disease presentation. Rigorous comparison of antibody testing platforms will inform the deployment of point-of-care technologies in healthcare settings and their use in the monitoring of SARS-CoV-2 infections.", + "rel_num_authors": 31, "rel_authors": [ { - "author_name": "Hitoshi Kawasuji", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Suzanne Pickering", + "author_inst": "King's College London" }, { - "author_name": "Yusuke Takegoshi", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Gilberto Betancor", + "author_inst": "King's College London" }, { - "author_name": "Makito Kaneda", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Rui Pedro Galao", + "author_inst": "King's College London" }, { - "author_name": "Akitoshi Ueno", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Blair Merrick", + "author_inst": "Guy's and St. Thomas' NHS Foundation Trust" }, { - "author_name": "Yuki Miyajima", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Adrian W Signell", + "author_inst": "King's College London" }, { - "author_name": "Koyomi Kawago", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Harry D Wilson", + "author_inst": "King's College London" }, { - "author_name": "Yasutaka Fukui", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Mark Tan Kia Ik", + "author_inst": "King's College London" }, { - "author_name": "Yoshihiko Yoshida", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Jeffrey Seow", + "author_inst": "King's College London" }, { - "author_name": "Miyuki Kimura", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Carl Graham", + "author_inst": "King's College London" }, { - "author_name": "Hiroshi Yamada", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Sam Acors", + "author_inst": "King's College London" }, { - "author_name": "Ippei Sakamaki", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Neophytos Kouphou", + "author_inst": "King's College London" }, { - "author_name": "Hideki Tani", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Kathryn JA Steel", + "author_inst": "King's College London" }, { - "author_name": "Yoshitomo Morinaga", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Oliver Hemmings", + "author_inst": "King's College London" }, { - "author_name": "Yoshihiro Yamamoto", - "author_inst": "Toyama University Graduate School of Medicine and Pharmaceutical Sciences, Toyama, Japan" + "author_name": "Amita Patel", + "author_inst": "Guy's and St.Thomas' NHS Foundation Trust" + }, + { + "author_name": "Gaia Nebbia", + "author_inst": "Guy's and St.Thomas' NHS Foundation Trust" + }, + { + "author_name": "Sam Douthwaite", + "author_inst": "Guy's and St.Thomas' NHS Foundation Trust" + }, + { + "author_name": "Lorcan O'Connell", + "author_inst": "Guy's and St.Thomas' NHS Foundation Trust" + }, + { + "author_name": "Jakub Luptak", + "author_inst": "MRC Laboratory of Molecular Biology, Cambridge" + }, + { + "author_name": "Laura McCoy", + "author_inst": "University College London" + }, + { + "author_name": "Philip JM Brouwer", + "author_inst": "University of Amsterdam" + }, + { + "author_name": "Marit J van Gils", + "author_inst": "University of Amsterdam" + }, + { + "author_name": "Rogier W Sanders", + "author_inst": "University of Amsterdam" + }, + { + "author_name": "Rocio Martinez Nunez", + "author_inst": "King's College London" + }, + { + "author_name": "Karen Bisnauthsing", + "author_inst": "Guy's and St.Thomas' NHS Foundation Trust" + }, + { + "author_name": "Geraldine O'Hara", + "author_inst": "Guy's and St.Thomas' NHS Foundation Trust" + }, + { + "author_name": "Eithne MacMahon", + "author_inst": "Guy's and St.Thomas' NHS Foundation Trust" + }, + { + "author_name": "Rahul Batra", + "author_inst": "Guy's and St.Thomas' NHS Foundation Trust" + }, + { + "author_name": "Michael H Malim", + "author_inst": "King's College London" + }, + { + "author_name": "Stuart JD Neil", + "author_inst": "King's College London" + }, + { + "author_name": "Katie Doores", + "author_inst": "King's College London" + }, + { + "author_name": "Jonathan D Edgeworth", + "author_inst": "King's College London" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1420747,53 +1420977,101 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.31.20118455", - "rel_title": "Hospital readmissions of discharged patients with COVID-19", + "rel_doi": "10.1101/2020.05.29.20117358", + "rel_title": "Tocilizumab for treatment of mechanically ventilated patients with COVID-19", "rel_date": "2020-06-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20118455", - "rel_abs": "BackgroundCOVID-19 infection has led to an overwhelming effort by health institutions to meet the high demand for hospital admissions.\n\nAimTo analyse the clinical variables associated with readmission of patients who had previously been discharged after admission for COVID-19.\n\nDesign and methodsWe studied a retrospective cohort of patients with laboratory-confirmed SARS-CoV-2 infection who were admitted and subsequently discharged alive. We then conducted a nested case-control study paired (1:1 ratio) by age, sex and period of admission.\n\nResultsOut of 1368 patients who were discharged during the study period, 61 patients (4.4%) were readmitted. Immunocompromised patients were at increased risk for readmission. There was also a trend towards a higher probability of readmission in hypertensive patients (p=0.07). Cases had had a shorter hospital stay and a higher prevalence of fever during the 48 hours prior to discharge. There were no significant differences in oxygen levels measured at admission and discharge by pulse oximetry intra-subject or between the groups. Neutrophil/lymphocyte ratio at hospital admission tended to be higher in cases than in controls (p=0.06). The motive for readmission in 10 patients (16.4%), was a thrombotic event in venous or arterial territory (p<0.001). Neither glucocorticoids nor anticoagulants prescribed at hospital discharge were associated with a lower readmission rate.\n\nConclusionsThe rate of readmission after discharge from hospital for COVID-19 was low. Immunocompromised patients and those presenting with fever during the 48 hours prior to discharge are at greater risk of readmission to hospital.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20117358", + "rel_abs": "BackgroundSevere COVID-19 can manifest in rapid decompensation and respiratory failure with elevated inflammatory markers. This presentation is consistent with cytokine release syndrome in chimeric antigen receptor T cell therapy, for which IL-6 blockade is approved treatment.\n\nMethodsWe assessed effectiveness and safety of IL-6 blockade with tocilizumab in a single-center cohort of patients with COVID-19 requiring mechanical ventilation. The primary endpoint was survival probability post-intubation; secondary analyses included an ordinal illness severity scale integrating superinfections. Outcomes in patients who received tocilizumab compared to tocilizumab-untreated controls were evaluated using multivariable Cox regression with propensity score inverse probability weighting (IPTW).\n\nFindings154 patients were included, of whom 78 received tocilizumab and 76 did not. Median follow-up was 47 days (range 28-67). Baseline characteristics were similar between groups, although tocilizumab-treated patients were younger (mean 55 vs. 60 years), less likely to have chronic pulmonary disease (10% vs. 28%), and had lower D-dimer values at time of intubation (median 2.4 vs. 6.5 mg/dL). In IPTW-adjusted models, tocilizumab was associated with a 45% reduction in hazard of death [hazard ratio 0.55 (95% CI 0.33, 0.90)] and improved status on the ordinal outcome scale [odds ratio per 1-level increase: 0.59 (0.36, 0.95)]. Though tocilizumab was associated with an increased proportion of patients with superinfections (54% vs. 26%; p<0.001), there was no difference in 28-day case fatality rate among tocilizumab-treated patients with versus without superinfection [22% vs. 15%; p=0.42].\n\nInterpretationIn this cohort of mechanically ventilated COVID-19 patients, tocilizumab was associated with a decreased likelihood of death despite higher superinfection occurrence. Randomized controlled trials are urgently needed to confirm these findings.\n\nKEY POINTSO_ST_ABSQuestionC_ST_ABSCan therapy with the IL-6 receptor antagonist tocilizumab improve outcomes in patients with severe COVID-19 illness requiring mechanical ventilation?\n\nFindingsIn this observational, controlled study of 154 patients, receipt of tocilizumab was associated with a 45% reduction in the hazard of death, despite twice the frequency of superinfection (54% vs 26%), both of which were statistically significant findings.\n\nMeaningTocilizumab therapy may improve survival in patients with COVID-19 illness requiring mechanical ventilation. These results can inform clinical practice pending the results of randomized clinical trials.", + "rel_num_authors": 22, "rel_authors": [ { - "author_name": "Lina Marcela Parra", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Emily C Somers", + "author_inst": "University of Michigan" }, { - "author_name": "MIreia Cantero", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Gregory A Eschenauer", + "author_inst": "University of Michigan" }, { - "author_name": "Ignacio Morras", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Jonathan P Troost", + "author_inst": "University of Michigan" }, { - "author_name": "Alberto Vallejo", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Jonathan L Golob", + "author_inst": "University of Michigan" }, { - "author_name": "Itziar Diego", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Tejal N Gandhi", + "author_inst": "University of Michigan" }, { - "author_name": "Elena Jimenez-Tejero", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Lu Wang", + "author_inst": "University of Michigan" }, { - "author_name": "Elena Munez", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Nina Zhou", + "author_inst": "University of Michigan" }, { - "author_name": "Angel Asensio", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Lindsay A Petty", + "author_inst": "University of Michigan" }, { - "author_name": "Ana Fernandez-Cruz", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Ji Hoon Baang", + "author_inst": "University of Michigan" }, { - "author_name": "Antonio Ramos-Martinez", - "author_inst": "HU Puerta de Hierro-Majadahonda" + "author_name": "Nicholas O Dillman", + "author_inst": "University of Michigan" + }, + { + "author_name": "David Frame", + "author_inst": "University of Michigan" + }, + { + "author_name": "Kevin S Gregg", + "author_inst": "University of Michigan" + }, + { + "author_name": "Dan R Kaul", + "author_inst": "University of MIchigan" + }, + { + "author_name": "Jerod Nagel", + "author_inst": "University of Michigan" + }, + { + "author_name": "Twisha S Patel", + "author_inst": "University of Michigan" + }, + { + "author_name": "Shiwei Zhou", + "author_inst": "University of Michigan" + }, + { + "author_name": "Adam S Lauring", + "author_inst": "University of Michigan" + }, + { + "author_name": "David A Hanauer", + "author_inst": "University of Michigan" + }, + { + "author_name": "Emily Toth Martin", + "author_inst": "University of Michigan" + }, + { + "author_name": "Pratima Sharma", + "author_inst": "University of Michigan" + }, + { + "author_name": "Christopher M Fung", + "author_inst": "University of Michigan" + }, + { + "author_name": "Jason M Pogue", + "author_inst": "University of Michigan" } ], "version": "1", @@ -1422017,53 +1422295,61 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.28.122671", - "rel_title": "Optimized pseudotyping conditions for the SARS-COV2 Spike glycoprotein", + "rel_doi": "10.1101/2020.05.29.122986", + "rel_title": "Risk factors associated with mortality in hospitalized patients with SARS-CoV-2 infection. A prospective, longitudinal, unicenter study in Reus, Spain", "rel_date": "2020-06-03", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.28.122671", - "rel_abs": "The SARS-COV2 Spike glycoprotein is solely responsible for binding to the host cell receptor and facilitating fusion between the viral and host membranes. The ability to generate viral particles pseudotyped with SARS-COV2 Spike is useful for many types of studies, such as characterization of neutralizing antibodies or development of fusion-inhibiting small molecules. Here we characterized the use of a codon-optimized SARS-COV2 Spike glycoprotein for the generation of pseudotyped HIV-1, MLV, and VSV particles. The full-length Spike protein functioned inefficiently with all three systems but was enhanced over 10-fold by deleting the last 19 amino acids of the cytoplasmic tail of Spike. Infection of 293FT target cells was only possible if the cells were engineered to stably express the human ACE-2 receptor, but stably introducing an additional copy of this receptor did not further enhance susceptibility. Stable introduction of the Spike activating protease TMPRSS2 further enhanced susceptibility to infection by 5-10 fold. Substitution of the signal peptide of the Spike protein with an optimal signal peptide did not enhance or reduce infectious particle production. However, modification of a single amino acid in the furin cleavage site of Spike (R682Q) enhanced infectious particle production another 10-fold. With all enhancing elements combined, the titer of pseudotyped particles reached almost 106 infectious particles/ml. Finally, HIV-1 particles pseudotyped with SARS-COV2 Spike was successfully used to detect neutralizing antibodies in plasma from COVID-19 patients, but not plasma from uninfected individuals.\n\nImportanceWhen working with pathogenic viruses, it is useful to have rapid quantitative tests for viral infectivity that can be performed without strict biocontainment restrictions. A common way of accomplishing this is to generate viral pseudoparticles that contain the surface glycoprotein from the pathogenic virus incorporated into a replication-defective viral particle that contains a sensitive reporter system. These pseudoparticles enter cells using the glycoprotein from the pathogenic virus leading to a readout for infection. Conditions that block entry of the pathogenic virus, such as neutralizing antibodies, will also block entry of the viral pseudoparticles. However, viral glycoproteins often are not readily suited for generating pseudoparticles. Here we describe a series of modifications that result in the production of relatively high titer SARS-COV2 pseudoparticles that are suitable for detection of neutralizing antibodies from COVID-19 patients.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.29.122986", + "rel_abs": "Spain is one of the countries that has suffered the most from the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the strain that causes coronavirus disease 2019 (COVID-19). However, there is a lack of information on the characteristics of this disease in the Spanish population. The objective of this study has been to characterize our patients from an epidemiological point of view and to identify the risk factors associated with mortality in our geographical area. We performed a prospective, longitudinal study on 188 hospitalized cases of SARS-Cov-2 infection in Hospital Universitari de Sant Joan, in Reus, Spain, admitted between 15th March 2020 and 30th April 2020. We recorded demographic data, signs and symptoms and comorbidities. We also calculated the Charlson and McCabe indices. A total of 43 deaths occurred during the study period. Deceased patients were older than the survivors (77.7 {+/-} 13.1 vs. 62.8 {+/-} 18.4 years; p < 0.001). Logistic regression analyses showed that fever, pneumonia, acute respiratory distress syndrome, diabetes mellitus and cancer were the variables that showed independent and statistically significant associations with mortality. The Charlson index was more efficient than the McCabe index in discriminating between deceased and survivors. This is one of the first studies to describe the factors associated with mortality in patients infected with SARS-CoV-2 in Spain, and one of the few in the Mediterranean area. We identified the main factors independently associated with mortality in our population. Further studies in are needed to complete and confirm our findings.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Marc C Johnson", - "author_inst": "University of Missouri, School of Medicine" + "author_name": "Simona Iftime", + "author_inst": "HUSJR" }, { - "author_name": "Terri D Lyddon", - "author_inst": "University of Missouri" + "author_name": "Ana F L\u00f3pez-Azcona", + "author_inst": "HUSJR" }, { - "author_name": "Reinier Suarez", - "author_inst": "University of Missouri" + "author_name": "Manuel Vicente-Miralles", + "author_inst": "HUSJR" }, { - "author_name": "Braxton Salcedo", - "author_inst": "University of Missouri" + "author_name": "Ramon Descarrega-Reina", + "author_inst": "HUSJR" }, { - "author_name": "Mary LePique", - "author_inst": "University of Missouri" + "author_name": "Anna Hern\u00e1ndez-Aguilera", + "author_inst": "HUSJR" }, { - "author_name": "Maddie Graham", - "author_inst": "University of Missouri" + "author_name": "Francesc Riu", + "author_inst": "HUSJR" }, { - "author_name": "Clifton L Ricana", - "author_inst": "University of Missouri" + "author_name": "Josep M Sim\u00f3", + "author_inst": "HUSJR" }, { - "author_name": "Carolyn A Robinson", - "author_inst": "University of Missouri" + "author_name": "Pedro Garrido", + "author_inst": "HUSJR" }, { - "author_name": "Detlef G Ritter", - "author_inst": "University of Missouri Health System" + "author_name": "Jorge Joven", + "author_inst": "HUSJR" + }, + { + "author_name": "Jordi Camps", + "author_inst": "Hospital Universitari Sant Joan de Reus" + }, + { + "author_name": "Antoni Castro", + "author_inst": "HUSJR" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "new results", "category": "microbiology" }, @@ -1423187,57 +1423473,29 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.25.20112623", - "rel_title": "Serological surveys in Reunion Island of the first hospitalized patients revealed that long-lived immunoglobulin G antibodies specific against SARS-CoV2 virus are rapidly vanishing in severe cases", + "rel_doi": "10.1101/2020.05.22.20110387", + "rel_title": "Mathematical Modeling and Analysis of COVID-19 pandemic in Nigeria", "rel_date": "2020-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.25.20112623", - "rel_abs": "Both cellular and humoral immunities are critically important to control COVID19 infection but little is known about the kinetics of those responses and, in particular, in patients who will go on to develop a severe form of the disease over several weeks. We herein report the first set of data of our prospective cohort study of 90 hospitalized cases. Serological surveys were thoroughly performed over 2 month period by assessing IgG and IgM responses by immunofluorescence, immunoblot, Western blot and conventional ELISA using clinical RUN isolates of SARS-CoV-2 immobilized on 96 well plates. While the IgM and, unexpectedly, the IgG responses were readily detected early during the course of the disease (5-7 days post-first symptoms), our results (n=3-5 and over the full dilution set of the plasma 1/200 to 1/12800) demonstrated a significant decrease (over 2.5-fold) of IgG levels in severe (ICU) hospitalized patients (exemplified in patient 1) by WB and ELISA. In contrast, mild non-ICU patients had a steady and yet robust rise in their specific IgG levels against the virus. Interestingly, both responses (IgM and IgG) were initially against the nucleocapsid (50kDa band on the WB) and spreading to other major viral protein S and domains (S1 and S2. In conclusion, serological testing may be helpful for the diagnosis of patients with negative RT-PCR results and for the identification of asymptomatic cases. Moreover, medical care and protections should be maintained particularly for recovered patients (severe cases) who may remain at risk of relapsing or reinfection. Experiments to ascertain T cell responses but although their kinetics overtime are now highly warranted. All in all, these studies will help to delineate the best routes for vaccination.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20110387", + "rel_abs": "A novel Coronavirus (COVID-19), caused by SARS-CoV-2, emerged from the Wuhan city of China at the end of 2019, causing devastating public health and socio-economic burden around the world. In the absence of a safe and effective vaccine or antiviral for use in humans, control and mitigation efforts against COVID-19 are focused on using non-pharmaceutical interventions (aimed at reducing community transmission of COVID-19), such as social (physical)-distancing, community lockdown, use of face masks in public, isolation and contact tracing of confirmed cases and quarantine of people suspected of being exposed to COVID-19. We developed a mathematical model for understanding the transmission dynamics and control of COVID-19 in Nigeria, one of the main epicenters of COVID-19 in Africa. Rigorous analysis of the Kermack-McKendrick-type compartmental epidemic model we developed, which takes the form of a deterministic system of nonlinear differential equations, reveal that the model has a continuum of disease-free equilibria which is locally-asymptotically stable whenever a certain epidemiological threshold, called the control reproduction (denoted by [R]c), is less than unity. The epidemiological implication of this result is that the pandemic can be effectively controlled (or even eliminated) in Nigeria if the control strategies implemented can bring (and maintain) the epidemiological threshold ([R]c) to a value less than unity. The model, which was parametrized using COVID-19 data published by Nigeria Centre for Disease Control (NCDC), was used to assess the community-wide impact of various control and mitigation strategies in the entire Nigerian nation, as well as in two states (Kano and Lagos) within the Nigerian federation and the Federal Capital Territory (FCT Abuja). It was shown that, for the worst-case scenario where social-distancing, lockdown and other community transmission reduction measures are not implemented, Nigeria would have recorded a devastatingly high COVID-19 mortality by April 2021 (in hundreds of thousands). It was, however, shown that COVID-19 can be effectively controlled using social-distancing measures provided its effectiveness level is at least moderate. Although the use of face masks in the public can significantly reduce COVID-19 in Nigeria, its use as a sole intervention strategy may fail to lead to the realistic elimination of the disease (since such elimination requires unrealistic high compliance in face mask usage in the public, in the range of 80% to 95%). COVID-19 elimination is feasible in both the entire Nigerian nation, and the States of Kano and Lagos, as well as the FCT, if the public face masks use strategy (using mask with moderate efficacy, and moderate compliance in its usage) is complemented with a social-distancing strategy. The lockdown measures implemented in Nigeria on March 30, 2020 need to be maintained for at least three to four months to lead to the effective containment of COVID-19 outbreaks in the country. Relaxing, or fully lifting, the lockdown measures sooner, in an effort to re-open the economy or the country, may trigger a deadly second wave of the pandemic.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Anthony Dobi", - "author_inst": "Unite de recherche en Pharmaco-Immunologie (UR-EPI), Universite et CHU de la Reunion, St Denis" - }, - { - "author_name": "Etienne Frumence", - "author_inst": "Laboratoire immunologie Clinique et experimentale de la ZOI (LICE-OI), Pole de Biologie, CHU de la Reunion, St Denis" - }, - { - "author_name": "Mahary LALARIZO RAKOTO", - "author_inst": "Laboratoire immunologie Clinique et experimentale de la ZOI (LICE-OI), Pole de Biologie, CHU de la Reunion, St Denis" - }, - { - "author_name": "Gregorie Lebeau", - "author_inst": "Unite de recherche en Pharmaco-Immunologie (UR-EPI), Universite et CHU de la Reunion, St Denis" - }, - { - "author_name": "Damien Vagner", - "author_inst": "UMR PIMIT Processus infectieux en milieu Insulaire tropical CNRS 9192, INSERM1187, IRD 249, Universite de la Reunion, St Denis" - }, - { - "author_name": "Anne-Laure SANDENON SETEYEN", - "author_inst": "Unite de recherche en Pharmaco-Immunologie (UR-EPI), Universite et CHU de la Reunion, St Denis" - }, - { - "author_name": "Claude Giry", - "author_inst": "CNR associe arbovirus, Laboratoire de Microbiologie, Pole de Biologie, CHU de la Reunion, St Denis" - }, - { - "author_name": "Axelle Septembre-Malaterre", - "author_inst": "Unite de recherche en Pharmaco-Immunologie (UR-EPI), Universite et CHU de la Reunion, St Denis" + "author_name": "Enahoro A. Iboi", + "author_inst": "Arizona State University" }, { - "author_name": "Marie-Christine Jaffar-Bandjee", - "author_inst": "CNR associe arbovirus, Laboratoire de Microbiologie, Pole de Biologie, CHU de la Reunion, St Denis" + "author_name": "Oluwaseun O. Sharomi", + "author_inst": "Complete HEOR Solutions" }, { - "author_name": "Loic Raffray", - "author_inst": "Service de Medecine Interne, CHU de la Reunion, St Denis" + "author_name": "Calistus N. Ngonghala", + "author_inst": "University of Florida" }, { - "author_name": "Philippe Gasque", - "author_inst": "Unite de recherche en Pharmaco-Immunologie (UR-EPI), Universite et CHU de la Reunion, St Denis" + "author_name": "Abba B. Gumel", + "author_inst": "Arizona State University" } ], "version": "1", @@ -1424869,49 +1425127,41 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.05.27.20114512", - "rel_title": "Diagnostic accuracy of a host response point-of-care test for identifying COVID-19", + "rel_doi": "10.1101/2020.05.27.20115048", + "rel_title": "Correlation of the global spread of coronavirus disease-19 with atmospheric air temperature", "rel_date": "2020-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20114512", - "rel_abs": "RationaleManagement of the COVID-19 pandemic is hampered by long delays associated with centralised laboratory PCR testing. In hospitals this leads to poor patient flow and nosocomial transmission and rapid, accurate diagnostic tests are urgently required. The FebriDx is a point-of-care test that detects an antiviral host response protein in finger prick blood within 10 minutes, but its accuracy for the detection of COVID-19 is unknown.\n\nObjectivesTo evaluate the diagnostic accuracy of FebriDx in hospitalised patients during the first wave of the pandemic\n\nMethodsMeasures of diagnostic accuracy were calculated based on FebriDx results compared to the reference standard of PCR, and stratified by duration of symptoms. A multivariable predictive model was developed and underwent internal validation.\n\nResultsFebriDx was performed on 251 patients and gave a valid result in 248. 118 of 248 (48%) were PCR positive for COVID-19. Sensitivity of FebriDx for the identification of COVID-19 was 93% (110/118; 95% CI 87 to 97%) and specificity was 86% (112/130; 95%CI 79 to 92%). Positive and negative likelihood ratios were 6.73 (95%CI 4.37 to 10.37) and 0.08 (95%CI 0.04 to 0.15) respectively. In the multivariate model diagnosis of COVID-19 was not significantly influenced by clinical symptoms and signs, and FebriDx accuracy was not improved by restricting testing to those with duration of symptoms of less than seven days.\n\nConclusionsDuring the first wave of the pandemic, FebriDx had high sensitivity for the identification of COVID-19 in hospitalised adults and could be deployed as a front door triage tool.\n\nTrial registrationISRCTN14966673", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20115048", + "rel_abs": "Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an enveloped virus that may be sensitive to heat. We assessed whether the spread of coronavirus disease 2019 (COVID-19) correlates with air temperature. We also studied whether additional climate, geographical, and population variables were correlated. The total number of confirmed COVID-19 cases and mortality rates reported in each country between 1st Jan and 31st Mar 2020 were compared with the countrys three-month average atmospheric air temperature, precipitation and latitude. Spearmans correlation coefficient ({rho}) was used to identify significant correlations. Our analysis included a total of 748,555 confirmed COVID-19 cases worldwide. The total number of patients with COVID-19 decreased with increasing atmospheric air temperature ({rho} = -0.54, 95%CI: [-0.64, -0.42]; P <0.001) and increased with an increasing latitude ({rho} = 0.60, 95%CI: [0.48, 0.70]; P <0.001). Our findings justify further studies to examine the effect of air temperature on infectivity of SAR-CoV-2.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Tristan William Clark", - "author_inst": "University of Southampton" + "author_name": "Yihienew M. Bezabih", + "author_inst": "Arsi University College of Health Sciences" }, { - "author_name": "Nathan James Brendish", - "author_inst": "University of Southampton" + "author_name": "Alemitu Mequanint", + "author_inst": "Addis Ababa Science and Technology University" }, { - "author_name": "Stephen Poole", - "author_inst": "NIHR Southampton Biomedical Research Centre" - }, - { - "author_name": "Vasanth V Naidu", - "author_inst": "University Hospital Southampton NHS Foundation Trust" - }, - { - "author_name": "Christopher Mansbridge", - "author_inst": "University Hospital Southampton NHS FoundationTrust" + "author_name": "Endalkachew alamneh", + "author_inst": "University of Tasmania" }, { - "author_name": "Nicholas Norton", - "author_inst": "University Hospital Southampton NHS Foundation Trust" + "author_name": "Alemayehu Bezabih", + "author_inst": "Nantes-Atlantic National College of Veterinary Medicine, Food Science and Engineering (ONIRIS)" }, { - "author_name": "Helen Wheeler", - "author_inst": "University Hospital Southampton NHS Foundation Trust" + "author_name": "Wilber Sabiiti", + "author_inst": "University of St Andrews" }, { - "author_name": "Laura Presland", - "author_inst": "University Hospital Southampton NHS Foundation Trust" + "author_name": "Anna Roujeinikova", + "author_inst": "Monash University" }, { - "author_name": "Sean Ewings", - "author_inst": "Southampton Clinical Trials Unit, University of Southampton, UK" + "author_name": "Woldesellassie Bezabhe", + "author_inst": "University of Tasmania" } ], "version": "1", @@ -1427003,43 +1427253,75 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.28.20116046", - "rel_title": "Immunochromatographic assays for COVID-19 epidemiological screening: our experience", + "rel_doi": "10.1101/2020.05.31.20115154", + "rel_title": "Exhaled breath is a significant source of SARS-CoV-2 emission", "rel_date": "2020-06-02", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.28.20116046", - "rel_abs": "In March 2020, the World Health Organization (WHO) declared a pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Due to the absence of effective treatment or biomedical prevention, understanding potential post infection immunity has important implications for epidemiologic assessments. For this reason, increasing number of in vitro diagnostic companies are developing serological assays to detect antibodies against SARS-CoV-2, but most of them lack the validation by third parties in relation to their quality, limiting their usefulness. We submitted to serological screening by two different immunochromatographic (IC) rapid testing for detection of IgG and IgM against SARS-CoV-2, 151 asymptomatic or minimally symptomatic healthcare workers previously tested positive for SARS-CoV-2 RT-PCR in order to evaluate the performance of rapid assays. Results showed discrepancies between molecular and IC results, and an inconsistency of immunoglobulins positivity patterns when compared to ELISA/CLIA results, highlighting the absolute necessity of assays performance validation before their marketing and use, in order to avoid errors in the results evaluation at both clinical and epidemiological level.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20115154", + "rel_abs": "Despite notable efforts in airborne SARS-CoV-2 detection, no clear evidence has emerged to show how SARS-CoV-2 is emitted into the environments. Here, 35 COVID-19 subjects were recruited; exhaled breath condensate (EBC), air samples and surface swabs were collected and analyzed for SARS-CoV-2 using reverse transcription-polymerase chain reaction (RT-PCR). EBC samples had the highest positive rate (16.7%, n = 30), followed by surface swabs(5.4%, n = 242), and air samples (3.8%, n = 26). COVID-19 patients were shown to exhale SARSCoV-2 into the air at an estimated rate of 103-105 RNA copies/min; while toilet and floor surfaces represented two important SARS-CoV-2 reservoirs. Our results imply that airborne transmission of SARS-CoV-2 plays a major role in COVID-19 spread, especially during the early stages of the disease.\n\nOne Sentence SummaryCOVID-19 patient exhales millions of SARS-CoV-2 particles per hour", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Andrea Bartolini", - "author_inst": "LUM - Unified Metropolitan Laboratory, AUSL Bologna, Bologna, Italy" + "author_name": "Jianxin Ma", + "author_inst": "Center for Disease Control and Prevention of Chaoyang District of Beijing, Beijing, China" }, { - "author_name": "Margherita Scapaticci", - "author_inst": "LUM - Unified Metropolitan Laboratory, AUSL Bologna, Bologna, Italy" + "author_name": "Xiao Qi", + "author_inst": "Center for Disease Control and Prevention of Chaoyang District of Beijing, Beijing, China." }, { - "author_name": "Marina Bioli", - "author_inst": "LUM - Unified Metropolitan Laboratory, AUSL Bologna, Bologna, Italy" + "author_name": "Haoxuan Chen", + "author_inst": "College of Environmental Sciences and Engineering, Peking University, Beijing, China" }, { - "author_name": "Tiziana Lazzarotto", - "author_inst": "Microbiology Unit - Department of Experimental, Diagnostic and Specialty Medicine, S. Orsola -Malpighi University Hospital, Bologna, Italy" + "author_name": "Xinyue Li", + "author_inst": "College of Environmental Sciences and Engineering, Peking University, Beijing, China" + }, + { + "author_name": "Zheng Zhan", + "author_inst": "Center for Disease Control and Prevention of Chaoyang District of Beijing, Beijing, China" }, { - "author_name": "Maria Carla Re", - "author_inst": "Microbiology Unit - Department of Experimental, Diagnostic and Specialty Medicine, S. Orsola -Malpighi University Hospital, Bologna, Italy" + "author_name": "Haibin Wang", + "author_inst": "Center for Disease Control and Prevention of Chaoyang District of Beijing, Beijing, China" }, { - "author_name": "Rita Mancini", - "author_inst": "LUM - Unified Metropolitan Laboratory, AUSL Bologna, Bologna, Italy" + "author_name": "Lingli Sun", + "author_inst": "Center for Disease Control and Prevention of Chaoyang District of Beijing, Beijing, China" + }, + { + "author_name": "Lu Zhang", + "author_inst": "College of Environmental Sciences and Engineering, Peking University, Beijing, China" + }, + { + "author_name": "Jiazhen Guo", + "author_inst": "Beijing Ditan Hospital, Capital Medical University, Beijing, China" + }, + { + "author_name": "Lidia Morawska", + "author_inst": "Queensland University of Technology" + }, + { + "author_name": "Sergey A. Grinshpun", + "author_inst": "University of Cincinnati" + }, + { + "author_name": "Pratim Biswas", + "author_inst": "Washington University in St. Louis, St. Louis" + }, + { + "author_name": "Richard C. Flagan", + "author_inst": "California Institute of Technology" + }, + { + "author_name": "Maosheng Yao", + "author_inst": "Peking University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pathology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.05.27.20114066", @@ -1428633,21 +1428915,41 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.05.31.20118695", - "rel_title": "ON THE UNCERTAINTY ABOUT HERD IMMUNITY LEVELS REQUIRED TO STOP COVID-19 EPIDEMICS", + "rel_doi": "10.1101/2020.05.29.20100735", + "rel_title": "Psychosocial factors and hospitalisations for COVID-19: Prospective cohort study of the general population", "rel_date": "2020-06-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.31.20118695", - "rel_abs": "COVID-19 evolved into a pandemic in 2020 affecting more than 150 countries. Given the absence of a vaccine, discussion has taken place on the strategy of allowing the virus to spread in a population, to increase population \"herd immunity\". Knowledge of the minimum proportion of a population required to have recovered from COVID-19 infection in order to attain \"herd\" immunity, Pcrit, is important for formulating epidemiological policy. A method for measuring uncertainty about Pcrit based on a widely used package, EpiEstim, is derived. The procedure is illustrated using data from twelve countries at two early times during the COVID-19 epidemic. It is shown that simple plug-in measures of confidence on estimates of Pcrit are misleading, but that a full characterization of statistical uncertainty can be derived from EpiEstim, which reports percentiles only. Because of the important levels of uncertainty, it is risky to design epidemiological policy based on guidance provided by a single point estimate.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20100735", + "rel_abs": "ObjectiveTo examine the association of a range of psychosocial factors with hospitalisation for COVID-19.\n\nDesignProspective cohort study.\n\nSettingEngland.\n\nParticipantsUK Biobank comprises around half a million people who were aged 40 to 69 years at study induction between 2006 and 2010 when information on psychosocial factors and covariates were captured.\n\nMain outcome measureHospitalisation for COVID-19 in England between 16th March and 26th April 2020 as provided by Public Health England.\n\nResultsThere were 908 hospitalisations for COVID-19 in an analytical sample of 431,051 people. In age- and sex-adjusted analyses, an elevated risk of COVID-19 was related to disadvantaged levels of education (odds ratio; 95% confidence interval: 2.05; 1.70, 2.47), income (2.00; 1.63, 2,47), area deprivation (2.20; 1.86, 2.59), occupation (1.39; 1.14, 1.69), psychological distress (1.58; 1.32, 1.89), mental health (1.50; 1.25, 1.79), neuroticism (1.19; 1.00, 1.42), and performance on two tests of cognitive function - verbal and numerical reasoning (2.66; 2.06, 3.34) and reaction speed (1.27; 1.08, 1.51). These associations were graded (p-value for trend [≤]0.038) such that effects were apparent across the full psychosocial continua. After mutual adjustment for these characteristics plus ethnicity, comorbidity, and lifestyle factors, only the relationship between lower cognitive function as measured using the reasoning test and a doubling in the risk of the infection remained (1.98; 1.38, 2.85).\n\nConclusionA range of psychosocial factors revealed associations with hospitalisations for COVID-19 of which the relation with cognitive function was most robust to statistical adjustment.\n\nBoxO_LSTWhat is already known on this subjectC_LSTO_LIGiven the recent discovery of COVID-19, its risk factors are not well understood.\nC_LIO_LIThe little evidence that is available has been gleaned from prognostic studies of disease progression and death.\nC_LIO_LIWe are not aware of any studies examining the role of psychosocial factors in the prevention of serious cases of the infection.\nC_LI\n\nO_LSTWhat this study addsC_LSTO_LIA higher risk of hospitalisation for COVID-19 was evident at disadvantaged levels of education, income, area deprivation, occupation, mental health, neuroticism, and cognitive function.\nC_LIO_LIAfter taking into account multiple confounding factors, the strongest association was apparent for cognitive function, a potential marker of health literacy.\nC_LI", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "DANIEL GIANOLA", - "author_inst": "UNIVERSITY OF WISCONSIN-MADISON" + "author_name": "George David Batty", + "author_inst": "University College London" + }, + { + "author_name": "Ian Deary", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Michelle Luciano", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Drew Altschul", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Mika Kivimaki", + "author_inst": "University College London" + }, + { + "author_name": "Catharine Gale", + "author_inst": "University of Southampton" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1429982,51 +1430284,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.29.124610", - "rel_title": "COVID-3D: An online resource to explore the structural distribution of genetic variation in SARS-CoV-2 and its implication on therapeutic development", + "rel_doi": "10.1101/2020.05.29.20116483", + "rel_title": "Mortality and use of angiotensin converting enzyme inhibitors in Covid 19 disease - a systematic review.", "rel_date": "2020-05-30", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.29.124610", - "rel_abs": "The emergence of the COVID-19 pandemic has spurred a global rush to uncover basic biological mechanisms, to inform effective vaccine and drug development. Despite viral novelty, global sequencing efforts have already identified genomic variation across isolates. To enable easy exploration and spatial visualization of the potential implications of SARS-CoV-2 mutations on infection, host immunity and drug development we have developed COVID-3D (http://biosig.unimelb.edu.au/covid3d/).", - "rel_num_authors": 8, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.29.20116483", + "rel_abs": "BackgroundInterest exits concerning the use of angiotensin converting enzyme inhibitors (ACEi) in patients with Covid-19 disease.\n\nObjectivesTo perform a systematic review on mortality associated to the use of ACEi in patients with Covid 19 disease.\n\nMethodsSearch in Medline (PubMed), in ISI Web of Knowledge and in medRxiv database; use of other sources.\n\nResultsA total of 33 articles were evaluated. Concerning the papers used to produce the meta-analyses, seven studies were selected, five of which were used. These five studies involved a total number of 944 patients treated with ACEi and 5173 not treated with ACEi. Increased mortality was seen in association to the use of ACEi in the context of Covid-19 disease (ACEi users versus non-users; odds ratio, 1.48; 95% confidence interval [CI], 1.02 to 2.15; P=0.04). When compared to mortality in patients treated with angiotensin receptor blockers, mortality of patients treated with ACEi was not significantly different (odds ratio, 0.96; 95% confidence interval [CI], 0.76 to 1.21; P=0.74). Concerning the remaining reports, different types of data adjustments were used by several authors, after which increased mortality was not seen in association to the use of ACEi in this context.\n\nConclusionsACEi use could act as a marker of increased mortality risk in some but not all Covid-19 disease settings. The data now presented do not prove a causal relation but argue in favor of carrying out clinical trials studying ACEi in Covid-19 patients, in order to establish the safety of ACEi use in this context.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Stephanie Portelli", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Moshe Olshansky", - "author_inst": "Baker Heart and Diabetes Institute" - }, - { - "author_name": "Carlos Henrique Miranda Rodrigues", - "author_inst": "University of Melbourne" - }, - { - "author_name": "YooChan Myung", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Michael Silk", - "author_inst": "University of Melbourne" - }, - { - "author_name": "Azadeh Alavi", - "author_inst": "Baker Heart and Diabetes Institute" - }, - { - "author_name": "Douglas E.V. Pires", - "author_inst": "University of Melbourne" - }, - { - "author_name": "David B. Ascher", - "author_inst": "University of Melbourne" + "author_name": "Jose Pedro L. Nunes", + "author_inst": "Faculdade de Medicina da Universidade do Porto" } ], "version": "1", - "license": "cc_by_nc_nd", - "type": "new results", - "category": "bioinformatics" + "license": "cc_no", + "type": "PUBLISHAHEADOFPRINT", + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2020.05.29.20116004", @@ -1431824,33 +1432098,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.28.20115980", - "rel_title": "Restarting after COVID-19: A Data-driven Evaluation of Opening Scenarios", + "rel_doi": "10.1101/2020.05.28.20115949", + "rel_title": "Socioeconomic disparities in subway use and COVID-19 outcomes in New York City", "rel_date": "2020-05-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.28.20115980", - "rel_abs": "To contain the COVID-19 pandemic, several governments introduced strict Non-Pharmaceutical Interventions (NPI) that restricted movement, public gatherings, national and international travel, and shut down large parts of the economy. Yet, the impact of the enforcement and subsequent loosening of these policies on the spread of COVID-19 is not well understood. Accordingly, we measure the impact of NPI on mitigating disease spread by exploiting the spatio-temporal variations in policy measures across the 16 states of Germany. This quasi-experiment identifies each policys effect on reducing disease spread. We adapt the SEIR (Susceptible-Exposed-Infected-Recovered) model for disease propagation to include data on daily confirmed cases, intra- and inter-state movement, and social distancing. By combining the model with measures of policy contributions on mobility reduction, we forecast scenarios for relaxing various types of NPIs. Our model finds that, in Germany, policies that mandated contact restrictions (e.g., movement in public space limited to two persons or people co-living), initial business closures (e.g., restaurant closures), stay-at-home orders (e.g., prohibition of non-essential trips), non-essential services (e.g., florists, museums) and retail outlet closures led to the sharpest drops in movement within and across states. Contact restrictions were the most effective at lowering infection rates, while border closures had only minimal effects at mitigating the spread of the disease, even though cross-border travel might have played a role in seeding the disease in the population. We believe that a deeper understanding of the policy effects on mitigating the spread of COVID-19 allows a more accurate forecast of the disease spread when NPIs are (partially) loosened, and thus also better informs policymakers towards making appropriate decisions.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.28.20115949", + "rel_abs": "BackgroundThe United States CDC has reported that racial and ethnic disparities in the COVID-19 pandemic may in part be due to socioeconomic disadvantages that require individuals to continue to work outside their home and a lack of paid sick leave.1 However, data-driven analyses of the socioeconomic determinants of COVID-19 burden are still needed. Using data from New York City (NYC), we aimed to determine how socioeconomic factors impact human mobility and COVID-19 burden.\n\nMethods/SummaryNew York City has a large amount of heterogeneity in socioeconomic status (SES) and demographics among neighborhoods. We used this heterogeneity to conduct a cross-sectional spatial analysis of the associations between human mobility (i.e., subway ridership), sociodemographic factors, and COVID-19 incidence as of April 26, 2020. We also conducted a secondary analysis of NYC boroughs (which are equivalent to counties in the city) to assess the relationship between the decline in subway use and the time it took for each borough to end the exponential growth period of COVID-19 cases.\n\nFindingsAreas with lower median income, a greater percentage of individuals who identify as non-white and/or Hispanic/Latino, a greater percentage of essential workers, and a greater percentage of healthcare workers had more subway use during the pandemic. When adjusted for the percent of essential workers, these association do not remain; this suggests essential work is what drives subway use in lower SES zip codes and communities of color. Increased subway use was associated with a higher rate of COVID-19 cases per 100,000 population when adjusted for testing effort (aRR = 1.11; 95% CI: 1.03 - 1.19), but this association was weaker once we adjusted for median income (aRR = 1.06; 95% CI: 1.00 - 1.12). All sociodemographic variables were significantly associated with the rate of positive cases per 100,000 population when adjusting for testing effort (except percent uninsured) and adjusting for both income and testing effort. The risk factor with the strongest association with COVID-19 was the percent of individuals in essential work (aRR = 1.59, 95% CI: 1.36 - 1.86). We found that subway use declined prior to any executive order, and there was an estimated 28-day lag between the onset of reduced subway use and the end of the exponential growth period of SARS-CoV-2 within New York City boroughs.\n\nInterpretationOur results suggest that the ability to stay home during the pandemic has been constrained by SES and work circumstances. Poorer neighborhoods are not afforded the same reductions in mobility as their richer counterparts. Furthermore, lower SES neighborhoods have higher disease burdens, which may be due to inequities in ability to shelter-in-place, and/or due to the plethora of other existing health disparities that increase vulnerability to COVID-19. Furthermore, the extended lag time between the dramatic fall in subway ridership and the end of the exponential growth phase for COVID-19 cases is important for future policy, because it demonstrates that if there is a resurgence, and stay-at-home orders are re-issued, then cities can expect to wait a month before reported cases will plateau.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Ashwin Aravindakshan", - "author_inst": "University of California, Davis" + "author_name": "Karla Therese L. Sy", + "author_inst": "Boston University" }, { - "author_name": "Jorn Boehnke", - "author_inst": "University of California, Davis" + "author_name": "Micaela E. Martinez", + "author_inst": "Columbia University" }, { - "author_name": "Ehsan Gholami", - "author_inst": "University of California, Davis" + "author_name": "Benjamin Rader", + "author_inst": "Boston University" }, { - "author_name": "Ashutosh Nayak", - "author_inst": "University of California, Davis" + "author_name": "Laura F. White", + "author_inst": "Boston University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1433114,25 +1433388,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.27.20111955", - "rel_title": "Age separation dramatically reduces COVID-19 mortality rate in a computational model of a large population", + "rel_doi": "10.1101/2020.05.27.20115212", + "rel_title": "Monitoring and forecasting the number of reported and unreported cases of the COVID-19 epidemic in Brazil using Particle Filter", "rel_date": "2020-05-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20111955", - "rel_abs": "COVID-19 pandemic has caused a global lock down in many countries throughout the world. Faced with a new reality, and until a vaccine or efficient treatment is found, humanity must figure out ways to keep economy going on one hand, yet keep the population safe on the other hand, especially those that are susceptible to this virus. Here we use a network simulation, with parameters that were drawn from what is known about the virus, to explore 5 different scenarios of partial lock down release. We find that separating age groups by reducing interactions between age groups, protects the general population and reduces mortality rates. Furthermore, addition of new connections within the same age group to compensate for the lost connections outside the age group, still has a strong beneficial influence and reduces the total death toll by 66%. While complete isolation from society may be the most protective scenario for the elderly population, it would have an emotional and possibly cognitive impact that might outweigh its benefit. We therefore propose creating age-related social recommendations or even restrictions, thereby allowing social connections but still strong protection for the older population.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20115212", + "rel_abs": "In this paper, we combine algorithm of Liu & West for the Particle Filter (PF) with SIRU-type epidemic model to monitor and forecast cases of Covid-19 in Brazil from February up to September. We filter the number of cumulative reported cases and estimate model parameters and more importantly unreported infectious cases (asymptomatic and symptomatic infectious individuals). The parameters under study are related to the attenuation factor of the transmission rate and the fraction of asymptomatic infectious becoming reported as symptomatic infectious. Initially, the problem is analysed through Particle Swarm Optimization (PSO) based simulations to provide initial guesses, which are then refined by means of PF simulations. Subsequently, two additional steps are performed to verify the capability of the adjusted model to predict and forecast new cases. According to the results, the pandemic peak is expected to take place in mid-June 2020 with about 25,000 news cases per day. As medical and hospital resources are limited, this result shows that public health interventions are essential and should not be relaxed prematurely, so that the coronavirus pandemic is controlled and conditions are available for the treatment of the most severe cases.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Liron Mizrahi", - "author_inst": "University of Haifa" + "author_name": "JULIO CESAR SAMPAIO DUTRA", + "author_inst": "Federal University of Espirito Santo" }, { - "author_name": "Shani Stern", - "author_inst": "University of Haifa" + "author_name": "Wellington Betencurte da Silva", + "author_inst": "Federal University of Espirito Santo" + }, + { + "author_name": "Jose Mir Justino da Costa", + "author_inst": "Federal University of Amazonas" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1434344,61 +1434622,45 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.05.27.20114652", - "rel_title": "A SARS-CoV-2 serological assay to determine the presence of blocking antibodies that compete for human ACE2 binding", + "rel_doi": "10.1101/2020.05.27.20113969", + "rel_title": "Correlation of population mortality of COVID-19 and testing coverage: a comparison among 36 OECD countries and Taiwan", "rel_date": "2020-05-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20114652", - "rel_abs": "As SARS-CoV-2 continues to spread around the world, there is an urgent need for new assay formats to characterize the humoral response to infection. Convalescent serum is being used for treatment and for isolation of patient-derived antibodies. However, currently there is not a simple means to estimate serum bulk neutralizing capability. Here we present an efficient competitive serological assay that can simultaneously determine an individuals seropositivity against the SARS-CoV-2 Spike protein and estimate the neutralizing capacity of anti-Spike antibodies to block interaction with the human angiotensin converting enzyme 2 (ACE2) required for viral entry. In this ELISA-based assay, we present natively-folded viral Spike protein receptor binding domain (RBD)-containing antigens via avidin-biotin interactions. Sera are then supplemented with soluble ACE2-Fc to compete for RBD-binding serum antibodies, and antibody binding quantified. Comparison of signal from untreated serum and ACE2-Fc-treated serum reveals the presence of antibodies that compete with ACE2 for RBD binding, as evidenced by loss of signal with ACE2-Fc treatment. In our test cohort of nine convalescent SARS-CoV-2 patients, we found all patients had developed anti-RBD antibodies targeting the epitope responsible for ACE2 engagement. This assay provides a simple and high-throughput method to screen patient sera for potentially neutralizing anti-Spike antibodies to enable identification of candidate sera for therapeutic use.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20113969", + "rel_abs": "Although testing is widely regarded as critical to fighting the Covid-19 pandemic, what measure and level of testing best reflects successful infection control remains unresolved. Our aim was to compare the sensitivity of two testing metrics-population testing number and testing coverage-to population mortality outcomes and identify a benchmark for testing adequacy with respect to population mortality and capture of potential disease burden. This ecological study aggregated publicly available data through April 12 on testing and outcomes related to COVID-19 across 36 OECD (Organization for Economic Development) countries and Taiwan. All OECD countries and Taiwan were included in this population-based study as a proxy for countries with highly developed economic and healthcare infrastructure. Spearman correlation coefficients were calculated between the aforementioned metrics and following outcome measures: deaths per 1 million people, case fatality rate, and case proportion of critical illness. Fractional polynomials were used to generate scatter plots to model the relationship between the testing metrics and outcomes. Testing coverage, but not population testing number, was highly correlated with population mortality (rs= -0.79, P=5.975e-09 vs rs = - 0.3, P=0.05) and case fatality rate (rs= -0.67, P=9.067e-06 vs rs= -0.21, P=0.20). A testing coverage threshold of 15-45 signified adequate testing: below 15, testing coverage was associated with exponentially increasing population mortality, whereas above 45, increased testing did not yield significant incremental mortality benefit. Testing coverage was better than population testing number in explaining country performance and can be used as an early and sensitive indicator of testing adequacy and disease burden. This may be particularly useful as countries consider re-opening their economies.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "James R. Byrnes", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Xin X. Zhou", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Irene Lui", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Susanna K. Elledge", - "author_inst": "University of California, San Francisco" - }, - { - "author_name": "Jeff E. Glasgow", - "author_inst": "University of California, San Francisco" + "author_name": "Wei Chen", + "author_inst": "Harvard Medical School, Boston, USA" }, { - "author_name": "Shion A. Lim", - "author_inst": "University of California, San Francisco" + "author_name": "Chien-Chang Lee", + "author_inst": "National Taiwan University Hospital" }, { - "author_name": "Rita Loudermilk", - "author_inst": "University of California, San Francisco" + "author_name": "Tzu-Chun Hsu", + "author_inst": "National Taiwan University Hospital" }, { - "author_name": "Charles Y. Chiu", - "author_inst": "University of California, San Francisco" + "author_name": "Wan-Ting Hsu", + "author_inst": "Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, USA" }, { - "author_name": "Michael R. Wilson", - "author_inst": "University of California, San Francisco" + "author_name": "Chang-Chuan Chan", + "author_inst": "College of Public Health, National Taiwan University" }, { - "author_name": "Kevin K. Leung", - "author_inst": "University of California, San Francisco" + "author_name": "Shyr-Chyr Chen", + "author_inst": "National Taiwan University Hospital" }, { - "author_name": "James A. Wells", - "author_inst": "University of California, San Francisco" + "author_name": "Chien-Jen Chen", + "author_inst": "Genomics Research Center, Academia Sinica, Taipei, Taiwan" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1435646,29 +1435908,25 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2020.05.26.20113886", - "rel_title": "COVID-19 (SARS-CoV-2) Ventilator Resource Management Using a Network Optimization Model and Predictive System Demand", + "rel_doi": "10.1101/2020.05.27.20113803", + "rel_title": "A vulnerability index for COVID-19: spatial analysis to inform equitable response in Kenya", "rel_date": "2020-05-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.26.20113886", - "rel_abs": "The COVID-19 (SARS-CoV-2) pandemic is overwhelming global healthcare delivery systems due to the exponential spike in cases requiring specialty tests, facilities and equipment, including complex, precision devices like ventilators. In particular, the surge in critically ill patients has revealed a significant deficiency in regional availability of respiratory care ventilators. The authors offer a mathematical framework for ventilator distribution under scarcity conditions using an optimized network model and solver. The framework is interoperable with existing COVID-19 healthcare demand models and scales for different user-defined system sizes, including hospital networks, city, state, regional and national-scale prioritization. The authors approach improves current capabilities for medical device resource management within the existing incident command system while accounting for availability of devices, ventilation treatment time periods, disinfection and cleaning between patients, as well as shipping logistics time. The authors present a proof of concept using a high fidelity COVID-19 data set from Colorado, discusses how to scale nationally, and emphasizes the importance of applying ethical human-in-the-loop decision making when using this or similar approaches to managing medical device resources during epidemic emergencies.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20113803", + "rel_abs": "BackgroundResponse to the COVID-19 pandemic calls for precision public health reflecting our improved understanding of who is the most vulnerable and their geographical location. We created three vulnerability indices to identify areas and people who require greater support while elucidating health inequities to inform emergency response in Kenya.\n\nMethodsGeospatial indicators were assembled to create three vulnerability indices; social (SVI), epidemiological (EVI) and a composite of the two (SEVI) resolved at 295 sub-counties in Kenya. SVI included nineteen indicators that affect the spread of disease; socio-economic inequities, access to services and population dynamics while EVI comprised five indicators describing comorbidities associated with COVID-19 severe disease progression. The indicators were scaled to a common measurement scale, spatially overlaid via arithmetic mean and equally weighted. The indices were classified into seven classes, 1-2 denoted low-vulnerability and 6-7 high-vulnerability. The population within vulnerabilities classes was quantified.\n\nResultsThe spatial variation of each index was heterogeneous across Kenya. Forty-nine north-western and partly eastern sub-counties (6.9 m people) were highly vulnerable while 58 sub-counties (9.7 m people) in western and central Kenya were the least vulnerable for SVI. For EVI, 48 sub-counties (7.2 m people) in central and the adjacent areas and 81 sub-counties (13.2 m people) in northern Kenya were the most and least vulnerable respectively. Overall (SEVI), 46 sub-counties (7.0 m people) around central and south-eastern were more vulnerable while 81 sub-counties (14.4 m people) that were least vulnerable.\n\nConclusionThe vulnerability indices created are tools relevant to the county, national government and stakeholders for prioritization and improved planning especially in highly vulnerable sub-counties where cases have not been confirmed. The heterogeneous nature of the vulnerability highlights the need to address social determinants of health disparities, strengthen the health system and establish programmes to cushion against the negative effects of the pandemic.\n\nSummaryO_ST_ABSKey questionsC_ST_ABSO_LSTWhat is already known?C_LSTO_LIDisasters and adverse health events such as epidemics and pandemics disproportionately affect population with significantly higher impacts on the most vulnerable and less resilient communities.\nC_LIO_LISignificant health, socio-economic, demographic and epidemiological disparities exist within Kenya when considering individual determinants, however, little is known about the spatial variation and inequities of their concurrence.\nC_LI\n\nO_LSTWhat are the new findings?C_LSTO_LISub-counties in the north-western and partly eastern Kenya are most vulnerable when considering social vulnerability index while central and south-east regions are most vulnerable based on the epidemiological vulnerability index affecting approximately 6.9 million and 7.2 million people respectively.\nC_LIO_LIThe combined index of social and epidemiological vulnerabilities shows that on average, 15% (7.0 million) of Kenyans reside in the most vulnerable sub-counties mainly located in the central and south-eastern parts of Kenya.\nC_LI\n\nO_LSTWhat do the new findings imply?C_LSTO_LITargeted interventions that cushion against negative effects to the most vulnerable sub-counties are essential to respond to the current COVID-19 pandemic.\nC_LIO_LIImplementation of strategies that address the socioeconomic determinants of health disparities and strengthening health systems is crucial to effectively prevent, detect and respond to future adverse health events or disasters in the country.\nC_LIO_LINeed for better quality data to define a robust vulnerability index at high spatial resolution that can be adapted and used in response to future disasters and adverse health events in the long run.\nC_LI", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Samuel Billingham", - "author_inst": "The MITRE Corporation" - }, - { - "author_name": "Rebecca Widrick", - "author_inst": "The MITRE Corporation" + "author_name": "Peter M Macharia", + "author_inst": "Population Health Unit, KEMRI Wellcome Trust Research Programme" }, { - "author_name": "Nathan J Edwards", - "author_inst": "The MITRE Corporation" + "author_name": "Noel K Joseph", + "author_inst": "Population Health Unit, KEMRI-Wellcome Trust Research Programme" }, { - "author_name": "Sybil Klaus", - "author_inst": "The MITRE Corporation" + "author_name": "Emelda A Okiro", + "author_inst": "Population Health Unit, KEMRI-Wellcome Trust Research Programme" } ], "version": "1", @@ -1437132,23 +1437390,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.26.20112680", - "rel_title": "Fast initial Covid-19 response means greater caution may be needed later", + "rel_doi": "10.1101/2020.05.26.20113787", + "rel_title": "COVID-Net: A deep learning based and interpretable predication model for the county-wise trajectories of COVID-19 in the United States", "rel_date": "2020-05-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.26.20112680", - "rel_abs": "BackgroundAs the Covid-19 pandemic unfolds it is becoming increasingly clear that the strength of the first wave of the epidemic varies significantly between countries. In this study a simple numerical model is used to illustrate the impact the timing of initial measures against Covid-19 has on the first wave of infection and possible implications this may have for the measures taken as the first wave is ebbing. The results highlight that delaying measures by 10 days is sufficient to largely account for the differences seen between countries such as the UK and Germany for the first wave of infections. A pronounced first wave means that a larger fraction of the total population will have been infected and is therefore likely to display immunity. Even if this fraction is far below the level needed for \"herd immunity\" the effective reproduction factor Re is decreased compared to a population that had no prior exposure to the virus. Even a small reduction in Re can have major influence on the evolution of the epidemic after the first wave of infections. A large first wave means the resulting value for Re will be lower than if the first wave was mild. Without either vaccine or effective treatment countries that experienced a small first wave should therefore relax measures at a slower pace than countries where the first wave was strong.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.26.20113787", + "rel_abs": "The cases of COVID-19 have been reported in the United States since January 2020. There were over 103 million confirmed cases and over one million deaths as of March 23, 2023. We propose a COVINet by combining the architecture of both Long Short-Term Memory and Gated Recurrent Unit and incorporating actionable covariates to offer high-accuracy prediction and explainable response. First, we train COVINet models for confirmed cases and total deaths with five input features, compare their Mean Absolute Errors (MAEs) and Mean Relative Errors (MREs) and benchmark COVINet against ten competing models from the United States CDC in the last four weeks before April 26, 2021. The results show that COVINet outperforms all competing models for MAEs and MREs when predicting total deaths. Then, we focus on the prediction for the most severe county in each of the top 10 hot-spot states using COVINet. The MREs are small for all predictions made in the last 7 or 30 days before March 23, 2023. Beyond predictive accuracy, COVINet offers high interpretability, enhancing the understanding of pandemic dynamics. This dual capability positions COVINet as a powerful tool for informing effective strategies in pandemic prevention and governmental decision-making.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Joel Joel-Marie Hirschi", - "author_inst": "National Oceanography Centre" + "author_name": "Yukang Jiang", + "author_inst": "School of Mathematics, Sun Yat-sen University" + }, + { + "author_name": "Ting Tian", + "author_inst": "School of Mathematics, Sun Yat-sen University" + }, + { + "author_name": "Wenting Zhou", + "author_inst": "School of Mathematics, Sun Yat-sen University" + }, + { + "author_name": "Yuting Zhang", + "author_inst": "School of Mathematics, Sun Yat-sen University" + }, + { + "author_name": "Zhongfei Li", + "author_inst": "School of Management, Sun Yat-sen University" + }, + { + "author_name": "Xueqin Wang", + "author_inst": "University of Science and Technology of China" + }, + { + "author_name": "Heping Zhang", + "author_inst": "School of Public Health, Yale University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.05.26.20113514", @@ -1438810,29 +1439092,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.26.20113761", - "rel_title": "Differentiating COVID-19 from other types of pneumonia with convolutional neural networks", + "rel_doi": "10.1101/2020.05.27.20112888", + "rel_title": "Evaluation of performance of two SARS-CoV-2 Rapid whole-blood finger-stick IgM-IgGCombined Antibody Tests", "rel_date": "2020-05-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.26.20113761", - "rel_abs": "INTRODUCTIONA widely-used method for diagnosing COVID-19 is the nucleic acid test based on real-time reverse transcriptase-polymerase chain reaction (RT-PCR). However, the sensitivity of real time RT-PCR tests is low and it can take up to 8 hours to receive the test results. Radiologic methods can provide higher sensitivity. The aim of this study is to investigate the use of X-ray and convolutional neural networks for the diagnosis of COVID-19 and to differentiate it from viral and/or bacterial pneumonia, as 2-class (bacterial pneumonia vs COVID-19 and viral pneumonia vs COVID-19) and 3- class (bacterial pneumonia, COVID-19, and healthy group (BCH), and among viral pneumonia, COVID- 19, and healthy group (VCH)) experiments.\n\nMETHODS225 COVID-19, 1,583 healthy control, 2,780 bacterial pneumonia, and 1,493 viral pneumonia chest X-ray images were used. 2-class- and 3-class-experiments were performed with different convolutional neural network (ConvNet) architectures, with different variations of convolutional layers and fully-connected layers.\n\nRESULTSThe results showed that bacterial pneumonia vs COVID-19 and viral pneumonia vs COVID- 19 reached a mean ROC AUC of 97.32% and 96.80%, respectively. In the 3-class-experiments, macro-average F1 scores of 95.79% and 94.59% were obtained in terms of detecting COVID-19 among BCH and VCH, respectively.\n\nCONCLUSIONSThe ConvNet was able to distinguish the COVID-19 images among non-COVID-19 images, namely bacterial and viral pneumonia as well as normal X-ray images.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.27.20112888", + "rel_abs": "BackgroundThe SARS-CoV-2 virus is responsible for the infectious respiratory disease called COVID-19 (COronaVIrus Disease). In response to the growing COVID-19 pandemic, Rapid Diagnostic Tests (RDTs) have been developed to detect specific antibodies, IgG and IgM, to SARS-CoV-2 virus in human whole blood. We conducted a real-life study to evaluate the performance of two RDTs, COVID-PRESTO(R) and COVID-DUO(R), compared to the gold standard, RT-PCR.\n\nMethodsRT-PCR testing of SARS-Cov-2 was performed from nasopharyngeal swab specimens collected in adult patients visiting the infectious disease department at the hospital (Orleans, France). Fingertip whole blood samples taken at different time points after onset of the disease were tested with RDTs. The specificity and sensitivity of the rapid test kits compared to test of reference (RT-PCR) were calculated.\n\nResultsAmong 381 patients with symptoms of COVID-19 who went to the hospital for a diagnostic, 143 patients were RT-PCR negative. Results of test with RDTs were all negative for these patients, indicating a specificity of 100% for both RDTs.\n\nIn the RT-PCR positive subgroup (n=238), 133 patients were tested with COVID-PRESTO(R) and 129 patients were tested with COVID-DUO(R) (24 patients tested with both). The further the onset of symptoms was from the date of collection, the greater the sensitivity. The sensitivity of COVID-PRESTO(R) test ranged from 10.00% for patients having experienced their 1st symptoms from 0 to 5 days ago to 100% in patients where symptoms had occurred more than 15 days before the date of tests. For COVID-DUO(R) test, the sensitivity ranged from 35.71% [0-5 days] to 100% (> 15 days).\n\nConclusionCOVID-PRESTO(R) and DUO(R) RDTs turned out to be very specific (none false positive) and to be sensitive enough after 15 days from onset of symptom. These easy to use IgG/IgM combined test kits are the first ones allowing a screening with capillary blood sample, by typing from a finger prick. These rapid tests are particularly interesting for screening in low resource settings.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Ilker Ozsahin", - "author_inst": "Near East University" + "author_name": "Thierry Prazuck", + "author_inst": "CHR Orleans, Department of infectious and tropical diseases" }, { - "author_name": "Confidence Onyebuchi", - "author_inst": "Cyprus International University" + "author_name": "Mathilda Colin", + "author_inst": "Department of infectious and tropical diseases, CHR Orleans" }, { - "author_name": "Boran Sekeroglu", - "author_inst": "Near East University" + "author_name": "Susanna Giache", + "author_inst": "Department of infectious and tropical diseases, CHR Orleans" + }, + { + "author_name": "Camelia Gubavu", + "author_inst": "Department of infectious and tropical diseases, CHR Orleans" + }, + { + "author_name": "Aymeric Seve", + "author_inst": "Department of infectious and tropical diseases, CHR Orleans" + }, + { + "author_name": "Vincent Rzepecki", + "author_inst": "Department of infectious and tropical diseases, CHR Orleans" + }, + { + "author_name": "Marie Chevereau-Choquet", + "author_inst": "Department of infectious and tropical diseases" + }, + { + "author_name": "Catherine Kiani", + "author_inst": "Department of infectious and tropical diseases, CHR Orleans" + }, + { + "author_name": "Victor Rodi", + "author_inst": "Department of infectious and tropical diseases, CHR Orleans" + }, + { + "author_name": "Elsa Lyonnet", + "author_inst": "Department of infectious and tropical diseases, CHR Orleans" + }, + { + "author_name": "Laura Courtellemont", + "author_inst": "Department of virology, CHR Orleans" + }, + { + "author_name": "Jerome Guinard", + "author_inst": "Department of virology, CHR Orleans" + }, + { + "author_name": "Gilles Pialoux", + "author_inst": "Department of infectious diseases, Hopital Tenon" + }, + { + "author_name": "Laurent Hocqueloux", + "author_inst": "Department of infectious and tropical diseases, CHR Orleans" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1440260,27 +1440586,43 @@ "category": "otolaryngology" }, { - "rel_doi": "10.1101/2020.05.19.20106575", - "rel_title": "Mitigation Policies and Emergency Care Management in Europe's Ground Zero for COVID-19", + "rel_doi": "10.1101/2020.05.19.20106641", + "rel_title": "Study Data Element Mapping: Feasibility of Defining Common Data Elements Across COVID-19 Studies", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20106575", - "rel_abs": "This paper draws from daily death registry data on 4,000 Italian municipalities to investigate two crucial policies that can dramatically affect the toll of COVID-19: the shutdown of non-essential businesses and the management of the emergency care system. Our results, which are robust to controlling for a host of co-factors, offer strong evidence that the closure of service activities is very effective in reducing COVID-19 mortality - this was about 15% lower in municipalities with a 10 percentage points higher employment share in shut down services. Shutting down factories, instead, is much less effective, plausibly because factory workers engage in more limited physical interactions relative to those in the consumer-facing service sector. Concerning the management of the health care system, we find that mortality strongly increases with distance from the intensive care unit (ICU). Municipalities at 10 km from the closest ICU experienced up to 50% higher mortality. This effect - which is largest within the epicenter and in days of abnormally high volumes of calls to the emergency line - underscores the importance of improving pre-hospital emergency services and building ambulance capacity to ensure timely transportation of critical patients to the ICU.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20106641", + "rel_abs": "BackgroundNumerous clinical studies are now underway investigating aspects of COVID-19. The aim of this study was to identify a selection of national and/or multicentre clinical COVID-19 studies in the United Kingdom to examine the feasibility and outcomes of documenting the most frequent data elements common across studies to rapidly inform future study design and demonstrate proof-of-concept for further subject-specific study data element mapping to improve research data management.\n\nMethods25 COVID-19 studies were included. For each, information regarding the specific data elements being collected was recorded. Data elements collated were arbitrarily divided into categories for ease of visualisation. Elements which were most frequently and consistently recorded across studies are presented in relation to their relative commonality.\n\nResultsAcross the 25 studies, 261 data elements were recorded in total. The most frequently recorded 100 data elements were identified across all studies and are presented with relative frequencies. Categories with the largest numbers of common elements included demographics, admission criteria, medical history and investigations. Mortality and need for specific respiratory support were the most common outcome measures, but with specific studies including a range of other outcome measures.\n\nConclusionThe findings of this study have demonstrated that it is feasible to collate specific data elements recorded across a range of studies investigating a specific clinical condition in order to identify those elements which are most common among studies. These data may be of value for those establishing new studies and to allow researchers to rapidly identify studies collecting data of potential use hence minimising duplication and increasing data re-use and interoperability", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Gabriele Ciminelli", - "author_inst": "MIT Sloan School of Management" + "author_name": "Priscilla Mathewson", + "author_inst": "University of Birmingham" }, { - "author_name": "S\u00edlvia Garcia-Mandic\u00f3", - "author_inst": "Organisation for Economic Cooperation and Development" + "author_name": "Ben Gordon", + "author_inst": "HDRUK" + }, + { + "author_name": "Kay Snowley", + "author_inst": "HDRUK" + }, + { + "author_name": "Clara Fennessy", + "author_inst": "HDRUK" + }, + { + "author_name": "Alastair Denniston", + "author_inst": "HDRUK" + }, + { + "author_name": "Neil Sebire", + "author_inst": "Great Ormond Street Hospital and ICH London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.05.19.20106799", @@ -1441822,21 +1442164,45 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.05.21.20108522", - "rel_title": "Expanding Covid-19 Testing: Mathematical Guidelines for the Optimal Sample Pool Size Given Positive Test Rate", + "rel_doi": "10.1101/2020.05.19.20107359", + "rel_title": "Identification of severity zones for mitigation strategy assessment COVID-19 outbreak in Malaysia", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20108522", - "rel_abs": "Widespread testing is essential to the mitigation of the spread of any virus, and is particularly central to the discussion on transitioning out of national quarantine. Sample pooling is a method that aims to multiply testing capability by using one testing kit for multiple samples, but will only be successful under certain conditions. This paper gives precise guidelines on those conditions for success: for any proposed sample pool size, explicit bounds on the positive infection rate are given that are informed by both discrete and statistical modeling.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.19.20107359", + "rel_abs": "The objective of this research is to identify severity zones for the COVID-19 outbreak in Malaysia. The technique employed for the purpose is fuzzy graph that can accommodate scarcity, quantity, and availability of data set. Two published sets of data by the Ministry of Health of Malaysia are used to implement the technique. The obtained results can offer descriptive insight, reflection, assessment, and strategizing actions in combating the pandemic.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Kayleigh Adams", - "author_inst": "UC Davic" + "author_name": "Tahir Ahmad", + "author_inst": "Universiti Teknologi Malaysia" + }, + { + "author_name": "Azmirul Ashaari", + "author_inst": "Universiti Teknologi Malaysia" + }, + { + "author_name": "Siti Rahmah Awang", + "author_inst": "Universiti Teknologi Malaysia" + }, + { + "author_name": "Siti Salwana Mamat", + "author_inst": "Universiti Teknologi Malaysia" + }, + { + "author_name": "Wan Munirah Wan Mohamad", + "author_inst": "Universiti Teknologi MARA" + }, + { + "author_name": "Amirul Aizad Ahmad Fuad", + "author_inst": "Universiti Teknologi Malaysia" + }, + { + "author_name": "Nurfarhana Hassan", + "author_inst": "Universiti Teknologi Malaysia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1443316,51 +1443682,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.25.20111047", - "rel_title": "Characteristics of Ischemic Stroke in COVID-19: A Need for Early Detection and Management", + "rel_doi": "10.1101/2020.05.23.20111500", + "rel_title": "Time delay epidemic model for COVID-19", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.25.20111047", - "rel_abs": "ObjectiveIn the setting of the Coronavirus Disease 2019 (COVID-19) global pandemic caused by SARS-CoV-2, a potential association of this disease with stroke has been suggested. We aimed to describe the characteristics of patients who were admitted with COVID-19 and had an acute ischemic stroke (AIS).\n\nMethodsThis is a case series of PCR-confirmed COVID-19 patients with ischemic stroke admitted to an academic health system in metropolitan Atlanta (USA) between March 24th,2020, and May 5th, 2020. Demographic, clinical, and radiographic characteristics were described.\n\nResultsOf 124 ischemic stroke patients admitted during this study period, 8 (6.5%) were also diagnosed with COVID-19. The mean age of patients was 64.3 {+/-} 6.5 years, 5 (62.5%) male, mean time from last-normal was 4.8 days [SD 4.8], and none received acute reperfusion therapy. All 8 patients had at least one stroke-associated co-morbidity. The predominant pattern of ischemic stroke was embolic; 3 were explained by atrial fibrillation while 5 (62.5%) were cryptogenic. In contrast, cryptogenic strokes were seen in 20 (16.1%) of 124 total stroke admissions during this time.\n\nConclusionsIn our case series, ischemic stroke affected COVID-19 patients with traditional stroke risk factors with an age of stroke presentation typically seen in non-COVID populations. We observed a predominantly embolic pattern of stroke with a higher than expected rate of cryptogenic strokes and with a prolonged median time to presentation and symptom recognition limiting the use of acute reperfusion treatments. These results highlight the need for increased community awareness, early identification, and management of AIS in COVID-19 patients.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.23.20111500", + "rel_abs": "A time delay epidemic model is presented for the spread of the Coronavirus 2019 (COVID-19) in China. The time delay effects affect infected individuals. Monte Carlo simulation is performed to estimate the transmission and recovery rates. The basic reproduction number is estimated in terms of the average infected ratio. This ratio can be used to monitor the policy performance of disease control during the spread of the disease.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Dinesh V. Jillella", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Nicholas J. Janocko", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Fadi Nahab", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Karima Benameur", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "James G. Greene", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Wendy L. Wright", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Mahmoud Obideen", - "author_inst": "Emory University School of Medicine" - }, - { - "author_name": "Srikant Rangaraju", - "author_inst": "Emory University School of Medicine" + "author_name": "Montri Maleewong", + "author_inst": "Kasetsart University" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "neurology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.23.20110650", @@ -1444870,39 +1445208,23 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.23.20110965", - "rel_title": "Association of age, sex, comorbidities, and clinical symptoms with the severity and mortality of COVID-19 cases: a meta-analysis with 85 studies and 67299 cases", + "rel_doi": "10.1101/2020.05.22.20110171", + "rel_title": "A data first approach to modelling Covid-19", "rel_date": "2020-05-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.23.20110965", - "rel_abs": "BackgroundA new pathogenic disease named COVID-19 became a global threat, first reported in Wuhan, China, in December 2019. The number of affected cases growing exponentially and now, more than 210 countries confirmed the cases.\n\nObjectiveThis meta-analysis aims to evaluate risk factors, the prevalence of comorbidity, and clinical characteristics in COVID-19 death patients compared to survival patients that can be used as a reference for further research and clinical decisions.\n\nMethodsPubMed, Science Direct, SAGE were searched to collect data about demographic, clinical characteristics, and comorbidities of confirmed COVID-19 patients from January 1, 2020, to May 17, 2020. Meta-analysis was performed with the use of Review Manager 5.3\n\nResultsEighty-five studies were included in Meta-analysis, including a total number of 67,299 patients with SARS-CoV-2 infection. Males are severely affected or died than females (OR = 2.26, p < 0.00001; OR = 3.59, p < 0.00001) are severely affected, or died by COVID-19 and cases with age [≥]50 are at higher risk of death than age <50 years (OR=334.23). Presence of any comorbidity or comorbidities like hypertension, cardiovascular disease, diabetes, cerebrovascular disease, respiratory disease, kidney disease, liver disease, malignancy significantly increased the risk of death compared to survival (OR = 3.46, 3.16, 4.67, 2.45, 5.84, 2.68, 5.62, 2.81,2.16). Among the clinical characteristics such as fever, cough, myalgia, diarrhea, abdominal pain, dyspnea, fatigue, sputum production, chest tightness headache and nausea or vomiting, only fatigue (OR = 1.31, 95%) and dyspnea increased the death significantly (OR= 1.31, 4.57). The rate of death of COVID-19 cases is 0.03-times lower than the rate of survival (OR = 0.03).\n\nConclusionOur result indicates that male patients are affected severely or died, the rate of death is more in the age [≥]50 group, and the rate of death is affected by comorbidities and clinical symptoms.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20110171", + "rel_abs": "The primary data for Covid-19 pandemic is in the form of time series for the number of confirmed, recovered and dead cases. This data is updated every day and is available for most countries from multiple sources such as [Gar20b, iD20]. In this work we present a two step procedure for model fitting to Covid-19 data. In the first step, time dependent transmission coefficients are constructed directly from the data and, in the second step, measures of those (minimum, maximum, mean, median etc.,) are used to set priors for fitting models to data. We call this approach a \"data driven approach\" or \"data first approach\". This scheme is complementary to Bayesian approach and can be used with or without that for parameter estimation. We use the procedure to fit a set of SIR and SIRD models, with time dependent contact rate, to Covid-19 data for a set of most affected countries. We find that SIR and SIRD models with constant transmission coefficients cannot fit Covid-19 data for most countries (mainly because social distancing, lockdown etc., make those time dependent). We find that any time dependent contact rate decaying with time can help to fit SIR and SIRD models for most of the countries. We also present constraints on transmission coefficients and basic reproduction number [Formula], as well as effective reproduction number [Formula]. The main contributions of our work are as follows. (1) presenting a two step procedure for model fitting to Covid-19 data (2) constraining transmission coefficients as well as [Formula] and [Formula], for a set of countries and (3) releasing a python package PyCov19 [Pra20b] that can used to fit a class of compartmental models, with time varying coefficients, to Covid-19 data.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Mohammad Safiqul Islam", - "author_inst": "Noakhali Science and Technology University" - }, - { - "author_name": "Md. Abdul Barek", - "author_inst": "Noakhali Science and Technology University" - }, - { - "author_name": "Md. Abdul Aziz", - "author_inst": "Noakhali Science and Technology University" - }, - { - "author_name": "Tutun Das Aka", - "author_inst": "Noakhali Science and Technology University" - }, - { - "author_name": "Md. Jakaria", - "author_inst": "The University of Melbourne" + "author_name": "JAYANTI PRASAD", + "author_inst": "Independent Researcher" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.23.20111021", @@ -1446128,39 +1446450,51 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.05.26.116608", - "rel_title": "Structure, function and variants analysis of the androgen-regulated TMPRSS2, a drug target candidate for COVID-19 infection", + "rel_doi": "10.1101/2020.05.21.20109512", + "rel_title": "Treatment of 6 COVID-19 Patients with Convalescent Plasma", "rel_date": "2020-05-26", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.26.116608", - "rel_abs": "SARS-CoV-2 is a novel virus causing mainly respiratory, but also gastrointestinal symptoms. Elucidating the molecular processes underlying SARS-CoV-2 infection, and how the genetic background of an individual is responsible for the variability in clinical presentation and severity of COVID-19 is essential in understanding this disease.\n\nCell infection by the SARS-CoV-2 virus requires binding of its Spike (S) protein to the ACE2 cell surface protein and priming of the S by the serine protease TMPRSS2. One may expect that genetic variants leading to a defective TMPRSS2 protein can affect SARS-CoV-2 ability to infect cells. We used a range of bioinformatics methods to estimate the prevalence and pathogenicity of TMPRSS2 genetic variants in the human population, and assess whether TMPRSS2 and ACE2 are co-expressed in the intestine, similarly to what is observed in lungs.\n\nWe generated a 3D structural model of the TMPRSS2 extracellular domain using the prediction server Phyre and studied 378 naturally-occurring TMPRSS2 variants reported in the GnomAD database. One common variant, p.V160M (rs12329760), is predicted damaging by both SIFT and PolyPhen2 and has a MAF of 0.25. Valine 160 is a highly conserved residue within the SRCS domain. The SRCS is found in proteins involved in host defence, such as CD5 and CD6, but its role in TMPRSS2 remains unknown. 84 rare variants (53 missense and 31 leading to a prematurely truncated protein, cumulative minor allele frequency (MAF) 7.34x10-4) cause structural destabilization and possibly protein misfolding, and are also predicted damaging by SIFT and PolyPhen2 prediction tools. Moreover, we extracted gene expression data from the human protein atlas and showed that both ACE2 and TMPRSS2 are expressed in the small intestine, duodenum and colon, as well as the kidneys and gallbladder.\n\nThe implications of our study are that: i. TMPRSS2 variants, in particular p.V160M with a MAF of 0.25, should be investigated as a possible marker of disease severity and prognosis in COVID-19 and ii. in vitro validation of the co-expression of TMPRSS2 and ACE2 in gastro-intestinal is warranted.", - "rel_num_authors": 5, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20109512", + "rel_abs": "ObjectiveTo describe the efficacy of convalescent plasma transfusion for COVID-19 patients.\n\nMethodsThis is a retrospective study of 6 COVID-19 patients with convalescent plasma at Guizhou Provincial Jiangjunshan Hospital - a tertial hospital, in Guiyang, Guizhou, China, from January 29, to April 30, 2020; final data of follow-up was May 12, 2020. Through the review of the electronic medical records of Guizhou Jiangjunshan Hospital, clinical data of 6 patients were obtained. Three patients with worsening symptoms after empirical treatment with antivirals were transfused convalescent plasma therapy for the first treatment, while the other three severe or critical COVID-19 patients with rapid progression were transfused. The efficacy of convalescent plasma depends on the relief of symptoms, changes in laboratory indicators and chest imaging abnormalities.\n\nResultsThe PaO2 / FiO2 and lymphocyte count of patients 1, 2 and 3 treated with convalescent plasma treatment for the first treatment period were changed from abnormal to normal. The levels of inflammation markers CRP and IL-6 of the patients decreased significantly. Chest imaging examination showed that the lung lesions gradually subsided. The relapsed patients (No. 4 and No. 6), after using convalescent plasma therapy, turned negative on two consecutive throat swab tests on Day 24 and Day 3, respectively.\n\nConclusionsConvalescent plasma treatment of COVID-19 is beneficial for those patients with be difficult to turn to negative or re-positive RT-PCR.\n\nKey PointsConvalescent plasma treatment of COVID-19 is beneficial for those patients with be difficult to turn to negative or re-positive RT-PCR.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Alessia David", - "author_inst": "Imperial College London" + "author_name": "Can Jin", + "author_inst": "Affiliated Hospital of Zunyi Medical University" }, { - "author_name": "Tarun Khanna", - "author_inst": "Imperial College London" + "author_name": "Juan Gu", + "author_inst": "Affiliated Hospital of Zunyi Medical University" }, { - "author_name": "Melina Beykou", - "author_inst": "Imperial College London" + "author_name": "Youshu Yuan", + "author_inst": "Guizhou University School of Medicine" }, { - "author_name": "Gordon Hanna", - "author_inst": "Imperial College London" + "author_name": "Qinying Long", + "author_inst": "Guizhou University School of Medicine" }, { - "author_name": "Michael J.E. Sternberg", - "author_inst": "Imperial College London" + "author_name": "Qi Zhang", + "author_inst": "Guizhou University School of Medicine" + }, + { + "author_name": "Hourong Zhou", + "author_inst": "Guizhou Provincial People Hospital" + }, + { + "author_name": "Weidong Wu", + "author_inst": "Guizhou Normal College" + }, + { + "author_name": "Wei Zhang", + "author_inst": "Affiliated Hospital of Zunyi Medical University" } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.26.116020", @@ -1447598,41 +1447932,41 @@ "category": "emergency medicine" }, { - "rel_doi": "10.1101/2020.05.22.20109231", - "rel_title": "Association of country-wide coronavirus mortality with demographics, testing, lockdowns, and public wearing of masks.", + "rel_doi": "10.1101/2020.05.21.20109017", + "rel_title": "SARS-CoV-2 infection in London, England: Impact of lockdown on community point-prevalence, March-May 2020", "rel_date": "2020-05-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20109231", - "rel_abs": "PurposeTo determine sources of variation between countries in per-capita mortality from COVID-19 (caused by the SARS-CoV-2 virus).\n\nMethodsPotential predictors of per-capita coronavirus-related mortality in 200 countries by May 9, 2020 were examined, including age, sex, obesity prevalence, temperature, urbanization, smoking, duration of infection, lockdowns, viral testing, contact tracing policies, and public mask-wearing norms and policies. Multivariable linear regression analysis was performed.\n\nResultsIn univariate analyses, the prevalence of smoking, per-capita gross domestic product, urbanization, and colder average country temperature were positively associated with coronavirus-related mortality. In a multivariable analysis of 196 countries, the duration of infection in the country, and the proportion of the population 60 years of age or older were positively associated with per-capita mortality, while duration of mask-wearing by the public was negatively associated with mortality (all p<0.001). International travel restrictions and a lower prevalence of obesity were independently associated with mortality in a model which controlled for testing policy. Internal lockdown requirements and viral testing policies and levels were not associated with mortality. The association of contact tracing policy with mortality approached statistical significance (p=0.06). In countries with cultural norms or government policies supporting public mask-wearing, per-capita coronavirus mortality increased on average by just 15.8% each week, as compared with 62.1% each week in remaining countries.\n\nConclusionsSocietal norms and government policies supporting the wearing of masks by the public, as well as international travel controls, are independently associated with lower per-capita mortality from COVID-19.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20109017", + "rel_abs": "COVID-19 point prevalence PCR community testing allows disease burden estimation. In a sample of London residents, point prevalence decreased from 2.2% (95%CI 1.4;3.5) in early April (reflecting infection around lockdown implementation) to 0.2% (95%CI 0.03-1.6) in early May (reflecting infection 3-5 weeks into lockdown). Extrapolation from reports of confirmed cases suggest that 5-7.6% of total infections were confirmed by testing during this period. These data complement seroprevalence surveys improving the understanding of transmission in London.", "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Christopher T Leffler", - "author_inst": "Virginia Commonwealth University" + "author_name": "Michael Edelstein", + "author_inst": "Public Health England" }, { - "author_name": "Edsel B Ing", - "author_inst": "University of Toronto" + "author_name": "Chinelo Obi", + "author_inst": "Public Health England" }, { - "author_name": "Joseph D. Lykins V", - "author_inst": "Virginia Commonwealth University" + "author_name": "Meera Chand", + "author_inst": "Public Health England" }, { - "author_name": "Matthew C. Hogan", - "author_inst": "Virginia Commonwealth University" + "author_name": "Susan Hopkins", + "author_inst": "Public Health England" }, { - "author_name": "Craig A. McKeown", - "author_inst": "University of Miami" + "author_name": "Kevin Brown", + "author_inst": "Public Health England" }, { - "author_name": "Andrzej Grzybowski", - "author_inst": "University of Warmia and Mazury" + "author_name": "Mary Ramsay", + "author_inst": "Public Health England" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1449160,59 +1449494,35 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.05.24.113043", - "rel_title": "Mass Spectrometric detection of SARS-CoV-2 virus in scrapings of the epithelium of the nasopharynx of infected patients via Nucleocapsid N protein", + "rel_doi": "10.1101/2020.05.25.114884", + "rel_title": "COVID-Align: Accurate online alignment of hCoV-19 genomes using a profile HMM", "rel_date": "2020-05-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.24.113043", - "rel_abs": "Detection of viral RNA by PCR is currently the main diagnostic tool for COVID-19 [1]. The PCR-based test, however, shows limited sensitivity, especially at early and late stages of the disease development [2,3], and is relatively time consuming. Fast and reliable complementary methods for detecting the viral infection would be of help in the current pandemia conditions. Mass-spectrometry is one of such possibilities. We have developed a mass-spectrometry based method for the detection of the SARS CoV-2 virus in nasopharynx epithelial swabs, based on the detection of the viral nucleocapsid N protein. The N protein of the SARS-COV-2 virus, the most abundant protein in the virion, is the best candidate for mass-spectrometric detection of the infection, and MS-based detection of several peptides from the SARS-COoV-2 nucleoprotein has been reported earlier by the Sinz group [4]. Our approach shows confident identification of the N protein in patient samples even with the lowest viral loads and a much simpler preparation procedure. Our main protocol consists of virus inactivation by heating and adding of isopropanol, and tryptic digestion of the proteins sedimented from the swabs followed by MS analysis. A set of unique peptides, produced as a result of proteolysis of the nucleocapsid phosphoprotein of SARS-CoV-2, is detected. The obtained results can further be used to create fast parallel mass-spectrometric approaches for the detection of the virus in the nasopharyngeal mucosa, saliva, sputum and other physiological fluids.", - "rel_num_authors": 10, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.25.114884", + "rel_abs": "MotivationThe first cases of the COVID-19 pandemic emerged in December 2019. Until the end of February 2020, the number of available genomes was below 1,000, and their multiple alignment was easily achieved using standard approaches. Subsequently, the availability of genomes has grown dramatically. Moreover, some genomes are of low quality with sequencing/assembly errors, making accurate re-alignment of all genomes nearly impossible on a daily basis. A more efficient, yet accurate approach was clearly required to pursue all subsequent bioinformatics analyses of this crucial data.\n\nResultshCoV-19 genomes are highly conserved, with very few indels and no recombination. This makes the profile HMM approach particularly well suited to align new genomes, add them to an existing alignment and filter problematic ones. Using a core of [~]2,500 high quality genomes, we estimated a profile using HMMER, and implemented this profile in COVID-Align, a user-friendly interface to be used online or as standalone via Docker. The alignment of 1,000 genomes requires less than 20mn on our cluster. Moreover, COVID-Align provides summary statistics, which can be used to determine the sequencing quality and evolutionary novelty of input genomes (e.g. number of new mutations and indels).\n\nAvailabilityhttps://covalign.pasteur.cloud, hub.docker.com/r/evolbioinfo/covid-align\n\nContactsolivier.gascuel@pasteur.fr, frederic.lemoine@pasteur.fr\n\nSupplementary informationSupplementary information is available at Bioinformatics online.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Evgeny (Eugene) N Nikolaev", - "author_inst": "Skolkovo Institute of Science and Technology, Moscow, Russia" - }, - { - "author_name": "Maria I Indeykina", - "author_inst": "Emanuel Institute for Biochemical Physics, Russian Academy of Sciences, Moscow, Russia" - }, - { - "author_name": "Alexander G Brzhozovskiy", - "author_inst": "Skolkovo Institute of Science and Technology, Moscow, Russia" - }, - { - "author_name": "Anna E Bugrova", - "author_inst": "Emanuel Institute for Biochemical Physics, Russian Academy of Sciences, Moscow, Russia" - }, - { - "author_name": "Alexey Kononikhin", - "author_inst": "Skolkovo Institute of Science and Technology, Moscow, Russia" - }, - { - "author_name": "Natalia L Starodubtseva", - "author_inst": "V. I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Healthcare of the Russian Federation, Moscow, Russia" - }, - { - "author_name": "Evgeniy V Petrotchenko", - "author_inst": "Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec, H3T 1E2, Canada" + "author_name": "Frederic Lemoine", + "author_inst": "Institut Pasteur" }, { - "author_name": "Grigoriy I Kovalev", - "author_inst": "Skolkovo Institute of Science and Technology, Moscow, Russia" + "author_name": "Luc Blassel", + "author_inst": "Institut Pasteur" }, { - "author_name": "Christoph H Borchers", - "author_inst": "Gerald Bronfman Department of Oncology, Jewish General Hospital, McGill University, Montreal, Quebec, H3T 1E2, Canada" + "author_name": "Jakub Voznica", + "author_inst": "Insitut Pasteur" }, { - "author_name": "Gennady T Sukhikh", - "author_inst": "V. I. Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Ministry of Healthcare of the Russian Federation, Moscow, Russia" + "author_name": "Olivier Gascuel", + "author_inst": "CNRS & Institut Pasteur" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "molecular biology" + "category": "bioinformatics" }, { "rel_doi": "10.1101/2020.05.24.20112110", @@ -1450690,27 +1451000,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.23.20110866", - "rel_title": "Visualizing the COVID-19 pandemic in Bangladesh using coxcombs: A tribute to Florence Nightingale", + "rel_doi": "10.1101/2020.05.22.20110429", + "rel_title": "C-Reactive protein and SOFA score as early predictors of critical care requirement in patients with COVID-19 pneumonia in Spain.", "rel_date": "2020-05-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.23.20110866", - "rel_abs": "Following detection of the first confirmed case of COVID-19 in early December 2019 in Wuhan, China, nearly six months have passed and almost every country in the world is battling against the COVID-19 war. The frontline warriors, namely the doctors, nurses and healthcare staff, have in many countries struggled to care for the sick under conditions of limited resources and protection and the threat of an overwhelmed healthcare system. It is during times such as this, that we draw strength and inspiration from Florence Nightingale - a passionate statistician, social reformer, feminist champion and a pioneer of modern nursing and data visualization. Nightingales famed Florence Night-ingle Diagram also known as \"coxcomb\", which was created 150 years ago and used to display the causes of death in the British Army hospital barracks, demonstrated how data visualization techniques could be a powerful medium of communication and a force for change. This paper pays tribute to Nightingales work by using data from Bangladesh to show that the coxcomb graph is still relevant in the era of COVID-19. The coxcomb graphs that have been produced to display COVID-19 data have provided deeper insights into the trends and relative changes of variables over the course of the pandemic. The paper also describes codes that allow one to easily reproduce the graphs using the statistical programming language R.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.22.20110429", + "rel_abs": "BackgroundSome patients infected by SARS-CoV-2 in the recent pandemic have required critical care, becoming one of the main limitations of the health systems. Our objective has been to identify potential markers at admission predicting the need for critical care in patients with COVID-19 pneumonia.\n\nMethodsWe retrospectively collected and analyzed data from electronic medical records of patients with laboratory-confirmed SARS-CoV-19 infection by real-time RT-PCR. A comparison was made between patients staying in the hospitalization ward with those who required critical care. Univariable and multivariable logistic regression methods were used to identify risk factors predicting critical care need.\n\nFindingsBetween March 15 and April 15, 2020, 150 patients under the age of 75 were selected (all with laboratory confirmed SARS-CoV-19 infection), 75 patients requiring intensive care assistance and 75 remaining the regular hospitalization ward. Most patients requiring critical care were males, 76% compared with 60% in the non-critical care group (p<0.05). Multivariable regression showed increasing odds of in-hospital critical care associated with increased C-reactive protein (CRP) (odds ratio 1.052 (1.009-1.101); p=0.0043) and higher Sequential Organ Failure Assessment (SOFA) score (1.968 (1.389-2.590) p<0.0001) both at the time of hospital admission. The AUC-ROC for the combined model was 0.83 (0.76-0.90) (vs AUC-ROC SOFA p<0.05).\n\nInterpretationPatients COVID-19 positive presenting at admission with high SOFA score [≥]2 combined with CRP [≥] 9,1 mg/mL could help clinicians to identify them as a group that will more likely require critical care so further actions might be implemented to improve their prognosis.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Hasinur Rahaman Khan", - "author_inst": "University of Dhaka, Bangladesh" + "author_name": "Luis Mario Vaquero Sr.", + "author_inst": "Hospital Universitario Salamanca" }, { - "author_name": "Tamanna Howlader", - "author_inst": "University of Dhaka, Bangladesh" + "author_name": "Maria Elisa Sanchez Barrado", + "author_inst": "Hospital Universitario Salamanca" + }, + { + "author_name": "Daniel Escobar Jr.", + "author_inst": "Hospital Universitario Salamanca" + }, + { + "author_name": "Pilar Arribas", + "author_inst": "Hospital Universitario Salamanca" + }, + { + "author_name": "Jose Ramon Gonzalez Sr.", + "author_inst": "Hospital Universitario Salamanca" + }, + { + "author_name": "Jesus Francisco Bermejo", + "author_inst": "Group of Biomedical research in sepsis (BioSepsis), IBSAL. Department of Medicine. University of Salamanca" + }, + { + "author_name": "Cristina Doncel", + "author_inst": "Group of Biomedical research in sepsis (BioSepsis), IBSAL. Department of Medicine. University of Salamanca." + }, + { + "author_name": "JM Bastida", + "author_inst": "Department of Hematology, University Hospital of Salamanca-IBSAL" + }, + { + "author_name": "Azucena Hernandez", + "author_inst": "Department of Anesthesiology and Reanimation , University Hospital of Salamanca-IBSAL" + }, + { + "author_name": "Carolina Jambrina", + "author_inst": "Department of Anesthesiology and Reanimation, University Hospital of Salamanca-IBSAL" + }, + { + "author_name": "Miguel Vicente Sanchez", + "author_inst": "Department of Anesthesiology and Reanimation, University Hospital of Salamanca-IBSAL" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.05.22.20110270", @@ -1451956,25 +1452302,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.20.20108340", - "rel_title": "The estimations of the COVID-19 incubation period: a systematic review of the literature", + "rel_doi": "10.1101/2020.05.21.20108605", + "rel_title": "Spatial and temporal dynamics of SARS-CoV-2 in COVID-19 patients: A systematic review", "rel_date": "2020-05-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20108340", - "rel_abs": "BackgroundA novel coronavirus (COVID-19) has taken the world by storm. The disease has spread very swiftly worldwide. A timely clue which includes the estimation of the incubation period among COVID-19 patients can allow governments and healthcare authorities to act accordingly.\n\nObjectivesto undertake a review and critical appraisal of all published/preprint reports that offer an estimation of incubation periods for COVID-19.\n\nEligibility criteriaThis research looked for all relevant published articles between the dates of December 1, 2019, and April 25, 2020, i.e. those that were related to the COVID-19 incubation period. Papers were included if they were written in English, and involved human participants. Papers were excluded if they were not original (e.g. reviews, editorials, letters, commentaries, or duplications).\n\nSources of evidenceCOVID-19 Open Research Dataset supplied by Georgetowns Centre for Security and Emerging Technology as well as PubMed and Embase via Arxiv, medRxiv, and bioRxiv.\n\nCharting methodsA data-charting form was jointly developed by the two reviewers (NZ and EA), to determine which variables to extract. The two reviewers independently charted the data, discussed the results, and updated the data-charting form.\n\nResults and conclusionsscreening was undertaken 44,000 articles with a final selection of 25 studies referring to 18 different experimental projects related to the estimation of the incubation period of COVID-19. The majority of extant published estimates offer empirical evidence showing that the incubation period for the virus is a mean of 7.8 days, with a median of 5.01 days, which falls into the ranges proposed by the WHO (0 to 14 days) and the ECDC (2 to 12 days). Nevertheless, a number of authors proposed that quarantine time should be a minimum of 14 days and that for estimates of mortality risks a median time delay of 13 days between illness and mortality should be under consideration. It is unclear as to whether any correlation exists between the age of patients and the length of time they incubate the virus.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.21.20108605", + "rel_abs": "BackgroundThe spatial and temporal dynamics of SARS-CoV-2 have been mainly described in form of case series or retrospective studies. In this study, we aimed to provide a coherent overview from published studies of the duration of viral detection and viral load in COVID-19 patients, stratified by specimen type, clinical severity and age.\n\nMethodWe systematically searched PubMed/MEDLINE and Cochrane review database for studies published between 1. November 2019 and 23rd of April 2020. We included studies that reported individual viral data over time measuring negative conversion by two consecutive negative tests, individual clinical severity and age. We excluded studies that reported viral data as patient fraction, reported only baseline data, included solely asymptomatic patients or were interventional studies. Extracted data included author, title, design, sample size, thresholds and genes of RT-PCR, patient age, COVID-19 severity, clinical characteristics, treatment, location of viral sampling, duration of viral detection, and viral load. We pooled the data of selected studies to determine effect estimates of duration of viral detection. Combined viral load was visualized over time.\n\nFindingsOut of 7226 titles screened, 37 studies met the inclusion criteria and were included in the qualitative analysis and 22 studies in the quantitative analysis comprising 650 COVID-19 patients. The pooled estimate of the duration of positive detection of the virus was in mild adult patients 12.1 days (CI: 10.12, 14.05) after symptom onset in the upper respiratory tract (URT), 24.1 days (CI: 10.02, 38.19) in lower respiratory tract (LRT), and 15.5 days (CI: 8.04, 22.88) in faeces. Further, in mild adult patients, the maximum viral load was ~ 6.61 x 108 viral copies/mL in the URT and ~ 2.69 x 108 viral copies/mL in the LRT, within the first week of symptom onset. The maximum viral load in faeces was reported as ~ 3.55 x 107 copies/mL on Day 9. In moderate-severe adult patients, the pooled estimate of mean duration of positive viral detection in the URT was 15.8 days (CI: 11.12, 20.56) after symptom onset, 23.2 days (CI: 21.49, 24.97) in the LRT, 20.8 days (CI: 16.40, 25.17) in faeces. The maximum viral load was 4.60 x 109 copies/mL on Day 8 in the URT, 3.45 x 108 copies/mL on Day 11 in the LRT, 2.76 x 106 copies/mL on Day 18 in faeces and 1 x 104 copies/mL on Day 3 in blood. In children with mild symptoms, the pooled estimate of the mean duration of positive SARS-CoV-2 viral detection was 11.1 days (CI: 7.14, 15.11) in the URT and 16.0 days (CI: 11.49, 20,47) in the faeces, without reporting quantitative viral data. Viral positivity was detected in the urine and eye in one patient.\n\nInterpretationOur analysis showed consistent viral detection from specimen from the URT, the LRT and faeces, irrespective of the clinical severity of COVID-19. Our analysis suggests that SARS-CoV-2 persists for a longer duration in the LRT compared to the URT, whereas the differences in the duration of viral detection between mild and moderate-severe patients is limited in the LRT, but an indication of longer duration of viral detection in feces and the URT for moderate-severe patients was shown. Further, viral load was demonstrated to peak in the URT within first weak of infection, whereas maximum viral load has been observed to occur later and within the second week of infection in the LRT.\n\nFundingThe project has received funding support from Innovation Fund Denmark.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Nazar Zaki", - "author_inst": "UAEU, UAE" + "author_name": "Anne Weiss", + "author_inst": "UNION therapeutics" }, { - "author_name": "Elfadil Abdalla Mohamed", - "author_inst": "Ajman University, UAE" + "author_name": "Mads Jellingsoe", + "author_inst": "UNION therapeutics" + }, + { + "author_name": "Morten Otto Alexander Sommer", + "author_inst": "Technical University of Denmark" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1453646,41 +1453996,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.20.20108068", - "rel_title": "Demographic and Clinical Characteristics of the Severe Covid-19 Infections: First Report from Mashhad University of Medical Sciences, Iran", + "rel_doi": "10.1101/2020.05.20.20108365", + "rel_title": "A Systematic Review and Meta-analysis of Therapeutic options against SARS-CoV-2", "rel_date": "2020-05-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20108068", - "rel_abs": "BackgroundCoronavirus Disease 2019 (Covid-19) is expanding worldwide. The characteristics of this infection in patients varies from country to country. To move forward, clinical data on infected patients are needed. Here, we report a comparison between fatalities and recovery of patients with severe Covid-19, based on demographic and clinical characteristics.\n\nMethodsBetween 5 March and 12 May 2020 in Mashhad, Iran, 1,278 of 4,000 suspected Covid-19 patients were confirmed positive by real-time reverse-transcriptase-polymerase-chain-reaction assay of upper respiratory specimens. We compared the demographic, exposure history and clinical symptoms of 925 survivors and 353 fatal cases with confirmed disease.\n\nResultsMean (SD) age for all confirmed patients was 56.9 (18.7) years, 67.1 (15.9) years in fatal cases and 53.0 (18.3) years in survivors. Multivariable logistic regression analysis showed that the outcome of patients was associated with age (OR = 1.049, P = 0.0001, 95% CI = 1.040-1.057). Despite a high burden of Covid-19 infections in the 30-39 and 40-49 year age groups, most of these (89.6% and 87.2%, respectively) recovered. The median (IQR) duration of hospitalization was 9.0 (6.0-14.0) days. The most prevalent co-morbidities were cardiovascular disorders (21%) and diabetes (16.3%). Dyspnoea (72.7%), cough (68.1%) and fever (63.8%) were the most frequent clinical symptoms. Healthcare workers, of whom two (3%) died, comprised 5.2% of infected-cases. Combination antiviral and antibiotic therapy was used in 43.0% of cases.\n\nConclusionsThe characteristics of severe Covid-19 varied substantially between fatal cases and survivors, with diabetes and cardiovascular disorders the most prevalent co-morbidities. In contrast to other studies, there were a higher number of fatalities in younger patients in our settings.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.20.20108365", + "rel_abs": "ImportanceTreatment options for Severe acute respiratory syndrome-related coronavirus-2 (SARS-CoV-2) are limited with no clarity on the efficacy and safety profiles.\n\nObjectiveTo assess if the effect estimate of any intervention improves the outcomes and safety profile.\n\nData sourcesPubMed, Embase, Cochrane Central were searched from December 1, 2019 to May 11, 2020.\n\nStudy selectionAny prospective/retrospective clinical study on SARS-CoV-2 patients [≥]18 years of age with report on therapeutic interventions.\n\nData synthesis and extractionData was screened and extracted by two independent investigators.\n\nMain outcomes and measuresThe primary outcome was all-cause in-hospital mortality. The secondary outcomes were rates of mechanical ventilation, viral clearance, adverse events, discharge, progression to severe disease, median time for clinical recovery and anti-viral clearance. Pooled rates and odds ratios (OR) were calculated.\n\nResultsA total of 29 studies with 5207 participants were included in the analysis. The pooled all-cause in-hospital mortality rate was 12.8% (95%CI: 8.1%-17.4%) in intervention arm. There was no significant difference in mortality between both arms overall (OR: 1.36, 95% CI: 0.97-1.89). The mortality was significantly higher in the Hydroxychloroquine (HCQ) group compared to control: (1.86, 95% CI: 1.38 - 2.50). The need for mechanical ventilation in patients with mild-moderate disease was 13.5% vs 9.8% in intervention and control groups, with no significant difference (OR: 1.58, 95% CI: 0.60 - 4.15).The median duration for viral clearance in the intervention arm was 6.1 (IQR: 4.3 - 8.8) days and control arm was 9 (IQR: 4.5 - 14) days, with no significant difference between the groups (p = 0.37). There was no significant difference between pooled adverse event rates in intervention and control groups: 34% vs 29.5% (OR: 1.44, 95% CI: 0.70 - 2.94), respectively. However, incidence of adverse events was significantly higher in HCQ sub-group (OR: 3.88, 95% CI: 1.60 - 9.45, I2 = 0%). There was no significant difference in other secondary outcomes.\n\nConclusion and relevanceThe use of hydroxychloroquine was associated with increased mortality and adverse event rates. No other therapeutic intervention including Lopinavir/Ritonavir, Remdesivir or Tocilizumab seem to alter the natural course of the disease. There is a further need for well-designed randomized clinical trials.\n\nArticle summary lineThe use of hydroxychloroquine was associated with increased mortality and adverse event rates in Severe acute respiratory syndrome-related coronavirus-2 infection and other therapeutic interventions did not show any difference in outcomes", "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Ladan Goshayeshi", - "author_inst": "Mashhad University of Medical Sciences" + "author_name": "Viveksandeep Thoguluva Chandrasekar", + "author_inst": "University of Kansas Medical Center" }, { - "author_name": "Mina Akbari Rad", - "author_inst": "Mashhad University of Medical Sciences" + "author_name": "Bhanuprasad Venkatesalu", + "author_inst": "Henry Ford Hospital, Detroit, Michigan, USA" }, { - "author_name": "Robert Bergquist", - "author_inst": "Geospatial Health Journal" + "author_name": "Harsh K Patel", + "author_inst": "Ochsner Clinic Foundation, New Orleans, Louisiana, USA" }, { - "author_name": "Abolghasem Allahyari", - "author_inst": "Mashhad University of Medical Sciences" + "author_name": "Marco Spadaccini", + "author_inst": "Humanitas University and Research Hospital, Rozanno, Milan, USA" }, { - "author_name": "- MUMS Covid-19 Research Team", - "author_inst": "" + "author_name": "Jacob Manteuffel", + "author_inst": "Henry Ford Hospital, Michigan, Detroit, USA" }, { - "author_name": "Benyamin Hoseini", - "author_inst": "Mashhad University of Medical Sciences" + "author_name": "Mayur S Ramesh", + "author_inst": "Henry Ford Health System" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1454940,45 +1455290,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.18.20105239", - "rel_title": "Risks to Children under-five in India from COVID-19", + "rel_doi": "10.1101/2020.05.17.20104638", + "rel_title": "High Filtration Efficiency Face Masks made from Sterilization Wraps", "rel_date": "2020-05-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20105239", - "rel_abs": "ObjectiveThe novel coronavirus, COVID-19, has rapidly emerged to become a global pandemic and is known to cause a high risk to patients over the age of 70 and those with co-morbidities, such as hypertension and diabetes. Though children are at comparatively lower risk compared to adults, the Indian population has a large young demographic that is likely to be at higher risk due to exposure to pollution, malnutrition and poor access to medical care. We aimed to quantify the potential impact of COVID-19 on Indias child population.\n\nMethodsWe combined district family household survey data with data from the COVID-19 outbreak in China to analyze the potential impact of COVID-19 on children under the age of 5, under three different scenarios; each of which assumed the prevalence of infection to be 0.5%, 1%, or 5%.\n\nResultsWe find that in the lowest prevalence scenario, across the most populous 18 Indian states, asymptomatic, non-hospitalized symptomatic and hospitalized symptomatic cases could reach 87,200, 412,900 and 31,900, respectively. In a moderate prevalence scenario, these figures reach 174,500, 825,800, and 63,800, and in the worst case, high prevalence scenario these cases could climb as high as 872,200, 4,128,900 and 319,700.\n\nConclusionThese estimates show COVID-19 has the potential to pose a substantial threat to Indias large population of children, particularly those suffering from malnutrition and exposure to indoor air pollution, who may have limited access to health services.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104638", + "rel_abs": "COVID-19 pandemic has spawned the need for mass production of N-95 respirators. We used Sterilization Wraps to produce face masks which maintained 93% particle capture efficacy post sterilization. This ubiquitously available material could be explored for production of high quality face masks at a cost less than 30 US cents.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Isabel Frost", - "author_inst": "Center for Disease Dynamics Economics & Policy" + "author_name": "Sachin Walawalkar", + "author_inst": "Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi- Mumbai, India." }, { - "author_name": "Katie Tseng", - "author_inst": "Center for Disease Dynamics Economics & Policy" + "author_name": "Navin Khattry", + "author_inst": "Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi- Mumbai, India. & Homi Bhabha National Institute, Mumbai, I" }, { - "author_name": "Stephanie Hauck", - "author_inst": "Center for Disease Dynamics Economics & Policy" + "author_name": "B.K. Sapra", + "author_inst": "Bhabha Atomic Research Centre (BARC), Mumbai, India. & Homi Bhabha National Institute, Mumbai, India." }, { - "author_name": "Geetanjali Kappor", - "author_inst": "Center for Disease Dynamics Economics & Policy" + "author_name": "Arshad Khan", + "author_inst": "Bhabha Atomic Research Centre (BARC), Mumbai, India. & Homi Bhabha National Institute, Mumbai, India." }, { - "author_name": "Aditi Sriram", - "author_inst": "Center for Disease Dynamics Economics & Policy" + "author_name": "Manish Joshi", + "author_inst": "Bhabha Atomic Research Centre (BARC), Mumbai, India. & Homi Bhabha National Institute, Mumbai, India." }, { - "author_name": "Arindam Nandi", - "author_inst": "The Center for Disease Dynamics, Economics & Policy" + "author_name": "Lalit Mohan", + "author_inst": "Bhabha Atomic Research Centre (BARC), Mumbai, India." }, { - "author_name": "Ramanan Laxminarayan", - "author_inst": "Center for Disease Dynamics Economics & Policy" + "author_name": "S.P. Srivastava", + "author_inst": "Bhabha Atomic Research Centre (BARC), Mumbai, India." + }, + { + "author_name": "Chital Naresh", + "author_inst": "Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi- Mumbai, India" + }, + { + "author_name": "Rajendra Badwe", + "author_inst": "Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi- Mumbai, India. & Homi Bhabha National Institute, Mumbai" + }, + { + "author_name": "Sudeep Gupta", + "author_inst": "Advanced Centre for Treatment, Research and Education in Cancer (ACTREC), Tata Memorial Centre, Navi- Mumbai, India. & Homi Bhabha National Institute, Mumbai, I" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1456614,147 +1456976,31 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.18.20086157", - "rel_title": "COVID-19 in Great Britain: epidemiological and clinical characteristics of the first few hundred (FF100) cases: a descriptive case series and case control analysis", + "rel_doi": "10.1101/2020.05.18.20102509", + "rel_title": "Low blood sodium increases risk and severity of COVID-19: a systematic review, meta-analysis and retrospective cohort study", "rel_date": "2020-05-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20086157", - "rel_abs": "ObjectivesFollowing detection of the first virologically-confirmed cases of COVID-19 in Great Britain, an enhanced surveillance study was initiated by Public Health England to describe the clinical presentation, course of disease and underlying health conditions associated with infection of the first few hundred cases.\n\nMethodsInformation was collected on the first COVID-19 cases according to the First Few X WHO protocol. Case-control analyses of the sensitivity, specificity and predictive value of symptoms and underlying health conditions associated with infection were conducted. Point prevalences of underlying health conditions among the UK general population were presented.\n\nFindingsThe majority of FF100 cases were imported (51.4%), of which the majority had recent travel to Italy (71.4%). 24.7% were secondary cases acquired mainly through household contact (40.4%). Children had lower odds of COVID-19 infection compared with the general population.\n\nThe clinical presentation of cases was dominated by cough, fever and fatigue. Non-linear relationships with age were observed for fever, and sensitivity and specificity of symptoms varied by age.\n\nConditions associated with higher odds of COVID-19 infection (after adjusting for age and sex) were chronic heart disease, immunosuppression and multimorbidity.\n\nConclusionThis study presents the first epidemiological and clinical summary of COVID-19 cases in Great Britain. The FFX study design enabled systematic data collection. The study characterized underlying health conditions associated with infection and set relative risks in context with population prevalence estimates. It also provides important evidence for generating case definitions to support public health risk assessment, clinical triage and diagnostic algorithms.", - "rel_num_authors": 32, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20102509", + "rel_abs": "BackgroundNovel coronavirus (SARS-CoV-2) infects human lung tissue cells through angiotensin-converting enzyme-2 (ACE2), and the body sodium is an important factor for regulating the expression of ACE2. Through a systematic review, meta-analysis and retrospective cohort study, we found that the low blood sodium population may significantly increase the risk and severity of SARS-CoV-2 infection.\n\nMethodsWe extracted the data of serum sodium concentrations of patients with COVID-19 on admission from the articles published between Jan 1 and April 28, 2020, and analyzed the relationship between the serum sodium concentrations and the illness severity of patients. Then we used a cohort of 244 patients with COVID-19 for a retrospective analysis.\n\nResultsWe identified 36 studies, one of which comprised 2736 patients.The mean serum sodium concentration in patients with COVID-19 was 138.6 mmol/L, which was much lower than the median level in population (142.0). The mean serum sodium concentration in severe/critical patients (137.0) was significantly lower than those in mild and moderate patients (140.8 and 138.7, respectively). Such findings were confirmed in a retrospective cohort study, of which the mean serum sodium concentration in all patients was 137.5 mmol/L, and the significant differences were found between the mild (139.2) and moderate (137.2) patients, and the mild and severe/critical (136.6) patients. Interestingly, such changes were not obvious in the serum chlorine and potassium concentrations.\n\nConclusionsThe low sodium state of patients with COVID-19 may not be the consequence of virus infection, but could be a physiological state possibly caused by living habits such as low salt diet and during aging process, which may result in ACE2 overexpression, and increase the risk and severity of COVID-19. These findings may provide a new idea for the prevention and treatment of COVID-19.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Nicola L Boddington", - "author_inst": "Public Health England" - }, - { - "author_name": "Andre Charlett", - "author_inst": "Public Health England" - }, - { - "author_name": "Suzanne Elgohari", - "author_inst": "Public Health England" - }, - { - "author_name": "Jemma L Walker", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Helen Mcdonald", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Chloe Byers", - "author_inst": "Public Health England" - }, - { - "author_name": "Laura Coughlan", - "author_inst": "Public Health England" - }, - { - "author_name": "Tatiana Garcia Vilaplana", - "author_inst": "Public Health England" - }, - { - "author_name": "Rosie Whillock", - "author_inst": "Public Health England" - }, - { - "author_name": "Mary Sinnathamby", - "author_inst": "Public Health England" - }, - { - "author_name": "Nikolaos Panagiotopoulos", - "author_inst": "Public Health England" - }, - { - "author_name": "Louise Letley", - "author_inst": "Public Health England" - }, - { - "author_name": "Pauline MacDonald", - "author_inst": "Public Health England" - }, - { - "author_name": "Roberto Vivancos", - "author_inst": "Public Health England" - }, - { - "author_name": "Obaghe Edeghere", - "author_inst": "Public Health England" - }, - { - "author_name": "Joseph Shingleton", - "author_inst": "Public Health England" - }, - { - "author_name": "Emma Bennett", - "author_inst": "Public Health England" - }, - { - "author_name": "Daniel J Grint", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Helen Strongman", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Kathryn E Mansfield", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Christopher Rentsch", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Caroline Minassian", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Ian J Douglas", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Rohini Mathur", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Maria Peppa", - "author_inst": "London School of Hygiene and Tropical Medicine" - }, - { - "author_name": "Simon Cottrell", - "author_inst": "Public Health Wales" - }, - { - "author_name": "Jim McMenamin", - "author_inst": "Public Health Scotland" - }, - { - "author_name": "Maria Zambon", - "author_inst": "Public Health England" - }, - { - "author_name": "Mary Ramsay", - "author_inst": "Public Health England" - }, - { - "author_name": "Gavin Dabrera", - "author_inst": "Public Health England" + "author_name": "Yi Luo", + "author_inst": "Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University" }, { - "author_name": "Vanessa Saliba", - "author_inst": "Public Health England" + "author_name": "Yirong Li", + "author_inst": "Department of Laboratory Medicine, Zhongnan Hospital of Wuhan University" }, { - "author_name": "Jamie Lopez Bernal", - "author_inst": "Public Health England" + "author_name": "Jiapei Dai", + "author_inst": "South-Central University for Nationalities" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "pharmacology and therapeutics" }, { "rel_doi": "10.1101/2020.05.17.20101915", @@ -1458216,37 +1458462,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.17.20104612", - "rel_title": "The correspondence between the structure of the terrestrial mobility network and the emergence of COVID-19 in Brazil", + "rel_doi": "10.1101/2020.05.17.20104653", + "rel_title": "State-by-State estimates of R0 at the start of COVID-19 outbreaks in the USA", "rel_date": "2020-05-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104612", - "rel_abs": "BACKGROUNDthe inter-cities mobility network serves as a proxy for the SARS-CoV-2 spreading network in a country.\n\nOBJECTIVEto investigate the correspondences between the structure of the mobility network and the emergence of COVID-19 cases in Brazilian cities.\n\nMETHODSwe adopt the data from the Brazilian Health Ministry and the terrestrial flow of people between cities from the IBGE database in two scales: Brazilian cities without the North region and cities from the Sao Paulo state. Grounded on the complex networks approach, cities are represented as nodes and the flows as edges. Network centrality measures such as strength and degree are ranked and compared to the list of Brazilian cities, ordered according to the day that they confirmed the first case of COVID-19.\n\nFINDINGSThe strength presents the best correspondences and the interiorization process of SARS-CoV-2 is captured in the Sao Paulo state when different thresholds are applied to the network flows.\n\nMAIN CONCLUSIONSthe strength captures the cities with a higher vulnerability of receiving new cases of COVID-19. Some countryside cities such as Feira de Santana (Bahia state), Ribeirao Preto (Sao Paulo state), and Caruaru (Pernambuco state) have strength comparable to states capitals, making them potential super spreaders.\n\nFinancial supportSao Paulo Research Foundation (FAPESP) Grant Numbers 2015/50122-0, 2018/06205-7 and 2020/06837-3; DFG-IRTG Grant Number 1740/2; CNPq Grant Numbers 420338/2018-7 and 101720/2020-3.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.17.20104653", + "rel_abs": "We estimated the initial rate of spread (r0) and basic reproduction number (R0) for States in the USA experiencing COVID-19 epidemics by analyzing death data time series using a time-varying autoregressive state-space model. The initial spread varied greatly among States, with the highest r0 = 0.31 [0.23, 0.39] (95% CI) in New York State, corresponding to R0 = 6.4 [4.3, 9.0] (95% CI). The variation in initial R0 was strongly correlated with the peak daily death count among States, showing that the initial R0 anticipates subsequent challenges in controlling epidemics. Furthermore, the variation in initial R0 implies different needs for public health measures. Finally, the States that relaxed public health measures early were not those with the lowest risks of resurgence, highlighting the need for science to guide public health policies.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Vander L. S. Freitas", - "author_inst": "Federal University of Ouro Preto (UFOP)" - }, - { - "author_name": "Thais C. R. O. Konstantyner", - "author_inst": "Federal University of Sao Paulo (UNIFESP)" - }, - { - "author_name": "Jeferson Feitosa", - "author_inst": "Sao Paulo State University (UNESP)" - }, - { - "author_name": "Catia S. N. Sepetauskas", - "author_inst": "National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN)" + "author_name": "Anthony R Ives", + "author_inst": "University of Wisconsin-Madison" }, { - "author_name": "Leonardo B. L. Santos", - "author_inst": "National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN)" + "author_name": "Claudio Bozzuto", + "author_inst": "Wildlife Analysis GmbH, Zurich, Switzerland" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1459798,59 +1460032,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.16.099242", - "rel_title": "Capillary Electrophoresis of PCR fragments with labelled primers for testing the SARS-Cov-2", + "rel_doi": "10.1101/2020.05.14.20101444", + "rel_title": "Detection of SARS-CoV-2 in pets living with COVID-19 owners diagnosed during the COVID-19 lockdown in Spain: A case of an asymptomatic cat with SARS-CoV-2 in Europe", "rel_date": "2020-05-21", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.16.099242", - "rel_abs": "BackgroundDue to the huge demand for SARS-Cov-2 determination, alternatives to the standard qtPCR tests are potentially useful for increasing the number of samples screened. Our aim was to develop a direct fluorescent PCR capillary-electrophoresis detection of the viral genome. We validated this approach on several SARS-Cov-2 positive and negative samples.\n\nStudy designWe isolated the naso-pharingeal RNA from 20 positive and 10 negative samples. The cDNA was synthesised and two fragments of the SARS-Cov-2 were amplified. One of the primers for each pair was 5-end fluorochrome labelled. The amplifications were subjected to capillary electrophoresis in ABI3130 sequencers to visualize the fluorescent peaks.\n\nResultsThe two SARS-Cov-2 fragments were successfully amplified in the positive samples, while the negative samples did not render fluorescent peaks.\n\nConclusionWe describe and alternative method to identify the SARS-Cov-2 genome that could be scaled to the analysis of approximately 100 samples in less than 5 hours. By combining a standard PCR with capillary electrophoresis our approach would overcome the limits imposed to many labs by the qtPCR (lack of reactive and real-time PCR equipment) and increase the testing capacity.", - "rel_num_authors": 10, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20101444", + "rel_abs": "During April-May 2020, the presence of respiratory syndrome coronavirus 2 (SARS-CoV-2) in pets living with coronavirus disease 2019 (COVID-19) owners was analyzed. From 23 pets, a cat without clinical symptoms showed positive results for SARS-CoV-2 in oropharyngeal swab using three RT-qPCR assays (negative rectal swab). SARS-CoV-2 was not detected in the remaining pets. Our finding suggests that cats may act as asymptomatic dispersers of SARS-CoV-2, although viral transmission from animals to humans seems unlikely.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "JUAN GOMEZ", - "author_inst": "HUCA" - }, - { - "author_name": "SANTIAGO MELON", - "author_inst": "HUCA" - }, - { - "author_name": "JOSE A BOGA", - "author_inst": "HUCA" - }, - { - "author_name": "MARTA E Alvarez-Arguelles", - "author_inst": "HUCA" + "author_name": "Ignacio Ruiz-Arrondo", + "author_inst": "Center of Rickettsiosis and Arthropod-Borne Diseases, Hospital Universitario San Pedro-CIBIR" }, { - "author_name": "SUSANA ROJO-ALBA", - "author_inst": "HUCA" + "author_name": "Aranzazu Portillo", + "author_inst": "Center of Rickettsiosis and Arthropod-Borne Diseases, Hospital Universitario San Pedro-CIBIR" }, { - "author_name": "ALVARO LEAL-NEGREDO", - "author_inst": "HUCA" + "author_name": "Ana M. Palomar", + "author_inst": "Center of Rickettsiosis and Arthropod-Borne Diseases, Hospital Universitario San Pedro-CIBIR" }, { - "author_name": "CRISTIAN Castello-Abietar", - "author_inst": "HUCA" + "author_name": "Sonia Santibanez", + "author_inst": "Center of Rickettsiosis and Arthropod-Borne Diseases, Hospital Universitario San Pedro-CIBIR" }, { - "author_name": "VICTORIA ALVAREZ", - "author_inst": "HUCA" + "author_name": "Paula Santibanez", + "author_inst": "Center of Rickettsiosis and Arthropod-Borne Diseases, Hospital Universitario San Pedro-CIBIR" }, { - "author_name": "ELIAS CUESTA-LLAVONA", - "author_inst": "HUCA" + "author_name": "Cristina Cervera", + "author_inst": "Center of Rickettsiosis and Arthropod-Borne Diseases, Hospital Universitario San Pedro-CIBIR" }, { - "author_name": "ELIECER COTO", - "author_inst": "HOSPITAL UNIVERSITARIO CENTRAL DE ASTURIAS-HUCA" + "author_name": "Jose A. Oteo", + "author_inst": "Center of Rickettsiosis and Arthropod-Borne Diseases, Hospital Universitario San Pedro-CIBIR" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.20.107342", @@ -1461140,21 +1461362,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.16.20104489", - "rel_title": "A Computer Simulation Study on novel Corona Virus Transmission among the People in a Queue", + "rel_doi": "10.1101/2020.05.16.20104315", + "rel_title": "Modes of transmission of COVID-19 outbreak- a mathematical study", "rel_date": "2020-05-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.16.20104489", - "rel_abs": "The World Health Organization (WHO) on March 11, 2020, has declared the novel Corona virus (COVID-19) outbreak a global pandemic. It is essential to understand how coronavirus transmits from one person to another and this knowledge will help protect the vulnerable and limit the spread of the Corona virus. The mode of respiratory transmission of Corona virus is not completely understood as of date. Using a computer simulation, this paper analyses the probability of spreading of Corona virus through air among the people who are standing in a queue. The parameters such as the diameter of the virus particle, room temperature, relative humidity, height of the person, distance between the people and the waiting time in the queue are considered in the computer model to determine the distribution of Corona virus and hence identify the risk factor of spreading the Covid-19. This paper describes the possibilities of getting infectious when a Covid-19 infected person present in a queue and the impact on the waiting time, distance between people and the position in the queue on the transmission of Corona virus.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.16.20104315", + "rel_abs": "The world has now paid a lot of attention to the outbreak of novel coronavirus (COVID-19). This virus mainly transmitted between humans through directly respiratory droplets and close contacts. However, there is currently some evidence where it has been claimed that it may be indirectly transmitted. In this work, we study the mode of transmission of COVID-19 epidemic system based on the susceptible-infected-recovered (SIR) model. We have calculated the basic reproduction number R0 by next-generation matrix method. We observed that if R0 < 1, then disease-free equilibrium point is locally as well as globally asymptotically stable but when R0 > 1, the endemic equilibrium point exists and is globally stable. Finally, some numerical simulation is presented to validate our results.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Santhosh Samuel Mathews", - "author_inst": "Amzetta" + "author_name": "Chandan Maji", + "author_inst": "Vivekananda College, Thakurpukur" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1462726,35 +1462948,27 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.14.20102087", - "rel_title": "Modeling the Effects of Non-PharmaceuticalInterventions on COVID-19 Spread in Kenya", + "rel_doi": "10.1101/2020.05.13.20100784", + "rel_title": "Predicting SARS-CoV-2 infection trend using technical analysis indicators", "rel_date": "2020-05-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20102087", - "rel_abs": "May 14, 2020\n\nMathematical modeling of non-pharmaceutical interventions (NPIs) of COVID-19 in Kenya is presented. An SEIR compartment model is considered with additional compartments of hospitalized population whose condition is severe or critical and also the fatalities compartment. The basic reproduction number (R0) is computed by next generation matrix approach and later expressed as a time-dependent function so as to incorporate the NPIs into the model. The resulting system of ordinary differential equations (ODEs) are solved using fourth-order and fifth-order Runge-Kutta methods. Different intervention scenarios are considered and results show that, implementation of closure of education insitutions, curfew and partial lockdown yield predicted delayed peaks of the overall infections, severe cases and fatalities and subsequently containement of the pandemic in the country.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20100784", + "rel_abs": "COVID-19 pandemic is a global emergency caused by SARS-CoV-2 infection. Without efficacious drugs or vaccines, mass quarantine has been the main strategy adopted by governments to contain the virus spread. This has led to a significant reduction in the number of infected people and deaths and to a diminished pressure over the health care system. However, an economic depression is following due to the forced absence of worker from their job and to the closure of many productive activities. For these reasons, governments are lessening progressively the mass quarantine measures to avoid an economic catastrophe. Nevertheless, the reopening of firms and commercial activities might lead to a resurgence of infection. In the worst-case scenario, this might impose the return to strict lockdown measures. Epidemiological models are therefore necessary to forecast possible new infection outbreaks and to inform government to promptly adopt new containment measures. In this context, we tested here if technical analysis methods commonly used in the financial market might provide early signal of change in the direction of SARS-Cov-2 infection trend in Italy, a country which has been strongly hit by the pandemic. We conclude that technical analysis indicators can be usefully adopted to this aim.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Duncan K. Gathungu", - "author_inst": "Jomo Kenyatta University of Agriculture and Technology" - }, - { - "author_name": "Viona N. Ojiambo", - "author_inst": "Jomo Kenyatta University of Agriculture and Technology" - }, - { - "author_name": "Mark E. M. Kimathi", - "author_inst": "Machakos University" + "author_name": "Marino Paroli", + "author_inst": "Sapienza University of Rome" }, { - "author_name": "Samuel M. Mwalili", - "author_inst": "Jomo Kenyatta University of Agriculture and Technology" + "author_name": "Maria Isabella Sirinian", + "author_inst": "Sapienza University of Rome" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.16.20102178", @@ -1463848,27 +1464062,87 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.16.20103903", - "rel_title": "Causal Modeling of Twitter Activity During COVID-19", + "rel_doi": "10.1101/2020.05.16.20103838", + "rel_title": "Preliminary evaluation of COVID-19 disease outcomes, test capacities and management approaches among African countries.", "rel_date": "2020-05-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.16.20103903", - "rel_abs": "Understanding the characteristics of public attention and perception is an essential prerequisite for appropriate crisis management during adverse health events. This is even more crucial during a pandemic such as COVID-19, as primary responsibility of risk management is not centralized to a single institution, but distributed across society. While numerous studies utilize Twitter data in descriptive or predictive context during COVID-19 pandemic, causal modeling of public attention has not been investigated. In this study, we propose a causal inference approach to discover and quantify causal relationships between pandemic characteristics (e.g. number of infections and deaths) and Twitter activity as well as public sentiment. Our results show that the proposed method can successfully capture the epidemiological domain knowledge and identify variables that affect public attention and perception. We believe our work contributes to the field of infodemiology by distinguishing events that correlate with public attention from events that cause public attention.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.16.20103838", + "rel_abs": "BackgroundFollowing the declaration of COVID-19 as a global pandemic and the report of index case in Africa, the number of countries in Africa with confirmed cases of the infection has grown tremendously with disease now being reported in almost all countries on the continent, with the exemption of Lesotho after 75 days. It is therefore necessary to evaluate the disease outcomes among the African countries as the situation unfolds for early identification of best practices for adoption.\n\nMethodsIn this study, COVID-19 disease outcomes (confirmed cases, deaths and recoveries), testing capacities and disease management approaches among African countries were evaluated. The relationship between COVID-19 infections in African countries and their performance on global resilient indices including the Human Development Index (HDI), performance on Sustainable Development Goals (SDGs) and the Global Risk Index (GRI) were also examined. Data acquired from various standard databases were evaluated over a period of 75 days from the date of reporting the index case.\n\nResultsThis study has revealed compelling spatial differences in the incidence, deaths and recoveries from COVID-19 among African countries. Egypt, South Africa, Morocco and Algeria were clustered as countries with highest values of COVID-19 disease outcomes on the continent during the 75-day period of observation. The cluster analysis and comparison of countries in terms of percentage recovered cases of confirmed infections revealed that Mauritius, Mauritania, Gambia, Burkina Faso, Madagascar, Togo and Uganda had the highest scores. Comparative analysis of COVID-19 across the world revealed that the parameters were relatively inconsequential in Oceania and Africa continents, while Europe, North America and Asia had significantly higher cases of disease outcomes. For COVID-19 testing capacities, South Africa, Ghana and Egypt are leading in total number of tests carried out. However when the number of tests carried out were related to population number of the countries, Djibouti, Mauritius, Ghana and South Africa are found to be the leading countries. With respect to management of the disease in Africa, all the countries adopted the WHO protocols, personal hygiene, economic palliatives and social distancing measures. Only three countries in Africa (Madagascar, Togo and Burkina Faso) had a state supported initiative to utilise traditional medicines or herbs as alternatives to control COVID-19. Additionally, most of the countries are providing prompt treatment of the patients with a range of drugs especially Hydroxychloroquine, Chloroquine and Chloroquine-Azithromycin combination. The study found that no strong relationship currently exists between the global resilient indicators (HDI, SDG and GRI) and COVID-19 cases across Africa.\n\nConclusionsThis study has revealed compelling spatial differences in disease outcomes among African countries and also found testing capacities for COVID-19 to be abysmally low in relation to the population. During the 75 days of observation, African countries have recorded significantly low number of deaths associated with COVID-19 and relatively high recovery rates. Countries in Africa with higher rate of recovery from the disease were found to have adopted strict adherence to some of WHO protocol to contain the disease, isolate all those who test positive to the disease and provide prompt treatment of the patients with a range of drugs especially Hydroxychloroquine, Chloroquine and Chloroquine-Azithromycin combination. The study recommends that the approaches adopted by the African countries which achieved high recovery rates from COVID-19 should be integrated into healthcare management plans for the disease across the continent even as the situation unfolds.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Oguzhan Gencoglu", - "author_inst": "Tampere University" + "author_name": "Adebayo A Otitoloju", + "author_inst": "Department of Zoology, Ecotoxicology & Conservation Unit, University of Lagos" }, { - "author_name": "Mathias Gruber", - "author_inst": "-" + "author_name": "Esther O Oluwole", + "author_inst": "Department of Community Health & Primary Care, College of Medicine, University of Lagos, Idi-Araba, Lagos, Nigeria" + }, + { + "author_name": "Kafilat A Bawa-Allah", + "author_inst": "Department of Zoology, Ecotoxicology & Conservation Unit, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Mayowa J Fasona", + "author_inst": "Department of Geography, Faculty of Social Sciences, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Ifeoma P Okafor", + "author_inst": "Department of Community Health & Primary Care, College of Medicine, University of Lagos, Idi-Araba, Lagos, Nigeria" + }, + { + "author_name": "Chukwuemeka Isanbor", + "author_inst": "Department of Chemistry, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Vincent O Osunkalu", + "author_inst": "Department of Haematology & Blood Transfusion, College of Medicine, University of Lagos, Idi-Araba, Lagos, Nigeria" + }, + { + "author_name": "Abimbola A Sowemimo", + "author_inst": "Department of Pharmacognosy, College of Medicine, University of Lagos, Idi-Araba, Lagos, Nigeria" + }, + { + "author_name": "Obafemi A Keshinro", + "author_inst": "Academic Planning Unit, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Idowu A Aneyo", + "author_inst": "Department of Zoology, Ecotoxicology & Conservation Unit, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Olawale S Folarin", + "author_inst": "Department of Zoology, Ecotoxicology & Conservation Unit, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Akinbami A Oladokun", + "author_inst": "Department of Zoology, Ecotoxicology & Conservation Unit, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Oluwatosin J Akinsola", + "author_inst": "Department of Community Health & Primary Care, College of Medicine, University of Lagos, Idi-Araba, Lagos, Nigeria" + }, + { + "author_name": "Christianah I Ayolabi", + "author_inst": "Department of Microbiology, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Tenny O Egwuatu", + "author_inst": "Department of Microbiology, Faculty of Science, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Victor A Owoyomi", + "author_inst": "Department of Sociology, Faculty of Social Sciences, University of Lagos, Akoka, Lagos, Nigeria" + }, + { + "author_name": "Anthony E Ogbeibu", + "author_inst": "Department of Animal and Environmental Biology, Faculty of Life Sciences, University of Benin, Benin City, Edo State, Nigeria" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.05.16.20104141", @@ -1465390,39 +1465664,111 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2020.05.13.20100602", - "rel_title": "Can we use these masks? Rapid Assessment of the Inhalation Resistance Performance of Uncertified Medical Face Masks in the Context of Restricted Resources Imposed during a Public Health Emergency", + "rel_doi": "10.1101/2020.05.14.20101576", + "rel_title": "Characteristics and outcome of SARS-CoV-2 infection in cancer patients.", "rel_date": "2020-05-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20100602", - "rel_abs": "In the case of a public health emergency such as the COVID-19 pandemic, access to large quantities of appropriate personal protection equipment (PPE) has presented a significant problem. A shortage of face masks and respirators has been widely reported across the world. A concerted effort to manufacture high volumes has not unsurprisingly put pressure on the supply chain and the important certification processes. PPE procured or donated as uncertified stock requires rigorous, expedient and scientifically informed evidence before decisions can be made regarding suitable deployment, expensive certification, return or possible destruction of stock. This paper reports a series of experiments devised in reaction to this situation. In this study, an experimental methodology for the assessment of the filtration performance of samples of real-world, uncertified, fluid resistant surgical masks (FRSM type IIR) was evaluated in the resource limited (lockdown) environment of the COVID-19 pandemic. A steady-state flow rig was adapted to incorporate a bespoke filter flow chamber for mounting face masks in order to evaluate the resistance to air flow as an indicator of mask inhalation performance. Pure air was drawn through a specified control surface area at known flow rate conditions; the resistance to the air flow through the masks was measured as the resulting pressure drop. Over 60 tests were performed from 4 different, randomly sampled batches and compared to a control sample of EN Type IIR certified FRSM masks. Steady-state volumetric airflow rates of 30 and 95 lmin-1 were chosen to represent deep breathing and vigorous exercise conditions respectively. The results showed that the sample masks produced a pressure drop of between 26% to 58% compared to the control batch at the lower flow rate and 22% to 55% at the higher rate. The results for each sample were consistent across both flow rates. Within the group of masks tested, two sets (between 48% and 58% of the reference set) showed the potential to be professionally assessed for appropriate deployment in a suitable setting. Although the absolute values of pressure drop measured by this method are unlikely to correlate with other testing approaches, the observed, indicative trends and relative performance of the masks is key to this approach. Critically, this method does not replace certification but it has enabled a public body to quickly make decisions; certify, re-assign, refund, thus saving time and resources. The total time spent conducting the tests was less than 8 hours and the low cost method proposed can be repurposed for low resource regions.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.14.20101576", + "rel_abs": "BackgroundConcerns have emerged about the higher risk of fatal COVID-19 in cancer patients. In this paper, we review the experience of a comprehensive cancer center.\n\nMethodsA prospective registry was set up at Institut Curie at the beginning of the COVID-19 pandemic. All cancer patients with suspected or proven COVID-19 were entered and actively followed for 28 days.\n\nResultsAmong 9,842 patients treated at Institut Curie between mid-March and early May 2020, 141 (1.4%) were diagnosed with COVID-19, based on RT-PCR testing and/or CT-scan. In line with our case-mix, breast cancer (40%) was the most common tumor type, followed by hematological and lung malignancies (both 13%). Patients with active cancer therapy or/and advanced cancer accounted for 88% and 69% of patients, respectively. At diagnosis, 79% of patients had COVID-19 related symptoms, with an extent of lung parenchyma involvement [≤]50% in 90% of patients. Blood count variations and C-reactive protein elevation were the most common laboratory abnormalities. Antibiotics and antiviral agents were administered in 48% and 7% of patients, respectively. At the time of analysis, 26 patients (18%) have died from COVID-19, and 81 (57%) were cured. Independent prognostic factors at the time of COVID-19 diagnosis associated with death or intensive care unit admission were extent of COVID-19 pneumonia and decreased O2 saturation.\n\nConclusionCOVID-19 incidence and presentation in cancer patients appear to be very similar to those in the general population. The outcome of COVID-19 is primarily driven by the initial severity of infection rather than patient or cancer characteristics.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Steven Begg", - "author_inst": "University of Brighton" + "author_name": "Clemence Basse", + "author_inst": "Institut Curie" }, { - "author_name": "Nwabueze G Emekwuru", - "author_inst": "Coventry University" + "author_name": "Sarah Diakite", + "author_inst": "Institut Curie" }, { - "author_name": "Nicolas Miche", - "author_inst": "University of Brighton" + "author_name": "Vincent Servois", + "author_inst": "Institut Curie" }, { - "author_name": "Bill Whitney", - "author_inst": "University of Brighton" + "author_name": "Maxime Frelaut", + "author_inst": "Institut Curie" }, { - "author_name": "Obuks Ejohwomu", - "author_inst": "University of Manchester" + "author_name": "Aurelien Noret", + "author_inst": "Institut Curie" + }, + { + "author_name": "Audrey Bellesoeur", + "author_inst": "Institut Curie" + }, + { + "author_name": "Pauline Moreau", + "author_inst": "Institut Curie" + }, + { + "author_name": "Marie-Ange Massiani", + "author_inst": "Institut Curie" + }, + { + "author_name": "Anne-Sophie Bouyer", + "author_inst": "Institut Curie" + }, + { + "author_name": "perrine vuagnat", + "author_inst": "institut curie" + }, + { + "author_name": "SAndra Malak", + "author_inst": "Institut Curie" + }, + { + "author_name": "Francois-Clement Bidard", + "author_inst": "Institut Curie" + }, + { + "author_name": "Dominique Vanjak", + "author_inst": "Institut Curie" + }, + { + "author_name": "Irene Kriegel", + "author_inst": "Institut Curie" + }, + { + "author_name": "Alexis Burnod", + "author_inst": "Institut Curie" + }, + { + "author_name": "Geoffroy Bilger", + "author_inst": "Institut Curie" + }, + { + "author_name": "Toulsie Ramtohul", + "author_inst": "Institut Curie" + }, + { + "author_name": "Gille Dhonneur", + "author_inst": "Institut Curie" + }, + { + "author_name": "Carole Bouleuc", + "author_inst": "Institut Curie" + }, + { + "author_name": "Nathalie Cassoux", + "author_inst": "Institut Curie" + }, + { + "author_name": "Xavier Paoletti", + "author_inst": "Institut Curie" + }, + { + "author_name": "Laurence Bozec", + "author_inst": "Institut Curie" + }, + { + "author_name": "Paul Cottu", + "author_inst": "Institut Curie" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "occupational and environmental health" + "category": "oncology" }, { "rel_doi": "10.1101/2020.05.14.20101808", @@ -1466464,147 +1466810,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.18.20105197", - "rel_title": "SARS-CoV-2 seroconversion in health care workers", + "rel_doi": "10.1101/2020.05.13.20097675", + "rel_title": "Assessment of service availability and Infection prevention measures in hospitals of Nepal during the transition phase of COVID-19 case surge", "rel_date": "2020-05-19", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.18.20105197", - "rel_abs": "BackgroundThe correlates of protection against SARS-CoV-2 and their longevity remain unclear. Studies in severely ill individuals have identified robust cellular and humoral immune responses against the virus. Asymptomatic infection with SARS-CoV-2 has also been described, but it is unknown whether this is sufficient to produce antibody responses.\n\nMethodsWe performed a cross-sectional study recruiting 554 health care workers from University Hospitals Birmingham NHS Foundation Trust who were at work and asymptomatic. Participants were tested for current infection with SARS-CoV-2 by nasopharyngeal swab for real-time polymerase chain reaction and for seroconversion by the measurement of anti-SARS-CoV-2 spike glycoprotein antibodies by enzyme linked immunosorbent assay. Results were interpreted in the context of previous, self-reported symptoms of illness consistent with COVID-19.\n\nResultsThe point prevalence of infection with SARS-CoV-2, determined by the detection of SARS-CoV-2 RNA on nasopharnygeal swab was 2.39% (n=13/544). Serum was available on 516 participants. The overall rate of seroconversion in the cohort was 24.4% (n=126/516). Individuals who had previously experienced a symptomatic illness consistent with COVID-19 had significantly greater seroconversion rates than those who had remained asymptomatic (37.5% vs 17.1%, {chi}2 =21.1034, p<0.0001). In the week preceding peak COVID-19-related mortality at UHBFT, seroconversion rates amongst those who were suffering from symptomatic illnesses peaked at 77.8%. Prior symptomatic illness generated quantitatively higher antibody responses than asymptomatic seroconversion. Seroconversion rates were highest amongst those working in housekeeping (34.5%), acute medicine (33.3%) and general internal medicine (30.3%) with lower rates observed in participants working in intensive care (14.8%) and emergency medicine (13.3%).\n\nConclusionsIn a large cross-sectional seroprevalence study of health-care workers, we demonstrate that asymptomatic seroconversion occurs, however prior symptomatic illness is associated with quantitatively higher antibody responses. The identification that the potential for seroconversion in health-care workers can associate differentially with certain hospital departments may inform future infection control and occupational health practices.\n\nResearch in contextO_ST_ABSEvidence before the studyC_ST_ABSTo date, no study has examined the cross-sectional seroprevalence of anti-SARS-CoV-2 antibodies in health care workers during the COVID-19 pandemic. Existing evidence suggests that the levels of SARS-CoV-2 antibodies developing following infection may vary with disease severity in keeping with previous coronavirus pandemics.\n\nAdded value of this studyWe demonstrate that seroconversion can occur in health care workers who have suffered no previous symptoms of SARS-Cov-2 infection. However, prior symptomatic infection tends to drive quantitatively superior antibody responses against the virus. We observed differential seroconversion rates in individuals working within different hospital departments. Using intensive care as a reference, the relative risk for seroconversion was greatest for those working in housekeeping, acute and general internal medicine.\n\nImplications of all the available evidenceInsight into the current seroprevalence of SARS-CoV-2 antibodies within a high-risk cohort of health-care workers is of direct relevance as a reference point for future community serological surveys. We provide further evidence of asymptomatic infection and seroconversion, strengthening the argument for regular, routine screening of health-care workers. Finally, we provide evidence that individuals working in particular roles within the NHS are at greater risk of seroconversion with significant implications for their occupational health.", - "rel_num_authors": 32, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20097675", + "rel_abs": "As with other coronavirus-affected countries, Nepals medical fraternity also expressed concerns regarding the governments public health strategies and hospital readiness in response to upgoing case surge. To gauge such response, we assessed service availability and Infection prevention and control (IPC) status in 110 hospitals situated across seven provinces. An electronic survey was sent out to the frontline clinicians working on those hospitals between 24th March and 7th April 2020; one response per hospital was analyzed. Hospitals were divided into small, medium, and large based on the total number of beds (small:[≤]15; medium:16-50; large:>50), and further categorized into public, private, and mixed based on the ownership. Out of 110 hospitals, 81% (22/27) of small, 39% (11/28) of medium, and 33% (18/55) of large hospitals had not allocated isolation beds for COVID-19 suspects. All small, majority of medium (89%; 25/28), and 50% of large hospitals did not have a functional intensive care unit (ICU) at the time of study. Nasopharyngeal (NP)/throat swab kits were available in one-third (35/110), whereas viral transport media (VTM), portable fridge box, and refrigerator were available in one-fifth (20%) of hospitals. Only one hospital (large/tertiary) had a functional PCR machine. Except for General practitioners, other health cadres--crucial during pandemics, were low in number. On IPC measures, the supplies of simple face masks, gloves and hand sanitizers were adequate in the majority of hospitals, however, N95-respirators, Filter masks, and PPE-suits were grossly lacking. Governments COVID-19 support was unevenly distributed across provinces; health facilities in Province 2, Gandaki, and Province 5 received fewer resources than others. Our findings alert the Nepalese and other governments to act early and proactively during health emergencies and not wait until the disease disrupts their health systems. Other countries with similar economy levels may undertake similar surveys to measure and improve their pandemic response.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Adrian M Shields", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" - }, - { - "author_name": "Sian E Faustini", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" - }, - { - "author_name": "Marisol Perez-Toledo", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Sian Jossi", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Erin L Aldera", - "author_inst": "Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Joel D Allen", - "author_inst": "School of Biological Sciences, University of Southampton, Southampton, UK" - }, - { - "author_name": "Saly Al-Taei", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" - }, - { - "author_name": "Claire Backhouse", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" - }, - { - "author_name": "Andrew Bosworth", - "author_inst": "University Hospital Birmingham NHS Foundation Trust, Birmingham, UK" - }, - { - "author_name": "Lyndsey Dunbar", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" - }, - { - "author_name": "Daniel Ebanks", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" - }, - { - "author_name": "Beena Emmanuel", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" - }, - { - "author_name": "Joanne Grey", - "author_inst": "University Hospital Birmingham NHS Foundation Trust, Birmingham, UK" - }, - { - "author_name": "I Michael Kidd", - "author_inst": "PHE Public Health Laboratory, Birmingham, UK" - }, - { - "author_name": "Golaeh McGinnell", - "author_inst": "University Hospital Birmingham NHS Foundation Trust, Birmingham, UK" - }, - { - "author_name": "Dee McLoughlin", - "author_inst": "Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Gabriella Morley", - "author_inst": "Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Danai Papakonstantinou", - "author_inst": "Institute of Microbiology and Infection, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Oliver Pickles", - "author_inst": "Surgical Research Laboratory, Institute of Cancer and Genomics Science, University of Birmingham, UK" - }, - { - "author_name": "Charlotte Poxon", - "author_inst": "Surgical Research Laboratory, Institute of Cancer and Genomics Science, University of Birmingham, UK" - }, - { - "author_name": "Megan Richter", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" - }, - { - "author_name": "Eloise Walker", - "author_inst": "Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Kasun Wanigasooriya", - "author_inst": "Surgical Research Laboratory, Institute of Cancer and Genomics Science, University of Birmingham, UK" - }, - { - "author_name": "Yasunori Watanabe", - "author_inst": "Oxford Glycobiology Institute, Department of Biochemistry, University of Oxford, Oxford, UK" - }, - { - "author_name": "Celina Whalley", - "author_inst": "Surgical Research Laboratory, Institute of Cancer and Genomics Science, University of Birmingham, UK" - }, - { - "author_name": "Agnieszka E Zielinska", - "author_inst": "Institute of Inflammation and Ageing, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Max Crispin", - "author_inst": "School of Biological Sciences, University of Southampton, Southampton, UK" + "author_name": "Suraj Bhattarai", + "author_inst": "Global Institute for Interdisciplinary Studies" }, { - "author_name": "David C Wraith", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" - }, - { - "author_name": "Andrew D Beggs", - "author_inst": "Surgical Research Laboratory, Institute of Cancer and Genomics Science, University of Birmingham, UK" - }, - { - "author_name": "Adam F Cunningham", - "author_inst": "Institute of Immunology and Immunotherapy, University of Birmingham, Birmingham, UK" + "author_name": "Jaya Dhungana", + "author_inst": "Chitwan Medical College" }, { - "author_name": "Mark T Drayson", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" + "author_name": "Tim Ensor", + "author_inst": "Nuffield Centre for International Health and Development, University of Leeds" }, { - "author_name": "Alex G Richter", - "author_inst": "Clinical Immunology Service, Institute of Immunology and Immunotherapy, University of Birmingham, UK" + "author_name": "Uttam Babu Shrestha", + "author_inst": "Global Institute for Interdisciplinary Studies" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", - "category": "allergy and immunology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.15.20096552", @@ -1468346,75 +1468580,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.11.20092692", - "rel_title": "Household transmission of COVID-19, Shenzhen, January-February 2020", + "rel_doi": "10.1101/2020.05.12.20093799", + "rel_title": "Video Consultation in Lung Transplant Recipients during the COVID-19 Pandemic", "rel_date": "2020-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.11.20092692", - "rel_abs": "Coronavirus disease 2019 has led to more than three million cases globally. Since the first family cluster of COVID-19 cases identified in Shenzhen in early January, most of the local transmission occurred within household contacts. Identifying the factors associated with household transmission is of great importance to guide preventive measures.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20093799", + "rel_abs": "BackgroundThe COVID-19 pandemic has disrupted health care systems worldwide. This is due to the demand for medical resources in other areas as well as concern for the risk of nosocomial SARS-CoV-2 exposure. The interruption of routine care is especially problematic for patients with chronic conditions requiring regular follow-up, such as lung transplant recipients. New methods like telemedicine are needed to provide care to these patients.\n\nMethodsA retrospective analysis of video consultations (VC) in comparison to on-site visits (OSV) was performed during a six-week period in a lung transplant center in Germany. VC included a structured work-up questionnaire and vital sign documentation.\n\nResultsDuring the 6-week study period, 75 VC were performed for 53 patients and 75 OSV by 51 patients occurred. By the end of our study period, 77% of physician-patient contacts occurred via VC. Overall, physician-patient consultations were reduced by 47% in comparison to an equivalent time frame in 2019. In 62% of cases, VC resulted in a concrete clinical decision. For two VC patients, the indication for inpatient admission was established during the consultation. One COVID-19 patient in home quarantine was admitted due to respiratory failure detected by VC. Patient satisfaction with VC was high.\n\nConclusionsBy transitioning to VC, OSV for lung transplant patients during the COVID-19 pandemic was reduced. VC was well received by the majority of patients. This technology can be adopted to provide care for a wide range of chronic illnesses.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Lan Wei", - "author_inst": "Shenzhen Center for Disease Control and Prevention" - }, - { - "author_name": "Qiuying Lv", - "author_inst": "Shenzhen Center for Disease Control and Prevention" - }, - { - "author_name": "Ying Wen", - "author_inst": "Shenzhen Center for Disease Control and Prevention" - }, - { - "author_name": "Shuo Feng", - "author_inst": "Oxford Vaccine Group, University of Oxford" - }, - { - "author_name": "Wei Gao", - "author_inst": "Shenzhen Center for Disease Control and Prevention" - }, - { - "author_name": "Zhigao Chen", - "author_inst": "Shenzhen Center for Disease Control and Prevention" - }, - { - "author_name": "Bin Cao", - "author_inst": "Shenzhen Center for Disease Control and Prevention" - }, - { - "author_name": "Xiaoliang Wu", - "author_inst": "Shenzhen Center for Disease Control and Prevention" - }, - { - "author_name": "Yan Lu", - "author_inst": "Shenzhen Center for Disease Control and Prevention" + "author_name": "Moritz Z. Kayser", + "author_inst": "Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany" }, { - "author_name": "Jin Zhao", - "author_inst": "zhaoj@szcdc.net" + "author_name": "Christina Valtin", + "author_inst": "Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany" }, { - "author_name": "Xuan Zou", - "author_inst": "Shenzhen Center for Disease Control and Prevention" + "author_name": "Mark Greer", + "author_inst": "Hannover Medical School, Department of Respiratory Medicine; Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), German Center for L" }, { - "author_name": "Tiejian Feng", - "author_inst": "Shenzhen Center for Disease Control and Prevention" + "author_name": "Bernd Karow", + "author_inst": "Department for Hospital Innovation and Quality Management, Hannover Medical School, Hannover, Germany" }, { - "author_name": "Benjamin J Cowling", - "author_inst": "The University of Hong Kong" + "author_name": "Jan Fuge", + "author_inst": "Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany; Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), " }, { - "author_name": "Shujiang Mei", - "author_inst": "Shenzhen Center for Disease Control and Prevention" + "author_name": "Jens Gottlieb", + "author_inst": "Department of Respiratory Medicine, Hannover Medical School, Hannover, Germany; Biomedical Research in Endstage and Obstructive Lung Disease Hannover (BREATH), " } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.05.15.20094284", @@ -1470252,47 +1470454,63 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.12.20094524", - "rel_title": "Perceived versus proven SARS-CoV-2 specific immune responses in health care workers", + "rel_doi": "10.1101/2020.05.12.20095885", + "rel_title": "Cardiac Structural and Functional Characteristics in Patients with Coronavirus Disease 2019: A Serial Echocardiographic Study", "rel_date": "2020-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20094524", - "rel_abs": "There have been concerns about high rates of thus far undiagnosed SARS-CoV-2 infections in the health care system. The COVID-19 Contact (CoCo) Study follows 217 frontline healthcare professionals at a university hospital with weekly SARS-CoV-2 specific serology (IgA/IgG). Study participants estimated their personal likelihood of having had a SARS-CoV-2 infection with a mean of 20.9% (range 0 to 90%). In contrast, anti-SARS-CoV-2-IgG prevalence was about 1-2% at baseline. Regular anti-SARS-CoV-2 IgG testing of health-care professionals may aid in directing resources for protective measures and care of COVID-19 patients in the long run.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20095885", + "rel_abs": "BACKGROUNDIncreasing attention has been paid to cardiac involvement in patients with coronavirus disease 2019 (COVID-19). Yet, scarce information is available regarding the morphological and functional features of cardiac impairments in these patients.\n\nMETHODSWe conducted a prospective and serial echocardiographic study to investigate the structural and functional cardiac changes among COVID-19 patients admitted to the intensive care unit (ICU). From January 21 to April 8, 2020, a total of 51 ICU patients (31 critically ill and 20 severely ill) with confirmed COVID-19 were monitored by serial transthoracic echocardiography examinations. Outcomes were followed up until April 8, 2020.\n\nRESULTSOf 51 ICU patients, 33 (64.7%) had cardiovascular comorbidities. Elevations of levels of cardiac biomarkers including high-sensitivity cardiac troponin-I (hs-cTnI) and brain natriuretic peptide were observed in 62.7% and 86.3% of patients, respectively. Forty-two (82.3%) had at least one left-heart and/or right-heart echocardiographic abnormality. The overall median left ventricular ejection fraction (LVEF) was 65.0% (IQR 58.0-69.0%), with most (44/86.3%) having preserved LVEF. Sixteen patients (31.4%) had increased pulmonary artery systolic pressure, and 14 (27.5%) had right-ventricle (RV) enlargement. During the study period, 12 (23.5%) patients died. LVEF was comparable between survivors and non-survivors, while non-survivors had more often pulmonary hypertension (58.3% vs. 23.1%; P=0.028) and RV enlargement (58.3% vs. 17.9%, P=0.011). Kaplan-Meier analysis demonstrated similar survival curves between patients with vs. without echocardiographic left-heart abnormalities (P=0.450 by log-rank test), while right-heart abnormalities had adverse impact on mortality (P=0.012 by log-rank test).\n\nCONCLUSIONSTypical cardiac abnormality in ICU patients with COVID-19 was right-heart dysfunction with preserved LVEF. Echocardiographic right-heart dysfunction was associated with disease severity and increased mortality in patients affected by COVID-19.\n\nCLINICAL TRIAL REGISTRATIONUnique identifier: NCT04352842.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Georg MN Behrens", - "author_inst": "Hannover Medical School" + "author_name": "Heng Ge", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" }, { - "author_name": "Anne Cossmann", - "author_inst": "Hannover Medical School" + "author_name": "Mingli Zhu", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" }, { - "author_name": "Metodi V Stankov", - "author_inst": "Hannover Medical School" + "author_name": "Jing Du", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" }, { - "author_name": "Torsten Witte", - "author_inst": "Hannover Medical School" + "author_name": "Yong Zhou", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" }, { - "author_name": "Diana Ernst", - "author_inst": "Hannover Medical School" + "author_name": "Wei Wang", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" }, { - "author_name": "Christine Happle", - "author_inst": "Hannover Medical School" + "author_name": "Wei Zhang", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" }, { - "author_name": "Alexandra Jablonka", - "author_inst": "Hannover Medical School" + "author_name": "Handong Jiang", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" + }, + { + "author_name": "Zhiqing Qiao", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" + }, + { + "author_name": "Zhichun Gu", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" + }, + { + "author_name": "Fenghua Li", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" + }, + { + "author_name": "Jun Pu Jr.", + "author_inst": "Renji Hospital, School of Medicine, Shanghai Jiaotong University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2020.05.11.20098335", @@ -1471414,43 +1471632,83 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.13.20098186", - "rel_title": "Excess Out-Of-Hospital Mortality and Declining Oxygen Saturation Documented by EMS During the COVID-19 Crisis in Tijuana, Mexico", + "rel_doi": "10.1101/2020.05.12.20099135", + "rel_title": "Covid-19 by Race and Ethnicity: A National Cohort Study of 6 Million United States Veterans", "rel_date": "2020-05-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20098186", - "rel_abs": "ObjectiveEmergency medical services (EMS) may serve as a key source of real-time data about the evolving health of COVID-19 affected populations, especially in low-and-middle-income countries (LMICs) with less rapid and reliable vital statistic registration systems. Although official COVID-19 statistics in Mexico report almost exclusively in-hospital mortality events, excess out-of-hospital mortality has been identified in other settings, including one EMS study in Italy that showed a 58% increase. EMS and hospital reports from several countries have suggested that silent hypoxemia--low oxygen saturation (SpO2) in the absence of dyspnea--is associated with COVID-19 outbreaks. It is unclear, however, how these phenomena can be generalized to LMICs. We assess how EMS data can be used in a sentinel capacity in Tijuana, a city on the Mexico-United States border with earlier exposure to COVID-19 than many LMIC settings.\n\nMethodsWe calculated numbers of weekly out-of-hospital deaths and respiratory cases seen by EMS in Tijuana, and estimate the difference between peak-epidemic rates (during April 14th-May 11th) and forecasted 2014-2019 trends. Results were compared with official COVID-19 statistics, stratified by neighborhood socioeconomic status (SES), and examined for changing demographic or clinical features, including mean (SpO2).\n\nResultsAn estimated 194.7 (95%CI: 135.5-253.9) excess out-of-hospital deaths events occurred, representing an increase of 145% (70%-338%) compared to forecasted trends. During the same window, only 8 COVID-19-positive, out-of-hospital deaths were reported in official statistics. This corresponded with a rise in respiratory cases of 274% (119%-1142%), and a drop in mean SpO2 to 77.7%, from 90.2% at baseline. The highest out-of-hospital death rates were observed in low-SES areas, although respiratory cases were more concentrated in high-SES areas.\n\nConclusionsEMS systems may play an important sentinel role in monitoring excess out-of-hospital mortality and other trends during the COVID-19 crisis in LMICs. Using EMS data, we observed increases in out-of-hospital deaths in Tijuana that were nearly threefold greater magnitude than increases reported using EMS data in Italy. Increased testing in out-of-hospital settings may be required to determine if excess mortality is being driven by COVID-19 infection, health system saturation, or patient avoidance of healthcare. We also found evidence of worsening rates of hypoxemia among respiratory patients seen by EMS, suggesting a rise in silent hypoxemia, which should be met with increased detection and clinical management efforts. Finally, we observed that social disparities in out-of-hospital death that warrant monitoring and amelioration.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20099135", + "rel_abs": "BackgroundThere is growing concern that racial and ethnic minority communities around the world are experiencing a disproportionate burden of morbidity and mortality from symptomatic SARS-Cov-2 infection or coronavirus disease 2019 (Covid-19). Most studies investigating racial and ethnic disparities to date have focused on hospitalized patients or have not characterized who received testing or those who tested positive for Covid-19.\n\nObjectiveTo compare patterns of testing and test results for coronavirus 2019 (Covid-19) and subsequent mortality by race and ethnicity in the largest integrated healthcare system in the United States.\n\nDesignRetrospective cohort study.\n\nSettingUnited States Department of Veterans Affairs (VA).\n\nParticipants5,834,543 individuals in care, among whom 62,098 were tested and 5,630 tested positive for Covid-19 between February 8 and May 4, 2020.\n\nExposuresSelf-reported race/ethnicity.\n\nMain outcome measuresWe evaluated associations between race/ethnicity and receipt of Covid-19 testing, a positive test result, and 30-day mortality, accounting for a wide range of demographic and clinical risk factors including comorbid conditions, site of care, and urban versus rural residence.\n\nResultsAmong all individuals in care, 74% were non-Hispanic white (white), 19% non-Hispanic black (black), and 7% Hispanic. Compared with white individuals, black and Hispanic individuals were more likely to be tested for Covid-19 (tests per 1000: white=9.0, [95% CI 8.9 to 9.1]; black=16.4, [16.2 to 16.7]; and Hispanic=12.2, [11.9 to 12.5]). While individuals from minority backgrounds were more likely to test positive (black vs white: OR 1.96, 95% CI 1.81 to 2.12; Hispanic vs white: OR 1.73, 95% CI 1.53 to 1.96), 30-day mortality did not differ by race/ethnicity (black vs white: OR 0.93, 95% CI 0.64 to 1.33; Hispanic vs white: OR 1.07, 95% CI 0.61 to 1.87).\n\nConclusionsBlack and Hispanic individuals are experiencing an excess burden of Covid-19 not entirely explained by underlying medical conditions or where they live or receive care. While there was no observed difference in mortality by race or ethnicity, our findings may underestimate risk in the broader US population as health disparities tend to be reduced in VA.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Joseph Friedman", - "author_inst": "Center for Social Medicine, University of California, Los Angeles (UCLA), USA" + "author_name": "Christopher T. Rentsch", + "author_inst": "US Department of Veterans Affairs, London School of Hygiene and Tropical Medicine" }, { - "author_name": "Alheli Calderon-Villarreal", - "author_inst": "Academia Mexicana de la Salud, Tijuana, Mexico" + "author_name": "Farah Kidwai-Khan", + "author_inst": "US Department of Veterans Affairs, Yale School of Medicine" }, { - "author_name": "Ietza Bojorquez", - "author_inst": "El Colegio de la Frontera Norte, Tijuana, Mexico" + "author_name": "Janet P. Tate", + "author_inst": "US Department of Veterans Affairs, Yale School of Medicine" }, { - "author_name": "Carlos Vera Hernandez", - "author_inst": "Mexican Red Cross, Tijuana, Mexico" + "author_name": "Lesley S. Park", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "David Schriger", - "author_inst": "Department of Emergency Medicine, UCLA" + "author_name": "Joseph T. King Jr.", + "author_inst": "US Department of Veterans Affairs, Yale School of Medicine" + }, + { + "author_name": "Melissa Skanderson", + "author_inst": "US Department of Veterans Affairs" + }, + { + "author_name": "Ronald G. Hauser", + "author_inst": "US Department of Veterans Affairs, Yale School of Medicine" + }, + { + "author_name": "Anna Schultze", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Christopher I. Jarvis", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Mark Holodniy", + "author_inst": "US Department of Veterans Affairs, Stanford University School of Medicine" + }, + { + "author_name": "Vincent Lo Re III", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Kathleen M. Akgun", + "author_inst": "US Department of Veterans Affairs, Yale School of Medicine" + }, + { + "author_name": "Kristina Crothers", + "author_inst": "VA Puget Sound Health Care System, University of Washington School of Medicine" + }, + { + "author_name": "Tamar H. Taddei", + "author_inst": "US Department of Veterans Affairs, Yale School of Medicine" + }, + { + "author_name": "Matthew S. Freiberg", + "author_inst": "Tennessee Valley Health Care System, Vanderbilt University Medical Center" }, { - "author_name": "Eva Tovar Hirashima", - "author_inst": "Mexican Red Cross, Tijuana, Mexico" + "author_name": "Amy C. Justice", + "author_inst": "US Department of Veterans Affairs, Yale School of Medicine, Yale School of Public Health" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "emergency medicine" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.05.11.20098798", @@ -1472724,39 +1472982,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.05.16.099747", - "rel_title": "REMBRANDT: A high-throughput barcoded sequencing approach for COVID-19 screening.", + "rel_doi": "10.1101/2020.05.16.099317", + "rel_title": "Distinct conformational states of SARS-CoV-2 spike protein", "rel_date": "2020-05-17", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.16.099747", - "rel_abs": "The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), also known as 2019 novel coronavirus (2019-nCoV), is a highly infectious RNA virus. A still-debated percentage of patients develop coronavirus disease 2019 (COVID-19) after infection, whose symptoms include fever, cough, shortness of breath and fatigue. Acute and life-threatening respiratory symptoms are experienced by 10-20% of symptomatic patients, particularly those with underlying medical conditions that includes diabetes, COPD and pregnancy. One of the main challenges in the containment of COVID-19 is the identification and isolation of asymptomatic/pre-symptomatic individuals. As communities re-open, large numbers of people will need to be tested and contact-tracing of positive patients will be required to prevent additional waves of infections and enable the continuous monitoring of the viral loads COVID-19 positive patients. A number of molecular assays are currently in clinical use to detect SARS-CoV-2. Many of them can accurately test hundreds or even thousands of patients every day. However, there are presently no testing platforms that enable more than 10,000 tests per day. Here, we describe the foundation for the REcombinase Mediated BaRcoding and AmplificatioN Diagnostic Tool (REMBRANDT), a high-throughput Next Generation Sequencing-based approach for the simultaneous screening of over 100,000 samples per day. The REMBRANDT protocol includes direct two-barcoded amplification of SARS-CoV-2 and control amplicons using an isothermal reaction, and the downstream library preparation for Illumina sequencing and bioinformatics analysis. This protocol represents a potentially powerful approach for community screening, a major bottleneck for testing samples from a large patient population for COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.16.099317", + "rel_abs": "The ongoing SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic has created urgent needs for intervention strategies to control the crisis. The spike (S) protein of the virus forms a trimer and catalyzes fusion between viral and target cell membranes - the first key step of viral infection. Here we report two cryo-EM structures, both derived from a single preparation of the full-length S protein, representing the prefusion (3.1[A] resolution) and postfusion (3.3[A] resolution) conformations, respectively. The spontaneous structural transition to the postfusion state under mild conditions is independent of target cells. The prefusion trimer forms a tightly packed structure with three receptor-binding domains clamped down by a segment adjacent to the fusion peptide, significantly different from recently published structures of a stabilized S ectodomain trimer. The postfusion conformation is a rigid tower-like trimer, but decorated by N-linked glycans along its long axis with almost even spacing, suggesting possible involvement in a mechanism protecting the virus from host immune responses and harsh external conditions. These findings advance our understanding of how SARS-CoV-2 enters a host cell and may guide development of vaccines and therapeutics.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Dario Palmieri", - "author_inst": "The Ohio State University" + "author_name": "Yongfei Cai", + "author_inst": "Boston Childrens Hospital" }, { - "author_name": "Jalal K Siddiqui", - "author_inst": "The Ohio State University" + "author_name": "Jun Zhang", + "author_inst": "Boston Childrens Hospital" }, { - "author_name": "Anne Gardner", - "author_inst": "The Ohio State University" + "author_name": "Tianshu Xiao", + "author_inst": "Boston Childrens Hospital" }, { - "author_name": "Richard Fishel", - "author_inst": "The Ohio State University" + "author_name": "Hanqin Peng", + "author_inst": "Boston Childrens Hospital" }, { - "author_name": "Wayne Miles", - "author_inst": "The Ohio State University" + "author_name": "Sarah M. Sterling", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Richard M. Walsh Jr.", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Shaun Rawson", + "author_inst": "Harvard Medical School" + }, + { + "author_name": "Sophia Rits-Volloch", + "author_inst": "Boston Childrens Hospital" + }, + { + "author_name": "Bing Chen", + "author_inst": "Boston Childrens Hospital" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "new results", - "category": "molecular biology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.05.17.100404", @@ -1473934,33 +1474208,25 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.05.12.20099481", - "rel_title": "The Evaluation of Deep Neural Networks and X-Ray as a Practical Alternative for Diagnosis and Management of COVID-19", + "rel_doi": "10.1101/2020.05.13.20099978", + "rel_title": "A Sparse Gaussian Network Model for Prediction the Growth Trend of COVID-19 Overseas Import Case: When can Hong Kong Lift the International Traffic Blockad?", "rel_date": "2020-05-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.12.20099481", - "rel_abs": "High-resolution computed tomography radiology is a critical tool in the diagnosis and management of COVID-19 infection; however, in smaller clinics around the world, there is a shortage of radiologists available to analyze these images. In this paper, we compare the performance of 16 available deep learning algorithms to help identify COVID19. We utilize an already existing diagnostic technology (X-ray) and an already existing neural network (ResNet-50) to diagnose COVID-19. Our approach eliminates the extra time and resources needed to develop new technology and associated algorithm, thus aiding the front-line in the race against the COVID-19 pandemic. Results show that ResNet-50 is the optimal pretrained neural network for the detection of COVID-19, using three different cross-validation ratios, based on training time, accuracy, and network size. We also present a custom visualization of the results that can be used to highlight important visual biomarkers of the disease and disease progression.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.13.20099978", + "rel_abs": "The COVID-19 virus was first discovered from China. It has been widely spread internationally. Currently, compare with the rising trend of the overall international epidemic situation, Chinas domestic epidemic situation has been contained and shows a steady and upward trend. In this situation, overseas imports have become the main channel for china to increase the number of infected people. Therefore, how to track the spread channel of international epidemics and predict the growth of overseas case imports is become an open research question. This study proposes a Gaussian sparse network model based on lasso and uses Hong Kong as an example. To explore the COVID-19 virus from a network perspective and analyzes 75 consecutive days of COV-19 data in 188 countries and regions around the world. This article establishes an epidemic spread relationship network between Hong Kong and various countries and regions around the world and build a regression model based on network information to fit Hong Kongs COV-19 epidemic growth data. The results show that the regression model based on the relationship network can better fit the existing cumulative number growth curve. After combining the SEIJR model, we predict the future development trend of cumulative cases in Hong Kong (without blocking international traffic). Based on the prediction results, we suggest that Hong Kong can lift the international traffic blockade from early to mid-June.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Mohamed Elgendi", - "author_inst": "University of British Columbia" - }, - { - "author_name": "Rich Fletcher", - "author_inst": "Massachusetts Institute of Technology" - }, - { - "author_name": "Newton Howard", - "author_inst": "University of Oxford" + "author_name": "Miao Rui", + "author_inst": "Faculty of Information Technology, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China" }, { - "author_name": "Carlo Menon", - "author_inst": "Simon FraserUniversity" + "author_name": "Dang Qi", + "author_inst": "Faculty of Information Technology, Macau University of Science and Technology, Avenida Wai Long, Taipa, Macau, China" }, { - "author_name": "Rabab Ward", - "author_inst": "University of British Columbia" + "author_name": "Liang Yong", + "author_inst": "State Key Laboratory of Quality Research in Chinese Medicines, Macau University of Science and Techn" } ], "version": "1", @@ -1475516,45 +1475782,25 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.05.14.095620", - "rel_title": "Unveiling diffusion pattern and structural impact of the most invasive SARS-CoV-2 spike mutation", + "rel_doi": "10.1101/2020.05.14.096131", + "rel_title": "The Red Queen's Crown: an evolutionary arms race between coronaviruses and mammalian species reflected in positive selection of the ACE2 receptor among many species", "rel_date": "2020-05-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.14.095620", - "rel_abs": "Starting in Wuhan, China, SARS-CoV-2 epidemics quickly propagated worldwide in less than three months, geographically sorting genomic variants in newly established propagules of infections. Stochasticity in transmission within and between countries and/or actual advantage in virus transmissibility could explain the high frequency reached by some genomic variants during the course of the outbreak.\n\nUsing a suite of statistical, population genetics, and theoretical approaches, we show that the globally most represented spike protein variant (i.e., the G clade, A [->] G nucleotide change at genomic position 23,403; D [->] G amino acid change at spike protein position 614) i) underwent a significant demographic expansion in most countries not explained by stochastic effects or enhanced pathogenicity; ii) affects the spike S1/S2 furin-like site increasing its conformational plasticity (short range effect), and iii) modifies the internal motion of the receptor-binding domain affecting its cross-connection with other functional domains (long-range effect).\n\nOur study unambiguously links the spread of the G614 with a non-random process, and we hypothesize that this process is related to the selective advantage produced by a specific structural modification of the spike protein. We conclude that the different conformation of the S1/S2 proteolytic site is at the basis of the higher transmission rate of this invasive SARS-CoV-2 variant, and provide structural information to guide the design of selective and efficient drugs.", - "rel_num_authors": 7, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.14.096131", + "rel_abs": "The world is going through a global viral pandemic with devastating effects on human life and socioeconomic activities. This pandemic is the result of a zoonotic coronavirus, Severe Acute Respirsatory Syndrom Coronavirus 2 (SARS-CoV-2) which is believed to have originated in bats and transferred to humans possibly through an intermediate host species (Zhou et al. 2020; Coronaviridae Study Group of the International Committee on Taxonomy of Viruses 2020). The virus attacks host cells by attaching to a cell membrane surface protein receptor called ACE2 (Ge et al. 2013; Zhou et al. 2020). Given the critical role of ACE2 as a binding receptor for a number of coronaviruses, we studied the molecular evolution of ACE2 in a diverse range of mammalian species. Using ACE2 as the target protein, we wanted to specifically test the Red Queen hypothesis (Dawkins and Krebs 1979) where the parasite and host engage in an evolutionary arms race which can result in positive selection of their traits associated to their fitness and survival. Our results clearly show a phylogenetically broad evolutionary response, in the form of positive selection detected at the codon-level in ACE2. We see positive selection occurring at deep branches as well as 13 incidents at the species level. We found the strongest level of positive selection in Tasmanian devil (Sarcophilus harrisii), donkey (Equus asinus), large flying fox (Pteropus vampyrus), Weddell seal (Leptonychotes weddellii), and dog (Canis lupus familiaris). At the codon-level, we found up to 10% of ACE2 codons are impacted by positive selection in the mammalian lineages studied. This phylogenetically broad evolutionary arms race can contribute to the emergence of new strains of coronaviruses in different mammalian lineages with a potential to transfer between species given the common binding receptor ACE2. Our study provides a molecular evolutionary perspective to the current pandemic and sheds light on its evolutionary mechanisms.\n\n\"Nothing in biology makes sense except in the light of evolution\" (Theodosius Dobzhansky)", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Emiliano Trucchi", - "author_inst": "Department of Life and Environmental Science, Marche Polytechnic University, Via Brecce Bianche, 60131, Ancona, Italy" - }, - { - "author_name": "Paolo Gratton", - "author_inst": "Department of Biology, University of Rome Tor Vergata, Via Cracovia, 1, 00133, Roma, Italy" - }, - { - "author_name": "Fabrizio Mafessoni", - "author_inst": "Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Deutscher Platz, 6, 04103, Leipzig, Germany" - }, - { - "author_name": "Stefano Motta", - "author_inst": "Department of Earth and Environmental Sciences, University of Milano-Bicocca, Piazza della Scienza 2, 20126, Milan, Italy" - }, - { - "author_name": "Francesco Cicconardi", - "author_inst": "School of Biological Sciences, University of Bristol, Bristol BS8 1TQ, UK" - }, - { - "author_name": "Giorgio Bertorelle", - "author_inst": "Department of Life Sciences and Biotechnology, University of Ferrara, Via Luigi Borsari 46, 44121, Ferrara, Italy" + "author_name": "Mehrdad Hajibabaei", + "author_inst": "University of Guelph" }, { - "author_name": "Daniele Di Marino", - "author_inst": "Department of Life and Environmental Sciences, New York-Marche Structural Biology Center (NY-MaSBiC), Polytechnic University of Marche, Via Brecce Bianche, 6013" + "author_name": "Gregory AC Singer", + "author_inst": "Centre for Environmental Genomics Applications, eDNAtec Inc." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", "category": "evolutionary biology" }, @@ -1477113,47 +1477359,35 @@ "category": "cardiovascular medicine" }, { - "rel_doi": "10.1101/2020.05.15.097741", - "rel_title": "Analysis of SARS-CoV-2 RNA-Sequences by Interpretable Machine Learning Models", + "rel_doi": "10.1101/2020.05.09.20096834", + "rel_title": "Triage tool for suspected COVID-19 patients in the emergency room: AIFELL score", "rel_date": "2020-05-15", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.15.097741", - "rel_abs": "We present an approach to investigate SARS-CoV-2 virus sequences based on alignment-free methods for RNA sequence comparison. In particular, we verify a given clustering result for the GISAID data set, which was obtained analyzing the molecular differences in coronavirus populations by phylogenetic trees. For this purpose, we use alignment-free dissimilarity measures for sequences and combine them with learning vector quantization classifiers for virus type discriminant analysis and classification. Those vector quantizers belong to the class of interpretable machine learning methods, which, on the one hand side provide additional knowledge about the classification decisions like discriminant feature correlations, and on the other hand can be equipped with a reject option. This option gives the model the property of self controlled evidence if applied to new data, i.e. the models refuses to make a classification decision, if the model evidence for the presented data is not given. After training such a classifier for the GISAID data set, we apply the obtained classifier model to another but unlabeled SARS-CoV-2 virus data set. On the one hand side, this allows us to assign new sequences to already known virus types and, on the other hand, the rejected sequences allow speculations about new virus types with respect to nucleotide base mutations in the viral sequences.\n\nAuthor summaryThe currently emerging global disease COVID-19 caused by novel SARS-CoV-2 viruses requires all scientific effort to investigate the development of the viral epidemy, the properties of the virus and its types. Investigations of the virus sequence are of special interest. Frequently, those are based on mathematical/statistical analysis. However, machine learning methods represent a promising alternative, if one focuses on interpretable models, i.e. those that do not act as black-boxes. Doing so, we apply variants of Learning Vector Quantizers to analyze the SARS-CoV-2 sequences. We encoded the sequences and compared them in their numerical representations to avoid the computationally costly comparison based on sequence alignments. Our resulting model is interpretable, robust, efficient, and has a self-controlling mechanism regarding the applicability to data. This framework was applied to two data sets concerning SARS-CoV-2. We were able to verify previously published virus type findings for one of the data sets by training our model to accurately identify the virus type of sequences. For sequences without virus type information (second data set), our trained model can predict them. Thereby, we observe a new scattered spreading of the sequences in the data space which probably is caused by mutations in the viral sequences.", - "rel_num_authors": 7, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.09.20096834", + "rel_abs": "Clinical prediction scores support the assessment of patients in the emergency setting to determine the need for further diagnostic and therapeutic steps. During the current COVID-19 pandemic, physicians in emergency rooms (ER) of many hospitals have a considerably higher patient load and need to decide within a short time frame whom to hospitalize. Based on our clinical experiences in dealing with COVID-19 patients at the University Hospital Zurich, we created a triage score with the acronym AIFELL consisting of clinical, radiological and laboratory findings.\n\nThe score was then evaluated in a retrospective analysis of 122 consecutive patients with suspected COVID-19 from March until mid-April 2020. Descriptive statistics, Students t-test, ANOVA and Scheffes post hoc analysis confirmed the diagnostic power of the score. The results suggest that the AIFELL score has potential as a triage tool in the ER setting intended to select probable COVID-19 cases for hospitalization in spontaneously presenting or referred patients with acute respiratory symptoms.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Thomas Villmann", - "author_inst": "University of Applied Sciences Mittweida" + "author_name": "Ian Levenfus", + "author_inst": "Department of Internal Medicine, University Hospital Zurich, Zurich, Switzerland" }, { - "author_name": "Marika Kaden", - "author_inst": "Hochschule Mittweida" + "author_name": "Enrico Ullmann", + "author_inst": "Department of Pediatric Psychiatry, Psychotherapy and Psychosomatics, University of Leipzig Medical Center, Leipzig, Germany" }, { - "author_name": "Katrin Sophie Bohnsack", - "author_inst": "Hochschule Mittweida" - }, - { - "author_name": "Mirko Weber", - "author_inst": "Hochschule Mittweida" + "author_name": "Edouard Battegay", + "author_inst": "Department of Internal Medicine, University Hospital Zurich, Zurich, Switzerland" }, { - "author_name": "Mateusz Kudla", - "author_inst": "Hochschule Mittweida" - }, - { - "author_name": "Kaja Gutowska", - "author_inst": "Politechnika Poznanska" - }, - { - "author_name": "Jacek Blazewicz", - "author_inst": "Politechnika Poznanska" + "author_name": "Mac\u00e9 M. Schuurmans", + "author_inst": "Division of Pulmonology, University Hospital Zurich, Zurich, Switzerland" } ], "version": "1", "license": "cc_by", - "type": "new results", - "category": "bioinformatics" + "type": "PUBLISHAHEADOFPRINT", + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.05.14.097170", @@ -1478935,163 +1479169,71 @@ "category": "neuroscience" }, { - "rel_doi": "10.1101/2020.05.15.096511", - "rel_title": "Broad sarbecovirus neutralizing antibodies define a key site of vulnerability on the SARS-CoV-2 spike protein", + "rel_doi": "10.1101/2020.05.15.098731", + "rel_title": "Favipiravir strikes the SARS-CoV-2 at its Achilles heel, the RNA polymerase", "rel_date": "2020-05-15", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.15.096511", - "rel_abs": "Broadly protective vaccines against known and pre-emergent coronaviruses are urgently needed. Critical to their development is a deeper understanding of cross-neutralizing antibody responses induced by natural human coronavirus (HCoV) infections. Here, we mined the memory B cell repertoire of a convalescent SARS donor and identified 200 SARS-CoV-2 binding antibodies that target multiple conserved sites on the spike (S) protein. A large proportion of the antibodies display high levels of somatic hypermutation and cross-react with circulating HCoVs, suggesting recall of pre-existing memory B cells (MBCs) elicited by prior HCoV infections. Several antibodies potently cross-neutralize SARS-CoV, SARS-CoV-2, and the bat SARS-like virus WIV1 by blocking receptor attachment and inducing S1 shedding. These antibodies represent promising candidates for therapeutic intervention and reveal a new target for the rational design of pan-sarbecovirus vaccines.", - "rel_num_authors": 36, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.15.098731", + "rel_abs": "The ongoing Corona Virus Disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has emphasized the urgent need for antiviral therapeutics. The viral RNA-dependent-RNA-polymerase (RdRp) is a promising target with polymerase inhibitors successfully used for the treatment of several viral diseases. Here we show that Favipiravir exerts an antiviral effect as a nucleotide analogue through a combination of chain termination, slowed RNA synthesis and lethal mutagenesis. The SARS-CoV RdRp complex is at least 10-fold more active than any other viral RdRp known. It possesses both unusually high nucleotide incorporation rates and high-error rates allowing facile insertion of Favipiravir into viral RNA, provoking C-to-U and G-to-A transitions in the already low cytosine content SARS-CoV-2 genome. The coronavirus RdRp complex represents an Achilles heel for SARS-CoV, supporting nucleoside analogues as promising candidates for the treatment of COVID-19.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Anna Z Wec", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Daniel Wrapp", - "author_inst": "Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA" - }, - { - "author_name": "Andrew S Herbert", - "author_inst": "U.S. Army Medical Research Institute of Infectious Diseases, Frederick, MD 21702, USA" - }, - { - "author_name": "Daniel P Maurer", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Denise Haslwanter", - "author_inst": "Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA" - }, - { - "author_name": "Mrunal Sakharkar", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Rohit K Jangra", - "author_inst": "Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA" - }, - { - "author_name": "M. Eugenia Dieterle", - "author_inst": "Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA" - }, - { - "author_name": "Asparouh Lilov", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Deli Huang", - "author_inst": "Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, CA 92037, USA" - }, - { - "author_name": "Longping V Tse", - "author_inst": "Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA." - }, - { - "author_name": "Nicole V Johnson", - "author_inst": "Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA" - }, - { - "author_name": "Ching-Lin Hsieh", - "author_inst": "Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA" - }, - { - "author_name": "Nianshuang Wang", - "author_inst": "Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA" - }, - { - "author_name": "Juergen H Nett", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Elizabeth Champney", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Irina Burnina", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Michael Brown", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Shu Lin", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Melanie Sinclair", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Carl Johnson", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Sarat Pudi", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" - }, - { - "author_name": "Robert Bortz III", - "author_inst": "Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA" - }, - { - "author_name": "Ariel S Wirchnianski", - "author_inst": "Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA" + "author_name": "Ashleigh Shannon", + "author_inst": "CNRS" }, { - "author_name": "Ethan Laudermilch", - "author_inst": "Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA" + "author_name": "Barbara Selisko", + "author_inst": "Aix-Marseille University" }, { - "author_name": "Catalina Florez", - "author_inst": "Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA" + "author_name": "Thi-Tuyet-Nhung Le", + "author_inst": "Aix-Marseille University" }, { - "author_name": "J. Maximilian Fels", - "author_inst": "Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA" + "author_name": "Johanna Huchting", + "author_inst": "University of Hamburg" }, { - "author_name": "Barney S Graham", - "author_inst": "Vaccine Research Center, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD 20892, USA" + "author_name": "Franck Touret", + "author_inst": "Aix-Marseille University" }, { - "author_name": "David Nemazee", - "author_inst": "Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, CA 92037, USA" + "author_name": "Genevieve Piorkowski", + "author_inst": "Aix-Marseille University" }, { - "author_name": "Dennis R Burton", - "author_inst": "Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, CA 92037, USA" + "author_name": "Veronique Fattorini", + "author_inst": "CNRS" }, { - "author_name": "Ralph S Baric", - "author_inst": "Department of Epidemiology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA. Departments of Microbiology and Immunology, The Univers" + "author_name": "Francois Ferron", + "author_inst": "Centre National de la Recherche Scientifique (CNRS)" }, { - "author_name": "James E Voss", - "author_inst": "Department of Immunology and Microbial Science, The Scripps Research Institute, La Jolla, CA 92037, USA" + "author_name": "Etienne Decroly", + "author_inst": "CNRS" }, { - "author_name": "Kartik Chandran", - "author_inst": "Department of Microbiology and Immunology, Albert Einstein College of Medicine, New York, NY, USA" + "author_name": "Chris Meier", + "author_inst": "University of Hamburg" }, { - "author_name": "John M Dye", - "author_inst": "U.S. Army Medical Research Institute of Infectious Diseases, Frederick, MD 21702, USA" + "author_name": "Bruno Coutard", + "author_inst": "Aix-Marseille University" }, { - "author_name": "Jason S McLellan", - "author_inst": "Department of Molecular Biosciences, The University of Texas at Austin, Austin, TX 78712, USA" + "author_name": "Olve Peersen", + "author_inst": "Colorado State University" }, { - "author_name": "Laura M Walker", - "author_inst": "Adimab LLC, Lebanon, NH 03766, USA" + "author_name": "Bruno Canard", + "author_inst": "CNRS" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", - "category": "immunology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.05.14.093054", @@ -1480625,37 +1480767,45 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.05.13.093971", - "rel_title": "Insights into molecular evolution recombination of pandemic SARS-CoV-2 using Saudi Arabian sequences", + "rel_doi": "10.1101/2020.05.13.093658", + "rel_title": "Evolutionary arms race between virus and host drives genetic diversity in bat SARS related coronavirus spike genes", "rel_date": "2020-05-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.13.093971", - "rel_abs": "The recently emerged SARS-CoV-2 (Coronaviridae; Betacoronavirus) is the underlying cause of COVID-19 disease. Here we assessed SARS-CoV2 from the Kingdom of Saudi Arabia alongside sequences of SARS-CoV, bat SARS-like CoVs and MERS-CoV, the latter currently detected in this region. Phylogenetic analysis, natural selection investigation and genome recombination analysis were performed. Our analysis showed that all Saudi SARS-CoV-2 sequences are of the same origin and closer proximity to bat SARS-like CoVs, followed by SARS-CoVs, however quite distant to MERS-CoV. Moreover, genome recombination analysis revealed two recombination events between SARS-CoV-2 and bat SARS-like CoVs. This was further assessed by S gene recombination analysis. These recombination events may be relevant to the emergence of this novel virus. Moreover, positive selection pressure was detected between SARS-CoV-2, bat SL-CoV isolates and human SARS-CoV isolates. However, the highest positive selection occurred between SARS-CoV-2 isolates and 2 bat-SL-CoV isolates (Bat-SL-RsSHC014 and Bat-SL-CoVZC45). This further indicates that SARS-CoV-2 isolates were adaptively evolved from bat SARS-like isolates, and that a virus with originating from bats triggered this pandemic. This study thuds sheds further light on the origin of this virus.\n\nAUTHOR SUMMARYThe emergence and subsequent pandemic of SARS-CoV-2 is a unique challenge to countries all over the world, including Saudi Arabia where cases of the related MERS are still being reported. Saudi SARS-CoV-2 sequences were found to be likely of the same or similar origin. In our analysis, SARS-CoV-2 were more closely related to bat SARS-like CoVs rather than to MERS-CoV (which originated in Saudi Arabia) or SARS-CoV, confirming other phylogenetic efforts on this pathogen. Recombination and positive selection analysis further suggest that bat coronaviruses may be at the origin of SARS-CoV-2 sequences. The data shown here give hints on the origin of this virus and may inform efforts on transmissibility, host adaptation and other biological aspects of this virus.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.13.093658", + "rel_abs": "The Chinese horseshoe bat (Rhinolophus sinicus), reservoir host of severe acute respiratory syndrome coronavirus (SARS-CoV), carries many bat SARS-related CoVs (SARSr-CoVs) with high genetic diversity, particularly in the spike gene. Despite these variations, some bat SARSr-CoVs can utilize the orthologs of human SARS-CoV receptor, angiotensin-converting enzyme 2 (ACE2), for entry. It is speculated that the interaction between bat ACE2 and SARSr-CoV spike proteins drives diversity. Here, we have identified a series of R. sinicus ACE2 variants with some polymorphic sites involved in the interaction with the SARS-CoV spike protein. Pseudoviruses or SARSr-CoVs carrying different spike proteins showed different infection efficiency in cells transiently expressing bat ACE2 variants. Consistent results were observed by binding affinity assays between SARS- and SARSr-CoV spike proteins and receptor molecules from bats and humans. All tested bat SARSr-CoV spike proteins had a higher binding affinity to human ACE2 than to bat ACE2, although they showed a 10-fold lower binding affinity to human ACE2 compared with their SARS-CoV counterpart. Structure modeling revealed that the difference in binding affinity between spike and ACE2 might be caused by the alteration of some key residues in the interface of these two molecules. Molecular evolution analysis indicates that these residues were under strong positive selection. These results suggest that the SARSr-CoV spike protein and R. sinicus ACE2 may have coevolved over time and experienced selection pressure from each other, triggering the evolutionary arms race dynamics. It further proves that R. sinicus is the natural host of SARSr-CoVs.\n\nImportanceEvolutionary arms race dynamics shape the diversity of viruses and their receptors. Identification of key residues which are involved in interspecies transmission is important to predict potential pathogen spillover from wildlife to humans. Previously, we have identified genetically diverse SARSr-CoV in Chinese horseshoe bats. Here, we show the highly polymorphic ACE2 in Chinese horseshoe bat populations. These ACE2 variants support SARS- and SARSr-CoV infection but with different binding affinity to different spike proteins. The higher binding affinity of SARSr-CoV spike to human ACE2 suggests that these viruses have the capacity of spillover to humans. The positive selection of residues at the interface between ACE2 and SARSr-CoV spike protein suggests a long-term and ongoing coevolutionary dynamics between them. Continued surveillance of this group of viruses in bats is necessary for the prevention of the next SARS-like disease.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Islam Nour", - "author_inst": "King Saud University" + "author_name": "Hua Guo", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" }, { - "author_name": "Ibrahim O. Alanazi", - "author_inst": "King Abdulaziz City for Science And Technology" + "author_name": "Bingjie Hu", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" }, { - "author_name": "Atif Hanif", - "author_inst": "King Saud University" + "author_name": "Xinglou Yang", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" }, { - "author_name": "Alain Kohl", - "author_inst": "University of Glasgow" + "author_name": "Leiping Zeng", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" }, { - "author_name": "Saleh A Eifan", - "author_inst": "King Saud University" + "author_name": "Bei Li", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" + }, + { + "author_name": "Songying Ouyang", + "author_inst": "Fujian Normal University" + }, + { + "author_name": "Zhengli Shi", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -1482199,33 +1482349,33 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.05.08.20095877", - "rel_title": "Forecasting Transmission Dynamics of COVID-19 Epidemic in India under Various Containment Measures- A Time-Dependent State-Space SIR Approach", + "rel_doi": "10.1101/2020.05.08.20095703", + "rel_title": "The real time effective reproductive number for COVID-19 in the United States", "rel_date": "2020-05-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095877", - "rel_abs": "ObjectivesOur primary objective is to predict the dynamics of COVID-19 epidemic in India while adjusting for the effects of various progressively implemented containment measures. Apart from forecasting the major turning points and parameters associated with the epidemic, we intend to provide an epidemiological assessment of the impact of these containment measures in India.\n\nMethodsWe propose a method based on time-series SIR model to estimate time-dependent modifiers for transmission rate of the infection. These modifiers are used in state-space SIR model to estimate reproduction number R0, expected total incidence, and to forecast the daily prevalence till the end of the epidemic. We consider four different scenarios, two based on current developments and two based on hypothetical situations for the purpose of comparison.\n\nResultsAssuming gradual relaxation in lockdown post 17 May 2020, we expect the prevalence of infecteds to cross 9 million, with at least 1 million severe cases, around the end of October 2020. For the same case, estimates of R0 for the phases no-intervention, partial-lockdown and lockdown are 4.46 (7.1), 1.47 (2.33), and 0.817 (1.29) respectively, assuming 14-day (24-day) infectious period.\n\nConclusionsEstimated modifiers give consistent estimates of unadjusted R0 across different scenarios, demonstrating precision. Results corroborate the effectiveness of lockdown measures in substantially reducing R0. Also, predictions are highly sensitive towards estimate of infectious period.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095703", + "rel_abs": "none.", "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Vishal Deo", - "author_inst": "Ramjas College, University of Delhi" + "author_name": "Yue Zhang", + "author_inst": "University of Utah" }, { - "author_name": "Anuradha Rajkonwar Chetiya", - "author_inst": "Ramjas College, University of delhi" + "author_name": "Lindsay T Keegan", + "author_inst": "University of Utah" }, { - "author_name": "Barnali Deka", - "author_inst": "Ramjas College, University of Delhi" + "author_name": "Qiu Yuqing", + "author_inst": "University of Utah" }, { - "author_name": "Gurprit Grover", - "author_inst": "Department of Statistics, University of Delhi" + "author_name": "Matthew H Samore", + "author_inst": "University of Utah" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1483469,21 +1483619,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.09.20096123", - "rel_title": "Breaking the back of COVID-19: Is Bangladesh doing enough testing?", + "rel_doi": "10.1101/2020.05.08.20095968", + "rel_title": "Effects of pre-existing morbidities on occurrence of death among COVID-19 disease patients: A systematic review and meta-analysis", "rel_date": "2020-05-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.09.20096123", - "rel_abs": "Following detection of the first 100 confirmed cases of COVID-19 in early April, Bangladesh stepped up its efforts to strengthen testing capacity in order to curb the spread of the disease across the country. This paper sheds light on the position of Bangladesh in relation to its South Asian neighbors India and Pakistan with respect to testing capacity and ability to detect cases with increased testing. It also analyzes recent data on case counts and testing numbers in Bangladesh, to provide an idea regarding the number of extra tests needed to detect a substantial number of cases within a short period of time. Findings indicate that compared to India and Pakistan, Bangladesh was able to detect more cases by increasing testing levels and expand its testing capacity by performing more per capita tests. In spite of these achievements, the rate of reported cases per 100 tests was consistently higher for Bangladesh compared to India, which suggests that in addition to increased testing, other factors, such as, effective enforcement of social distancing and efficient contact tracing are just as important in curbing the spread of the disease. The analysis reveals that current testing levels in Bangladesh are not adequate. Based on the findings, we recommend a 30-50% growth of the current test rate in the next few days so that by detecting and isolating more cases, Bangladesh could, in effect, contain the spread of new infections. The challenge, however, is to mobilize resources necessary to expand geographical coverage and improve testing quality while enforcing social distancing and performing efficient contact tracing.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095968", + "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19), the most hectic pandemic of the era, is increasing exponentially and taking thousands of lives worldwide. This study aimed to assess the prevalence of pre-existing morbidities among COVID-19 infected patients and their mortality risks against each type of pre-existing morbidity category.\n\nMethodsTo conduct this systematic review and meta-analysis, Medline, Web of Science, Scopus, and CINAHL databases were searched using specified relavent keywords. Further searches were conducted using the reference list of the selected studies, renowned pre-print servers (e.g., medRxiv, bioRixv, SSRN), and relevant journal websites. Studies written in the English language included if those were conducted among COVID-19 patients with and without comorbidities and presented survivor vs. non-survivor counts or hazard/odds of deaths or survivors against types of pre-existing morbidities. Comorbidities reported in the selected studies were grouped into eight categories. The pooled likelihoods of deaths in each category were estimated using a fixed or random-effect model, based on the heterogeneity assessment. Publication bias was assessed by visual inspection of the funnel plot asymmetry and Eggers regression test. Trim and Fill method was used if there any publication bias was found.\n\nResultsA total of 42 studies included in this study comprised of 39,398 samples. The most common pre-existing morbidities in COVID-19 infected patients were hypertension (36.5%), cardiovascular disease (11.9%), and diabetes (22.0%). The higher likelihood of deaths was found among COVID-19 patients who had pre-existing cardiovascular diseases (OR: 3.32, 95% CI: 2.79-3.95), immune and metabolic disorders (OR: 2.39, 95% CI: 2.00-2.85), respiratory diseases (OR: 2.02, 95% CI: 1.80-2.26), cerebrovascular diseases (OR: 4.12, 95% CI: 3.04-5.58), any types of cancers (OR: 2.22, 95% CI: 1.63-3.03), renal (OR: 3.02, 95% CI: 2.60-3.52), and liver diseases (OR: 1.44, 95% CI: 1.21-1.71).\n\nConclusionsThis study provides evidence of a higher likelihood of deaths among COVID-19 patients against morbidity categories. These findings could potentially help healthcare providers to sort out the most endangered COVID-19 patients by comorbidities, take precautionary measures during hospitalization, assess susceptibility to death, and prioritize their treatment, which could potentially reduce the number of fatalities in COVID-19.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Hasinur Rahaman Khan", - "author_inst": "Applied Statistics, ISRT, University of Dhaka, Bangladesh" + "author_name": "Mostaured Khan", + "author_inst": "University of Rajshahi" }, { - "author_name": "Tamanna Howlader", - "author_inst": "Applied Statistics, ISRT, University of Dhaka, Bangladesh" + "author_name": "Md Nuruzzaman Khan", + "author_inst": "Jatiya Kabi Kazi Nazrul Islam University" + }, + { + "author_name": "Md. Golam Mustagir", + "author_inst": "University of Rajshahi" + }, + { + "author_name": "Juwel Rana", + "author_inst": "University of Massachusetts Amherst" + }, + { + "author_name": "Md Saiful Islam", + "author_inst": "Directorate General of Health Services" + }, + { + "author_name": "Md Iqbal Kabir", + "author_inst": "Directorate General of Health Services" } ], "version": "1", @@ -1485031,37 +1485197,33 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.05.08.20095521", - "rel_title": "Expected impact of reopening schools after lockdown on COVID-19 epidemic in Ile-de-France", + "rel_doi": "10.1101/2020.05.08.20095448", + "rel_title": "Genetic drift and environmental spreading dynamics of COVID-19", "rel_date": "2020-05-12", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095521", - "rel_abs": "As countries in Europe implement strategies to control COVID-19 pandemic, different options are chosen regarding schools. Through a stochastic age-structured transmission model calibrated to the observed epidemic in Ile-de-France in the first wave, we explored scenarios of partial, progressive, or full school reopening. Given the uncertainty on childrens role, we found that reopening schools after lockdown may increase COVID-19 cases, yet protocols exist that maintain the epidemic controlled. Under a scenario with stable epidemic activity if schools were closed, reopening pre-schools and primary schools would lead up to 76% [67, 84]% occupation of ICU beds if no other school level reopened, or if middle and high schools reopened later. Immediately reopening all school levels may overwhelm the ICU system. Priority should be given to pre- and primary schools allowing younger children to resume learning and development, whereas full attendance in middle and high schools is not recommended for stable or increasing epidemic activity. Large-scale test and trace are required to maintain the epidemic under control. Ex-post assessment shows that progressive reopening of schools, limited attendance, and strong adoption of preventive measures contributed to a decreasing epidemic after lifting the first lockdown.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.08.20095448", + "rel_abs": "BackgroundCurrent propagation models of COVID-19 are poorly consistent with existing epidemiological data and with evidence that the SARS-CoV-2 genome is mutating, for potential aggressive evolution of the disease.\n\nMethodsWe challenged regional versus genetic evolution models of COVID-19 at a whole-population level, over 168,089 laboratory-confirmed SARS-CoV-2 infection cases in Italy, Spain and Scandinavia. Diffusion data in Germany, France and UK provided a validation dataset of 210,239 additional cases.\n\nResultsThe mean doubling time of COVID-19 cases was 6.63 days in Northern versus 5.38 days in Southern Italy. Spain extended this trend of faster diffusion in Southern Europe, with a doubling time of 4.2 days. Slower doubling times were observed in Sweden (9.4 days), Finland (10.8 days), Norway (12.95 days). COVID-19 doubling time in Germany (7.0 days), France (7.5 days) and UK (7.2 days) supported the North/South gradient model. Clusters of SARS-CoV-2 mutations upon sequential diffusion across distinct geographic areas were not found to clearly correlate with regional distribution dynamics.\n\nConclusionsAcquisition of mutations, upon SARS-CoV-2 spreading across distinct geographic areas, did not distinctly associate to enhanced virus aggressiveness, and failed to explain regional diffusion heterogeneity at early phases of the pandemic. Our findings indicate that COVID-19 transmission rates associate to a sharp North/South climate gradient, with faster spreading in Southern regions. Thus, warmer climate conditions may not limit SARS-CoV-2 infectivity. Very cold regions may be better spared by recurrent courses of SARS-CoV-2 infection.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Laura Di Domenico", - "author_inst": "INSERM, Sorbonne Universite" - }, - { - "author_name": "Giulia Pullano", - "author_inst": "INSERM, Sorbonne Universite" + "author_name": "Saverio Alberti", + "author_inst": "University of Messina" }, { - "author_name": "Chiara E. Sabbatini", - "author_inst": "INSERM, Sorbonne Universite" + "author_name": "Roberta Di Pietro", + "author_inst": "University of Chieti-Pescara" }, { - "author_name": "Pierre-Yves Bo\u00eblle", - "author_inst": "INSERM" + "author_name": "Mariangela Basile", + "author_inst": "University of Chieti-Pescara" }, { - "author_name": "Vittoria Colizza", - "author_inst": "INSERM" + "author_name": "Laura Antolini", + "author_inst": "University of Milano Bicocca" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1486637,35 +1486799,18 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.05.12.091090", - "rel_title": "Static All-Atom Energetic Mappings of the SARS-Cov-2 Spike Protein with Potential Latch Identification of the Down State Protomer", + "rel_doi": "10.1101/2020.05.11.089763", + "rel_title": "Children's Hospital Los Angeles COVID-19 Analysis Research Database (CARD) - A Resource for Rapid SARS-CoV-2 Genome Identification Using Interactive Online Phylogenetic Tools", "rel_date": "2020-05-12", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.12.091090", - "rel_abs": "The SARS-Cov-2 virion responsible for the current world-wide pandemic Covid-19 has a characteristic Spike protein (S) on its surface that embellishes both a prefusion state and fusion state. The prefusion Spike protein (S) is a large trimeric protein where each protomer may be in a so-called Up state or Down state, depending on the configuration of its receptor binding domain (RBD). The Up state is believed to allow binding of the virion to ACE-2 receptors on human epithelial cells, whereas the Down state is believed to be relatively inactive or reduced in its binding behavior. We have performed detailed all-atom, dominant energy landscape mappings for noncovalent interactions (charge, partial charge, and van der Waals) of the SARS-Cov-2 Spike protein in its static prefusion state based on recent structural information. We included both interchain interactions and intrachain (domain) interactions in our mappings in order to determine any telling differences (different so-called \"glue\" points) between residues in the Up and Down state protomers. In general, the S2 or fusion machinery domain of S is relatively rigid with strong noncovalent interactions facilitated by helical secondary structures, whereas the S1 domain, which contains the RBD and N-terminal domain (NTD), is relatively more flexible and characterized by beta strand structural motifs. The S2 domain demonstrated no appreciable energetic differences between Up and Down protomers, including interchain as well as each protomers intrachain, S1-S2 interactions. However, the S1 domain interactions across neighboring protomers, which include the RBD-NTD cross chain interactions, showed significant energetic differences between Up-Down and Down-Down neighboring protomers. Surprisingly, the Up-Down, RBD-NTD interactions were overall stronger and more numerous than the Down-Down cross chain interactions, including the appearance of the three residue sequence ALA520-PRO521-ALA522 associated with a turn structure in the RBD of the Up state protomer. Additionally, our intrachain dominant energy mappings within each protomer, identified a significant \"glue\" point or possible \"latch\" for the Down state protomer between the S1 subdomain, SD1, and the RBD domain of the same protomer that was completely missing in the Up state protomer analysis. Ironically, this dominant energetic interaction in the Down state protomer involved the backbone atoms of the same three residue sequence ALA520-PRO521-ALA522 of the RBD with the R-group of GLN564 in the SD1 domain. Thus, this same three residue sequence acts as a stabilizer of the RBD in the Up conformation through its interactions with its neighboring NTD chain and a kind of latch in the Down state conformation through its interactions with its own SD1 domain. The dominant interaction energy residues identified here are also conserved across reported variations of SARS-Cov-2, as well as the closely related virions SARS-Cov and the bat corona virus RatG13. To help verify the potential latch for the Down state protomer, we conducted some preliminary molecular dynamic simulations that effectively turn off this specific latch glue point via a single point mutation of GLN564. Interestingly, the single point mutation lead to the latch releasing in less than a few nanoseconds, but the latch remained fixed in the wild state protomer for up to 0.1 microseconds that were simulated. Many more detailed studies are needed to understand the dynamics of the Up and Down states of the Spike protein, including the stabilizing chain-chain interactions and the mechanisms of transition from Down to Up state protomers. Nonetheless, static dominant energy landscape mappings and preliminary molecular dynamic studies given here may represent a useful starting point for more detailed dynamic analyses and hopefully an improved understanding of the structure-function relationship of this highly complex protein associated with COVID-19.", - "rel_num_authors": 4, - "rel_authors": [ - { - "author_name": "Michael H Peters", - "author_inst": "Virginia Commonwealth University" - }, - { - "author_name": "Oscar Bastidas", - "author_inst": "University of Minnesota" - }, - { - "author_name": "Daniel S. Kokron", - "author_inst": "NASA Ames Research Center" - }, - { - "author_name": "Christopher E. Henze", - "author_inst": "NASA Ames Research Center" - } - ], + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.11.089763", + "rel_abs": "Effective response to the Coronavirus Disease 2019 (COVID-19) pandemic requires genomic resources and bioinformatics tools for genomic epidemiology and surveillance studies that involve characterizing full-length viral genomes, identifying origins of infections, determining the relatedness of viral infections, performing phylogenetic analyses, and monitoring the continuous evolution of the SARS-CoV-2 viral genomes. The Childrens Hospital, Los Angeles (CHLA) COVID-19 Analysis Research Database (CARD) (https://covid19.cpmbiodev.net/) is a comprehensive genomic resource that provides access to full-length SARS-CoV-2 viral genomes and associated meta-data for over 30,000 (as of May 20, 2020) isolates collected from global sequencing repositories and the sequencing performed at the Center for Personalized Medicine (CPM) at CHLA. Reference phylogenetic trees of global and USA viral isolates were constructed and are periodically updated using selected high quality SARS-CoV-2 genome sequences. These provide the baseline and analytical context for identifying the origin of a viral infection, as well as the relatedness of SARS-CoV-2 genomes of interest. A web-based and interactive Phylogenetic Tree Browser supports flexible tree manipulation and advanced analysis based on keyword search while highlighting time series animation, as well as subtree export for graphical representation or offline exploration. A Virus Genome Tracker accepts complete or partial SARS-CoV-2 genome sequence, compares it against all available sequences in the database (>30,000 at time of writing), detects and annotates the variants, and places the new viral isolate within the global or USA phylogenetic contexts based upon variant profiles and haplotype comparisons, in a few seconds. The generated analysis can potentially aid in genomic surveillance to trace the transmission of any new infection. Using CHLA CARD, we demonstrate the identification of a candidate outbreak point where 13 of 31 CHLA internal isolates may have originated. We also discovered multiple indels of unknown clinical significance in the orf3a gene, and revealed a number of USA-specific variants and haplotypes.", + "rel_num_authors": 0, + "rel_authors": null, "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "biophysics" + "category": "genomics" }, { "rel_doi": "10.1101/2020.05.12.091082", @@ -1488119,39 +1488264,59 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.06.20073742", - "rel_title": "Evaluating transmission heterogeneity and super-spreading event of COVID-19 in a metropolis of China", + "rel_doi": "10.1101/2020.05.07.20083386", + "rel_title": "A Rapid Decrease in Stroke, Acute Coronary Syndrome, and Corresponding Interventions at 65 United States Hospitals Following Emergence of COVID-19", "rel_date": "2020-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.06.20073742", - "rel_abs": "BackgroundCOVID-19 caused rapid mass infection worldwide. Understanding its transmission characteristics including heterogeneity is of vital importance for prediction and intervention of future epidemics. In addition, transmission heterogeneity usually envokes super spreading events (SSEs) where certain individuals infect large numbers of secondary cases. Till now, studies of transmission heterogeneity of COVID-19 and its underlying reason are far from reaching an agreement.\n\nMethodsWe collected information of all infected cases between January 21 and February 26, 2020 from official public sources in Tianjin, a metropolis of China. . Utilizing a heterogeneous transmission model based on branching process along with a negative binomial offspring distribution, we estimated the reproductive number R and the dispersion parameter k which characterized the transmission potential and heterogeneity, respectively. Furthermore, we studied the SSE in Tianjin outbreak and evaluated the effect of control measures undertaken by local government based on the heterogeneous model.\n\nResultsA total of 135 confirmed cases (including 34 imported cases and 101 local infections) in Tianjin by February 26th 2020 entered the study. We grouped them into 43 transmission chains with the largest chain of 45 cases and the longest chain of 4 generations. The estimated reproduction number R was at 0.67 (95%CI: 0.54~0.84), and the dispersion parameter k was at 0.25 (95% CI: 0.13~0.88). A super spreader causing six infections in Tianjin, was identified. In addition, our simulation results showed that the outbreak in Tianjin would have caused 165 infections and sustained for 7.56 generations on average if no control measures had been taken by local government since January 28th.\n\nConclusionsOur analysis suggested that the transmission of COVID-19 was subcritical but with significant heterogeneity and may incur SSE. More efforts are needed to verify the transmission heterogeneity of COVID-19 in other populations and its contributing factors, which is important for developing targeted measures to curb the pandemic.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20083386", + "rel_abs": "BackgroundFollowing the emergence of coronavirus disease 2019 (COVID-19), early reports suggested a decrease in stroke and acute coronary syndrome (ACS). We sought to provide descriptive statistics for stroke and ACS from a sample of hospitals throughout the United States, comparing data from March 2020 to similar months pre-COVID.\n\nMethodsWe performed a retrospective analysis of 65 academic and community hospitals in the Vizient Clinical Data Base. The primary outcome is monthly count of stroke and ACS, and acute procedures for both, from February and March in 2020 compared to the same months in 2018 and 2019. Results are aggregated for all hospitals and reported by Census Region.\n\nResultsWe identified 51,246 strokes (42,780 ischemic, 8,466 hemorrhagic), 1,043 mechanical thrombectomies (MT), 836 tissue plasminogen activator (tPA) administrations, 36,551 ACS, and 3,925 percutaneous coronary interventions (PCI) for ACS. In February 2020, relative to February 2018 and 2019, hospitalizations with any discharge diagnosis of stroke and ACS increased by 9.8% and 12.1%, respectively, while in March 2020 they decreased 18.5% and 7.5%, relative to March 2018 and 2019. When only including hospitalizations with the primary discharge diagnosis of stroke or ACS, in March 2020 they decreased 17.6% and 25.7%, respectively. In March 2020, tPA decreased 3.3%, MT increased 18.8%, although in February 2020 it had increased 36.8%, and PCI decreased 14.7%. These decreases were observed in all Census regions.\n\nConclusionsFollowing greater recognition of the risks of COVID-19, hospitalizations with stroke and ACS were markedly diminished in a geographically diverse sample of United States hospitals. Because the most likely explanation is that some patients with stroke and ACS did not seek medical care, the underlying reasons for this decrease warrant additional study to inform public health efforts and clinical care during this and future pandemics.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Yunjun Zhang", - "author_inst": "Peking University" + "author_name": "Adam de Havenon", + "author_inst": "University of Utah" }, { - "author_name": "Yuying Li", - "author_inst": "Peking University" + "author_name": "John Ney", + "author_inst": "Boston University" }, { - "author_name": "Lu Wang", - "author_inst": "Peking University" + "author_name": "Brian Callaghan", + "author_inst": "University of Michigan" }, { - "author_name": "Mingyuan Li", - "author_inst": "Peking University" + "author_name": "Alen Delic", + "author_inst": "University fo Utah" }, { - "author_name": "Xiao-Hua Zhou", - "author_inst": "Peking University" + "author_name": "Sam Hohmann", + "author_inst": "Vizient" + }, + { + "author_name": "Ernie Shippey", + "author_inst": "Vizient" + }, + { + "author_name": "Shadi Yaghi", + "author_inst": "New York University" + }, + { + "author_name": "Mohammad Anadani", + "author_inst": "Washington University" + }, + { + "author_name": "Gregory Esper", + "author_inst": "Emory University" + }, + { + "author_name": "Jennifer Majersik", + "author_inst": "University of Utah" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2020.05.07.20091652", @@ -1489665,25 +1489830,29 @@ "category": "health systems and quality improvement" }, { - "rel_doi": "10.1101/2020.05.07.20094094", - "rel_title": "Epidemiology of CoVID-19 and predictors of recovery in the Republic of Korea", + "rel_doi": "10.1101/2020.05.07.20093864", + "rel_title": "Utility of Cloth Masks in Preventing Respiratory Infections: A Systematic Review", "rel_date": "2020-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20094094", - "rel_abs": "BackgroundThe recent CoVID-19 pandemic has emerged as a threat to global health. Though current evidence on the epidemiology of the disease is emerging, very little is known about the predictors of recovery.\n\nObjectivesTo describe the epidemiology of confirmed CoVID-19 patients in Republic of Korea and identify predictors of recovery.\n\nMaterials and methodsUsing publicly available data for confirmed CoVID-19 cases from the Korea Centers for Disease Control and Prevention from January 20, 2020 to April 30, 2020, we undertook descriptive analyses of cases stratified by sex, age group, place of exposure, date of confirmation and province. Correlation was tested among all predictors (sex, age group, place of exposure and province) with the Pearsons correlation coefficient. Associations between recovery from CoVID-19 and predictors were estimated using a multivariable logistic regression model.\n\nResultsMajority of the confirmed cases were females (56%), from 20-29 age group (24.3%), and primarily from three provinces -- Gyeongsangbuk-do (36.9%), Gyeonggi-do (20.5%) and Seoul (17.1%). Case fatality ratio was 2.1% and 41.6% cases recovered. Older patients, patients from provinces such as Daegu, Gyeonggi-do, Gyeongsangbuk-do, Jeju-do, Jeollabuk-do and Jeollanam-do, and those contracting the disease from healthcare settings had lower recovery.\n\nConclusionsOur study adds to the very limited evidence base on potential predictors of survival among confirmed CoVID-19 cases. We call additional research to explore the predictors of recovery and support development of policies to protect the vulnerable patient groups.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20093864", + "rel_abs": "BackgroundUsing face masks is one of the possible prevention methods against respiratory pathogens. A number of studies and reviews have been performed regarding the use of medical grade masks like surgical masks, N95 respirators etc. However, the use of cloth masks has received little attention.\n\nObjectivesThe purpose of this review is to analyze the available data regarding the use of cloth masks for the prevention of respiratory infections. We intended to use data from both clinical and non-clinical studies to arrive at our conclusion.\n\nMethodsWe used PubMed, Cochrane Library and Google Scholar as our source databases. Both clinical and non-clinical studies, which had data regarding the efficacy of cloth masks, were selected. Articles not containing analyzable data including opinion articles, review articles etc. were excluded. After screening the search results, ten studies could be included in our review.\n\nData relevant to our objective was extracted from each study including clinical efficacy, compliance, filtration efficacy etc. Data from some studies were simplified for the purpose of comparison. Extracted data was summarized and categorized for detailed analysis. Qualitative synthesis of the data was performed. But the heterogeneity between the studies did not allow for a meta-analysis.\n\nDiscussionThe review was limited by a lack of sufficient clinical studies. Lack of standardization between studies was another limitation.\n\nAlthough cloth masks generally perform poorer than the medical grade masks, they may be better than no masks at all. Filtration efficacy varied greatly depending on the material used, with some materials showing a filtration efficacy above 90%. However, leakage could reduce efficacy of masks by about 50%. Standardization of cloth masks and appropriate use is essential for cloth masks to be effective. However, result of a randomized controlled trial suggest that they may be ineffective in the healthcare setting.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Ashis Das", - "author_inst": "The World Bank" + "author_name": "Agnibho Mondal", + "author_inst": "School of Tropical Medicine, Kolkata" }, { - "author_name": "Saji Saraswathy Gopalan", - "author_inst": "World Bank" + "author_name": "Arnavjyoti Das", + "author_inst": "Institute of Medical Sciences, Banaras Hindu University" + }, + { + "author_name": "Rama Prosad Goswami", + "author_inst": "School of Tropical Medicine, Kolkata" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1491307,29 +1491476,41 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.07.20094714", - "rel_title": "DOUBLE POWER LAW FOR COVID-19: PREDICTION OF NEW CASES AND DEATH RATES IN ITALY AND SPAIN", + "rel_doi": "10.1101/2020.05.07.20094250", + "rel_title": "Racial and Ethnic Disparities in Population Level Covid-19 Mortality", "rel_date": "2020-05-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20094714", - "rel_abs": "1.The novel corona virus SARS-CoV-2 appeared at the end of 2019, spreading rapidly and causing a severe respiratory syndrome (COVID-19) with high mortality (2-5%). Until a vaccine or therapy is found, the most effective method of prophylaxis has been to minimize transmission via rigorous social distancing and seclusion of all but essential workers. Such measures, implemented at different times and to varying degrees world-wide, have reduced the rate of transmission compared with early phases of the pandemic, resulting in \"flattening of the curve\" followed by a gradual reduction in mortality after >6 weeks of rigorous social distancing measures. The cost of rigorous social distancing has been seen in radically reduced economic activity, job losses, disruption of schooling and social institutions. A key question facing policy makers and individuals is when to resume normal economic and social activity in the face of persistent community transmission of SARS-CoV-2. To help address this question, we have developed a model that accurately describes the entire transmission and mortality curves in Italy and Spain, two hard-hit countries that have maintained severe social distancing measures for over 2 months. Our model quantitatively describes the rapid rise and slow decay of new cases and deaths observed under stringent social distancing (the \"long tail\" effect). We predict that even when social distancing is rigorously maintained, the number of COVID-19 deaths after peak mortality may be 2 - 3 times larger than the total number of deaths up to the peak. Our model has important policy implications for countries currently debating how to ease social distancing measures.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.07.20094250", + "rel_abs": "BackgroundCurrent reporting of Covid-19 mortality data by race and ethnicity across the United States could bias our understanding of population-mortality disparities. Moreover, stark differences in age distribution by race and ethnicity groups are seldom accounted for in analyses.\n\nMethodsTo address these gaps, we conducted a cross-sectional study using publicly-reported Covid-19 mortality data to assess the quality of race and ethnicity data (Black, Latinx, white), and estimated age-adjusted disparities using a random effects meta-analytic approach.\n\nResultsWe found only 28 states, and NYC, reported race and ethnicity-stratified Covid-19 mortality along with large variation in the percent of missing race and ethnicity data by state. Aggregated relative risk of death estimates for Black compared to the white population was 3.57 (95% CI: 2.84-4.48). Similarly, Latinx population displayed 1.88 (95% CI: 1.61-2.19) times higher risk of death than white patients.\n\nDiscussionIn states providing race and ethnicity data, we identified significant population-level Covid-19 mortality disparities. We demonstrated the importance of adjusting for age differences across population groups to prevent underestimating disparities in younger population groups. The availability of high-quality and comprehensive race and ethnicity data is necessary to address factors contributing to inequity in Covid-19 mortality.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Vladimir A. Osherovich", - "author_inst": "NASA/GSFC/CUA" + "author_name": "Cary P Gross", + "author_inst": "Yale School of Medicine" + }, + { + "author_name": "Utibe R Essien", + "author_inst": "University of Pittsburgh" + }, + { + "author_name": "Saamir Pasha", + "author_inst": "Yale University" + }, + { + "author_name": "Jacob R Gross", + "author_inst": "Tufts University" }, { - "author_name": "Joseph Fainberg", - "author_inst": "NASA/GSFC" + "author_name": "Shi-yi Wang", + "author_inst": "Yale University" }, { - "author_name": "Lev Z. Osherovich", - "author_inst": "Versant Ventures" + "author_name": "Marcella Nunez-Smith", + "author_inst": "Yale University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1492605,53 +1492786,45 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.05.09.086249", - "rel_title": "Cholesterol and COVID19 lethality in elderly.", + "rel_doi": "10.1101/2020.05.09.086223", + "rel_title": "Multiple introductions, regional spread and local differentiation during the first week of COVID-19 epidemic in Montevideo, Uruguay", "rel_date": "2020-05-10", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.09.086249", - "rel_abs": "Coronavirus disease 2019 (COVID19) is a respiratory infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originating in Wuhan, China in 2019. The disease is notably severe in elderly and those with underlying chronic conditions. A molecular mechanism that explains why the elderly are vulnerable and why children are resistant is largely unknown. Here we show loading cells with cholesterol from blood serum using the cholesterol transport protein apolipoprotein E (apoE) enhances the entry of pseudotyped SARS-CoV-2 and the infectivity of the virion. Super resolution imaging of the SARS-CoV-2 entry point with high cholesterol shows almost twice the total number of endocytic entry points. Cholesterol concomitantly traffics angiotensinogen converting enzyme (ACE2) to the endocytic entry site where SARS-CoV-2 presumably docks to efficiently exploit entry into the cell. Furthermore, in cells producing virus, cholesterol optimally positions furin for priming SARS-CoV-2, producing a more infectious virion with improved binding to the ACE2 receptor. In vivo, age and high fat diet induces cholesterol loading by up to 40% and trafficking of ACE2 to endocytic entry sites in lung tissue from mice. We propose a component of COVID19 severity based on tissue cholesterol level and the sensitivity of ACE2 and furin to cholesterol. Molecules that reduce cholesterol or disrupt ACE2 localization with viral entry points or furin localization in the producer cells, may reduce the severity of COVID19 in obese patients.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.09.086223", + "rel_abs": "BackgroundAfter its emergence in China in December 2019, the new coronavirus disease (COVID-19) caused by SARS-CoV-2, has rapidly spread infecting more than 3 million people worldwide. South America is among the last regions hit by COVID-19 pandemic. In Uruguay, first cases were detected on March 13 th 2020 presumably imported by travelers returning from Europe.\n\nMethodsWe performed whole-genome sequencing of 10 SARS-CoV-2 from patients diagnosed during the first week (March 16th to 19th) of COVID-19 outbreak in Uruguay. Then, we applied genomic epidemiology using a global dataset to reconstruct the local spatio-temporal dynamics of SARS-CoV-2.\n\nResultsOur phylogeographic analysis showed three independent introductions of SARS-CoV-2 from different continents. Also, we evidenced regional circulation of viral strains originally detected in Spain. Introduction of SARS-CoV-2 in Uruguay could date back as early as Feb 20th. Identification of specific mutations showed rapid local genetic differentiation.\n\nConclusionsWe evidenced early independent introductions of SARS-CoV-2 that likely occurred before first cases were detected. Our analysis set the bases for future genomic epidemiology studies to understand the dynamics of SARS-CoV-2 in Uruguay and the Latin America and the Caribbean region.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Hao Wang", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Zixuan Yuan", - "author_inst": "The Scripps Research Institute" - }, - { - "author_name": "Mahmud Arif Pavel", - "author_inst": "The Scripps Research Institute" + "author_name": "Cecilia Salazar", + "author_inst": "Institut Pasteur Montevideo" }, { - "author_name": "Sonia Mediouni Jablonski", - "author_inst": "Scripps Research" + "author_name": "Florencia Diaz-Viraque", + "author_inst": "Institut Pasteur Montevideo" }, { - "author_name": "Joseph Jablonski", - "author_inst": "Scripps Research" + "author_name": "Marianoel Pereira-Gomez", + "author_inst": "Institut Pasteur Montevideo" }, { - "author_name": "Robert Hobson", - "author_inst": "Bruker" + "author_name": "Ignacio Ferres", + "author_inst": "Institut Pasteur Montevideo" }, { - "author_name": "Susana Valente", - "author_inst": "Scripps Research" + "author_name": "Pilar Moreno", + "author_inst": "Institut Pasteur Montevideo" }, { - "author_name": "Chakravarthy B. Reddy", - "author_inst": "University of Utah Health Sciences Center" + "author_name": "Gonzalo Moratorio", + "author_inst": "Institut Pasteur Montevideo" }, { - "author_name": "Scott Hansen", - "author_inst": "The Scripps Research Institute" + "author_name": "Gregorio Iraola", + "author_inst": "Institut Pasteur Montevideo" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "new results", "category": "microbiology" }, @@ -1494427,57 +1494600,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.05.20091918", - "rel_title": "Identification and Analysis of Shared Risk Factors in Sepsis and High Mortality Risk COVID-19 Patients", + "rel_doi": "10.1101/2020.05.05.20091975", + "rel_title": "BCG vaccine-induced protection from COVID-19 infection, wishful thinking or a game changer?", "rel_date": "2020-05-09", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20091918", - "rel_abs": "BACKGROUNDCoronavirus disease 2019 (COVID-19) is a novel coronavirus strain disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease is highly transmissible and severe disease including viral sepsis has been reported in up to 16% of hospitalized cases. The admission characteristics associated with increased odds of hospital mortality among confirmed cases of COVID-19 include severe hypoxia, low platelet count, elevated bilirubin, hypoalbuminemia and reduced glomerular filtration rate. These symptoms correlate highly with severe sepsis cases. The diseases also share similar comorbidity risks including dementia, type 2 diabetes mellitus, coronary heart disease, hypertension and chronic renal failure. Sepsis has been observed in up to 59% of hospitalized COVID-19 patients.\n\nIt is highly desirable to identify risk factors and novel therapy/drug repurposing avenues for late-stage severe COVID-19 patients. This would enable better protection of at-risk populations and clinical stratification of COVID-19 patients according to their risk for developing life threatening disease.\n\nMETHODSAs there is currently insufficient data available for confirmed COVID-19 patients correlating their genomic profile, disease severity and outcome, co-morbidities and treatments as well as epidemiological risk factors (such as ethnicity, blood group, smoking, BMI etc.), a direct study of the impact of host genomics on disease severity and outcomes is not yet possible. We therefore ran a study on the UK Biobank sepsis cohort as a surrogate to identify sepsis associated signatures and genes, and correlated these with COVID-19 patients.\n\nSepsis is itself a life-threatening inflammatory health condition with a mortality rate of approximately 20%. Like the initial studies for COVID-19 patients, standard genome wide association studies (GWAS) have previously failed to identify more than a handful of genetic variants that predispose individuals to developing sepsis.\n\nRESULTSWe used a combinatorial association approach to analyze a sepsis population derived from UK Biobank. We identified 70 sepsis risk-associated genes, which provide insights into the disease mechanisms underlying sepsis pathogenesis. Many of these targets can be grouped by common mechanisms of action such as endothelial cell dysfunction, PI3K/mTOR pathway signaling, immune response regulation, aberrant GABA and neurogenic signaling.\n\nCONCLUSIONThis study has identified 70 sepsis related genes, many of them for the first time, that can reasonably be considered to be potentially relevant to severe COVID-19 patients. We have further identified 59 drug repurposing candidates for 13 of these targets that can be used for the development of novel therapeutic strategies to increase the survival rate of patients who develop sepsis and potentially severe COVID-19.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20091975", + "rel_abs": "A series of epidemiological explorations has suggested a negative association between national BCG vaccination policy and the prevalence and mortality of COVID-19. However, these comparisons are difficult to validate due to broad differences between countries such as socioeconomic status, demographic structure, rural vs. urban settings, time of arrival of the pandemic, number of diagnostic tests and criteria for testing, and national control strategies to limit the spread of COVID-19. We review evidence for a potential biological basis of BCG cross-protection from severe COVID-19, and refine the epidemiological analysis to mitigate effects of potentially confounding factors (e.g., stage of the COVID-19 epidemic, development, rurality, population density, and age structure). A strong correlation between the BCG index, an estimation of the degree of universal BCG vaccination deployment in a country, and COVID-19 mortality in different socially similar European countries was observed (r2 = 0.88; p = 8x10-7), indicating that every 10% increase in the BCG index was associated with a 10.4% reduction in COVID-19 mortality. Results fail to confirm the null hypothesis of no-association between BCG vaccination and COVID-19 mortality, and suggest that BCG could have a protective effect. Nevertheless, the analyses are restricted to coarse-scale signals and should be considered with caution. BCG vaccination clinical trials are required to corroborate the patterns detected here, and to establish causality between BCG vaccination and protection from severe COVID-19. Public health implications of a plausible BCG cross-protection from severe COVID-19 are discussed.\n\nSignificance StatementThe COVID-19 pandemic is one of the most devastating in recent history. The bacillus Calmette-Guerin (BCG) vaccine against tuberculosis also confers broad protection against other infectious diseases, and it has been proposed that it could reduce the severity of COVID-19. This epidemiological study assessed the global linkage between BCG vaccination and COVID-19 mortality. Signals of BCG vaccination effect on COVID-19 mortality are influenced by social, economic, and demographic differences between countries. After mitigating multiple confounding factors, several significant associations between BCG vaccination and reduced COVID-19 deaths were observed. This study highlights the need for mechanistic studies behind the effect of BCG vaccination on COVID-19, and for clinical evaluation of the effectiveness of BCG vaccination to protect from severe COVID-19.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Sayoni Das", - "author_inst": "PrecisionLife Ltd" - }, - { - "author_name": "Krystyna Taylor", - "author_inst": "PrecisionLife Ltd" - }, - { - "author_name": "Matthew Pearson", - "author_inst": "PrecisionLife Ltd" - }, - { - "author_name": "James Kozubek", - "author_inst": "PrecisionLife Ltd" - }, - { - "author_name": "Marcin Pawlowski", - "author_inst": "PrecisionLife Ltd" - }, - { - "author_name": "Claus Erik Jensen", - "author_inst": "PrecisionLife Ltd" - }, - { - "author_name": "Zbigniew Skowron", - "author_inst": "PrecisionLife Ltd" - }, - { - "author_name": "Gert Lykke M\u00f8ller", - "author_inst": "PrecisionLife Ltd" + "author_name": "Luis E Escobar", + "author_inst": "Virginia Tech" }, { - "author_name": "Mark Strivens", - "author_inst": "PrecisionLife Ltd" + "author_name": "Alvaro Molina-Cruz", + "author_inst": "National Institutes of Health" }, { - "author_name": "Steve Gardner", - "author_inst": "PrecisionLife Ltd" + "author_name": "Carolina Barillas-Mury", + "author_inst": "National Institutes of Health" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1495821,29 +1495966,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.02.20086314", - "rel_title": "Testing lags and emerging COVID-19 outbreaks in federal penitentiaries in Canada", + "rel_doi": "10.1101/2020.05.05.20085902", + "rel_title": "CoVID-19 prediction for India from the existing data and SIR(D) model study", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.02.20086314", - "rel_abs": "ObjectivesTo provide the first known comprehensive analysis of COVID-19 outcomes in a federal penitentiary system. We examined the following COVID-19 outcomes within federal penitentiaries in Canada and contrasted them with estimates for the overall population in the penitentiaries respective provincial jurisdictions: testing, prevalence, the proportion recovered, and fatality.\n\nMethodsData for prisons were obtained from the Correctional Service of Canada and, for the general population, from the Esri COVID-19 Canadian Outbreak Tracking Hub. Data were retrieved between March 30 and April 21, 2020, and are accurate to this date. Penitentiary-, province- and sex-specific frequency statistics for each outcome were calculated.\n\nResultsData on 50 of 51 penitentiaries (98%) were available. Of these, 72% of penitentiaries reported fewer tests per 1000 population than the Canadian general population average (16 tests/1000 population), and 24% of penitentiaries reported zero tests. Penitentiaries with high levels of testing were those that already had elevated COVID-19 prevalence. Five penitentiaries reported an outbreak (at least one case). Hardest hit penitentiaries were those in Quebec, Ontario, and British Columbia, with some prisons reporting COVID-19 prevalence of 30% to 40%. Of these, two were womens prisons. Female prisoners were over-represented among cases (31% of cases overall, despite representing 5% of the total prison population).\n\nConclusionIncreased sentinel or universal testing may be appropriate given the confined nature of prison populations. This, along with rigorous infection prevention control practices and the potential release of prisoners, will be needed to curb current outbreaks and those likely to come.\n\nGRAPHICAL SUMMARY\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=83 SRC=\"FIGDIR/small/20086314v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (21K):\norg.highwire.dtl.DTLVardef@1502c7eorg.highwire.dtl.DTLVardef@991027org.highwire.dtl.DTLVardef@f378f4org.highwire.dtl.DTLVardef@89f447_HPS_FORMAT_FIGEXP M_FIG C_FIG O_LIBetween 20% and 57% fewer tests per 1000 population have been conducted in federal prisons in Saskatchewan, New Brunswick, Nova Scotia and Alberta than in the general population of those provinces.\nC_LIO_LIThough Alberta, Manitoba, Saskatchewan, New Brunswick and Nova Scotia are reporting lower counts of COVID-19 cases, these are also the regions reporting the lowest levels of testing.\nC_LIO_LICase incidence has been highest in federal prisons in Quebec, Ontario, and British Columbia, where a total of five prisons are experiencing outbreaks (1 or more cases). These regions are those reporting the highest levels of testing - higher than the testing levels in the general population.\nC_LI", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20085902", + "rel_abs": "CoVID-19 is spreading throughout the world at an alarming rate. So far it has spread over 200 countries in the whole world. Mathematical modeling of an epidemic like CoVID-19 is always useful for strategic decision making, especially it is very useful to gain some understanding of the future of the epidemic in densely populous countries like India. We use a simple yet effective mathematical model SIR(D) to predict the future of the epidemic in India by using the existing data. We also estimate the effect of lock-down/social isolation via a time-dependent coefficient of the model. The model study with realistic parameters set shows that the epidemic will be at its peak around the end of June or the first week of July with almost 108 Indians most likely being infected if the lock-down relaxed after May 3, 2020. However, the total number of infected population will become one-third of what predicted here if we consider that people only in the red zones (approximately one-third of Indias population) are susceptible to the infection. Even in a very optimistic scenario we expect that at least the infected numbers of people will be [Formula].", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Alexandra Blair", - "author_inst": "University of Toronto Dalla Lana School of Public Health, Toronto, Canada" + "author_name": "Aditya Rajesh", + "author_inst": "IIT, Bhilai, India." }, { - "author_name": "Abtin Parnia", - "author_inst": "University of Toronto Dalla Lana School of Public Health, Toronto, Canada" + "author_name": "Haidas Pai", + "author_inst": "SINP, Kolkata, India." }, { - "author_name": "Arjumand Siddiqi", - "author_inst": "University of Toronto Dalla Lana School of Public Health, Toronto, Canada; Gillings School of Global Public Health, University of North Carolina-Chapel Hill, C" + "author_name": "Victor Roy", + "author_inst": "NISER, Bhubaneswar, India." + }, + { + "author_name": "Subhasis Samanta", + "author_inst": "Jan Kochanowski University, 25-406 Kielce, Poland" + }, + { + "author_name": "Sabyasachi Ghosh", + "author_inst": "IIT, Bhilai, India." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1497739,29 +1497892,505 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.04.20091132", - "rel_title": "Phenomenological Modelling of COVID-19 epidemics in Sri Lanka, Italy and Hebei Province of China", + "rel_doi": "10.1101/2020.05.04.20090902", + "rel_title": "More than just smell - COVID-19 is associated with severe impairment of smell, taste, and chemesthesis", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20091132", - "rel_abs": "The COVID-19 pandemic has resulted in increasing number of infections and deaths on a daily basis. There is no specific treatment or vaccine identified and the focus has been preventive measures based on statistical and mathematical models. These have relied on analyzing the behavior of populations and characteristics of the infection and applying modelling techniques. The analysis of epidemiological curve fitting on number of daily infections across affected countries could give useful insights on the characteristics of the epidemic. A variety of phenomenological models are available to capture dynamics of disease spread and growth. Data for this study used the number of daily new infections and cumulative number of infections in COVID-19 in three selected countries, Sri Lanka, Italy and Hebei province of China, from the first day of appearance of cases to 20th April 2020. In this study Gompertz, Logistic and Exponential growth curves were fitted on cumulative number of infections across countries. Akaikes information criteria (AIC) was used in determining the best fitting curve for each country. Results revealed that the most appropriate growth curves for Sri Lanka, Italy and China-Hebei are Exponential, Gompertz and Logistic curves respectively. The overall growth rate and final epidemic size evaluated from best models for the three countries and short-term forecasts were also generated. Log incidences over time in each country were regressed before and after the identified peak time of the respective outbreaks of countries. Hence, doubling time/halving time together with daily growth rates and predictions were estimated. Findings altogether demonstrate that outbreak seems extinct in Hebei-China whereas further transmissions are possible in Sri Lanka. In Italy, current outbreak transmits in a decreasing rate.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090902", + "rel_abs": "Recent anecdotal and scientific reports have provided evidence of a link between COVID-19 and chemosensory impairments such as anosmia. However, these reports have downplayed or failed to distinguish potential effects on taste, ignored chemesthesis, generally lacked quantitative measurements, were mostly restricted to data from single countries. Here, we report the development, implementation and initial results of a multi-lingual, international questionnaire to assess self-reported quantity and quality of perception in three distinct chemosensory modalities (smell, taste, and chemesthesis) before and during COVID-19. In the first 11 days after questionnaire launch, 4039 participants (2913 women, 1118 men, 8 other, ages 19-79) reported a COVID-19 diagnosis either via laboratory tests or clinical assessment. Importantly, smell, taste and chemesthetic function were each significantly reduced compared to their status before the disease. Difference scores (maximum possible change {+/-}100) revealed a mean reduction of smell (-79.7 {+/-} 28.7, mean {+/-} SD), taste (-69.0 {+/-} 32.6), and chemesthetic (-37.3 {+/-} 36.2) function during COVID-19. Qualitative changes in olfactory ability (parosmia and phantosmia) were relatively rare and correlated with smell loss. Importantly, perceived nasal obstruction did not account for smell loss. Furthermore, chemosensory impairments were similar between participants in the laboratory test and clinical assessment groups. These results show that COVID-19-associated chemosensory impairment is not limited to smell, but also affects taste and chemesthesis. The multimodal impact of COVID-19 and lack of perceived nasal obstruction suggest that SARS-CoV-2 infection may disrupt sensory-neural mechanisms.", + "rel_num_authors": 122, "rel_authors": [ { - "author_name": "A M C H Attanayake", - "author_inst": "University of Kelaniya" + "author_name": "Valentina Parma", + "author_inst": "Department of Psychology, Temple University" }, { - "author_name": "sanjeewa Perera", - "author_inst": "University of Colombo" + "author_name": "Kathrin Ohla", + "author_inst": "Institute of Neuroscience and Medicine (INM-3), Research Center J\u00fclich" }, { - "author_name": "Saroj Jayasinghe", - "author_inst": "University of Colombo Faculty of Medicine" + "author_name": "Maria G. Veldhuizen", + "author_inst": "Department of Anatomy, School of Medicine, Mersin University" + }, + { + "author_name": "Masha Y. Niv", + "author_inst": "The Institute of Biochemistry, Food Science and Nutrition, The Hebrew University of Jerusalem" + }, + { + "author_name": "Christine E. Kelly", + "author_inst": "AbScent" + }, + { + "author_name": "Alyssa J. Bakke", + "author_inst": "Food Science, The Pennsylvania State University" + }, + { + "author_name": "Keiland W. Cooper", + "author_inst": "Interdepartmental Neuroscience Program, University of California Irvine" + }, + { + "author_name": "C\u00e9dric Bouysset", + "author_inst": "Institut de Chimie de Nice, Universit\u00e9 C\u00f4te d'Azur" + }, + { + "author_name": "Nicola Pirastu", + "author_inst": "Centre for Global Health Research, Usher Institute, The University of Edinburgh" + }, + { + "author_name": "Michele Dibattista", + "author_inst": "Department of Basic Medical Sciences, Neuroscience and Sensory Organs, Universita' degli Studi di Bari A. Moro" + }, + { + "author_name": "Rishemjit Kaur", + "author_inst": "V1-B, CSIR-Central Scientific Instruments Organisation" + }, + { + "author_name": "Marco Tullio Liuzza", + "author_inst": "Department of Medical and Surgical Sciences, \"Magna Graecia\" University of Catanzaro" + }, + { + "author_name": "Marta Y. Pepino", + "author_inst": "Food Science and Human Nutrition, University of Illinois at Urbana Champaign" + }, + { + "author_name": "Veronika Sch\u00f6pf", + "author_inst": "Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna" + }, + { + "author_name": "Veronica Pereda-Loth", + "author_inst": "GSBMS - Medecine Evolutive UMR5288, Universit\u00e9 de Toulouse" + }, + { + "author_name": "Shannon B Olsson", + "author_inst": "National Centre for Biological Sciences, National Centre for Biological Sciences, Tata Institute of Fundamental Research" + }, + { + "author_name": "Richard C Gerkin", + "author_inst": "School of Life Sciences, Arizona State University" + }, + { + "author_name": "Paloma Rohlfs Dom\u00ednguez", + "author_inst": "Department of Psychology and Anthropology, University of Extremadura" + }, + { + "author_name": "Javier Albayay", + "author_inst": "Department of General Psychology, University of Padova" + }, + { + "author_name": "Michael C. Farruggia", + "author_inst": "Psychiatry, Yale University School of Medicine" + }, + { + "author_name": "Surabhi Bhutani", + "author_inst": "Exercise and Nutritional Sciences, San Diego State University" + }, + { + "author_name": "Alexander W Fjaeldstad", + "author_inst": "Department of Otolaryngology, Hospital Unit West, Aarhus University" + }, + { + "author_name": "Ritesh Kumar", + "author_inst": "Biocomputation group, University of Hertfordshire" + }, + { + "author_name": "Anna Menini", + "author_inst": "Neuroscience Area, SISSA, International School for Advanced Studies" + }, + { + "author_name": "Moustafa Bensafi", + "author_inst": "Neuropop team, Lyon Neuroscience Research Center, CNRS UMR5292 - INSERM U1028 - University Lyon 1" + }, + { + "author_name": "Mari Sandell", + "author_inst": "Department of Food and Nutrition, Functional Foods Forum, University of Helsinki, University of Turku" + }, + { + "author_name": "Iordanis Konstantinidis", + "author_inst": "2nd Academic ORL Department, Aristotle University" + }, + { + "author_name": "Antonella Di Pizio", + "author_inst": "Section In-silico Biology and Machine Learning, Leibniz-Institute for Food Systems Biology at the Technical University of Munich" + }, + { + "author_name": "Federica Genovese", + "author_inst": "Monell Chemical Senses Center" + }, + { + "author_name": "Lina \u00d6zt\u00fcrk", + "author_inst": "Mersin University" + }, + { + "author_name": "Thierry Thomas-Danguin", + "author_inst": "CSGA-Centre for Taste and Feeding Behavior, INRAE" + }, + { + "author_name": "Johannes Frasnelli", + "author_inst": "Anatomy, Universit\u00e9 du Qu\u00e9bec \u00e0 Trois-Rivi\u00e8res" + }, + { + "author_name": "Sanne Boesveldt", + "author_inst": "Division of Human Nutrition and Health, Wageningen University" + }, + { + "author_name": "\u00d6zlem Saatci", + "author_inst": "otorhinolaryngology, Medical Science University" + }, + { + "author_name": "Luis R. Saraiva", + "author_inst": "Translational Medicine Division, Sidra Medicine" + }, + { + "author_name": "Cailu Lin", + "author_inst": "Monell Chemical Senses Center" + }, + { + "author_name": "J\u00e9r\u00f4me Golebiowski", + "author_inst": "Institut de Chimie de Nice, UMR CNRS 7272, Universit\u00e9 C\u00f4te d'Azur" + }, + { + "author_name": "Liang-Dar Hwang", + "author_inst": "The University of Queensland Diamantina Institute, The University of Queensland" + }, + { + "author_name": "Mehmet Hakan Ozdener", + "author_inst": "Monell Chemical Senses Center" + }, + { + "author_name": "Maria Dolors Gu\u00e0rdia", + "author_inst": "Food Technology, IRTA" + }, + { + "author_name": "Christophe Laudamiel", + "author_inst": "DreamAir Llc" + }, + { + "author_name": "Marina Ritchie", + "author_inst": "Neurobiology and Behavior, University of California, Irvine" + }, + { + "author_name": "Jan Havl\u00edcek", + "author_inst": "Department of Zoology, Charles University" + }, + { + "author_name": "Denis Pierron", + "author_inst": "M\u00e9decine Evolutive UMR5288, Universit\u00e9 de Toulouse-CNRS" + }, + { + "author_name": "Eugeni Roura", + "author_inst": "Centre for Nutrition and Food Sciences, The University of Queensland" + }, + { + "author_name": "Marta Navarro", + "author_inst": "Centre for Nutrition and Food Sciences, The University of Queensland" + }, + { + "author_name": "Alissa A. Nolden", + "author_inst": "Department of Food Science, University of Massachusetts" + }, + { + "author_name": "Juyun Lim", + "author_inst": "Food Science and Technology, Oregon State University" + }, + { + "author_name": "KL Whitcroft", + "author_inst": "Ear Institute, UCL" + }, + { + "author_name": "Lauren R. Colquitt", + "author_inst": "Monell Chemical Senses Center" + }, + { + "author_name": "Camille Ferdenzi", + "author_inst": "Lyon Neuroscience Research Center, CNRS UMR5292 - INSERM U1028 - University Lyon 1" + }, + { + "author_name": "Evelyn V. Brindha", + "author_inst": "EEE, Karunya University" + }, + { + "author_name": "Aytug Altundag", + "author_inst": "Otorhinolaryngology Department, Biruni University" + }, + { + "author_name": "Alberto Macchi", + "author_inst": "ENT department, Italian Academy Of Rhinology - Assi Sette Laghi Varese" + }, + { + "author_name": "Alexia Nunez-Parra", + "author_inst": "Department of Biology, Universidad de Chile" + }, + { + "author_name": "Zara M. Patel", + "author_inst": "Department of Biology, Stanford University School of Medicine" + }, + { + "author_name": "S\u00e9bastien Fiorucci", + "author_inst": "Institut de Chimie de Nice, UMR 7272 CNRS, Universit\u00e9 C\u00f4te d'Azur" + }, + { + "author_name": "Carl M. Philpott", + "author_inst": "The Norfolk Smell & Taste Clinic, University of East Anglia" + }, + { + "author_name": "Barry C. Smith", + "author_inst": "Institute of Philosophy, University of London" + }, + { + "author_name": "Johan N Lundstr\u00f6m", + "author_inst": "Department of Clinical Neuroscience, Karolinska Institutet" + }, + { + "author_name": "Carla Mucignat", + "author_inst": "Department of Molecular Medicine, University of Padova" + }, + { + "author_name": "Jane K. Parker", + "author_inst": "Department of Food and Nutritional Sciences, University of Reading" + }, + { + "author_name": "Mirjam van den Brink", + "author_inst": "Laboratory of Behavioural Gastronomy, Maastricht University" + }, + { + "author_name": "Michael Schmuker", + "author_inst": "Department of Computer Science, University of Hertfordshire" + }, + { + "author_name": "Florian Ph.S Fischmeister", + "author_inst": "Institute of Psychology, University of Graz" + }, + { + "author_name": "Thomas Heinbockel", + "author_inst": "Department of Anatomy, Howard University College of Medicine" + }, + { + "author_name": "Vonnie D.C. Shields", + "author_inst": "Biological Sciences Department, Fisher College of Science and Mathematics, Towson University" + }, + { + "author_name": "Farhoud Faraji", + "author_inst": "Otolaryngology-Head and Neck Surgery, University of California San Diego Health" + }, + { + "author_name": "Enrique Enrique Santamar\u00eda", + "author_inst": "Clinical Neuroproteomics Unit, Navarrabiomed-IDISNA" + }, + { + "author_name": "William E.A. Fredborg", + "author_inst": "Department of Psychology, Stockholm University" + }, + { + "author_name": "Gabriella Morini", + "author_inst": "University of Gastronomic Sciences" + }, + { + "author_name": "Jonas K. Olofsson", + "author_inst": "Department of Psychology, Stockholm University" + }, + { + "author_name": "Maryam Jalessi", + "author_inst": "Skull Base Research Center, The Five Senses Institute, Iran University of Medical Sciences" + }, + { + "author_name": "Noam Karni", + "author_inst": "Skull Base Research Center, Hadassah Medical Center" + }, + { + "author_name": "Anna D'Errico", + "author_inst": "Skull Base Research Center, Goethe Universit\u00e4t Frankfurt" + }, + { + "author_name": "Rafieh Alizadeh", + "author_inst": "ENT and Head and Neck Research Center and Department,Hazrat Rasoul Hospital, the Five Senses Institute, Iran University of Medical Sciences" + }, + { + "author_name": "Robert Pellegrino", + "author_inst": "Food Science Department, University of Tennessee" + }, + { + "author_name": "Pablo Meyer", + "author_inst": "Health Care and Life Sciences, IBM T.J. Watson Research Center" + }, + { + "author_name": "Caroline Huart", + "author_inst": "Otorhinolaryngology, Cliniques universitaires Saint-Luc, Brussels, Belgium" + }, + { + "author_name": "Ben Chen", + "author_inst": "Otorhinolaryngology, Guangzhou Medical University" + }, + { + "author_name": "Graciela M. Soler", + "author_inst": "Otorhinolaringology, Buenos Aires University and GEOG (Grupo de Estudio de Olfato y Gusto)" + }, + { + "author_name": "Mohammed K. Alwashahi", + "author_inst": "Surgery Department, ENT Division, Sultan Qaboos University" + }, + { + "author_name": "Olagunju Abdulrahman", + "author_inst": "Department of Physiology, The Federal University of Technology, Akure, Nigeria." + }, + { + "author_name": "Antje Welge-L\u00fcssen", + "author_inst": "Department of Physiology, University Hospital Basel, Basel" + }, + { + "author_name": "Pamela Dalton", + "author_inst": "Monell Chemical Senses Center" + }, + { + "author_name": "Jessica Freiherr", + "author_inst": "Department of Psychiatry and Psychotherapy, FAU Erlangen" + }, + { + "author_name": "Carol H. Yan", + "author_inst": "Department of Psychiatry and Psychotherapy, University of California San Diego" + }, + { + "author_name": "Jasper H. B. de Groot", + "author_inst": "Psychology, Utrecht University" + }, + { + "author_name": "Vera V. Voznessenskaya", + "author_inst": "Innovative Technologies, Severtsov Institute of Ecology and Evolution RAS" + }, + { + "author_name": "Hadar Klein", + "author_inst": "Innovative Technologies, The Hebrew University of Jerusalem" + }, + { + "author_name": "Jingguo Chen", + "author_inst": "Department of Otolaryngology-Head and Neck Surgery, Second Affiliated Hospital of Xi'an Jiaotong University" + }, + { + "author_name": "Masako Okamoto", + "author_inst": "Department of Applied Biological Chemistry, The University of Tokyo" + }, + { + "author_name": "Elizabeth A. Sell", + "author_inst": "Perelman School of Medicine, University of Pennsylvania" + }, + { + "author_name": "Preet Bano Singh", + "author_inst": "Department of Oral Surgery and Oral Medicine, Faculty of Dentistry, University of Oslo" + }, + { + "author_name": "Julie Walsh-Messinger", + "author_inst": "Psychology, University of Dayton" + }, + { + "author_name": "Nicholas S. Archer", + "author_inst": "Agriculture and Food, The Commonwealth Scientific and Industrial Research Organisation (CSIRO)" + }, + { + "author_name": "Sachiko Koyama", + "author_inst": "Department of Biology, Indiana University" + }, + { + "author_name": "Vincent Deary", + "author_inst": "Department of Psychology, Northumbria University Newcastle" + }, + { + "author_name": "S. Craig Roberts", + "author_inst": "Division of Psychology, University of Stirling" + }, + { + "author_name": "H\u00fcseyin Yanik", + "author_inst": "Electrical and Electronics Engineering, Mersin University" + }, + { + "author_name": "Samet Albayrak", + "author_inst": "Cognitive Science, Middle East Technical University" + }, + { + "author_name": "Lenka Martinec Nov\u00e1kov", + "author_inst": "Department of Anthropology, Charles University, Faculty of Humanities" + }, + { + "author_name": "Ilja Croijmans", + "author_inst": "Faculty of Social and Behavioral Sciences, Utrecht University" + }, + { + "author_name": "Patricia Portillo Mazal", + "author_inst": "Servicio Otorrinolaringolog\u00eda, Hospital Italiano de Buenos Aires" + }, + { + "author_name": "Shima T. Moein", + "author_inst": "School of Biological Sciences, Institute for Research in Fundamental Sciences" + }, + { + "author_name": "Eitan Margulis", + "author_inst": "Institute of Biochemistry, Food Science and Nutrition, The Hebrew University of Jerusalem" + }, + { + "author_name": "Coralie Mignot", + "author_inst": "Department of Otorhinolaryngology, Smell and Taste Center, Dresden" + }, + { + "author_name": "Sajidxa Mari\u00f1o", + "author_inst": "Founder and CEO, Centro de Otorrinolaringolog\u00eda Respira Libre" + }, + { + "author_name": "Dejan Georgiev", + "author_inst": "Department of Neurology, University Medical Centre Ljubljana" + }, + { + "author_name": "Pavan K. Kaushik", + "author_inst": "National Center for Biological Sciences, Tata Institute of Fundamental Research" + }, + { + "author_name": "Bettina Malnic", + "author_inst": "Department of Biochemistry, University of S\u00e3o Paulo, Brazil" + }, + { + "author_name": "Hong Wang", + "author_inst": "Monell Chemical Senses Center" + }, + { + "author_name": "Shima Seyed-Allaei", + "author_inst": "School of Cognitive Sciences, Institute for Research in Fundamental Sciences" + }, + { + "author_name": "Nur Yoluk", + "author_inst": "Institute of Health Sciences, Mersin University" + }, + { + "author_name": "Sara Razzaghi", + "author_inst": "Bilkent Brain Research Center, Bilkent University" + }, + { + "author_name": "Jeb M. Justice", + "author_inst": "Otolaryngology, University of Florida" + }, + { + "author_name": "Diego Restrepo", + "author_inst": "Department of Cell and Developmental Biology, University of Colorado Anschutz Medical Campus" + }, + { + "author_name": "Julien W Hsieh", + "author_inst": "Rhinology- Olfactology Unit, ENT Department, Geneva University Hospitals" + }, + { + "author_name": "Danielle R. Reed", + "author_inst": "Monell Chemical Senses Center" + }, + { + "author_name": "Thomas Hummel", + "author_inst": "Department of Otrohinolaryngology, Technische Universitat Dresden" + }, + { + "author_name": "Steven D Munger", + "author_inst": "Department of Pharmacology and Therapeutics and Center for Smell and Taste, University of Florida" + }, + { + "author_name": "John E Hayes", + "author_inst": "Department of Food Science, The Pennsylvania State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1499093,35 +1499722,27 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.05.03.20089755", - "rel_title": "Who maintains a good mental health in a locked-down country? A French nationwide online survey of 11,391 participants", + "rel_doi": "10.1101/2020.05.06.080960", + "rel_title": "The transcriptomic profiling of COVID-19 compared to SARS, MERS, Ebola, and H1N1", "rel_date": "2020-05-08", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.03.20089755", - "rel_abs": "BackgroundLockdown measures induce massive societal perturbations and can differentially affect mental wellbeing in populations depending on individual determinants. We aim at investigating the sociodemographic and environmental determinants of wellbeing during global lockdown due to the SARS-CoV-2 pandemic.\n\nMethodsA nationwide survey was sent online to the French population during the second week of global lockdown during the SARS-CoV-2 pandemic, between March 25, 2020 and March 30, 2020. Volunteers were recruited on social networks, online newspapers, and mailing lists. We analyzed sociodemographic and environmental variables obtained from a co-built and evidence-based questionnaire. Mental wellbeing was measured by the Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS).\n\nResultsWe analyzed data from 11,391 (56.6%) out of 20,235 participants who answered the questionnaire. After weighting data on age and gender distributions, 5415 of the respondents were male (47.5%), 5932 were female (52.1%), and 52 (0.5%) registered as \"other.\" Multivariate analyses indicated that various factors impacted mental wellbeing. Being female (p < .001), a student (p < .001), disabled (p = .001), or having no access to outdoor space (p = 0.02) was associated with lower WEMWBS scores. Conversely, being employed (p < .001) and having more social contacts (p < .01) were both associated with greater mental wellbeing.\n\nInterpretationWe revealed differences in mental wellbeing among the French population at the early stages of global lockdown. Authorities should consider the particular vulnerability of students, persons with disabilities, and those living in constrained housing conditions that could increase the negative impact of lockdown on mental health.", - "rel_num_authors": 4, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.06.080960", + "rel_abs": "COVID-19 pandemic is a global crisis that threatens our way of life. As of April 29, 2020, COVID-19 has claimed more than 200,000 lives, with a global mortality rate of ~7% and recovery rate of ~30%. Understanding the interaction of cellular targets to the SARS-CoV2 infection is crucial for therapeutic development. Therefore, the aim of this study was to perform a comparative analysis of transcriptomic signatures of infection of COVID-19 compared to different respiratory viruses (Ebola, H1N1, MERS-CoV, and SARS-CoV), to determine unique anti-COVID1-19 gene signature. We identified for the first time molecular pathways for Heparin-binding, RAGE, miRNA, and PLA2 inhibitors, to be associated with SARS-CoV2 infection. The NRCAM and SAA2 that are involved in severe inflammatory response, and FGF1 and FOXO1 genes, which are associated with immune regulation, were found to be associated with a cellular gene response to COVID-19 infection. Moreover, several cytokines, most significantly the IL-8, IL-6, demonstrated key associations with COVID-19 infection. Interestingly, the only response gene that was shared between the five viral infections was SERPINB1. The PPI study sheds light on genes with high interaction activity that COVID-19 shares with other viral infections. The findings showed that the genetic pathways associated with Rheumatoid arthritis, AGE-RAGE signaling system, Malaria, Hepatitis B, and Influenza A were of high significance. We found that the virogenomic transcriptome of infection, gene modulation of host antiviral responses, and GO terms of both COVID-19 and Ebola are more similar compared to SARS, H1N1, and MERS. This work compares the virogenomic signatures of highly pathogenic viruses and provides valid targets for potential therapy against COVID-19.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Frederic HAESEBAERT", - "author_inst": "CH le Vinatier" - }, - { - "author_name": "Julie Haesebaert", - "author_inst": "Lyon University" - }, - { - "author_name": "Elodie Zante", - "author_inst": "Ch Le Vinatier" + "author_name": "Alsamman M Alsamman", + "author_inst": "Search Results Web results Agricultural Genetic Engineering Research Institute (AGERl)" }, { - "author_name": "Nicolas Franck", - "author_inst": "Lyon University" + "author_name": "Hatem Zayed", + "author_inst": "Department of Biomedical Sciences College of Health Sciences, QU Health, Qatar University, Doha, Qatar." } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "psychiatry and clinical psychology" + "type": "new results", + "category": "genomics" }, { "rel_doi": "10.1101/2020.05.04.20088625", @@ -1500679,53 +1501300,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.05.20092635", - "rel_title": "Studies of Novel Coronavirus Disease 19 (COVID-19) Pandemic: A Global Analysis of Literature", + "rel_doi": "10.1101/2020.05.02.20088724", + "rel_title": "The Infection Rate of the Coronavirus Disease 2019 (COVID-19) in Wuhan, China", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092635", - "rel_abs": "An exponential growth of literature about novel coronavirus disease 19 (COVID-19) has been observed in the last few months. This textual analysis of 5,780 publications extracted from the Web of Science, Medline, and Scopus databases was performed to explore the current research focuses and propose further research agenda. The Latent Dirichlet allocation was used for topic modeling. Regression analysis was conducted to examine country variations in the research focuses. Results indicated that publications were mainly contributed by the United States, China, and European countries. Guidelines for emergency care and surgical, viral pathogenesis, and global responses in the COVID-19 pandemic were the most common topics. There was variation in the research approaches to mitigate COVID-19 problems in countries with different income and transmission levels. Findings highlighted the need for global research collaboration among high- and low/middle-income countries in the different stages of prevention and control the pandemic.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.02.20088724", + "rel_abs": "Summary BoxO_ST_ABSWhat is already known about this subject?C_ST_ABSThe Wuhan city in China had a much higher mortality rate (Feb 10th statistics: 748 death/18,454 diagnosis =4.05%; Apr 24th statistics: 3,869 death/50,333 diagnosis=7.69%) than the rest of China.\n\nWhat are the new findings?Based on our analysis, the number of infected people in Wuhan is estimated to be 143,000 (88,000 to 242,000) in late January and early February, significantly higher than the published number of diagnosed cases.\n\nWhat are the recommendations for policy and practice?Increased awareness of the original infection rates in Wuhan, China is critically important for proper public health measures at all levels, as well as to eliminate panic caused by overestimated mortality rate that may bias health policy actions by the authorities", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Bach Xuan Tran", - "author_inst": "Hanoi Medical University" - }, - { - "author_name": "Giang Hai Ha", - "author_inst": "Duy Tan University, Da Nang 550000, Vietnam" - }, - { - "author_name": "Long Hoang Nguyen", - "author_inst": "VNU School of Medicine and Pharmacy, Vietnam National University, Hanoi 100000, Vietnam" - }, - { - "author_name": "Giang Thu Vu", - "author_inst": "Nguyen Tat Thanh University, Ho Chi Minh City 700000, Vietnam" - }, - { - "author_name": "Hai Thanh Phan", - "author_inst": "Duy Tan University, Da Nang 550000, Vietnam" + "author_name": "Huiqi Qu", + "author_inst": "Children's Hospital of Philadelphia" }, { - "author_name": "Huong Thi Le", - "author_inst": "Hanoi Medical University, Hanoi 100000, Vietnam" + "author_name": "Zhangkai Cheng", + "author_inst": "The University of Sydney" }, { - "author_name": "Carl A. Latkin", - "author_inst": "Johns Hopkins University, Baltimore, MD 21205, United States" + "author_name": "Zhifeng Duan", + "author_inst": "Childrens Hospital of Philadelphia" }, { - "author_name": "Cyrus S.H. Ho", - "author_inst": "Department of Psychological Medicine, National University Hospital, Singapore 119074, Singapore" + "author_name": "Lifeng Tian", + "author_inst": "Childrens Hospital of Philadelphia" }, { - "author_name": "Roger C.M. Ho", - "author_inst": "Department of Psychological Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 119228, Singapore" + "author_name": "Hakon Hakonarson", + "author_inst": "The Children's Hospital of Philadelphia and Unviersity of Pennsylvania" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1502377,25 +1502982,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.05.04.20090324", - "rel_title": "Estimating Excess Deaths in the United States Early in the COVID-19 Pandemic", + "rel_doi": "10.1101/2020.05.04.20090233", + "rel_title": "Search for the trend of COVID-19 infection following Farr's law, IDEA model and power law.", "rel_date": "2020-05-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090324", - "rel_abs": "1Deaths are frequently under-estimated during emergencies, times when accurate mortality estimates are crucial for pandemic response and public adherence to non-pharmaceutical interventions. This study estimates excess all-cause, pneumonia, and influenza mortality during the COVID-19 health emergency using the June 12, 2020 release of weekly mortality data from the United States (U.S.) Mortality Surveillance Survey (MSS) from September 27, 2015 to May 9, 2020, using semiparametric and conventional time-series models in 9 states with high reported COVID-19 deaths and apparently complete mortality data: California, Colorado, Florida, Illinois, Massachusetts, Michigan, New Jersey, New York, and Washington. The May 9 endpoint was chosen due to apparently increased reporting lags in provisional mortality counts. We estimated greater excess mortality than official COVID-19 mortality in the U.S. (excess mortality 95% confidence interval (CI) (80862, 107284) vs. 78834 COVID-19 deaths) and 6 states: California (excess mortality 95% CI (2891, 5873) vs. 2849 COVID-19 deaths); Illinois (95% CI (4412, 5871) vs. 3525 COVID-19 deaths); Massachusetts (95% CI (5061, 6317) vs. 5050 COVID-19 deaths); New Jersey (95% CI (12497, 15307) vs. 10465 COVID-19 deaths); and New York (95% CI (30469, 37722) vs. 26584 COVID-19 deaths). Conventional model results were consistent with semiparametric results but less precise.\n\nOfficial COVID-19 mortality substantially understates actual mortality, suggesting greater case-fatality rates. Mortality reporting lags appeared to worsen during the pandemic, when timeliness in surveillance systems was most crucial for improving pandemic response.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090233", + "rel_abs": "Following power law, Farrs law and IDEA model, we analyze the data of COVID-19 pandemic for India up to 2 May, 2020 and for Germany, France, Italy, the USA, Singapore, China and Denmark up to 26 April, 2020. The cumulative total number of infected persons as a function of elapsed time has been fitted with power law to find the scaling exponent ({gamma}). The reduction in{gamma} in different countries signals the reduction in the growth of infection, possibly, due to long-term Government intervention. The extent of infection and reproduction rate R0 of the same are also examined using Farrs law and IDEA model. The new cases per day with time assume Gaussian bell shaped curve, obeying the rule that faster rise follows faster decay. In India and Singapore, the peak of the bell shaped curve is still elusive. It is found that, till date, countries such as Denmark and India implementing sooner lockdown have underwent lower number of new cases of infection. Daily variation shows, R0 of all the countries is reducing, ushering in fresh hopes to combat COVID-19. Finally, we try to make a prediction as to the date on which the different countries will come down to daily cases of infection as low as one hundred (100).", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Roberto Rivera", - "author_inst": "University of Puerto Rico - Mayaguez" + "author_name": "SRIJIT BHATTACHARYA", + "author_inst": "BARASAT GOVERNMENT COLLEGE" }, { - "author_name": "Janet Rosenbaum", - "author_inst": "SUNY downstate" + "author_name": "Md Moinul Islam", + "author_inst": "Department of Physics, APC College, New Barrakpur, Kolkata-700131, W.B, India." }, { - "author_name": "Walter Quispe", - "author_inst": "University of Puerto Rico - Mayaguez" + "author_name": "Alokkumar De", + "author_inst": "Department of Physics, Raniganj Girls College, Raniganj-713358, W.B., India" } ], "version": "1", @@ -1504050,33 +1504655,25 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2020.05.04.20090670", - "rel_title": "Projection of COVID-19 Cases and Deaths in the US as Individual States Re-open May 4,2020", + "rel_doi": "10.1101/2020.05.05.20092361", + "rel_title": "Cooperative virus propagation underlies COVID-19 transmission dynamics", "rel_date": "2020-05-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.04.20090670", - "rel_abs": "In March and April 2020, control measures enforcing social distancing and restricting individual movement and contact were adopted across the United States in an effort to slow the spread and growth of COVID-19. However, a number of states have now begun to ease these restrictions. Here, we evaluate the effects of loosening stay-at-home orders on COVID-19 incidence and related outcomes. We use a metapopulation model applied at county resolution to simulate the spread and growth of COVID-19 incidence in the United States. We calibrate the model against county-level daily case and death data collected from February 21, 2020 to May 2, 2020, and project the outbreak in 3,142 US counties for 6 weeks into the future. Projections for daily reported cases, daily new infections (both reported and unreported), new and cumulative hospital bed demand, ICU bed and ventilator demand, as well as daily mortality, are generated. We observe a rebound in COVID-19 incidence and deaths beginning in late May, approximately 2 to 4 weeks after states begin to reopen. Importantly, the lag between infection acquisition and case confirmation, coupled with insufficient broader testing and contact tracing, will mask any rebound and exponential growth of the COVID-19 until it is well underway.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.05.20092361", + "rel_abs": "The global pandemic due to the emergence of a novel coronavirus (COVID-19) is a threat to the future health of humanity. There remains an urgent need to understand its transmission characteristics and design effective interventions to mitigate its spread. In this study, we define a non-linear (known in biochemistry models as allosteric or cooperative) relationship between viral shedding, viral dose and COVID-19 infection propagation. We develop a mathematical model of the dynamics of COVID-19 to link quantitative features of viral shedding, human exposure and transmission in nine countries impacted by the ongoing COVID-19 pandemic. The model was then used to evaluate the efficacy of interventions against virus transmission. We found that cooperativity was important to capture country-specific transmission dynamics and leads to resistance to mitigating transmission in mild or moderate interventions. The behaviors of the model emphasize that strict interventions greatly limiting both virus shedding and human exposure are indispensable to achieving effective containment of COVID-19.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Teresa Yamana", - "author_inst": "Columbia University" - }, - { - "author_name": "Sen Pei", - "author_inst": "Columbia University" - }, - { - "author_name": "Sasikiran Kandula", - "author_inst": "Columbia University" + "author_name": "Ziwei Dai", + "author_inst": "Duke University" }, { - "author_name": "Jeffrey Shaman", - "author_inst": "Columbia University" + "author_name": "Jason W Locasale", + "author_inst": "Duke University" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1505320,37 +1505917,113 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.05.01.20081034", - "rel_title": "Evaluation of nCoV-QS (MiCo BioMed) for RT-qPCR detection of SARS-CoV-2 from nasopharyngeal samples using CDC FDA EUA qPCR kit as a gold standard: an example of the need of validation studies.", + "rel_doi": "10.1101/2020.05.02.20088898", + "rel_title": "Repeated seroprevalence of anti-SARS-CoV-2 IgG antibodies in a population-based sample from Geneva, Switzerland", "rel_date": "2020-05-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20081034", - "rel_abs": "BackgroundSeveral qPCR kits are available for SARS-CoV-2 diagnosis, mostly lacking of evaluation due to covid19 emergency.\n\nObjectiveWe evaluated nCoV-QS (MiCo BioMed) kit using CDC kit as gold standard.\n\nResultsWe found limitations for nCoV-QS: 1) lower sensitivity 2) lack of RNA quality control probe 3) no capacity to quantify viral load.\n\nConclussionsValidation studies should be implemented for any SARS-CoV-2 RT-qPCR commercial kit to prevent unreliable diagnosis.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.02.20088898", + "rel_abs": "BackgroundAssessing the burden of COVID-19 based on medically-attended case counts is suboptimal given its reliance on testing strategy, changing case definitions and the wide spectrum of disease presentation. Population-based serosurveys provide one avenue for estimating infection rates and monitoring the progression of the epidemic, overcoming many of these limitations.\n\nMethodsTaking advantage of a pool of adult participants from population-representative surveys conducted in Geneva, Switzerland, we implemented a study consisting of 8 weekly serosurveys among these participants and their household members older than 5 years. We tested each participant for anti-SARS-CoV-2-IgG antibodies using a commercially available enzyme-linked immunosorbent assay (Euroimmun AG, Lubeck, Germany). We estimated seroprevalence using a Bayesian regression model taking into account test performance and adjusting for the age and sex of Genevas population.\n\nResultsIn the first three weeks, we enrolled 1335 participants coming from 633 households, with 16% <20 years of age and 53.6% female, a distribution similar to that of Geneva. In the first week, we estimated a seroprevalence of 3.1% (95% CI 0.2-5.99, n=343). This increased to 6.1% (95% CI 2.69.33, n=416) in the second, and to 9.7% (95% CI 6.1-13.11, n=576) in the third week. We found that 5-19 year-olds (6.0%, 95% CI 2.3-10.2%) had similar seroprevalence to 20-49 year olds (8.5%, 95%CI 4.99-11.7), while significantly lower seroprevalence was observed among those 50 and older (3.7%, 95% CI 0.99-6.0, p=0.0008).\n\nInterpretationAssuming that the presence of IgG antibodies is at least in the short-term associated with immunity, these results highlight that the epidemic is far from burning out simply due to herd immunity. Further, no differences in seroprevalence between children and middle age adults are observed. These results must be considered as Switzerland and the world look towards easing restrictions aimed at curbing transmission.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Byron Freire-Paspuel", - "author_inst": "Universidad de las Americas" + "author_name": "Silvia Stringhini", + "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland; Faculty of Medicine, University of Geneva, Geneva, Switzerland; University Centre fo" }, { - "author_name": "Patricio Vega", - "author_inst": "ABG- Galapagos" + "author_name": "Ania Wisniak", + "author_inst": "Institute of Global Health, University of Geneva, Geneva, Switzerland" }, { - "author_name": "Alberto Velez", - "author_inst": "ABG-Galapagos" + "author_name": "Giovanni Piumatti", + "author_inst": "Geneva University Hospitals" }, { - "author_name": "Paulina Castello", - "author_inst": "ABG-Galapagos" + "author_name": "Andrew S Azman", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Marilyn Cruz", - "author_inst": "ABG-Galapagos" + "author_name": "Stephen A Lauer", + "author_inst": "Johns Hopkins University" }, { - "author_name": "Miguel Angel Garcia Bereguiain", - "author_inst": "Universidad de Las Americas" + "author_name": "Helene Baysson", + "author_inst": "University of Geneva" + }, + { + "author_name": "David De Ridder", + "author_inst": "University of Geneva" + }, + { + "author_name": "Dusan Petrovic", + "author_inst": "Geneva University Hospitals" + }, + { + "author_name": "Stephanie Schrempft", + "author_inst": "Geneva University Hospitals" + }, + { + "author_name": "Kailing Marcus", + "author_inst": "Geneva University Hospitals" + }, + { + "author_name": "Isabelle Arm-Vernez", + "author_inst": "Geneva Center for Emerging Viral Diseases and Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland" + }, + { + "author_name": "Sabine Yerly", + "author_inst": "Geneva University Hospitals" + }, + { + "author_name": "Olivia Keiser", + "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland" + }, + { + "author_name": "Samia Hurst", + "author_inst": "Institut Ethique, Histoire, Humanites, University of Geneva, Geneva, Switzerland" + }, + { + "author_name": "Klara Posfay-Barbe", + "author_inst": "Faculty of Medicine, University of Geneva, Geneva, Switzerland" + }, + { + "author_name": "Didier Trono", + "author_inst": "School of Life Sciences, Ecole Polytechnique Federale de Lausanne (EPFL), Lausanne, Switzerland" + }, + { + "author_name": "Didier Pittet", + "author_inst": "Centre for Vaccinology, Department of Pathology and Immunology, University of Geneva, Geneva, Switzerland" + }, + { + "author_name": "Laurent Getaz", + "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" + }, + { + "author_name": "Francois Chappuis", + "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" + }, + { + "author_name": "Isabella Eckerle", + "author_inst": "Geneva Center for Emerging Viral Diseases and Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland" + }, + { + "author_name": "Nicolas Vuilleumier", + "author_inst": "Division of Laboratory Medicine, Geneva University Hospitals, Geneva, Switzerland" + }, + { + "author_name": "Benjamin Meyer", + "author_inst": "University of Geneva" + }, + { + "author_name": "Antoine Flahault", + "author_inst": "Institute of Global Health, Faculty of Medicine, University of Geneva, Geneva, Switzerland" + }, + { + "author_name": "Laurent Kaiser", + "author_inst": "Geneva Center for Emerging Viral Diseases and Laboratory of Virology, Geneva University Hospitals, Geneva, Switzerland" + }, + { + "author_name": "Idris Guessous", + "author_inst": "Division of Primary Care, Geneva University Hospitals, Geneva, Switzerland" } ], "version": "1", @@ -1506806,53 +1507479,109 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.05.01.20087114", - "rel_title": "Lung disease severity, Coronary Artery Calcium, Coronary inflammation and Mortality in Coronavirus Disease 2019.", + "rel_doi": "10.1101/2020.05.01.20087130", + "rel_title": "Dose prediction for repurposing nitazoxanide in SARS-CoV-2 treatment or chemoprophylaxis", "rel_date": "2020-05-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087114", - "rel_abs": "The authors have withdrawn this manuscript at the request of their local IRB, because the objectives outlined in this study were not specifically approved by the IRB. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087130", + "rel_abs": "BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been declared a global pandemic by the World Health Organisation and urgent treatment and prevention strategies are needed. Many clinical trials have been initiated with existing medications, but assessments of the expected plasma and lung exposures at the selected doses have not featured in the prioritisation process. Although no antiviral data is currently available for the major phenolic circulating metabolite of nitazoxanide (known as tizoxanide), the parent ester drug has been shown to exhibit in vitro activity against SARS-CoV-2. Nitazoxanide is an anthelmintic drug and its metabolite tizoxanide has been described to have broad antiviral activity against influenza and other coronaviruses. The present study used physiologically-based pharmacokinetic (PBPK) modelling to inform optimal doses of nitazoxanide capable of maintaining plasma and lung tizoxanide exposures above the reported nitazoxanide 90% effective concentration (EC90) against SARS-CoV-2.\n\nMethodsA whole-body PBPK model was constructed for oral administration of nitazoxanide and validated against available tizoxanide pharmacokinetic data for healthy individuals receiving single doses between 500 mg - 4000 mg with and without food. Additional validation against multiple-dose pharmacokinetic data when given with food was conducted. The validated model was then used to predict alternative doses expected to maintain tizoxanide plasma and lung concentrations over the reported nitazoxanide EC90 in >90% of the simulated population. Optimal design software PopDes was used to estimate an optimal sparse sampling strategy for future clinical trials.\n\nResultsThe PBPK model was validated with AAFE values between 1.01 - 1.58 and a difference less than 2-fold between observed and simulated values for all the reported clinical doses. The model predicted optimal doses of 1200 mg QID, 1600 mg TID, 2900 mg BID in the fasted state and 700 mg QID, 900 mg TID and 1400 mg BID when given with food, to provide tizoxanide plasma and lung concentrations over the reported in vitro EC90 of nitazoxanide against SARS-CoV-2. For BID regimens an optimal sparse sampling strategy of 0.25, 1, 3 and 12h post dose was estimated.\n\nConclusionThe PBPK model predicted that it was possible to achieve plasma and lung tizoxanide concentrations, using proven safe doses of nitazoxanide, that exceed the EC90 for SARS-CoV-2. The PBPK model describing tizoxanide plasma pharmacokinetics after oral administration of nitazoxanide was successfully validated against clinical data. This dose prediction assumes that the tizoxanide metabolite has activity against SARS-CoV-2 similar to that reported for nitazoxanide, as has been reported for other viruses. The model and the reported dosing strategies provide a rational basis for the design (optimising plasma and lung exposures) of future clinical trials of nitazoxanide in the treatment or prevention of SARS-CoV-2 infection.", + "rel_num_authors": 23, "rel_authors": [ { - "author_name": "Nicola Gaibazzi", - "author_inst": "University Hospital of Parma" + "author_name": "Rajith KR Rajoli", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" }, { - "author_name": "Chiara Martini", - "author_inst": "University Hospital of Parma" + "author_name": "Henry Pertinez", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" }, { - "author_name": "Maria Mattioli", - "author_inst": "University Hospital of Parma" + "author_name": "Usman Arshad", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" }, { - "author_name": "Domenico Tuttolomondo", - "author_inst": "University Hospital of Parma" + "author_name": "Helen Box", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" }, { - "author_name": "Angela Guidorossi", - "author_inst": "University Hospital of Parma" + "author_name": "Lee Tatham", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" }, { - "author_name": "Sergio Suma", - "author_inst": "University Hospital of Parma" + "author_name": "Paul Curley", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" }, { - "author_name": "Damini Dey", - "author_inst": "Cedars-Sinai Medical Center, Los Angeles" + "author_name": "Megan Neary", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" }, { - "author_name": "Anselmo Palumbo", - "author_inst": "University Hospital of Parma" + "author_name": "Joanne Sharp", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" }, { - "author_name": "Massimo De Filippo", - "author_inst": "University Hospital of Parma" + "author_name": "Neill J Liptrott", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" + }, + { + "author_name": "Anthony Valentijn", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" + }, + { + "author_name": "Christopher David", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" + }, + { + "author_name": "Steve P Rannard", + "author_inst": "Department of Chemistry, University of Liverpool, Liverpool, L69 3BX, UK" + }, + { + "author_name": "Ghaith Aljayyoussi", + "author_inst": "Centre for Drugs and Diagnostics. Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool L3 5QA, UK" + }, + { + "author_name": "Shaun H Pennington", + "author_inst": "Centre for Drugs and Diagnostics. Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool L3 5QA, UK" + }, + { + "author_name": "Andrew Hill", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" + }, + { + "author_name": "Marta Boffito", + "author_inst": "Chelsea and Westminster NHS Foundation Trust and St Stephens AIDS Trust 4th Floor, Chelsea and Westminster Hospital, 369 Fulham Road, London, SW10 9NH, UK" + }, + { + "author_name": "Stephen A Ward", + "author_inst": "Centre for Drugs and Diagnostics. Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool L3 5QA, UK" + }, + { + "author_name": "Saye H Khoo", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" + }, + { + "author_name": "Patrick G Bray", + "author_inst": "Pat Bray Electrical, 260D Orrell Road, Orrell, Wigan, WN5 8QZ, UK" + }, + { + "author_name": "Paul M. O'Neill", + "author_inst": "Department of Chemistry, University of Liverpool, Liverpool, L69 3BX, UK" + }, + { + "author_name": "W. Dave Hong", + "author_inst": "Department of Chemistry, University of Liverpool, Liverpool, L69 3BX, UK" + }, + { + "author_name": "Giancarlo Biagini", + "author_inst": "Centre for Drugs and Diagnostics. Department of Tropical Disease Biology, Liverpool School of Tropical Medicine, Liverpool L3 5QA, UK" + }, + { + "author_name": "Andrew Owen", + "author_inst": "Department of Molecular and Clinical Pharmacology, Materials Innovation Factory, University of Liverpool, Liverpool, L7 3NY, UK" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1508020,67 +1508749,51 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.05.01.20088179", - "rel_title": "Impact of policy interventions and social distancing on SARS-CoV-2 transmission in the United States", + "rel_doi": "10.1101/2020.05.01.20087932", + "rel_title": "Correlation of coagulation parameters with clinical outcomes in Coronavirus-19 affected minorities in United States: Observational cohort", "rel_date": "2020-05-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20088179", - "rel_abs": "BackgroundPolicymakers have employed various non-pharmaceutical interventions (NPIs) such as stay-at-home orders and school closures to limit the spread of Coronavirus disease (COVID-19). However, these measures are not without cost, and careful analysis is critical to quantify their impact on disease spread and guide future initiatives. This study aims to measure the impact of NPIs on the effective reproductive number (Rt) and other COVID-19 outcomes in U.S. states.\n\nMethodsIn order to standardize the stage of disease spread in each state, this study analyzes the weeks immediately after each state reached 500 cases. The primary outcomes were average Rt in the week following 500 cases and doubling time from 500 to 1000 cases. Linear and logistic regressions were performed in R to assess the impact of various NPIs while controlling for population density, GDP, and certain health metrics. This analysis was repeated for deaths with doubling time from 50 to 100 deaths and included several healthcare infrastructure control variables.\n\nResultsStates that had a stay-at-home order in place at the time of their 500th case are associated with lower average Rt the following week compared to states without a stay-at-home order (p < 0.001) and are significantly less likely to have an Rt>1 (OR 0.07, 95% CI 0.01 to 0.37, p = 0.004). These states also experienced a significantly longer doubling time from 500 to 1000 cases (HR 0.35, 95% CI 0.17 to 0.72, p = 0.004). States in the highest quartile of average time spent at home were also slower to reach 1000 cases than those in the lowest quartile (HR 0.18, 95% CI 0.06 to 0.53, p = 0.002).\n\nDiscussionFew studies have analyzed the effect of statewide stay-at-home orders, school closures, and other social distancing measures in the U.S., which has faced the largest COVID-19 case burden. States with stay-at-home orders have a 93% decrease in the odds of having a positive Rt at a standardized point in disease burden. States that plan to scale back such measures should carefully monitor transmission metrics.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.05.01.20087932", + "rel_abs": "ImportanceCOVID-19 has caused a worldwide illness and New York has become the epicenter of COVID-19 in the United States. Currently Bronx has the highest prevalence per capita in New York.\n\nObjectiveTo investigate the coagulopathic presentation of COVID and its natural course and to investigate whether hematologic and coagulation parameters can be used to assess illness severity and death.\n\nDesignRetrospective case study of positive COVID inpatients between 3/20/2020-3/31/2020.\n\nSettingMontefiore Health System main hospital, Moses, a large tertiary care center in the Bronx.\n\nParticipantsAdult inpatients with positive COVID tests hospitalized at MHS.\n\nExposure (for observational studies)Datasets of participants were queried for physiological, demographic (age, sex, socioeconomic status and self-reported race and/or ethnicity) and laboratory data.\n\nMain Outcome and MeasuresRelationship and predictive value of measured parameters to mortality and illness severity.\n\nResultsOf the 217 in this case review, 70 died during hospitalization while 147 were discharged home. Only the admission PT and first D-Dimer could very significantly differentiate those who were discharged alive and those who died. Logistic regression analysis shows increased odds ratio for mortality by first D-Dimer within 48 hrs. of admission. The optimal cut-point for the initial D-Dimer to predict mortality was found to be 1.65 g/mL\n\nConclusionsWe describe here a comprehensive assessment of hematologic and coagulation parameters in COVID and examine the relationship of these to mortality. We demonstrate that both initial and maximum D-Dimer values are biomarkers that can be used for survival assessments.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Nickolas Dreher", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Zachary Spiera", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Fiona M McAuley", - "author_inst": "Mount Sinai" - }, - { - "author_name": "Lindsey Kuohn", - "author_inst": "Mount Sinai" - }, - { - "author_name": "John R Durbin", - "author_inst": "Mount Sinai" + "author_name": "Morayma Reyes Gil", + "author_inst": "Montefiore Medical Center" }, { - "author_name": "Naoum Fares Marayati", - "author_inst": "Mount Sinai" + "author_name": "Jesus D Gonzalez-Lugo", + "author_inst": "Montefiore Medical Center" }, { - "author_name": "Muhammad Ali", - "author_inst": "Mount Sinai" + "author_name": "Shafia Rahman", + "author_inst": "Montefiore Medical Center" }, { - "author_name": "Adam Y Li", - "author_inst": "Mount Sinai" + "author_name": "Mohammad Barouqa", + "author_inst": "Montefiore Medical Center" }, { - "author_name": "Theodore C Hannah", - "author_inst": "Mount Sinai" + "author_name": "James Szymnaski", + "author_inst": "Montefiore Medical Center and Albert Einstein College of Medicine" }, { - "author_name": "Alex Gometz", - "author_inst": "Concussion Management of New York" + "author_name": "Kenji Ikemura", + "author_inst": "Montefiore Medical Center" }, { - "author_name": "JT Kostman", - "author_inst": "ProtectedBy.AI" + "author_name": "Yungtai Lo", + "author_inst": "Albert Einstein College of Medicine" }, { - "author_name": "Tanvir F Choudhri", - "author_inst": "Mount Sinai" + "author_name": "Henny H Billett", + "author_inst": "Montefiore Medical Center and Albert Einstein College of Medicine" } ], "version": "1", "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health policy" + "category": "hematology" }, { "rel_doi": "10.1101/2020.05.02.20089045", @@ -1509606,39 +1510319,91 @@ "category": "pharmacology and therapeutics" }, { - "rel_doi": "10.1101/2020.04.29.20085563", - "rel_title": "Public knowledge, attitudes and practices towards COVID-19: A cross-sectional study in Malaysia", + "rel_doi": "10.1101/2020.04.30.20085928", + "rel_title": "COVID-19 in breast cancer patients: a cohort at the Institut Curie hospitals in the Paris area", "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20085563", - "rel_abs": "In an effort to mitigate the outbreak of COVID-19, many countries have imposed drastic lockdown, movement control or shelter in place orders on their residents. The effectiveness of these mitigation measures is highly dependent on cooperation and compliance of all members of society. The knowledge, attitudes and practices people hold toward the disease play an integral role in determining a societys readiness to accept behavioural change measures from health authorities. The aim of this study was to determine the knowledge levels, attitudes and practices toward COVID-19 among the Malaysian public. A cross-sectional online survey of 4,850 Malaysian residents was conducted between 27th March and 3rd April 2020. The survey instrument consisted of demographic characteristics, 13 items on knowledge, 3 items on attitudes and 3 items on practices, modified from a previously published questionnaire on COVID-19. Descriptive statistics, chi-square tests, t-tests and one-way analysis of variance (ANOVA) were conducted. The overall correct rate of the knowledge questionnaire was 80.5%. Most participants held positive attitudes toward the successful control of COVID-19 (83.1%), the ability of Malaysia to conquer the disease (95.9%) and the way the Malaysian government was handling the crisis (89.9%). Most participants were also taking precautions such as avoiding crowds (83.4%) and practising proper hand hygiene (87.8%) in the week before the movement control order started. However, the wearing of face masks was less common (51.2%). This survey is among the first to assess knowledge, attitudes and practice in response to the COVID-19 pandemic in Malaysia. The results highlight the importance of consistent messaging from health authorities and the government as well as the need for tailored health education programs to improve levels of knowledge, attitudes and practices.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20085928", + "rel_abs": "BackgroundCancer patients have been reported to be at higher risk of COVID-19 complications and deaths. We report the characteristics and outcome of patients diagnosed with COVID-19 during breast cancer treatment at Institut Curie hospitals (ICH, Paris area, France).\n\nMethodsAn IRB-approved prospective registry was set up at ICH on March 13th, 2020 for all breast cancer patients with COVID-19 symptoms or radiologic signs. Registered data included patient history, tumor characteristics and treatments, COVID-19 symptoms, radiological features and outcome. Data extraction was done on April 25th, 2020. COVID-19 patients were defined as those with either a positive RNA test or typical, newly appeared lung CT-scan abnormalities.\n\nResultsAmong 15,600 patients actively treated for early or metastatic breast cancer during the last 4 months at ICH, 76 patients with suspected COVID-19 infection were included in the registry and followed. Fifty-nine of these patients were diagnosed with COVID-19 based on viral RNA testing (N=41) or typical radiologic signs: 37/59 (63%) COVID-19 patients were treated for metastatic breast cancer, and 13/59 (22%) of them were taking corticosteroids daily. Common clinical features mostly consisted of fever and/or cough, while ground-glass opacities were the most common radiologic sign at diagnosis. We found no association between prior radiation therapy fields or extent of radiation therapy sequelae and extent of COVID-19 lung lesions. Twenty-eight of these 59 patients (47%) were hospitalized and 6 (10%) were transferred to an intensive care unit. At the time of analysis, 45/59 (76%) patients were recovering or had been cured, 10/59 (17%) were still followed and 4/59 (7%) had died from COVID-19. All 4 patients who died had significant non-cancer comorbidities. In univariate analysis, hypertension and age (>70) were the two factors associated with a higher risk of intensive care unit admission and/or death.\n\nConclusionsThis prospective registry analysis suggests that the COVID-19 mortality rate in breast cancer patients depends more on comorbidities than prior radiation therapy or current anti-cancer treatment. Special attention must be paid to comorbidities when estimating the risk of severe COVID-19 in breast cancer patients.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Emma MW Mohamad", - "author_inst": "UNIVERSITI KEBANGSAAN MALAYSIA" + "author_name": "Perrine Vuagnat", + "author_inst": "Institut Curie" }, { - "author_name": "Arina Anis Azlan", - "author_inst": "Universiti Kebangsaan Malaysia" + "author_name": "Maxime Frelaut", + "author_inst": "Institut Curie" }, { - "author_name": "Mohammad Rezal Hamzah", - "author_inst": "Universiti Malaysia Perlis" + "author_name": "Toulsie Ramtohul", + "author_inst": "Institut Curie" }, { - "author_name": "Jen Sern Tham", - "author_inst": "Universiti Putra Malaysia" + "author_name": "Clemence Basse", + "author_inst": "Institut Curie" + }, + { + "author_name": "Sarah Diakite", + "author_inst": "Institut Curie" + }, + { + "author_name": "Aurelien Noret", + "author_inst": "Institut Curie" + }, + { + "author_name": "Audrey Bellesoeur", + "author_inst": "Institut Curie" + }, + { + "author_name": "Vincent Servois", + "author_inst": "Institut Curie" }, { - "author_name": "Suffian Hadi Ayub", - "author_inst": "Sunway University Malaysia" + "author_name": "Delphine Hequet", + "author_inst": "Institut Curie" + }, + { + "author_name": "Enora Laas", + "author_inst": "Institut Curie" + }, + { + "author_name": "Youlia Kirova", + "author_inst": "Institut Curie" + }, + { + "author_name": "Luc Cabel", + "author_inst": "Institut Curie" + }, + { + "author_name": "Jean-Yves Pierga", + "author_inst": "Institut Curie" + }, + { + "author_name": "Institut Curie Breast Cancer and COVID Group", + "author_inst": "" + }, + { + "author_name": "Laurence Bozec", + "author_inst": "Institut Curie" + }, + { + "author_name": "Xavier Paoletti", + "author_inst": "INSERM U900" + }, + { + "author_name": "Paul Cottu", + "author_inst": "Institut Curie" + }, + { + "author_name": "Francois-Clement Bidard", + "author_inst": "Institut Curie" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "oncology" }, { "rel_doi": "10.1101/2020.04.29.20085472", @@ -1510956,61 +1511721,65 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.30.20086652", - "rel_title": "Perspectives of Cancer Patients and Their Health during the COVID-19 Pandemic", + "rel_doi": "10.1101/2020.04.30.20085316", + "rel_title": "Worldwide Effectiveness of Various Non-Pharmaceutical Intervention Control Strategies on the Global COVID-19 Pandemic: A Linearised Control Model", "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20086652", - "rel_abs": "IntroductionThe immunosuppressive nature of some cancers and many cancer-directed treatments may increase the risk of infection with and severe sequelae from Coronavirus Disease 2019 (COVID-19). The objective of this study was to compare concerns about COVID-19 among individuals undergoing cancer treatment to those with a history of cancer not currently receiving therapy and to those without a cancer history.\n\nMethodsWe conducted a cross-sectional anonymous online survey study of adults currently residing in the United States. Participants were recruited over a one-week period (April 3-11, 2020) using promoted advertisements on Facebook and Twitter. Groups were compared using chi-squared tests, Fishers exact tests, and t-tests.\n\nResults543 respondents from 47 states provided information on their cancer history and were included in analyses. Participants receiving active treatment reported greater concern about coronavirus infection (p<0.0001), higher levels of family distress caused by the COVID-19 pandemic (p=0.004), and greater concern that the general public does not adequately understand the seriousness of COVID-19 (p=0.04). Those with metastatic disease were more likely to indicate that COVID-19 had negatively affected their cancer care compared to patients with non-metastatic cancer (50.8% vs. 31.0%; p=0.02). The most commonly reported treatment modifications included chemotherapy delays.\n\nConclusionsPatients undergoing active treatment for cancer were most concerned about the short-term effects of the COVID-19 pandemic on the logistics as well as potential efficacy of ongoing cancer treatment, longer term effects, and overarching societal concerns that the population at large is not as concerned about the public health implications of the coronavirus.", - "rel_num_authors": 12, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20085316", + "rel_abs": "BackgroundCOVID-19 is a virus which has lead to a global pandemic. Worldwide, more than 130 countries have imposed severe restrictions, which form part of a set of non-pharmaceutical interventions (NPI)s. We aimed to quantify the country-specific effects of these NPIs and compare them using the Oxford COVID-19 Government Response Tracker (OxCGRT) stringency index, p, as a measure of NPI stringency.\n\nMethodsWe developed a dual latent/observable Susceptible Infected Recovered Deaths (SIRD) model and applied it on each of 22 countries and 25 states in the US using publicly available data. The observable model parameters were extracted using kernel functions. The regression of the transmission rate, {beta}, as a function of p in each locale was modeled through the intervention leverage, s, an initial transmission rate, {beta}0 and a typical adjustment time, [Formula].\n\nResultsThe world average for the intervention leverage, s = 0.01 (95% CI 0.0102 - 0.0112) had an ensemble standard deviation of 0.0017 (95% C.I. 0.0014 - 0.0021), strongly indicating a universal behavior.\n\nDiscussionOur study indicates that removing NPIs too swiftly will result in the resurgence of the spread within one to two months, in alignment with the current WHO recommendations. Moreover, we have quantified and are able to predict the effect of various combinations of NPIs. There is a minimum NPI level, below which leads to resurgence of the outbreak (in the absence of pharmaceutical and clinical advances). For the epidemic to remain sub-critical, the rate with which the intervention leverage s increases should outpace that of the relaxation of NPIs.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Emil Lou", - "author_inst": "University of Minnesota" + "author_name": "Jacques Naude", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "Deanna Teoh", - "author_inst": "University of Minnesota" + "author_name": "Bruce Mellado", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "Katherine Brown", - "author_inst": "University of Minnesota" + "author_name": "Joshua Choma", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "Anne Blaes", - "author_inst": "University of Minnesota" + "author_name": "Fabio Correa", + "author_inst": "Rhodes University" }, { - "author_name": "Shernan G. Holtan", - "author_inst": "University of Minnesota" + "author_name": "Salah Dahbi", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "Patricia Jewett", - "author_inst": "University of Minnesota" + "author_name": "Barry Dwolatzky", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "Helen Parsons", - "author_inst": "University of Minnesota" + "author_name": "Leslie Dwolatzky", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "E. Waruiru Mburu", - "author_inst": "University of Minnesota" + "author_name": "Kentaro Hayasi", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "Lauren Thomaier", - "author_inst": "University of Minnesota" + "author_name": "Benjamin Lieberman", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "Jane Yuet Ching Hui", - "author_inst": "University of Minnesota" + "author_name": "Caroline Maslo", + "author_inst": "Netcare" }, { - "author_name": "Heather H. Nelson", - "author_inst": "University of Minnesota" + "author_name": "Kgomotso Monnakgotla", + "author_inst": "University of the Witwatersrand" }, { - "author_name": "Rachel I. Vogel", - "author_inst": "University of Minnesota" + "author_name": "Xifeng Ruan", + "author_inst": "University of the Witwatersrand" + }, + { + "author_name": "Finn Stevenson", + "author_inst": "University of the Witwatersrand" } ], "version": "1", @@ -1512210,85 +1512979,185 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.30.20082172", - "rel_title": "Monitoring social distancing and SARS-CoV-2 transmission in Brazil using cell phone mobility data", + "rel_doi": "10.1101/2020.04.29.20082099", + "rel_title": "Rapid development of COVID-19 rapid diagnostics for low resource settings: accelerating delivery through transparency, responsiveness, and open collaboration", "rel_date": "2020-05-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.30.20082172", - "rel_abs": "Social distancing measures have emerged as the predominant intervention for containing the spread of COVID-19, but evaluating adherence and effectiveness remains a challenge. We assessed the relationship between aggregated mobility data collected from mobile phone users and the time-dependent reproduction number R(t), using severe acute respiratory illness (SARI) cases reported by Sao Paulo and Rio de Janeiro. We found that the proportion of individuals staying home all day (isolation index) had a strong inverse correlation with R(t) (rho<-0.7) and was predictive of COVID-19 transmissibility (p<0.0001). Furthermore, indexs of 46.7% had the highest accuracy (93.9%) to predict R(t) below one. This metric can be monitored in real time to assess adherence to social distancing measures and predict their effectiveness for controlling SARS-CoV-2 transmission.\n\nOne Sentence SummaryMobility data to monitoring social distancing in the COVID-19 outbreak", - "rel_num_authors": 18, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20082099", + "rel_abs": "Here we describe an open and transparent consortium for the rapid development of COVID-19 rapid diagnostics tests. We report diagnostic accuracy data on the Mologic manufactured IgG COVID-19 ELISA on known positive serum samples and on a panel of known negative respiratory and viral serum samples pre-December 2019.\n\nIn January, Mologic, embarked on a product development pathway for COVID-19 diagnostics focusing on ELISA and rapid diagnostic tests (RDTs), with anticipated funding from Wellcome Trust and DFID.\n\n834 clinical samples from known COVID-19 patients and hospital negative controls were tested on Mologics IgG ELISA. The reported sensitivity on 270 clinical samples from 124 prospectively enrolled patients was 94% (95% CI: 89.60% - 96.81%) on day 10 or more post laboratory diagnosis, and 96% (95% CI: 84.85% - 99.46%) between 14-21 days post symptom onset. A specificity panel comprising 564 samples collected pre-December 2019 were tested to include most common respiratory pathogens, other types of coronavirus, and flaviviruses. Specificity in this panel was 97% (95% CI: 95.65% - 98.50%).\n\nThis is the first in a series of Mologic products for COVID-19, which will be deployed for COVID-19 diagnosis, contact tracing and sero-epidemiological studies to estimate disease burden and transmission with a focus on ensuring access, affordability, and availability to low-resource settings.", + "rel_num_authors": 43, "rel_authors": [ { - "author_name": "Silvano B de Oliveira", - "author_inst": "National Immunization Program, Department of Immunization and Communicable Diseases, Secretariat of Health Surveillance, Ministry of Health, Brazil" + "author_name": "Emily R Adams", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Victor Bertollo Gomes Porto", - "author_inst": "National Immunization Program, Department of Immunization and Communicable Diseases, Secretariat of Health Surveillance, Ministry of Health, Brazil." + "author_name": "Yolanda Augustin", + "author_inst": "St Georges University of London" }, { - "author_name": "Fabiana Ganem", - "author_inst": "National Immunization Program, Department of Immunization and Communicable Diseases, Secretariat of Health Surveillance, Ministry of Health, Brazil." + "author_name": "Rachel L Byrne", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Fabio Macedo Mendes", - "author_inst": "University of Brasilia, Brazil" + "author_name": "David J Clark", + "author_inst": "St Georges University of London" }, { - "author_name": "Maria Almiron", - "author_inst": "Panamerican Health Organization, Brazil" + "author_name": "Michael Cocozza", + "author_inst": "Mologic" }, { - "author_name": "Wanderson Kleber de Oliveira", - "author_inst": "Secretariat of Health Surveillance, Ministry of Health, Brazil." + "author_name": "Ana I Cubas-Atienzar", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Francieli Fontana Sutile Tardetti Fantinato", - "author_inst": "National Immunization Program, Department of Immunization and Communicable Diseases, Secretariat of Health Surveillance, Ministry of Health, Brazil." + "author_name": "Luis E Cuevas", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Walquiria Aparecida Ferreira de Almeida", - "author_inst": "National Immunization Program, Department of Immunization and Communicable Diseases, Secretariat of Health Surveillance, Ministry of Health, Brazil." + "author_name": "Martina Cusinato", + "author_inst": "St Georges University of London" }, { - "author_name": "Abel Pereira de Macedo Borges", - "author_inst": "InLoco company" + "author_name": "Benedict M. O. Davies", + "author_inst": "St Georges University of London" }, { - "author_name": "Hector Natan Batista Pinheiro", - "author_inst": "Inloco company" + "author_name": "Mark Davies", + "author_inst": "Mologic" }, { - "author_name": "Raiza dos Santos Oliveira", - "author_inst": "Inloco company" + "author_name": "Paul Davies", + "author_inst": "Mologic" }, { - "author_name": "Jason R Andrews", - "author_inst": "Division of Infectious Diseases and Geographic Medicine, Stanford University School of Medicine, USA." + "author_name": "Annelyse Duvoix", + "author_inst": "Mologic" }, { - "author_name": "Nuno R. Faria", - "author_inst": "University of Oxford" + "author_name": "Nicholas M Eckersley", + "author_inst": "St Georges University of London" }, { - "author_name": "Marcelo Barreto Lopes", - "author_inst": "Arbor Research Collaborative for Health, USA." + "author_name": "Thomas Edwards", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Wildo Araujo", - "author_inst": "Universidade de Brasilia" + "author_name": "Thomas Fletcher", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Fredi A Diaz-Quijano", - "author_inst": "Universidade de Sao Paulo" + "author_name": "Alice j Fraser", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Helder I Nakaya", - "author_inst": "University of Sao Paulo" + "author_name": "Gala Garrod", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Julio Croda", - "author_inst": "Oswaldo Cruz Foundation" + "author_name": "Linda Hadcocks", + "author_inst": "St Georges University of London" + }, + { + "author_name": "QInxue Hu", + "author_inst": "St Georges University of London" + }, + { + "author_name": "Michael johnson", + "author_inst": "Mologic" + }, + { + "author_name": "Grant A Kay", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Katherin Keymer", + "author_inst": "Liverpool University Hospitals Foundation Trust" + }, + { + "author_name": "Daniela Kirwan", + "author_inst": "St Georges University of London" + }, + { + "author_name": "Kesja Klekotko", + "author_inst": "Mologic" + }, + { + "author_name": "Zawditu Lewis", + "author_inst": "Mologic" + }, + { + "author_name": "Jenifer Mason", + "author_inst": "Liverpool University Hospitals Foundation Trust" + }, + { + "author_name": "Josie Mensah-Kane", + "author_inst": "Mologic" + }, + { + "author_name": "Stefanie Menzies", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Irene Monahan", + "author_inst": "St Georges University of London" + }, + { + "author_name": "Catherine M Moore", + "author_inst": "St Georges University of London" + }, + { + "author_name": "Gerhard Nebe-von-Caron", + "author_inst": "Mologic" + }, + { + "author_name": "Sophie I Owen", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "Tim Planche", + "author_inst": "St Georges University of London" + }, + { + "author_name": "Chris Sainter", + "author_inst": "Mologic" + }, + { + "author_name": "James Schouten", + "author_inst": "Mologic" + }, + { + "author_name": "Henry M Staines", + "author_inst": "St Georges University of London" + }, + { + "author_name": "Lance Turtle", + "author_inst": "University of Liverpool" + }, + { + "author_name": "Chris Williams", + "author_inst": "Liverpool School of Tropical Medicine" + }, + { + "author_name": "John Wilkins", + "author_inst": "Mologic" + }, + { + "author_name": "Kevin Woolston", + "author_inst": "Mologic" + }, + { + "author_name": "Amadou A Sall", + "author_inst": "Institut Pasteur de Dakar" + }, + { + "author_name": "Joseph R.A. Fitchett", + "author_inst": "Mologic" + }, + { + "author_name": "Sanjeev Krishna", + "author_inst": "St Georges University of London" } ], "version": "1", @@ -1513800,133 +1514669,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.29.20084533", - "rel_title": "Pre-Existing Characteristics Associated with Covid-19 Illness Severity", - "rel_date": "2020-05-05", + "rel_doi": "10.1101/2020.04.28.20084053", + "rel_title": "Periodic COVID-19 Testing in Emergency Department Staff", + "rel_date": "2020-05-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20084533", - "rel_abs": "BackgroundCertain individuals, when infected by SARS-CoV-2, tend to develop the more severe forms of Covid-19 illness for reasons that remain unclear.\n\nMethodsWe studied N=442 patients who presented with laboratory confirmed Covid-19 illness to our U.S. metropolitan healthcare system. We curated data from the electronic health record, and used multivariable logistic regression to examine the association of pre-existing traits with a Covid-19 illness severity defined by level of required care: need for hospital admission, need for intensive care, and need for intubation.\n\nResultsOf all patients studied, 48% required hospitalization, 17% required intensive care, and 12% required intubation. In multivariable-adjusted analyses, patients requiring a higher levels of care were more likely to be older (OR 1.5 per 10 years, P<0.001), male (OR 2.0, P=0.001), African American (OR 2.1, P=0.011), obese (OR 2.0, P=0.021), with diabetes mellitus (OR 1.8, P=0.037), and with a higher comorbidity index (OR 1.8 per SD, P<0.001). Several clinical associations were more pronounced in younger compared to older patients (Pinteraction<0.05). Of all hospitalized patients, males required higher levels of care (OR 2.5, P=0.003) irrespective of age, race, or morbidity profile.\n\nConclusionsIn our healthcare system, greater Covid-19 illness severity is seen in patients who are older, male, African American, obese, with diabetes, and with greater overall comorbidity burden. Certain comorbidities paradoxically augment risk to a greater extent in younger patients. In hospitalized patients, male sex is the main determinant of needing more intensive care. Further investigation is needed to understand the mechanisms underlying these findings.", - "rel_num_authors": 29, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20084053", + "rel_abs": "BackgroundAs the number of COVID-19 cases in the US continues to rise and hospitals are experiencing personal protective equipment (PPE) shortages, healthcare workers have been disproportionately affected by COVID-19 infection. Since COVID-19 testing is now available, some have raised the question of whether we should be routinely testing asymptomatic healthcare workers.\n\nMethodsUsing publicly available data on COVID-19 infections and emergency department visits, as well as internal hospital staffing information, we generated a mathematical model to predict the impact of periodic COVID-19 testing in asymptomatic members of the emergency department staff in regions affected by COVID-19 infection. We calculated various transmission constants based on the Diamond Princess cruise ship data, used a logistic model to calculate new infections, and we created a Markov model according to average COVID-19 incubation time.\n\nResultsOur model predicts that after 30 days, with a transmission constant of 1.219e-4 new infections per person2, weekly COVID-19 testing of healthcare workers (HCW) would reduce new HCW and patient infections by 5.1% and bi-weekly testing would reduce both by 2.3%. At a transmission constant of 3.660e-4 new infections per person,2 weekly testing would reduce infections by 21.1% and bi-weekly testing would reduce infections by 9.7-9.8%. For a lower transmission constant of 4.067e-5 new infections per person2, weekly and biweekly HCW testing would result in a 1.54% and 0.7% reduction in infections respectively.\n\nConclusionPeriodic COVID-19 testing for emergency department staff in regions that are heavily-affected by COVID-19 and/or facing resource constraints may reduce COVID-19 transmission significantly among healthcare workers and previously-uninfected patients.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Joseph E. Ebinger", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Natalie Achamallah", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Hongwei Ji", - "author_inst": "Tongji University" - }, - { - "author_name": "Brian L. Claggett", - "author_inst": "Brigham and Womens Hospital" - }, - { - "author_name": "Nancy Sun", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Patrick Botting", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Trevor-Trung Nguyen", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Eric Luong", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Elizabeth H. Kim", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Eunice Park", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Yunxian Liu", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Ryan Rosenberry", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Yuri Matusov", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Steven Zhao", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Isabel Pedraza", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Tanzira Zaman", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Michael Thompson", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Koen Raedschelders", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Anders H. Berg", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Jonathan D. Grein", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Paul W. Noble", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Sumeet S. Chugh", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "C. Noel Bairey Merz", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Eduardo Marb\u00e1n", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Jennifer E. Van Eyk", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Scott D. Solomon", - "author_inst": "Brigham and Womens Hospital" - }, - { - "author_name": "Christine M. Albert", - "author_inst": "Cedars-Sinai Medical Center" - }, - { - "author_name": "Peter Chen", - "author_inst": "Cedars-Sinai Medical Center" + "author_name": "Yuemei Zhang", + "author_inst": "University of Washington" }, { - "author_name": "Susan Cheng", - "author_inst": "Cedars-Sinai Medical Center" + "author_name": "Sheng-Ru Cheng", + "author_inst": "University of Illinois at Urbana-Champaign" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1515822,57 +1516583,21 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.04.29.20084061", - "rel_title": "Psychological Stress and Gender Differences during COVID-19 Pandemic in Chinese Population", + "rel_doi": "10.1101/2020.04.28.20083329", + "rel_title": "Releasing the lockdown in the UK Covid-19 epidemic: a stochastic model", "rel_date": "2020-05-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.29.20084061", - "rel_abs": "About 83000 COVID-19 patients were confirmed in China up to May 2020. The effects of this public health crisis - and the varied efforts to contains its spread - have altered individuals \"normal\" daily functioning. This impact on social, psychological, and emotional well-being remain relatively unexplored, especially the ways in which Chinese men and women experience and respond to potential behavioral-related stressors. A cross-sectional study was conducted in late February 2020. Demographic characteristics and residential living conditions were measured along with psychological stress and behavior responses to the COVID-19 epidemic. 3088 questionnaires were received: 1749 females (56.6%) and 1339 males (43.4%). The mean level of stress, as measured by a visual analog scale, was 3.4 (SD=2.4) - but differed significantly by sex. Besides sex, factors positively associated with stress included: age ([≤]45 years), employment (unsteady income, unemployed), risk infection population (exposed to COVID-19, completed medical observation), difficulties encountered (diseases, work/study, financial, mental), behaviors(higher desire for COVID-19 knowledge, more time spent on the COVID-19). \"Protective\" factors included frequently contact with colleagues, calmness, and psychological resilience. Males and females also differed significantly in adapting to current living/working status, coping with heating, and psychological support service needs. Among Chinese, self-reported stress related to the COVID-19 epidemic were significantly related to sex, age, employment, resilience and coping styles. Future responses to such public health threats may wish to provide sex- and/or age-appropriate supports for psychological health and emotional well-being to those at greatest risk of experiencing stress.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20083329", + "rel_abs": "BackgroundIn a classic epidemic, the infected population has an early exponential phase, before slowing and fading to its peak. Mitigating interventions may change the exponent during the rising phase and a plateau can replace a peak. With interventions comes the risk that relaxation causes a second-wave. In the UK Covid-19 epidemic, infections cannot be counted, but their influence is seen in the curve of the mortality data. This work simulated social distancing and the lockdown in the UK Covid-19 epidemic to explore strategies for relaxation.\n\nMethodsCumulative mortality data was transposed 20 days earlier to identify three doubling periods separated by the 17th March--social distancing, and 23rd March--lockdown. A set of stochastic processes simulated viral transmission between interacting individuals using Covid-19 incubation and illness durations. Social distancing and restrictions on interactions were imposed and later relaxed.\n\nPrincipal FindingsDaily mortality data, consistent with that seen in the UK Covid-19 epidemic to 24th April 2020 was simulated. This output predicts that under a lockdown maintained till early July 2020, UK deaths will exceed 31,000, but leave a large susceptible population and a requirement for vaccination or quarantine. An earlier staged relaxation carries a risk of a second-wave. The model allows exploration of strategies for lifting the lockdown.\n\nInterpretationSocial distancing and the lockdown have had an impressive impact on the UK Covid-19 epidemic and saved lives, caution is now needed in planning its relaxation.\n\nFundingUnfunded research.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe classical Susceptible, Infected, Recovered, (SIR) epidemiological model with additional compartments and sophistications have been widely used to make forecasts in the Covid-19 pandemic but are not easily accessible.\n\nAdded value of this studyThis study adds reassurance that the interventions of social distancing introduced on the 17th March and the lockdown of the 23rd March 2020 have reduced mortality. The risks of a second-wave on their relaxation are real and illustrated graphically.\n\nImplications of all the available evidenceTogether with other models, credence is given to the risks of a second-wave in the UK Covid-19 epidemic on the relaxation of restrictions.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Kangxing Song", - "author_inst": "Department of Cardiology, the First Medical Center, Chinese PLA General Hospital" - }, - { - "author_name": "Rui Xu", - "author_inst": "Institute of Clinical Basic Medicine, China Academy of Chinese Medical Sciences" - }, - { - "author_name": "Terry D. Stratton", - "author_inst": "Department of Behavioral Science, College of Medicine, University of Kentucky" - }, - { - "author_name": "Voyko Kavcic", - "author_inst": "Institute of Gerontology, Wayne State University" - }, - { - "author_name": "Dan Luo", - "author_inst": "School of Public Health, Central South University" - }, - { - "author_name": "Fengsu Hou", - "author_inst": "Shenzhen Kangning Hospital" - }, - { - "author_name": "Fengying Bi", - "author_inst": "School of Public Health, Central South University" - }, - { - "author_name": "Rong Jiao", - "author_inst": "The First Clinical College, Hainan Meidical University" - }, - { - "author_name": "Shiyan Yan", - "author_inst": "Institute of Clinical Basic Medicine, China Academy of Chinese Medical Sciences" - }, - { - "author_name": "Yang Jiang", - "author_inst": "Department of Behavioral Science, College of Medicine" + "author_name": "Anthony D Lander", + "author_inst": "Birmingham Women's and Children's Hospital" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1517488,43 +1518213,419 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.28.20083378", - "rel_title": "Ocular toxicity and Hydroxychloroquine: A Rapid Meta-Analysis", + "rel_doi": "10.1101/2020.04.27.20081901", + "rel_title": "Enhanced Contact Investigations for Nine Early Travel-Related Cases of SARS-CoV-2 in the United States", "rel_date": "2020-05-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20083378", - "rel_abs": "Rapid access to evidence is crucial in times of evolving clinical crisis. To that end, we propose a novel mechanism to answer clinical queries: Rapid Meta-Analysis (RMA). Unlike traditional meta-analysis, RMA balances quick time-to-production with reasonable data quality assurances, leveraging Artificial Intelligence to strike this balance. This article presents an example RMA to a currently relevant clinical question: Is ocular toxicity and vision compromise a side effect with hydroxychloroquine therapy?\n\nAs of this writing, hydroxychloroquine is a leading candidate in the treatment of COVID-19. By combining AI with human analysis, our RMA identified 11 studies looking at ocular toxicity as a side effect and estimated the incidence to be 3.4% (95% CI: 1.11-9.96%). The heterogeneity across the individual study findings was high, and interpretation of the result should take this into account. Importantly, this RMA, from search to screen to analysis, took less than 30 minutes to produce.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20081901", + "rel_abs": "BackgroundCoronavirus disease 2019 (COVID-19), the respiratory disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first identified in Wuhan, China and has since become pandemic. As part of initial response activities in the United States, enhanced contact investigations were conducted to enable early identification and isolation of additional cases and to learn more about risk factors for transmission.\n\nMethodsClose contacts of nine early travel-related cases in the United States were identified. Close contacts meeting criteria for active monitoring were followed, and selected individuals were targeted for collection of additional exposure details and respiratory samples. Respiratory samples were tested for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (RT-PCR) at the Centers for Disease Control and Prevention.\n\nResultsThere were 404 close contacts who underwent active monitoring in the response jurisdictions; 338 had at least basic exposure data, of whom 159 had [≥]1 set of respiratory samples collected and tested. Across all known close contacts under monitoring, two additional cases were identified; both secondary cases were in spouses of travel-associated case patients. The secondary attack rate among household members, all of whom had [≥]1 respiratory sample tested, was 13% (95% CI: 4 - 38%).\n\nConclusionsThe enhanced contact tracing investigations undertaken around nine early travel-related cases of COVID-19 in the United States identified two cases of secondary transmission, both spouses. Rapid detection and isolation of the travel-associated case patients, enabled by public awareness of COVID-19 among travelers from China, may have mitigated transmission risk among close contacts of these cases.", + "rel_num_authors": 100, "rel_authors": [ { - "author_name": "Matthew Michelson", - "author_inst": "Evid Science, InferLink" + "author_name": "Rachel M Burke", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Sharon Balter", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Emily Barnes", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Vaughn Barry", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Karri Bartlett", + "author_inst": "Public Health Madison & Dane County, WI" + }, + { + "author_name": "Karlyn D Beer", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Isaac Benowitz", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Holly M Biggs", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Hollianne Bruce", + "author_inst": "Snohomish Health District, Everett, WA" + }, + { + "author_name": "Jonathan Bryant-Genevier", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Jordan Cates", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Kevin Chatham-Stephens", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Nora Chea", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Howard Chiou", + "author_inst": "Centers for Disease Control and Prevention, Los Angeles County Public Health Department, CA" + }, + { + "author_name": "Demian Christiansen", + "author_inst": "Cook County Department of Public Health, IL" + }, + { + "author_name": "Victoria Chu", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Shauna Clark", + "author_inst": "Public Health Seattle-King County, WA" + }, + { + "author_name": "Sara H. Cody", + "author_inst": "County of Santa Clara, Public Health Department" + }, + { + "author_name": "Max Cohen", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Erin E Conners", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Vishal Dasari", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Patrick Dawson", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Traci DeSalvo", + "author_inst": "Wisconsin Department of Health Services, WI" + }, + { + "author_name": "Matthew Donahue", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Alissa Dratch", + "author_inst": "Orange County Health Authority" + }, + { + "author_name": "Lindsey Duca", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Steven Minton", - "author_inst": "InferLink" + "author_name": "Jeffrey Duchin", + "author_inst": "Public Health Seattle-King County, WA" }, { - "author_name": "Tiffany Chow", - "author_inst": "Evid Science" + "author_name": "Jonathan W Dyal", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Neil Martin", - "author_inst": "Pacific Neuroscience Institute, Providence St John's Health Center" + "author_name": "Leora R Feldstein", + "author_inst": "Centers for Disease Control and Prevention" }, { - "author_name": "Mike Ross", - "author_inst": "Evid Science" + "author_name": "Marty Fenstersheib", + "author_inst": "San Benito County" }, { - "author_name": "Amelia Tee", - "author_inst": "Evid Science" + "author_name": "Marc Fischer", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Rebecca Fisher", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Chelsea Foo", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Brandi Freeman-Ponder", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Alicia M Fry", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Jessica Gant", + "author_inst": "Washington State Public Health Lab" + }, + { + "author_name": "Romesh Gautom", + "author_inst": "Washington State Department of Health" + }, + { + "author_name": "Isaac Ghinai", + "author_inst": "Centers for Disease Control and Prevention, Chicago Department of Public Health" + }, + { + "author_name": "Prabhu Gounder", + "author_inst": "County of Los Angeles Public Health" + }, + { + "author_name": "Cheri T Grigg", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Jeffrey Gunzenhauser", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Aron J Hall", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "George S Han", + "author_inst": "County of Santa Clara Public Health Department" + }, + { + "author_name": "Thomas Haupt", + "author_inst": "Wisconsin Department of Health Services" + }, + { + "author_name": "Michelle Holshue", + "author_inst": "Centers for Disease Control and Prevention, Washington State Department of Health" + }, + { + "author_name": "Jennifer Hunter", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Mireille B Ibrahim", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Max W Jacobs", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "M. Claire Jarashow", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Kiran Joshi", + "author_inst": "Cook County Department of Public Health, IL" + }, + { + "author_name": "Talar Kamali", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Vance Kawakami", + "author_inst": "Public Health Seattle-King County, WA" + }, + { + "author_name": "Moon Kim", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Hannah Kirking", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Amanda Kita-Yarbro", + "author_inst": "Public Health Madison & Dane County, WI" + }, + { + "author_name": "Rachel Klos", + "author_inst": "Wisconsin Division of Public Health" + }, + { + "author_name": "Miwako Kobayashi", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Anna Kocharian", + "author_inst": "Wisconsin Department of Health Services" + }, + { + "author_name": "Misty Lang", + "author_inst": "Washington State Public Health Lab" + }, + { + "author_name": "Jennifer Layden", + "author_inst": "Chicago Department of Public Health, IL" + }, + { + "author_name": "Eva Leidman", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Scott Lindquist", + "author_inst": "Washington State Department of Health" + }, + { + "author_name": "Stephen Lindstrom", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Ruth Link-Gelles", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Mariel Marlow", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Claire P Mattison", + "author_inst": "Centers for Disease Control and Prevention, Oak Ridge Institute for Science and Education" + }, + { + "author_name": "Nancy McClung", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Tristan McPherson", + "author_inst": "Centers for Disease Control and Prevention, Chicago Department of Public Health, IL" + }, + { + "author_name": "Lynn Mello", + "author_inst": "San Benito County Public Health Services, CA" + }, + { + "author_name": "Claire M Midgley", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Shannon Novosad", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Megan T Patel", + "author_inst": "Illinois Department of Public Health, IL" + }, + { + "author_name": "Kristen Pettrone", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Satish K Pillai", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Ian W Pray", + "author_inst": "Wisconsin Department of Health Services, Centers for Disease Control and Prevention" + }, + { + "author_name": "Heather E Reese", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Heather Rhodes", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Susan Robinson", + "author_inst": "Arizona Department of Health Services" + }, + { + "author_name": "Melissa Rolfes", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Janell Routh", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Rachel Rubin", + "author_inst": "Cook County Department of Public Health, IL" + }, + { + "author_name": "Sarah L Rudman", + "author_inst": "County of Santa Clara Public Health Department, CA" + }, + { + "author_name": "Denny Russell", + "author_inst": "Washington State Public Health Lab" + }, + { + "author_name": "Sarah Scott", + "author_inst": "Centers for Disease Control and Prevention, Maricopa County Department of Public Health, AZ" + }, + { + "author_name": "Varun Shetty", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Sarah E Smith-Jeffcoat", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Elizabeth A Soda", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Chris Spitters", + "author_inst": "Snohomish Health District, WA" + }, + { + "author_name": "Bryan Stierman", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Rebecca Sunenshine", + "author_inst": "Centers for Disease Control and Prevention, Maricopa County Public Health, AZ" + }, + { + "author_name": "Dawn Terashita", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Elizabeth Traub", + "author_inst": "Los Angeles County Department of Public Health" + }, + { + "author_name": "Grace E Vahey", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Jennifer R Verani", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Megan Wallace", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Matthew Westercamp", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Jonathan Wortham", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Amy Xie", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Anna Yousaf", + "author_inst": "Centers for Disease Control and Prevention" + }, + { + "author_name": "Matthew Zahn", + "author_inst": "Orange County Health Authority, CA" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc0", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.27.20081620", @@ -1518918,43 +1520019,31 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2020.05.01.071050", - "rel_title": "CoV-Seq: SARS-CoV-2 Genome Analysis and Visualization", + "rel_doi": "10.1101/2020.05.01.073262", + "rel_title": "SARS-CoV-2 is well adapted for humans. What does this mean for re-emergence?", "rel_date": "2020-05-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.01.071050", - "rel_abs": "SummaryCOVID-19 has become a global pandemic not long after its inception in late 2019. SARS-CoV-2 genomes are being sequenced and shared on public repositories at a fast pace. To keep up with these updates, scientists need to frequently refresh and reclean datasets, which is ad hoc and labor-intensive. Further, scientists with limited bioinformatics or programming knowledge may find it difficult to analyze SARS-CoV-2 genomes. In order to address these challenges, we developed CoV-Seq, a webserver to enable simple and rapid analysis of SARS-CoV-2 genomes. Given a new sequence, CoV-Seq automatically predicts gene boundaries and identifies genetic variants, which are presented in an interactive genome visualizer and are downloadable for further analysis. A command-line interface is also available for high-throughput processing.\n\nAvailability and ImplementationCoV-Seq is implemented in Python and Javascript. The webserver is available at http://covseq.baidu.com/ and the source code is available from https://github.com/boxiangliu/covseq.\n\nContactjollier.liu@gmail.com\n\nSupplementary informationSupplementary information are available at bioRxiv online.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.01.073262", + "rel_abs": "In a side-by-side comparison of evolutionary dynamics between the 2019/2020 SARS-CoV-2 and the 2003 SARS-CoV, we were surprised to find that SARS-CoV-2 resembles SARS-CoV in the late phase of the 2003 epidemic after SARS-CoV had developed several advantageous adaptations for human transmission. Our observations suggest that by the time SARS-CoV-2 was first detected in late 2019, it was already pre-adapted to human transmission to an extent similar to late epidemic SARS-CoV. However, no precursors or branches of evolution stemming from a less human-adapted SARS-CoV-2-like virus have been detected. The sudden appearance of a highly infectious SARS-CoV-2 presents a major cause for concern that should motivate stronger international efforts to identify the source and prevent near future re-emergence. Any existing pools of SARS-CoV-2 progenitors would be particularly dangerous if similarly well adapted for human transmission. To look for clues regarding intermediate hosts, we analyze recent key findings relating to how SARS-CoV-2 could have evolved and adapted for human transmission, and examine the environmental samples from the Wuhan Huanan seafood market. Importantly, the market samples are genetically identical to human SARS-CoV-2 isolates and were therefore most likely from human sources. We conclude by describing and advocating for measured and effective approaches implemented in the 2002-2004 SARS outbreaks to identify lingering population(s) of progenitor virus.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Boxiang Liu", - "author_inst": "Baidu Research USA, Sunnyvale, California, 94089, USA" - }, - { - "author_name": "Kaibo Liu", - "author_inst": "Baidu Research USA, Sunnyvale, California, 94089, USA" - }, - { - "author_name": "He Zhang", - "author_inst": "Baidu Research USA, Sunnyvale, California, 94089, USA" - }, - { - "author_name": "Liang Zhang", - "author_inst": "School of Electrical Engineering & Computer Science, Oregon State University, Corvallis, OR 97330, USA" + "author_name": "Shing Hei Zhan", + "author_inst": "University of British Columbia" }, { - "author_name": "Yuchen Bian", - "author_inst": "Baidu Research USA, Sunnyvale, California, 94089, USA" + "author_name": "Benjamin E Deverman", + "author_inst": "Broad Institute of MIT and Harvard" }, { - "author_name": "Liang Huang", - "author_inst": "School of Electrical Engineering & Computer Science, Oregon State University, Corvallis, OR 97330, USA" + "author_name": "Yulia Alina Chan", + "author_inst": "Broad Institute of MIT & Harvard" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "new results", - "category": "bioinformatics" + "category": "evolutionary biology" }, { "rel_doi": "10.1101/2020.04.28.20082669", @@ -1520496,191 +1521585,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.27.20080309", - "rel_title": "Serial measurements in COVID-19-induced acute respiratory disease to unravel heterogeneity of the disease course: design of the Maastricht Intensive Care COVID cohort; MaastrICCht", + "rel_doi": "10.1101/2020.04.26.20080317", + "rel_title": "Fast and easy disinfection of coronavirus-contaminated face masks using ozone gas produced by a dielectric barrier discharge plasma generator", "rel_date": "2020-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20080309", - "rel_abs": "BackgroundThe course of the disease in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection in mechanically ventilated patients is unknown. To unravel the clinical heterogeneity of the SARS-CoV-2 infection in these patients, we designed the prospective observational Maastricht Intensive Care COVID cohort; MaastrICCht. We incorporated serial measurements that harbour aetiological, diagnostic and predictive information. The study aims to investigate the heterogeneity of the natural course of critically ill patients with SARS-CoV-2 infection.\n\nStudy populationMechanically ventilated patients admitted to the Intensive Care with SARS- CoV-2 infection.\n\nMain messageWe will collect clinical variables, vital parameters, laboratory variables, mechanical ventilator settings, chest electrical impedance tomography, electrocardiograms, echocardiography as well as other imaging modalities to assess heterogeneity of the natural course of SARS-CoV-2 infection in critically ill patients. The MaastrICCht cohort is, also designed to foster various other studies and registries and intends to create an open-source database for investigators. Therefore, a major part of the data collection is aligned with an existing national Intensive Care data registry and two international COVID-19 data collection initiatives. Additionally, we create a flexible design, so that additional measures can be added during the ongoing study based on new knowledge obtained from the rapidly growing body of evidence.\n\nConclusionThe spread of the COVID-19 pandemic requires the swift implementation of observational research to unravel heterogeneity of the natural course of the disease of SARS- CoV-2 infection in mechanically ventilated patients. Our design is expected to enhance aetiological, diagnostic and prognostic understanding of the disease. This paper describes the design of the MaastrICCht cohort.\n\nStrengths and limitations of this studyO_LISerial measurements that characterize the disease course of SARS-CoV-2 infection in mechanically ventilated patients\nC_LIO_LIData collection and analysis according to a predefined protocol\nC_LIO_LIFlexible, evolving design enabling the study of multiple aspects of SARS-CoV-2 infection in mechanically ventilated patients\nC_LIO_LISingle centre, including only ICU patients\nC_LI", - "rel_num_authors": 43, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20080317", + "rel_abs": "Face masks are one of the currently available options for preventing the transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has caused the 2019 pandemic. However, with the increasing demand for protection, face masks are becoming limited in stock, and the concerned individuals and healthcare workers from many countries are now facing the issue of the reuse of potentially contaminated masks. Although various technologies already exist for the sterilization of medical equipment, most of them are not applicable for eliminating virus from face masks. Thus, there is an urgent need to develop a fast and easy method of disinfecting contaminated face masks. In this study, using a human coronavirus (HCoV-229E) as a surrogate for SARS-CoV-2 contamination on face masks, we show that the virus loses its infectivity to a human cell line (MRC-5) when exposed for a short period of time (1 min) to ozone gas produced by a dielectric barrier discharge plasma generator. Scanning electron microscopy and particulate filtration efficiency (PFE) tests revealed that there was no structural or functional deterioration observed in the face masks even after they underwent excessive exposure to ozone (five 1-minute exposures). Interestingly, for face masks exposed to ozone gas for 5 min, the amplification of HCoV-229E RNA by reverse transcription polymerase chain reaction suggested a loss of infectivity under the effect of ozone, primarily owing to the damage caused to viral envelopes or envelope proteins. Ozone gas is a strong oxidizing agent with the ability to kill viruses on hard-to-reach surfaces, including the fabric structure of face masks. These results suggest that it may be possible to rapidly disinfect contaminated face masks using a plasma generator in a well-ventilated place.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Jeanette Tas", - "author_inst": "MUMC" - }, - { - "author_name": "Rob J.J. van Gassel", - "author_inst": "MUMC" - }, - { - "author_name": "Serge J.H. heines", - "author_inst": "MUMC" - }, - { - "author_name": "Mark M.G. Mulder", - "author_inst": "MUMC" - }, - { - "author_name": "Nanon F.L. heijnen", - "author_inst": "MUMC" - }, - { - "author_name": "Melanie J Acampo - de Jong", - "author_inst": "MUMC" - }, - { - "author_name": "Julia L.M. Bels", - "author_inst": "MUMC" - }, - { - "author_name": "Frank C Bennis", - "author_inst": "MUMC" - }, - { - "author_name": "Marcel Koelmann", - "author_inst": "MUMC" - }, - { - "author_name": "Rald V.M. Groven", - "author_inst": "MUMC" - }, - { - "author_name": "Moniek A Donkers", - "author_inst": "MUMC" - }, - { - "author_name": "Frank van Rosmalen", - "author_inst": "MUMC" - }, - { - "author_name": "Ben J.M. Hermans", - "author_inst": "MUMC" - }, - { - "author_name": "- Maastricht Intensive Care COVID Study Group", - "author_inst": "" - }, - { - "author_name": "Steven J.R. Meex", - "author_inst": "MUMC" - }, - { - "author_name": "Alma M.A. Mingels", - "author_inst": "MUMC" - }, - { - "author_name": "Otto Bekers", - "author_inst": "MUMC" - }, - { - "author_name": "Paul H.M. Savelkoul", - "author_inst": "MUMC" - }, - { - "author_name": "Astrid M.L Oude Lashof", - "author_inst": "MUMC" - }, - { - "author_name": "Joachim E Wildberger", - "author_inst": "MUMC" - }, - { - "author_name": "Fabian H Tijssen", - "author_inst": "MUMC" - }, - { - "author_name": "Wolfgang F.F.A. Buhre", - "author_inst": "MUMC" - }, - { - "author_name": "Jan-Willem E.M. Sels", - "author_inst": "MUMC" - }, - { - "author_name": "Chahinda Ghossein-Doha", - "author_inst": "MUMC" - }, - { - "author_name": "Rob G.H. Driessen", - "author_inst": "MUMC" - }, - { - "author_name": "Pieter L Kubben", - "author_inst": "MUMC" - }, - { - "author_name": "Marcus L.F. Janssen", - "author_inst": "MUMC" - }, - { - "author_name": "Gerry A.F. Nicolaes", - "author_inst": "MUMC" - }, - { - "author_name": "Uli Strauch", - "author_inst": "MUMC" - }, - { - "author_name": "Zafer Geyik", - "author_inst": "MUMC" - }, - { - "author_name": "Thijs S.R. Delnoij", - "author_inst": "MUMC" - }, - { - "author_name": "Kim H.M. Walraven", - "author_inst": "MUMC" - }, - { - "author_name": "Coen D.A. Stehouwer", - "author_inst": "MUMC" - }, - { - "author_name": "Jeanine A.M.C.F. Verbunt", - "author_inst": "MUMC" - }, - { - "author_name": "Walther N.K.A. van Mook", - "author_inst": "MUMC" - }, - { - "author_name": "Susanne van Santen", - "author_inst": "MUMC" + "author_name": "Jinyeop Lee", + "author_inst": "Sungkyunkwan University" }, { - "author_name": "Ronny M. Schnabel", - "author_inst": "MUMC" + "author_name": "Cheolwoo Bong", + "author_inst": "Sungkyunkwan University" }, { - "author_name": "Marcel J.H. Aries", - "author_inst": "MUMC" + "author_name": "Pan K. Bae", + "author_inst": "Korea Research Institute of Bioscience and Biotechnology" }, { - "author_name": "Marcel C.G. van de Poll", - "author_inst": "MUMC" + "author_name": "Abdurhaman T. Abafog", + "author_inst": "Sungkyunkwan University" }, { - "author_name": "Dennis C.J.J. Bergmans", - "author_inst": "MUMC" + "author_name": "Seung Ho Baek", + "author_inst": "Sungkyunkwan University" }, { - "author_name": "Iwan C.C. van der Horst", - "author_inst": "MUMC" + "author_name": "Yong-Beom Shin", + "author_inst": "Korea Research Institute of Bioscience and Biotechnology" }, { - "author_name": "Sander M.J. van Kuijk", - "author_inst": "MUMC" + "author_name": "Moon S. Park", + "author_inst": "Sungkyunkwan University" }, { - "author_name": "Bas C.T. van Bussel", - "author_inst": "MUMC" + "author_name": "Sungsu Park", + "author_inst": "Sungkyunkwan University" } ], "version": "1", "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.04.26.20079988", @@ -1522010,35 +1522959,43 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.26.20080655", - "rel_title": "Preparedness and Mitigation by projecting the risk against COVID-19 transmission using Machine Learning Techniques", + "rel_doi": "10.1101/2020.04.27.20079962", + "rel_title": "Epidemic analysis of COVID-19 Outbreak and Counter-Measures in France", "rel_date": "2020-05-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20080655", - "rel_abs": "The outbreak of COVID-19 is first identified in China, which later spread to various parts of the globe and was pronounced pandemic by the World Health Organization (WHO). The disease of transmissible person-to-person pneumonia caused by the extreme acute respiratory coronavirus 2 syndrome (SARS-COV-2, also known as COVID-19), has sparked a global warning. Thermal screening, quarantining, and later lockdown were methods employed by various nations to contain the spread of the virus. Though exercising various possible plans to contain the spread help in mitigating the effect of COVID-19, projecting the rise and preparing to face the crisis would help in minimizing the effect. In the scenario, this study attempts to use Machine Learning tools to forecast the possible rise in the number of cases by considering the data of daily new cases. To capture the uncertainty, three different techniques: (i) Decision Tree algorithm, (ii) Support Vector Machine algorithm, and (iii) Gaussian process regression are used to project the data and capture the possible deviation. Based on the projection of new cases, recovered cases, deceased cases, medical facilities, population density, number of tests conducted, and facilities of services, are considered to define the criticality index (CI). CI is used to classify all the districts of the country in the regions of high risk, low risk, and moderate risk. An online dashpot is created, which updates the data on daily bases for the next four weeks. The prospective suggestions of this study would aid in planning the strategies to apply the lockdown/ any other plan for any country, which can take other parameters to define the CI.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.27.20079962", + "rel_abs": "The COVID-19 pandemic has triggered world-wide attention among data scientists and epidemiologists to analyze and predict the outcomes, by using previous statistical epidemic models. We propose to use a variant of the well known SEIR model to analyze the spread of COVID-19 in France, by taking in to account the national lockdown declared in March 11, 2020. Particle Swarm Optimisation (PSO) is used to find optimal parameters for the model in the case of France. We propose to fit the model based only on the number of daily fatalities, where an R2 score based error metric is used. As the official number of confirmed cases is not reliable due to the lack of widespread testing, especially in the first phases of the outbreak, we show that basing the model optimisation on the number of fatalities can provide legitimate results.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Akshay Kumar", - "author_inst": "Birla Institute of Technology and Science, Pilani Campus, Rajasthan, 333031, India" + "author_name": "Eren Unlu", + "author_inst": "Datategy" }, { - "author_name": "Farhan Mohammad Khan", - "author_inst": "Birla Institute of Technology and Science, Pilani Campus, Rajasthan, 333031, India" + "author_name": "Hippolyte Leger", + "author_inst": "Datategy" }, { - "author_name": "Rajiv Gupta", - "author_inst": "Birla Institute of Technology and Science, Pilani Campus, Rajasthan, 333031, India" + "author_name": "Oleksandr Motornyi", + "author_inst": "Datategy" }, { - "author_name": "Harish Puppala", - "author_inst": "BML Munjal University" + "author_name": "Alia Rukubayihunga", + "author_inst": "Datategy" + }, + { + "author_name": "Thibaud Ishacian", + "author_inst": "Datategy" + }, + { + "author_name": "Mehdi Chouiten", + "author_inst": "Datategy" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.26.20080218", @@ -1523412,37 +1524369,41 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.05.01.071654", - "rel_title": "Mutational spectra of SARS-CoV-2 orf1ab polyprotein and Signature mutations in the United States of America", + "rel_doi": "10.1101/2020.05.01.071985", + "rel_title": "On spatial molecular arrangements of SARS-CoV2 genomes of Indian patients", "rel_date": "2020-05-01", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.01.071654", - "rel_abs": "Pandemic COVID-19 outbreak has been caused due to SARS-COV2 pathogen, resulting millions of infection and death worldwide, USA being on top at the present moment. The long, complex orf1ab polyproteins of SARS-COV2 play an important role in viral RNA synthesis. To assess the impact of mutations in this important domain, we analyzed 1134 complete protein sequences of orf1ab polyprotein from NCBI Virus database from affected patients across various states of USA from December 2019 to 25th April, 2020. Multiple sequence alignment using Clustal Omega followed by statistical significance was calculated. Four significant mutations T265I (nsp 2), P4715L (nsp 12) and P5828L and Y5865C (both at nsp 13) were identified in important non-structural proteins, which function either as replicase or helicase. A comparative analysis shows 265T>I, 5828P>L and 5865Y>C are unique to USA and not reported from Europe or Asia; while one, 4715P>L is predominant in both Europe and USA. Mutational changes in amino acids are predicted to alter structure and function of corresponding proteins, thereby it is imperative to consider the mutational spectra while designing new antiviral therapeutics targeting viral orf1ab.", - "rel_num_authors": 5, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.05.01.071985", + "rel_abs": "A pandemic caused by the SARS-CoV2 is being experienced by the whole world since December, 2019. A thorough understanding beyond just sequential similarities among the protein coding genes of SARS-CoV2 is important in order to differentiate or relate to the other known CoVs of the same genus. In this study, we compare three genomes namely MT012098 (India-Kerala), MT050493 (India-Kerala), MT358637 (India-Gujrat) from India with NC_045512 (China-Wuhan) to view the spatial as well as molecular arrangements of nucleotide bases of all the genes embedded in these four genomes. Based on different features extracted for each gene embedded in these genomes, corresponding phylogenetic relationships have been built up. Differences in phylogenetic tree arrangement with individual gene suggest that three genomes of Indian origin have come from three different origins or the evolution of viral genome is very fast process. This study would also help to understand the virulence factors, disease pathogenicity, origin and transmission of the SARS-CoV2.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Shuvam Banerjee", - "author_inst": "University of Calcutta" + "author_name": "Sk. Sarif Hassan", + "author_inst": "Pingla Thana Mahavidyalaya" }, { - "author_name": "Sohan Seal", - "author_inst": "Ramakrishna Mission Vidyamandira, Belur Math, Howrah" + "author_name": "Atanu Moitra", + "author_inst": "CMO, Government of West Bengal, India." }, { - "author_name": "Riju Dey", - "author_inst": "Ramakrishna Mission Vidyamandira, Belur Math, Howrah" + "author_name": "Ranjeet K Rout", + "author_inst": "National Institute of Technology Srinagar, Hazratbal-190006, J&K, India" }, { - "author_name": "Kousik kr. Mondal", - "author_inst": "University of Calcutta" + "author_name": "Pabitra Pal Choudhury", + "author_inst": "Applied Statistics Unit, Indian Statistical Institute, Kolkata 700108, West Bengal, India." }, { - "author_name": "Pritha Bhattacharjee", - "author_inst": "University of Calcutta" + "author_name": "Prasanta Pramanik", + "author_inst": "Finance Department, Government of West Bengal, India." + }, + { + "author_name": "Siddhartha Sankar Jana", + "author_inst": "School of Biological Sciences, Indian Association for the Cultivation of Science, West Bengal, 700032, India." } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by_nc_nd", "type": "new results", "category": "bioinformatics" }, @@ -1524738,73 +1525699,53 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.24.20077487", - "rel_title": "SUCCESSFUL MANUFACTURING OF CLINICAL-GRADE SARS-CoV-2 SPECIFIC T CELLS FOR ADOPTIVE CELL THERAPY", + "rel_doi": "10.1101/2020.04.24.20078741", + "rel_title": "Modelling of Systemic versus Pulmonary Chloroquine Exposure in Man for COVID-19 Dose Selection", "rel_date": "2020-04-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20077487", - "rel_abs": "BackgroundAdoptive therapy with SARS-CoV-2 specific T cells for COVID-19 has not been reported. The feasibility of rapid clinical-grade manufacturing of virus-specific T cells from convalescent donors has not been demonstrated for this or prior pandemics.\n\nMethodsOne unit of whole blood was collected from each convalescent donor following standard blood bank practices. After the plasma was separated and stored separately, the leukocytes were stimulated using overlapping peptides of SARS-CoV-2, covering the immunodominant sequence domains of the S protein and the complete sequence of the N and M proteins. Thereaftesr, functionally reactive cells were enriched overnight using an automated device capturing IFN{gamma}-secreting cells.\n\nFindingsFrom 1x109 leukocytes, 0.56 to 1.16x106 IFN{gamma}+ T cells were produced from each of the first two donors. Most of the T cells (64% to 71%) were IFN{gamma}+, with preferential enrichment of CD56+ T cells, effector memory T cells, and effector memory RA+ T cells. TCRV{beta} spectratyping revealed oligoclonal distribution, with over-representation of subfamilies including V{beta}3, V{beta}16 and V{beta}17. With just two donors, the probability that a recipient in the same ethnic group would share at least one donor HLA allele or one haplotype could be as high as >90% and >30%, respectively.\n\nInterpretationsThis study is limited by small number of donors and absence of recipient data; however, crucial first proof-of-principle data are provided demonstrating the feasibility of clinical-grade production of SARS-CoV-2 specific T cells for urgent clinical use, conceivably with plasma therapy concurrently. Our data showing that virus-specific T cells can be detected easily after brief stimulation with SARS-CoV-2 specific peptides suggest that a parallel diagnostic assay can be developed alongside serology testing.\n\nFundingThe study was funded by a SingHealth Duke-NUS Academic Medicine COVID-19 Rapid Response Research Grant.", - "rel_num_authors": 14, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078741", + "rel_abs": "Chloroquine has attracted intense attention as a potential clinical candidate for prevention and treatment of COVID-19 based on reports of in-vitro efficacy against SARS-CoV-2. While the pharmacokinetic-pharmacodynamic (PK-PD) relationship of chloroquine is well established for malaria, there is sparse information regarding its dose-effect relationship in the context of COVID-19.\n\nHere, we explore the PK-PD relationship of chloroquine for COVID-19 by modelling both achievable systemic and pulmonary drug concentrations. Our data indicate that the standard anti-malarial treatment dose of 25mg/kg over three days does not deliver sufficient systemic drug exposures for the inhibition of viral replication. In contrast, PK predictions of chloroquine in the lungs using in-vivo data or human physiologically-based PK models, suggest that doses as low as 3mg/kg/day for 3 days could deliver exposures that are significantly higher than reported antiviral-EC90s for up to a week. Moreover, if pulmonary exposure is a driver for prevention, simulations show that chronic daily dosing of chloroquine may be unnecessary for prophylaxis purposes. Instead, once weekly doses of 5mg/kg would be sufficient to achieve a continuous cover of therapeutically active pulmonary exposures.\n\nThese findings reveal a highly compartmentalised distribution of chloroquine in man that may significantly affect its therapeutic potential against COVID-19. The systemic circulation is shown as one site where chloroquine exposure is insufficient to inhibit SARS-CoV-2 replication. However, if therapeutic activity is driven by pulmonary exposure, it should be possible to reduce the chloroquine dose to safe levels. Carefully designed randomized controlled trials are urgently required to address these outstanding issues.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Wing Leung", - "author_inst": "KKH, SingHealth Duke-NUS" - }, - { - "author_name": "Teck Guan Soh", - "author_inst": "National University Hospital" - }, - { - "author_name": "Yeh Ching Linn", - "author_inst": "Singapore General Hospital" - }, - { - "author_name": "Jenny Guek-Hong Low", - "author_inst": "Singapore General Hospital" - }, - { - "author_name": "Jiashen Loh", - "author_inst": "Sengkang General Hospital" - }, - { - "author_name": "Marieta Chan", - "author_inst": "Health Sciences Authority" + "author_name": "Ghaith Aljayyoussi", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Wee Joo Chng", - "author_inst": "National University Hospital" + "author_name": "Rajith Rajoli", + "author_inst": "University of Liverpool" }, { - "author_name": "Liang Piu Koh", - "author_inst": "National University Hospital" + "author_name": "Henry Pertinez", + "author_inst": "University of Liverpool" }, { - "author_name": "Michelle Li-Mei Poon", - "author_inst": "National University Hospital" + "author_name": "Shaun Pennington", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "King Pan Ng", - "author_inst": "KKH" + "author_name": "W. David Hong", + "author_inst": "University of Liveprool" }, { - "author_name": "Chik Hong Kuick", - "author_inst": "KKH" + "author_name": "Paul O'Neill", + "author_inst": "University of Liverpool" }, { - "author_name": "Thuan Tong Tan", - "author_inst": "Singapore General Hospital" + "author_name": "Andrew Owen", + "author_inst": "University of Liverpool" }, { - "author_name": "Lip Kun Tan", - "author_inst": "National University Hospital" + "author_name": "Steve Ward", + "author_inst": "Liverpool School of Tropical Medicine" }, { - "author_name": "Michaela Su-fern Seng", - "author_inst": "KKH" + "author_name": "Giancarlo Biagini", + "author_inst": "Liverpool School of Tropical Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1526172,25 +1527113,33 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.28.20083873", - "rel_title": "Bayesian Inference of COVID-19 Spreading Rates in South Africa", + "rel_doi": "10.1101/2020.04.28.20083865", + "rel_title": "Fractional SIR Epidemiological Models", "rel_date": "2020-04-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20083873", - "rel_abs": "The Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has highlighted the need for the development of prompt mitigating responses under conditions of high uncertainty. Fundamental to the design of rapid state reactions is the ability to perform epidemiological model parameter inference for localised trajectory predictions. In this work, we perform Bayesian parameter inference using Markov Chain Monte Carlo (MCMC) methods on the Susceptible-Infected-Recovered (SIR) and Susceptible-Exposed-Infected-Recovered (SEIR) epidemiological models with time-varying spreading rates for South Africa. The results find two change points in the spreading rate of COVID-19 in South Africa as inferred from the confirmed cases. The first change point coincides with state enactment of a travel ban and the resultant containment of imported infections. The second change point coincides with the start of a state-led mass screening and testing programme which has highlighted community-level disease spread that was not well represented in the initial largely traveller based and private laboratory dominated testing data. The results further suggest that due to the likely effect of the national lockdown, community level transmissions are slower than the original imported case driven spread of the disease.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.28.20083865", + "rel_abs": "The purpose of this work is to make a case for epidemiological models with fractional exponent in the contribution of sub-populations to the transmission rate. More specifically, we question the standard assumption in the literature on epidemiological models, where the transmission rate dictating propagation of infections is taken to be proportional to the product between the infected and susceptible sub-populations; a model that relies on strong mixing between the two groups and widespread contact between members of the groups. We content, that contact between infected and susceptible individuals, especially during the early phases of an epidemic, takes place over a (possibly diffused) boundary between the respective sub-populations. As a result, the rate of transmission depends on the product of fractional powers instead. The intuition relies on the fact that infection grows in geographically concentrated cells, in contrast to the standard product model that relies on complete mixing of the susceptible to infected sub-populations. We validate the hypothesis of fractional exponents i) by numerical simulation for disease propagation in graphs imposing a local structure to allowed disease transmissions and ii) by fitting the model to a COVID-19 data set provided by John Hopkins University (JHUCSSE) for the period Jan-31-20 to Mar-24-20, for the countries of Italy, Germany, Iran, and France.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Rendani Mbuvha", - "author_inst": "University of Witwatersrand" + "author_name": "Amirhossein Taghvaei", + "author_inst": "University of California, Irvine" }, { - "author_name": "Tshilidzi Marwala", - "author_inst": "University of Johannesburg" + "author_name": "Tryphon T. Georgiou", + "author_inst": "University of California, Irvine" + }, + { + "author_name": "Larry Norton", + "author_inst": "Memorial Sloan Kettering Cancer Center" + }, + { + "author_name": "Allen R Tannenbaum", + "author_inst": "Stony Brook University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1527242,49 +1528191,25 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.04.25.20079830", - "rel_title": "FIRST DETECTION OF SARS-COV-2 IN UNTREATED WASTEWATERS IN ITALY", + "rel_doi": "10.1101/2020.04.25.20079848", + "rel_title": "Effects of latency and age structure on the dynamics and containment of COVID-19", "rel_date": "2020-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.25.20079830", - "rel_abs": "Several studies have demonstrated the advantages of environmental surveillance through the monitoring of sewer systems for the assessment of viruses circulating in a given community (wastewater-based epidemiology, WBE).\n\nDuring the COVID-19 public health emergency, many reports have described the presence of SARS-CoV-2 RNA in stools from COVID-19 patients, and a few studies reported the occurrence of SARS-CoV-2 in wastewaters worldwide. Italy is among the worlds worst-affected countries in the COVID-19 pandemic, but so far there are no studies assessing the presence of SARS-CoV-2 in Italian wastewaters. To this aim, twelve influent sewage samples, collected between February and April 2020 from Wastewater Treatment Plants in Milan and Rome, were tested adapting, for concentration, the standard WHO procedure for Poliovirus surveillance. Molecular analysis was undertaken with three nested protocols, including a newly designed SARS-CoV-2 specific primer set.\n\nSARS-CoV-2 RNA detection occurred in volumes of 250 mL of wastewaters collected in both areas at high (Milan) and low (Rome) epidemic circulation, according to clinical data. Overall, 6 out of 12 samples were positive. One of the positive results was obtained in a Milan wastewater sample collected a few days after the first notified Italian case of autochthonous SARS-CoV-2.\n\nThe study shows that WBE has the potential to be applied to SARS-CoV-2 as a sensitive tool to study spatial and temporal trends of virus circulation in the population.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.25.20079848", + "rel_abs": "In this paper we develop an SEIR-type model of COVID-19, with account for two particular aspects: non-exponential distribution of incubation and recovery periods, as well as age structure of the population. For the mean-field model, which does not distinguish between different age groups, we demonstrate that including a more realistic Gamma distribution of incubation and recovery periods may not have an effect on the total number of deaths and the overall size of an epidemic, but it has a major effect in terms of increasing the peak numbers of infected and critical care cases, as well as on changing the timescales of an epidemic, both in terms of time to reach the peak, and the overall duration of an outbreak. In order to obtain more accurate estimates of disease progression and investigate different strategies for introducing and lifting the lockdown, we have also considered an age-structured version of the model, which has allowed us to include more accurate data on age-specific rates of hospitalisation and COVID-19 related mortality. Applying this model to three comparable neighbouring regions in the UK has delivered some fascinating insights regarding the effect of quarantine in regions with different population structure. We have discovered that for a fixed quarantine duration, the timing of its start is very important in the sense that the second epidemic wave after lifting the quarantine can be significantly smaller or larger depending on the specific population structure. Also, the later the fixed-duration quarantine is introduced, the smaller is the resulting final number of deaths at the end of the outbreak. When the quarantine is introduced simultaneously for all regions, increasing quarantine duration postpones and slightly reduces the epidemic peak, though without noticeable differences in peak magnitude between different quarantine durations.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Giuseppina La Rosa", - "author_inst": "National Institute of Health" - }, - { - "author_name": "Marcello Iaconelli", - "author_inst": "National Institute of Health" - }, - { - "author_name": "Pamela Mancini", - "author_inst": "National Institute of Health" - }, - { - "author_name": "Giusy Bonanno Ferraro", - "author_inst": "National Institute of Health" - }, - { - "author_name": "Carolina Veneri", - "author_inst": "National Institute of Health" - }, - { - "author_name": "Lucia Bonadonna", - "author_inst": "National Institute of Health" - }, - { - "author_name": "Luca Lucentini", - "author_inst": "National Institute of Health" + "author_name": "Konstantin B Blyuss", + "author_inst": "University of Sussex" }, { - "author_name": "Elisabetta Suffredini", - "author_inst": "National Institute of Health" + "author_name": "Yuliya N Kyrychko", + "author_inst": "University of Sussex" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1528828,55 +1529753,71 @@ "category": "biophysics" }, { - "rel_doi": "10.1101/2020.04.29.068098", - "rel_title": "Mass spectrometry analysis of newly emerging coronavirus HCoV-19 spike S protein and human ACE2 reveals camouflaging glycans and unique post-translational modifications", + "rel_doi": "10.1101/2020.04.26.20080242", + "rel_title": "Systematic review of international guidelines for tracheostomy in COVID-19 patients.", "rel_date": "2020-04-29", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.29.068098", - "rel_abs": "The pneumonia-causing COVID-19 pandemia has prompt worldwide efforts to understand its biological and clinical traits of newly identified HCoV-19 virus. In this study, post-translational modification (PTM) of recombinant HCoV-19 S and hACE2 were characterized by LC-MSMS. We revealed that both proteins were highly decorated with specific proportions of N-glycan subtypes. Out of 21 possible glycosites in HCoV-19 S protein, 20 were confirmed completely occupied by N-glycans, with oligomannose glycans being the most abundant type. All 7 possible glycosylation sites in hACE2 were completely occupied mainly by complex type N-glycans. However, we showed that glycosylation did not directly contribute to the binding affinity between SARS-CoV spike protein and hACE2. Additionally, we also identified multiple sites methylated in both proteins, and multiple prolines in hACE2 were converted to hydroxylproline. Refined structural models were built by adding N-glycan and PTMs to recently published cryo-EM structure of the HCoV-19 S and hACE2 generated with glycosylation sites in the vicinity of binding surface. The PTM and glycan maps of both HCoV-19 S and hACE2 provide additional structural details to study mechanisms underlying host attachment, immune response mediated by S protein and hACE2, as well as knowledge to develop remedies and vaccines desperately needed nowadays.", - "rel_num_authors": 9, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.26.20080242", + "rel_abs": "At this moment, the world leaves under the SARS-CoV-2 outbreak pandemic. As Otolaryngologists - Head & Neck Surgeons, we need to perform and participate in examinations and procedures within the head and neck region and airway that are at particularly high risk of exposure and infection because of aerosol and droplet contamination. One of those surgical procedures on demand at this moment is tracheostomy, due the increasing admission in ICU departments and the increased need of ventilatory support secondary to respiratory distress syndrome. This review of international guidelines for tracheostomy in COVID-19 infected patients, aiming to summarize in a systematic way the available recommendations from 18 guidelines from all over the world.", + "rel_num_authors": 13, "rel_authors": [ { - "author_name": "Zeyu Sun", - "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Disease,The First Affiliated Hospital, Zhejiang University" + "author_name": "Carlos M Chiesa-Estomba", + "author_inst": "Hospital Universitario Donostia" }, { - "author_name": "Keyi Ren", - "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Disease,The First Affiliated Hospital, Zhejiang University" + "author_name": "Jerome R Lechien", + "author_inst": "University of Mons" }, { - "author_name": "Xing Zhang", - "author_inst": "Department of Biophysics & Center of Cryo-Electron Microscopy, Zhejiang University School of Medicine, Zhejiang University" + "author_name": "Christian Calvo-Henriquez", + "author_inst": "Hospital Complex of Santiago de Compostela" }, { - "author_name": "Jinghua Chen", - "author_inst": "Department of Biophysics & Center of Cryo-Electron Microscopy, Zhejiang University School of Medicine, Zhejiang University" + "author_name": "Nicolas Fakhry", + "author_inst": "Head and Neck Surgery Universitary Hospital of la Conception" }, { - "author_name": "Zhengyi Jiang", - "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Disease,The First Affiliated Hospital, Zhejiang University" + "author_name": "Petros D Karkos", + "author_inst": "AHEPA University Hospital" }, { - "author_name": "Jing Jiang", - "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Disease,The First Affiliated Hospital, Zhejiang University" + "author_name": "Shazia Peer", + "author_inst": "University of Cape Town" }, { - "author_name": "Feiyang Ji", - "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Disease,The First Affiliated Hospital, Zhejiang University" + "author_name": "Jon A Sistiaga-Suarez", + "author_inst": "Hospital Universitario Donostia" }, { - "author_name": "Xiaoxi Ouyang", - "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Disease,The First Affiliated Hospital, Zhejiang University" + "author_name": "Jose A Gonzalez-Garcia", + "author_inst": "Hospital Universitario Donostia" }, { - "author_name": "Lanjuan Li", - "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Disease,The First Affiliated Hospital, Zhejiang University" + "author_name": "Giovanni Cammaroto", + "author_inst": "Morgagni Pierantoni Hospital" + }, + { + "author_name": "Miguel Mayo", + "author_inst": "Hospital Complex of A Coruna" + }, + { + "author_name": "Pablo Parente-Arias", + "author_inst": "Hospital Lucus Agusti" + }, + { + "author_name": "Sven Saussez", + "author_inst": "University of Mons" + }, + { + "author_name": "Tareck Ayad", + "author_inst": "Centre Hospitalier de l universite de Montreal" } ], "version": "1", - "license": "cc_no", - "type": "confirmatory results", - "category": "molecular biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "otolaryngology" }, { "rel_doi": "10.1101/2020.04.25.20080200", @@ -1530418,29 +1531359,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.23.20077446", - "rel_title": "On the estimation of the total number of SARS-CoV-2 infections", + "rel_doi": "10.1101/2020.04.24.20077289", + "rel_title": "The role of spatial structure in the infection spread models: population density map of England example", "rel_date": "2020-04-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.23.20077446", - "rel_abs": "We introduce a simple methodology to estimate the infection fatality rate (IFR) and from here the total number of infected with SARS-CoV-2. The virus has shown to be highly infectious and thus we based our method under the assumption that all members of a household with at least one confirmed case of COVID-19 should be infected, therefore we estimate the IFR using the number of secondary fatalities in households. The simplicity of the methodology allows for large sample sizes, since it requires minimal laboratory testing capabilities. We applied this methodology to a database of 3,232 confirmed cases in Mexico and arrived to an IFR estimate within the range reported in other studies.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20077289", + "rel_abs": "In the current situation of a pandemic caused by COVID-19 developing models accurately predicting the dynamics of the outbreaks in time and space became extremely important.\n\nIndividual-based models (IBM) simulating the spread of infection in a population have a few advantages compared to classical equation-based approach. First, they use individuals as units, which represent the population, and reflect the local variations happening in real life. Second, the simplicity of modelling the interactions between the individuals, which may not be the case when using differential equations.\n\nWe propose to use freely available population density maps to simulate the infection spread in the human population on the scale of an individual country or a city. We explore the effect of social distancing and show that it can reduce the outbreak when applied before or during peak time, but it can also inflict the second wave when relaxed after the peak. This can be explained by a large proportion of susceptible individuals, even in the large cities, after the first wave.\n\nThe model can be adapted to any spatial scale from a single hospital to multiple countries.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "CARLOS M HERNANDEZ-SUAREZ", - "author_inst": "UNIVERSIDAD DE COLIMA" - }, - { - "author_name": "Paolo Verme", - "author_inst": "World Bank" + "author_name": "Gregory I Mashanov", + "author_inst": "The Francis Crick Institute" }, { - "author_name": "Efren Murillo-Zamora", - "author_inst": "Departamento de Epidemiologia, Unidad de Medicina Familiar No. 19, IMSS" + "author_name": "Alla Mashanova", + "author_inst": "The University of Hertfordshire" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1532076,87 +1533013,23 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.24.20069633", - "rel_title": "Lung injury in patients with or suspected COVID-19 : a comparison between lung ultrasound and chest CT-scanner severity assessments, an observational study", + "rel_doi": "10.1101/2020.04.24.20075333", + "rel_title": "Regional differences in reported Covid-19 cases show genetic correlations with higher socio-economic status and better health, potentially confounding studies on the genetics of disease susceptibility", "rel_date": "2020-04-28", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20069633", - "rel_abs": "BackgroundChest CT (CT) is the reference for assessing pulmonary injury in suspected or diagnosed COVID-19 with signs of clinical severity. We explored the role of lung ultrasonography (LU) in quickly assessing lung status in these patients.\n\nMethodseChoVid is a multicentric study based on routinely collected data, conducted in 3 emergency units of Assistance Publique des Hopitaux de Paris (APHP); 107 patients were included between March 19, 2020 and April 01, 2020 and underwent LU, a short clinical assessment by 2 emergency physicians blinded to each others and a CT. LU consisted of scoring lesions in 8 chest zones from 0 to 3, defining a severity global score (GS) ranging from 0 to 24. CT severity score ranged from 0 to 3 according to the extent of interstitial pneumonia signs. 48 patients underwent LU by both an expert and a newly trained physician.\n\nFindingsThe GS showed good performance to predict CT severity assessment of COVID-19 as normal versus pathologic: AUC=0.93, maximal Youden index 1 with 95% sensitivity, and 83% specificity. Similar performance was found for CT assessment as normal or minimal versus moderate or severe (n=90): AUC 0.89, maximal Youden index 7 with 86% sensitivity, and 78% specificity. Good agreement was found for zone scoring assessed by new trainee (30mn theory + 30mn practice) and expert (n=14,14*8 checkpoints), weighted kappa 0.85-1; moderate agreement was found for new trainee (n=48, 30mn theory) and expert, kappa 0.62-0.81.\n\nInterpretationGS score is a simple tool to assess lung damage severity in patients with suspected or diagnosed COVID-19. Comparing the performance of new trainees and expert physicians opens a path for adoption beyond the scope of experts. LU is a good candidate for patients triage, especially in case of CT availability issues.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20075333", + "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSIn March 2020, England showed a rapid increase in Covid-19 cases. Susceptibility for infectious diseases like Covid-19 is likely to be partly genetic. Mapping the genetic susceptibility for Covid-19 outcomes may reveal biological mechanisms that could potentially aid in drug or vaccine developments. However, as the disease spreads unevenly across the country, regional allele frequency differences could become spuriously associated with disease prevalence.\n\nMethodsA regional genome-wide association study (RGWAS) was conducted in 396,042 individuals from England to investigate the association between 1.2 million genetic variants and regional differences in daily reported Covid-19 cases from March 1st to April 18th 2020.\n\nResultsThe polygenic signal increases during the first weeks of March, peaking at March 13th with the measured genetic variants explaining [~]3% of the variance, including two genome-wide significant loci. The explained variance starts to drop at the end of March and reaches almost zero on April 18th. The majority of this temporary polygenic signal is due to genes associated with higher educational attainment and better health.\n\nConclusionsThe temporary positive relationship between Covid-19 cases and regional socio-economic status (SES) at the beginning of the Covid-19 outbreak may reflect 1) a higher degree of international travelers, 2) more social contacts, and/or 3) better testing capacities in higher SES regions. These signals are in the opposite direction of expected disease risk increasing effects, which has the potential to cancel out signals of interest. Genetic association studies should be aware of the timing and location of cases as this can introduce interfering polygenic signals that reflect regional differences in genes associated with behavior.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Mehdi Benchoufi", - "author_inst": "Center for Clinical Epidemiology, Hotel-Dieu Hospital, Assistance Publique-Hopitaux de Paris (AP-HP), Paris, France - METHODS Team, Center for Research in Epide" - }, - { - "author_name": "Jerome Bokobza", - "author_inst": "Adult Emergency Department, Cochin Hospital, Assistance Publique Hopitaux de Paris, Paris, France" - }, - { - "author_name": "Anthony Anthony Chauvin", - "author_inst": "Adult Emergency Department, Hopital Lariboisiere, Assistance Publique Hopitaux de Paris, University Diderot, Paris, France" - }, - { - "author_name": "Elisabeth Dion", - "author_inst": "Imaging department Hotel Dieu, Assistance Publique-Hopitaux de Paris, Universite de Paris,Paris, France." - }, - { - "author_name": "Marie-Laure Baranne", - "author_inst": "Center for Clinical Epidemiology, Hotel-Dieu Hospital, Assistance Publique-Hopitaux de Paris (AP-HP), Paris, France" - }, - { - "author_name": "Fabien Levan", - "author_inst": "Adult Emergency Department, Hopital Cochin, Assistance Publique Hopitaux de Paris, Paris, France" - }, - { - "author_name": "Maxime Gautier", - "author_inst": "Adult Emergency Department, Hopital Lariboisiere, Assistance Publique Hopitaux de Paris, Paris, France" - }, - { - "author_name": "Delphine Cantin", - "author_inst": "Adult Emergency Department, Hotel Dieu Hospital, Assistance Publique Hopitaux de Paris, Paris, France" - }, - { - "author_name": "Thomas d Humieres", - "author_inst": "Physiology department, Henri Mondor University Hospital, APHP, Creteil, France" - }, - { - "author_name": "Cedric Gil-Jardine", - "author_inst": "Adult Emergency Department SAMU-SMUR, Pellegrin Hospital, University Hospital Center, Bordeaux, France - Bordeaux Population Health, INSERM U1219, IETO Team, B" - }, - { - "author_name": "Sylvain Benenati", - "author_inst": "Adult Emergency Department, Hospital Group South Ile-de-France, Melun, France" - }, - { - "author_name": "Mathieu Oberlin", - "author_inst": "Adult Emergency Department, New Civil Hospital, Strasbourg, France" - }, - { - "author_name": "Mikael Martinez", - "author_inst": "Adult Emergency Department, Forez Hospital Center, Montbrison, France - Nord Emergency Network Ligerien Ardeche (REULIAN), Hospital Center Le Corbusier, Firminy" - }, - { - "author_name": "Nathalie Kahn", - "author_inst": "Imaging department Hotel Dieu, Assistance Publique Hopitaux de Paris, Paris University, France" - }, - { - "author_name": "Abdourahmane Diallo", - "author_inst": "Clinical Trial Unit Hospital, Lariboisiere St-Louis Fernand-Widal Hospital Group, Assistance Publique Hopitaux de Paris, Paris University, Paris, France" - }, - { - "author_name": "Eric Vicaut", - "author_inst": "Clinical Trial Unit Hospital, Lariboisiere St-Louis Fernand-Widal Hospital Group, Assistance Publique-Hopitaux de Paris, Paris University, Paris, France" - }, - { - "author_name": "Pierre Bourrier", - "author_inst": "Imaging Department Saint-Louis Hospital, Assistance Publique des Hopitaux de Paris, Paris, France" + "author_name": "Abdel Abdellaoui", + "author_inst": "Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2020.04.22.20075648", @@ -1533458,35 +1534331,55 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.21.20044594", - "rel_title": "Smart Pooled sample Testing for COVID-19: A Possible Solution for Sparsity of Test Kits", + "rel_doi": "10.1101/2020.04.24.20078477", + "rel_title": "COVID-19 in Iran: A Deeper Look Into The Future", "rel_date": "2020-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20044594", - "rel_abs": "There is an exponential growth of COVID-19. The adaptation of preventive measures to limit the spread of infection among the people is the best solution to this health issue. The identification of infected cases and their isolation from healthy people is one of the most important preventive measures. In this regard, screening of the samples from a large number of people is needed which requires a lot of reagent kits for the detection of SARS-CoV-2. The use of smart pooled sample testing with the help of algorithms may be a quite useful strategy in the current prevailing scenario of the COVID-19 pandemic. With the help of this strategy, the optimum number of samples to be pooled for a single test may be determined based on the total positivity rate of the particular community.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.24.20078477", + "rel_abs": "The novel corona-virus (COVID-19) has led to a pandemic, affecting almost all countries and regions in a few weeks, and therefore a global plan is needed to overcome this battle. Iran has been among the first few countries that has been affected severely, after China, which forced the government to put some restriction and enforce social distancing in majority of the country. In less than 2 months, Iran has more than 80,000 confirmed cases, and more than 5,000 death. Based on the official statistics from Irans government, the number of daily cases has started to go down recently, but many people believe if the lockdown is lifted without proper social distancing enforcement, there is a possibility for a second wave of COVID-19 cases. In this work, we analyze at the data for the number cases in Iran in the past few weeks, and train a predictive model to estimate the possible future trends for the number of cases in Iran, depending on the government policy in the coming weeks and months. Our analysis may help political leaders and health officials to take proper action toward handling COVID-19 in the coming months.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Syed Usama Khalid Bukhari", - "author_inst": "The University of Lahore" + "author_name": "Rahele Kafieh", + "author_inst": "Isfahan university of Medical Sciences" }, { - "author_name": "Syed Safwan Khalid", - "author_inst": "COMSATS University, Islamabad, Pakistan" + "author_name": "Roya Arian", + "author_inst": "Isfahan university of Medical Sciences" }, { - "author_name": "Asmara Syed", - "author_inst": "Faculty of Medicine, Northern Border University, Arar- Kingdom of Saudi Arabia" + "author_name": "Narges Saeedizadeh", + "author_inst": "Isfahan university of Medical Sciences" }, { - "author_name": "Syed Sajid Hussain Shah", - "author_inst": "Faculty of Medicine, Northern Border University, Arar- Kingdom of Saudi Arabia" + "author_name": "Shervin Minaee", + "author_inst": "Snap Inc." + }, + { + "author_name": "zahra amini", + "author_inst": "Isfahan university of Medical Sciences" + }, + { + "author_name": "Sunil Kumar Yadav", + "author_inst": "Nocturne GmbH" + }, + { + "author_name": "Atefeh Vaezi", + "author_inst": "Isfahan university of Medical Sciences" + }, + { + "author_name": "Nima Rezaei", + "author_inst": "Tehran university of Medical Sciences" + }, + { + "author_name": "Shaghayegh Haghjooy Javanmard", + "author_inst": "Isfahan university of Medical Sciences" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "pathology" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.22.056762", @@ -1534880,29 +1535773,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.22.20075861", - "rel_title": "The Potential Impact of Interruptions to HIV Services: A Modelling Case Study for South Africa", + "rel_doi": "10.1101/2020.04.22.20075770", + "rel_title": "Influenza-Negative Influenza-Like Illness (fnILI) Z-Score as a Proxy for Incidence and Mortality of COVID-19", "rel_date": "2020-04-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20075861", - "rel_abs": "The numbers of deaths caused by HIV could increase substantially if the COVID-19 epidemic leads to interruptions in the availability of HIV services. We compare publicly available scenarios for COVID-19 mortality with predicted additional HIV-related mortality based on assumptions about possible interruptions in HIV programs. An interruption in the supply of ART for 40% of those on ART for 3 months could cause a number of deaths on the same order of magnitude as the number that are anticipated to be saved from COVID-19 through social distancing measures. In contrast, if the disruption can be managed such that the supply and usage of ART is maintained, the increase in AIDS deaths would be limited to 1% over five years, although this could still be accompanied by substantial increases in new HIV infections if there are reductions in VMMC, oral PrEP use, and condom availability.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20075770", + "rel_abs": "Though ideal for determining the burden of disease, SARS-CoV2 test shortages preclude its implementation as a robust surveillance system in the US. We correlated the use of the derivative influenza-negative influenza-like illness (fnILI) z-score from the CDC as a proxy for incident cases and disease-specific deaths. For every unit increase of fnILI z-score, the number of cases increased by 70.2 (95%CI[5.1,135.3]) and number of deaths increased by 2.1 (95%CI[1.0,3.2]). FnILI data may serve as an accurate outcome measurement to track the spread of the and allow for informed and timely decision-making on public health interventions.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Britta L Jewell", - "author_inst": "Imperial College London" + "author_name": "Fatima N Mirza", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Jennifer A Smith", - "author_inst": "Imperial College London" + "author_name": "Amyn A. Malik", + "author_inst": "Yale School of Medicine" }, { - "author_name": "Timothy B Hallett", - "author_inst": "Imperial College London" + "author_name": "Saad B. Omer", + "author_inst": "Yale School of Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1535898,75 +1536791,115 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.04.25.060947", - "rel_title": "MINERVA: A facile strategy for SARS-CoV-2 whole genome deep sequencing of clinical samples", + "rel_doi": "10.1101/2020.04.21.050633", + "rel_title": "Rapid SARS-CoV-2 whole genome sequencing for informed public health decision making in the Netherlands", "rel_date": "2020-04-25", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.25.060947", - "rel_abs": "The novel coronavirus disease 2019 (COVID-19) pandemic poses a serious public health risk. Analyzing the genome of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) from clinical samples is crucial for the understanding of viral spread and viral evolution, as well as for vaccine development. Existing sample preparation methods for viral genome sequencing are demanding on user technique and time, and thus not ideal for time-sensitive clinical samples; these methods are also not optimized for high performance on viral genomes. We have developed MetagenomIc RNA EnRichment VirAl sequencing (MINERVA), a facile, practical, and robust approach for metagenomic and deep viral sequencing from clinical samples. This approach uses direct tagmentation of RNA/DNA hybrids using Tn5 transposase to greatly simplify the sequencing library construction process, while subsequent targeted enrichment can generate viral genomes with high sensitivity, coverage, and depth. We demonstrate the utility of MINERVA on pharyngeal, sputum and stool samples collected from COVID-19 patients, successfully obtaining both whole metatranscriptomes and complete high-depth high-coverage SARS-CoV-2 genomes from these clinical samples, with high yield and robustness. MINERVA is compatible with clinical nucleic extracts containing carrier RNA. With a shortened hands-on time from sample to virus-enriched sequencing-ready library, this rapid, versatile, and clinic-friendly approach will facilitate monitoring of viral genetic variations during outbreaks, both current and future.", - "rel_num_authors": 14, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.21.050633", + "rel_abs": "SARS-CoV-2 is a novel coronavirus that has rapidly spread across the globe. In the Netherlands, the first case of SARS-CoV-2 has been notified on the 27th of February. Here, we describe the first three weeks of the SARS-CoV-2 outbreak in the Netherlands, which started with several different introductory events from Italy, Austria, Germany and France followed by local amplification in, and later also, outside the South of the Netherlands. The timely generation of whole genome sequences combined with epidemiological investigations facilitated early decision making in an attempt to control local transmission of SARS-CoV-2 in the Netherlands.", + "rel_num_authors": 24, "rel_authors": [ { - "author_name": "Chen Chen", - "author_inst": "Beijing Ditan Hospital" + "author_name": "Bas B. Oude Munnink", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" }, { - "author_name": "Jizhou Li", - "author_inst": "Tsinghua University" + "author_name": "David F Nieuwenhuijse", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" }, { - "author_name": "Lin Di", - "author_inst": "Peking University" + "author_name": "Mart Stein", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands" }, { - "author_name": "Qiuyu Jing", - "author_inst": "The Hong Kong University of Science and Technology" + "author_name": "Manon Haverkarte", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands" }, { - "author_name": "Pengcheng Du", - "author_inst": "Beijing Ditan Hospital" + "author_name": "Madelief Mollers", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands" }, { - "author_name": "Chuan Song", - "author_inst": "Beijing Ditan Hospital" + "author_name": "Sandra K. Kamga", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands" }, { - "author_name": "Jiarui Li", - "author_inst": "Beijing Ditan Hospital" + "author_name": "Claudia Schapendonk", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" }, { - "author_name": "Qiong Li", - "author_inst": "Tsinghua University" + "author_name": "Pascal Lexmond", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" }, { - "author_name": "Yunlong Cao", - "author_inst": "Peking University" + "author_name": "Mark Pronk", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" }, { - "author_name": "Sunney Xie", - "author_inst": "Peking University" + "author_name": "Anne van der Linden", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" }, { - "author_name": "Angela Ruohao Wu", - "author_inst": "The Hong Kong University of Science and Technology" + "author_name": "Theo Bestebroer", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" }, { - "author_name": "Hui Zeng", - "author_inst": "Beijing Ditan Hospital" + "author_name": "Irina Chestakova", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" }, { - "author_name": "Yanyi Huang", - "author_inst": "Peking University" + "author_name": "Ronald J. Overmars", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" }, { - "author_name": "Jianbin Wang", - "author_inst": "Tsinghua University" + "author_name": "Stefan van Nieuwkoop", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" + }, + { + "author_name": "Richard Molenkamp", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" + }, + { + "author_name": "Annemieke van der Eijck", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" + }, + { + "author_name": "Corine GeurtsvanKessel", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" + }, + { + "author_name": "Harry Vennema", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands" + }, + { + "author_name": "Adam Meijer", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands" + }, + { + "author_name": "Andrew Rambaut", + "author_inst": "University of Edinburgh" + }, + { + "author_name": "Jaap van Dissel", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands" + }, + { + "author_name": "Reina Sikkema", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" + }, + { + "author_name": "Aura Timen", + "author_inst": "Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands" + }, + { + "author_name": "Marion Koopmans", + "author_inst": "ErasmusMC, Department of Viroscience, WHO collaborating centre for arbovirus and viral hemorrhagic fever Reference and Research, Rotterdam, the Netherlands" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_no", "type": "new results", - "category": "molecular biology" + "category": "genomics" }, { "rel_doi": "10.1101/2020.04.20.052258", @@ -1537452,37 +1538385,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.22.20074914", - "rel_title": "Antibody tests in detecting SARS-CoV-2 infection: a meta-analysis", + "rel_doi": "10.1101/2020.04.22.20074898", + "rel_title": "Non-Linear fitting of Sigmoidal Growth Curves to predict a maximum limit to the total number of COVID-19 cases in the United States.", "rel_date": "2020-04-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20074914", - "rel_abs": "BackgroundWith the emergence of SARS-CoV-2 and the associated Coronavirus disease 2019 (COVID-19), there is an imperative need for diagnostic tests that can identify the infection. Although Nucleic Acid Test (NAT) is considered to be the gold standard, serological tests based on antibodies could be very helpful. However, individual studies measuring the accuracy of the various tests are usually underpowered and inconsistent, thus, a comparison of different tests is needed.\n\nMethodsWe performed a systematic review and meta-analysis following the PRISMA guidelines. We conducted the literature search in PubMed, medRxiv and bioRxiv. For the statistical analysis we used the bivariate method for meta-analysis of diagnostic tests pooling sensitivities and specificities. We evaluated IgM and IgG tests based on Enzyme-linked immunosorbent assay (ELISA), Chemiluminescence Enzyme Immunoassays (CLIA), Fluorescence Immunoassays (FIA) and the point-of-care (POC) Lateral Flow Immunoassays (LFIA) that are based on immunochromatography.\n\nFindingsIn total, we identified 38 eligible studies that include data from 7,848 individuals. The analyses showed that tests using the S antigen are more sensitive than N antigen-based tests. IgG tests perform better compared to IgM ones, and show better sensitivity when the samples were taken longer after the onset of symptoms. Moreover, irrespective of the method, a combined IgG/IgM test seems to be a better choice in terms of sensitivity than measuring either antibody type alone. All methods yielded high specificity with some of them (ELISA and LFIA) reaching levels around 99%. ELISA- and CLIA-based methods performed better in terms of sensitivity (90-94%) followed by LFIA and FIA with sensitivities ranging from 80% to 86%.\n\nInterpretationELISA tests could be a safer choice at this stage of the pandemic. POC tests (LFIA), that are more attractive for large seroprevalence studies show high specificity but lower sensitivity and this should be taken into account when designing and performing seroprevalence studies.\n\nFundingNone", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.22.20074898", + "rel_abs": "In the present work is used non-linear fitting of the \"Gompert\" and \"Logistic\" growth models to the number of total COVID-19 cases from the United States as a country and individually by states. The methodology allowed us to estimate that the maximum limit for the total number of cases of COVID-19 patients such as those registered with the World Health Organization will be approximately one million and one hundred thousand cases to the United States. Up to 04/19/20 the models indicate that United States reached 70% of this maximum number of \"total cases\" and the United States will reach 95% of this limit by 05/14/2020. The application of the nonlinear fitting of growth curves to the individual data of each American state showed that only 25% of them did not reach, on 04/19/20, the percentage of 59% of the maximum limit of \"total cases\" and that 17 of the 50 states still will not have reached 95% of that limit on 05/14/20.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Panagiota I Kontou", - "author_inst": "University of Thessaly" - }, - { - "author_name": "Georgia G Braliou", - "author_inst": "University of Thessaly" - }, - { - "author_name": "Niki L Dimou", - "author_inst": "International Agency for Research on Cancer" - }, - { - "author_name": "Georgios Nikolopoulos", - "author_inst": "University of Cyprus" - }, - { - "author_name": "Pantelis G Bagos", - "author_inst": "University of Thessaly" + "author_name": "Carlos Maximiliano Dutra Sr.", + "author_inst": "UNIPAMPA" } ], "version": "1", - "license": "cc_no", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1539106,47 +1540023,55 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2020.04.21.20066761", - "rel_title": "Risk of drug-induced Long QT Syndrome associated with the use of repurposed COVID-19 drugs: a systematic review", + "rel_doi": "10.1101/2020.04.20.20068676", + "rel_title": "Understanding the Collective Responses of Populations to the COVID-19 Pandemic in Mainland China", "rel_date": "2020-04-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20066761", - "rel_abs": "The risk-benefit ratio associated with the use of repurposed drugs to treat 2019 SARS-CoV-2 related infectious disease (COVID-19) is complicated since benefits are awaited, not proven. A thorough literature search was conducted to source information on the pharmacological properties of 5 drugs and 1 combination (azithromycin, chloroquine, favipiravir, hydroxychloroquine, remdesivir, and lopinavir/ritonavir) repurposed to treat COVID-19. A risk assessment of drug-induced Long QT Syndrome (LQTS) associated with COVID-19 repurposed drugs was performed and compared to 23 well-known torsadogenic and 10 low torsadogenic risk compounds. Computer calculations were performed using pharmacokinetic and pharmacodynamic data, including affinity to block the rapid component of the delayed rectifier cardiac potassium current (IKr) encoded by the human ether-a-go-go gene (hERG), propensity to prolong cardiac repolarization (QT interval) and cause torsade de pointes (TdP). Seven different LQTS indices were calculated and compared. The U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS) database was queried with specific key words relating to arrhythmogenic events. Estimators of LQTS risk levels indicated a very high or moderate risk for all COVID-19 repurposed drugs with the exception for azithromycin, although cases of TdP have been reported with this drug. There was excellent agreement among the various indices used to assess risk of drug-induced LQTS for the 6 repurposed medications and 23 torsadogenic compounds. Based on our results, monitoring of the QT interval shall be performed when some COVID-19 repurposed drugs are used, as such monitoring is possible for hospitalized patients or with the use of biodevices for outpatients.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20068676", + "rel_abs": "Timely information acquisition and stay-at-home measures have been considered as two effective steps that every person could take to help contain the coronavirus (COVID-19) pandemic. From the perspectives of information and mobility, this work aims at evaluating to what degree the massive population has responded to the emergencies of the COVID-19 pandemic in China. Using the real-time and historical data collected from the Baidu Maps and Baidu search engines, we confirm the strong correlation between the local pandemic situation in every major Chinese city and the population inflows from Wuhan between 1 January and 23 January 2020. We further evidence that, in cities under more critical situations, people are likely to engage COVID-19-related searches more frequently, while they are not likely to escape from the cities. Finally, the correlation analysis using search and mobility data shows that well-informed individuals are likely to travel less, even while the overall travel demands are low compared to the historical records. Partial correlation analysis has been conducted to test the significance of these observations with respect to other controlling factors.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Veronique Michaud", - "author_inst": "Tabula Rasa HealthCare" + "author_name": "Haoyi Xiong", + "author_inst": "Baidu Inc." + }, + { + "author_name": "Ji Liu", + "author_inst": "Baidu Inc." + }, + { + "author_name": "Jizhou Huang", + "author_inst": "Baidu Inc." }, { - "author_name": "Pamela Dow", - "author_inst": "Tabula Rasa HealthCare" + "author_name": "Siyu Huang", + "author_inst": "Baidu Inc." }, { - "author_name": "Sweilem B Al Rihani", - "author_inst": "Tabula Rasa HealthCare" + "author_name": "Haozhe An", + "author_inst": "Baidu Inc." }, { - "author_name": "Malavika Deodhar", - "author_inst": "Tabula Rasa HealthCare" + "author_name": "Qi Kang", + "author_inst": "Baidu Inc." }, { - "author_name": "Meghan Arwood", - "author_inst": "Tabula Rasa HealthCare" + "author_name": "Ying Li", + "author_inst": "Baidu Inc." }, { - "author_name": "Brian Cicali", - "author_inst": "University of Florida" + "author_name": "Dejing Dou", + "author_inst": "Baidu Inc." }, { - "author_name": "Jacques Turgeon", - "author_inst": "Tabula Rasa HealthCare" + "author_name": "Haifeng Wang", + "author_inst": "Baidu Inc." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.21.20074468", @@ -1540812,71 +1541737,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.20.20072470", - "rel_title": "Prevalence of SARS-CoV-2 infection in previously undiagnosed health care workers at the onset of the U.S. COVID-19 epidemic", + "rel_doi": "10.1101/2020.04.21.20074138", + "rel_title": "Prediction of the COVID-19 Epidemic Trends Based on SEIR and AI Models", "rel_date": "2020-04-24", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072470", - "rel_abs": "ImportanceHealthcare workers are presumed to be at increased risk of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection due to occupational exposure to infected patients. However, no epidemiological study has examined the prevalence of SARS-CoV-2 infection in a cohort of healthcare workers during the early phase of community transmission.\n\nObjectiveTo determine the baseline prevalence of SARS-CoV-2 infection in a cohort of previously undiagnosed healthcare workers and a comparison group of non-healthcare workers.\n\nDesignProspective cohort study\n\nSettingA large U.S. university and two affiliated university hospitals\n\nParticipants546 health care workers and 283 non-health care workers with no known prior SARS-CoV-2 infection\n\nExposureHealthcare worker status and role\n\nMain outcome(s) and measure(s)SARS-CoV-2 infection status as determined by presence of SARS-CoV-2 RNA in oropharyngeal swabs.\n\nResultsAt baseline, 41 (5.0%) of participants tested positive for SARS-CoV-2 infection, of whom 14 (34.2%) reported symptoms. The prevalence of SARS-CoV-2 infection was higher among healthcare workers (7.3%) than in non-healthcare workers (0.4%), representing a 7.0% greater absolute risk (95% confidence interval for risk difference 4.7%, 9.3%). The majority of infected healthcare workers (62.5%) worked as nurses. Positive tests increased across the two weeks of cohort recruitment in line with rising confirmed cases in the hospitals and surrounding counties.\n\nConclusions and relevanceIn a prospective cohort conducted in the early phases of community transmission, healthcare workers had a higher prevalence of SARS-CoV-2 infection than non-healthcare workers, attesting to the occupational hazards of caring for patients in this crisis. Baseline data reported here will enable us to monitor the spread of infection and examine risk factors for transmission among healthcare workers. These results will inform optimal strategies for protecting the healthcare workforce, their families, and their patients.\n\nClinicaltrials.gov registration number:NCT04336215\n\nKey pointsO_ST_ABSQuestionC_ST_ABSAmong previously undiagnosed individuals, is the prevalence of SARS-CoV-2 infection higher in U.S. healthcare workers compared to non-healthcare workers in the early phase of the U.S. COVID-19 epidemic?\n\nFindingsThe prevalence of SARS-CoV-2 infection was 7.3% in healthcare workers and 0.4% in non-healthcare workers, representing 7.0% greater absolute risk in the former (95% confidence interval for risk difference 4.7%, 9.3%). Infections were most common among nursing staff.\n\nMeaningHealth care workers, particularly those with high levels of close patient contact, may be particularly vulnerable to SARS-CoV-2 infection. Additional strategies are needed to protect these critical frontline workers.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.21.20074138", + "rel_abs": "The outbreak of novel coronavirus-caused pneumonia (COVID-19) in Wuhan has attracted worldwide attention. To contain its spread, China adopted unprecedented nationwide interventions on January 23. We sought to show how these control measures impacted the containment of the epidemic. We proposed an SEIR(Susceptible-Exposed-Infectious-Removed) model to analyze the epidemic trend in Wuhan and use the AI model to analyze the epidemic trend in non-Wuhan areas. We found that if the closure was lifted, the outbreak in non-Wuhan areas of mainland China would double in size. Our SEIR and AI model was effective in predicting the COVID-19 epidemic peaks and sizes. The implementation of control measures on January 23, 2020, was indispensable in reducing the eventual COVID-19 epidemic size.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Emily S Barrett", - "author_inst": "Rutgers School of Public Health" - }, - { - "author_name": "Daniel B. Horton", - "author_inst": "Rutgers Robert Wood Johnson Medical School" - }, - { - "author_name": "Jason Roy", - "author_inst": "Rutgers School of Public Health" - }, - { - "author_name": "Maria Laura Gennaro", - "author_inst": "New Jersey Medical School" - }, - { - "author_name": "Andrew Brooks", - "author_inst": "RUCDR Infinite Biologics, Rutgers University" - }, - { - "author_name": "Jay Tischfield", - "author_inst": "RUCDR Infinite Biologics, Rutgers University" - }, - { - "author_name": "Patricia Greenberg", - "author_inst": "Rutgers School of Public Health" - }, - { - "author_name": "Tracy Andrews", - "author_inst": "Rutgers School of Public Health" - }, - { - "author_name": "Sugeet Jagpal", - "author_inst": "Rutgers Robert Wood Johnson Medical School" + "author_name": "Shuo Feng", + "author_inst": "Peking University" }, { - "author_name": "Nancy Reilly", - "author_inst": "Rutgers Institute for Translational Medicine & Science" + "author_name": "Zebang Feng", + "author_inst": "Peking University" }, { - "author_name": "Martin J. Blaser", - "author_inst": "Center for Advanced Biotechnology and Medicine; Rutgers University" + "author_name": "Chen Ling", + "author_inst": "Harbin Institute of Technology" }, { - "author_name": "Jeffrey Carson", - "author_inst": "Rutgers Robert Wood Johnson Medical School" + "author_name": "Chen Chang", + "author_inst": "Beijing Key Laboratory of Precision Forestry, Beijing Forestry University" }, { - "author_name": "Reynold A. Panettieri Jr.", - "author_inst": "Rutgers Institute for Translational Medicine & Science" + "author_name": "Zhongke Feng", + "author_inst": "Beijing Key Laboratory of Precision Forestry, Beijing Forestry University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.20.20072421", @@ -1542402,71 +1543295,23 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.04.17.20070219", - "rel_title": "From Community Acquired Pneumonia to COVID-19: A Deep Learning Based Method for Quantitative Analysis of COVID-19 on thick-section CT Scans", + "rel_doi": "10.1101/2020.04.20.20072991", + "rel_title": "Monitoring COVID-19 progression: Look at Us Today, See Yourself Tomorrow", "rel_date": "2020-04-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20070219", - "rel_abs": "BackgroundThick-section CT scanners are more affordable for the developing countries. Considering the widely spread COVID-19, it is of great benefit to develop an automated and accurate system for quantification of COVID-19 associated lung abnormalities using thick-section chest CT images.\n\nPurposeTo develop a fully automated AI system to quantitatively assess the disease severity and disease progression using thick-section chest CT images.\n\nMaterials and MethodsIn this retrospective study, a deep learning based system was developed to automatically segment and quantify the COVID-19 infected lung regions on thick-section chest CT images. 531 thick-section CT scans from 204 patients diagnosed with COVID-19 were collected from one appointed COVID-19 hospital from 23 January 2020 to 12 February 2020. The lung abnormalities were first segmented by a deep learning model. To assess the disease severity (non-severe or severe) and the progression, two imaging bio-markers were automatically computed, i.e., the portion of infection (POI) and the average infection HU (iHU). The performance of lung abnormality segmentation was examined using Dice coefficient, while the assessment of disease severity and the disease progression were evaluated using the area under the receiver operating characteristic curve (AUC) and the Cohens kappa statistic, respectively.\n\nResultsDice coefficient between the segmentation of the AI system and the manual delineations of two experienced radiologists for the COVID-19 infected lung abnormalities were 0.74{+/-}0.28 and 0.76{+/-}0.29, respectively, which were close to the inter-observer agreement, i.e., 0.79{+/-}0.25. The computed two imaging bio-markers can distinguish between the severe and non-severe stages with an AUC of 0.9680 (p-value< 0.001). Very good agreement ({kappa} = 0.8220) between the AI system and the radiologists were achieved on evaluating the changes of infection volumes.\n\nConclusionsA deep learning based AI system built on the thick-section CT imaging can accurately quantify the COVID-19 associated lung abnormalities, assess the disease severity and its progressions.\n\nKey ResultsA deep learning based AI system was able to accurately segment the infected lung regions by COVID-19 using the thick-section CT scans (Dice coefficient [≥] 0.74).\n\nThe computed imaging bio-markers were able to distinguish between the non-severe and severe COVID-19 stages (area under the receiver operating characteristic curve 0.968).\n\nThe infection volume changes computed by the AI system was able to assess the COVID-19 progression (Cohens kappa 0.8220).\n\nSummary StatementA deep learning based AI system built on the thick-section CT imaging can accurately quantify the COVID-19 infected lung regions, assess patients disease severity and their disease progressions.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.20.20072991", + "rel_abs": "The coronavirus disease 2019 (COVID-19) pandemic is causing public health emergency and economic crisis all over the globe. Being widely spread, the virus can make any place in the world a new epicenter of the possible second wave of outbreaks. To control the pandemic progression, monitoring of the virus spreading is imperative. This paper proposes a simple and robust approach to monitor the COVID-19 pandemic progression in many countries or regions. This data science pipeline can provide actionable insights via straightforward COVID-19 data visualization for many regions at a glance, which informs of relative time delay of the pandemic progression, projected numbers of confirmed cases in the near future, and the sizes of infections.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Zhang Li", - "author_inst": "College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, China" - }, - { - "author_name": "Zheng Zhong", - "author_inst": "Department of Radiology, The First Hospital of Changsha City, Changsha, China" - }, - { - "author_name": "Yang Li", - "author_inst": "College of Aerospace Science and Engineering, National University of Defense Technology, Changsha, China" - }, - { - "author_name": "Tianyu Zhang", - "author_inst": "Department of Radiology, Netherlands Cancer Institute (NKI), Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands" - }, - { - "author_name": "Liangxin Gao", - "author_inst": "PingAn Technology, Shenzhen, China" - }, - { - "author_name": "Dakai Jin", - "author_inst": "PAII Inc., Bethesda, MD, USA" - }, - { - "author_name": "Yue Sun", - "author_inst": "Department of Electrical Engineering, Eindhoven University of Technology, 5600 MB Eindhoven, The Netherlands" - }, - { - "author_name": "Xianghua Ye", - "author_inst": "Department of Radiotherapy, The First Affiliated Hospital, Zhejiang University, Hangzhou, Zhejiang, China" - }, - { - "author_name": "Li Yu", - "author_inst": "Hunan LanXi Biotechnology Ltd., Changsha, China" - }, - { - "author_name": "Zheyu Hu", - "author_inst": "Hunan Cancer Hospital, the Affiliated Cancer Hospital of Xiangya Medical School, Central South University, Changsha, China" - }, - { - "author_name": "Jing Xiao", - "author_inst": "PingAn Technology, Shenzhen, China" - }, - { - "author_name": "Lingyun Huang", - "author_inst": "PingAn Technology, Shenzhen, China" - }, - { - "author_name": "Yuling Tang", - "author_inst": "Department of Respiratory Medicine, The First Hospital of Changsha City, Changsha, China" + "author_name": "Jungsik Noh", + "author_inst": "UT Southwestern Medical Center" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "radiology and imaging" + "category": "health systems and quality improvement" }, { "rel_doi": "10.1101/2020.04.20.20072934", @@ -1544024,45 +1544869,61 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.18.20070565", - "rel_title": "Clinical Characteristics of 20,662 Patients with COVID-19 in mainland China: A Systemic Review and Meta-analysis", + "rel_doi": "10.1101/2020.04.18.20070920", + "rel_title": "Trends of SARS-Cov-2 infection in 67 countries: Role of climate zone, temperature, humidity and curve behavior of cumulative frequency on duplication time", "rel_date": "2020-04-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.18.20070565", - "rel_abs": "Coronavirus disease 2019 (COVID-19) is a global pandemic and has been widely reported; however, a comprehensive systemic review and meta-analysis has not been conducted. We systematically investigated the clinical characteristics of COVID-19 in mainland China to guide diagnosis and treatment. We searched the PubMed, Embase, Scopus, Web of Science, Cochrane Library, bioRxiv, medRxiv, and SSRN databases for studies related to COVID-19 published or preprinted in English or Chinese from January 1 to March 15, 2020. Clinical studies on COVID-19 performed in mainland China were included. We collected primary outcomes including signs and symptoms, chest CT imaging, laboratory tests, and treatments. Study selection, data extraction, and risk of bias assessment were performed by two independent reviewers. Qualitative and quantitative synthesis was conducted, and random-effects models were applied to pooled estimates. This study is registered with PROSPERO (number CRD42020171606). Of the 3624 records identified, 147 studies (20,662 patients) were analyzed. The mean age of patients with COVID-19 was 49.40 years, 53.45% were male, and 38.52% had at least one comorbidity. Fever and cough were the most common symptoms, followed by fatigue, expectoration, and shortness of breath. Most patients with COVID-19 had abnormal chest CT findings with ground glass opacity (70.70%) or consolidation (29.91%). Laboratory findings shown lymphopenia, increased lactate dehydrogenase, increased infection-related indicators, and fibrinolytic hyperactivity. Antiviral therapy, antibiotic therapy, and corticosteroids were administered to 89.75%, 79.13%, and 35.64% of patients, respectively. Most clinical characteristics of COVID-19 are non-specific. Patients with suspected should be evaluated by virological assays and clinically treated.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.18.20070920", + "rel_abs": "ObjectiveTo analyze the role of temperature, humidity, date of first case diagnosed (DFC) and the behavior of the growth-curve of cumulative frequency (CF) [number of days to rise (DCS) and reach the first 100 cases (D100), and the difference between them ({Delta}DD)] with the doubling time (Td) of Covid-19 cases in 67 countries grouped by climate zone.\n\nDesignRetrospective incident case study.\n\nSettingWHO based register of cumulative incidence of Covid-19 cases.\n\nParticipants1,706,914 subjects diagnosed between 12-29-2019 and 4-15-2020.\n\nExposuresSARS-Cov-2 virus, ambient humidity, temperature and climate areas (temperate, tropical/subtropical).\n\nMain outcome measuresComparison of DCS, D100, {Delta}DD, DFC, humidity, temperature, Td for the first (Td10) and second (Td20) ten days of the CF growth-curve between countries according to climate zone, and identification of factors involved in Td, as well as predictors of CF using lineal regression models.\n\nResultsTd10 and Td20 were [≥]3 days longer in tropical/subtropical vs. temperate areas (2.8{+/-}1.2 vs. 5.7{+/-}3.4; p=1.41E-05 and 4.6{+/-}1.8 vs. 8.6{+/-}4.2; p=9.7E-05, respectively). The factors involved in Td10 (DFC and {Delta}DD) were different than those in Td20 (Td10 and climate areas). After D100, the fastest growth-curves during the first 10 days, were associated with Td10<2 and Td10<3 in temperate and tropical/subtropical countries, respectively. The fold change Td20/Td10 >2 was associated with earlier flattening of the growth-curve. In multivariate models, Td10, DFC and ambient temperature were negatively related with CF and explained 44.7% (r2 = 0.447) of CF variability at day 20 of the growth-curve, while Td20 and DFC were negatively related with CF and explained 63.8% (r2 = 0.638) of CF variability towards day 30 of the growth-curve.\n\nConclusionsThe larger Td in tropical/subtropical countries is positively related to DFC and temperature. Td and environmental factors explain 64% of CF variability in the best of cases. Therefore, other factors, such as pandemic containment measures, would explain the remaining variability.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Chong Tang", - "author_inst": "Peking university shougang hospital" + "author_name": "Jaime Berumen", + "author_inst": "Unidad de Medicina Experimental, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico" }, { - "author_name": "Keshi Zhang", - "author_inst": "Peking university shougang hospital" + "author_name": "Max Schmulson", + "author_inst": "Unidad de Medicina Experimental, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico" }, { - "author_name": "Wenlong Wang", - "author_inst": "Peking university shougang hospital" + "author_name": "Guadalupe Guerrero", + "author_inst": "Hospital General de Mexico, Dr. Eduardo Liceaga, Mexico City, Mexico" }, { - "author_name": "Zheng Pei", - "author_inst": "Peking university shougang hospital" + "author_name": "Elizabeth Barrera", + "author_inst": "Unidad de Medicina Experimental, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico" }, { - "author_name": "Zheng Liu", - "author_inst": "Peking university shougang hospital" + "author_name": "Jorge Larriva-Sahd", + "author_inst": "Instituto de Neurobiologia, Universidad Nacional Autonoma de Mexico, Campus Juriquilla, Queretaro Mexico" }, { - "author_name": "Ping Yuan", - "author_inst": "Peking university shougang hospital" + "author_name": "Gustavo Olaiz", + "author_inst": "Centro de Investigacion en politicas, poblacion y salud, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City Mexico" + }, + { + "author_name": "Rebeca Garcia-Leyva", + "author_inst": "Unidad de Medicina Experimental, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico" + }, + { + "author_name": "Rosa M Wong-Chew", + "author_inst": "Division de Investigacion, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico" + }, + { + "author_name": "Miguel Betancourt-Cravioto", + "author_inst": "Fundacion Carlos Slim, Mexico City, Mexico" }, { - "author_name": "Zhenpeng Guan", - "author_inst": "Peking university shougang hospital" + "author_name": "Hector Gallardo", + "author_inst": "Fundacion Carlos Slim, Mexico City, Mexico" }, { - "author_name": "Jin Gu", - "author_inst": "Peking university shougang hospital" + "author_name": "German Fajardo-Dolci", + "author_inst": "Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico" + }, + { + "author_name": "Roberto Tapia-Conyer", + "author_inst": "Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Mexico City, Mexico" } ], "version": "1", @@ -1545850,31 +1546711,43 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.04.13.20064287", - "rel_title": "Does TB Vaccination Reduce COVID-19 Infection?: No Evidence from a Regression Discontinuity Analysis", + "rel_doi": "10.1101/2020.04.16.20067421", + "rel_title": "Self-reported COVID-19 symptoms on Twitter: An analysis and a research resource", "rel_date": "2020-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20064287", - "rel_abs": "In the middle of the global COVID-19 pandemic, the BCG hypothesis, the prevalence and severity of the COVID-19 outbreak seems to be correlated with whether a country has a universal coverage of Bacillus-Calmette-Guerin (BCG), a vaccine for tuberculosis disease (TB), has emerged and attracted the attention of scientific community and media outlets. However, all existing claims are based on cross-country correlations that do not exclude the possibility of spurious correlation. We merged country-age-level case statistics with the start/termination years of BCG vaccination policy and conducted a regression discontinuity and difference-indifference analysis. The results do not support the BCG hypothesis.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20067421", + "rel_abs": "ObjectiveTo mine Twitter to quantitatively analyze COVID-19 symptoms self-reported by users, compare symptom distributions against clinical studies, and create a symptom lexicon for the research community.\n\nMaterials and methodsWe retrieved tweets using COVID-19-related keywords, and performed semi-automatic filtering to curate self-reports of positive-tested users. We extracted COVID-19-related symptoms mentioned by the users, mapped them to standard concept IDs (UMLS), and compared the distributions to those reported in early studies from clinical settings.\n\nResultsWe identified 203 positive-tested users who reported 1002 symptoms using 668 unique expressions. The most frequently-reported symptoms were fever/pyrexia (66.1%), cough (57.9%), body ache/pain (42.7%), fatigue (42.1%), headache (37.4%), and dyspnea (36.3%) amongst users who reported at least 1 symptom. Mild symptoms, such as anosmia (28.7%) and ageusia (28.1%) were frequently reported on Twitter, but not in clinical studies.\n\nConclusionThe spectrum of COVID-19 symptoms identified from Twitter may complement those identified in clinical settings.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Masao Fukui", - "author_inst": "Massachusetts Institute of Technology" + "author_name": "Abeed Sarker", + "author_inst": "Emory University" }, { - "author_name": "Kohei Kawaguchi", - "author_inst": "Hong Kong University of Science and Technology" + "author_name": "Sahithi Lakamana", + "author_inst": "Emory University" + }, + { + "author_name": "Whitney Hogg-Bremer", + "author_inst": "Emory University" + }, + { + "author_name": "Angel Xie", + "author_inst": "Emory University" + }, + { + "author_name": "Mohammed Ali Al-Garadi", + "author_inst": "Emory University" }, { - "author_name": "Hiroaki Matsuura", - "author_inst": "Shoin University" + "author_name": "Yuan-Chi Yang", + "author_inst": "Emory University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.04.16.20067603", @@ -1547304,27 +1548177,47 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.17.20069823", - "rel_title": "An ecological study of socioeconomic predictors in detection of COVID-19 cases across neighborhoods in New York City", + "rel_doi": "10.1101/2020.04.17.20070102", + "rel_title": "Social Distancing and Personal Protective Measures Decrease Influenza Morbidity and Mortality", "rel_date": "2020-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20069823", - "rel_abs": "BackgroundNew York City was the first major urban center of the COVID-19 pandemic in the USA. Cases are clustered in the city, with certain neighborhoods experiencing more cases than others. We investigate whether potential socioeconomic factors can explain between-neighborhood variation in the number of detected COVID-19 cases.\n\nMethodsData were collected from 177 Zip Code Tabulation Areas (ZCTA) in New York City (99.9% of the population). We fit multiple Bayesian Besag-York-Mollie (BYM) mixed models using positive COVID-19 tests as the outcome and a set of 10 representative economic, demographic, and health-care associated ZCTA-level parameters as potential predictors. The BYM model includes both spatial and nonspatial random effects to account for clustering and overdispersion.\n\nResultsMultiple different regression approaches indicated a consistent, statistically significant association between detected COVID-19 cases and dependent (under 18 or 65+ years old) population, male to female ratio, and median household income. In the final model, we found that an increase of only 1% in dependent population is associated with a 2.5% increase in detected COVID-19 cases (95% confidence interval (CI): 1.6% to 3.4%, p < 0.0005). An increase of 1 male per 100 females is associated with a 1.0% (95% CI: 0.6% to 1.5%, p < 0.0005) increases in detected cases. A decrease of $10,000 median household income is associated with a 2.5% (95% CI: 1.0% to 4.1% p = 0.002) increase in detected COVID-19 cases.\n\nConclusionsOur findings indicate associations between neighborhoods with a large dependent population, those with a high proportion of males, and low-income neighborhoods and detected COVID-19 cases. Given the elevated mortality in aging populations, the study highlights the importance of public health management during and after the current COVID-19 pandemic. Further work is warranted to fully understand the mechanisms by which these factors may have affected the number of detected cases, either in terms of the true number of cases or access to testing.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20070102", + "rel_abs": "Seasonal influenza (flu) is an underappreciated source of disease morbidity and mortality worldwide. While vaccination remains the cornerstone of influenza prevention, common measures practiced during the COVID-19 pandemic such as social distancing, the use of protective face masks, and frequent hand washing are rarely utilized during flu season. In this investigation, we examined the effect of these preventative measures in decreasing influenza burden this year. We examined three countries with major COVID-19 outbreaks i.e. China, Italy and the United States, and compared the flu activity this year to the average of the last 4 years (2015-2019). We found that this year in China and Italy, there was a significantly steeper decline of flu cases than average, which correlated with an increase in positive COVID-19 case reports in those countries. These \"averted\" cases can be translated into a substantial decrease in morbidity and mortality. As such, we conclude that the current COVID-19 pandemic is a reminder that behavioral measures can decrease the burden of communicable respiratory infections, and these measures should be adopted to an extent during normal influenza season.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Richard Stuart Whittle", - "author_inst": "Texas A&M University" + "author_name": "Grant M Young", + "author_inst": "Yale University" }, { - "author_name": "Ana Diaz-Artiles", - "author_inst": "Texas A&M University" + "author_name": "Xiaohua Peng", + "author_inst": "Yale University" + }, + { + "author_name": "Andre Rebaza", + "author_inst": "Yale University" + }, + { + "author_name": "Santos Bermejo", + "author_inst": "Yale University" + }, + { + "author_name": "De Chang", + "author_inst": "Yale University" + }, + { + "author_name": "Lokesh Sharma", + "author_inst": "Yale University" + }, + { + "author_name": "Charles Dela Cruz", + "author_inst": "Yale University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.04.17.20069567", @@ -1548974,57 +1549867,25 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.17.20068577", - "rel_title": "Aerosolized Hydrogen Peroxide Decontamination of N95 Respirators, with Fit-Testing and Virologic Confirmation of Suitability for Re-Use During the COVID-19 Pandemic", + "rel_doi": "10.1101/2020.04.16.20068031", + "rel_title": "Psychological impact of infectious disease outbreaks on pregnant women: Rapid evidence review", "rel_date": "2020-04-22", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20068577", - "rel_abs": "In response to the demand for N95 respirators by healthcare workers during the COVID-19 pandemic, we evaluated decontamination of N95 respirators using an aerosolized hydrogen peroxide (aHP) system. This system is designed to dispense a consistent atomized spray of aerosolized, 7% hydrogen peroxide (H2O2) solution over a treatment cycle. Multiple N95 respirator models were subjected to ten or more cycles of respirator decontamination, with a select number periodically assessed for qualitative and quantitative fit testing. In parallel, we assessed the ability of aHP treatment to inactivate multiple viruses absorbed onto respirators, including phi6 bacteriophage, HSV-1, CVB3, and SARS-CoV-2. For pathogens transmitted via respiratory droplets and aerosols, it is critical to address respirator safety for reuse. This study provided experimental validation of an aHP treatment process that decontaminates the respirators while maintaining N95 function. External NIOSH certification verified respirator structural integrity and filtration efficiency after ten rounds of aHP treatment. Virus inactivation by aHP was comparable to the decontamination of commercial spore-based biological indicators. These data demonstrate that the aHP process is effective, with successful fit-testing of respirators after multiple aHP cycles, effective decontamination of multiple virus species including SARS-CoV- 2, successful decontamination of bacterial spores, and filtration efficiency maintained at or greater than 95%. While this study did not include extended or clinical use of N95 respirators between aHP cycles, these data provide proof of concept for aHP decontamination of N95 respirators before reuse in a crisis-capacity scenario.\n\nImportanceThe COVID-19 pandemic led to unprecedented pressure on healthcare and research facilities to provide personal protective equipment. The respiratory nature of the SARS-CoV2 pathogen makes respirator facepieces a critical protection measure to limit inhalation of this virus. While respirator facepieces were designed for single-use and disposal, the pandemic increased overall demand for N95 respirators, and corresponding manufacturing and supply chain limitations necessitated the safe reuse of respirators when necessary. In this study, we repurposed an aerosolized hydrogen peroxide (aHP) system that is regularly utilized to decontaminate materials in a biosafety level 3 (BSL3) facility, to develop methods for decontamination of N95 respirators. Results from virus inactivation, biological indicators, respirator fit testing, and filtration efficiency testing all indicated that the process was effective at rendering N95 respirators safe for reuse. This proof-of-concept study establishes baseline data for future testing of aHP in crisis capacity respirator-reuse scenarios.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20068031", + "rel_abs": "Infectious disease outbreaks can be distressing for everyone, especially so for those deemed to be particularly vulnerable, such as pregnant women who have been named a high-risk group in the current COVID-19 pandemic. This rapid review aimed to summarise existing literature on the psychological impact of infectious disease outbreaks on women who were pregnant at the time of the outbreak. In April 2020 five databases were searched for relevant literature and main findings were extracted. Thirteen papers were included in the review. The following themes were identified: negative emotional states; living with uncertainty; concerns about infection; concerns about and uptake of prophylaxis or treatment; disrupted routines; non-pharmaceutical protective behaviours; social support; demands from others; financial and occupational concerns; disrupted expectations of birth, prenatal care and postnatal care, and; sources of information. Results showed that pregnant women have unique needs during infectious disease outbreaks and could benefit from: up-to-date, consistent information and guidance; appropriate support and advice from healthcare professionals, particularly with regards to the risks and benefits of prophylaxis and treatment; virtual support groups, and; designating locations or staff specifically for pregnant women.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "T. Hans Derr", - "author_inst": "Pennsylvania State University" - }, - { - "author_name": "Melissa A. James", - "author_inst": "Pennsylvania State University" - }, - { - "author_name": "Chad V. Kuny", - "author_inst": "Pennsylvania State University" - }, - { - "author_name": "Devanshi Patel", - "author_inst": "Pennsylvania State University" - }, - { - "author_name": "Prem P. Kandel", - "author_inst": "Pennsylvania State University" - }, - { - "author_name": "Cassandra Field", - "author_inst": "Pennsylvania State University" - }, - { - "author_name": "Matthew D. Beckman", - "author_inst": "Pennsylvania State University" - }, - { - "author_name": "Kevin L. Hockett", - "author_inst": "Pennsylvania State University" - }, - { - "author_name": "Mark A. Bates", - "author_inst": "Pennsylvania State University" + "author_name": "Samantha K Brooks", + "author_inst": "King's College London" }, { - "author_name": "Troy C Sutton", - "author_inst": "Pennsylvania State University" + "author_name": "Dale Weston", + "author_inst": "Public Health England" }, { - "author_name": "Moriah L Szpara", - "author_inst": "Pennsylvania State University" + "author_name": "Neil Greenberg", + "author_inst": "King's College London" } ], "version": "1", @@ -1550296,27 +1551157,59 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.19.20071951", - "rel_title": "Seasonality and uncertainty in COVID-19 growth rates", - "rel_date": "2020-04-22", + "rel_doi": "10.1101/2020.04.17.20057125", + "rel_title": "COVID-19 Critical Illness Pathophysiology Driven by Diffuse Pulmonary Thrombi and Pulmonary Endothelial Dysfunction Responsive to Thrombolysis", + "rel_date": "2020-04-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.19.20071951", - "rel_abs": "The virus causing COVID-19 has spread rapidly worldwide and threatens millions of lives. It remains unknown if summer weather will reduce its continued spread, thereby alleviating strains on hospitals and providing time for vaccine development. Early insights from laboratory studies of related coronaviruses predicted that COVID-19 would decline at higher temperatures, humidity, and ultraviolet light. Using current, fine-scaled weather data and global reports of infection we developed a model that explained 36% of variation in early growth rates before intervention, with 17% based on weather or demography and 19% based on country-specific effects. We found that ultraviolet light was most strongly associated with lower COVID-19 growth rates. Projections suggest that, in the absence of intervention, COVID-19 will decrease temporarily during summer, rebound by autumn, and peak next winter. However, uncertainty remains high and the probability of a weekly doubling rate remained >20% throughout the summer in the absence of control. Consequently, aggressive policy interventions will likely be needed in spite of seasonal trends.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.17.20057125", + "rel_abs": "Critically ill COVID-19 patients have relatively well-preserved lung mechanics despite severe gas exchange abnormalities, a feature not consistent with classical ARDS but more consistent with pulmonary vascular disease. Patients with severe COVID-19 also demonstrate markedly abnormal coagulation, with elevated D-dimers and higher rates of venous thromboembolism. We present four cases of patients with severe COVID-19 pneumonia with severe respiratory failure and shock who demonstrated immediate improvements in gas exchange and/or hemodynamics with systemic tPA.\n\nSubject category4.6 ICU Management and Outcome", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Cory Merow", - "author_inst": "University of Connecticut" + "author_name": "Hooman D Poor", + "author_inst": "Icahn School of Medicine at Mount Sinai" }, { - "author_name": "Mark C Urban", - "author_inst": "University of Connecticut" + "author_name": "Corey E. Ventetuolo", + "author_inst": "Alpert Medical School of Brown University" + }, + { + "author_name": "Thomas Tolbert", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Glen Chun", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Gregory Serrao", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Amanda Zeidman", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Neha S. Dangayach", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Jeffrey Olin", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Roopa Kohli-Seth", + "author_inst": "Icahn School of Medicine at Mount Sinai" + }, + { + "author_name": "Charles A. Powell", + "author_inst": "Icahn School of Medicine at Mount Sinai" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.04.20.20073304", @@ -1551782,25 +1552675,73 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.16.20067553", - "rel_title": "Early forecasts of the evolution of the COVID-19 outbreaks and quantitative assessment of the effectiveness of countering measures.", + "rel_doi": "10.1101/2020.04.16.20067504", + "rel_title": "The effect of inter-city travel restrictions on geographical spread of COVID-19: Evidence from Wuhan, China", "rel_date": "2020-04-21", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20067553", - "rel_abs": "We discovered that the time evolution of the inverse fractional daily growth of new infections, N/{Delta} N, in the current outbreak of COVID-19 is accurately described by a universal function, namely the two-parameter Gumbel cumulative function, in all countries that we have investigated. While the two Gumbel parameters, as determined bit fits to the data, vary from country to country (and even within different regions of the same country), reflecting the diversity and efficacy of the adopted containment measures, the functional form of the evolution of {Delta} N/N appears to be universal. The result of the fit in a given region or country appears to be stable against variations of the selected time interval. This makes it possible to robustly estimate the two parameters from the data data even over relatively small time periods. In turn, this allows one to predict with large advance and well-controlled confidence levels, the time of the peak in the daily new infections, its magnitude and duration (hence the total infections), as well as the time when the daily new infections decrease to a pre-set value (e.g. less than about 2 new infections per day per million people), which can be very useful for planning the reopening of economic and social activities. We use this formalism to predict and compare these key features of the evolution of the COVID-19 disease in a number of countries and provide a quantitative assessment of the degree of success in in their efforts to countain the outbreak.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.16.20067504", + "rel_abs": "BackgroundTo contain the spread of COVID-19, a cordon sanitaire was put in place in Wuhan prior to the Lunar New Year, on 23 January 2020, restricting travel to other parts of China. We assess the efficacy of the cordon sanitaire to delay the introduction and onset of local transmission of COVID-19 in other major cities in mainland China.\n\nMethodsWe estimated the number of infected travellers from Wuhan to other major cities in mainland China from November 2019 to March 2020 using previously estimated COVID-19 prevalence in Wuhan and publicly available mobility data. We focused on Beijing, Chongqing, Hangzhou, and Shenzhen as four representative major cities to identify the potential independent contribution of the cordon sanitaire and holiday travel. To do this, we simulated outbreaks generated by infected arrivals in these destination cities using stochastic branching processes. We also modelled the effect of the cordon sanitaire in combination with reduced transmissibility scenarios representing the effect of local non-pharmaceutical interventions.\n\nFindingsIn the four cities, given the potentially high prevalence of COVID-19 in Wuhan between Dec 2019 and early Jan 2020, local transmission may have been seeded as early as 2 - 8 January 2020. By the time the cordon sanitaire was imposed, simulated case counts were likely in the hundreds. The cordon sanitaire alone did not substantially affect the epidemic progression in these cities, although it may have had some effect in smaller cities.\n\nInterpretationOur results indicate that the cordon sanitaire may not have prevented COVID-19 spread in major Chinese cities; local non-pharmaceutical interventions were likely more important for this.\n\nResearch in ContextO_ST_ABSEvidence before this studyC_ST_ABSIn late 2019, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was detected in Wuhan, China. In response to the outbreak, authorities enacted a cordon sanitaire in order to limit spread. Several studies have sought to determine the efficacy of the policy; a search of PubMed for \"coronavirus AND (travel restrictions OR travel ban OR shutdown OR cordon sanitaire) AND (Wuhan OR China)\" returned 24 results. However other studies have relied on reported cases to determine efficacy, which are likely subject to reporting and testing biases. Early outbreak dynamics are also subject to a significant degree of stochastic uncertainty due to small numbers of cases.\n\nAdded value of this studyHere we use publicly-available mobility data and a stochastic branching process model to evaluate the efficacy of the cordon sanitaire to limiting the spread of COVID-19 from Wuhan to other cities in mainland China, while accounting for underreporting and uncertainty. We find that although travel restrictions led to a significant decrease in the number of individuals leaving Wuhan during the busy post-Lunar New Year holiday travel period, local transmission was likely already established in major cities. Thus, the travel restrictions likely did not affect the epidemic trajectory substantially in these cities.\n\nImplications of all the available evidenceA cordon sanitaire around the epicentre alone may not be able to reduce COVID-19 incidence when implemented after local transmission has occurred in highly connected neighbors. Local non-pharmaceutical interventions to reduce transmissibility (e.g., school and workplace closures) may have contributed more to the observed decrease in incidence in mainland China.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Emanuele Daddi", - "author_inst": "CEA Saclay" + "author_name": "Billy J Quilty", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Charlie Diamond", + "author_inst": "London School of Hygiene and Tropical Medicine" }, { - "author_name": "Mauro Giavalisco", - "author_inst": "University of Massachusetts Amherst" + "author_name": "Yang Liu", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Hamish Gibbs", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Timothy W Russell", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Christopher I Jarvis", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Kiesha Prem", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Carl A B Pearson", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Samuel J Clifford", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Stefan Flasche", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "CMMID COVID-19 working group", + "author_inst": "" + }, + { + "author_name": "Petra Klepac", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Rosalind M Eggo", + "author_inst": "London School of Hygiene and Tropical Medicine" + }, + { + "author_name": "Mark Jit", + "author_inst": "London School of Hygiene and Tropical Medicine" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1553808,303 +1554749,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.15.20066407", - "rel_title": "Evaluation of antibody testing for SARS-Cov-2 using ELISA and lateral flow immunoassays", + "rel_doi": "10.1101/2020.04.15.20067074", + "rel_title": "Total COVID-19 Mortality in Italy: Excess Mortality and Age Dependence through Time-Series Analysis", "rel_date": "2020-04-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.15.20066407", - "rel_abs": "BackgroundThe COVID-19 pandemic caused >1 million infections during January-March 2020. There is an urgent need for reliable antibody detection approaches to support diagnosis, vaccine development, safe release of individuals from quarantine, and population lock-down exit strategies. We set out to evaluate the performance of ELISA and lateral flow immunoassay (LFIA) devices.\n\nMethodsWe tested plasma for COVID (SARS-CoV-2) IgM and IgG antibodies by ELISA and using nine different LFIA devices. We used a panel of plasma samples from individuals who have had confirmed COVID infection based on a PCR result (n=40), and pre-pandemic negative control samples banked in the UK prior to December-2019 (n=142).\n\nResultsELISA detected IgM or IgG in 34/40 individuals with a confirmed history of COVID infection (sensitivity 85%, 95%CI 70-94%), vs. 0/50 pre-pandemic controls (specificity 100% [95%CI 93-100%]). IgG levels were detected in 31/31 COVID-positive individuals tested [≥]10 days after symptom onset (sensitivity 100%, 95%CI 89-100%). IgG titres rose during the 3 weeks post symptom onset and began to fall by 8 weeks, but remained above the detection threshold. Point estimates for the sensitivity of LFIA devices ranged from 55-70% versus RT-PCR and 65-85% versus ELISA, with specificity 95-100% and 93-100% respectively. Within the limits of the study size, the performance of most LFIA devices was similar.\n\nConclusionsCurrently available commercial LFIA devices do not perform sufficiently well for individual patient applications. However, ELISA can be calibrated to be specific for detecting and quantifying SARS-CoV-2 IgM and IgG and is highly sensitive for IgG from 10 days following first symptoms.", - "rel_num_authors": 71, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.15.20067074", + "rel_abs": "We perform a counterfactual time series analysis on 2020 mortality data from towns in Italy using data from the previous five years as control. We find an excess mortality that is correlated in time with the official COVID-19 death rate, but exceeds it by a factor of at least 1.5. Our analysis suggests that there is a large population of predominantly older people that are missing from the official fatality statistics. We estimate that the number of cOvID-19 deaths in Italy is 49,000-53,000 as of May 9 2020, as compared to the official number of 33,000. The Population Fatality Rate (PFR) has reached 0.26% in the most affected region of Lombardia and 0.58% in the most affected province of Bergamo. These PFRs constitutes a lower bound to the Infection Fatality Rate (IFR). We combine the PFRs with the Test Positivity Ratio to derive the lower bound of 0.61% on the IFR for Lombardia. We further estimate the IFR as a function of age and find a steeper age dependence than previous studies: we find 17% of COVID-related deaths are attributed to the age group above 90, 7.5% to 80-89, declining to 0.04% for age 40-49 and 0.01% for age 30-39, the latter more than an order of magnitude lower than previous estimates. We observe that the IFR traces the Yearly Mortality Rate (YMR) above ages of 60 years, which can be used as a model to estimate the IFR for other populations and thus other regions in the world. We predict an IFR lower bound of 0.5% for NYC and that 27% of the total COVID-19 fatalities in NYC should arise from the population below 65 years. This is in agreement with the official NYC data and three times higher than the percentage observed in Lombardia. Combining the PFR with the Princess Diamond cruise ship IFR for ages above 70 we estimate the infection rates (IR) for regions in Italy. These peak in Lombardia at 26% (13%-47%, 95% c.l.), and for provinces in Bergamo at 69% (35%-100%, 95% c.I.). These estimates suggest that the number of infected people greatly exceeds the number of positive tests, e.g., by a factor of 35 in Lombardia.*", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Emily R Adams", - "author_inst": "Liverpool School of Tropical Medicine" - }, - { - "author_name": "Mark Ainsworth", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Rekha Anand", - "author_inst": "NHSBT Birmingham," - }, - { - "author_name": "Monique I Andersson", - "author_inst": "Department of Microbiology, Oxford University Hospital NHS Foundation Trust" - }, - { - "author_name": "Kathryn Auckland", - "author_inst": "The Wellcome Centre for Human Genetics, University of Oxford" - }, - { - "author_name": "J Kenneth Baillie", - "author_inst": "Roslin Institute, University of Edinburgh" - }, - { - "author_name": "Eleanor Barnes", - "author_inst": "Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Sally Beer", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "John Bell", - "author_inst": "Department of Medicine, University of Oxford" - }, - { - "author_name": "Tamsin Berry", - "author_inst": "Department of Health and Social Care, University of Oxford" - }, - { - "author_name": "Sagida Bibi", - "author_inst": "Oxford Vaccine group, Department of Pediatrics, University of Oxford" - }, - { - "author_name": "Miles Carroll", - "author_inst": "Nuffield Department of Medicine, Centre of Tropical Medicine and Global Health and Public Health England" - }, - { - "author_name": "Senthil Chinnakannan", - "author_inst": "Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Elizabeth Clutterbuck", - "author_inst": "Oxford Vaccine Group, Department of Paediatrics, University of Oxford" - }, - { - "author_name": "Richard J Cornall", - "author_inst": "Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Derrick W Crook", - "author_inst": "NIHR Oxford Biomedical Research Centre" - }, - { - "author_name": "Thushan De Silva", - "author_inst": "Department of Infection, Immunity and Cardiovascular, Disease, The Medical School, University of Sheffield" - }, - { - "author_name": "Wanwisa Dejnirattisai", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Kate E Dingle", - "author_inst": "NIHR Oxford Biomedical Research Centre, University of Oxford" - }, - { - "author_name": "Christina Dold", - "author_inst": "Oxford Vaccine Group, Department of Paediatrics, University of Oxford" - }, - { - "author_name": "Alexis Espinosa", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "David W Eyre", - "author_inst": "Big Data Institute, University of Oxford" - }, - { - "author_name": "Helen Farmer", - "author_inst": "Department of Health and Social Care, University of Oxford" - }, - { - "author_name": "Maria Fernandez Mendoza", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Dominique Georgiou", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Sarah J Hoosdally", - "author_inst": "Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Alistair Hunter", - "author_inst": "NHSBT Basildon" - }, - { - "author_name": "Katie Jeffrey", - "author_inst": "Department of Clinical Medicine, Oxford University Hospitals NHS Foundation Trusts" - }, - { - "author_name": "Paul Klenerman", - "author_inst": "Nuffield Department so Medicine, University of Oxford" - }, - { - "author_name": "Julian Knight", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Clarice Knowles", - "author_inst": "Department of Health and Social Care, University of Oxford" - }, - { - "author_name": "Andrew J Kwok", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Ullrich Leuschner", - "author_inst": "NHSBT Oxford" - }, - { - "author_name": "Robert Levin", - "author_inst": "Worthing Hospital, Worthing, West Sussex" - }, - { - "author_name": "Chang Liu", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Cesar Lopez-Camacho", - "author_inst": "Wellcome Centre of Genetics, Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Jose Carlos Martinez Garrido", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Philippa C Matthews", - "author_inst": "Nuffield Department of Medicine, University of Medicine" - }, - { - "author_name": "Hannah McGivern", - "author_inst": "Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium" - }, - { - "author_name": "Alexander J Mentzer", - "author_inst": "Wellcome Centre for Human Genetics, University of Oxford" - }, - { - "author_name": "Jonathan Milton", - "author_inst": "Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium" - }, - { - "author_name": "Juthathip Mongkolsapaya", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Shona C Moore", - "author_inst": "NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, University of Liverpool" - }, - { - "author_name": "Marta S Oliveira", - "author_inst": "Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium" - }, - { - "author_name": "Fiona Pereira", - "author_inst": "Imperial College London" - }, - { - "author_name": "Elena Perez Lopez", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Timothy Peto", - "author_inst": "NIHR Oxford Biomedical Research centre, University of Oxford" - }, - { - "author_name": "Rutger J Ploeg", - "author_inst": "Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium" - }, - { - "author_name": "Andrew Pollard", - "author_inst": "Department of Paediatrics, University of Oxford" - }, - { - "author_name": "Tessa Prince", - "author_inst": "NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, University of Liverpool" - }, - { - "author_name": "David J Roberts", - "author_inst": "NHSBT Oxford" - }, - { - "author_name": "Justine K Rudkin", - "author_inst": "Nuffield Department of Population Health & Big Data Institute, University of Oxford" - }, - { - "author_name": "Veronica Sanchez", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Gavin R Screaton", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Malcolm G Semple", - "author_inst": "Health Protection Unit In Emerging and Zoonotic Infection, University of Liverpool" - }, - { - "author_name": "Donal T Skelly", - "author_inst": "Nuffield Department of Clinical Neurosciences, University of Oxford" - }, - { - "author_name": "Jose Slon-Campos", - "author_inst": "University of Oxford" - }, - { - "author_name": "Elliot Nathan Smith", - "author_inst": "Department of Health and Social Care, University of Oxford" - }, - { - "author_name": "Alberto Jose Sobrino Diaz", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Julie Staves", - "author_inst": "Oxford University Hospitals," - }, - { - "author_name": "David Stuart", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine" - }, - { - "author_name": "Piyada Supasa", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford" - }, - { - "author_name": "Tomas Surik", - "author_inst": "Nuffield Department of Surgical Sciences, University of Oxford and UK QUOD Consortium" - }, - { - "author_name": "Hannah Thraves", - "author_inst": "Oxford University Hospitals NHS Foundation Trust" - }, - { - "author_name": "Pat Tsang", - "author_inst": "NHSBT Oxford" - }, - { - "author_name": "Lance Turtle", - "author_inst": "NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, University of Liverpool" - }, - { - "author_name": "A Sarah Walker", - "author_inst": "Nuffield Department of Medicine, University of Oxford" + "author_name": "Chirag Modi", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Beibei Wang", - "author_inst": "Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford" + "author_name": "Vanessa Boehm", + "author_inst": "University of California, Berkeley" }, { - "author_name": "Charlotte Washington", - "author_inst": "NHSBT, Birmingham" + "author_name": "Simone Ferraro", + "author_inst": "Lawrence Berkeley National Lab" }, { - "author_name": "Nicholas Watkins", - "author_inst": "NHSBT, Cambridge" + "author_name": "George Stein", + "author_inst": "University of California, Berkeley" }, { - "author_name": "James Whitehouse", - "author_inst": "Department of Health and Social Care, University of Oxford" + "author_name": "Uros Seljak", + "author_inst": "University of California, Berkeley" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.15.20067058", @@ -1555578,31 +1556255,119 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.04.13.20064295", - "rel_title": "Benefits and Risks of Chloroquine and Hydroxychloroquine in The Treatment of Viral Diseases: A Meta-Analysis of Placebo Randomized Controlled Trials", + "rel_doi": "10.1101/2020.04.15.037564", + "rel_title": "Supramolecular Organization Predicts Protein Nanoparticle Delivery to Neutrophils for Acute Lung Inflammation Diagnosis and Treatment", "rel_date": "2020-04-18", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20064295", - "rel_abs": "Background and ObjectiveRecently, in the scramble to find drugs to treat COVID-19, chloroquine (CQ) and its derivative hydroxychloroquine (HCQ) have rapidly gained the publics attention. In this study, we conducted a meta-analysis of randomized clinical trials (RCTs) to evaluate the efficacy and safety of CQ and HCQ in the treatment of viral diseases.\n\nMethodsWe searched PubMed, EMBASE, Cochrane Central, Web of Science, Clinical Trials Registries, CNKI, Wanfang Data, CQVIP, and Preprint Servers through April 4, 2020, for randomized controlled trials (RCTs) that examined the efficacy and safety of CQ and HCQ against viral infection. We analyzed pooled data on the overall efficacy, the relative risks over the placebo, and the prevalence of adverse events. Trial sequential analysis (TSA) was also performed to evaluate the random errors in the meta-analysis. Potential moderators of drug-placebo efficacy differences were analyzed by meta-regression.\n\nResultsThe analysis included 11 RCTs with 2613 adult patients. Both the plasma viral load (standard mean difference: 0.29, 95% CI: -1.19 - 1.76, P = 0.70) and the improvement of clinical symptoms (odds ratio: 2.36, 95% CI: 0.81 - 6.92, P = 0.11) were not different between the intervention and placebo arm. There was significant heterogeneity for the efficacy assessment, which was primarily explained by the mean patients age and the sample size. Compared to the placebo, CQ and HCQ had increased risk of mild adverse events (risk ratio: 1.51, 95% CI: 1.35 - 1.70, P < 0.05, TSA adjusted 95% CI: 1.31 - 2.19), which were statistically significant in nervous, integumentary, and gastrointestinal systems. The most common adverse events were observed in the nervous system, with the pooled prevalence of 31.4 % (95% CI: 10.5% - 56.7%).\n\nConclusionsInsufficient data were available to support the antiviral efficacy of CQ and HCQ due to the high heterogeneity caused by patients age. Mild side effects are expected for the current antiviral dose regimens of CQ and HCQ. Treatment outcomes may be enhanced by better-selected patients based on age and well-controlled adverse events.\n\nThis meta-analysis was registered on OSF (ID: https://osf.io/386aw)", - "rel_num_authors": 3, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.15.037564", + "rel_abs": "Acute lung inflammation has severe morbidity, as seen in COVID-19 patients. Lung inflammation is accompanied or led by massive accumulation of neutrophils in pulmonary capillaries (\"margination\"). We sought to identify nanostructural properties that predispose nanoparticles to accumulate in pulmonary marginated neutrophils, and therefore to target severely inflamed lungs. We designed a library of nanoparticles and conducted an in vivo screen of biodistributions in naive mice and mice treated with lipopolysaccharides. We found that supramolecular organization of protein in nanoparticles predicts uptake in inflamed lungs. Specifically, nanoparticles with agglutinated protein (NAPs) efficiently home to pulmonary neutrophils, while protein nanoparticles with symmetric structure (e.g. viral capsids) are ignored by pulmonary neutrophils. We validated this finding by engineering protein-conjugated liposomes that recapitulate NAP targeting to neutrophils in inflamed lungs. We show that NAPs can diagnose acute lung injury in SPECT imaging and that NAP-like liposomes can mitigate neutrophil extravasation and pulmonary edema arising in lung inflammation. Finally, we demonstrate that ischemic ex vivo human lungs selectively take up NAPs, illustrating translational potential. This work demonstrates that structure-dependent interactions with neutrophils can dramatically alter the biodistribution of nanoparticles, and NAPs have significant potential in detecting and treating respiratory conditions arising from injury or infections.", + "rel_num_authors": 25, "rel_authors": [ { - "author_name": "Jing Wang", - "author_inst": "Yantai Yuhuangding Hospital, China" + "author_name": "Jacob W Myerson", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Li Yu", - "author_inst": "Shengjing Hospital of China Medical University" + "author_name": "Priyal N Patel", + "author_inst": "University of Pennsylvania" }, { - "author_name": "Kefeng Li", - "author_inst": "University of California, San Diego" + "author_name": "Nahal Habibi", + "author_inst": "University of Michigan at Ann Arbor" + }, + { + "author_name": "Landis R Walsh", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Yi-Wei Lee", + "author_inst": "University of Massachusetts at Amherst" + }, + { + "author_name": "David C Luther", + "author_inst": "University of Massachusetts at Amherst" + }, + { + "author_name": "Laura T Ferguson", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Michael H Zaleski", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Marco E Zamora", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Oscar A. Marcos-Contreras", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Patrick M Glassman", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Ian Johnston", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Elizabeth D Hood", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Tea Shuvaeva", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Jason V Gregory", + "author_inst": "University of Michigan" + }, + { + "author_name": "Raisa Y Kiseleva", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Jia Nong", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Kathryn M Rubey", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Colin F Greineder", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Samir Mitragotri", + "author_inst": "Harvard University" + }, + { + "author_name": "George S Worthen", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Vincent M Rotello", + "author_inst": "University of Massachusetts at Amherst" + }, + { + "author_name": "Joerg Lahann", + "author_inst": "University of Michigan" + }, + { + "author_name": "Vladimir R Muzykantov", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Jacob S Brenner", + "author_inst": "University of Pennsylvania" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "PUBLISHAHEADOFPRINT", - "category": "pharmacology and therapeutics" + "type": "new results", + "category": "bioengineering" }, { "rel_doi": "10.1101/2020.04.16.043273", @@ -1557280,69 +1558045,29 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.15.20065995", - "rel_title": "SARS-Cov-2 RNA Found on Particulate Matter of Bergamo in Northern Italy: First Preliminary Evidence", + "rel_doi": "10.1101/2020.04.15.20066308", + "rel_title": "Analysis of the mitigation strategies for COVID-19: from mathematical modelling perspective", "rel_date": "2020-04-18", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.15.20065995", - "rel_abs": "In previous communications, we have hypothesized the possibility that SARS-CoV-2 virus could be present on particulate matter (PM) during the spreading of the infection, consistently with evidence already available for other viruses. Here, we present the first results of the analyses that we have performed on 34 PM10 samples of outdoor/airborne PM10 from an industrial site of Bergamo Province, collected with two different air samplers over a continuous 3-weeks period, from February 21st to March 13th. We can confirm to have reasonably demonstrated the presence of SARS-CoV-2 viral RNA by detecting highly specific RtDR gene on 8 filters in two parallel PCR analyses. This is the first preliminary evidence that SARS-CoV-2 RNA can be present on outdoor particulate matter, thus suggesting that, in conditions of atmospheric stability and high concentrations of PM, SARS-CoV-2 could create clusters with outdoor PM and, by reducing their diffusion coefficient, enhance the persistence of the virus in the atmosphere. Further confirmations of this preliminary evidence are ongoing, and should include real-time assessment about the vitality of the SARS-CoV-2 as well as its virulence when adsorbed on particulate matter. At the present, no assumptions can be made concerning the correlation between the presence of the virus on PM and COVID-19 outbreak progression. Other issues to be specifically addressed are the average concentrations of PM eventually required for a potential boost effect of the contagion (in case it is confirmed that PM might act as a carrier for the viral droplet nuclei), or even the theoretic possibility of immunization consequent to minimal dose exposures at lower thresholds of PM.", - "rel_num_authors": 13, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.15.20066308", + "rel_abs": "In this article, a mathematical model for the transmission of COVID-19 disease is formulated and analysed. It is shown that the model exhibits a backward bifurcation at [R]0 = 1 when recovered individuals do not develop a permanent immunity for the disease. In the absence of reinfection, it is proved that the model is without backward bifurcation and the disease free equilibrium is globally asymptotically stable for [R]0 < 1. By using available data, the model is validated and parameter values are estimated. The sensitivity of the value of [R]0 to changes in any of the parameter values involved in its formula is analysed. Moreover, various mitigation strategies are investigated using the proposed model and it is observed that the asymptomatic infectious group of individuals may play the major role in the re-emergence of the disease in the future. Therefore, it is recommended that in the absence of vaccination, countries need to develop capacities to detect and isolate at least 30% of the asymptomatic infectious group of individuals while treating in isolation at least 50% of symptomatic patients to control the disease.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Leonardo Setti", - "author_inst": "University of Bologna" - }, - { - "author_name": "Fabrizio Passarini", - "author_inst": "University of Bologna" - }, - { - "author_name": "Gianluigi De Gennaro", - "author_inst": "University of Bari, Italy" - }, - { - "author_name": "Pierluigi Baribieri", - "author_inst": "University of Trieste" - }, - { - "author_name": "Maria Grazia Perrone", - "author_inst": "Environmental Research Division, TCR TECORA, Milan, Italy" - }, - { - "author_name": "Massimo Borelli", - "author_inst": "University of Trieste, Italy" - }, - { - "author_name": "Jolanda Palmisani", - "author_inst": "University of Bari" - }, - { - "author_name": "Alessia Di Gilio", - "author_inst": "University of Bari" - }, - { - "author_name": "Valentina Torboli", - "author_inst": "University of Trieste" - }, - { - "author_name": "Alberto Pallavicini", - "author_inst": "University of Trieste" + "author_name": "Semu Kassa", + "author_inst": "Botswana International University of Science and Technology" }, { - "author_name": "Maurizio Ruscio", - "author_inst": "Division of Laboratory Medicine, University Hospital Giuliano Isontina (ASU GI), Trieste, Italy" + "author_name": "Hatson John Boscoh Njagarah", + "author_inst": "Botswana International University of Science and Technology" }, { - "author_name": "PRISCO PISCITELLI", - "author_inst": "ISBEM" - }, - { - "author_name": "Alessandro Miani", - "author_inst": "Italian Society of Environmental Medicine, SIMA, Milan, Italy" + "author_name": "Yibeltal Adane Terefe", + "author_inst": "University of Limpopo" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1558898,33 +1559623,25 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.14.20065375", - "rel_title": "Informing Homemade Emergency Facemask Design: The Ability of Common Fabrics to Filter Ultrafine Particles", + "rel_doi": "10.1101/2020.04.14.20065607", + "rel_title": "Applying the SEIR Model in Forecasting The COVID-19 Trend in Malaysia: A Preliminary Study", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20065375", - "rel_abs": "ObjectivesWe examined the ability of fabrics which might be used to create homemade face masks to filter out ultrafine (0.1m and smaller in diameter) particles at the velocity of adult human coughing.\n\nMethodTwenty commonly available fabrics and materials were evaluated for their ability to reduce air concentrations of ultrafine particles at a face velocity of 16.5 m/s. Further assessment was made on the filtration ability of select fabrics while damp and of fabric combinations which might be used to construct homemade masks.\n\nResultsSingle fabric layers blocked a range of ultrafine particles. When fabrics were layered, significantly more ultrafine particles were filtered. Nonwoven fusible interfacing significantly increased filtration.\n\nConclusionsThe current coronavirus pandemic has left many communities without access N95 facemasks. Our findings suggest that face masks made from layered common fabric can help filter ultrafine particles and provide some protection for the wearer when commercial facemasks are unavailable.\n\nSTRENGHTS AND LIMITATIONS OF THIS STUDYO_LITested a large number of potential facemask materials, including materials currently in common use such as Lycra which have not been previously tested\nC_LIO_LIEvaluated filtration efficiency at coughing velocities, more closely mimicking use-case of masks worn for community protection than previous studies\nC_LIO_LIAssess the data from prior published work and current study, creating a picture of Filtration Efficiency and the impact of velocity\nC_LIO_LIDid not discriminate between pathogenic and non-pathogenic particles\nC_LIO_LIBreathing resistance was estimated based on qualitative feedback\nC_LI", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20065607", + "rel_abs": "On March 18, 2020 the Malaysian government implemented a 14-day Movement Control Order (MCO) as part of the mitigation plan in controlling the COVID-19 epidemic in the country. The MCO aims to limit the contact rates among the population and hence prevent the surge of infected individuals. However, the trend of the epidemic before and after the MCO was not apparent. By applying the Susceptible, Exposed, Infectious and Removed (SEIR) mathematical model, we aimed to forecast the trend of COVID-19 epidemic in Malaysia using data from March 17 to 27, 2020. Based on several predetermined assumptions, the results of the analyses showed that after the implementation of the 14-day MCO from March 18 to 31, 2020, it is forecasted that the epidemic in Malaysia will peak approximately in the end of April 2020 and will subside by about the first week of July 2020. The MCO will \"flatten the epidemic curve\" but will prolong the duration of the epidemic. Decision to extend the duration of the MCO should depend on the consideration of socioeconomic factors as well.\n\nAuthor summaryDr. Aidalina Mahmud is a Public Health Specialist and a medical lecturer in the Department of Community Health, Universiti Putra Malaysia. Dr. Lim Poh Ying is a Biostatistician and is a senior lecturer in the Department of Community Health, Universiti Putra Malaysia.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Eugenia O'Kelly", - "author_inst": "Cambridge University" - }, - { - "author_name": "Sophia Pirog", - "author_inst": "Northwestern University" - }, - { - "author_name": "James Ward", - "author_inst": "Cambridge University" + "author_name": "Aidalina Mahmud", + "author_inst": "Universiti Putra Malaysia" }, { - "author_name": "P John Clarkson", - "author_inst": "Cambridge University" + "author_name": "Poh Ying Lim", + "author_inst": "Univeristi Putra Malaysia" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "public and global health" }, @@ -1560248,25 +1560965,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.14.20065318", - "rel_title": "State-level variation of initial COVID-19 dynamics in the United States: The role of local government interventions", + "rel_doi": "10.1101/2020.04.14.20065342", + "rel_title": "Estimate of COVID-19 case prevalence in India based on surveillance data of patients with severe acute respiratory illness", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20065318", - "rel_abs": "During an epidemic, metrics such as R0, doubling time, and case fatality rates are important in understanding and predicting the course of an epidemic. However, if collected over country or regional scales, these metrics hide important smaller-scale, local dynamics. We examine how commonly used epidemiological metrics differ for each individual state within the United States during the initial COVID-19 outbreak. We found that the case number, and trajectory of cases, differs considerably between states. We show that early non-pharmaceutical, government actions, were the most important determinant of epidemic dynamics. In particular, restricting restaurant operations was correlated with increased doubling times. Although individual states are clearly not independent, they can serve as small, natural experiments in how different demographic patterns and government responses can impact the course of an epidemic.\n\nDaily updates to figures in this manuscript are available at: https://github.com/eastonwhite/COVID19_US_States", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20065342", + "rel_abs": "In absence of extensive testing for SARS-CoV-2, true prevalence of COVID-19 cases in India remain unknown. In this study, a conservative estimate of prevalence of COVID-19 is calculated based on the age wise COVID-19 positivity rate among patients with severe respiratory illness as reported by Indian Council of Medical Research. Calculations in the study estimates a cumulative number of 17151 COVID-19 positive cases by the end of April 2, 2020.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Easton R White", - "author_inst": "University of Vermont" - }, - { - "author_name": "Laurent R H\u00e9bert-Dufresne", - "author_inst": "University of Vermont" + "author_name": "Padmanaban Venkatesan", + "author_inst": "Christian Medical College" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1561482,27 +1562195,39 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.12.20061929", - "rel_title": "Ad-hoc Assembly of Lean Extracorporeal Membrane Oxygenation Systems for COVID-19", + "rel_doi": "10.1101/2020.04.12.20062166", + "rel_title": "Immediate and Near Future Prediction of COVID-19 Patients in the U.S. Population Aged 65+ With the Prior Medical Conditions of Hypertension, Cardiovascular and Lung Diseases: Methods, Models and Acute Care Estimates", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.12.20061929", - "rel_abs": "BackgroundThe COVID-19 epidemic is overwhelming intensive care units with bilateral pneumonia patients requiring respiratory assistance. Bottlenecks in availability of ventilators and extracorporeal membrane oxygenation may contribute to mortality, implying ethically difficult rationing decisions. It is unclear if accelerated equipment production will meet demand, calling for fallback solutions for life support in worst-case scenarios.\n\nMethodsVeno-venous extracorporeal gas exchange (VV-ECMO) can provide vital support in bilateral lung failure. VV-ECMO essentially comprises large flow venous accesses, membrane gas exchange, and a blood pump. As thousands of FDA and CE certified Impella blood pumps and consoles are distributed globally for cardiac support, we explored ad-hoc assembly of lean ECMO systems by embedding Impella pumps coaxially in tubes in combination with standard gas exchangers.\n\nResultsAd-hoc integration of Impella blood pumps with gas exchange modules, standard cannulas for large bore venous access, regular ECMO tubing, Y-pieces and connectors led to lean ECMO systems with stable performance over several days. Oxygenation of 2.5-5 L of blood/minute is realistic. Benefit/risk analysis appears favorable if a patient requires respiratory support but cannot be supported because of lack of ventilators or unavailability of a required ECMO system.\n\nConclusionAd-hoc assembly of veno-venous ECMOs using Impella pumps is feasible and results in stable blood flow across gas exchange modules. However, such off-label use of the devices calls for specific ethical and regulatory considerations prior to their use as last resort in patients for whom no other treatment modalities are available.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.12.20062166", + "rel_abs": "ImportanceGiven the rapid rise of COVID-19 cases in the U.S. during March 2020 there has been a severe burden on the health care systems and care providers in the country. The impact of the virus so far was higher on the population aged 65+. Hospitalizations were higher among those with underlying medical conditions, namely, hypertension, cardiovascular and lung diseases. Hence, to have an idea of the number of new COVID-19 infections among these high-risk populations that could occur in the short-term could assist promptly to the countrys health care system for immediate health care planning. These estimates may aid us in better understanding the potential volumes of patients requiring inpatient care.\n\nObjectiveTo provide immediate and short-term model-based predictions of COVID-19 patients in the U.S. population aged 65+ during April-June, 2020, those with the prior medical conditions of hypertension, cardiovascular and lung diseases.\n\nDesign, Setting, and ParticipantsWe developed age-structured dynamic mathematical combined with wavelet analysis to understand the number of new cases that may emerge in the U.S. population aged 65+. We have estimated the number of people aged 65+ who might have three underlying conditions mentioned and a possible number of hospitalizations among them due to COVID-19 if they get infected. We have used publicly available data sources for developing our framework and estimates.\n\nResultsWe estimate that there are 13 million individuals aged 65+ who have one or a combination of three major prior medical conditions in the U.S. who need to be protected against COVID-19 to reduce a large number of hospitalizations and associated deaths. Hospitalizations of patients both with and without ICU-admissions with more prevalent underlying conditions could range between 31,633 (20,310 non-ICU hospitalizations and 11,323 ICU-admissions) to 94,666 (60,779 non-ICU hospitalizations and 33,866 ICU-admissions) cases during the same period. Under a rapid spread of the virus environment, these hospitalizations could be beyond 430,000 within the above three-month period.\n\nConclusions and RelevanceCOVID-19 continues to dramatically and adversely affect the lives of people aged 65+ in the U.S. During the next three months which could result in thousands of hospitalizations if precautions against the virus spread are not implemented and adhered to.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Patrick Hunziker", - "author_inst": "University Hospital Basel" + "author_name": "Arni S.R. Srinivasa Rao", + "author_inst": "Medical College of Gerogia" }, { - "author_name": "Urs Zenklusen", - "author_inst": "University Hospital Basel" + "author_name": "Douglas D Miller", + "author_inst": "Medical College of Georgia, Augusta University" + }, + { + "author_name": "Adam E Berman", + "author_inst": "Medical College of Georgia, Augusta University" + }, + { + "author_name": "David C Hess", + "author_inst": "Medical College of Georgia, Augusta University" + }, + { + "author_name": "Steven G Krantz", + "author_inst": "Washington University in St. Louis" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "intensive care and critical care medicine" + "category": "cardiovascular medicine" }, { "rel_doi": "10.1101/2020.04.12.20062893", @@ -1562584,49 +1563309,85 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.13.20062760", - "rel_title": "Estimates of regional infectivity of COVID-19in the United Kingdom following imposition of social distancingmeasures", + "rel_doi": "10.1101/2020.04.14.20062463", + "rel_title": "COVID-19 Antibody Seroprevalence in Santa Clara County, California", "rel_date": "2020-04-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20062760", - "rel_abs": "We describe regional variation in the reproduction number of SARS-CoV-2 infections observed using publicly reported data in the UK, with a view to understanding both if there are clear hot spots in viral spread in the country, or other spatial patterns. Based on case data up to the 9th April, we estimate that the viral replication number remains above 1 overall in the UK but that its trend is to decrease. This suggests the peak of the first wave of COVID-19 patients is imminent. We find that there is significant regional variation in the UK and that this is changing over time. Within England currently the reproductive ratio is lowest in the Midlands (1.11 95% CI 1.07; 1.14), and highest in the North East of England (1.38 95% CI 1.33-1.42). There are long and variable time delays between infection and detection of cases, and thus it remains unclear whether the reduction in the reproductive number is a result of social distancing measures. If we are to prevent further outbreaks, it is critical that we both reduce the time taken for detection and improve our ability to predict the regional spread of outbreaks.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.14.20062463", + "rel_abs": "BackgroundAddressing COVID-19 is a pressing health and social concern. To date, many epidemic projections and policies addressing COVID-19 have been designed without seroprevalence data to inform epidemic parameters. We measured the seroprevalence of antibodies to SARS-CoV-2 in a community sample drawn from Santa Clara County.\n\nMethodsOn April 3-4, 2020, we tested county residents for antibodies to SARS-CoV-2 using a lateral flow immunoassay. Participants were recruited using Facebook ads targeting a sample of individuals living within the county by demographic and geographic characteristics. We estimate weights to adjust our sample to match the zip code, sex, and race/ethnicity distribution within the county. We report both the weighted and unweighted prevalence of antibodies to SARS-CoV-2. We also adjust for test performance characteristics by combining data from 16 independent samples obtained from manufacturers data, regulatory submissions, and independent evaluations: 13 samples for specificity (3,324 specimens) and 3 samples for sensitivity (157 specimens).\n\nResultsThe raw prevalence of antibodies to SARS-CoV-2 in our sample was 1.5% (exact binomial 95CI 1.1-2.0%). Test performance specificity in our data was 99.5% (95CI 99.2-99.7%) and sensitivity was 82.8% (95CI 76.0-88.4%). The unweighted prevalence adjusted for test performance characteristics was 1.2% (95CI 0.7-1.8%). After weighting for population demographics of Santa Clara County, the prevalence was 2.8% (95CI 1.3-4.7%), using bootstrap to estimate confidence bounds. These prevalence point estimates imply that 54,000 (95CI 25,000 to 91,000 using weighted prevalence; 23,000 with 95CI 14,000-35,000 using unweighted prevalence) people were infected in Santa Clara County by early April, many more than the approximately 1,000 confirmed cases at the time of the survey.\n\nConclusionsThe estimated population prevalence of SARS-CoV-2 antibodies in Santa Clara County implies that the infection may be much more widespread than indicated by the number of confirmed cases. More studies are needed to improve precision of prevalence estimates. Locally-derived population prevalence estimates should be used to calibrate epidemic and mortality projections.", + "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Robert J Challen", - "author_inst": "EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, Devon, UK." + "author_name": "Eran Bendavid", + "author_inst": "Stanford University" }, { - "author_name": "Krasimira Tsaneva-Atanasova", - "author_inst": "EPSRC Centre for Predictive Modelling in Healthcare, University of Exeter, Exeter, Devon, UK." + "author_name": "Bianca Mulaney", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Martin Pitt", - "author_inst": "NIHR CLAHRC for the South West Peninsula, St Lukes Campus, University of Exeter Medical School, Exeter, UK." + "author_name": "Neeraj Sood", + "author_inst": "University of Southern California" }, { - "author_name": "Tom Edwards", - "author_inst": "Taunton and Somerset NHS Foundation Trust, Taunton, Somerset, UK" + "author_name": "Soleil Shah", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Luke Gompels", - "author_inst": "Taunton and Somerset NHS Foundation Trust, Taunton, Somerset, UK" + "author_name": "Emilia Ling", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Lucas Lacasa", - "author_inst": "School of Mathematical Sciences, Queen Mary University of London, London E1 4NS, UK" + "author_name": "Rebecca Bromley-Dulfano", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Ellen Brooks-Pollock", - "author_inst": "Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK" + "author_name": "Cara Lai", + "author_inst": "Stanford University School of Medicine" }, { - "author_name": "Leon Danon", - "author_inst": "Data Science Institute, College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK." + "author_name": "Zoe Weissberg", + "author_inst": "Stanford University School of Medicine" + }, + { + "author_name": "Rodrigo Saavedra-Walker", + "author_inst": "Health Education is Power, Inc.," + }, + { + "author_name": "James Tedrow", + "author_inst": "The Compliance Resource Group, Inc." + }, + { + "author_name": "Dona Tversky", + "author_inst": "Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine" + }, + { + "author_name": "Andrew Bogan", + "author_inst": "Bogan Associates" + }, + { + "author_name": "Thomas Kupiec", + "author_inst": "ARL BioPharma, Inc." + }, + { + "author_name": "Daniel Eichner", + "author_inst": "Sports Medicine Research and Testing Laboratory" + }, + { + "author_name": "Ribhav Gupta", + "author_inst": "Department of Epidemiology and Population Health, Stanford University School of Medicine" + }, + { + "author_name": "John Ioannidis", + "author_inst": "Department of Epidemiology and Population Health, Stanford University School of Medicine" + }, + { + "author_name": "Jay Bhattacharya", + "author_inst": "Department of Medicine, Stanford University School of Medicine" } ], "version": "1", - "license": "cc_by", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1563654,27 +1564415,79 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.13.20063669", - "rel_title": "Smoking is Associated with COVID-19 Progression: A Meta-Analysis", + "rel_doi": "10.1101/2020.04.11.20062026", + "rel_title": "Vapor H2O2 sterilization as a decontamination method for the reuse of N95 respirators in the COVID-19 emergency", "rel_date": "2020-04-16", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.13.20063669", - "rel_abs": "ObjectiveTo determine the association between smoking and progression of COVID-19.\n\nDesignA meta-analysis of 12 published papers.\n\nData SourcePubMed database was searched on April 6, 2020.\n\nEligibility criteria and data analysisWe included studies reporting smoking behavior of COVID-19 patients and progression of disease. Search terms included \"smoking\", \"smoker*\", \"characteristics\", \"risk factors\", \"outcomes\", and \"COVID-19\", \"COVID\", \"coronavirus\", \"sar cov-2\", \"sar cov 2\". There were no language limitations. One author extracted information for each study, screened the abstract or the full text, with questions resolved through discussion among both authors. A random effects meta-analysis was applied.\n\nMain Outcome MeasuresThe study outcome was progression of COVID-19 among people who already had the disease.\n\nResultsWe identified 12 papers with a total of 9,025 COVID-19 patients, 878 (9.7%) with severe disease and 495 with a history of smoking (5.5%). The meta-analysis showed a significant association between smoking and progression of COVID-19 (OR 2.25, 95% CI 1.49-3.39, p=0.001). Limitations in the 12 papers suggest that the actual risk of smoking may be higher.\n\nConclusionsSmoking is a risk factor for progression of COVID-19, with smokers having higher odds of COVID-19 progression than never smokers. Physicians and public health professionals should collect data on smoking as part of clinical management and add smoking cessation to the list of practices to blunt the COVID-19 pandemic.\n\nWhat is already known on this topicO_LISmoking increases risk and severity of pulmonary infections because of damage to upper airways and a decrease in pulmonary immune function.\nC_LI\n\nWhat this study addsO_LISmoking is associated with COVID-19 severity.\nC_LIO_LISmoking history should be part of clinical management of COVID-19 patients and cessation should be added to the list of practices to blunt the COVID-19 pandemic.\nC_LI", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.11.20062026", + "rel_abs": "There are a variety of methods routinely used in the sterilization of medical devices using hydrogen peroxide (H2O2) including vaporization, plasma generation and ionization. Many of these systems are used for sterilization and are validated for bioburden reduction using bacterial spores.\n\nHere, we explored the benefits of using vaporized H2O2 (VHP) treatment of N95 respirators for emergency decontamination and reuse to alleviate PPE shortages for healthcare workers in the COVID-19 emergency. The factors that are considered for the effective reuse of these respirators are the fit, the filter efficiency and the decontamination/disinfection level for SARS-CoV-2, which is the causative virus for COVID-19 and other organisms of concern in the hospital environment such as methicillin-resistant Staphylococcus aureus or Clostridium difficile. WE showed that the method did not affect fit or filter efficiency at least for one cycle and resulted in a >6 log reduction in bacterial spores and >3.8 log reduction in the infectious SARS-CoV2 load on N95 respirators.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Roengrudee Patanavanich", - "author_inst": "University of California San Francisco" + "author_name": "Ebru Oral", + "author_inst": "Massachusetts General Hospital/Harvard Medical School" }, { - "author_name": "Stanton A Glantz", - "author_inst": "University of California San Francisco" + "author_name": "Keith K Wannomae", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Rachel L Connolly", + "author_inst": "Massachusetts General Hospital" + }, + { + "author_name": "Joseph A Gardecki", + "author_inst": "Massachusetts General Hospital/Harvard Medical School" + }, + { + "author_name": "Hui Min Leung", + "author_inst": "Massachusetts General Hospital/Harvard Medical School" + }, + { + "author_name": "Orhun K Muratoglu", + "author_inst": "Massachusetts General Hospital/Harvard Medical School" + }, + { + "author_name": "Anthony Griffiths", + "author_inst": "Boston University" + }, + { + "author_name": "Anna N Honko", + "author_inst": "Boston University" + }, + { + "author_name": "Laura E Avena", + "author_inst": "Boston University" + }, + { + "author_name": "Lindsay GA McKay", + "author_inst": "Boston University" + }, + { + "author_name": "Nick Flynn", + "author_inst": "Boston University" + }, + { + "author_name": "Nadia Storm", + "author_inst": "Boston University" + }, + { + "author_name": "Sierra N Downs", + "author_inst": "Boston University" + }, + { + "author_name": "Ralph Jones", + "author_inst": "B & V Testing" + }, + { + "author_name": "Brandon Emmal", + "author_inst": "B & V Testing" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "occupational and environmental health" }, { "rel_doi": "10.1101/2020.04.15.040618", @@ -1564951,51 +1565764,67 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.11.20061408", - "rel_title": "A Preliminary Assessment of Novel Coronavirus (COVID-19) Knowledge and Perceptions in Nigeria", + "rel_doi": "10.1101/2020.04.11.20062091", + "rel_title": "Cardiac or Infectious? Transfer Learning with Chest X-Rays for ER Patient Classification", "rel_date": "2020-04-15", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.11.20061408", - "rel_abs": "This study assessed knowledge and perceptions about COVID-19 among the general public in Nigeria during the initial week of the pandemic lockdown in the country. From March 28 to April 4, 2020, this cross-sectional survey used an anonymous online questionnaire to collect data from respondents within Nigeria. Purposive and snowball sampling techniques were used to recruit 1357 respondents, aged 15-70 years, from 180 cities and towns within Nigeria. Study data were analysed using descriptive statistics. Approximately more than half (57.02%) of the respondents were male with high level of education (48.86% bachelors degree or higher). Approximately half of the respondents (46.94%) opined that COVID-19 was \"a biological weapon designed by the Chinese government.\" About 94% of the respondents identified \"contact with airborne droplets via breathing, sneezing, or coughing\" as the most common mode of transmission; most respondents associated COVID-19 with coughing (81.13%), shortness of breath (73.47%) and fever (62.79%). \"Regular hand washing and social distancing\" was selected by most respondents (94.25%) as a way of preventing infection whereas 11.86% reported \"consuming gins, garlic, ginger, herbal mixtures and African foods/soups\" as preventive measures against COVID-19. Majority of the respondents (91.73%) thought COVID-19 is deadly; and most respondents (84.3%) got 4 or more answers correctly. It was also observed that the traditional media (TV/Radio) are the most common source of health information about COVID-19 (93.5%). Findings revealed that Nigerians have relatively high knowledge, mostly derived from traditional media, about COVID-19. Their perceptions of COVID-19 bear implications across public health initiatives, compliance with precautionary behavior as well as bilateral relations with foreign nations. Evidence-based campaign should be intensified to remove misconceptions and promote precautionary measures.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.11.20062091", + "rel_abs": "One of the challenges with urgent evaluation of patients with acute respiratory distress syndrome (ARDS) in the emergency room (ER) is distinguishing between cardiac vs infectious etiologies for their pulmonary findings. We evaluated ER patient classification for cardiac and infection causes with clinical data and chest X-ray image data. We show that a deep-learning model trained with an external image data set can be used to extract image features and improve the classification accuracy of a data set that does not contain enough image data to train a deep-learning model. We also conducted clinical feature importance analysis and identified the most important clinical features for ER patient classification. This model can be upgraded to include a SARS-CoV-2 specific classification with COVID-19 patients data. The current model is publicly available with an interface at the web link: http://nbttranslationalresearch.org/.\n\nData statementThe clinical data and chest x-ray image data for this study were collected and prepared by the residents and researchers of the Joint Translational Research Lab of Arkansas State University (A-State) and St. Bernards Medical Center (SBMC) Internal Medicine Residency Program. As data collection is on-going for the project stage-II of clinical testing, raw data is not currently available for data sharing to the public.\n\nEthicsThis study was approved by the St. Bernards Medical Centers Institutional Review Board (IRB).", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Peter O OLAPEGBA", - "author_inst": "University of Ibadan" + "author_name": "Jonathan Stubblefield", + "author_inst": "Arkansas State University" }, { - "author_name": "Olusola AYANDELE", - "author_inst": "The Polytechnic Ibadan" + "author_name": "Mitchell Hervert", + "author_inst": "St. Bernards Medical Center" }, { - "author_name": "Samson Olowo KOLAWOLE", - "author_inst": "Nigeria Police Academy, Wudil, Kano" + "author_name": "Jason Causey", + "author_inst": "Arkansas State University" }, { - "author_name": "Rotimi OGUNTAYO", - "author_inst": "University of Ilorin" + "author_name": "Jake Qualls", + "author_inst": "Arkansas State University" }, { - "author_name": "Joshua Chiroma GANDI", - "author_inst": "University of Jos" + "author_name": "Wei Dong", + "author_inst": "Ann Arbor Algorithm" }, { - "author_name": "Abdullahi Lawal DANGIWA", - "author_inst": "Federal University, Dutse" + "author_name": "Lingrui Cai", + "author_inst": "Ann Arbor Algorithm" }, { - "author_name": "Iboro Friday Akpan OTTU", - "author_inst": "University of Uyo" + "author_name": "Jennifer Fowler", + "author_inst": "Arkansas State University" }, { - "author_name": "Steven Kator IORFA", - "author_inst": "University of Nigeria, Nsukka" + "author_name": "Emily Bellis", + "author_inst": "Arkansas State University" + }, + { + "author_name": "Karl Walker", + "author_inst": "University of Arkansas at Pine Bluff" + }, + { + "author_name": "Jason H. Moore", + "author_inst": "University of Pennsylvania" + }, + { + "author_name": "Sara Nehring", + "author_inst": "St. Bernards Medical Center" + }, + { + "author_name": "Xiuzhen Huang", + "author_inst": "Arkansas State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "health informatics" }, { "rel_doi": "10.1101/2020.04.11.20061952", @@ -1566469,25 +1567298,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.09.20059311", - "rel_title": "Real-time forecasts and risk assessment of novel coronavirus (COVID-19) cases: A data-driven analysis", + "rel_doi": "10.1101/2020.04.09.20059865", + "rel_title": "Forecasting the scale of the COVID-19 epidemic in Kenya", "rel_date": "2020-04-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20059311", - "rel_abs": "The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting 201 countries and territories around the globe. As of April 4, 2020, it has caused a pandemic outbreak with more than 11,16,643 confirmed infections and more than 59,170 reported deaths worldwide. The main focus of this paper is two-fold: (a) generating short term (real-time) forecasts of the future COVID-19 cases for multiple countries; (b) risk assessment (in terms of case fatality rate) of the novel COVID-19 for some profoundly affected countries by finding various important demographic characteristics of the countries along with some disease characteristics. To solve the first problem, we presented a hybrid approach based on autoregressive integrated moving average model and Wavelet-based forecasting model that can generate short-term (ten days ahead) forecasts of the number of daily confirmed cases for Canada, France, India, South Korea, and the UK. The predictions of the future outbreak for different countries will be useful for the effective allocation of health care resources and will act as an early-warning system for government policymakers. In the second problem, we applied an optimal regression tree algorithm to find essential causal variables that significantly affect the case fatality rates for different countries. This data-driven analysis will necessarily provide deep insights into the study of early risk assessments for 50 immensely affected countries.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20059865", + "rel_abs": "BackgroundThe first COVID-19 case in Kenya was confirmed on March 13th, 2020. Here, we provide forecasts for the potential incidence rate, and magnitude, of a COVID-19 epidemic in Kenya based on the observed growth rate and age distribution of confirmed COVID-19 cases observed in China, whilst accounting for the demographic and geographic dissimilarities between China and Kenya.\n\nMethodsWe developed a modelling framework to simulate SARS-CoV-2 transmission in Kenya, KenyaCoV. KenyaCoV was used to simulate SARS-CoV-2 transmission both within, and between, different Kenyan regions and age groups. KenyaCoV was parameterized using a combination of human mobility data between the defined regions, the recent 2019 Kenyan census, and estimates of age group social interaction rates specific to Kenya. Key epidemiological characteristics such as the basic reproductive number and the age-specific rate of developing COVID-19 symptoms after infection with SARS-CoV-2, were adapted for the Kenyan setting from a combination of published estimates and analysis of the age distribution of cases observed in the Chinese outbreak.\n\nResultsWe find that if person-to-person transmission becomes established within Kenya, identifying the role of subclinical, and therefore largely undetected, infected individuals is critical to predicting and containing a very significant epidemic. Depending on the transmission scenario our reproductive number estimates for Kenya range from 1.78 (95% CI 1.44 -2.14) to 3.46 (95% CI 2.81-4.17). In scenarios where asymptomatic infected individuals are transmitting significantly, we expect a rapidly growing epidemic which cannot be contained only by case isolation. In these scenarios, there is potential for a very high percentage of the population becoming infected (median estimates: >80% over six months), and a significant epidemic of symptomatic COVID-19 cases. Exceptional social distancing measures can slow transmission, flattening the epidemic curve, but the risk of epidemic rebound after lifting restrictions is predicted to be high.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Tanujit Chakraborty", - "author_inst": "Indian Statistical Institute, Kolkata" + "author_name": "Samuel P C Brand", + "author_inst": "University of Warwick" }, { - "author_name": "Indrajit Ghosh", - "author_inst": "Indian Statistical Institute, Kolkata" + "author_name": "Rabia Aziza", + "author_inst": "University of Warwick" + }, + { + "author_name": "Ivy K Kombe", + "author_inst": "Kenya Medical Research Institute, Wellcome Trust Research Programme" + }, + { + "author_name": "Charles N Agoti", + "author_inst": "Kenya Medical Research Institute, Wellcome Trust Research Programme" + }, + { + "author_name": "Joe Hilton", + "author_inst": "University of Warwick" + }, + { + "author_name": "Kat S Rock", + "author_inst": "University of Warwick" + }, + { + "author_name": "Andrea Parisi", + "author_inst": "University of Warwick" + }, + { + "author_name": "D James Nokes", + "author_inst": "Kenya Medical Research Institute, Wellcome Trust Research Programme and University of Warwick" + }, + { + "author_name": "Matt Keeling", + "author_inst": "University of Warwick" + }, + { + "author_name": "Edwine Barasa", + "author_inst": "Kenya Medical Research Institute, Wellcome Trust Research Programme" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1567739,33 +1568600,53 @@ "category": "genetic and genomic medicine" }, { - "rel_doi": "10.1101/2020.04.10.20061192", - "rel_title": "COVID-19 most vulnerable Mexican cities lack the public health infrastructure to face the pandemic: a new temporally-explicit model", + "rel_doi": "10.1101/2020.04.09.20060103", + "rel_title": "Acceptance and preference for COVID-19 vaccination in health-care workers (HCWs)", "rel_date": "2020-04-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.10.20061192", - "rel_abs": "Recently, a wide array of epidemiological models have been developed to guide public health actors in containing the rapid dissemination of the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), cause of COVID-19. Despite their usefulness, many epidemiological models recently developed to understand the spread of SARS-CoV-2 and infection rates of COVID-19 fall short as they ignore human mobility, limiting our understanding of the spread of the disease, together with the vulnerability of population centers in a broad scale. We developed a new temporally-explicit model and simulated several social distancing scenarios to predict the vulnerability to COVID-19 of 50 Mexican cities that are interconnected by their air transportation network. Additionally, we assessed the sufficiency of the public health infrastructure in the focal cities to face the pandemic over time. Based on our model, we show that the most important cities within the Mexican air transportation network are the most vulnerable to COVID-19, with all assessed public health infrastructure being insufficient to face the modeled scenario for the pandemic after 100 days. Despite these alarming findings, our results show that social distancing could dramatically decrease the total number of infected people (77% drop-off for the 45% distancing scenario when contrasted with no distancing), flattening the growth of infection rate. Thus, we consider that this study provides useful information that may help decision-makers to timely implement health policies to anticipate and lessen the impact of the current pandemic in Mexico.\n\nSignificance StatementWe used a new temporally-explicit model focused on air transportation networks to predict the vulnerability of 50 focal Mexican cities to COVID-19. We found that most vulnerable cities lack of the required public health infrastructure (i.e., number of inpatient and intensive care unit beds) to face this new pandemic, overloading in all cases after 100 days. However, our results show that a 45% social distancing scenario can reduce the number of infected people by up to 78.7%, flattening the growth rate of people with COVID-19 before infection rates soar exponentially countrywide.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20060103", + "rel_abs": "BackgroundA major obstacle to successful coronavirus disease (COVID-19) vaccine rollout is vaccine hesitancy. Acceptance of and preferences for COVID-19 vaccination among healthcare workers (HCWs) is critical, because they are a key target group for vaccination programs, and they are also highly influential to vaccine uptake in the wider population. This study sought to comparatively determine the acceptance of and preference for COVID-19 vaccination among HCWs and the general population.\n\nMethodsAn Internet-based, region-stratified discrete-choice experiment was conducted among 352 HCWs and 189 general population respondents recruited in March 2020 from 26 Chinese provinces. We accessed knowledge of disease, attitude towards and acceptance of COVID-19 vaccination. Several attributes (related to COVID-19 disease, COVID-19 vaccination and one social acceptance) were identified as key determinants of vaccine acceptance.\n\nResultsHCWs had a more in-depth understanding of COVID-19 and showed a higher willingness to accept COVID-19 vaccines with lower effectiveness and/or more severe adverse effects compared to the general population. 76.4% of HCWs (vs 72.5% of the general population) expressed willingness to receive vaccination ({chi}2=2.904, p=0.234). High levels of willingness to accept influenza (65.3%) and pneumococcal (55.7%) vaccination were also seen in HCWs. Future COVID-19 disease incidence (OR: 4.367, 95% CI 3.721-5.126), decisions about vaccination among social contacts of respondents (OR 0.398, 95% CI 0.339-0.467), and infection risk >30% (OR 2.706, 95% CI 1.776-2.425) significantly increased the probability of vaccination acceptance in HCWs.\n\nConclusionMulti-component interventions to address the key determinants of hesitancy in both HCWs and in the general population should be considered for COVID-19 vaccination programs.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Wesley Dattilo Sr.", - "author_inst": "Instituto de Ecologia AC" + "author_name": "Chuanxi Fu", + "author_inst": "Institute of Infectious Disease and Vaccine, School of Public Health, Zhejiang Chinese Medical University" }, { - "author_name": "Alcides Castro e Silva", - "author_inst": "Universidade Federal de Ouro Preto" + "author_name": "Zheng Wei", + "author_inst": "Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University" }, { - "author_name": "Roger Guevara Sr.", - "author_inst": "Instituto de Ecologia AC" + "author_name": "Fengchang Zhu", + "author_inst": "Chinese Pharmaceutical Association" }, { - "author_name": "Ian MacGregor-Fors", - "author_inst": "Instituto de Ecologia AC" + "author_name": "Sen Pei", + "author_inst": "Mailman School of Public Health, Columbia University" }, { - "author_name": "Servio Pontes Ribeiro", - "author_inst": "Universidade Federal de Ouro Preto" + "author_name": "Shunping Li", + "author_inst": "NHC Key Laboratory of Health Economics and Policy Research, Shandong University;School of Health Care Management, Shandong University" + }, + { + "author_name": "Liuren Zhang", + "author_inst": "Institute of Infectious Disease and Vaccine, School of Public Health, Zhejiang Chinese Medical University" + }, + { + "author_name": "Xiaohui Sun", + "author_inst": "Department of Epidemiology, School of Public Health, Zhejiang Chinese Medical University" + }, + { + "author_name": "Yue Wu", + "author_inst": "School of Public Health, Zhejiang Chinese Medical University" + }, + { + "author_name": "Ping Liu", + "author_inst": "NHC Key Laboratory of Health Economics and Policy Research, Shandong University;School of Health Care Management, Shandong University" + }, + { + "author_name": "Mark Jit", + "author_inst": "Department of Infectious Disease Epidemiology, London School of Hygiene & Tropical Medicine" } ], "version": "1", @@ -1569105,27 +1569986,67 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.04.09.20059345", - "rel_title": "Chasing the ghost of infection past: identifying thresholds of change during the COVID-19 infection in Spain", + "rel_doi": "10.1101/2020.04.09.20060129", + "rel_title": "COVID-19 Global Pandemic Planning: Decontamination and Reuse Processes for N95 Respirators", "rel_date": "2020-04-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20059345", - "rel_abs": "COVID-19 pandemic has spread worldwide rapidly from its first outbreak in China, with different impacts depending on the age and social structure of the populations, and the measures taken by each government. Within Europe, the first countries to be strongly affected have been Italy and Spain. In Spain, infection has expanded in highly populated areas, resulting in one of the largest nationwide bursts so far by early April. We analyze the evolution of the growth curve of the epidemic in both the whole of Spain, Madrid Autonomous Region (the second largest conurbation in Europe), and Catalonia (which includes Spains second largest city), based on the cumulative numbers of reported cases and deaths. We conducted segmented, poisson regressions on log-transformed data to identify changes in the slope of these curves and/or sudden shifts in the number of cases (i.e. changes in the intercept) at fitted breaking points, and compared their results with a timeline including both key events of the epidemic and containment measures taken by the national and regional governments. Results were largely consistent in the six curves analyzed (reported infections and deaths for Spain, Madrid and Catalonia, respectively), showing three major clusters of shifts in slopes (growth rates) on March 13-19, March 23-29 and April 1-5 that resulted in 33-71% reductions of slope, and originated in infections on March 3-9, 13-19 and 22-26; as well as a decrease in the infection rate following the strengthened lockdown of 29-30 April, only for Madrid and Catalonia. Small upward shifts in the progress of the disease in Madrid were not associated with significant increases in the intercept of the curve, and seem related with unevenness in case reporting; but they did so in Spain and Catalonia, where they were probably associated to specific events of group infection in Vitoria and to the onset of the outbreak in Catalonia. These results evidence an early deceleration in the spread of COVID-19 coinciding with personal hygiene and social distancing recommendations, as well as the general awareness of the population; and a second, stronger decrease when harder isolation measures were enforced. The combination of these two inflection points seemingly led to the start of the contention of the disease outbreak by early April, the limit of our time series. This highlights the importance of adopting public health strategies that include disseminating basic knowledge on personal hygiene and reduced social contact at the onset of the epidemic, and the importance of early enforcement of hard confinement measures for its subsequent contention.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.09.20060129", + "rel_abs": "Coronavirus disease 2019 (COVID-19) is an illness caused by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The disease was first identified as a cluster of respiratory illness in Wuhan City, Hubei Province, China in December 2019, and has rapidly spread across the globe to greater than 200 countries. Healthcare providers are at an increased risk for contracting the disease due to occupational exposure and require appropriate personal protective equipment (PPE), including N95 respirators. The rapid worldwide spread of high numbers of COVID-19 cases has facilitated the need for a substantial supply of PPE that is largely unavailable in many settings, thereby creating critical shortages. Creative solutions for the decontamination and safe reuse of PPE to protect our frontline healthcare personnel are essential. Here, we describe the development of a process that began in late February 2020 for selecting and implementing the use of hydrogen peroxide vapor (HPV) as viable method to reprocess N95 respirators. Since pre-existing HPV decontamination chambers were not available, we optimized the sterilization process in an operating room after experiencing initial challenges in other environments. Details are provided about the prioritization and implementation of processes for collection and storage, pre-processing, HPV decontamination, and post-processing of filtering facepiece respirators (FFRs). Important lessons learned from this experience include, developing an adequate reserve of PPE for effective reprocessing and distribution, and identifying a suitable location with optimal environmental controls (i.e., operating room). Collectively, information presented here provides a framework for other institutions considering decontamination procedures for N95 respirators.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Luis Santamaria", - "author_inst": "Donana Biological Station (EBD-CSIC)" + "author_name": "Douglas Jay Perkins", + "author_inst": "Center for Global Health, Department of Internal Medicine, UNM Health Science Center" }, { - "author_name": "Joaquin Hortal", - "author_inst": "Museo Nacional de Ciencias Naturales (MNCN-CSIC)" + "author_name": "Steven Villescas", + "author_inst": "University of New Mexico Hospital, Facilities Safety" + }, + { + "author_name": "Terry H Wu", + "author_inst": "Division of Epidemiology, Biostatistics, and Preventive Medicine, Center for Infectious Disease and Immunity, Department of Internal Medicine, University of New" + }, + { + "author_name": "Timothy B Muller", + "author_inst": "Office of Research, University of New Mexico Health Science Center" + }, + { + "author_name": "Steven Bradfute", + "author_inst": "Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center" + }, + { + "author_name": "Ivy Foo-Hurwitz", + "author_inst": "Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center" + }, + { + "author_name": "Qiuying Cheng", + "author_inst": "Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center" + }, + { + "author_name": "Hannah Wilcox", + "author_inst": "School of Medicine, University of New Mexico Health Science Center" + }, + { + "author_name": "Myissa Weiss", + "author_inst": "School of Medicine, University of New Mexico Health Science Center" + }, + { + "author_name": "Chris Bartlett", + "author_inst": "Division of Hospital Medicine, Department of Internal Medicine, University of New Mexico Health Science Center" + }, + { + "author_name": "Jens Langsjoen", + "author_inst": "Division of Hospital Medicine, Department of Internal Medicine, University of New Mexico Health Science Center" + }, + { + "author_name": "Phil Seidenberg", + "author_inst": "Department of Emergency Medicine, University of New Mexico Health Science Center" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.10.20060335", @@ -1570563,31 +1571484,63 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.04.05.026005", - "rel_title": "Immuno-informatics Characterization SARS-CoV-2 Spike Glycoprotein for Prioritization of Epitope based Multivalent Peptide Vaccine", - "rel_date": "2020-04-12", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.05.026005", - "rel_abs": "The COVID-19 pandemic caused by SARS-CoV-2 is a public-health emergency of international concern and thus calling for the development of safe and effective therapeutics and prophylactics particularly a vaccine to protect against the infection. SARS-CoV-2 spike glycoprotein is an attractive candidate for vaccine, antibodies and inhibitor development because of many roles it plays in attachment, fusion and entry into the host cell. In this study, we characterized the SARS-CoV-2 spike glycoprotein by immune-informatics techniques to put forward potential B and T cell epitopes, followed by the use of epitopes in construction of a multi-epitope peptide vaccine construct (MEPVC). The MEPVC revealed robust host immune system simulation with high production of immunoglobulins, cytokines and interleukins. Stable conformation of the MEPVC with a representative innate immune TLR3 receptor was observed involving strong hydrophobic and hydrophilic chemical interactions, along with enhanced contribution from salt-bridges towards inter-molecular stability. Molecular dynamics simulation in solution aided further in interpreting strong affinity of the MEPVC for TLR3. This stability is the attribute of several vital residues from both TLR3 and MEPVC as shown by radial distribution function (RDF) and a novel analytical tool axial frequency distribution (AFD). Comprehensive binding free energies estimation was provided at the end that concluded major domination by electrostatic and minor from van der Waals. Summing all, the designed MEPVC has tremendous potential of providing protective immunity against COVID-19 and thus has the potential to be considered in experimental studies.", - "rel_num_authors": 3, + "rel_doi": "10.1101/2020.04.06.20054841", + "rel_title": "The need of health policy perspective to protect Healthcare Workers during COVID-19 pandemic. A GRADE rapid review on the N95 respirators effectiveness.", + "rel_date": "2020-04-11", + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20054841", + "rel_abs": "Protecting Health Care Workers (HCWs) during routine care of suspected or confirmed COVID-19 patients is of paramount importance to halt the SARS-CoV-2 (Severe Acute Respiratory Syndrome-Coronavirus-2) pandemic. The WHO, ECDC and CDC have issued conflicting guidelines on the use of respiratory filters (N95) by HCWs. We searched PubMed, Embase and The Cochrane Library from the inception to March 21, 2020 to identify randomized controlled trials (RCTs) comparing N95 respirators versus surgical masks for prevention of COVID-19 or any other respiratory infection among HCWs. The grading of recommendations, assessment, development, and evaluation (GRADE) was used to evaluate the quality of evidence. Four RCTs involving 8736 HCWs were included. We did not find any trial specifically on prevention of COVID-19. However, wearing N95 respirators can prevent 73 more (95% CI 46-91) clinical respiratory infections per 1000 HCWs compared to surgical masks (2 RCTs; 2594 patients; low quality of evidence). A protective effect of N95 respirators in laboratory-confirmed bacterial colonization (RR= 0.41; 95%CI 0.28-0.61) was also found. A trend in favour of N95 respirators was observed in preventing laboratory-confirmed respiratory viral infections, laboratory-confirmed respiratory infection, and influenza like illness. We found no direct high quality evidence on whether N95 respirators are better than surgical masks for HCWs protection from SARS-CoV-2. However, low quality evidence suggests that N95 respirators protect HCWs from clinical respiratory infections. This finding should be contemplated to decide the best strategy to support the resilience of healthcare systems facing the potentially catastrophic SARS-CoV-2 pandemic.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Saba Ismail", - "author_inst": "Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University Islamabad, Pakistan" + "author_name": "Primiano Iannone", + "author_inst": "Centro Eccellenza Clinica, Qualita' e Sicurezza delle Cure, Istituto Superiore di Sanita', Rome, Italy" }, { - "author_name": "Sajjad Ahmad", - "author_inst": "Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University Islamabad, Pakistan" + "author_name": "Greta Castellini", + "author_inst": "IRCCS Istituto Ortopedico Galeazzi, Unit of Clinical Epidemiology, Milan, Italy" + }, + { + "author_name": "Daniela Coclite", + "author_inst": "Centro Eccellenza Clinica, Qualita' e Sicurezza delle Cure, Istituto Superiore di Sanita', Rome, Italy" + }, + { + "author_name": "Antonello Napoletano", + "author_inst": "Centro Eccellenza Clinica, Qualita' e Sicurezza delle Cure, Istituto Superiore di Sanita', Rome, Italy" + }, + { + "author_name": "Alice Fauci", + "author_inst": "Centro Eccellenza Clinica, Qualita' e Sicurezza delle Cure, Istituto Superiore di Sanita', Rome, Italy" }, { - "author_name": "Syed Sikander Azam", - "author_inst": "Computational Biology Lab, National Center for Bioinformatics, Quaid-i-Azam University Islamabad, Pakistan" + "author_name": "Laura Iacorossi", + "author_inst": "Centro Eccellenza Clinica, Qualita' e Sicurezza delle Cure, Istituto Superiore di Sanita', Rome, Italy." + }, + { + "author_name": "Daniela D'Angelo", + "author_inst": "Centro Eccellenza Clinica, Qualita' e Sicurezza delle Cure, Istituto Superiore di Sanita', Rome, Italy" + }, + { + "author_name": "Cristina Renzi", + "author_inst": "University College London-UCL, Institute of Epidemiology & Health Care, London, UK" + }, + { + "author_name": "Giuseppe La Torre", + "author_inst": "Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy" + }, + { + "author_name": "Claudio Mastroianni", + "author_inst": "Department of Public Health and Infectious Diseases, Sapienza University of Rome, Rome, Italy" + }, + { + "author_name": "Silvia Gianola", + "author_inst": "IRCCS Istituto Ortopedico Galeazzi, Unit of Clinical Epidemiology, Milan, Italy" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "bioinformatics" + "license": "cc_by_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.07.20056812", @@ -1571745,31 +1572698,31 @@ "category": "respiratory medicine" }, { - "rel_doi": "10.1101/2020.04.06.20055640", - "rel_title": "Gaussian Statistics and Data-Assimilated Model of Mortality due to COVID-19: China, USA, Italy, Spain, UK, Iran, and the World Total", + "rel_doi": "10.1101/2020.04.06.20055632", + "rel_title": "Association of County-Level Socioeconomic and Political Characteristics with Engagement in Social Distancing for COVID-19", "rel_date": "2020-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20055640", - "rel_abs": "Covid-19 is characterized by rapid transmission and severe symptoms, leading to deaths in some cases (ranging from 1.5 to 12% of the affected, depending on the country). We identify the Gaussian nature of mortality due to covid-19, as shown in China where it appears to have run its course (during the first sweep of the pandemic at least) and other coutnries, and also in Imperial College modeling. Gaussian distribution involves three parameters, the height, peak location and the width, and the streaming data can be used to infer function value, slope and inflection location as a minimum set of constraints to estimate the subsequent trajectories. Thus, we apply the Gaussian function template as the basis for a data-assimilated model of covid-19 trajectories, first to USA, United Kingdom (UK), Iran and the world total in this study. As more data become available, the Gaussian trajectories are updated, for other nations and also for state-by-state projections in USA.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20055632", + "rel_abs": "The U.S. is the epicenter of the coronavirus disease 2019 (COVID-19) pandemic. In response, governments have implemented measures to slow transmission through \"social distancing.\" However, the practice of social distancing may depend on prevailing socioeconomic conditions and beliefs. Using 15-17 million anonymized cell phone records, we find that lower per capita income and greater Republican orientation were associated with significantly reduced social distancing among U.S. counties. These associations persisted after adjusting for county-level sociodemographic and labor market characteristics as well as state fixed effects. These results may help policymakers and health professionals identify communities that are most vulnerable to transmission and direct resources and communications accordingly.", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "T.-W. Lee", - "author_inst": "Arizona State University" + "author_name": "Nolan M Kavanagh", + "author_inst": "University of Pennsylvania, University of Michigan" }, { - "author_name": "J.E. Park", - "author_inst": "Arizona State University" + "author_name": "Rishi R Goel", + "author_inst": "University of Pennsylvania" }, { - "author_name": "David Hung", - "author_inst": "Shanghai Jiatong University" + "author_name": "Atheendar S Venkataramani", + "author_inst": "University of Pennsylvania" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "health informatics" + "category": "health policy" }, { "rel_doi": "10.1101/2020.04.06.20055368", @@ -1573071,39 +1574024,31 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.09.033910", - "rel_title": "Integrative Network Biology Framework Elucidates Molecular Mechanisms of SARS-CoV-2 Pathogenesis", + "rel_doi": "10.1101/2020.04.08.20057661", + "rel_title": "Towards reduction in bias in epidemic curves due to outcome misclassification through Bayesian analysis of time-series of laboratory test results: Case study of COVID-19 in Alberta, Canada and Philadelphia, USA", "rel_date": "2020-04-11", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.09.033910", - "rel_abs": "COVID-19 (Coronavirus disease 2019) is a respiratory illness caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). While the pathophysiology of this deadly virus is complex and largely unknown, we employ a network biology-fueled approach and integrated multiomics data pertaining to lung epithelial cells-specific coexpression network and human interactome to generate Calu-3-specific human-SARS-CoV-2 Interactome (CSI). Topological clustering and pathway enrichment analysis show that SARS-CoV-2 target central nodes of host-viral network that participate in core functional pathways. Network centrality analyses discover 28 high-value SARS-CoV-2 targets, which are possibly involved in viral entry, proliferation and survival to establish infection and facilitate disease progression. Our probabilistic modeling framework elucidates critical regulatory circuitry and molecular events pertinent to COVID-19, particularly the host modifying responses and cytokine storm. Overall, our network centric analyses reveal novel molecular components, uncover structural and functional modules, and provide molecular insights into SARS-CoV-2 pathogenicity.", - "rel_num_authors": 5, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20057661", + "rel_abs": "The aim of our work was to better understand misclassification errors in identification of true cases of COVID-19 and to study the impact of these errors in epidemic curves. We examined publically available time-series data of laboratory tests for SARS-CoV-2 viral infection, the causal agent for COVID-19, to try to explore, using a Bayesian approach, about the sensitivity and specificity of the PCR-based diagnostic test. Data originated from Alberta, Canada (available on 3/28/2020) and city of Philadelphia, USA (available on 3/31/2020). Our analysis revealed that the data were compatible with near-perfect specificity but it was challenging to gain information about sensitivity (prior and posterior largely overlapped). We applied these insights to uncertainty/bias analysis of epidemic curves into jurisdictions under the assumptions of both improving and degrading sensitivity. If the sensitivity improved from 60 to 95%, the observed and adjusted epidemic curves likely fall within the 95% confidence intervals of the observed counts. However, bias in the shape and peak of the epidemic curves can be pronounced, if sensitivity either degrades or remains poor in the 60-70% range. In the extreme scenario, hundreds of undiagnosed cases, even among tested, are possible, potentially leading to further unchecked contagion should these cases not self-isolate. The best way to better understand bias in the epidemic curves of COVID-19 due to errors in testing is to empirically evaluate misclassification of diagnosis in clinical settings and apply this knowledge to adjustment of epidemic curves, a task for which the Bayesian method we presented is well-suited.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Nilesh Kumar", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "Bharat Mishra", - "author_inst": "University of Alabama at Birmingham" - }, - { - "author_name": "Adeel Mehmood", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Igor Burstyn", + "author_inst": "Drexel University" }, { - "author_name": "Mohammad Athar", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Neal D. Goldstein", + "author_inst": "Drexel University" }, { - "author_name": "M Shahid Mukhtar", - "author_inst": "University of Alabama at Birmingham" + "author_name": "Paul Gustafson", + "author_inst": "The University of British Columbia" } ], "version": "1", - "license": "cc_no", - "type": "new results", - "category": "systems biology" + "license": "cc_by", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.07.030924", @@ -1574368,21 +1575313,25 @@ "category": "intensive care and critical care medicine" }, { - "rel_doi": "10.1101/2020.04.08.20057588", - "rel_title": "On the corona infection model with contact restriction", + "rel_doi": "10.1101/2020.04.08.20055095", + "rel_title": "Prediction on Covid-19 epidemic for different countries: Focusing on South Asia under various precautionary measures", "rel_date": "2020-04-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20057588", - "rel_abs": "This article presents a mathematical infection model that is designed to estimate the course of coronavirus infection in Germany for several days in advance: How many people become ill or die, what is the temporal development? If the contact restriction is perfect, then the model predicts the development of the virus infection after the initial subsidence of the infection. However, since this restriction cannot always be strictly adhered to, the model is dynamically adapted to the development. This makes it possible to estimate the number of infected people, the number of new infections and deaths in Germany about a week in advance.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.08.20055095", + "rel_abs": "The coronavirus disease 2019 (COVID-19), which emerged from Wuhan, China, is now a pandemic, affecting across the globe. Government of different countries have developed and adopted various policies to contain this epidemic and the most common were the social distancing and lockdown. We proposed a SEIR epidemic model that accommodates the effects of lockdown and individual based precautionary measures and used it to estimate model parameters from the epidemic data up to 2nd April, 2020, freely available in GitHub repository for COVID-19, for nine developed and developing countries. We used the estimated parameters to predict the disease burden in these countries with special emphasis on India, Bangladesh and Pakistan. Our analysis revealed that the lockdown and recommended individual hygiene can slow down the outbreak but unable to eradicate the disease from the society. With the current human-to-human transmission rate and existing level of personal precautionary, the number of infected individuals in India will be increasing at least for the next 3 months and the peak will come in 5 months. We can, however, reduce the epidemic size and prolong the time to arrive epidemic peak by seriously following the measures suggested by the authorities. We need to wait for another one month to obtain more data and epidemiological parameters for giving a better prediction about the pandemic. It is to be mentioned that research community is working for drugs and/ or vaccines against COVID19 and the presence of such pharmaceutical interventions will significantly alter the results.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Juergen Mimkes", - "author_inst": "Paderborn University" + "author_name": "Abhijit Paul", + "author_inst": "Translational Health Science and Technology Institute" }, { - "author_name": "Rainer Janssen", - "author_inst": "Engineering Bureau Paderborn" + "author_name": "Samrat Chatterjee", + "author_inst": "Translational Health Science and Technology Institute" + }, + { + "author_name": "Nandadulal Bairagi", + "author_inst": "Jadavpur University" } ], "version": "1", @@ -1575446,59 +1576395,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.06.20042580", - "rel_title": "Interferon-a2b treatment for COVID-19", + "rel_doi": "10.1101/2020.04.07.20052142", + "rel_title": "Spatial Correlation of Particulate Matter Pollution and Death Rate of COVID-19", "rel_date": "2020-04-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.06.20042580", - "rel_abs": "BackgroundThe global pandemic of COVID-19 cases caused by infection with SARS-CoV-2 is ongoing, with no approved antiviral intervention. We describe here the effects of treatment with interferon-2b in a cohort of confirmed COVID-19 cases in Wuhan, China.\n\nMethodsIn this retrospective study, 77 adults hospitalized with confirmed COVID-19 were treated with either nebulized IFN-2b (5mU b.i.d.), arbidol (200mg t.i.d.) or a combination of IFN-2b plus arbidol. Serial SARS-CoV-2 testing along with hematological measurements, including cell counts and blood biochemistry, serum cytokine levels, temperature and blood oxygen saturation levels were recorded for each patient during their hospital stay.\n\nResultsTreatment with IFN-2b with or without arbidol significantly reduced the duration of detectable virus in the upper respiratory tract and in parallel reduced duration of elevated blood levels for the inflammatory markers IL-6 and CRP.\n\nConclusionThese findings suggest that IFN-2b should be further investigated as a therapy in COVID-19 cases.", - "rel_num_authors": 10, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20052142", + "rel_abs": "The Coronavirus (COVID-19) epidemic, which was first reported in December 2019 in Wuhan, China, has caused 3,314 death as of March 31, 2020 in China. This study aimed to investigate the spatial associations of daily particulate matter (PM) concentrations with death rate of COVID-19 in China. We conducted a cross-sectional analysis to examine the spatial associations of daily PM2.5 and PM10 concentrations with death rate of COVID-19 in China through multiple linear regression method. We found that COVID-19 held higher death rates with increasing concentration of PM2.5 and PM10 levels in the spatial scale, which may affect the process of patients developed from mild to severe and finally influence the prognosis of COVID-19 patients.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Qiong Zhou", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Xiao-Shan Wei", - "author_inst": "Union Hospital, Tongii Medical College,Huazhong University of Science and Technology" - }, - { - "author_name": "Xuan Xiang", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" - }, - { - "author_name": "Xu Wang", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Ye Yao", + "author_inst": "Department of Biostatics, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Zi-Hao Wang", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Jinhua Pan", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Virginia Chen", - "author_inst": "Prevention of Organ Failure (PROOF) Centre of Excellence & University of British Columbia" + "author_name": "Weidong Wang", + "author_inst": "Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Casey P Shannon", - "author_inst": "Prevention of Organ Failure (PROOF) Centre of Excellence & University of British Columbia" + "author_name": "Zhixi Liu", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Scott J Tebbutt", - "author_inst": "Prevention of Organ Failure (PROOF) Centre of Excellence & University of British Columbia" + "author_name": "Haidong Kan", + "author_inst": "Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Tobias R Kollmann", - "author_inst": "Telethon Kids Institute Western Australia" + "author_name": "Xia Meng", + "author_inst": "Department of Environmental Health, School of Public Health, Fudan University, Shanghai 200032, China" }, { - "author_name": "Eleanor N Fish", - "author_inst": "University Health Network & University of Toronto" + "author_name": "Weibing Wang", + "author_inst": "Department of Epidemiology, School of Public Health, Fudan University, Shanghai 200032, China" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.04.06.20039909", @@ -1576656,31 +1577593,23 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.04.05.026377", - "rel_title": "On the interactions of the receptor-binding domain of SARS-CoV-1 and SARS-CoV-2 spike proteins with monoclonal antibodies and the receptor ACE2", + "rel_doi": "10.1101/2020.04.07.20056960", + "rel_title": "Effects of latency on estimates of the COVID-19 replication number", "rel_date": "2020-04-10", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.05.026377", - "rel_abs": "A new betacoronavirus named SARS-CoV-2 has emerged as a new threat to global health and economy. A promising target for both diagnosis and therapeutics treatments of the new disease named COVID-19 is the coronavirus (CoV) spike (S) glycoprotein. By constant-pH Monte Carlo simulations and the PROCEEDpKa method, we have mapped the electrostatic epitopes for four monoclonal antibodies and the angiotensin-converting enzyme 2 (ACE2) on both SARS-CoV-1 and the new SARS-CoV-2 S receptor binding domain (RBD) proteins. We also calculated free energy of interactions and shown that the S RBD proteins from both SARS viruses binds to ACE2 with similar affinities. However, the affinity between the S RBD protein from the new SARS-CoV-2 and ACE2 is higher than for any studied antibody previously found complexed with SARS-CoV-1. Based on physical chemical analysis and free energies estimates, we can shed some light on the involved molecular recognition processes, their clinical aspects, the implications for drug developments, and suggest structural modifications on the CR3022 antibody that would improve its binding affinities for SARS-CoV-2 and contribute to address the ongoing international health crisis.", - "rel_num_authors": 3, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.07.20056960", + "rel_abs": "It is not currently known how long it takes a person infected by the COVID-19 virus to become infectious. Models of the spread of COVID-19 use very different lengths for this latency period, leading to very different estimates of the replication number R, even when models work from the same underlying data sets. In this paper we quantify how much varying the length of the latency period affects estimates of R, and thus the fraction of the population that is predicted to be infected in the first wave of the pandemic. This variation underscores the uncertainty in our understanding of R and raises the possibility that R may be considerably greater than has been assumed by those shaping public policy.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Carolina Correa Giron", - "author_inst": "Universidade Federal do Triangulo Mineiro, Departamento de Saude Coletiva, Rua Vigario Carlos, 38025-350 - Uberaba - MG, Brazil" - }, - { - "author_name": "Aatto Laaksonen", - "author_inst": "Department of Materials and Environmental Chemistry, Arrhenius Laboratory, Stockholm University, SE-106 91 Stockholm, Sweden" - }, - { - "author_name": "Fernando Luis Barroso da Silva", - "author_inst": "University of Sao Paulo" + "author_name": "Lorenzo A Sadun", + "author_inst": "University of Texas at Austin" } ], "version": "1", "license": "cc_by_nc_nd", - "type": "new results", - "category": "biophysics" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.04.06.028647", @@ -1578662,51 +1579591,35 @@ "category": "immunology" }, { - "rel_doi": "10.1101/2020.04.07.030650", - "rel_title": "The spatial and cell-type distribution of SARS-CoV-2 receptor ACE2 in human and mouse brain", + "rel_doi": "10.1101/2020.04.07.030445", + "rel_title": "3D Models of glycosylated SARS-CoV-2 spike protein suggest challenges and opportunities for vaccine development", "rel_date": "2020-04-09", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.07.030650", - "rel_abs": "By engaging angiotensin-converting enzyme 2 (ACE2 or Ace2), the novel pathogenic SARS-coronavirus 2 (SARS-CoV-2) may invade host cells in many organs, including the brain. However, the distribution of ACE2 in the brain is still obscure. Here we investigated the ACE2 expression in the brain by analyzing data from publicly available brain transcriptome databases. According to our spatial distribution analysis, ACE2 was relatively highly expressed in some brain locations, such as the choroid plexus and paraventricular nuclei of the thalamus. According to cell-type distribution analysis, nuclear expression of ACE2 was found in many neurons (both excitatory and inhibitory neurons) and some non-neuron cells (mainly astrocytes, oligodendrocytes, and endothelial cells) in human middle temporal gyrus and posterior cingulate cortex. A few ACE2-expressing nuclei were found in a hippocampal dataset, and none were detected in the prefrontal cortex. Except for the additional high expression of Ace2 in the olfactory bulb areas for spatial distribution as well as in the pericytes and endothelial cells for cell-type distribution, the distribution of Ace2 in mouse brain was similar to that in the human brain. Thus, our results reveal an outline of ACE2/Ace2 distribution in the human and mouse brain, which indicates the brain infection of SARS-CoV-2 may be capable of inducing central nervous system symptoms in coronavirus disease 2019 (COVID-19) patients. Potential species differences should be considered when using mouse models to study the neurological effects of SARS-CoV-2 infection.", - "rel_num_authors": 8, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.07.030445", + "rel_abs": "Here we have generated 3D structures of glycoforms of the spike (S) glycoprotein from SARS-CoV-2, based on reported 3D structures and glycomics data for the protein produced in HEK293 cells. We also analyze structures for glycoforms representing those present in the nascent glycoproteins (prior to enzymatic modifications in the Golgi), as well as those that are commonly observed on antigens present in other viruses.\n\nThese models were subjected to molecular dynamics (MD) simulation to determine the extent to which glycan microheterogeneity impacts the antigenicity of the S glycoprotein. Lastly, we have identified peptides in the S glycoprotein that are likely to be presented in human leukocyte antigen (HLA) complexes, and discuss the role of S protein glycosylation in potentially modulating the adaptive immune response to the SARS-CoV-2 virus or to a related vaccine.\n\nThe 3D structures show that the protein surface is extensively shielded from antibody recognition by glycans, with the exception of the ACE2 receptor binding domain, and also that the degree of shielding is largely insensitive to the specific glycoform. Despite the relatively modest contribution of the glycans to the total molecular weight (17% for the HEK293 glycoform) the level of surface shielding is disproportionately high at 42%.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Rongrong Chen", - "author_inst": "Zhejiang Chinese Medical University" - }, - { - "author_name": "Jie Yu", - "author_inst": "Zhejiang Chinese Medical University" - }, - { - "author_name": "Keer Wang", - "author_inst": "Zhejiang Chinese Medical University" - }, - { - "author_name": "Derek Howard", - "author_inst": "Centre for Addiction and Mental Health" - }, - { - "author_name": "Leon French", - "author_inst": "Centre for Addiction and Mental Health" + "author_name": "Oliver C. Grant", + "author_inst": "University of Georgia" }, { - "author_name": "Zhong Chen", - "author_inst": "Zhejiang Chinese Medical University" + "author_name": "David Montgomery", + "author_inst": "University of Georgia" }, { - "author_name": "Chengping Wen", - "author_inst": "Zhejiang Chinese Medical University" + "author_name": "Keigo Ito", + "author_inst": "University of Georgia" }, { - "author_name": "Zhenghao Xu", - "author_inst": "Zhejiang Chinese Medical University" + "author_name": "Robert J Woods", + "author_inst": "University of Georgia" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "neuroscience" + "category": "immunology" }, { "rel_doi": "10.1101/2020.04.07.029934", @@ -1580051,51 +1580964,27 @@ "category": "molecular biology" }, { - "rel_doi": "10.1101/2020.04.03.20052548", - "rel_title": "Lack of Antiviral Activity of Darunavir against SARS-CoV-2", + "rel_doi": "10.1101/2020.04.06.028811", + "rel_title": "The Potential Use of Unprocessed Sample for RT-qPCR Detection of COVID-19 without an RNA Extraction Step", "rel_date": "2020-04-08", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20052548", - "rel_abs": "Given the high need and the absence of specific antivirals for treatment of COVID-19 (the disease caused by severe acute respiratory syndrome-associated coronavirus-2 [SARS-CoV-2]), human immunodeficiency virus (HIV) protease inhibitors are being considered as therapeutic alternatives. Prezcobix/Rezolsta is a fixed-dose combination of 800 mg of the HIV protease inhibitor darunavir (DRV) and 150 mg cobicistat, a CYP3A4 inhibitor, which is indicated in combination with other antiretroviral agents for the treatment of HIV infection. There are currently no definitive data on the safety and efficacy of DRV/cobicistat for treatment of COVID-19. The in vitro antiviral activity of darunavir against a clinical isolate from a patient infected with SARS-CoV-2 was assessed. DRV showed no activity against SARS-CoV-2 at clinically relevant concentrations (EC50 >100 M). Remdesivir, used as a positive control, showed potent antiviral activity (EC50 = 0.38 M). Overall, the data do not support the use of DRV for treatment of COVID-19.", - "rel_num_authors": 8, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.04.06.028811", + "rel_abs": "Quantitative reverse transcription polymerase chain reaction (RT-qPCR) assay is the gold standard recommended to test for acute SARS-CoV-2 infection.1-4 It has been used by the Centers for Disease Control and Prevention (CDC) and several other companies in their Emergency Use Authorization (EUA) assays. With many PCR-based molecular assays, an extraction step is routinely used as part of the protocol. This step can take up a significant amount of time and labor, especially if the extraction is performed manually. Long assay time, partly caused by slow sample preparation steps, has created a large backlog when testing patient samples suspected of COVID-19. Using flu and RSV clinical specimens, we have collected evidence that the RT-qPCR assay can be performed directly on patient sample material from a nasal swab immersed in virus transport medium (VTM) without an RNA extraction step. We have also used this approach to test for the direct detection of SARS-CoV-2 reference materials spiked in VTM. Our data, while preliminary, suggest that using a few microliters of these untreated samples still can lead to sensitive test results. If RNA extraction steps can be omitted without significantly affecting clinical sensitivity, the turn-around time of COVID-19 tests and the backlog we currently experience can be reduced drastically. Next, we will confirm our findings using patient samples.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Sandra De Meyer", - "author_inst": "Janssen Pharmaceutica" - }, - { - "author_name": "Denisa Bojkova", - "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany" - }, - { - "author_name": "Jindrich Cinati", - "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany" - }, - { - "author_name": "Ellen Van Damme", - "author_inst": "Janssen Pharmaceutica NV, Beerse, Belgium" - }, - { - "author_name": "Christophe Buyck", - "author_inst": "Janssen Pharmaceutica NV, Beerse, Belgium" - }, - { - "author_name": "Marnix Van Loock", - "author_inst": "Janssen Pharmaceutica NV, Beerse, Belgium" - }, - { - "author_name": "Brian Woodfall", - "author_inst": "Janssen Biopharma Inc, South San Francisco, CA, USA" + "author_name": "Arunkumar Arumugam", + "author_inst": "AI Biosciences, Inc." }, { - "author_name": "Sandra Ciesek", - "author_inst": "Institute of Medical Virology, University Hospital Frankfurt, Goethe University, Frankfurt am Main, Germany; German Center for Infection Research (DZIF), Frankf" + "author_name": "Season S Wong", + "author_inst": "AI Biosciences, Inc." } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nd", + "type": "new results", + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.04.03.20052530", @@ -1581389,17 +1582278,21 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.02.20050914", - "rel_title": "A statistical method of batch screening entrying population from abroad by stages and groups in COVID-19 nucleic acid testing", + "rel_doi": "10.1101/2020.04.02.20050153", + "rel_title": "CoViD19 Meta heuristicoptimization based forecast methodon time dependent bootstrappeddata", "rel_date": "2020-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20050914", - "rel_abs": "PurposeTo screen for COVID-19 patients in immigration using minimal nucleic acid testing (NAT).\n\nMethodsIn the first phase, nasopharyngeal swab samples from the inbound population were numbered and grouped. The samples in the group were mixed together, and a NAT test was performed. When the test result is negative, it means that everyone in the group is not infected and the screening of the group is complete. When the test results were positive, the group moved on to the second stage. In the second stage, all samples in the positive group will be tested individually for NAT.\n\nResultsThe advantages and considerations of the method are discussed. Prevalence in the incoming population was a determinant of the sample size within the group. The lower the incidence, the larger the sample size within the group, the higher the savings in NAT and testing costs.\n\nConclusionThis method has significant efficiency and cost advantages in COVID-19 screening. It can also be used to screen other populations, such as community populations and people at high risk of infection, etc.", - "rel_num_authors": 1, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20050153", + "rel_abs": "A compounded method - exploiting the searching capabilities of an operation research algorithm and the power of bootstrap techniques - is presented. The resulting algorithm has been successfully tested to predict the turning point reached by the epidemic curve followed by the CoViD-19 virus in Italy. Futures lines of research, which include the generalization of the method to a broad set of distribution, will be finally given.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Cheng Yuan yuan", - "author_inst": "Henan University Huaihe hospital" + "author_name": "Livio Fenga", + "author_inst": "Italian National Institute of Statistics" + }, + { + "author_name": "Carlo Del Castello", + "author_inst": "Kantar" } ], "version": "1", @@ -1582603,33 +1583496,49 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.04.20053629", - "rel_title": "Association of COVID-19 Infections in San Francisco in Early March 2020 with Travel to New York and Europe", + "rel_doi": "10.1101/2020.04.04.20053637", + "rel_title": "Estimate of the development of the epidemic reproduction number Rt from Coronavirus SARS-CoV-2 case data and implications for political measures based on prognostics", "rel_date": "2020-04-07", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.04.20053629", - "rel_abs": "Real-time dissemination of epidemiological survey data from positive COVID-19 cases is critical to support efforts to contain or reduce spread of viral infection in the community. Here we detected a significant association between domestic travel or travel to Europe and the identification of new cases in San Francisco, California, USA. These findings suggest that domestic and European travelers may need to be prioritized for evaluation of acute infection from COVID-19 in the setting of limited testing capacity.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.04.20053637", + "rel_abs": "The novel Coronavirus SARS-CoV-2 (COVID-19) has induced a world-wide pandemic and subsequent non-pharmaceutical interventions (NPI) in order to control the spreading of the virus. NPIs are considered to be critical in order to at least delay the peak number of infected individuals and to prevent the health care system becoming overwhelmed by the number of patients to treat in hospitals or in intensive care units (ICUs). However, there is also increasing concern that the NPIs in place would increase mortality because of other diseases, increase the frequency of suicide and increase the risk of an economic recession with unforeseeable implications. It is therefore instrumental to evaluate the necessity of NPIs and to monitor the progress of containment of virus spreading.\n\nWe used a data-driven estimation of the evolution of the reproduction number for viral spreading in Germany as well as in all its federal states. Based on an extended infection-epidemic model, parameterized with data from the Robert Koch Institute and, alternatively, with parameters stemming from a fit to the initial phase of COVID-19 spreading in different regions of Italy, we found that the reproduction number was decreased to a range below 1 in all federal states. The development in Germany suggests that NPIs can be partially released based on an established new culture of social distancing, face masks and mutual care within the population. However, any release of measures delays reaching low incidence numbers. The strategy to reduce daily new cases to a sufficiently low level to be controlled by contact tracing and testing turned out to work in Germany. This requires a responsible behaviour of the population, optimised contact tracing techniques and extended testing capacities in contact clusters.\n\nAuthor summaryAs of mid-June Germany was able to control the pandemic to an extent that the health care system was not overwhelmed and the daily new reported infections appear under control. We analysed the evolution of the reproduction number during the epidemic in Germany and the efficiency of non-pharmaceutical interventions (NPIs) in containing viral spread. The results suggest that the cultural change induced by NPIs in interpersonal interactions and distancing allows for a partial release of political measures. However, this requires a functional case isolation and contact tracing of new cases by local health departments, early identification of contact clusters and consequent isolation of those clusters.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Wei Gu", - "author_inst": "University of California, San Francisco" + "author_name": "Sahamoddin Khailaie", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Kevin Reyes", - "author_inst": "University of California, San Francisco" + "author_name": "Tanmay Mitra", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Elaine Hsu", - "author_inst": "University of California, San Francisco" + "author_name": "Arnab Bandyopadhyay", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Steve Miller", - "author_inst": "University of California, San Francisco" + "author_name": "Marta Schips", + "author_inst": "Helmholtz Centre for Infection Research" }, { - "author_name": "Charles Y Chiu", - "author_inst": "University of California, San Francisco" + "author_name": "Pietro Mascheroni", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Patrizio Vanella", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Berit Lange", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Sebastian Binder", + "author_inst": "Helmholtz Centre for Infection Research" + }, + { + "author_name": "Michael Meyer-Hermann", + "author_inst": "Helmholtz Centre for Infection Research" } ], "version": "1", @@ -1584021,29 +1584930,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.02.20051680", - "rel_title": "COVID-19 epidemic: Power law spread and flattening of the curve", + "rel_doi": "10.1101/2020.04.03.20051821", + "rel_title": "Predicting clinical needs derived from the COVID-19 pandemic: the case of Spain", "rel_date": "2020-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20051680", - "rel_abs": "In this paper, we analyze the real-time infection data of COVID-19 epidemic for nine nations. Our analysis is up to 7 April 2020. For China and South Korea, who have already flattened their infection curves, the number of infected individuals (I(t)) exhibits power-law behavior before flattening of the curve. Italy has transitioned to the power-law regime for some time. For the other six nations--USA, Spain, Germany, France, Japan, and India--a power-law regime is beginning to appear after exponential growth. We argue that the transition from an exponential regime to a power-law regime may act as an indicator for flattening of the epidemic curve. We also argue that long-term community transmission and/or the transmission by asymptomatic carriers traveling long distances may be inducing the power-law growth of the epidemic.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20051821", + "rel_abs": "BackgroundThe evolution of the pandemic caused by COVID-19, its high reproductive number and the associated clinical needs, is overwhelming national health systems. We propose a method for predicting both ICU requirements and the number of deaths, and which will enable the health authorities of the countries involved to plan the resources needed to face the pandemic as many days in advance as possible.\n\nMethodsWe use official Spanish data to predict ICU admissions and deaths based on the number of infections. We employ OLS to perform the econometric estimation, and through RMSE, MSE, MAPE, and SMAPE forecast performance measures we select the best lagged predictor of both dependent variables.\n\nFindingsFor Spain, our prediction shows that the best predictor of ICU admissions is the number of people infected eight days before, and that the best predictor of deaths is the number of people infected five days before. In the first case, we obtain a 98% coefficient of determination, and in the second a 97% coefficient. The estimated delayed elasticities find that a 1% increase in the number of cases today will imply a 0.72% increase in ICU patients eight days later and a 1.09% increase in the number of deaths five days later.\n\nInterpretationThe model is not intended to analyse the epidemiology of COVID-19. Our objective is rather to estimate a leading indicator of clinical needs. Having a forecast model available several days in advance can enable governments to more effectively face the gap between needs and resources triggered by the outbreak and thus reduce the deaths caused by COVID-19.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSDaily news regarding the exponential growth of those affected by COVID-19 shows that healthcare resources are being overwhelmed by clinical needs in many countries. In particular, serious problems are arising in the most affected countries due to the shortage of ICU beds and the large number of deaths that the authorities are unable to deal with. National health authorities do not have adequate prediction mechanisms to facilitate clinical crisis management. We have performed bibliographic searches of the usual terms used to designate COVID-19, together with those of \"prediction\", \"estimation\", \"ICU\", \"mortality\" and the like, both in Pubmed and in Google Scholar. The predictive literature related to COVID-19 remains very sparse and the few models that do exist are based on exponential adjustments for forecasting the population affected. However, these models lose their predictive accuracy when the growth rate of infections decreases, added to which such models fail to determine the most statistically efficient maximum prediction time.\n\nAdded value of this studyWe apply a previously unused method based on predictions through delayed logarithmic estimates of ICU admissions and deaths based on the number of infections. For Spain, we estimate that the best predictor of ICU admissions is the number of people infected eight days before and that the best predictor of deaths is the number of those infected five days before. The findings herald a step forward that improves the possibility of managing the health crisis.\n\nImplications of all the available evidenceWe provide a method to estimate a leading indicator of needs, which thus far has been unavailable to health authorities and which should allow them to plan for the resources required. Furthermore, it is a versatile and simple method that is applicable to any country, state, region, city or hospital area as well as to any type of health care need associated with the COVID-19 pandemic and similar future ones.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Mahendra K. Verma", - "author_inst": "I. I. T. Kanpur" + "author_name": "Luis Angel Hierro-Recio", + "author_inst": "University of Seville" }, { - "author_name": "Ali Asad", - "author_inst": "I. I. T. Kanpur" + "author_name": "Antonio Jose Garzon-Gordon", + "author_inst": "University of Seville" }, { - "author_name": "Soumyadeep Chatterjee", - "author_inst": "I. I. T. Kanpur" + "author_name": "Pedro Atienza-Montero", + "author_inst": "University of Seville" + }, + { + "author_name": "Jose Luis Marquez", + "author_inst": "Virgen del Rocio Hospital (Seville-Spain)" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1585259,53 +1586172,21 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.02.20050955", - "rel_title": "Reduction of lymphocyte at early stage elevates severity and death risk of COVID-19 patients: a hospital-based case-cohort study", + "rel_doi": "10.1101/2020.04.02.20050674", + "rel_title": "Dynamics of COVID-19 epidemics: SEIR models underestimate peak infection rates and overestimateepidemic duration", "rel_date": "2020-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20050955", - "rel_abs": "Background and objectiveSevere acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-induced coronavirus disease 2019 (COVID-19) has been pandemic worldwide. Several reports observed a reduction of lymphocytes among COVID-19 patients. However, clinical significance of lymphocyte reduction in COVID-19 patients remains unclear. The objective of this study was to analyze the association between lymphocyte reduction at early stage and the prognosis of COVID-19 patients.\n\nMethodsAll 192 hospitalized patients with COVID-19 were enrolled. Electronic medical records, including demographic data, clinical characteristics, comorbidities and exposure history, were collected. Biochemical indexes on admission and chest computed tomography (CT) were detected. Patients prognosis was followed up.\n\nResultsOn admission, 84 (43.8%) patients suffered from lymphocyte reduction among COVID-19 patients. The count and percentage of lymphocytes on admission were lower among more than seventy-year-old patients than those of younger patients. Multivariate logistic regression revealed that older age was a risk factor of lymphocyte reduction. Of interest, chest CT score, a key marker of lung injury, was increased among COVID-19 patients with lymphocyte reduction. By contrast, PaCO2, SpO2 and oxygenation index, several respiratory function markers, were decreased in COVID-19 patients with lymphocyte reduction. Moreover, TBIL and DBIL, two markers of hepatic injury, creatinine and urea nitrogen, two indices of renal function, and creatine kinase, AST and LDH, three myocardial enzymes, were elevated in COVID-19 patients with lymphocyte reduction. Among 84 COVID-19 patients with lymphocyte reduction, 32.1% died. Fatality rate was obviously higher in COVID-19 patients with lymphocyte reduction than those with normal lymphocyte (RR=5.789, P<0.001).\n\nConclusionOlder COVID-19 patients are more susceptible to lymphocyte reduction. Lymphocyte reduction at early stage aggravates the severity of multiple organ injuries and elevates death risk of COVID-19 patients.", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.02.20050674", + "rel_abs": "Compartment models of infectious diseases, such as SEIR, are being used extensively to model the COVID-19 epidemic. Transitions between compartments are modelled either as instantaneous rates in differential equations, or as transition probabilities in discrete time difference or matrix equations. These models give accurate estimates of the position of equilibrium points, when the rate at which individuals enter each stage is equal to the rate at which they exit from it. However, they do not accurately capture the distribution of times that an individual spends in each compartment, so do not accurately capture the transient dynamics of epidemics. Here we show how matrix models can provide a straightforward route to accurately model stage durations, and thus correctly reproduce epidemic dynamics. We apply this approach to modelling the dynamics of a COVID-19 epidemic. We show that a SEIR model underestimates peak infection rates (by a factor of three using published parameter estimates based on the progress of the epidemic in Wuhan) and substantially overestimates epidemic persistence after the peak has passed.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Jun Fei", - "author_inst": "Anhui Medical University" - }, - { - "author_name": "Lin Fu", - "author_inst": "Anhui Medical University" - }, - { - "author_name": "Ying Li", - "author_inst": "Huazhong University of Science and Technology" - }, - { - "author_name": "Hui-Xian Xiang", - "author_inst": "Anhui Medical University" - }, - { - "author_name": "Ying Xiang", - "author_inst": "Anhui Medical University" - }, - { - "author_name": "Meng-Die Li", - "author_inst": "Anhui Medical University" - }, - { - "author_name": "Fang-Fang Liu", - "author_inst": "Anhui Medical University" - }, - { - "author_name": "De-xiang Xu", - "author_inst": "Anhui Medical University" - }, - { - "author_name": "Hui Zhao", - "author_inst": "Anhui Medical University" + "author_name": "Alastair Grant", + "author_inst": "University of East Anglia" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1586377,83 +1587258,123 @@ "category": "public and global health" }, { - "rel_doi": "10.1101/2020.04.03.20051722", - "rel_title": "Urinalysis, but not blood biochemistry, detects the early renal-impairment in patients with COVID-19", + "rel_doi": "10.1101/2020.04.03.20047977", + "rel_title": "ACE2 variants underlie interindividual variability and susceptibility to COVID-19 in Italian population", "rel_date": "2020-04-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20051722", - "rel_abs": "BackgroundIn December 2019, a novel coronavirus (SARS-CoV-2) caused infectious disease, termed COVID-19, outbroke in Wuhan, China. COVID-19 patients manifested as lung injury with complications in other organs, such as liver, heart, gastrointestinal tract, especially for severe cases. However, whether COVID-19 causes significant acute kidney injury (AKI) remained controversial.\n\nMethodsWe retrospectively analyzed the clinical characteristics, urine and blood routine tests and other laboratory parameters of hospitalized COVID-19 patients in Wuhan Union Hospital.\n\nFindings178 patients, admitted to Wuhan Union hospital from February 02 to February 29, 2020, were included in this study. No patient (0 [0%]) presented increased serum creatinine (Scr), and 5 (2.8%) patients showed increased blood urea nitrogen (BUN), indicating few cases with \"kidney dysfunction\". However,for patients (83) with no history of kidney disease who received routine urine test upon hospitalization, 45 (54.2%) patients displayed abnormality in urinalysis, such as proteinuria, hematuria and leukocyturia, while none of the patients was recorded to have acute kidney injury (AKI) throughout the study. Meanwhile, the patients with abnormal urinalysis usually had worse disease progression reflecting by laboratory parameters presentations, including markers of liver injury, inflammation, and coagulation.\n\nConclusionMany patients manifested by abnormal urinalysis on admission, including proteinuria or hematuria. Our results revealed that urinalysis is better in unveiling potential kidney impairment of COVID-19 patients than blood chemistry test and urinalysis could be used to reflect and predict the disease severity. We therefore recommend pay more attention in urinalysis and kidney impairment in COVID-19 patients.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.03.20047977", + "rel_abs": "In December 2019, an initial cluster of interstitial bilateral pneumonia emerged in Wuhan, China. A human-to-human transmission was assumed and a previously unrecognized entity, termed coronavirus-disease-19 (COVID-19) due to a novel coronavirus (SARS-CoV-2) was described. The infection has rapidly spread out all over the world and Italy has been the first European country experiencing the endemic wave with unexpected clinical severity in comparison with Asian countries.\n\nIt has been shown that SARS-CoV-2 utilizes angiotensin converting enzyme 2 (ACE2) as host receptor and host proteases for cell surface binding and internalization. Thus, a predisposing genetic background can give reason for inter-individual disease susceptibility and/or severity. Taking advantage of the Network of Italian Genomes (NIG), here we mined whole-exome-sequencing data of 6930 Italian control individuals from five different centers looking for ACE2 variants. A number of variants with a potential impact on protein stability were identified. Among these, three more common missense changes, p.(Asn720Asp), p.(Lys26Arg), p.(Gly211Arg) were predicted to interfere with protein structure and stabilization. Rare variants likely interfering with the internalization process, namely p.(Leu351Val) and p.(Pro389His), predicted to interfere with SARS-CoV-2 spike protein binding, were also observed. Comparison of ACE2 WES data between a cohort of 131 patients and 258 controls allowed identifying a statistically significant (P value <0,029) higher allelic variability in controls compared to patients. These findings suggest that a predisposing genetic background may contribute to the observed inter-individual clinical variability associated with COVID-19, allowing an evidence-based risk assessment leading to personalized preventive measures and therapeutic options.", + "rel_num_authors": 26, "rel_authors": [ { - "author_name": "Haifeng zhou Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Elisa Benetti", + "author_inst": "University of Siena" }, { - "author_name": "Zili Zhang Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Rossella Tita", + "author_inst": "Azienda Ospedaliera Universitaria Senese" }, { - "author_name": "Heng Fan Sr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Ottavia Spiga", + "author_inst": "University of Siena" }, { - "author_name": "Junyi Li Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Andrea Ciolfi", + "author_inst": "Ospedale Pediatrico Bambino Gesu, Roma" }, { - "author_name": "Mingyue Li Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Giovanni Birolo", + "author_inst": "University of Turin, Turin" }, { - "author_name": "Yalan Dong Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Alessandro Bruselles", + "author_inst": "Istituto Superiore di Sanita, Rome" }, { - "author_name": "Weina Guo Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Gabriella Doddato", + "author_inst": "University of Siena" }, { - "author_name": "Lan Lin Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Annarita Giliberti", + "author_inst": "University of Siena" }, { - "author_name": "Zhenyu Kang Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Cterina Marconi", + "author_inst": "University of Bologna" }, { - "author_name": "Ting Yu Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Francesco Musacchia", + "author_inst": "Telethon Institute of Genetics and Medicine, Pozzuoli, Italy" }, { - "author_name": "Chunxia Tian Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Tommaso Pippucci", + "author_inst": "Sant Orsola Malpighi University Hospital, Bologna" }, { - "author_name": "Yang Gui Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Annalaura Torella", + "author_inst": "University of Campania Luigi Vanvitelli, Caserta, Italy" }, { - "author_name": "Renjie Qin Jr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Alfonso Trezza", + "author_inst": "University of Siena" }, { - "author_name": "Haijun Wang Sr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Floriana Valentino", + "author_inst": "University of Siena" }, { - "author_name": "ShanShan Luo Sr.", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Mrgherita Baldassarri", + "author_inst": "University of Siena" }, { - "author_name": "Desheng Hu", - "author_inst": "Union Hospital, Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Alfredo Brusco", + "author_inst": "University of Turin" + }, + { + "author_name": "Rosanna Asselta", + "author_inst": "Humanitas University, Rozzano, Milan, Italy" + }, + { + "author_name": "Bruttini Mirella", + "author_inst": "University of Siena" + }, + { + "author_name": "Simone Furini", + "author_inst": "University of Siena" + }, + { + "author_name": "Marco Seri", + "author_inst": "University of Bologna" + }, + { + "author_name": "Vincenzo Nigro", + "author_inst": "University of Campania Luigi Vanvitelli, Napoli, Italy" + }, + { + "author_name": "Giuseppe Matullo", + "author_inst": "University of Turin, Turin, Italy" + }, + { + "author_name": "Marco Tartaglia", + "author_inst": "Ospedale Pediatrico Bambino Gesu, Rome, Italy" + }, + { + "author_name": "Francesca Mari", + "author_inst": "University of Siena" + }, + { + "author_name": "Alessandra Renieri", + "author_inst": "University of Siena" + }, + { + "author_name": "Annamaria Pinto", + "author_inst": "Azienda Ospedaliera Universitaria Senese" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "urology" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2020.04.03.20047530", @@ -1587739,39 +1588660,47 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.04.01.20041186", - "rel_title": "Countrywide quarantine only mildly increased anxiety level during COVID-19 outbreak in China", + "rel_doi": "10.1101/2020.03.30.20044545", + "rel_title": "A Mini Review on Current Clinical and Research Findings for Children Suffering from COVID-19", "rel_date": "2020-04-04", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.01.20041186", - "rel_abs": "In the recent outbreak of COVID-19, many countries have taken various kinds of quarantine measures to slow down the explosive spreading of COVID-19. Although these measures were proven to be successful in stopping the outbreak in China, the potential adverse effects of countrywide quarantine have not been thoroughly investigated. In this study, we performed an online survey to evaluate the psychological effects of quarantine in China using Zung Self-rating Anxiety Scale in February 2020 when the outbreak was nearly peaked in China. Along with the anxiety scores, limited personal information such as age, gender, region, education, occupation and specifically, the type and duration of quarantine were collected for analysis. For a total number of 992 valid questionnaires, clinical significance of anxiety symptoms was observed in 9.58% respondents according to clinical diagnostic standards in China. Statistical results showed population with different age, education level, health status and personnel category responded differently. Other characteristics such as gender, marital status, region, and acquaintance with suspected or confirmed cases of COVID-19 did not affect anxiety levels significantly. Respondents experienced different forms of quarantine showed different anxiety levels. Unexpectedly, longer durations of quarantine did not lead to significant increase of anxiety level. Our results suggest a rather mild psychological influence caused by the countrywide quarantine during COVID-19 outbreak in China and provided reference for other countries and regions to battle COVID-19.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.30.20044545", + "rel_abs": "BackgroundAs the novel coronavirus triggering COVID-19 has broken out in Wuhan, China and spread rapidly worldwide, it threatens the lives of thousands of people and poses a global threat on the economies of the entire world. However, infection with COVID-19 is currently rare in children.\n\nObjectiveTo discuss the latest findings and research focus on the basis of characteristics of children confirmed with COVID-19, and provide an insight into the future treatment and research direction.\n\nMethodsWe searched the terms \"COVID-19 OR coronavirus OR SARS-CoV-2\" AND \"Pediatric OR children\" on PubMed, Embase, Cochrane library, NIH, CDC, and CNKI. The authors also reviewed the guidelines published on Chinese CDC and Chinese NHC.\n\nResultsWe included 25 published literature references related to the epidemiology, clinical manifestation, accessary examination, treatment, and prognosis of pediatric patients with COVID-19.\n\nConclusionThe numbers of children with COVID-19 pneumonia infection are small, and most of them come from family aggregation. Symptoms are mainly mild or even asymptomatic, which allow children to be a risk factor for transmission. Thus, strict epidemiological history screening is needed for early diagnosis and segregation. This holds especially for infants, who are more susceptible to infection than other age groups in pediatric age, but have most likely subtle and unspecific symptoms. They need to be paid more attention to. CT examination is a necessity for screening the suspected cases, because most of the pediatric patients are mild cases, and plain chest X-ray do not usually show the lesions or the detailed features. Therefore, early chest CT examination combined with pathogenic detection is a recommended clinical diagnosis scheme in children. The risk factors which may suggest severe or critical progress for children are: Fast respiratory rate and/or; lethargy and drowsiness mental state and/or; lactate progressively increasing and/or; imaging showed bilateral or multi lobed infiltration, pleural effusion or rapidly expending of lesions in a short period of time and/or; less than 3 months old or those who underly diseases. For those critical pediatric patients with positive SARS-CoV-2 diagnosis, polypnea may be the most common symptom. For treatment, the elevated PCT seen in children in contrast to adults suggests that the underlying coinfection/secondary infection may be more common in pediatric patients and appropriate antibacterial treatment should be considered. Once cytokine storm is found in these patients, anti-autoimmune or blood-purifying therapy should be given in time. Furthermore, effective isolation measures and appropriate psychological comfort need to be provided timely.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Wei Hu", - "author_inst": "Xuzhou Oriental People's Hospital" + "author_name": "Xiao Li", + "author_inst": "Childrens Hospital of Chongqing Medical University, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Tec" }, { - "author_name": "Li Su", - "author_inst": "Institute of Psychology, Chinese Academy of Sciences" + "author_name": "Kun Qian", + "author_inst": "The University of Tokyo" }, { - "author_name": "Juan Qiao", - "author_inst": "Xuzhou Oriental People's Hospital" + "author_name": "Ling-ling Xie", + "author_inst": "Childrens Hospital of Chongqing Medical University, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Tec" }, { - "author_name": "Jing Zhu", - "author_inst": "Xuzhou Oriental People's Hospital" + "author_name": "Xiu-juan Li", + "author_inst": "Children's Hospital of Chongqing Medical University, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Te" }, { - "author_name": "Yi Zhou", - "author_inst": "Army Medical University" + "author_name": "Min Cheng", + "author_inst": "Children's Hospital of Chongqing Medical University, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Te" + }, + { + "author_name": "Li Jiang", + "author_inst": "Children's Hospital of Chongqing Medical University, Ministry of Education Key Laboratory of Child Development and Disorders, China International Science and Te" + }, + { + "author_name": "Bjoern W. Schuller", + "author_inst": "Imperial College London" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "pediatrics" }, { "rel_doi": "10.1101/2020.04.01.20047381", @@ -1589061,41 +1589990,29 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.04.01.20050526", - "rel_title": "Meteorological factors correlate with transmission of 2019-nCoV: Proof of incidence of novel coronavirus pneumonia in Hubei Province, China", + "rel_doi": "10.1101/2020.04.01.20050542", + "rel_title": "Using ILI surveillance to estimate state-specific case detection rates and forecast SARS-CoV-2 spread in the United States", "rel_date": "2020-04-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.01.20050526", - "rel_abs": "Objectivemany potential factors contribute to the outbreak of COVID-19.It aims to explore the effects of various meteorological factors on the incidence of COVID-19.\n\nMethodsTaking Hubei province of China as an example, where COVID-19 was first reported and there were the most cases, we collected 53 days of confirmed cases (total 67773 cases) and ten meteorological parameters up to March 10. Correlation analysis and linear regression were used to judge the relationship of meteorological factors and increment of COVID-19 confirmed cases.\n\nResultsUnder 95% CI, the increment of confirmed cases in Hubei were correlated with four meteorological parameters of average pressure, average temperature, minimum temperature and average water vapor pressure (equivalent to absolute humidity).The average pressure was positively correlated with the increment (r=+0.358).The negative correlations included average temperature (r=-0.306), minimum temperature (r=-0.347), and average water vapor pressure (r=-0.326). The linear regression results show if minimum temperature increases by 1{square}, the incremental confirmed cases in Hubei decreases by 72.470 units on average.\n\nConclusionStatistically, the incidence of COVID-19 was correlated with average pressure, average temperature, minimum temperature and average water vapor pressure. It is positively correlated with the average pressure and negatively correlated with the other three parameters. Compared with relative humidity, 2019-nCov is more sensitive to water vapor pressure. The reason why the epidemic situation in Hubei expanded rapidly is significantly related to the climate characteristics of low temperature and dryness of Hubei in winter.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.04.01.20050542", + "rel_abs": "Detection of SARS-CoV-2 infections to date has relied on RT-PCR testing. However, a failure to identify early cases imported to a country, bottlenecks in RT-PCR testing, and the existence of infections which are asymptomatic, sub-clinical, or with an alternative presentation than the standard cough and fever have resulted in an under-counting of the true prevalence of SARS-CoV-2. Here, we show how publicly available CDC influenza-like illness (ILI) outpatient surveillance data can be repurposed to estimate the detection rate of symptomatic SARS-CoV-2 infections. We find a surge of non-influenza ILI above the seasonal average and show that this surge is correlated with COVID case counts across states. By quantifying the number of excess ILI patients in March relative to previous years and comparing excess ILI to confirmed COVID case counts, we estimate the syndromic case detection rate of SARS-CoV-2 in the US to be less than 13%. If only 1/3 of patients infected with SARS-CoV-2 sought care, the ILI surge would correspond to more than 8.7 million new SARS-CoV-2 infections across the US during the three week period from March 8 to March 28. Combining excess ILI counts with the date of onset of community transmission in the US, we also show that the early epidemic in the US was unlikely to be doubling slower than every 4 days. Together these results suggest a conceptual model for the COVID epidemic in the US in which rapid spread across the US are combined with a large population of infected patients with presumably mild-to-moderate clinical symptoms. We emphasize the importance of testing these findings with seroprevalence data, and discuss the broader potential to use syndromic time series for early detection and understanding of emerging infectious diseases.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jianfeng Li", - "author_inst": "Beijing Municipal Institute of Labour Protections, Beijing Academy of Science and Technology" - }, - { - "author_name": "Linyuan Zhang", - "author_inst": "National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention" - }, - { - "author_name": "Zhihua Ren", - "author_inst": "National Meteorological Information Center, China Meteorological Administration Meteorological Data Center" - }, - { - "author_name": "Caihong Xing", - "author_inst": "National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention" + "author_name": "Justin D Silverman", + "author_inst": "Penn State" }, { - "author_name": "Peihuan Qiao", - "author_inst": "National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention" + "author_name": "Nathaniel Hupert", + "author_inst": "Weill Cornell Medicine, Cornell University" }, { - "author_name": "Bing Chang", - "author_inst": "National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention" + "author_name": "Alex D Washburne", + "author_inst": "Montana State University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1590219,83 +1591136,63 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.03.31.019216", - "rel_title": "Virus-host interactome and proteomic survey of PMBCs from COVID-19 patients reveal potential virulence factors influencing SARS-CoV-2 pathogenesis", + "rel_doi": "10.1101/2020.03.31.013268", + "rel_title": "SARS-CoV-2 receptor and entry genes are expressed by sustentacular cells in the human olfactory neuroepithelium", "rel_date": "2020-04-02", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.31.019216", - "rel_abs": "The ongoing coronavirus disease (COVID-19) pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a global public health concern due to relatively easy person-to-person transmission and the current lack of effective antiviral therapy. However, the exact molecular mechanisms of SARS-CoV-2 pathogenesis remain largely unknown. We exploited an integrated proteomics approach to systematically investigate intra-viral and virus-host interactomes for the identification of unrealized SARS-CoV-2 host targets and participation of cellular proteins in the response to viral infection using peripheral blood mononuclear cells (PBMCs) isolated from COVID-19 patients. Using this approach, we elucidated 251 host proteins targeted by SARS-CoV-2 and more than 200 host proteins that are significantly perturbed in COVID-19 derived PBMCs. From the interactome, we further identified that non-structural protein nsp9 and nsp10 interact with NKRF, a NF-[Kcy]B repressor, and may precipitate the strong IL-8/IL-6 mediated chemotaxis of neutrophils and overexuberant host inflammatory response observed in COVID-19 patients. Our integrative study not only presents a systematic examination of SARS-CoV-2-induced perturbation of host targets and cellular networks to reflect disease etiology, but also reveals insights into the mechanisms by which SARS-CoV-2 triggers cytokine storms and represents a powerful resource in the quest for therapeutic intervention.", - "rel_num_authors": 16, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.31.013268", + "rel_abs": "Various reports indicate an association between COVID-19 and anosmia, suggesting an infection of the olfactory sensory epithelium, and thus a possible direct virus access to the brain. To test this hypothesis, we generated RNA-seq libraries from human olfactory neuroepithelia, in which we found substantial expression of the genes coding for the virus receptor angiotensin-converting enzyme-2 (ACE2), and for the virus internalization enhancer TMPRSS2. We analyzed a human olfactory single-cell RNA-seq dataset and determined that sustentacular cells, which maintain the integrity of olfactory sensory neurons, express ACE2 and TMPRSS2. We then observed that the ACE2 protein was highly expressed in a subset of sustentacular cells in human and mouse olfactory tissues. Finally, we found ACE2 transcripts in specific brain cell types, both in mice and humans. Sustentacular cells thus represent a potential entry door for SARS-CoV-2 in a neuronal sensory system that is in direct connection with the brain.", + "rel_num_authors": 11, "rel_authors": [ { - "author_name": "Qiming Liang", - "author_inst": "Shanghai Jiao Tong University School of Medicine" - }, - { - "author_name": "Jingjiao Li", - "author_inst": "Shanghai Jiao Tong University School of Medicine" - }, - { - "author_name": "Mingquan Guo", - "author_inst": "Shanghai Public Health Clinical Center, Fudan University," - }, - { - "author_name": "Xiaoxu Tian", - "author_inst": "Shanghai Advanced Research Institute, Chinese Academy of Sciences" - }, - { - "author_name": "Chengrong Liu", - "author_inst": "Shanghai Jiao Tong University School of Medicine" - }, - { - "author_name": "Xin Wang", - "author_inst": "Shanghai Jiao Tong University School of Medicine" + "author_name": "Leon Fodoulian", + "author_inst": "University of Geneva" }, { - "author_name": "Xing Yang", - "author_inst": "Shanghai Jiao Tong University School of Medicine" + "author_name": "Joel Tuberosa", + "author_inst": "University of Geneva" }, { - "author_name": "Ping Wu", - "author_inst": "Shanghai Advanced Research Institute, Chinese Academy of Sciences" + "author_name": "Daniel Rossier", + "author_inst": "University of Geneva" }, { - "author_name": "Zixuan Xiao", - "author_inst": "University of Alberta, Canada" + "author_name": "Madlaina Boillat", + "author_inst": "University of Geneva" }, { - "author_name": "Yafei Qu", - "author_inst": "Shanghai Jiao Tong University School of Medicine" + "author_name": "Chen-Da Kan", + "author_inst": "University of Geneva" }, { - "author_name": "Yue Yin", - "author_inst": "Shanghai Advanced Research Institute, Chinese Academy of Sciences" + "author_name": "Veronique Pauli", + "author_inst": "University of Geneva" }, { - "author_name": "Joyce Fu", - "author_inst": "University of California, Riverside" + "author_name": "Kristof Egervari", + "author_inst": "University of Geneva" }, { - "author_name": "Zhaoqin Zhu", - "author_inst": "Shanghai Public Health Clinical Center, Fudan University" + "author_name": "Johannes A. Lobrinus", + "author_inst": "Geneva University Hospital" }, { - "author_name": "Zhenshan Liu", - "author_inst": "Shanghai Jiao Tong University School of Medicine" + "author_name": "Basile Landis", + "author_inst": "Geneva University Hospitals" }, { - "author_name": "Chao Peng", - "author_inst": "Shanghai Advanced Research Institute, Chinese Academy of Sciences" + "author_name": "Alan Carleton", + "author_inst": "University of Geneva" }, { - "author_name": "Tongyu Zhu", - "author_inst": "Shanghai Public Health Clinical Center, Fudan University" + "author_name": "Ivan Rodriguez", + "author_inst": "University of Geneva" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "microbiology" + "category": "neuroscience" }, { "rel_doi": "10.1101/2020.03.30.014555", @@ -1591365,21 +1592262,21 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.03.27.20045062", - "rel_title": "How lethal is the novel coronavirus, and how many undetected cases there are? The importance of being tested.", + "rel_doi": "10.1101/2020.03.29.20046862", + "rel_title": "Stochastic Compartmental Modelling of SARS-CoV-2 with Approximate Bayesian Computation", "rel_date": "2020-04-01", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.27.20045062", - "rel_abs": "There is big concern for estimating the lethality and the extent of undetected infections associated with the novel coronavirus SARS-CoV2 outbreak. While detailed epidemiological models are certainly needed, I suggest here an orthogonal approach based on a minimum number of parameters robustly fitted from the cumulative data easily accessible for all countries at the John Hopkins University database that became the worldwide reference for the pandemics. I show that, after few days from the beginning of the outbreak, the apparent death rate can be extrapolated to infinite time through regularized regression such as rescaled ridge regression. The variation from country to country of these extrapolated death rates appears to depend almost only (r2 = 0.91) on the ratio between performed tests and detected cases even when the apparent instantaneous lethality rates are as different as 9% in Italy and 0.4% in Germany. Extrapolating to the limit of infinite number of tests, I obtain a death rate of 0.012 {+/-} 0.012, in agreement with other estimates. The inverse relationship between the extrapolated death rate and the intensity tests allows estimating that more than 50% of cases were undetected in most countries, with more than 90% undetected cases in countries severely hit by the epidemics such as Italy. Finally, I propose to adopt the ratio between the cumulative number of recovered and deceased persons as an indicator that can anticipate the halting of the epidemics.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.29.20046862", + "rel_abs": "In this proof-of-concept study, we model the spread of SARS-CoV-2 in various environments with a stochastic susceptible-infectious-recovered (SIR) compartmental model. We fit this model to the latest epidemic data with an approximate Bayesian computation (ABC) technique. Within this SIR-ABC framework, we extrapolate long-term infection curves for several regions and evaluate their steepness. We propose several applications and extensions of the SIR-ABC technique.", "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Ugo Bastolla", - "author_inst": "CSIC" + "author_name": "Vedant Chandra", + "author_inst": "Department of Physics and Astronomy, Johns Hopkins University" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1592598,31 +1593495,31 @@ "category": "cell biology" }, { - "rel_doi": "10.1101/2020.03.28.013607", - "rel_title": "Computational Design of Peptides to Block Binding of the SARS-CoV-2 Spike Protein to Human ACE2", + "rel_doi": "10.1101/2020.03.29.013342", + "rel_title": "A one-enzyme RT-qPCR assay for SARS-CoV-2, and procedures for reagent production", "rel_date": "2020-03-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.28.013607", - "rel_abs": "The outbreak of COVID-19 has now become a global pandemic and it continues to spread rapidly worldwide, severely threatening lives and economic stability. Making the problem worse, there is no specific antiviral drug that can be used to treat COVID-19 to date. SARS-CoV-2 initiates its entry into human cells by binding to angiotensin-converting enzyme 2 (hACE2) via the receptor binding domain (RBD) of its spike protein. Therefore, molecules that can block SARS-CoV-2 from binding to hACE2 may potentially prevent the virus from entering human cells and serve as an effective antiviral drug. Based on this idea, we designed a series of peptides that can strongly bind to SARS-CoV-2 RBD in computational experiments. Specifically, we first constructed a 31-mer peptidic scaffold by linking two fragments grafted from hACE2 (a.a. 22-44 and 351-357) with a linker glycine, and then redesigned the peptide sequence to enhance its binding affinity to SARS-CoV-2 RBD. Compared with several computational studies that failed to identify that SARS-CoV-2 shows higher binding affinity for hACE2 than SARS-CoV, our protein design scoring function, EvoEF2, makes a correct identification, which is consistent with the recently reported experimental data, implying its high accuracy. The top designed peptide binders exhibited much stronger binding potency to hACE2 than the wild-type (-53.35 vs. -46.46 EvoEF2 energy unit for design and wild-type, respectively). The extensive and detailed computational analyses support the high reasonability of the designed binders, which not only recapitulated the critical native binding interactions but also introduced new favorable interactions to enhance binding. Due to the urgent situation created by COVID-19, we share these computational data to the community, which should be helpful to develop potential antiviral peptide drugs to combat this pandemic.", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.29.013342", + "rel_abs": "ABSTRACTGiven the scale of the ongoing COVID-19 pandemic, the need for reliable, scalable testing, and the likelihood of reagent shortages, especially in resource-poor settings, we have developed a RT-qPCR assay that relies on an alternative to conventional viral reverse transcriptases, a thermostable reverse transcriptase / DNA polymerase (RTX)1. Here we show that RTX performs comparably to the other assays sanctioned by the CDC and validated in kit format. We demonstrate two modes of RTX use \u2013 (i) dye-based RT-qPCR assays that require only RTX polymerase, and (ii) TaqMan RT-qPCR assays that use a combination of RTX and Taq DNA polymerases (as the RTX exonuclease does not degrade a TaqMan probe). We also provide straightforward recipes for the purification of this alternative reagent. We anticipate that in low resource or point-of-need settings researchers could obtain the available constructs from Addgene or our lab and begin to develop their own assays, within whatever regulatory framework exists for them.We lay out protocols for dye-based and TaqMan probe-based assays, in order to best compare with \u2018gold standard\u2019 reagents. These protocols should form the basis of further modifications that can simplify the assay to the use of overexpressing cells themselves as reagents.Developing dye-based and TaqMan probe-based RT-qPCR assays with RTXCompeting Interest StatementThe authors have declared no competing interest.View Full Text", "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Xiaoqiang Huang", - "author_inst": "University of Michigan" + "author_name": "Sanchita Bhadra", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Robin Pearce", - "author_inst": "University of Michigan" + "author_name": "Andre C Maranhao", + "author_inst": "University of Texas at Austin" }, { - "author_name": "Yang Zhang", - "author_inst": "University of Michigan" + "author_name": "Andrew D Ellington", + "author_inst": "University of Texas at Austin" } ], "version": "1", "license": "cc_by_nc_nd", "type": "new results", - "category": "bioinformatics" + "category": "molecular biology" }, { "rel_doi": "10.1101/2020.03.30.015008", @@ -1594228,83 +1595125,51 @@ "category": "psychiatry and clinical psychology" }, { - "rel_doi": "10.1101/2020.03.27.20045757", - "rel_title": "Changing transmission dynamics of COVID-19 in China: a nationwide population-based piecewise mathematical modelling study", + "rel_doi": "10.1101/2020.03.23.20041350", + "rel_title": "Genetic Profiles in Pharmacogenes Indicate Personalized Drug Therapy for COVID-19", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.27.20045757", - "rel_abs": "BackgroundThe first case of COVID-19 atypical pneumonia was reported in Wuhan, China on December 1, 2019. Since then, at least 33 other countries have been affected and there is a possibility of a global outbreak. A tremendous amount of effort has been made to understand its transmission dynamics; however, the temporal and spatial transmission heterogeneity and changing epidemiology have been mostly ignored. The epidemic mechanism of COVID-19 remains largely unclear.\n\nMethodsEpidemiological data on COVID-19 in China and daily population movement data from Wuhan to other cities were obtained and analyzed. To describe the transmission dynamics of COVID-19 at different spatio-temporal scales, we used a three-stage continuous-time Susceptible-Exposed-Infectious-Recovered (SEIR) meta-population model based on the characteristics and transmission dynamics of each stage: 1) local epidemic from December 1, 2019 to January 9, 2020; 2) long-distance spread due to the Spring Festival travel rush from January 10 to 22, 2020; and 3) intra-provincial transmission from January 23, 2020 when travel restrictions were imposed. Together with the basic reproduction number (R0) for mathematical modelling, we also considered the variation in infectivity and introduced the controlled reproduction number (Rc) by assuming that exposed individuals to be infectious; we then simulated the future spread of COVID across Wuhan and all the provinces in mainland China. In addition, we built a novel source tracing algorithm to infer the initial exposed number of individuals in Wuhan on January 10, 2020, to estimate the number of infections early during this epidemic.\n\nFindingsThe spatial patterns of disease spread were heterogeneous. The estimated controlled reproduction number (Rc) in the neighboring provinces of Hubei province were relatively large, and the nationwide reproduction number - except for Hubei - ranged from 0.98 to 2.74 with an average of 1.79 (95% CI 1.77-1.80). Infectivity was significantly greater for exposed than infectious individuals, and exposed individuals were predicted to have become the major source of infection after January 23. For the epidemic process, most provinces reached their epidemic peak before February 10, 2020. It is expected that the maximum number of infections will be approached by the end of March. The final infectious size is estimated to be about 58,000 for Wuhan, 20,800 for the rest of Hubei province, and 17,000 for the other provinces in mainland China. Moreover, the estimated number of the exposed individuals is much greater than the officially reported number of infectious individuals in Wuhan on January 10, 2020.\n\nInterpretationThe transmission dynamics of COVID-19 have been changing over time and were heterogeneous across regions. There was a substantial underestimation of the number of exposed individuals in Wuhan early in the epidemic, and the Spring Festival travel rush played an important role in enhancing and accelerating the spread of COVID-19. However, Chinas unprecedented large-scale travel restrictions quickly reduced Rc. The next challenge for the control of COVID-19 will be the second great population movement brought by removing these travel restrictions.", - "rel_num_authors": 16, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.23.20041350", + "rel_abs": "BackgroundThe coronavirus disease 2019 (COVID-19) has become a global pandemic currently. Many drugs showed potential for COVID-19 therapy. However, genetic factors which can lead to different drug efficiency and toxicity among populations are still undisclosed in COVID-19 therapy.\n\nMethodsWe selected 67 potential drugs for COVID-19 therapy (DCTs) from clinical guideline and clinical trials databases. 313 pharmaco-genes related to these therapeutic drugs were included. Variation information in 125,748 exomes were collected for racial differences analyses. The expression level of pharmaco-genes in single cell resolution was evaluated from single-cell RNA sequencing (scRNA-seq) data of 17 healthy adults.\n\nResultsPharmacogenes, including CYP3A4, ABCB1, SLCO1B1, ALB, CYP3A5, were involved in the process of more than multi DCTs. 224 potential drug-drug interactions (DDIs) of DCTs were predicted, while 112 of them have been reported. Racial discrepancy of common nonsynonymous mutations was found in pharmacogenes including: VDR, ITPA, G6PD, CYP3A4 and ABCB1 which related to DCTs including ribavirin, -interferon, chloroquine and lopinavir. Moreover, ACE2, the target of 2019-nCoV, was only found in parts of lung cells, which makes drugs like chloroquine that prevent virus binding to ACE2 more specific than other targeted drugs such as camostat mesylate.\n\nConclusionsAt least 17 drugs for COVID-19 therapy with predictable pharmacogenes should be carefully utilized in risk races which are consisted of more risk allele carriers. At least 29 drugs with potential of DDIs are reported to be affected by other DDIs, they should be replaced by similar drugs without interaction if it is possible. Drugs which specifically targeted to infected cells with ACE2 such as chloroquine are preferred in COVID-19 therapy.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Jiawen Hou", - "author_inst": "Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai 200433, China; Centre for Computational Systems Biology and Rese" - }, - { - "author_name": "Jie Hong", - "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Min" - }, - { - "author_name": "Boyun Ji", - "author_inst": "School of Mathematical Sciences and Shanghai Center for Mathematical Sciences, Fudan University, Shanghai 200433, China" - }, - { - "author_name": "Bowen Dong", - "author_inst": "School of Mathematical Sciences and Shanghai Center for Mathematical Sciences, Fudan University, Shanghai 200433, China" - }, - { - "author_name": "Yue Chen", - "author_inst": "Department of Epidemiology and Community Medicine, Faculty of Medicine, University of Ottawa, 451 Smyth Rd, Ottawa, Ontario, Canada" - }, - { - "author_name": "Michael P Ward", - "author_inst": "Faculty of Veterinary Science, The University of Sydney NSW, Sydney, Australia" - }, - { - "author_name": "Wei Tu", - "author_inst": "Department of Geology and Geography, Georgia Southern University, Statesboro, GA 30460, USA" - }, - { - "author_name": "Zhen Jin", - "author_inst": "Complex Systems Research Center, Shanxi University, Taiyuan, Shan'xi 030006" - }, - { - "author_name": "Jian Hu", - "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Min" + "author_name": "Lei-Yun Wang", + "author_inst": "Department of Clinical Pharmacology, Xiangya Hospital, Central South University" }, { - "author_name": "Qing Su", - "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Min" + "author_name": "Jia-Jia Cui", + "author_inst": "Department of Clinical Pharmacology, Xiangya Hospital, Central South University" }, { - "author_name": "Wenge Wang", - "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Min" + "author_name": "Qian-Ying OuYang", + "author_inst": "Department of Clinical Pharmacology, Xiangya Hospital, Central South University" }, { - "author_name": "Zheng Zhao", - "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Min" + "author_name": "Yan Zhan", + "author_inst": "Department of Clinical Pharmacology, Xiangya Hospital, Central South University" }, { - "author_name": "Shuang Xiao", - "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Min" + "author_name": "Yi-Min Wang", + "author_inst": "Genetalks Co., Ltd" }, { - "author_name": "Jiaqi Huang", - "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Min" + "author_name": "Xiang-Yang Xu", + "author_inst": "Genetalks Co., Ltd" }, { - "author_name": "Wei Lin", - "author_inst": "School of Mathematical Sciences and Shanghai Center for Mathematical Sciences, Fudan University, Shanghai 200433, China" + "author_name": "Cheng-Xian Guo", + "author_inst": "Center of Clinical Pharmacology, the Third Xiangya Hospital, Central South University" }, { - "author_name": "Zhijie Zhang", - "author_inst": "Department of Epidemiology and Health Statistics, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety, Min" + "author_name": "JiYe Yin", + "author_inst": "Institute of Clinical Pharmacology, Xiangya Hospital, Central South University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "public and global health" + "category": "genetic and genomic medicine" }, { "rel_doi": "10.1101/2020.03.27.20045138", @@ -1595398,21 +1596263,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.27.20045005", - "rel_title": "A modified SEIR model to predict the COVID-19 outbreak in Spain: simulating control scenarios and multi-scale epidemics", + "rel_doi": "10.1101/2020.03.27.20045237", + "rel_title": "Dynamic Modeling to Identify Mitigation Strategies for Covid-19 Pandemic", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.27.20045005", - "rel_abs": "AO_SCPLOWBSTRACTC_SCPLOWAfter the spread of SARS-CoV-2 epidemic out of China, evolution in the pandemic worldwide shows dramatic differences among countries. In Europe, the situation of Italy first and later Spain has generated great concern, and despite other countries show better prospects, large uncertainties yet remain on the future evolution and the efficacy of containment, mitigation or attack strategies. Here we applied a modified SEIR compartmental model accounting for the spread of infection during the latent period, in which we also incorporate effects of varying proportions of containment. We fit data to quarantined populations in order to account for the uncertainties in case reporting and study the scenario projections for the 17 individual regions (CCAA). Results indicate that with data for March 23, the epidemics follows an evolution similar to the isolation of 1, 5 percent of the population and if there were no effects of intervention actions it might reach a maximum over 1.4M infected around April27. The effect on the epidemics of the ongoing partial confinement measures is yet unknown (an update of results with data until March 31st is included), but increasing the isolation around ten times more could drastically reduce the peak to over 100k cases by early April, while each day of delay in taking this hard containment scenario represents an 90 percent increase of the infected population at the peak. Dynamics at the sub aggregated levels of CCAA show epidemics at the different levels of progression with the most worrying situation in Madrid an Catalonia. Increasing alpha values up to 10 times, in addition to a drastic reduction in clinical cases, would also more than halve the number of deaths. Updates for March 31st simulations indicate a substantial reduction in burden is underway. A similar approach conducted for Italy pre- and post-interventions also begins to suggest substantial reduction in both infected and deaths has been achieved, showing the efficacy of drastic social distancing interventions.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.27.20045237", + "rel_abs": "SARS-CoV2 spread is hard to control, as asymptomatic people contribute to transmission. Currently, Covid-19 mitigation imposes social distancing and isolates the diseased. This slows down virus spread, eases stress on health care systems and thereby reduces the death toll. However, this strategy takes a high economic toll, and virus transmission will surge again if measures are lifted. App-based contact tracing of symptomatic cases and isolating their contacts has been proposed as an alternative, but may not suffice for mitigation, as asymptomatic infections remain unidentified. Here, we evaluate complementary mitigation strategies relying on virus-RNA testing to detect and quarantine both, symptomatic and asymptomatic cases. Epidemic dynamics modeling shows that stopping the pandemic by mass testing alone is unrealistic, as we lack enough tests. However, realistic numbers of tests may suffice in a smart-testing strategy, e.g. when biasing tests towards people with exceptionally high numbers of contacts. These people are at particularly high risk to become infected (with or without symptoms) and transmit the virus. A mitigation strategy combining smart testing with contact counting (STeCC) and contact tracing in one app would reduce R0 by 2.4-fold (e.g. from R0=2.4 to R0=1) with realistic test numbers ({approx}166 per 100000 people per day) when a realistic fraction of smartphone owners use the app ({approx}72%, i.e. {approx}50% in total population). Thereby, STeCC expands the portfolio of mitigation strategies and may help easing social distancing without compromising public health.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Leonardo R Lopez", - "author_inst": "Barcelona Institute for Global Health" + "author_name": "Hossein Gorji", + "author_inst": "EPFL" }, { - "author_name": "Xavier Rodo", - "author_inst": "Barcelona Institute for Global Health" + "author_name": "Markus Arnoldini", + "author_inst": "ETH Zurich" + }, + { + "author_name": "David F Jenny", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Alexandre Duc", + "author_inst": "HEIG-VD" + }, + { + "author_name": "Wolf-Dietrich Hardt", + "author_inst": "ETH Zurich" + }, + { + "author_name": "Patrick Jenny", + "author_inst": "ETH Zurich" } ], "version": "1", @@ -1596780,63 +1597661,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.03.26.20043042", - "rel_title": "Analysis and Prediction of False Negative Results for SARS-CoV-2 Detection with Pharyngeal Swab Specimen in COVID-19 Patients: A Retrospective Study", + "rel_doi": "10.1101/2020.03.29.014415", + "rel_title": "Flocked swab might be one main reason causing the high false-negative rate in COVID-19 screening----the advantages of a novel silicone swab", "rel_date": "2020-03-30", - "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.26.20043042", - "rel_abs": "BackgroundFalse negative results of SARS-CoV-2 nucleic acid detection pose threats to COVID-19 patients and medical workers alike.\n\nObjectiveTo develop multivariate models to determine clinical characteristics that contribute to false negative results of SARS-CoV-2 nucleic acid detection, and use them to predict false negative results as well as time windows for testing positive.\n\nDesignRetrospective Cohort Study (Ethics number of Tongji Hospital: No. IRBID: TJ-20200320)\n\nSettingA database of outpatients in Tongji Hospital (University Hospital) from 15 January 2020 to 19 February 2020.\n\nPatients1,324 outpatients with COVID-19\n\nMeasurementsClinical information on CT imaging reports, blood routine tests, and clinic symptoms were collected. A multivariate logistic regression was used to explain and predict false negative testing results of SARS-CoV-2 detection. A multivariate accelerated failure model was used to analyze and predict delayed time windows for testing positive.\n\nResultsOf the 1,324 outpatients who diagnosed of COVID-19, 633 patients tested positive in their first SARS-CoV-2 nucleic acid test (47.8%), with a mean age of 51 years (SD=14.9); the rest, which had a mean age of 47 years (SD=15.4), tested negative in the first test. \"Ground glass opacity\" in a CT imaging report was associated with a lower chance of false negatives (aOR, 0.56), and reduced the length of time window for testing positive by 26%. \"Consolidation\" was associated with a higher chance of false negatives (aOR, 1.57), and extended the length of time window for testing positive by 44%. In blood routine tests, basophils (aOR, 1.28) and eosinophils (aOR, 1.29) were associated with a higher chance of false negatives, and were found to extend the time window for testing positive by 23% and 41%, respectively. Age and gender also affected the significantly.\n\nLimitationData were generated in a large single-center study.\n\nConclusionTesting outcome and positive window of SARS-CoV-2 detection for COVID-19 patients were associated with CT imaging results, blood routine tests, and clinical symptoms. Taking into account relevant information in CT imaging reports, blood routine tests, and clinical symptoms helped reduce a false negative testing outcome. The predictive AFT model, what we believe to be one of the first statistical models for predicting time window of SARS-CoV-2 detection, could help clinicians improve the accuracy and efficiency of the diagnosis, and hence, optimizes the timing of nucleic acid detection and alleviates the shortage of nucleic acid detection kits around the world.\n\nPrimary Funding SourceNone.", - "rel_num_authors": 11, + "rel_site": "bioRxiv", + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.29.014415", + "rel_abs": "RNA testing using RT-PCR can provide direct evidence for diagnoses of COVID-19 which has brought unexpected disasters and changes to our human society. However, the absorption of cotton swab for RNA lysates may lead to a low concentration of detectable RNA, which might be one of the main reasons for the unstable positive detecting rate. We designed and manufactured a kind of silicone swab with concave-convex structure, and further compared the effects of silicone and cotton swab on RNA extraction. Principal component analysis and Paired Wilcoxcon test suggested that a higher RNA concentration and A260/A280 would be obtained using silicone swab. The results indicated that our silicone swab had a more excellent ability to sample than the cotton swab, characterized by the higher quantity and quality of extracted RNA. Thus, we advised that the current cotton swabs need to be improved urgently in COVID-19 diagnoses and the process of \"sample collection\" and \"sample pre-processing\" must be standardized and emphasized.\n\nHighlightsThe current cotton swabs need to be improved urgently in COVID-19 screening.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Hui Xu", - "author_inst": "Department of Anesthesiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China" + "author_name": "Jianye Zhou", + "author_inst": "Biomedical Research Center, Key Laboratory of Oral Diseases of Gansu Province, Key Laboratory of Stomatology of State Ethnic Affairs Commission, Northwest Minzu" }, { - "author_name": "Li Yan", - "author_inst": "Department of Emergency, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China" - }, - { - "author_name": "Chun (Martin) Qiu", - "author_inst": "Lazaridis School, Wilfrid Laurier University, Waterloo, Ontario" - }, - { - "author_name": "Bo Jiao", - "author_inst": "Department of Anesthesiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China" + "author_name": "Zhongtian Bai", + "author_inst": "The second Department of General Surgery, the First Hospital of Lanzhou University, Lanzhou, Gansu Province, China" }, { - "author_name": "Yanyan Chen", - "author_inst": "Department of Information Management, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Nan Jiang", + "author_inst": "Department of Applied Soil Biochemistry, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang Province, China" }, { - "author_name": "Xi Tan", - "author_inst": "Department of Anesthesiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China" + "author_name": "Xiaodong Li", + "author_inst": "Institute of Chinese Materia Medica, Gansu Provincial Hospital of Traditional Chinese Medicine, Lanzhou, Gansu Province, China" }, { - "author_name": "Zhuo Chen", - "author_inst": "Outpatient department office,Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology" + "author_name": "Xiaohui Zhang", + "author_inst": "Biomedical Research Center, Key Laboratory of Oral Diseases of Gansu Province, Key Laboratory of Stomatology of State Ethnic Affairs Commission, Northwest Minzu" }, { - "author_name": "Ling Ai", - "author_inst": "Department of Anesthesiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China" + "author_name": "Zhiqiang Li", + "author_inst": "Biomedical Research Center, Key Laboratory of Oral Diseases of Gansu Province, Key Laboratory of Stomatology of State Ethnic Affairs Commission, Northwest Minzu" }, { - "author_name": "Yaru Xiao", - "author_inst": "Department of Emergency, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China" + "author_name": "Yonghong Li", + "author_inst": "NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, Gansu Province, China" }, { - "author_name": "Ailin Luo", - "author_inst": "Department of Anesthesiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China" + "author_name": "Zhongren Ma", + "author_inst": "Biomedical Research Center, Key Laboratory of Oral Diseases of Gansu Province, Key Laboratory of Sto" }, { - "author_name": "Shusheng Li", - "author_inst": "Department of Emergency, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China" + "author_name": "Jin Zhao", + "author_inst": "Biomedical Research Center, Key Laboratory of Oral Diseases of Gansu Province, Key Laboratory of Stomatology of State Ethnic Affairs Commission, Northwest Minzu" } ], "version": "1", - "license": "cc_no", - "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "license": "cc_by_nc_nd", + "type": "new results", + "category": "microbiology" }, { "rel_doi": "10.1101/2020.03.26.20044750", @@ -1598062,35 +1598935,31 @@ "category": "occupational and environmental health" }, { - "rel_doi": "10.1101/2020.03.26.20044214", - "rel_title": "Projecting the Spread of COVID19 for Germany", + "rel_doi": "10.1101/2020.03.25.20043703", + "rel_title": "Laboratory findings, signs and symptoms, clinical outcomes of Patients with COVID-19 Infection: an updated systematic review and meta-analysis", "rel_date": "2020-03-30", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.26.20044214", - "rel_abs": "We model the evolution of the number of individuals that are reported to be sick with COVID-19 in Germany. Our theoretical framework builds on a continuous time Markov chain with four states: healthy without infection, sick, healthy after recovery or after infection but without symptoms and dead. Our quantitative solution matches the number of sick individuals up to the most recent observation and ends with a share of sick individuals following from infection rates and sickness probabilities. We employ this framework to study inter alia the expected peak of the number of sick individuals in a scenario without public regulation of social contacts. We also study the effects of public regulations. For all scenarios we report the expected end of the CoV-2 epidemic.\n\nWe have four general findings: First, current epidemiological thinking implies that the long-run effects of the epidemic only depend on the aggregate long-run infection rate and on the individual risk to turn sick after an infection. Any measures by individuals and the public therefore only influence the dynamics of spread of CoV-2. Second, predictions about the duration and level of the epidemic must strongly distinguish between the officially reported numbers (Robert Koch Institut, RKI) and actual numbers of sick individuals. Third, given the current (scarce) medical knowledge about long-run infection rate and individual risks to turn sick, any prediction on the length (duration in months) and strength (e.g. maximum numbers of sick individuals on a given day) is subject to a lot of uncertainty. Our predictions therefore offer robustness analyses that provide ranges on how long the epidemic will last and how strong it will be. Fourth, public interventions that are already in place and that are being discussed can lead to more and less severe outcomes of the epidemic. If an intervention takes place too early, the epidemic can actually be stronger than with an intervention that starts later. Interventions should therefore be contingent on current infection rates in regions or countries.\n\nConcerning predictions about COVID-19 in Germany, we find that the long-run number of sick individuals (that are reported to the RKI), once the epidemic is over, will lie between 500 thousand and 5 million individuals. While this seems to be an absurd large range for a precise projection, this reflects the uncertainty about the long-run infection rate in Germany. If we assume that Germany will follow the good scenario of Hubei (and we are even a bit more conservative given discussions about data quality), we will end up with 500 thousand sick individuals over the entire epidemic. If by contrast we believe (as many argue) that once the epidemic is over 70% of the population will have been infected (and thereby immune), we will end up at 5 million cases.\n\nDefining the end of the epidemic by less than 100 newly reported sick individuals per day, we find a large variation depending on the effectiveness of governmental pleas and regulations to reduce social contacts. An epidemic that is not influenced by public health measures would end mid June 2020. With public health measures lasting for few weeks, the end is delayed by around one month or two. The advantage of the delay, however, is to reduce the peak number of individuals that are simultaneously sick. When we believe in long-run infection rates of 70%, this number is equally high for all scenarios we went through and well above 1 million. When we can hope for the Hubei-scenario, the maximum number of sick individuals will be around 200 thousand \"only\".\n\nWhatever value of the range of long-run infection rates we want to assume, the epidemic will last at least until June, with extensive and potentially future public health measures, it will last until July. In the worst case, it will last until end of August.\n\nWe emphasize that all projections are subject to uncertainty and permanent monitoring of observed incidences are taken into account to update the projection. The most recent projections are available at https://www.macro.economics.unimainz.de/corona-blog/.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.25.20043703", + "rel_abs": "Background and AimCoronaviruses disease 2019 (COVID-19), for the first time detected in Wuhan, China, rapidly speared around the world and be a Public Health Emergency of International Concern (PHEIC). The aim of the current survey is collecting laboratory findings, analysis them and reporting a specific pattern for help to COVID-19 diagnosis.\n\nMethodsTo collect laboratory characteristics, we searched \"PubMed\" electronic database with the following keywords: \"COVID-19\" \"2019 novel coronavirus\" \"laboratory findings\" \"clinical characteristics\".\n\nResultsOnce the initial searches 493 studies were yielded. After removing duplicates studies 480 studies were remained. The 12 studies obtained from the literature, of which 58.3% (7) of studies were case-control (8-14), and 41.7% (5) remaining studies were designed as cross-sectional (1,15-18)\n\nConclusionThe result of the current study showed that in the early stage of COVID-19 infection, maybe there are not significant laboratory findings, but with disease progression, the one or more than signs include increasing AST, ALT, LDH, CK, CRP, ESR, WBC, neutrophil, and decreasing Hemoglobin, lymphocyte count, eosinophil count can be seen. Elevating D-dimer and FDP are associated with ARDS development and can be used as prognostic factors.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Jean Roch Donsimoni", - "author_inst": "Johannes Gutenberg-University" - }, - { - "author_name": "Rene Glawion", - "author_inst": "Universitaet Hamburg" + "author_name": "Mina Ebrahimi", + "author_inst": "Ahvaz jundishapur university of medical sciences" }, { - "author_name": "Bodo Plachter", - "author_inst": "Johannes Gutenberg-University" + "author_name": "Amal Saki", + "author_inst": "Ahvaz jundishapur university of medical sciences" }, { - "author_name": "Klaus Waelde", - "author_inst": "Johannes Gutenberg-University" + "author_name": "Fakher rahim", + "author_inst": "Ahvaz Jundishapur University of Medical Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "health economics" + "category": "emergency medicine" }, { "rel_doi": "10.1101/2020.03.26.20044412", @@ -1599408,25 +1600277,81 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.23.20040998", - "rel_title": "A demographic adjustment to improve measurement of COVID-19 severity at the developing stage of the pandemic", + "rel_doi": "10.1101/2020.03.24.20041020", + "rel_title": "Systematic review and critical appraisal of prediction models for diagnosis and prognosis of COVID-19 infection", "rel_date": "2020-03-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.23.20040998", - "rel_abs": "The need for accurate statistics has never been felt so deeply as the novel COVID-19 pathogen spreads around the world and quantifying its severity is a primary clinical and public health issue. In Italy, the magnitude and increasing trend of the case-fatality risk (CFR) is fueling the already high levels of public alarm. In this paper, we highlight that the widely used crude CFR is an inaccurate measure of the disease severity since the pandemic is still unfolding. With the goal to improve its comparability over time and across countries at this stage, we then propose a demographic adjustment of the CFR that addresses the bias arising from differential case ascertainment by age. When applied to publicly released data for Italy, we show that until March 16 our adjusted CFR was similar to that of Wuhan - the most affected Chinese region, where COVID-19 has now been contained. This indicates that our adjusted CFR improves its comparability over time, making an important tool to chart the course of the COVID-19 pandemic across countries. Since March 16, the Italian COVID-19 outbreak has entered a new phase, with the northern and southern regions following different trajectories. As a result, our adjusted CFR has been increasing between March 16 and March 20. Data at the subnational level are needed to correctly assess the disease severity in the country at this stage.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20041020", + "rel_abs": "ObjectiveTo review and critically appraise published and preprint reports of models that aim to predict either (i) presence of existing COVID-19 infection, (ii) future complications in individuals already diagnosed with COVID-19, or (iii) models to identify individuals at high risk for COVID-19 in the general population.\n\nDesignRapid systematic review and critical appraisal of prediction models for diagnosis or prognosis of COVID-19 infection.\n\nData sourcesPubMed, EMBASE via Ovid, Arxiv, medRxiv and bioRxiv until 24th March 2020.\n\nStudy selectionStudies that developed or validated a multivariable COVID-19 related prediction model. Two authors independently screened titles, abstracts and full text.\n\nData extractionData from included studies were extracted independently by at least two authors based on the CHARMS checklist, and risk of bias was assessed using PROBAST. Data were extracted on various domains including the participants, predictors, outcomes, data analysis, and prediction model performance.\n\nResults2696 titles were screened. Of these, 27 studies describing 31 prediction models were included for data extraction and critical appraisal. We identified three models to predict hospital admission from pneumonia and other events (as a proxy for covid-19 pneumonia) in the general population; 18 diagnostic models to detect COVID-19 infection in symptomatic individuals (13 of which were machine learning utilising computed tomography (CT) results); and ten prognostic models for predicting mortality risk, progression to a severe state, or length of hospital stay. Only one of these studies used data on COVID-19 cases outside of China. Most reported predictors of presence of COVID-19 in suspected patients included age, body temperature, and signs and symptoms. Most reported predictors of severe prognosis in infected patients included age, sex, features derived from CT, C-reactive protein, lactic dehydrogenase, and lymphocyte count.\n\nEstimated C-index estimates for the prediction models ranged from 0.73 to 0.81 in those for the general population (reported for all 3 general population models), from 0.81 to > 0.99 in those for diagnosis (reported for 13 of the 18 diagnostic models), and from 0.85 to 0.98 in those for prognosis (reported for 6 of the 10 prognostic models). All studies were rated at high risk of bias, mostly because of non-representative selection of control patients, exclusion of patients who had not experienced the event of interest by the end of the study, and poor statistical analysis, including high risk of model overfitting. Reporting quality varied substantially between studies. A description of the study population and intended use of the models was absent in almost all reports, and calibration of predictions was rarely assessed.\n\nConclusionCOVID-19 related prediction models are quickly entering the academic literature, to support medical decision making at a time where this is urgently needed. Our review indicates proposed models are poorly reported and at high risk of bias. Thus, their reported performance is likely optimistic and using them to support medical decision making is not advised. We call for immediate sharing of the individual participant data from COVID-19 studies to support collaborative efforts in building more rigorously developed prediction models and validating (evaluating) existing models. The aforementioned predictors identified in multiple included studies could be considered as candidate predictors for new models. We also stress the need to follow methodological guidance when developing and validating prediction models, as unreliable predictions may cause more harm than benefit when used to guide clinical decisions. Finally, studies should adhere to the TRIPOD statement to facilitate validating, appraising, advocating and clinically using the reported models.\n\nSystematic review registration protocolosf.io/ehc47/, registration: osf.io/wy245\n\nSummary boxesO_ST_ABSWhat is already known on this topicC_ST_ABS- The sharp recent increase in COVID-19 infections has put a strain on healthcare systems worldwide, necessitating efficient early detection, diagnosis of patients suspected of the infection and prognostication of COVID-19 confirmed cases.\n- Viral nucleic acid testing and chest CT are standard methods for diagnosing COVID-19, but are time-consuming.\n- Earlier reports suggest that the elderly, patients with comorbidity (COPD, cardiovascular disease, hypertension), and patients presenting with dyspnoea are vulnerable to more severe morbidity and mortality after COVID-19 infection.\n\n\nWhat this study adds- We identified three models to predict hospital admission from pneumonia and other events (as a proxy for COVID-19 pneumonia) in the general population.\n- We identified 18 diagnostic models for COVID-19 detection in symptomatic patients.\n- 13 of these were machine learning models based on CT images.\n- We identified ten prognostic models for COVID-19 infected patients, of which six aimed to predict mortality risk in confirmed or suspected COVID-19 patients, two aimed to predict progression to a severe or critical state, and two aimed to predict a hospital stay of more than 10 days from admission.\n- Included studies were poorly reported compromising their subsequent appraisal, and recommendation for use in daily practice. All studies were appraised at high risk of bias, raising concern that the models may be flawed and perform poorly when applied in practice, such that their predictions may be unreliable.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Simona Bignami", - "author_inst": "Universite de Montreal" + "author_name": "Laure Wynants", + "author_inst": "Maastricht University / KU Leuven" }, { - "author_name": "Daniela Ghio", - "author_inst": "Joint Research Center European Commission" + "author_name": "Ben Van Calster", + "author_inst": "KU Leuven" + }, + { + "author_name": "Marc MJ Bonten", + "author_inst": "Utrecht University" + }, + { + "author_name": "Gary S Collins", + "author_inst": "University of Oxford" + }, + { + "author_name": "Thomas PA Debray", + "author_inst": "Utrecht University" + }, + { + "author_name": "Maarten De Vos", + "author_inst": "KU Leuven" + }, + { + "author_name": "Maria C Haller", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Georg Heinze", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Karel GM Moons", + "author_inst": "Utrecht University" + }, + { + "author_name": "Richard D Riley", + "author_inst": "Keele University" + }, + { + "author_name": "Ewoud Schuit", + "author_inst": "Utrecht University" + }, + { + "author_name": "Luc Smits", + "author_inst": "Maastricht University" + }, + { + "author_name": "Kym IE Snell", + "author_inst": "Keele University" + }, + { + "author_name": "Ewout W Steyerberg", + "author_inst": "Leiden University Medical Centre" + }, + { + "author_name": "Christine Wallisch", + "author_inst": "Medical University of Vienna" + }, + { + "author_name": "Maarten van Smeden", + "author_inst": "Utrecht University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1600990,85 +1601915,33 @@ "category": "health informatics" }, { - "rel_doi": "10.1101/2020.03.23.20039362", - "rel_title": "Immune Cell Profiling of COVID-19 Patients in the Recovery Stage by Single-Cell Sequencing", + "rel_doi": "10.1101/2020.03.25.20043877", + "rel_title": "The current state of COVID-19 in Australia: importation and spread", "rel_date": "2020-03-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.23.20039362", - "rel_abs": "COVID-19, caused by SARS-CoV-2, has recently affected over 300,000 people and killed more than 10,000. The manner in which the key immune cell subsets change and their states during the course of COVID-19 remain unclear. Here, we applied single-cell technology to comprehensively characterize transcriptional changes in peripheral blood mononuclear cells during the recovery stage of COVID-19. Compared with healthy controls, in patients in the early recovery stage (ERS) of COVID-19, T cells decreased remarkably, whereas monocytes increased. A detailed analysis of the monocytes revealed that there was an increased ratio of classical CD14++ monocytes with high inflammatory gene expression as well as a greater abundance of CD14++IL1B+ monocytes in the ERS. CD4+ and CD8+ T cells decreased significantly and expressed high levels of inflammatory genes in the ERS. Among the B cells, the plasma cells increased remarkably, whereas the naive B cells decreased. Our study identified several novel B cell-receptor (BCR) changes, such as IGHV3-23 and IGHV3-7, and confirmed isotypes (IGHV3-15, IGHV3-30, and IGKV3-11) previously used for virus vaccine development. The strongest pairing frequencies, IGHV3-23-IGHJ4, indicated a monoclonal state associated with SARS-CoV-2 specificity. Furthermore, integrated analysis predicted that IL-1{beta} and M-CSF may be novel candidate target genes for inflammatory storm and that TNFSF13, IL-18, IL-2 and IL-4 may be beneficial for the recovery of COVID-19 patients. Our study provides the first evidence of an inflammatory immune signature in the ERS, suggesting that COVID-19 patients are still vulnerable after hospital discharge. Our identification of novel BCR signaling may lead to the development of vaccines and antibodies for the treatment of COVID-19.\n\nHighlights- The immune response was sustained for more than 7 days in the early recovery stage of COVID-19, suggesting that COVID-19 patients are still vulnerable after hospital discharge.\n- Single-cell analysis revealed a predominant subset of CD14++ IL1{beta}+ monocytes in patients in the ERS of COVID-19.\n- Newly identified virus-specific B cell-receptor changes, such as IGHV3-23, IGHV3-7, IGHV3-15, IGHV3-30, and IGKV3-11, could be helpful in the development of vaccines and antibodies against SARS-CoV-2.\n- IL-1{beta} and M-CSF were discovered as novel mediators of inflammatory cytokine storm, and TNFSF13, IL-2, IL-4, and IL-18 may be beneficial for recovery.", - "rel_num_authors": 17, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.25.20043877", + "rel_abs": "BackgroundThe rapid global spread of coronavirus disease (COVID-19) is unprecedented. The outbreak has quickly spread to more than 100 countries reporting over 100,000 confirmed cases. Australia reported its first case of COVID-19 on 25th January 2020 and has since implemented travel restrictions to stop further introduction of the virus.\n\nMethodsWe analysed daily global COVID-19 data published by the World Health Organisation to investigate the spread of the virus thus far. To assess the current risk of COVID-19 importation and local spread in Australia we predict international passenger flows into Australia during 2020.\n\nFindingsOur analysis of global data shows that Australia can expect a similar growth rate of reported cases as observed in France and the United States. We identify travel patterns of Australian citizens/residents and foreign travellers that can inform the implementation of new and the alteration of existing travel restrictions related to COVID-19.\n\nInterpretationOur findings identify the risk reduction potential of current travel bans, based on the proportion of returning travellers to Australia that are residents or visitors. The similarity of the exponential growth in the epidemic curve in Australia to other countries guides forecasts of COVID-19 growth in Australia, and opportunities for drawing lessons from other countries with more advanced outbreaks.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Wen Wen", - "author_inst": "National Center for Liver Cancer, Second Military Medical University, Shanghai, China" - }, - { - "author_name": "Wenru Su", - "author_inst": "State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China" - }, - { - "author_name": "Hao Tang", - "author_inst": "Department of Respiratory and Critical Care Medicine Changzheng Hospital, Second Military Medical University, Shanghai, China" - }, - { - "author_name": "Wenqing Le", - "author_inst": "Department of Critical Care,Wuhan Hankou Hospital, Hubei, China" - }, - { - "author_name": "Xiaopeng Zhang", - "author_inst": "Laboratory of Vaccine and Antibody Engineering, Beijing Institute of Biotechnology, Beijing, China" - }, - { - "author_name": "Yingfeng Zheng", - "author_inst": "State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China" - }, - { - "author_name": "XiuXing Liu", - "author_inst": "State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China" - }, - { - "author_name": "Lihui Xie", - "author_inst": "State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China" - }, - { - "author_name": "Jianmin Li", - "author_inst": "Laboratory of Vaccine and Antibody Engineering, Beijing Institute of Biotechnology, Beijing, China" - }, - { - "author_name": "Jinguo Ye", - "author_inst": "State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China" - }, - { - "author_name": "Xiuliang Cui", - "author_inst": "National Center for Liver Cancer Second Military Medical University, Shanghai, China" - }, - { - "author_name": "Yushan Miao", - "author_inst": "Department of Respiratory and Critical Care Medicine Changzheng Hospital, Second Military Medical University, Shanghai, China" - }, - { - "author_name": "Depeng Wang", - "author_inst": "GrandOmics Diagnosis Co. Ltd. Wuhan, Hubei, China" - }, - { - "author_name": "Jiantao Dong", - "author_inst": "Berry Genomics Co. Ltd, Beijing, China" + "author_name": "Jessica Liebig", + "author_inst": "CSIRO" }, { - "author_name": "Chuan-Le Xiao", - "author_inst": "State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-sen University, Guangzhou, China" + "author_name": "Raja Jurdak", + "author_inst": "Queensland University of Technology" }, { - "author_name": "Wei Chen", - "author_inst": "Laboratory of Vaccine and Antibody Engineering, Beijing Institute of Biotechnology, Beijing, China" + "author_name": "Ahmad El Shoghri", + "author_inst": "University of New South Wales" }, { - "author_name": "Hongyang Wang", - "author_inst": "National Center for Liver Cancer, Second Military Medical University, Shanghai, China" + "author_name": "Dean Paini", + "author_inst": "CSIRO" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1602532,25 +1603405,57 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.21.20040667", - "rel_title": "COVID-19 in Canada: Predictions for the future and control lessons from Asia", + "rel_doi": "10.1101/2020.03.23.20041913", + "rel_title": "SARS-CoV-2 infection in 86 healthcare workers in two Dutch hospitals in March 2020", "rel_date": "2020-03-27", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.21.20040667", - "rel_abs": "COVID-19 has spread with unequal efficiency in various parts of the world. In several European countries including Italy, the increase in the number of COVID-19 cases has followed a consistent, exponential pattern of spread. However, some countries, notably Taiwan and Hong Kong, have achieved a different outcome and have managed to bring the COVID-19 outbreak in their countries rapidly under control, without entering the exponential pattern and with very few cases. They have used several different approaches to COVID-19 outbreak control, including the innovative use of smartphone technology and the widespread use of surgical face masks. We show through our models, that Canada has followed the same, consistent COVID-19 exponential growth pattern that is seen in Italy. Both nationally and in its most heavily affected provinces, there is exponential growth of COVID-19 cases, making it possible to make predictions for the future, if no further interventions are made in public health policy. In particular, we argue for the urgent introduction of surgical face masks in health care and other settings and the harnessing of the power of smartphone technology on a national scale.", - "rel_num_authors": 2, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.23.20041913", + "rel_abs": "BackgroundOn February 27, 2020, the first patient with COVID-19 was reported in the Netherlands. During the following weeks, nine healthcare workers (HCWs) were diagnosed with COVID-19 in two Dutch teaching hospitals, eight of whom had no history of travel to China or Northern-Italy. A low-threshold screening regimen was implemented to determine the prevalence and clinical presentation of COVID-19 among HCWs in these two hospitals.\n\nMethodsHCWs who suffered from fever or respiratory symptoms were voluntarily tested for SARS-CoV-2 by real-time reverse-transcriptase PCR on oropharyngeal samples. Structured interviews were conducted to document symptoms for all HCWs with confirmed COVID-19.\n\nFindingsThirteen-hundred fifty-three (14%) of 9,705 HCWs employed were tested, 86 (6%) of whom were infected with SARS-CoV-2. Most HCWs suffered from relatively mild disease and only 46 (53%) reported fever. Eighty (93%) HCWs met a case definition of fever and/or coughing and/or shortness of breath. None of the HCWs identified through the screening reported a travel history to China or Northern Italy, and 3 (3%) reported to have been exposed to an inpatient known with COVID-19 prior to the onset of symptoms.\n\nInterpretationWithin two weeks after the first Dutch case was detected, a substantial proportion of HCWs with fever or respiratory symptoms were infected with SARS-CoV-2, probably caused by acquisition of the virus in the community during the early phase of local spread. The high prevalence of mild clinical presentations, frequently not including fever, asks for less stringent use of the currently recommended case-definition for suspected COVID-19.\n\nRESEARCH IN PERSPECTIVEO_ST_ABSEvidence before this studyC_ST_ABSThis study was conducted in response to the global spread of SARS-CoV-2, and the detection of eight healthcare workers (HCWs) in two Dutch teaching hospitals within two weeks after the first patient with COVID-19 was detected in the Netherlands who had no history of travel to China or Northern-Italy, raising the question of whether undetected community circulation was occurring.\n\nAdded value of this studyTo the best of our knowledge, this report is the first to describe the prevalence, the clinical presentation and early outcomes of COVID-19 in HCWs, which may be helpful for others seeking to identify HCWs suspected for COVID-19 in an outbreak situation.\n\nImplications of all the available evidenceWe describe that within two weeks after the first Dutch case was detected, a substantial proportion of HCWs with fever or (mild) respiratory symptoms were infected with SARS-CoV-2, probably caused by acquisition of the virus in the community during the early phase of local spread. The high prevalence of mild clinical presentations, frequently not including fever, asks for less stringent use of the currently recommended case-definition for suspected COVID-19.", + "rel_num_authors": 10, "rel_authors": [ { - "author_name": "Cornelius Christian", - "author_inst": "Brock University" + "author_name": "Marjolein Kluytmans", + "author_inst": "Amphia Hospital" }, { - "author_name": "Francis Christian", - "author_inst": "University of Saskatchewan" + "author_name": "Anton Buiting", + "author_inst": "Elisabeth-TweeSteden Hospital" + }, + { + "author_name": "Suzan Pas", + "author_inst": "Bravis Hospital" + }, + { + "author_name": "Robbert Bentvelsen", + "author_inst": "Amphia Hospital" + }, + { + "author_name": "Wouter van den Bijllaardt", + "author_inst": "Amphia Hospital" + }, + { + "author_name": "Anne van Oudheusden", + "author_inst": "Elisabeth-TweeSteden Hospital" + }, + { + "author_name": "Miranda van Rijen", + "author_inst": "Amphia Hospital" + }, + { + "author_name": "Jaco Verweij", + "author_inst": "Elisabeth-TweeSteden Hospital" + }, + { + "author_name": "Marion Koopmans", + "author_inst": "Erasmus Medical Center" + }, + { + "author_name": "Jan Kluytmans", + "author_inst": "Amphia Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by_nc", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1604082,53 +1604987,125 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.24.20042903", - "rel_title": "COVID-19 clinical characteristics, and sex-specific risk of mortality: Systematic Review and Meta-analysis", + "rel_doi": "10.1101/2020.03.24.20042382", + "rel_title": "Viral Kinetics and Antibody Responses in Patients with COVID-19", "rel_date": "2020-03-26", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20042903", - "rel_abs": "ObjectivesThe rapidly evolving coronavirus disease 2019 (COVID-19), was declared a pandemic by the World Health Organization on March 11, 2020. It was first detected in the city of Wuhan in China and has spread globally resulting in substantial health and economic crisis in many countries. Observational studies have partially identified the different aspects of this disease. Up to this date, no comprehensive systematic review for the clinical, laboratory, epidemiologic and mortality findings has been published. We conducted this systematic review and meta-analysis for a better understanding of COVID-19.\n\nMethodsWe reviewed the scientific literature published from January 1, 2019 to March 3, 2020. Statistical analyses were performed with STATA (version 14, IC; Stata Corporation, College Station, TX, USA). The pooled frequency with 95% confidence intervals (CI) was assessed using random effect model. Publication bias was assessed and p <0.05 was considered a statistically significant publication bias.\n\nResultsOut of 1102 studies, 32 satisfied the inclusion criteria. A total of 4789 patients with a mean age of 49 years were evaluated. Fever (83.0%, CI 77.5 to 87.6), cough (65.2%, CI 58.6 to 71.2) and myalgia/fatigue (34.7, CI 26.0 to 44.4) were the most common symptoms. The most prevalent comorbidities were hypertension (18.5 %, CI 12.7 to 24.4) and Cardiovascular disease (14.9 %, CI 6.0 to 23.8). Among the laboratory abnormalities, elevated C-Reactive Protein (CRP) (72.0% (CI 54.3 to 84.6) and lymphopenia (50.1%, CI 38.0 to 62.4) were the most common findings. Bilateral ground-glass opacities (66.0%, CI 51.1 to 78.0) was the most common CT-Scan presentation. Pooled mortality rate was 6.6%, with males having significantly higher mortality compared to females (OR 3.4; 95% CI 1.2 to 9.1, P = 0.01).\n\nConclusionCOVID-19 commonly presented with a progressive course of cough and fever with more than half of hospitalized patients showing leukopenia or a high CRP on their laboratory findings. Mortality associated with COVID19 was higher than that reported in studies in China with Males having a 3-fold higher risk of mortality in COVID19 compared to females.\n\nSummary boxO_ST_ABSWhat is already known in this topicC_ST_ABSO_LICOVID-19 was declared a pandemic by the World Health Organization on March 11, 2020.\nC_LIO_LIMany observational studies have separately dealt with different clinical and epidemiologic features of this new and rapidly evolving disease.\nC_LIO_LIVery few systematic reviews about COVID-19 have been done and there was still a need for a systematic review and meta-analysis related to the clinical findings and the mortality of the disease in order to have a better understanding of COVID-19.\nC_LIO_LIPrevious reports have indicated that older age and presence of multiple comorbidities are associated with increased mortality.\nC_LI\n\nWhat this study addsO_LIThe mortality rate in our study for hospitalized COVID-19 patients was 6.6% and males had around 3-fold higher risk of mortality compared to females (OR 3.4; 95% CI 1.2-9.1, P = 0.01).\nC_LIO_LIThese findings could indicate the need for more aggressive treatment of COVID-19 in males.\nC_LI", - "rel_num_authors": 9, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.24.20042382", + "rel_abs": "BackgroundA pandemic of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been spreading over the world. However, the viral dynamics, host serologic responses, and their associations with clinical manifestations, have not been well described in prospective cohort.\n\nMethodsWe conducted a prospective cohort and enrolled 67 COVID-19 patients admitting between Jan 26 and Feb 5, 2020. Clinical specimens including nasopharyngeal swab, sputum, blood, urine and stool were tested periodically according to standardized case report form with final follow-up on February 27. The routes and duration of viral shedding, antibody response, and their associations with disease severity and clinical manifestations were systematically evaluated. Coronaviral particles in clinical specimens were observed by transmission electron microscopy (TEM).\n\nResultsThe median duration of SARS-CoV-2 RNA shedding were 12 (3-38), 19 (5-37), and 18 (7-26) days in nasopharyngeal swabs, sputum and stools, respectively. Only 13 urines (5.6%) and 12 plasmas (5.7%) were viral positive. Prolonged viral shedding was observed in severe patients than that of non-severe patients. Cough but not fever, aligned with viral shedding in clinical respiratory specimens, meanwhile the positive stool-RNA appeared to align with the proportion who concurrently had cough and sputum production, but not diarrhea. Typical coronaviral particles could be found directly in sputum by TEM. The anti-nucleocapsid-protein IgM started on day 7 and positive rate peaked on day 28, while that of IgG was on day 10 and day 49 after illness onset. IgM and IgG appear earlier, and their titers are significantly higher in severe patients than non-severe patients (p<0.05). The weak responders for IgG had a significantly higher viral clearance rate than that of strong responders (p= 0.011).\n\nConclusionsNasopharyngeal, sputum and stools rather than blood and urine, were the major shedding routes for SARS-CoV-2, and meanwhile sputum had a prolonged viral shedding. Symptom cough seems to be aligned with viral shedding in clinical respiratory and fecal specimens. Stronger antibody response was associated with delayed viral clearance and disease severity.\n\nSummary boxesO_ST_ABSWhat is already known on this topicC_ST_ABSAs a newly appearing infectious disease, early efforts have focused on virus identification, describing the epidemiologic characteristics, clinical course, prognostics for critically illed cases and mortality. Among COVID-19 cases reported in mainland China (72 314 cases, updated through February 11, 2020), 81% are mild, 14% are severe, and 5% are critical. The estimated overall case fatality rate (CFR) is 2.3%.\n\nSome case series reported had shown that SARS-CoV-2 could shed in upper/lower respiratory specimens, stools, blood and urines of patients. However, important knowledge gaps remain, particularly regarding full kinetics of viral shedding and host serologic responses in association with clinical manifestations and host factors.\n\nWhat this study addsThe incubation period has no change after spreading out of Wuhan, and has no sex or age differences, however, children had prolonged incubation period. Due to early recognition and intervention, COVID-19 illness of Chongqing cohort is milder than that of Wuhan patients reported.\n\nThis prospective cohort study on SARS-CoV-2 infection shows clearly that the viral and serological kinetics were related in duration of infection, disease severity, and clinical manifestations of COVID-19. Our data demonstrate that nasopharyngeal, sputum and stools are major shedding routes for SARS-CoV-2, and stronger NP antibody response is associated with delayed viral clearance and disease severity.", + "rel_num_authors": 27, "rel_authors": [ { - "author_name": "Mohammad Javad Nasiri", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Wenting Tan", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" }, { - "author_name": "Sara Haddadi", - "author_inst": "University of Miami Miller School of Medicine" + "author_name": "Yanqiu Lu", + "author_inst": "Division of Infectious Diseases, Chongqing Public Health Medical Center, Chongqing 400036, China" }, { - "author_name": "Azin Tahvildari", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Juan Zhang", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" }, { - "author_name": "Yeganeh Farsi", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Jing Wang", + "author_inst": "Division of Laboratory Diagnosis, Chongqing Public Health Medical Center, Chongqing 400036, China;" }, { - "author_name": "Mahta Arbabi", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Yunjie Dan", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" }, { - "author_name": "Saba Hasanzadeh", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Zhaoxia Tan", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" }, { - "author_name": "Parnian Jamshidi", - "author_inst": "Shahid Beheshti University of Medical Sciences" + "author_name": "Xiaoqing He", + "author_inst": "Division of Infectious Diseases, Chongqing Public Health Medical Center, Chongqing 400036, China" }, { - "author_name": "Mukunthan Murthi", - "author_inst": "University of Miami Miller School of Medicine" + "author_name": "Chunfang Qian", + "author_inst": "Sector of Isolation Ward, Chongqing Public Health Medical Center, Chongqing 400036, China" }, { - "author_name": "Mehdi Mirsaeidi", - "author_inst": "University of Miami Miller School of Medicine" + "author_name": "Qiangzhong Sun", + "author_inst": "Sector of Isolation Ward, Chongqing Public Health Medical Center, Chongqing 400036, China" + }, + { + "author_name": "Qingli Hu", + "author_inst": "Sector of Isolation Ward, Chongqing Public Health Medical Center, Chongqing 400036, China" + }, + { + "author_name": "Honglan Liu", + "author_inst": "Sector of Isolation Ward, Chongqing Public Health Medical Center, Chongqing 400036, China" + }, + { + "author_name": "Sikuan Ye", + "author_inst": "Sector of Isolation Ward, Chongqing Public Health Medical Center, Chongqing 400036, China" + }, + { + "author_name": "Xiaomei Xiang", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Yi Zhou", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Wei Zhang", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Yanzhi Guo", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Xiu-Hua Wang", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Weiwei He", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Xing Wan", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Fengming Sun", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Quanfang Wei", + "author_inst": "Biomedical Analysis Center, College of Basic Medicine, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Cong Chen", + "author_inst": "Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Guangqiang Pan", + "author_inst": "Department of Pathology, Xinqiao Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Jie Xia", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Qing Mao", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" + }, + { + "author_name": "Yaokai Chen", + "author_inst": "Division of Infectious Diseases, Chongqing Public Health Medical Center, Chongqing 400036, China" + }, + { + "author_name": "Guohong Deng", + "author_inst": "Department of Infectious Diseases, Southwest Hospital, Third Military Medical University (Army Medial University), Chongqing 400038, China" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1605624,63 +1606601,51 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.22.002204", - "rel_title": "Characterisation of the transcriptome and proteome of SARS-CoV-2 using direct RNA sequencing and tandem mass spectrometry reveals evidence for a cell passage induced in-frame deletion in the spike glycoprotein that removes the furin-like cleavage site.", + "rel_doi": "10.1101/2020.03.21.20037267", + "rel_title": "Effect of SARS-CoV-2 infection upon male gonadal function: A single center-based study", "rel_date": "2020-03-24", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.22.002204", - "rel_abs": "Direct RNA sequencing using an Oxford Nanopore MinION characterised the transcriptome of SARS-CoV-2 grown in Vero E6 cells. This cell line is being widely used to propagate the novel coronavirus. The viral transcriptome was analysed using a recently developed ORF-centric pipeline. This revealed the pattern of viral transcripts, (i.e. subgenomic mRNAs), generally fitted the predicted replication and transcription model for coronaviruses. A 24 nt in-frame deletion was detected in subgenomic mRNAs encoding the spike (S) glycoprotein. This feature was identified in over half of the mapped transcripts and was predicted to remove a proposed furin cleavage site from the S glycoprotein. This motif directs cleavage of the S glycoprotein into functional subunits during virus entry or exit. Cleavage of the S glycoprotein can be a barrier to zoonotic coronavirus transmission and affect viral pathogenicity. Allied to this transcriptome analysis, tandem mass spectrometry was used to identify over 500 viral peptides and 44 phosphopeptides, covering almost all of the proteins predicted to be encoded by the SARS-CoV-2 genome, including peptides unique to the deleted variant of the S glycoprotein. Detection of an apparently viable deletion in the furin cleavage site of the S glycoprotein reinforces the point that this and other regions of SARS-CoV-2 proteins may readily mutate. This is of clear significance given the interest in the S glycoprotein as a potential vaccine target and the observation that the furin cleavage site likely contributes strongly to the pathogenesis and zoonosis of this virus. The viral genome sequence should be carefully monitored during the growth of viral stocks for research, animal challenge models and, potentially, in clinical samples. Such variations may result in different levels of virulence, morbidity and mortality.", - "rel_num_authors": 11, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.21.20037267", + "rel_abs": "Since SARS-CoV-2 infection was first identified in December 2019, it spread rapidly and a global pandemic of COVID-19 has occurred. ACE2, the receptor for entry into the target cells by SARS-CoV-2, was found to abundantly express in testes, including spermatogonia, Leydig and Sertoli cells. However, there is no clinical evidence about whether SARS-CoV-2 infection can affect male gonadal function so far. In this study, we compared the sex-related hormones between 81 reproductive-aged men with SARS-CoV-2 infection and 100 age-matched healthy men, and found that serum luteinizing hormone (LH) was significantly increased, but the ratio of testosterone (T) to LH and the ratio of follicle stimulating hormone (FSH) to LH were dramatically decreased in males with COVID-19. Besides, multivariable regression analysis indicated that c-reactive protein (CRP) level was significantly associated with serum T:LH ratio in COVID-19 patients. This study provides the first direct evidence about the influence of medical condition of COVID-19 on male sex hormones, alerting more attention to gonadal function evaluation among patients recovered from SARS-CoV-2 infection, especially the reproductive-aged men.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Andrew D. Davidson", - "author_inst": "University of Bristol" - }, - { - "author_name": "Maia Kavangh Williamson", - "author_inst": "University of Bristol" - }, - { - "author_name": "Sebastian Lewis", - "author_inst": "Universiry of Bristol" - }, - { - "author_name": "Deborah Shoemark", - "author_inst": "University of Bristol" + "author_name": "Ling Ma", + "author_inst": "Reproductive Medicine Center, Zhongnan Hospital, Wuhan University," }, { - "author_name": "Miles W Carroll", - "author_inst": "Public Health England" + "author_name": "Wen Xie", + "author_inst": "Department of Laboratory Medicine, Zhongnan Hospital, Wuhan University; Department of Laboratory Medicine, Wuhan Leishenshan Hospital," }, { - "author_name": "Kate Heesom", - "author_inst": "University of Bristol" + "author_name": "Danyang Li", + "author_inst": "Reproductive Medicine Center, Zhongnan Hospital, Wuhan University," }, { - "author_name": "Maria Zambon", - "author_inst": "Public Health England" + "author_name": "Lei Shi", + "author_inst": "Reproductive Medicine Center, Zhongnan Hospital, Wuhan University," }, { - "author_name": "Joanna Ellis", - "author_inst": "Public Health England" + "author_name": "Yanhong Mao", + "author_inst": "Reproductive Medicine Center, Zhongnan Hospital, Wuhan University," }, { - "author_name": "Phillip A Lewis", - "author_inst": "University of Bristol" + "author_name": "Yao Xiong", + "author_inst": "Reproductive Medicine Center, Zhongnan Hospital, Wuhan University," }, { - "author_name": "Julian A Hiscox", - "author_inst": "University of Liverpool" + "author_name": "Yuanzhen Zhang", + "author_inst": "Reproductive Medicine Center, Zhongnan Hospital, Wuhan University; Hubei Clinical Research Center for Prenatal Diagnosis and Birth Health; Department of Obstetr" }, { - "author_name": "David A Matthews", - "author_inst": "University of Bristol" + "author_name": "Ming Zhang", + "author_inst": "Reproductive Medicine Center, Zhongnan Hospital, Wuhan University; Hubei Clinical Research Center for Prenatal Diagnosis and Birth Health," } ], "version": "1", - "license": "cc_by", - "type": "new results", - "category": "microbiology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "sexual and reproductive health" }, { "rel_doi": "10.1101/2020.03.19.20039354", @@ -1607102,85 +1608067,85 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.19.20038315", - "rel_title": "Association between Clinical, Laboratory and CT Characteristics and RT-PCR Results in the Follow-up of COVID-19 patients", + "rel_doi": "10.1101/2020.03.19.20038539", + "rel_title": "Clinical Characteristics of Coronavirus Disease 2019 in Hainan, China", "rel_date": "2020-03-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.19.20038315", - "rel_abs": "BackgroundSince December 2019, more than 100,000 coronavirus disease 2019 (COVID-19) patients have been confirmed globally based on positive viral nucleic acids with real-time reverse transcriptase-polymerase chain reaction (RT-PCR). However, the association between clinical, laboratory and CT characteristics and RT-PCR results is still unclear. We sought to examine this association in detail, especially in recovered patients.\n\nMethodsWe analysed data from 52 confirmed patients who had been discharged with COVID-19. The clinical, laboratory, and radiological data were dynamically recorded and compared with the admission and follow-up RT-PCR results.\n\nResultsIn this cohort, 52 admitted COVID-19 patients who had confirmed positive RT-PCR results were discharged after 2 rounds of consecutively negative RT-PCR results. Compared with admission levels, CRP levels (median 4.93 mg/L [IQR: 1.78-10.20]) decreased significantly (p<0.001). and lymphocyte counts (median 1.50x109/L [IQR: 1.11-1.88]) increased obviously after obtaining negative RT-PCR results (p<0.001). Additionally, substantially improved inflammatory exudation was observed on chest CT except for 2 progressed patients. At the two-week follow-up after discharge, 7 patients had re-positive RT-PCR results, including the abovementioned 2 progressed patients. Among the 7 patients, new GGO was demonstrated in 2 patients. There were no significant differences in CPR levels or lymphocyte counts when comparing the negative and re-positive PCT results (all p >0.05).\n\nConclusionHeterogeneity between CT features and RT-PCR results was found in COVID-19, especially in some recovered patients with negative RT-PCR results. Our study highlights that both RT-PCR and chest CT should be considered as the key determinants for the diagnosis and management of COVID-19 patients.", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.19.20038539", + "rel_abs": "BackgroundSince January 2020, coronavirus disease 2019 (Covid-19) has spread rapidly and developing the pandemic model around the world. Data have been needed on the clinical characteristics of the affected patients in an imported cases as model in island outside Wuhan.\n\nMethodsWe conducted a retrospective study included all 168 confirmed cases of Covid-19 in Hainan province from 22 January 2020 to 13 March 2020. Cases were confirmed by real-time RT-PCR and were analysed for demographic, clinical, radiological and laboratory data.\n\nResultsOf 168 patients, 160 have been discharged, 6 have died and 2 remain hospitalized. The median age was 51.0 years and 51.8% were females. 129 (76.8%) patients were imported cases, and 118 (70.2%), 51 (30.4%) and 52 (31%) of patients lived in Wuhan or traveled to Wuhan, had contact with Covid-19 patients, or had contact with Wuhan residents, respectively. The most common symptoms at onset of illness were fever (65.5%), dry cough (48.8%) and expectoration (32.1%). On admission, ground-glass opacity was the most common radiologic finding on chest computed tomography (60.2%). The elderly people with diabetes, hypertension and CVD are more likely to develop severe cases. Follow-up of 160 discharged patients found that 20 patients (12.5%) had a positive RT-PCR test results of pharyngeal swabs or anal swabs or fecal.\n\nConclusionsIn light of the rapid spread of Covid-19 around the world, early diagnosis and quarantine is important to curb the spread of Covid-19 and intensive treatments in early stage is to prevent patients away from critical condition.", "rel_num_authors": 17, "rel_authors": [ { - "author_name": "Hang Fu", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Shijiao Yan", + "author_inst": "Hainan Medical University" }, { - "author_name": "Huayan Xu", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Xingyue Song", + "author_inst": "Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Na Zhang", - "author_inst": "Department of Radiology, Public Health Clinical Center of Chengdu, Cheng Du, China" + "author_name": "Feng Lin", + "author_inst": "Hainan Affiliated Hospital of Hainan Medical University" }, { - "author_name": "Hong Xu", - "author_inst": "Department of Ultrasonography, West China Second University Hospital, Sichuan University, Chengdu, China" + "author_name": "Haiyan Zhu", + "author_inst": "the First Medical Center of Chinese PLA General Hospital" }, { - "author_name": "Zhenlin Li", - "author_inst": "Department of Radiology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China" + "author_name": "Xiaozhi Wang", + "author_inst": "The Second Affiliated Hospital of Hainan Medical University" }, { - "author_name": "Huizhu Chen", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Min Li", + "author_inst": "The second naval hospital of southern theater command of PLA" }, { - "author_name": "Rong Xu", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Jianwen Ruan", + "author_inst": "Haikou People's Hospital" }, { - "author_name": "Ran Sun", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Changfeng Lin", + "author_inst": "The Third People's Hospital of Hainan Province" }, { - "author_name": "Lingyi Wen", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Xiaoran Liu", + "author_inst": "the First Affiliated Hospital of Hainan Medical University" }, { - "author_name": "Linjun Xie", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Qiang Wu", + "author_inst": "Hainan Medical University" }, { - "author_name": "Hui Liu", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Zhiqian Luo", + "author_inst": "The First Affiliated Hospital of Hainan Medical University" }, { - "author_name": "Kun Zhang", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Wenning Fu", + "author_inst": "Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Chuan Fu", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Song Chen", + "author_inst": "The First Affiliated Hospital of Hainan Medical University" }, { - "author_name": "Keke Hou", - "author_inst": "Department of Radiology, Public Health Clinical Center of Chengdu, Cheng Du, China" + "author_name": "Yong Yuan", + "author_inst": "Hainan Medical University" }, { - "author_name": "Zhigang Yang", - "author_inst": "Department of Radiology, State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, China" + "author_name": "Shengxing Liu", + "author_inst": "Hainan Medical University" }, { - "author_name": "Ming Yang", - "author_inst": "Department of Respiratory Medicine, Public Health Clinical Center of Chengdu, Cheng Du, China" + "author_name": "Jinjian Yao", + "author_inst": "Hainan Affiliated Hospital of Hainan Medical University" }, { - "author_name": "Yingkun Guo Sr.", - "author_inst": "Department of Radiology, Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospi" + "author_name": "Chuanzhu Lv", + "author_inst": "The Second Affiliated Hospital of Hainan Medical University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1608948,85 +1609913,73 @@ "category": "biochemistry" }, { - "rel_doi": "10.1101/2020.03.21.001628", - "rel_title": "Respiratory disease and virus shedding in rhesus macaques inoculated with SARS-CoV-2", + "rel_doi": "10.1101/2020.03.19.998179", + "rel_title": "Molecular characterization of SARS-CoV-2 in the first COVID-19 cluster in France reveals an amino-acid deletion in nsp2 (Asp268Del)", "rel_date": "2020-03-21", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.21.001628", - "rel_abs": "An outbreak of a novel coronavirus, now named SARS-CoV-2, causing respiratory disease and a [~]2% case fatality rate started in Wuhan, China in December 2019. Following unprecedented rapid global spread, the World Health Organization declared COVID-19 a pandemic on March 11, 2020. Although data on disease in humans are emerging at a steady pace, certain aspects of the pathogenesis of SARS-CoV-2 can only be studied in detail in animal models, where repeated sampling and tissue collection is possible. Here, we show that SARS-CoV-2 causes respiratory disease in infected rhesus macaques, with disease lasting 8-16 days. Pulmonary infiltrates, a hallmark of human disease, were visible in lung radiographs of all animals. High viral loads were detected in swabs from the nose and throat of all animals as well as in bronchoalveolar lavages; in one animal we observed prolonged rectal shedding. Taken together, the rhesus macaque recapitulates moderate disease observed in the majority of human cases. The establishment of the rhesus macaque as a model of COVID-19 will increase our understanding of the pathogenesis of this disease and will aid development and testing of medical countermeasures.", - "rel_num_authors": 17, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.19.998179", + "rel_abs": "We present the first genetic characterization of a COVID-19 cluster in Europe using metagenomic next-generation sequencing (mNGS). Despite low viral loads, the mNGS workflow used herein allowed to characterize the whole genome sequences of SARS-CoV2 isolated from an asymptomatic patient, in 2 clinical samples collected 1 day apart. Comparison of these sequences suggests viral evolution with development of quasispecies. In addition, the present workflow identified a new deletion in nsp2 (Asp268Del) which was found in all 3 samples originating from this cluster as well as in 37 other viruses collected in England and in Netherlands, suggesting the spread of this deletion in Europe. The impact of Asp268Del on SARS-CoV-2 transmission and pathogenicity, as well as on PCR performances and anti-viral strategy should be rapidly evaluated in further studies.", + "rel_num_authors": 14, "rel_authors": [ { - "author_name": "Vincent Munster", - "author_inst": "NIAID" - }, - { - "author_name": "Friederike Feldmann", - "author_inst": "NIAID" - }, - { - "author_name": "Brandi Williamson", - "author_inst": "NIAID" - }, - { - "author_name": "Neeltje van Doremalen", - "author_inst": "NIAID" + "author_name": "Antonin Bal", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Lizzette Perez-Perez,", - "author_inst": "NIAID" + "author_name": "Gregory Destras", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Jonathan Schultz", - "author_inst": "NIAID" + "author_name": "Alexandre Gaymard", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Kimberly Meade-White", - "author_inst": "NIAID" + "author_name": "Maude Bouscambert-Duchamp", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Atsushi Okumura", - "author_inst": "NIAID" + "author_name": "Martine Valette", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Julie Callison", - "author_inst": "NIAID" + "author_name": "Vanessa Escuret", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Beniah Brumbaugh", - "author_inst": "NIAID" + "author_name": "Emilie Frobert", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Victoria Avanzato", - "author_inst": "NIAID" + "author_name": "Genevieve Billaud", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Rebecca Rosenke", - "author_inst": "NIAID" + "author_name": "Sophie Trouillet-Assant", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Patrick Hanley", - "author_inst": "NIAID" + "author_name": "Valerie Cheynet", + "author_inst": "BioMerieux" }, { - "author_name": "Greg Saturday", - "author_inst": "NIAID" + "author_name": "Karen Brengel-Pesce", + "author_inst": "BioMerieux" }, { - "author_name": "Dana Scott", - "author_inst": "NIAID" + "author_name": "Florence Morfin", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Elizabeth Fischer", - "author_inst": "NIAID" + "author_name": "Bruno Lina", + "author_inst": "Hospices Civils de Lyon" }, { - "author_name": "Emmie de Wit", - "author_inst": "NIAID, NIH" + "author_name": "Laurence Josset", + "author_inst": "Hospices Civils de Lyon" } ], "version": "1", - "license": "cc0", + "license": "cc_by_nc_nd", "type": "new results", "category": "microbiology" }, @@ -1610382,35 +1611335,79 @@ "category": "allergy and immunology" }, { - "rel_doi": "10.1101/2020.03.16.20037176", - "rel_title": "Hundreds of severe pediatric COVID-19 infections in Wuhan prior to the lockdown", + "rel_doi": "10.1101/2020.03.18.20038125", + "rel_title": "Non-severe vs severe symptomatic COVID-19: 104 cases from the outbreak on the cruise ship \"Diamond Princess\" in Japan", "rel_date": "2020-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.16.20037176", - "rel_abs": "Before January 22, 2020, only one pediatric case of COVID-19 was reported in mainland China1,2. However, a retrospective surveillance study3 identified six children who had been hospitalized for COVID-19 in one of three central Wuhan hospitals between January 7th and January 15th. Given that Wuhan has over 395 other hospitals, there may have been far more severe pediatric cases than reported.", - "rel_num_authors": 4, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.18.20038125", + "rel_abs": "BackgroundThe ongoing outbreak of the coronavirus disease 2019 (COVID-19) is a global threat. Identification of markers for symptom onset and disease progression is a pressing issue. We compared the clinical features on admission among patients who were diagnosed with asymptomatic, mild, and severe COVID-19 at the end of observation.\n\nMethodsThis retrospective, single-center study included 104 patients with laboratory-confirmed COVID-19 from the mass infection on the Diamond Princess cruise ship from February 11 to February 25, 2020. Clinical records, laboratory data, and radiological findings were analyzed. Clinical outcomes were followed up until February 26, 2020. Clinical features on admission were compared among those with different disease severity at the end of observation. Univariate analysis identified factors associated with symptom onset and disease progression.\n\nFindingsThe median age was 68 years, and 54 patients were male. Briefly, 43, 41, and 20 patients on admission and 33, 43, and 28 patients at the end of observation had asymptomatic, mild, and severe COVID-19, respectively. Serum lactate hydrogenase levels were significantly higher in 10 patients who were asymptomatic on admission but developed symptomatic COVID-19 compared with 33 patients who remained asymptomatic throughout the observation period. Older age, consolidation on chest computed tomography, and lymphopenia on admission were more frequent in patients with severe COVID-19 than those with mild COVID-19 at the end of observation.\n\nInterpretationLactate dehydrogenase level is a potential predictor of symptom onset in COVID-19. Older age, consolidation on chest CT images, and lymphopenia might be risk factors for disease progression of COVID-19 and contribute to the clinical management.\n\nFundingNot applicable.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched the PubMed database from its inception until March 1, 2020, for articles published in English using the keywords \"novel coronavirus,\" \"2019 novel coronavirus,\" \"2019-nCoV,\" \"Severe acute respiratory syndrome coronavirus 2,\" \"SARS-CoV2,\" \"COVID-19,\" \"mass infection,\" \"herd infection,\" \"cruise ship,\" \"Diamond Princess,\" \"asymptomatic,\" and \"subclinical.\" There were no published clinical studies featuring COVID-19 as a result of mass infection on board a cruise ship. We found published articles entitled \"Characteristics of COVID-19 infection in Beijing\" and \"Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study,\" which compared patients with asymptomatic, mild, and severe COVID-19. However, none of the studies described potential markers for symptom onset or disease progression in patients with COVID-19.\n\nAdded value of this studyWe present the differences in clinical characteristics of 104 patients with laboratory-confirmed COVID-19 as a result of mass infection on the Diamond Princess cruise ship who were treated at Self-Defense Forces Central Hospital, Japan from February 11 to February 25, 2020. On admission, 43, 41, and 20 patients had asymptomatic, mild, and severe COVID-19, respectively, whereas 33, 43, and 28 patients were determined to have asymptomatic, mild, and severe COVID-19, respectively, at the end of observation. During the observation period, 10 of the 43 (23.3%) asymptomatic patients on admission developed symptoms of COVID-19. Conversely, eight of the 84 (9.5%) patients with asymptomatic and mild COVID-19 on admission developed severe disease during the observation period. The serum lactate dehydrogenase (LDH) levels were significantly higher in 10 patients who were initially asymptomatic on admission to the hospital and developed symptomatic COVID-19 during the observation period compared with 33 patients who remained asymptomatic throughout the observation period. The prevalence rates of consolidation on chest computed tomography (CT) images and lymphopenia were significantly higher in eight patients who developed severe COVID-19 during the observation period compared with the 76 patients with asymptomatic or mild disease at the end of the observation. Older age, consolidation on chest CT, and lymphopenia on admission were more frequent in patients with severe COVID-19 (n = 28) than those with mild COVID-19 (n = 43) at the end of observation. LDH level might be marker for symptom onset in patients with COVID-19, whereas older age, consolidation on chest CT imaging, and lymphopenia are potential risk factors for disease progression. The current report findings will contribute to the improvement of clinical management in patients with COVID-19.\n\nImplications of all the available evidenceSerum LDH level is a potential predictor of symptom onset of COVID-19, whereas older age, consolidation on chest CT imaging, and lymphopenia have potential utility as markers for disease progression.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Zhanwei Du", - "author_inst": "University of Texas at Austin" + "author_name": "Sakiko Tabata", + "author_inst": "Self-Defense Forces Central Hospital" }, { - "author_name": "Ciara Nugent", - "author_inst": "University of Texas at Austin" + "author_name": "Kazuo Imai", + "author_inst": "Saitama Medical University" }, { - "author_name": "Benjamin J Cowling", - "author_inst": "The University of Hong Kong" + "author_name": "Shuichi Kawano", + "author_inst": "Japan Ground Self-Defense Force Medical Service School" }, { - "author_name": "Lauren Ancel Meyers", - "author_inst": "The University of Texas at Austin" + "author_name": "Mayu Ikeda", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Tatsuya Kodama", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Kazuyasu Miyoshi", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Hirofumi Obinata", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Satoshi Mimura", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Tsutomu Kodera", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Manabu Kitagaki", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Michiya Sato", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Satoshi Suzuki", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Toshimitsu Ito", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Yasuhide Uwabe", + "author_inst": "Self-Defense Forces Central Hospital" + }, + { + "author_name": "Kaku Tamura", + "author_inst": "Self-Defense Forces Central Hospital" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.03.18.20038133", @@ -1611612,33 +1612609,25 @@ "category": "health policy" }, { - "rel_doi": "10.1101/2020.03.16.20037291", - "rel_title": "Short-range airborne route dominates exposure of respiratory infection during close contact", + "rel_doi": "10.1101/2020.03.17.20037903", + "rel_title": "Double-Quencher Probes Improved the Detection Sensitivity of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) by One-Step RT-PCR", "rel_date": "2020-03-20", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.16.20037291", - "rel_abs": "A susceptible person experiences the highest exposure risk of respiratory infection when he or she is in close proximity with an infected person. The large droplet route has been commonly believed to be dominant for most respiratory infections since the early 20th century, and the associated droplet precaution is widely known and practiced in hospitals and in the community. The mechanism of exposure to droplets expired at close contact, however, remains surprisingly unexplored. In this study, the exposure to exhaled droplets during close contact (< 2 m) via both the short-range airborne and large droplet sub-routes is studied using a simple mathematical model of expired flows and droplet dispersion/deposition/inhalation, which enables the calculation of exposure due to both deposition and inhalation. The short-range airborne route is found to dominate at most distances studied during both talking and coughing. The large droplet route only dominates when the droplets are larger than 100 m and when the subjects are within 0.2 m while talking or 0.5 m while coughing. The smaller the exhaled droplets, the more important the short-range airborne route. The large droplet route contributes less than 10% of exposure when the droplets are smaller than 50 m and when the subjects are more than 0.3 m apart, even while coughing.\n\nPractical implicationsOur simple but novel analysis shows that conventional surgical masks are not effective if most infectious viruses are contained in fine droplets, and non-conventional intervention methods such as personalised ventilation should be considered as infection prevention strategies given the possible dominance of the short-range airborne route, although further clinical evidence is needed.\n\nNomenclatureO_ST_ABSSubscriptC_ST_ABSi Droplets of different diameter groups (i = 1, 2, ..., N)\n\nLD Large droplet route\n\nSR Short-range airborne route\n\nSymbolsA0 Area of source mouth [m2]\n\nAE Aspiration efficiency [-]\n\nAr0 Archimedes number [-]\n\nbg Gaussian half width [m]\n\nbt Top-hat half width [m]\n\nCD Drag coefficient [-]\n\nCI Specific heat of liquid [J*kg-1*K-1]\n\nCs Specific heat of solid [J*kg-1*K-1]\n\nCT Correction factor for diffusion coefficient due to temperature dependence [-]\n\ndd Droplet diameter [m]\n\ndd0 Droplet initial diameter [m]\n\nde1 Major axis of eye ellipse [m]\n\nde2 Minor axis of eye ellipse [m]\n\ndh Characteristic diameter of human head [m]\n\ndm Mouth diameter [m]\n\ndn Nostril diameter [m]\n\nD{infty} Binary diffusion coefficient far from droplet [m2*s-1]\n\nDE Deposition efficiency [-]\n\neLD Exposure due to large droplet route [L]\n\neSR Exposure due to short-range airborne route [L]\n\ng Gravitational acceleration [m*s-2]\n\nIv Mass current [kg*s-1]\n\nIF Inhalation fraction [-]\n\nKc Constant (=0.3) [-]\n\nKg Thermal conductivity of air [W*m-1*K-1]\n\nLS Exposure ratio between large droplet and short-range airborne [-]\n\nLv Latent heat of vaporization [J*kg-1]\n\nmd Droplet mass [kg]\n\nmI Mass of liquid in a droplet [kg]\n\nms Mass of solid in a droplet [kg]\n\nM0 Jet initial momentum [m4*s-2]\n\nMW Molecular weight of H2O [kg*mol-1]\n\nMF Membrane fraction [-]\n\nn Number of droplets [n]\n\nn0 Number of droplets expelled immediately at mouth [n]\n\nNin Number of droplets entering the inhalation zone [n]\n\nNm Number of droplets potentially deposited on mucous membranes [n]\n\nNt Total number of released droplets [n]\n\nNu Nusselt number [-]\n\np Total pressure [Pa]\n\npv{infty} Vapour pressure distant from droplet surface [Pa]\n\npvs Vapour pressure at droplet surface [Pa]\n\nQjet Jet flow rate [m3*s-1]\n\nr Radial distance away from jet centreline [m]\n\nrd Droplet radius [m]\n\nR Radius of jet potential core [m]\n\nRg Universal gas constant [J*K-1*mol-1]\n\ns Jet centreline trajectory length [m]\n\nSin Width of region on sampler enclosed by limiting stream surface [m]\n\nSh Sherwood number [-]\n\nStc Stokes number in convergent part of air stream [-]\n\nSth Stokes number for head [-]\n\nStm Stokes number for mouth [-]\n\nt Time [s]\n\nT0 Initial temperature of jet [K]\n\nT{infty} Ambient temperature [K]\n\nTd Droplet temperature [K]\n\nu0 Initial velocity at mouth outlet [m*s-1]\n\nud Droplet velocity [m*s-1]\n\nug Gaussian velocity [m*s-1]\n\nugas Gas velocity [m*s-1]\n\nugc Gaussian centreline velocity [m*s-1]\n\nuin Inhalation velocity [m*s-1]\n\nut Top-hat velocity [m*s-1]\n\nvp Individual droplet volume considering evaporation [m3]\n\nx Horizontal distance between source and target [m]\n\nz Jet vertical centreline position [m]\n\n{rho}0 Jet initial density [kg*m-3]\n\n{rho}{infty}Ambient air density [kg*m-3]\n\n{rho}d Droplet density [kg*m-3]\n\n{rho}g Gas density [kg*m-3]\n\n{Delta}{rho}Density difference between jet and ambient air [kg*m-3]\n\ng Gas dynamic viscosity [Pa*s]\n\n {varphi}Sampling ratio in axisymmetric flow system [-]\n\nc Impaction efficiency in convergent part of air stream [-]", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.17.20037903", + "rel_abs": "BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerges in Wuhan City, Hubei Province, spreads worldwide, and threats the human life. The detection of SARS-CoV-2 is important for the prevention of the outbreak and management of patients. Real-time reverse-transcription polymerase chain reaction (RT-PCR) assay detected the virus in clinical laboratory.\n\nMethodsThis study utilized primers and single-quencher probes in accordance with the Centers for Disease Control and Prevention (CDC) in the USA and the National Institute of Infectious Diseases (NIID) in Japan. Moreover, we designed the double-quencher probes (YCH assay) according to the oligonucleotide sequence established by NIID. Using these assays, we conducted a one-step real-time RT-PCR with serial DNA positive control to assess the detection sensitivity.\n\nResultsThe threshold cycle (Ct) value of RT-PCR was relatively low in CDC and YCH assays compared to NIID assay. Serial dilution assay showed that both CDC and YCH assays could detect a low-copy number of DNA positive control. The background fluorescent signal at the baseline was lower in YCH than that of NIID.\n\nConclusionDouble-quencher probes decreased background fluorescent signal and improved detection sensitivity of SARS-CoV-2.", + "rel_num_authors": 3, "rel_authors": [ { - "author_name": "Wenzhao Chen", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Nan Zhang", - "author_inst": "The University of Hong Kong" - }, - { - "author_name": "Jianjian Wei", - "author_inst": "Zhejiang University" + "author_name": "Yosuke Hirotsu", + "author_inst": "Yamanashi Central Hospital" }, { - "author_name": "Hui-Ling YEN", - "author_inst": "The University of Hong Kong" + "author_name": "Hitoshi Mochizuki", + "author_inst": "Yamanashi Central Hospital" }, { - "author_name": "Yuguo Li", - "author_inst": "The University of Hong Kong" + "author_name": "Masao Omata", + "author_inst": "Yamanashi Central Hospital" } ], "version": "1", @@ -1613298,107 +1614287,23 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.16.994152", - "rel_title": "Characterization of the SARS-CoV-2 Spike in an Early Prefusion Conformation", + "rel_doi": "10.1101/2020.03.13.20035253", + "rel_title": "Impact of city and residential unit lockdowns on prevention and control of COVID-19", "rel_date": "2020-03-17", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.16.994152", - "rel_abs": "Pandemic coronavirus disease 2019 (COVID-19) is caused by the emerging severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), for which there are no efficacious vaccines or therapeutics that are urgently needed. We expressed three versions of spike (S) proteins--receptor binding domain (RBD), S1 subunit and S ectodomain--in insect cells. RBD appears monomer in solutions, whereas S1 and S associate into homotrimer with substantial glycosylation. The three proteins confer excellent antigenicity with six convalescent COVID-19 patient sera. Cryo-electron microscopy (cryo-EM) analyses indicate that the SARS-CoV-2 S trimer dominate in a unique conformation distinguished from the classic prefusion conformation of coronaviruses by the upper S1 region at lower position ~15 [A] proximal to viral membrane. Such conformation is proposed as an early prefusion state for the SARS-CoV-2 spike that may broaden the knowledge of coronavirus and facilitate vaccine development.", - "rel_num_authors": 22, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.13.20035253", + "rel_abs": "With respect to the asymptomatic transmission characteristics of the novel coronavirus that appeared in 2019 (COVID-19), a susceptible-asymptomatic-infected-recovered-death (SAIRD) model that considered human mobility was constructed in this study. The dissemination of COVID-19 was simulated using computational experiments to identify the mechanisms underlying the impact of city and residential lockdowns on controlling the spread of the epidemic. Results: The implementation of measures to lock down cities led to higher mortality rates in these cities, due to reduced mobility. Moreover, implementing city lockdown along with addition of hospital beds led to improved cure and reduced mortality rates. Stringent implementation and early lockdown of residential units effectively controlled the spread of the epidemic, and reduced the number of hospital bed requirements. Collectively, measures to lock down cities and residential units should be taken to prevent the spread of COVID-19. In addition, medical resources should be increased in cities under lockdown. Implementation of these measures would reduce the spread of the virus to other cities and allow appropriate treatment of patients in cities under lockdown.", + "rel_num_authors": 1, "rel_authors": [ { - "author_name": "Tingting Li", - "author_inst": "Xiamen University" - }, - { - "author_name": "Qingbing Zheng", - "author_inst": "Xiamen University" - }, - { - "author_name": "Hai Yu", - "author_inst": "Xiamen University" - }, - { - "author_name": "Dinghui Wu", - "author_inst": "The First Affiliated Hospital of Xiamen University" - }, - { - "author_name": "Wenhui Xue", - "author_inst": "Xiamen University" - }, - { - "author_name": "Yuyun Zhang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Xiaofen Huang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Lizhi Zhou", - "author_inst": "Xiamen University" - }, - { - "author_name": "Zhigang Zhang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Zhenghui Zha", - "author_inst": "Xiamen University" - }, - { - "author_name": "Tingting Chen", - "author_inst": "Xiamen University" - }, - { - "author_name": "Zhiping Wang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Jie Chen", - "author_inst": "Xiamen University" - }, - { - "author_name": "Hui Sun", - "author_inst": "Xiamen University" - }, - { - "author_name": "Tingting Deng", - "author_inst": "Xiamen University" - }, - { - "author_name": "Yingbin Wang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Yixin Chen", - "author_inst": "Xiamen University" - }, - { - "author_name": "Qinjian Zhao", - "author_inst": "Xiamen University" - }, - { - "author_name": "Jun Zhang", - "author_inst": "Xiamen University" - }, - { - "author_name": "Ying Gu", - "author_inst": "Xiamen University" - }, - { - "author_name": "Shaowei Li", - "author_inst": "Xiamen University" - }, - { - "author_name": "Ningshao Xia", - "author_inst": "Xiamen University" + "author_name": "Peng Shao", + "author_inst": "Xi'an Polytechnic University" } ], "version": "1", - "license": "", - "type": "new results", - "category": "molecular biology" + "license": "cc_by_nc_nd", + "type": "PUBLISHAHEADOFPRINT", + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.03.15.993097", @@ -1614976,47 +1615881,39 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.14.20035873", - "rel_title": "Expected impact of COVID-19 outbreak in a major metropolitan area in Brazil", + "rel_doi": "10.1101/2020.03.14.20035956", + "rel_title": "Assessment of public attention, risk perception, emotional and behavioural responses to the COVID-19 outbreak: social media surveillance in China", "rel_date": "2020-03-17", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.14.20035873", - "rel_abs": "In January 2020 China reported to the World Health Organization an outbreak of pneumonia of undetermined origin in the city of Wuhan, Hubei. In January 30, 2020, the World Health Organization declared the outbreak of COVID-19 as a Public Health Emergency of International Interest (PHEI).\n\nObjectivesThe aim of this study is to assess the impact of a COVID-19 epidemic in the metropolitan region of Sao Paulo, Brazil.\n\nMethodsWe used a generalized SEIR (Susceptibles, Exposed, Infectious, Recovered) model, with additional Hospitalized variables (SEIHR model) and age-stratified structure to analyze the expected time evolution during the onset of the epidemic in the metropolitan area of Sao Paulo. The model allows to determine the evolution of the number of cases, the number of patients admitted to hospitals and deaths caused by COVID-19. In order to investigate the sensibility of our results with respect to parameter estimation errors we performed Monte Carlo analysis with 100 000 simulations by sampling parameter values from an uniform distribution in the confidence interval.\n\nResultsWe estimate 1 368 (IQR: 880, 2 407) cases, 301 (22%) in older people ([≥]60 years), 81 (50, 143) hospitalizations, and 14 (9, 26) deaths in the first 30 days, and 38 583 (IQR: 16 698, 113, 163) cases, 8 427 (21.8%) in older people ([≥]60 years), 2181 (914, 6392) hospitalizations, and 397(166, 1205) deaths in the first 60 days.\n\nLimitationsWe supposed a constant transmission probability Pc among different age-groups, and that every severe and critic case will be hospitalized, as well as that the detection capacity in all the primary healthcare services does not change during the outbreak.\n\nConclusionSupposing the reported parameters in the literature apply in the city of Sao Paulo, our study shows that it is expected that the impact of a COVID-19 outbreak will be important, requiring special planning from the authorities. This is the first study for a major metropolitan center in the south hemisphere, and we believe it can provide policy makers with a prognosis of the burden of the pandemic not only in Brazil, but also in other tropical zones, allowing to estimate total cases, hospitalization and deaths, in support to the management of the public health emergence caused by COVID-19.", - "rel_num_authors": 7, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.14.20035956", + "rel_abs": "BackgroundUsing social media surveillance data, this study aimed to assess public attention, risk perception, emotion, and behavioural response to the COVID-19 outbreak in real time.\n\nMethodsWe collected data from most popular social medias: Sina Weibo, Baidu search engine, and Ali e-commerce marketplace, from 1 Dec 2019 to 15 Feb 2020. Weibo post counts and Baidu searches were used to generate indices assessing public attention. Public intention and actual adoption of recommended protection measures or panic buying triggered by rumours and misinformation were measured by Baidu and Ali indices. Qualitative Weibo posts were analysed by the Linguistic Inquiry and Word Count text analysis programme to assess public emotion responses to epidemiological events, governments announcements, and control measures.\n\nFindingsWe identified two missed windows of opportunity for early epidemic control of the COVID-19 outbreak, one in Dec 2019 and the other between 31 Dec and 19 Jan, when public attention was very low despite the emerging outbreak. Delayed release of information ignited negative public emotions. The public responded quickly to government announcements and adopted recommended behaviours according to issued guidelines. We found rumours and misinformation regarding remedies and cures led to panic buying during the outbreak, and timely clarification of rumours effectively reduced irrational behaviour.\n\nInterpretationSocial media surveillance can enable timely assessments of public reaction to risk communication and epidemic control measures, and the immediate clarification of rumours. This should be fully incorporated into epidemic preparedness and response systems.\n\nFundingNational Natural Science Foundation of China.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Tarcisio M Rocha Filho", - "author_inst": "International Center for Condensed Matter Physics and Instituto de Fisica, Universidade de Brasilia, Brasilia, DF, BRAZIL" - }, - { - "author_name": "Fabiana S. Ganem dos Santos", - "author_inst": "Departamento de Imunizacao e Doencas Transmissiveis (DEIDT/SVS), Ministerio da Saude, Brasilia, DF, BRAZIL" - }, - { - "author_name": "Victor B Gomes", - "author_inst": "Departamento de Imunizacao e Doencas Transmissiveis (DEIDT/SVS), Ministerio da Saude, Brasilia, DF, BRAZIL" + "author_name": "Zhiyuan Hou", + "author_inst": "Fudan University" }, { - "author_name": "Thiago A.H. Rocha", - "author_inst": "Organizacao Panamericana de Saude (OPAS), Brasilia, DF, BRAZIL" + "author_name": "Fanxing Du", + "author_inst": "Fudan University" }, { - "author_name": "Julio H.R. Croda", - "author_inst": "Departamento de Imunizacao e Doencas Transmissiveis (DEIDT/SVS), Ministerio da Saude, Brasilia, DF, BRAZIL" + "author_name": "Hao Jiang", + "author_inst": "Fudan University" }, { - "author_name": "Walter M Ramalho", - "author_inst": "Faculdade de Ceilandia & Nucleo de Medicina Tropical, Universidade de Brasilia, Brasilia, DF, BRAZIL" + "author_name": "Xinyu Zhou", + "author_inst": "Fudan University" }, { - "author_name": "Wildo N Araujo", - "author_inst": "Faculdade de Ceilandia & Nucleo de Medicina Tropical, Universidade de Brasilia, Brasilia, DF, BRAZIL" + "author_name": "Leesa Lin", + "author_inst": "London School of Hygiene & Tropical Medicine" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "public and global health" }, { "rel_doi": "10.1101/2020.03.13.20035618", @@ -1616537,127 +1617434,27 @@ "category": "genomics" }, { - "rel_doi": "10.1101/2020.03.13.990226", - "rel_title": "Reinfection could not occur in SARS-CoV-2 infected rhesus macaques", + "rel_doi": "10.1101/2020.03.13.990267", + "rel_title": "Differential Antibody Recognition by Novel SARS-CoV-2 and SARS-CoV Spike Protein Receptor Binding Domains: Mechanistic Insights", "rel_date": "2020-03-14", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.13.990226", - "rel_abs": "A global pandemic of Corona Virus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome CoV-2 (SARS-CoV-2) is ongoing spread. It remains unclear whether the convalescing patients have a risk of reinfection. Rhesus macaques were rechallenged with SARS-CoV-2 during an early recovery phase from initial infection characterized by weight loss, interstitial pneumonia and systemic viral dissemination mainly in respiratory and gastrointestinal tracts. The monkeys rechallenged with the identical SARS-CoV-2 strain have failed to produce detectable viral dissemination, clinical manifestations and histopathological changes. A notably enhanced neutralizing antibody response might contribute the protection of rhesus macaques from the reinfection by SARS-CoV-2. Our results indicated that primary SARS-CoV-2 infection protects from subsequent reinfection.\n\nOne Sentence SummaryNeutralizing antibodies against SARS-CoV-2 might protect rhesus macaques which have undergone an initial infection from reinfection during early recovery days.", - "rel_num_authors": 27, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.03.13.990267", + "rel_abs": "The appearance of the novel betacoronavirus SARS-CoV-2 represents a major threat to human health, and its diffusion around the world is causing dramatic consequences. The knowledge of the 3D structures of SARS-CoV-2 proteins can facilitate the development of therapeutic and diagnostic molecules. Specifically, comparative analyses of the structures of SARS-CoV-2 proteins and homologous proteins from previously characterized viruses, such as SARS-CoV, can reveal the common and/or distinctive traits that underlie the mechanisms of recognition of cell receptors and of molecules of the immune system.\n\nHerein, we apply our recently developed energy-based methods for the prediction of antibody-binding epitopes and protein-protein interaction regions to the Receptor Binding Domain (RBD) of the Spike proteins from SARS-CoV-2 and SARS-CoV. Our analysis focusses only on the study of the structure of RBDs in isolation, without making use of any previous knowledge of binding properties. Importantly, our results highlight structural and sequence differences among the regions that are predicted to be immunoreactive and bind/elicit antibodies. These results provide a rational basis to the observation that several SARS-CoV RDB-specific monoclonal antibodies fail to appreciably bind the SARS-CoV-2 counterpart. Furthermore, we correctly identify the region of SARS-CoV-2 RBD that is engaged by the cell receptor ACE2 during viral entry into host cells.\n\nThe data, sequences and structures we present here can be useful for the development of novel therapeutic and diagnostic interventions.", + "rel_num_authors": 2, "rel_authors": [ { - "author_name": "Linlin Bao", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Wei Deng", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Hong Gao", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Chong Xiao", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Jiayi Liu", - "author_inst": "Bejing Anzhen Hospital, Capital Medical University." - }, - { - "author_name": "Jing Xue", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Qi Lv", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Jiangning Liu", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Pin Yu", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Yanfeng Xu", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Feifei Qi", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Yajin Qu", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Fengdi Li", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Zhiguang Xiang", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Haisheng Yu", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Shuran Gong", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Mingya Liu", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Guanpeng Wang", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Shunyi Wang", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Zhiqi Song", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Ying Liu", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences" - }, - { - "author_name": "Wenjie Zhao", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Yunlin Han", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Linna Zhao", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Xing Liu", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." - }, - { - "author_name": "Qiang Wei", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." + "author_name": "Filippo Marchetti", + "author_inst": "University of Pavia" }, { - "author_name": "Chuan Qin", - "author_inst": "Institute of Laboratory Animal Science, Chinese Academy of Medical Sciences." + "author_name": "Giorgio Colombo", + "author_inst": "University of Pavia" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "microbiology" + "category": "biochemistry" }, { "rel_doi": "10.1101/2020.03.12.988865", @@ -1618269,31 +1619066,79 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.10.20033738", - "rel_title": "Effectiveness of isolation and contact tracing for containment and slowing down a COVID-19 epidemic: a modelling study", + "rel_doi": "10.1101/2020.03.10.20033522", + "rel_title": "Protocol for a randomized controlled trial testing inhaled nitric oxide therapy in spontaneously breathing patients with COVID-19", "rel_date": "2020-03-13", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.10.20033738", - "rel_abs": "BackgroundNovel coronavirus (SARS-CoV-2) has extended its range of transmission in all parts of the world, with substantial variation in rates of transmission and severity of associated disease. Many countries have implemented social distancing as a measure to control further spread.\n\nMethodsWe evaluate whether and under which conditions containment or slowing down COVID-19 epidemics are possible by isolation and contact tracing in settings with various levels of social distancing. We use a stochastic transmission model in which every person generates novel infections according to a probability distribution that is affected by the incubation period distribution (time from infection to symptoms), distribution of the latent period (time from infection to onset of infectiousness), and overall transmissibility. The model distinguishes between close contacts (e.g., within a household) and other contacts in the population. Social distancing affects the number of contacts outside but not within the household.\n\nFindingsThe proportion of asymptomatic or unascertained cases has a strong impact on the controllability of the disease. If the proportion of asymptomatic infections is larger than 30%, contact tracing and isolation cannot achieve containment for an R0 of 2.5. Achieving containment by social distancing requires a reduction of numbers of non-household contacts by around 90%. Depending on the realized level of contact reduction, tracing and isolation of only household contacts, or of household and non-household contacts are necessary to reduce the effective reproduction number to below 1. A combination of social distancing with isolation and contact tracing leads to synergistic effects that increase the prospect of containment.\n\nInterpretationIsolation and contact tracing can be an effective means to slow down epidemics, but only if the majority of cases are ascertained. In a situation with social distancing, contact tracing can act synergistically and tip the scale towards containment, and can therefore be a tool for controlling COVID-19 epidemics as part of an exit strategy from current lockdown measures.\n\nFundingThis research was partly funded by ZonMw project number 91216062.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSAs of 8 April 2020, the novel coronavirus (SARS-CoV-2) has spread to more than 170 countries and has caused near 90,000 deaths of COVID-19 worldwide. In the absence of effective medicines and vaccines, the preventive measures are limited to social distancing, isolation of confirmed and suspected cases, and identification and quarantining of their contacts. Evidence suggests that a substantial portion of transmission may occur before the onset of symptoms and before cases can be isolated, and that many cases remain unascertained. This has potentially important implications for the prospect of containment by combinations of these measures.\n\nAdded value of this studyUsing a stochastic transmission model armed with current best estimates of epidemiological parameters, we evaluated under which conditions containment could be achieved with combinations of social distancing, isolation and contact tracing. We investigated the level of social distancing needed for containment, and how an additional implementation of isolation and contact tracing may likely help to in reducing the effective reproduction number to below 1, the critical threshold. We analyzed what proportion of household and non-household contacts need to be isolated effectively to achieve containment depending on the level of social distancing in the population. We estimated the impact of combinations of these measures on epidemic growth rate and doubling time for the number of infections. We find that under realistic assumptions on the level of social distancing, additional isolation and contact tracing are needed for stopping the epidemic. Whether quarantining only household contacts is sufficient, depends on levels of social distancing and timeliness of tracing and isolation.\n\nImplications of all the available evidenceOur analyses based on best understanding of the epidemiology of COVID-19, highlight that if social distancing is not complete, isolation and contact tracing at least of household contacts can help to delay and lower the epidemic peak. High levels of timely contact tracing of household and non-household contacts may be sufficient to control the epidemic.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.10.20033522", + "rel_abs": "Introductionthe current worldwide outbreak of Coronavirus disease 2019 (COVID-19) due to a novel coronavirus (SARS-CoV-2) is seriously threatening the public health. The number of infected patients is continuously increasing and the need for Intensive Care Unit admission ranges from 5 to 26%. The mortality is reported to be around 3.4% with higher values for the elderly and in patients with comorbidities. Moreover, this condition is challenging the healthcare system where the outbreak reached its highest value. To date there is still no available treatment for SARS-CoV-2. Clinical and preclinical evidence suggests that nitric oxide (NO) has a beneficial effect on the coronavirus-mediated acute respiratory syndrome, and this can be related to its viricidal effect. The time from the symptoms onset to the development of severe respiratory distress is relatively long. We hypothesize that high concentrations of inhaled NO administered during early phases of COVID-19 infection can prevent the progression of the disease.\n\nMethods and analysisThis is a multicenter randomized controlled trial. Spontaneous breathing patients admitted to the hospital for symptomatic COVID-19 infection will be eligible to enter the study. Patients in the treatment group will receive inhaled NO at high doses (140-180 parts per million) for 30 minutes, 2 sessions every day for 14 days in addition to the hospital care. Patient in the control group will receive only hospital care. The primary outcome is the percentage of patients requiring endotracheal intubation due to the progression of the disease in the first 28 days from enrollment in the study. Secondary outcomes include mortality at 28 days, proportion of negative test for SARS-CoV-2 at 7 days and time to clinical recovery.\n\nEthics and disseminationThe trial protocol has been approved at the Investigation Review Boards of Xijing Hospital (Xian, China) and The Partners Human Research Committee of Massachusetts General Hospital (Boston, USA) is pending. Recruitment is expected to start in March 2020. Results of this study will be published in scientific journals, presented at scientific meetings, and on related website or media in fighting this widespread contagious disease.\n\nTrial registrationClinicaltrials.gov. NCT submitted", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Mirjam E Kretzschmar", - "author_inst": "University Medical Center Utrecht, Utrecht University" + "author_name": "Lorenzo Berra", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" }, { - "author_name": "Ganna Rozhnova", - "author_inst": "University Medical Center Utrecht, Utrecht University" + "author_name": "Chong Lei", + "author_inst": "Xijing Hospital" }, { - "author_name": "Michiel E van Boven", - "author_inst": "University Medical Center Utrecht, Utrecht University" + "author_name": "Binxiao Su", + "author_inst": "Xijing Hospital" + }, + { + "author_name": "Hailong Dong", + "author_inst": "Xijing Hospital" + }, + { + "author_name": "Bijan Safaee Fakhr", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" + }, + { + "author_name": "Luigi Giuseppe Grassi", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" + }, + { + "author_name": "Raffaele Di Fenza", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA; University of Milan-Bicocca, Milan, Italy" + }, + { + "author_name": "Stefano Gianni", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" + }, + { + "author_name": "Riccardo Pinciroli", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" + }, + { + "author_name": "Emanuele Vassena", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" + }, + { + "author_name": "Caio Cesar Araujo Morais", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" + }, + { + "author_name": "Andrea Bellavia", + "author_inst": "Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA" + }, + { + "author_name": "Stefano Spina", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" + }, + { + "author_name": "Robert Kacmarek", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" + }, + { + "author_name": "Ryan Carroll", + "author_inst": "Massachusetts General Hospital, Boston, MA, USA" } ], "version": "1", "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "intensive care and critical care medicine" }, { "rel_doi": "10.1101/2020.03.09.20033530", @@ -1620526,41 +1621371,45 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.03.08.20031229", - "rel_title": "Mortality of COVID-19 is Associated with Cellular Immune Function Compared to Immune Function in Chinese Han Population", + "rel_doi": "10.1101/2020.03.08.20029710", + "rel_title": "A retrospective study of the clinical characteristics of COVID-19 infection in 26 children", "rel_date": "2020-03-10", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.08.20031229", - "rel_abs": "In December 2019, novel coronavirus (SARS-CoV-2) infected pneumonia occurred in Wuhan, China. The number of cases has increased rapidly but information on the clinical characteristics of SARS-CoV-2 pneumonia compared to normal controls in Chinese Han population is limited. Our objective is to describe the clinical characteristics of SARS-CoV-2 pneumonia compared to normal controls in the Chinese Han population. In this case series of 752 patients, the full spectrum of cases is described. Fever was present in 86-90% of the patients. The second most common symptom was cough (49.1-51.0%), fatigue (25.2-27.1%), sputum (20.0-23.1%), and headache (9.8-11.1%). the mortality rate is 4.6% in Wuhan, 1.9% in Beijing, and 0.9% in Shanghai. Our findings showed that the levels of lymphocytes were 0.8(IQR, 0.6-1.1)109/L in Wuhan, 1.0(IQR, 0.7-1.4)109/L in Beijing, and 1.1 (IQR, 0.8-1.5) 109/L in Shanghai before admission to hospitals, respectively, indicating that cellular immune function might relate to the mortality. Based on the reference ranges of normal Chinese Han population and the data of the critically ill patients we have observed, it is recommended that reference ranges of people at high risk of COVID-19 infection are CD3+ lymphocytes below 900 cells/mm3, CD4+ lymphocytes below 500 cells/mm3, and CD8+ lymphocytes below 300 cells/mm3.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.08.20029710", + "rel_abs": "BackgroundThe outbreak of novel coronavirus pneumonia in China began in December 2019. Studies on novel coronavirus disease (COVID-19) were less based on pediatric patients. This study aimed to reveal the clinical characteristics of COVID-19 in children.\n\nMethodThis study retrospectively analyzed the clinical symptoms, laboratory results, chest CT, and treatment of children with laboratory-confirmed COVID-19(ie, with samples that were positive for 2019 novel coronavirus[2019-nCoV]) who were admitted to Shenzhen Center of National Infectious Disease Clinical Medical Research from January 16 to February 8, 2020.\n\nResultNine patients had no obvious clinical symptom. 11 patients developed fever. Other symptoms, including cough(in eleven of seventeen patients), rhinorrhea(in two), diarrhea(in two), vomiting(in two), were also observed. A small minority of patients had lymphocytopenia. Alanine transaminase or transaminase increased in three cases. According to chest CT scan, 11 patients showed unilateral pneumonia, 8 patients had no pulmonary infiltration. No serious complications such as acute respiratory syndrome and acute lung injury occurred in all patients.\n\nConclusionThe clinical characteristics of 2019-nCoV infection in children were different from adult. The overall condition of children were mild and have a good prognosis.\n\nMainpointCOVID-19 is a kind of new infectious disease.The clinical characteristics of 2019-nCoV infection in children may different from adult. Myocardium likely less affected by 2019-nCoV in children.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Qiang Zeng Sr.", - "author_inst": "Chinese PLA General Hospital" + "author_name": "Anjue Tang", + "author_inst": "The Third People's Hospital of Shenzhen" }, { - "author_name": "Yong-zhe Li Sr.", - "author_inst": "Peking Union Medical College Hospital" + "author_name": "Wenhui Xu", + "author_inst": "the Third People's Hospital of Shenzhen" }, { - "author_name": "Gang Huang Sr.", - "author_inst": "Shanghai University of Medicine and Health Sciences" + "author_name": "min shen", + "author_inst": "the Third People's Hospital of Shenzhen" }, { - "author_name": "Wei Wu Sr.", - "author_inst": "Peking Union Medical College and Chinese Academy of Medical Sciences" + "author_name": "Peifen Chen", + "author_inst": "the Third People's Hospital of Shenzhen" }, { - "author_name": "Sheng-yong Dong Sr.", - "author_inst": "Chinese PLA General Hospital" + "author_name": "Guobao Li", + "author_inst": "the Third People's Hospital of Shenzhen" }, { - "author_name": "Yang Xu", - "author_inst": "Shanghai University of Medicine and Health Sciences" + "author_name": "Yingxia Liu", + "author_inst": "National Infectious Diseases Clinical Medical Research Center, Shenzhen, China." + }, + { + "author_name": "Lei Liu", + "author_inst": "National Infectious Diseases Clinical Medical Research Center, Shenzhen, China." } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1622060,89 +1622909,61 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.05.20031591", - "rel_title": "Acute Myocardial Injury of Patients with Coronavirus Disease 2019", + "rel_doi": "10.1101/2020.03.04.20031401", + "rel_title": "Outcome reporting from protocols of clinical trials of Coronavirus Disease 2019 (COVID-19): a review", "rel_date": "2020-03-08", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.05.20031591", - "rel_abs": "BackgroundSince the outbreak of the Coronavirus Disease 2019 (COVID-19) in China, respiratory manifestations of the disease have been observed. However, as a fatal comorbidity, acute myocardial injury (AMI) in COVID-19 patients has not been previously investigated in detail. We investigated the clinical characteristics of COVID-19 patients with AMI and determined the risk factors for AMI in them.\n\nMethodsWe analyzed data from 53 consecutive laboratory-confirmed and hospitalized COVID-19 patients (28 men, 25 women; age, 19-81 years). We collected information on epidemiological and demographic characteristics, clinical features, routine laboratory tests (including cardiac injury biomarkers), echocardiography, electrocardiography, imaging findings, management methods, and clinical outcomes.\n\nResultsCardiac complications were found in 42 of the 53 (79.25%) patients: tachycardia (n=15), electrocardiography abnormities (n=11), diastolic dysfunction (n=20), elevated myocardial enzymes (n=30), and AMI (n=6). All the six AMI patients were aged >60 years; five of them had two or more underlying comorbidities (hypertension, diabetes, cardiovascular diseases, and chronic obstructive pulmonary disease). Novel coronavirus pneumonia (NCP) severity was higher in the AMI patients than in patients with non-definite AMI (p<0.001). All the AMI patients required care in intensive care unit; of them, three died, two remain hospitalized. Multivariate analyses showed that C-reactive protein (CRP) levels, NCP severity, and underlying comorbidities were the risk factors for cardiac abnormalities in COVID-19 patients.\n\nConclusionsCardiac complications are common in COVID-19 patients. Elevated CRP levels, underlying comorbidities, and NCP severity are the main risk factors for cardiac complications in COVID-19 patients.", - "rel_num_authors": 19, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.04.20031401", + "rel_abs": "ObjectivesTo examine heterogeneity of outcomes in protocols of clinical trials of Coronavirus Disease 2019 (COVID-19) and to identify outcomes for prioritization in developing a core outcome set (COS) in this field.\n\nDesignThis study is a review.\n\nData sourcesDatabases of ICMJE-accepted clinical trial registry platform were searched on February 14, 2020.\n\nEligibility CriteriaRandomized controlled trials (RCTs) and non-RCTs of COVID-19 were considered. Conditions of patients include common type, severe type or critical type. Interventions include traditional Chinese medicine (TCM) and Western medicine. We excluded trials that for discharged patients, psychological intervention and complications of COVID-19.\n\nData extraction and synthesisThe general information and outcomes, outcome measurement instruments and measurement times were extracted. The results were analysed by descriptive analysis.\n\nResults19 registry platforms were searched. A total of 97 protocols were included from 160 protocols. For protocols of TCM clinical trials, 76 outcomes from 16 outcome domains were reported, and almost half (34/76, 44.74%) of outcomes were reported only once; the most frequently reported outcome was time of SARS-CoV-2 RNA turns to negative. 27 (27/76, 35.53%) outcomes were provided one or more outcome measurement instruments. 10 outcomes were provided one or more measurement time frame. For protocols of western medicine clinical trials, 126 outcomes from 17 outcome domains were reported; almost half (62/126, 49.21%) of outcomes were reported only once; the most frequently reported outcome was proportion of patients with negative SARS-CoV-2. 27 outcomes were provided one or more outcome measurement instruments. 40 (40/126, 31.75%) outcomes were provided one or more measurement time frame.\n\nConclusionOutcome reporting in protocols of clinical trials of COVID-19 is inconsistent. Thus, developing a core outcome set is necessary.\n\nStrengths and limitations of this study1. This review is the first to describe variation in outcomes, outcome measurement instruments and outcome measurement time reporting in clinical trials for Coronavirus Disease 2019 (COVID-19).\n2. All the database of ICMJE-accepted clinical trial registry platform were searched, and randomized controlled trials and observational studies were considered.\n4. The aim of this review was to provide a list of outcomes for clinical trials of COVID-19, both interventions of Traditional Chinese Medicine and western medicine were considered.\n5. When the searching was conducted, no clinical trials were registered by countries out of China, so all of included protocols were from China.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Huayan Xu", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" - }, - { - "author_name": "Keke Hou", - "author_inst": "Public Health Clinical Center of Chengdu" - }, - { - "author_name": "Hong Xu", - "author_inst": "West China Second University Hospital, Sichuan University" - }, - { - "author_name": "Zhenlin Li", - "author_inst": "State Key Laboratory of Biotherapy, West China Hospital, Sichuan University" - }, - { - "author_name": "Huizhu Chen", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" - }, - { - "author_name": "Na Zhang", - "author_inst": "Public Health Clinical Center of Chengdu" - }, - { - "author_name": "Rong Xu", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" - }, - { - "author_name": "Hang Fu", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" + "author_name": "Ruijin Qiu", + "author_inst": "Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine" }, { - "author_name": "Ran Sun", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" + "author_name": "Xuxu Wei", + "author_inst": "Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine" }, { - "author_name": "Lingyi Wen", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" + "author_name": "Mengzhu Zhao", + "author_inst": "First Teaching Hospital of Tianjin University of Traditional Chinese Medicine." }, { - "author_name": "Linjun Xie", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" + "author_name": "Changming Zhong", + "author_inst": "Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine." }, { - "author_name": "Hui Liu", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" + "author_name": "Chen Zhao", + "author_inst": "Institute of Basic Research In Clinical Medicine, China Academy of Chinese Medical Sciences" }, { - "author_name": "Kun Zhang", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" + "author_name": "Jiayuan Hu", + "author_inst": "Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine." }, { - "author_name": "Joseph B Selvanayagam", - "author_inst": "Flinders Medical Centre, Flinders University of South Australia" + "author_name": "Min Li", + "author_inst": "Beijing University of Chinese Medicine Third Affiliated Hospital" }, { - "author_name": "Chuan Fu", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, West China Second University Hospital, Sichuan University" + "author_name": "Ya Huang", + "author_inst": "Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine." }, { - "author_name": "Shihua Zhao", - "author_inst": "Cardiac Imaging Center, Fuwai Hospital, National Center for Cardiovascular Diseases of China, Chinese Academy of Medical Sciences and Peking Union Medical Colle" + "author_name": "Songjie Han", + "author_inst": "Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine." }, { - "author_name": "Zhigang Yang", - "author_inst": "State Key Laboratory of Biotherapy, West China Hospital, Sichuan University" + "author_name": "Tianmai He", + "author_inst": "Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine." }, { - "author_name": "Ming Yang", - "author_inst": "Public Health Clinical Center of Chengdu" + "author_name": "Jing Chen", + "author_inst": "Baokang Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin China" }, { - "author_name": "Yingkun Guo", - "author_inst": "Key Laboratory of Birth Defects and Related Diseases of Women and Children of Ministry of Education, Sichuan university" + "author_name": "Hongcai Shang", + "author_inst": "Key Laboratory of Chinese Internal Medicine of Ministry of Education and Beijing, Dongzhimen Hospital, Beijing University of Chinese Medicine." } ], "version": "1", @@ -1623641,29 +1624462,45 @@ "category": "radiology and imaging" }, { - "rel_doi": "10.1101/2020.03.03.20030858", - "rel_title": "Prediction of New Coronavirus Infection Based on a Modified SEIR Model", + "rel_doi": "10.1101/2020.03.04.20030916", + "rel_title": "Serological detection of 2019-nCoV respond to the epidemic: A useful complement to nucleic acid testing", "rel_date": "2020-03-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.03.20030858", - "rel_abs": "BACKGROUNDThe outbreak of the new coronavirus infection in Wuhan City, Hubei Province in December 2019, poses a huge threat to China and even global public health security. Respiratory droplets and contact transmission are the main routes of transmission of new coronaviruses. Compared with SARS and Ebola viruses, new coronavirus infections are infectious during the incubation period. Traditional SEIR (susceptibility-exposure-infection-Removal) There are some differences in conditions for the prediction of the epidemic trend of new coronavirus infection. The outbreak of the new coronavirus infection coincided with the Spring Festival before and after the Chinese Spring Festival.It is necessary to make appropriate optimization and amendments to the traditional model to meet the actual evolution of the epidemic situation.\n\nMETHODSThe traditional SEIR model assumes that the virus-infected person is not infectious during the incubation period and that the infected person did not take isolation measures during the illness. The transmission of the new coronavirus no longer meets the basic assumptions of the classical kinetic system. Therefore, this article first establishes a modified SEIR model. Predict and analyze the changing trend of the epidemic situation, then estimate the parameters involved in the infection dynamics model, and then use Matlab to simulate the established dynamic equations based on public data and analyze the results. Recommendations for universal prevention and control of infectious diseases.\n\nRESULTSThe first case of new coronavirus infection was confirmed in Wuhan on December 8, 2019. When Wuhan City took no action, assuming the average daily number of contacts per infected person k = 5, the number of infected persons will reach about 2,384,803 people; If wuhan adopts the measures of sealing the city on January 22, 2020, under the premise of k=2, the number of infected people decreases by 19,773 compared with that on January 23, and there is no significant change in the time when the number of infected people reaches the peak. Under the premise of k = 1, the number of infected persons was reduced by 14,330 compared with the closure on January 23, and the time to reach the peak of the number of infected persons was reduced by 2 days. If Wuhan City is closed for one day, the number of infected persons will increase from 106,145 to 130,626 under the premise of k = 2; the number of infected persons will increase from 74,369 to 92,010 under the premise of k = 1.\n\nCONCLUSIONSComparing the number of confirmed diagnoses actually notified by the department with the number of infected people obtained from the simulation of the model, it can be seen that the city closure measures adopted by the Wuhan Municipal Government on January 23 and the first-level response measures adopted by the country are effective for the epidemic Prevention and control play a vital role. Wearing a mask when going out and avoiding close contact with people can effectively reduce the infection rate.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.04.20030916", + "rel_abs": "Corona Virus Disease 2019 (COVID-19) has spread rapidly to more than 70 countries and regions overseas and over 80000 cases have been infected, resulting in more than three thousand deaths. Rapid diagnosis of patients remains a bottleneck in containing the progress of the epidemic. We used automated chemiluminescent immunoassay to detect serum IgM and IgG antibodies to 2019-nCoV of 736 subjects. COVID-19 patients were becoming reactive(positive) for specific antibodies from 7-12 days after the onset of morbidity. Specific IgM and IgG increased with the progression of the disease. The areas under the ROC curves of IgM and IgG were 0.988 and 1.000, respectively. Specific antibody detection has good sensitivity and specificity. Detection of specific antibodies in patients with fever can be a good distinction between COVID-19 and other diseases, so as to be a complement to nucleic acid diagnosis to early diagnosis of suspected cases.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Zhou Tang", - "author_inst": "Sichuan Academy of Social Sciences" + "author_name": "Jin Zhang", + "author_inst": "Shengjing Hospital of China Medical University" }, { - "author_name": "Xianbin Li", - "author_inst": "Sichuan Academy of Social Sciences" + "author_name": "Jianhua Liu", + "author_inst": "Shengjing Hospital of China Medical University" }, { - "author_name": "Houqiang Li", - "author_inst": "Sichuan Academy of Social Sciences" + "author_name": "Na Li", + "author_inst": "Shengjing Hospital of China Medical University" + }, + { + "author_name": "Yong Liu", + "author_inst": "Shengjing Hospital of China Medical University" + }, + { + "author_name": "Rui Ye", + "author_inst": "Shengjing Hospital of China Medical University" + }, + { + "author_name": "Xiaosong Qin", + "author_inst": "Shengjing Hospital of China Medical University" + }, + { + "author_name": "Rui Zheng", + "author_inst": "Shengjing Hospital of China Medical University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1625343,61 +1626180,77 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.02.29.20029462", - "rel_title": "68 Consecutive patients assessed for COVID-19 infection; experience from a UK regional infectious disease unit", + "rel_doi": "10.1101/2020.03.04.20029538", + "rel_title": "Nanopore target sequencing for accurate and comprehensive detection of SARS-CoV-2 and other respiratory viruses", "rel_date": "2020-03-06", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.29.20029462", - "rel_abs": "Clinical assessment of possible infection with SARS-CoV-2, the novel coronavirus responsible for the outbreak of COVID-19 respiratory illness, has been a major activity of infectious diseases services in the UK and elsewhere since the first report of cases in December 2019. We report our case series of 68 patients, reviewed by Infectious Diseases Consultants at a Regional Infectious Diseases Unit in the UK. We prospectively evaluated our service between the 29th Jan 2020 and 24th Feb 2020.\n\nDemographic, clinical, epidemiological and laboratory data were collected. We have compared clinical features and subsequent diagnosis between well patients not requiring admission for clinical reasons or antimicrobials with those assessed as needing either admission or antimicrobial treatment.\n\nFinal microbiological diagnoses included SARS-CoV-2 (COVID-19), Mycoplasma pneumonia, influenza A, RSV, non SARS/MERS coronaviruses, rhinovirus/enterovirus. 9/68 were treated with antimicrobials, 15/68 were admitted to a negative pressure room of whom 5/68 were admitted solely due to an inability to isolate at home. Patients requiring either admission on clinical grounds or antimicrobials (14/68) were similar to those not requiring admission or antimicrobials, with modestly more fever and shortness of breath in the clinically admitted / antimicrobial group. The most commonly prescribed antimicrobials were doxycycline, moxifloxacin and oseltamivir.\n\nThe majority of patients had mild illness which did not require a clinical intervention to manage. This finding supports a community testing approach supported by clinicians to review the proportion of more unwell patients.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.04.20029538", + "rel_abs": "The ongoing novel coronavirus pneumonia COVID-19 outbreak in Wuhan, China, has engendered numerous cases of infection and death. COVID-19 diagnosis relies upon nucleic acid detection; however, current recommended methods exhibit high false-negative rates, low sensitivity, and cannot identify other respiratory virus infections, thereby resulting patient misdiagnosis and impeding epidemic containment. Combining the advantages of target amplification and long-read, real-time nanopore sequencing, we developed nanopore target sequencing (NTS) to detect SARS- CoV-2 and other respiratory viruses simultaneously within 6-10 h. Parallel testing with approved qPCR kits of SARS-CoV-2 and NTS using 61 nucleic acid samples from suspected COVID-19 cases confirmed that NTS identified more infected patients as positive, and could also monitor for mutated nucleic acid sequence or other respiratory virus infection in the test sample. NTS is thus suitable for contemporary COVID-19 diagnosis; moreover, this platform can be further extended for diagnosing other viruses or pathogens.", + "rel_num_authors": 15, "rel_authors": [ { - "author_name": "Nicholas Easom", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Ming Wang", + "author_inst": "Department of Clinical Laboratory, Renmin Hospital of Wuhan University" }, { - "author_name": "Peter Moss", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Aisi Fu", + "author_inst": "Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and Wuhan University School of Pharmaceutical Sciences" }, { - "author_name": "Gavin Barlow", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Ben Hu", + "author_inst": "Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and Wuhan University School of Pharmaceutical Sciences" }, { - "author_name": "Anda Samson", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Yongqing Tong", + "author_inst": "Department of Clinical Laboratory, Renmin Hospital of Wuhan University" }, { - "author_name": "Tom Taynton", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Ran Liu", + "author_inst": "Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and Wuhan University School of Pharmaceutical Sciences" }, { - "author_name": "Kate Adams", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Jiashuang Gu", + "author_inst": "Wuhan Dgensee Clinical Laboratory Co., Ltd." }, { - "author_name": "Monica Ivan", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Jianghao Liu", + "author_inst": "Wuhan Dgensee Clinical Laboratory Co., Ltd." }, { - "author_name": "Phillipa Burns", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Wen Jiang", + "author_inst": "Wuhan Dgensee Clinical Laboratory Co., Ltd." }, { - "author_name": "Kavitha Gajee", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Gaigai Shen", + "author_inst": "Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and Wuhan University School of Pharmaceutical Sciences" }, { - "author_name": "Kirstine Eastick", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Wanxu Zhao", + "author_inst": "Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and Wuhan University School of Pharmaceutical Sciences" }, { - "author_name": "Patrick Lillie", - "author_inst": "Department of Infection, Hull University Teaching Hospitals NHS Trust, Hull, East Yorkshire, United Kingdom" + "author_name": "Dong Men", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" + }, + { + "author_name": "Lilei Yu", + "author_inst": "Department of Internal Medicine, Renmin Hospital of Wuhan University." + }, + { + "author_name": "Zixin Deng", + "author_inst": "Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and Wuhan University School of Pharmaceutical Sciences" + }, + { + "author_name": "Yan Li", + "author_inst": "Department of Clinical Laboratory, Renmin Hospital of Wuhan University" + }, + { + "author_name": "Tiangang Liu", + "author_inst": "Key Laboratory of Combinatorial Biosynthesis and Drug Discovery, Ministry of Education and Wuhan University School of Pharmaceutical Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1627248,39 +1628101,47 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.03.02.20030064", - "rel_title": "Forecasting the Cumulative Number of COVID-19 Deaths in China: Can More Lives Be Saved?", + "rel_doi": "10.1101/2020.02.28.20028555", + "rel_title": "Analysis of epidemiological characteristics of coronavirus 2019 infection and preventive measures in Shenzhen China: a heavy population city", "rel_date": "2020-03-03", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.03.02.20030064", - "rel_abs": "The COVID-19 outbreak is on-going in China. Here we estimated the potential total numbers of COVID-19 deaths in China, outside Hubei (in China), Hubei Province, Wuhan City and outside Wuhan (in Hubei) by Boltzmann function-based analyses, which are 3342 (95% CI, 3214, 3527), 111 (109, 114), 3245 (3100, 3423), 2613 (2498, 2767) and 627 (603, 654), respectively. The results may help to evaluate the severity of COVID-19 outbreaks and facilitate timely mental service for the families of passed patients.", - "rel_num_authors": 5, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.28.20028555", + "rel_abs": "Coronavirus 2019 infection (COVID-19) outbroke in Wuhan, Hubei and spread to all provinces in China and other countries. Shenzhen ranked the top cities outside Wuhan with reported 416 confirmed cases by February 20, 2020. Here, we analyzed the epidemiological characteristics of COVID-19 in Shenzhen and potential link to the preventive strategies for the whole city and inside hospitals. Based on the daily new cases, the epidemic of COVID-19 in Shenzhen can be classified into three phases: the slow increase phase from January 19 to January 28, the rapid increase and plateau phase from January 29 to February 5 and the decline phase since February 6. In the three phases, the number of patients from Hubei decreased, and the number of familial clustering cases increased. The newly diagnosed COVID-19 cases reached its peak around January 31, which was 7 days after the peak date of cases arrival at Shenzhen. A series of early preventive strategies were implemented since January 19, which included detection of body temperature at all entrances of main traffic and buildings, outpatients service specially for patients with fever in all main hospitals in Shenzhen. All the patients with fever were screened with nasal or throat swab PCR detection of coronavirus 2019, Chest CT and blood lymphocyte counting in order to find out early case of COVID-19. Observation wards were established in every main hospital and a designated hospital was responsible for admission and medical care of all confirmed cases. Protection procedure was established for all medical staff involved in the screening and care of suspected and confirmed cases. 14 days isolated observation of all subjects arrived at Shenzhen from Hubei was implemented in February 2. After the implementation of all these strategies and measures, the COVID-19 cases started to decline since February 6. There were almost no community transmission and nosocomial infection occurred in Shenzhen.\n\nIn conclusion, in situation of major outbreak of respiratory infectious disease, such as COVID-19, in nearby province of Hubei, Shenzhen, a high population density, high proportion of external population and high mobility city, has to face the imported cases and risk of spreading the outbreak into Shenzhen city. The implementation of early preventive strategies and measures in Shenzhen were successful in early identification of COVID-19 cases and prevented major outbreak occurred in Shenzhen. Early identification of imported cases, prevention of family clustering transmission, preventive measures in the public area and very strict infection control procedure in hospital setting are crucial for the successful control of outbreak in Shenzhen.", + "rel_num_authors": 7, "rel_authors": [ { - "author_name": "Cheng Long", - "author_inst": "West China Hospital of Sichuan University" + "author_name": "Kai Yang", + "author_inst": "Jinan university" }, { - "author_name": "Qi Ying", - "author_inst": "Texas A&M University College Station" + "author_name": "Lingwei Wang", + "author_inst": "Jinan University" }, { - "author_name": "Xinmiao Fu", - "author_inst": "Fujian Normal University" + "author_name": "Furong Li", + "author_inst": "Jinan university" }, { - "author_name": "Zhongyan Li", - "author_inst": "Fujian Normal University" + "author_name": "Dandan Chen", + "author_inst": "Jinan university" }, { - "author_name": "Yuanyuan Gao", - "author_inst": "Fujian Normal University" + "author_name": "Xi Li", + "author_inst": "Jinan university" + }, + { + "author_name": "Chen Qiu", + "author_inst": "Jinan university" + }, + { + "author_name": "Rongchang Chen", + "author_inst": "Jinan University" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", - "category": "epidemiology" + "category": "respiratory medicine" }, { "rel_doi": "10.1101/2020.03.01.20029397", @@ -1628589,57 +1629450,85 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.02.27.20027524", - "rel_title": "Sex differences in clinical findings among patients with coronavirus disease 2019 (COVID-19) and severe condition", + "rel_doi": "10.1101/2020.02.26.20028589", + "rel_title": "Heart injury signs are associated with higher and earlier mortality in coronavirus disease 2019 (COVID-19)", "rel_date": "2020-02-29", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.27.20027524", - "rel_abs": "ObjectiveTo compare the sex differences in the clinical findings among patients with severe coronavirus disease 2019 (COVID-19).\n\nMethodsWe retrospectively collected data of 47 patients diagnosed as severe type of COVID-19 from February 8 to 22, 2020, including demographics, illness history, physical examination, laboratory test, management, and compared differences between men and women.\n\nResultsOf the 47 patients, 28 (59.6%) were men. The median age was 62 years, and 30 (63.8%) had comorbidities. The initial symptoms were mainly fever (34 [72.3%]), cough (36 [76.6%]), myalgia (5 [10.6%]) and fatigue (7 [14.9%]). Procalcitonin level was higher in men than in women (0.08 vs. 0.04ng/ml, p=0.002). N-terminal-pro brain natriuretic peptide increased in 16 (57.1%) men and 5 (26.3%) women (p=0.037). Five men (17.9%) had detected positive influenza A antibody, but no women. During 2-week admission, 5 (17.9%) men and 1 (5.3%) woman were reclassified into the critical type due to deterioration. Mortality was 3.6% in men and 0 in women respectively. Four (21.1%) women and one man (3.6%) recovered and discharged from hospital.\n\nConclusionSex differences may exist in COVID-19 patients of severe type. Men are likely to have more complicated clinical condition and worse in-hospital outcomes as compared to women.", - "rel_num_authors": 11, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.26.20028589", + "rel_abs": "ImportanceHeart injury can be easily induced by viral infection such as adenovirus and enterovirus. However, whether coronavirus disease 2019 (COVID-19) causes heart injury and hereby impacts mortality has not yet been fully evaluated.\n\nObjectiveTo explore whether heart injury occurs in COVID-19 on admission and hereby aggravates mortality later.\n\nDesign, Setting, and ParticipantsA single-center retrospective cohort study including 188 COVID-19 patients admitted from December 25, 2019 to January 27, 2020 in Wuhan Jinyintan Hospital, China; follow up was completed on February 11, 2020.\n\nExposuresHigh levels of heart injury indicators on admission (hs-TNI; CK; CK-MB; LDH; -HBDH).\n\nMain Outcomes and MeasuresMortality in hospital and days from admission to mortality (survival days).\n\nResultsOf 188 patients with COVID-19, the mean age was 51.9 years (standard deviation: 14.26; range: 21[~]83 years) and 119 (63.3%) were male. Increased hs-TnI levels on admission tended to occur in older patients and patients with comorbidity (especially hypertension). High hs-TnI on admission ([≥] 6.126 pg/mL), even within the clinical normal range (0[~]28 pg/mL), already can be associated with higher mortality. High hs-TnI was associated with increased inflammatory levels (neutrophils, IL-6, CRP, and PCT) and decreased immune levels (lymphocytes, monocytes, and CD4+ and CD8+ T cells). CK was not associated with mortality. Increased CK-MB levels tended to occur in male patients and patients with current smoking. High CK-MB on admission was associated with higher mortality. High CK-MB was associated with increased inflammatory levels and decreased lymphocytes. Increased LDH and -HBDH levels tended to occur in older patients and patients with hypertension. Both high LDH and -HBDH on admission were associated with higher mortality. Both high LDH and -HBDH were associated with increased inflammatory levels and decreased immune levels. hs-TNI level on admission was negatively correlated with survival days (r= -0.42, 95% CI= -0.64[~]-0.12, P=0.005). LDH level on admission was negatively correlated with survival days (r= -0.35, 95% CI= -0.59[~]-0.05, P=0.022).\n\nConclusions and RelevanceHeart injury signs arise in COVID-19, especially in older patients, patients with hypertension and male patients with current smoking. COVID-19 virus might attack heart via inducing inflammatory storm. High levels of heart injury indicators on admission are associated with higher mortality and shorter survival days. COVID-19 patients with signs of heart injury on admission must be early identified and carefully managed by cardiologists, because COVID-19 is never just confined to respiratory injury.\n\nKey pointsO_ST_ABSQuestionC_ST_ABSDoes coronavirus disease 2019 (COVID-19) cause heart injury and hereby impact mortality?\n\nFindingsIn this retrospective cohort study including 188 patients with COVID-19, patients with high levels of high-sensitivity cardiac troponin I (hs-TNI) on admission had significantly higher mortality (50.0%) than patients with moderate or low levels of hs-TNI (10.0% or 9.1%). hs-TNI level on admission was significantly negatively correlated with survival days (r= -0.42, 95% CI= -0.64[~]-0.12, P=0.005).\n\nMeaningCOVID-19 patients with signs of heart injury on admission must be early identified and carefully managed by cardiologists, in order to maximally prevent or rescue heart injury-related mortality in COVID-19.", + "rel_num_authors": 18, "rel_authors": [ { - "author_name": "Jing Li", - "author_inst": "Division of Cardiology, Beijing Hospital, Beijing 100730, China" + "author_name": "Chaomin Wu", + "author_inst": "QingPu Branch of Zhongshan Hospital Affiliated to Fudan University" }, { - "author_name": "Yinghua Zhang", - "author_inst": "Division of Cardiology, Xuanwu Hospital Capital Medical University, Beijing 100053, China" + "author_name": "Xianglin Hu", + "author_inst": "Zhongshan Hospital, Fudan University, China" }, { - "author_name": "Fang Wang", - "author_inst": "Division of Cardiology, Beijing Hospital, Beijing 100730, China" + "author_name": "Jianxin Song", + "author_inst": "Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology" }, { - "author_name": "Bing Liu", - "author_inst": "Division of Cardiology, Beijing Hospital, Beijing 100730, China" + "author_name": "Chunling Du", + "author_inst": "QingPu Branch of Zhongshan Hospital Affiliated to Fudan University" }, { - "author_name": "Hui Li", - "author_inst": "Division of Cardiology, Beijing Hospital, Beijing 100730, China" + "author_name": "Jie Xu", + "author_inst": "Fengxian Guhua Hospital, Shanghai" }, { - "author_name": "Guodong Tang", - "author_inst": "Division of Cardiology, Beijing Hospital, Beijing 100730, China" + "author_name": "Dong Yang", + "author_inst": "Zhongshan Hospital, Fudan University, China" }, { - "author_name": "Zhigang Chang", - "author_inst": "Division of Intensive Care Unit, Beijing Hospital, Beijing 100730, China" + "author_name": "Dechang Chen", + "author_inst": "Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai" }, { - "author_name": "Aihua Liu", - "author_inst": "Division of Rheumatology and Immunology, Beijing Hospital, Beijing 100730, China" + "author_name": "Ming Zhong", + "author_inst": "Zhongshan Hospital, Fudan University, China" }, { - "author_name": "Chunyi Fu", - "author_inst": "Division of Emergency, Beijing Hospital, Beijing 100730, China" + "author_name": "Jinjun Jiang", + "author_inst": "Zhongshan Hospital, Fudan University, China" }, { - "author_name": "Jing Gao", - "author_inst": "Division of Cardiology, Xuanwu Hospital Capital Medical University, Beijing 100053, China" + "author_name": "Weining Xiong", + "author_inst": "Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine" }, { - "author_name": "Jing Li", - "author_inst": "Division of Cardiology, Xuanwu Hospital Capital Medical University, Beijing 100053, China" + "author_name": "Ke Lang", + "author_inst": "Zhongshan Hospital, Fudan University, China" + }, + { + "author_name": "Yuye Zhang", + "author_inst": "Zhongshan Hospital, Fudan University, China" + }, + { + "author_name": "Guohua Shi", + "author_inst": "Qingpu Traditional Chinese Medicine Hospital, Shanghai," + }, + { + "author_name": "Lei Xu", + "author_inst": "Gongli Hospital, Pudong New Area, Shanghai," + }, + { + "author_name": "Yuanlin Song", + "author_inst": "Zhongshan Hospital, Fudan University, China" + }, + { + "author_name": "Xin Zhou", + "author_inst": "Shanghai General Hospital, School of Medicine in Shanghai Jiao Tong University" + }, + { + "author_name": "Ming Wei", + "author_inst": "Wuhan Jinyintan Hospital, Wuhan" + }, + { + "author_name": "Junhua Zheng", + "author_inst": "Shanghai General Hospital, School of Medicine in Shanghai Jiao Tong University" } ], "version": "1", @@ -1630347,43 +1631236,83 @@ "category": "bioinformatics" }, { - "rel_doi": "10.1101/2020.02.22.961268", - "rel_title": "A simple magnetic nanoparticles-based viral RNA extraction method for efficient detection of SARS-CoV-2", + "rel_doi": "10.1101/2020.02.25.963546", + "rel_title": "An Effective CTL Peptide Vaccine for Ebola Zaire Based on Survivors' CD8+ Targeting of a Particular Nucleocapsid Protein Epitope with Potential Implications for COVID-19 Vaccine Design", "rel_date": "2020-02-27", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.22.961268", - "rel_abs": "1The ongoing outbreak of the novel coronavirus disease 2019 (COVID-19) originating from Wuhan, China, draws worldwide concerns due to its long incubation period and strong infectivity. Although RT-PCR-based molecular diagnosis techniques are being widely applied for clinical diagnosis currently, timely and accurate diagnosis are still limited due to labour intensive and time-consuming operations of these techniques. To address the issue, herein we report the synthesis of poly (amino ester) with carboxyl groups (PC)-coated magnetic nanoparticles (pcMNPs), and the development of pcMNPs-based viral RNA extraction method for the sensitive detection of COVID-19 causing virus, the SARS-CoV-2. This method combines the lysis and binding steps into one step, and the pcMNPs-RNA complexes can be directly introduced into subsequent RT-PCR reactions. The simplified process can purify viral RNA from multiple samples within 20 min using a simple manual method or an automated high-throughput approach. By identifying two different regions (ORFlab and N gene) of viral RNA, a 10-copy sensitivity and a strong linear correlation between 10 and 105 copies of SARS-CoV-2 pseudovirus particles are achieved. Benefitting from the simplicity and excellent performances, this new extraction method can dramatically reduce the turn-around time and operational requirements in current molecular diagnosis of COVID-19, in particular for the early clinical diagnosis.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.25.963546", + "rel_abs": "The 2013-2016 West Africa EBOV epidemic was the biggest EBOV outbreak to date. An analysis of virus-specific CD8+ T-cell immunity in 30 survivors showed that 26 of those individuals had a CD8+ response to at least one EBOV protein. The dominant response (25/26 subjects) was specific to the EBOV nucleocapsid protein (NP). It has been suggested that epitopes on the EBOV NP could form an important part of an effective T-cell vaccine for Ebola Zaire. We show that a 9-amino-acid peptide NP44-52 (YQVNNLEEI) located in a conserved region of EBOV NP provides protection against morbidity and mortality after mouse adapted EBOV challenge. A single vaccination in a C57BL/6 mouse using an adjuvanted microsphere peptide vaccine formulation containing NP44-52 is enough to confer immunity in mice. Our work suggests that a peptide vaccine based on CD8+ T-cell immunity in EBOV survivors is conceptually sound and feasible. Nucleocapsid proteins within SARS-CoV-2 contain multiple class I epitopes with predicted HLA restrictions consistent with broad population coverage. A similar approach to a CTL vaccine design may be possible for that virus.", + "rel_num_authors": 16, "rel_authors": [ { - "author_name": "Zhen Zhao", - "author_inst": "Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences" + "author_name": "Charles V Herst", + "author_inst": "Flow Pharma, Inc" }, { - "author_name": "Haodong Cui", - "author_inst": "Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences" + "author_name": "Scott Burkholz", + "author_inst": "Flow Pharma, Inc" }, { - "author_name": "Wenxing Song", - "author_inst": "Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences" + "author_name": "John Sidney", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Xiaoling Ru", - "author_inst": "Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences" + "author_name": "Alessandro Sette", + "author_inst": "La Jolla Institute for Immunology" }, { - "author_name": "Wenhua Zhou", - "author_inst": "Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences" + "author_name": "Paul E Harris", + "author_inst": "Columbia University" }, { - "author_name": "Xuefeng Yu", - "author_inst": "Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences" + "author_name": "Shane Massey", + "author_inst": "University of Texas Medical Branch Office of Development" + }, + { + "author_name": "Trevor Brasel", + "author_inst": "University of Texas Medical Branch Office of Development" + }, + { + "author_name": "Edecio Cunha-Neto", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "Daniela S Rosa", + "author_inst": "University of Sao Paulo" + }, + { + "author_name": "William Chong Hang Chao", + "author_inst": "University of Macau" + }, + { + "author_name": "Richard Thomas Carback III", + "author_inst": "Flow Pharma, Inc" + }, + { + "author_name": "Tom Hodge", + "author_inst": "Flow Pharma, Inc" + }, + { + "author_name": "Lu Wang", + "author_inst": "Flow Pharma, Inc" + }, + { + "author_name": "Serban Ciotlos", + "author_inst": "Flow Pharma, Inc" + }, + { + "author_name": "Peter Lloyd", + "author_inst": "Flow Pharma, Inc" + }, + { + "author_name": "Reid Martin Rubsamen", + "author_inst": "Flow Pharma, Inc & Massachusetts General Hospital" } ], "version": "1", "license": "cc_no", "type": "new results", - "category": "molecular biology" + "category": "immunology" }, { "rel_doi": "10.1101/2020.02.24.963348", @@ -1631989,41 +1632918,37 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.02.24.20026773", - "rel_title": "Characterizing the transmission and identifying the control strategy for COVID-19 through epidemiological modeling", + "rel_doi": "10.1101/2020.02.21.20026468", + "rel_title": "Trends in Transmissibility of 2019 Novel Coronavirus-infected Pneumonia in Wuhan and 29 Provinces in China", "rel_date": "2020-02-25", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.24.20026773", - "rel_abs": "The outbreak of the novel coronavirus disease, COVID-19, originating from Wuhan, China in early December, has infected more than 70,000 people in China and other countries and has caused more than 2,000 deaths. As the disease continues to spread, the biomedical society urgently began identifying effective approaches to prevent further outbreaks. Through rigorous epidemiological analysis, we characterized the fast transmission of COVID-19 with a basic reproductive number 5.6 and proved a sole zoonotic source to originate in Wuhan. No changes in transmission have been noted across generations. By evaluating different control strategies through predictive modeling and Monte carlo simulations, a comprehensive quarantine in hospitals and quarantine stations has been found to be the most effective approach. Government action to immediately enforce this quarantine is highly recommended.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.21.20026468", + "rel_abs": "BackgroundThe 2019 coronavirus disease (COVID-19) represents a significant public health threat globally. Here we describe efforts to compare epidemic growth, size and peaking time for countries in Asia, Europe, North America, South America and Australia in the early epidemic phase.\n\nMethodsUsing the time series of cases reported from January 20, 2020 to February 13, 2020 and transportation data from December 1, 2019 to January 23, 2020 we have built a novel time-varying growth model to predict the epidemic trend in China. We extended our method, using cases reported from January 26, 2020 - or the date of the earliest case reported, to April 9, 2020 to predict future epidemic trend and size in 41 countries. We estimated the impact of control measures on the epidemic trend.\n\nResultsOur time-varying growth model yielded high concordance in the predicted epidemic size and trend with the observed figures in C hina. Among the other 41 countries, the peak time has been observed in 28 countries before or around April 9, 2020; the peak date and epidemic size were highly consistent with our estimates. We predicted the remaining countries would peak in April or May 2020, except India in July and Pakistan in August. The epidemic trajectory would reach the plateau in May or June for the majority of countries in the current wave. Countries that could emerge to be new epidemic centers are India, Pakistan, Brazil, Mexico, and Russia with a prediction of 105 cases for these countries. The effective reproduction number Rt displayed a downward trend with time across countries, revealing the impact of the intervention remeasures i.e. social distancing. Rt remained the highest in the UK (median 2.62) and the US (median 2.19) in the fourth week after the epidemic onset.\n\nConclusionsNew epidemic centers are expected to continue to emerge across the whole world. Greater challenges such as those in the healthcare system would be faced by developing countries in hotspots. A domestic approach to curb the pandemic must align with joint international efforts to effectively control the spread of COVID-19. Our model promotes a reliable transmissibility characterization and epidemic forecasting using the incidence of cases in the early epidemic phase.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Ke K. Zhang", - "author_inst": "TEXAS A&M UNIVERSITY HEALTH SCIENCE CTR" - }, - { - "author_name": "Linglin Xie", - "author_inst": "Texas A&M University" + "author_name": "Huazhen Lin", + "author_inst": "Southwestern University of Finance and Economics" }, { - "author_name": "Lauren Lawless", - "author_inst": "Texas A&M University" + "author_name": "Wei Liu", + "author_inst": "Southwestern University of Finance and Economics" }, { - "author_name": "Huijuan Zhou", - "author_inst": "Texas A&M University" + "author_name": "Hong Gao", + "author_inst": "Southwestern University of Finance and Economics" }, { - "author_name": "Guannan Gao", - "author_inst": "Texas A&M University" + "author_name": "Jinyu Nie", + "author_inst": "Southwestern University of Finance and Economics" }, { - "author_name": "Chengbin Xue", - "author_inst": "Huazhong University of Science and Technology" + "author_name": "Qiao Fan", + "author_inst": "Duke-NUS Medical School" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1633747,77 +1634672,37 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.02.18.20024281", - "rel_title": "Phase adjusted estimation of the number of 2019 novel coronavirus cases in Wuhan, China", + "rel_doi": "10.1101/2020.02.19.20025148", + "rel_title": "Trends and prediction in daily incidence of novel coronavirus infection in China, Hubei Province and Wuhan City: an application of Farr law", "rel_date": "2020-02-23", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.18.20024281", - "rel_abs": "An outbreak of clusters of viral pneumonia due to a novel coronavirus (2019-nCoV / SARS-CoV-2) happened in Wuhan, Hubei Province in China in December 2019. Since the outbreak, several groups reported estimated R0 of Coronavirus Disease 2019 (COVID-19) and generated valuable prediction for the early phase of this outbreak. After implementation of strict prevention and control measures in China, new estimation is needed. An infectious disease dynamics SEIR (Susceptible, Exposed, Infectious and Removed) model was applied to estimate the epidemic trend in Wuhan, China under two assumptions of Rt. In the first assumption, Rt was assumed to maintain over 1. The estimated number of infections would continue to increase throughout February without any indication of dropping with Rt = 1.9, 2.6 or 3.1. The number of infections would reach 11,044, 70,258 and 227,989, respectively, by 29 February 2020. In the second assumption, Rt was assumed to gradually decrease at different phases from high level of transmission (Rt = 3.1, 2.6 and 1.9) to below 1 (Rt = 0.9 or 0.5) owing to increasingly implemented public heath intervention. Several phases were divided by the dates when various levels of prevention and control measures were taken in effect in Wuhan. The estimated number of infections would reach the peak in late February, which is 58,077-84,520 or 55,869-81,393. Whether or not the peak of the number of infections would occur in February 2020 may be an important index for evaluating the sufficiency of the current measures taken in China. Regardless of the occurrence of the peak, the currently strict measures in Wuhan should be continuously implemented and necessary strict public health measures should be applied in other locations in China with high number of COVID-19 cases, in order to reduce Rt to an ideal level and control the infection.", - "rel_num_authors": 15, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.19.20025148", + "rel_abs": "BackgroundThe recent outbreak of novel coronavirus (2019-nCoV) has infected tens of thousands of patients in China. Studies have forecasted future trends of the incidence of 2019-nCoV infection, but appeared unsuccessful. Farrs law is a classic epidemiology theory/practice for predicting epidemics. Therefore, we used and validated a model based on Farrs law to predict the daily-incidence of 2019-nCoV infection in China and 2 regions of high-incidence.\n\nMethodsWe extracted the 2019-nCoV incidence data of China, Hubei Province and Wuhan City from websites of the Chinese and Hubei health commissions. A model based on Farrs law was developed using the data available on Feb. 8, 2020, and used to predict daily-incidence of 2019-nCoV infection in China, Hubei Province and Wuhan City afterward.\n\nResultsWe observed 50,995 (37001 on or before Feb. 8) incident cases in China from January 16 to February 15, 2020. The daily-incidence has peaked in China, Hubei Providence and Wuhan City, but with different downward slopes. If no major changes occur, our model shows that the daily-incidence of 2019-nCoV will drop to single-digit by February 25 for China and Hubei Province, but by March 8 for Wuhan city. However, predicted 75% confidence intervals of daily-incidence in all 3 regions of interest had an upward trend. The predicted trends overall match the prospectively-collected data, confirming usefulness of these models.\n\nConclusionsThis study shows the daily-incidence of 2019-nCoV in China, Hubei Province and Wuhan City has reached the peak and was decreasing. However, there is a possibility of upward trend.", + "rel_num_authors": 5, "rel_authors": [ { - "author_name": "Huwen Wang", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" - }, - { - "author_name": "Zezhou Wang", - "author_inst": "Department of Cancer Prevention, Shanghai Cancer Center, Fudan University; Department of oncology, Shanghai Medical College, Fudan University, Shanghai 200025, " - }, - { - "author_name": "Yinqiao Dong", - "author_inst": "Department of Environmental and Occupational Health, School of Public Health, China Medical University, Shenyang 110122, China" - }, - { - "author_name": "Ruijie Chang", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" - }, - { - "author_name": "Chen Xu", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" - }, - { - "author_name": "Xiaoyue Yu", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" - }, - { - "author_name": "Shuxian Zhang", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" - }, - { - "author_name": "Lhakpa Tsamlag", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" - }, - { - "author_name": "Meili Shang", - "author_inst": "Sanlin Community Health Service Center, Shanghai 200124, China" - }, - { - "author_name": "Jinyan Huang", - "author_inst": "State Key Laboratory of Medical Genomics, Shanghai Institute of Hematology, National Research Center for Translational Medicine (Shanghai), Rui-Jin Hospital, Sh" - }, - { - "author_name": "Ying Wang", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" + "author_name": "Jie Xu", + "author_inst": "Department of Infectious Disease, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China" }, { - "author_name": "Gang Xu", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" + "author_name": "Yajiao Cheng", + "author_inst": "Department of Infectious Disease, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China" }, { - "author_name": "Tian Shen", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" + "author_name": "Xiaoling Yuan", + "author_inst": "Department of Infectious Disease, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China" }, { - "author_name": "Xinxin Zhang", - "author_inst": "Research Laboratory of Clinical Virology, National Research Center for Translational Medicine (Shanghai)c, Rui-Jin Hospital, and Rui-Jin Hospital North, Shangha" + "author_name": "Wei V. Li", + "author_inst": "Department of Biostatistics and Epidemiology Rutgers School of Public Health, Piscataway, NJ, USA" }, { - "author_name": "Yong Cai", - "author_inst": "School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China" + "author_name": "Lanjing Zhang", + "author_inst": "Princeton Medical Center/Rutgers University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1635316,31 +1636201,55 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.02.19.950253", - "rel_title": "Pangolin homology associated with 2019-nCoV", + "rel_doi": "10.1101/2020.02.16.951723", + "rel_title": "SARS-CoV-2 and SARS-CoV Spike-RBD Structure and Receptor Binding Comparison and Potential Implications on Neutralizing Antibody and Vaccine Development", "rel_date": "2020-02-20", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.19.950253", - "rel_abs": "To explore potential intermediate host of a novel coronavirus is vital to rapidly control continuous COVID-19 spread. We found genomic and evolutionary evidences of the occurrence of 2019-nCoV-like coronavirus (named as Pangolin-CoV) from dead Malayan Pangolins. Pangolin-CoV is 91.02% and 90.55% identical at the whole genome level to 2019-nCoV and BatCoV RaTG13, respectively. Pangolin-CoV is the lowest common ancestor of 2019-nCoV and RaTG13. The S1 protein of Pangolin-CoV is much more closely related to 2019-nCoV than RaTG13. Five key amino-acid residues involved in the interaction with human ACE2 are completely consistent between Pangolin-CoV and 2019-nCoV but four amino-acid mutations occur in RaTG13. It indicates Pangolin-CoV has similar pathogenic potential to 2019-nCoV, and would be helpful to trace the origin and probable intermediate host of 2019-nCoV.", - "rel_num_authors": 3, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.16.951723", + "rel_abs": "SARS-CoV-2 and SARS-CoV share a common human receptor ACE2. Protein-protein interaction structure modeling indicates that spike-RBD of the two viruses also has similar overall binding conformation and binding free energy to ACE2. In vitro assays using recombinant ACE2 proteins and ACE2 expressing cells confirmed the two coronaviruses similar binding affinities to ACE2. The above studies provide experimental supporting evidences and possible explanation for the high transmissibility observed in the SARS-CoV-2 outbreak. Potent ACE2-blocking SARS-CoV neutralizing antibodies showed limited cross-binding and neutralizing activities to SARS-CoV-2. ACE2-non-blocking SARS-CoV RBD antibodies, though with weaker neutralizing activities against SARS-CoV, showed positive cross-neutralizing activities to SARS-CoV-2 with an unknown mechanism. These findings suggest a trade-off between the efficacy and spectrum for therapeutic antibodies to different coronaviruses, and hence highlight the possibilities and challenges in developing broadly protecting antibodies and vaccines against SARS-CoV-2 and its future mutants.", + "rel_num_authors": 9, "rel_authors": [ { - "author_name": "Zhigang Zhang", - "author_inst": "Yunnan University" + "author_name": "Liangzhi Xie", + "author_inst": "Sinocelltech Group Ltd." }, { - "author_name": "Qunfu Wu", - "author_inst": "Yunnan University" + "author_name": "Chunyun Sun", + "author_inst": "Sinocelltech Group Ltd." }, { - "author_name": "Tao Zhang", - "author_inst": "Yunnan University" + "author_name": "Chunxia Luo", + "author_inst": "Sinocelltech Group Ltd." + }, + { + "author_name": "Yanjing Zhang", + "author_inst": "Sinocelltech Group Ltd." + }, + { + "author_name": "Jie Zhang", + "author_inst": "Sino Biological Inc." + }, + { + "author_name": "Jiahui Yang", + "author_inst": "Sino Biological Inc." + }, + { + "author_name": "Long Chen", + "author_inst": "Sinocelltech Group Ltd." + }, + { + "author_name": "Ji Yang", + "author_inst": "Sinocelltech Group Ltd." + }, + { + "author_name": "Jing Li", + "author_inst": "Sinocelltech Group Ltd." } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "pathology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.02.17.952879", @@ -1636754,35 +1637663,51 @@ "category": "evolutionary biology" }, { - "rel_doi": "10.1101/2020.02.10.942185", - "rel_title": "Structural modeling of 2019-novel coronavirus (nCoV) spike protein reveals a proteolytically-sensitive activation loop as a distinguishing feature compared to SARS-CoV and related SARS-like coronaviruses", + "rel_doi": "10.1101/2020.02.13.20022715", + "rel_title": "Analysis of meteorological conditions and prediction of epidemic trend of 2019-nCoV infection in 2020", "rel_date": "2020-02-18", - "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.02.10.942185", - "rel_abs": "The 2019 novel coronavirus (2019-nCoV) is currently causing a widespread outbreak centered on Hubei province, China and is a major public health concern. Taxonomically 2019-nCoV is closely related to SARS-CoV and SARS-related bat coronaviruses, and it appears to share a common receptor with SARS-CoV (ACE-2). Here, we perform structural modeling of the 2019-nCoV spike glycoprotein. Our data provide support for the similar receptor utilization between 2019-nCoV and SARS-CoV, despite a relatively low amino acid similarity in the receptor binding module. Compared to SARS-CoV, we identify an extended structural loop containing basic amino acids at the interface of the receptor binding (S1) and fusion (S2) domains, which we predict to be proteolytically-sensitive. We suggest this loop confers fusion activation and entry properties more in line with MERS-CoV and other coronaviruses, and that the presence of this structural loop in 2019-nCoV may affect virus stability and transmission.", - "rel_num_authors": 4, + "rel_site": "medRxiv", + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.13.20022715", + "rel_abs": "ObjectiveTo investigate the meteorological condition for incidence and spread of 2019-nCoV infection, to predict the epidemiology of the infectious disease, and to provide a scientific basis for prevention and control measures against the new disease.\n\nMethodsThe meteorological factors during the outbreak period of the novel coronavirus pneumonia in Wuhan in 2019 were collected and analyzed, and were confirmed with those of Severe Acute Respiratory Syndrome (SARS) in China in 2003. Data of patients infected with 2019-nCoV and SARS coronavirus were collected from WHO website and other public sources.\n\nResultsThis study found that the suitable temperature range for 2019-nCoV survival is (13-24 {degrees}C), among which 19{degrees}C lasting about 60 days is conducive to the spread between the vector and humans; the humidity range is 50%-80%, of which about 75% humidity is conducive to the survival of the coronavirus; the suitable precipitation range is below 30 mm/month. Cold air and continuous low temperature over one week are helpful for the elimination of the virus. The prediction results show that with the approach of spring, the temperature in north China gradually rises, and the coronavirus spreads to middle and high latitudes along the temperature line of 13-19 {degrees}C. The population of new coronavirus infections is concentrated in Beijing, Tianjin, Hebei, Jiangsu, Zhejiang, Shanghai and other urban agglomerations. Starting from May 2020, the Beijing-Tianjin-Hebei urban agglomeration, the Central China Zhengzhou-Wuhan urban agglomeration, the eastern Jiangsu-Zhejiang-Shanghai urban agglomeration, and the southern Pearl River Delta urban agglomeration are all under a high temperature above 24 {degrees}C, which is not conducive to the survival and reproduction of coronaviruses, so the epidemic is expected to end.\n\nConclusionsA wide range of continuous warm and dry weather is conducive to the survival of 2019-nCoV. The coming of spring, in addition to the original Wuhan-Zhengzhou urban agglomeration in central China, means that the prevention and control measures in big cities located in mid-latitude should be strengthened, especially the monitoring of transportation hubs. The Pearl River Delta urban agglomeration is a concentrated area of population in south China, with a faster temperature rise than those in mid-high latitudes, and thus the prevention in this area should be prioritized. From a global perspective, cities with a mean temperature below 24 {degrees}C are all high-risk cities for 2019-nCoV transmission before June.", + "rel_num_authors": 8, "rel_authors": [ { - "author_name": "Javier A. Jaimes", - "author_inst": "Cornell University" + "author_name": "Jin Bu", + "author_inst": "Hospital for Skin Diseases (Institute of Dermatology), Chinese Academy of Medical Sciences and Pekin Union Medical College" }, { - "author_name": "Nicole M Andre", - "author_inst": "Cornell University" + "author_name": "Dong-Dong Peng", + "author_inst": "Institute of Tropical and Marine Meteorology, China Meteorological Administration" }, { - "author_name": "Jean K Millet", - "author_inst": "INRAE" + "author_name": "Hui Xiao", + "author_inst": "Institute of Tropical and Marine Meteorology, China Meteorological Administration" }, { - "author_name": "Gary R. Whittaker", - "author_inst": "Cornell University" + "author_name": "Qian Yue", + "author_inst": "Institute of Tropical and Marine Meteorology, China Meteorological Administration" + }, + { + "author_name": "Yan Han", + "author_inst": "Hospital for Skin Diseases (Institute of Dermatology), Chinese Academy of Medical Sciences and Peking Union Medical College" + }, + { + "author_name": "Yu Lin", + "author_inst": "Shenzhen Withsum Technology Limited" + }, + { + "author_name": "Gang Hu", + "author_inst": "School of Agriculture, Sun Yat-sen University" + }, + { + "author_name": "Jing Chen", + "author_inst": "Institute of Tropical and Marine Meteorology, China Meteorological Administration" } ], "version": "1", "license": "cc_no", - "type": "new results", - "category": "microbiology" + "type": "PUBLISHAHEADOFPRINT", + "category": "infectious diseases" }, { "rel_doi": "10.1101/2020.02.12.20022400", @@ -1638024,51 +1638949,35 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.02.12.20021386", - "rel_title": "Long-Term Persistence of IgG Antibodies in SARS-CoV Infected Healthcare Workers", + "rel_doi": "10.1101/2020.02.12.20022566", + "rel_title": "A spatial model of CoVID-19 transmission in England and Wales: early spread and peak timing", "rel_date": "2020-02-14", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.12.20021386", - "rel_abs": "BACKGROUNDThe ongoing worldwide outbreak of the 2019-nCoV is markedly similar to the severe acute respiratory syndrome (SARS) outbreak 17 years ago. During the 2002-2003 SARS outbreak, healthcare workers formed a special population of patients. Although virus-specific IgG play important roles in virus neutralization and prevention against future infection, limited information is available regarding the long term persistence of IgG after infection with SARS-like coronavirus.\n\nMETHODSA long-term prospective cohort study followed 34 SARS-CoV-infected healthcare workers from a hospital with clustered infected cases during the 2002-2003 SARS outbreak in Guangzhou, China, with a 13-year follow-up. Serum samples were collected annually from 2003-2015. Twenty SARS-CoV-infected and 40 non-infected healthcare workers were enrolled in 2015, and their serum samples were collected. All sera were tested for IgG antibodies with ELISA using whole virus and a recombinant nucleocapsid protein of SARS-CoV, as a diagnostic antigen.\n\nRESULTSAnti SARS-CoV IgG was found to persist for up to 12 years. IgG titers typically peaked in 2004, declining rapidly from 2004-2006, and then continued to decline at a slower rate. IgG titers in SARS-CoV-infected healthcare workers remained at a significantly high level until 2015. Patients treated with corticosteroids at the time of infection were found to have lower IgG titers than those without.\n\nCONCLUSIONSIgG antibodies against SARS-CoV can persist for at least 12 years. The presence of SARS-CoV IgG might provide protection against SARS-CoV and other betacoronavirus. This study provides valuable information regarding humoral immune responses against SARS-CoV and the 2019-nCoV.", - "rel_num_authors": 8, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.12.20022566", + "rel_abs": "BackgroundAn outbreak of a novel coronavirus, named CoVID-19, was first reported in China on 31 December 2019. As of 9 February 2020, cases have been reported in 25 countries, including probable cases of human-to-human transmission in England.\n\nMethodsWe adapted an existing national-scale metapopulation model to capture the spread of CoVID-19 in England and Wales. We used 2011 census data to capture population sizes and population movement, together with parameter estimates from the current outbreak in China.\n\nResultsWe predict that a CoVID-19 outbreak will peak 126 to 147 days ([~]4 months) after the start of person-to-person transmission in England and Wales in the absence of controls, assuming biological parameters remain unchanged. Therefore, if person-to-person transmission persists from February, we predict the epidemic peak would occur in June. The starting location has minimal impact on peak timing, and model stochasticity varies peak timing by 10 days. Incorporating realistic parameter uncertainty leads to estimates of peak time ranging from 78 days to 241 days after person-to-person transmission has been established. Seasonal changes in transmission rate substantially impact the timing and size of the epidemic peak, as well as the total attack rate.\n\nDiscussionWe provide initial estimates of the potential course of CoVID-19 in England and Wales in the absence of control measures. These results can be refined with improved estimates of epidemiological parameters, and permit investigation of control measures and cost effectiveness analyses. Seasonal changes in transmission rate could shift the timing of the peak into winter months, which will have important implications for health-care capacity planning.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Xiaoqin Guo", - "author_inst": "Sun Yat-sen University" - }, - { - "author_name": "Zhongmin Guo", - "author_inst": "Sun Yat-sen University" - }, - { - "author_name": "Chaohui Duan", - "author_inst": "Sun Yat-sen University" - }, - { - "author_name": "Zeliang chen", - "author_inst": "Sun Yat-Sen University - North Campus Library" - }, - { - "author_name": "Guoling Wang", - "author_inst": "Sun Yat-sen University" + "author_name": "Leon Danon", + "author_inst": "University of Exeter" }, { - "author_name": "Yi Lu", - "author_inst": "Boston University" + "author_name": "Ellen Brooks-Pollock", + "author_inst": "University of Bristol" }, { - "author_name": "Mengfeng Li", - "author_inst": "Sun Yat-sen University" + "author_name": "Mick Bailey", + "author_inst": "University of Bristol" }, { - "author_name": "Jiahai Lu", - "author_inst": "Sun Yat-sen University" + "author_name": "Matt J Keeling", + "author_inst": "University of Warwick" } ], "version": "1", - "license": "cc_by_nd", + "license": "cc_by_nc_nd", "type": "PUBLISHAHEADOFPRINT", - "category": "infectious diseases" + "category": "epidemiology" }, { "rel_doi": "10.1101/2020.02.05.936013", @@ -1639442,29 +1640351,41 @@ "category": "infectious diseases" }, { - "rel_doi": "10.1101/2020.02.07.20021196", - "rel_title": "Tracking the spread of novel coronavirus (2019-nCoV) based on big data", + "rel_doi": "10.1101/2020.02.07.20021154", + "rel_title": "The Novel Coronavirus, 2019-nCoV, is Highly Contagious and More Infectious Than Initially Estimated", "rel_date": "2020-02-11", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.07.20021196", - "rel_abs": "The novel coronavirus (2019-nCoV) appeared in Wuhan in late 2019 have infected 34,598 people, and killed 723 among them until 8th February 2020. The new virus has spread to at least 316 cities (until 1st February 2020) in China. We used the traffic flow data from Baidu Map, and number of air passengers who left Wuhan from 1st January to 26th January, to quantify the potential infectious people. We developed multiple linear models with local population and air passengers as predicted variables to explain the variance of confirmed cases in every city across China. We found the contribution of air passengers from Wuhan was decreasing gradually, but the effect of local population was increasing, indicating the trend of local transmission. However, the increase of local transmission is slow during the early stage of novel coronavirus, due to the super strict control measures carried out by government agents and communities.", - "rel_num_authors": 3, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.07.20021154", + "rel_abs": "The novel coronavirus (2019-nCoV) is a recently emerged human pathogen that has spread widely since January 2020. Initially, the basic reproductive number, R0, was estimated to be 2.2 to 2.7. Here we provide a new estimate of this quantity. We collected extensive individual case reports and estimated key epidemiology parameters, including the incubation period. Integrating these estimates and high-resolution real-time human travel and infection data with mathematical models, we estimated that the number of infected individuals during early epidemic double every 2.4 days, and the R0 value is likely to be between 4.7 and 6.6. We further show that quarantine and contact tracing of symptomatic individuals alone may not be effective and early, strong control measures are needed to stop transmission of the virus.\n\nOne-sentence summaryBy collecting and analyzing spatiotemporal data, we estimated the transmission potential for 2019-nCoV.", + "rel_num_authors": 6, "rel_authors": [ { - "author_name": "Xumao Zhao", - "author_inst": "Lanzhou University" + "author_name": "Steven Sanche", + "author_inst": "Los Alamos National Laboratory" }, { - "author_name": "Xiang Liu", - "author_inst": "Lanzhou University" + "author_name": "Yen Ting Lin", + "author_inst": "Los Alamos National Laboratory" }, { - "author_name": "Xinhai Li", - "author_inst": "Institute of Zoology, Chinese Academy of Sciences" + "author_name": "Chonggang Xu", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Ethan Romero-Severson", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Nick Hengartner", + "author_inst": "Los Alamos National Laboratory" + }, + { + "author_name": "Ruian Ke", + "author_inst": "Los Alamos National Laboratory" } ], "version": "1", - "license": "cc_by", + "license": "cc_no", "type": "PUBLISHAHEADOFPRINT", "category": "epidemiology" }, @@ -1641136,41 +1642057,33 @@ "category": "epidemiology" }, { - "rel_doi": "10.1101/2020.02.03.20020263", - "rel_title": "Network-based Drug Repurposing for Human Coronavirus", + "rel_doi": "10.1101/2020.02.04.20020438", + "rel_title": "The impact of traffic isolation in Wuhan on the spread of 2019-nCov", "rel_date": "2020-02-05", "rel_site": "medRxiv", - "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.03.20020263", - "rel_abs": "Human Coronaviruses (HCoVs), including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle east respiratory syndrome coronavirus (MERS-CoV), and 2019 novel coronavirus (2019-nCoV), lead global epidemics with high morbidity and mortality. However, there are currently no effective drugs targeting 2019-nCoV. Drug repurposing, represented as an effective drug discovery strategy from existing drugs, could shorten the time and reduce the cost compared to de novo drug discovery. In this study, we present an integrative, antiviral drug repurposing methodology implementing a systems pharmacology-based network medicine platform, quantifying the interplay between the HCoV-host interactome and drug targets in the human protein-protein interaction network. Phylogenetic analyses of 15 HCoV whole genomes reveal that 2019-nCoV has the highest nucleotide sequence identity with SARS-CoV (79.7%) among the six other known pathogenic HCoVs. Specifically, the envelope and nucleocapsid proteins of 2019-nCoV are two evolutionarily conserved regions, having the sequence identities of 96% and 89.6%, respectively, compared to SARS-CoV. Using network proximity analyses of drug targets and known HCoV-host interactions in the human protein-protein interactome, we computationally identified 135 putative repurposable drugs for the potential prevention and treatment of HCoVs. In addition, we prioritized 16 potential anti-HCoV repurposable drugs (including melatonin, mercaptopurine, and sirolimus) that were further validated by enrichment analyses of drug-gene signatures and HCoV-induced transcriptomics data in human cell lines. Finally, we showcased three potential drug combinations (including sirolimus plus dactinomycin, mercaptopurine plus melatonin, and toremifene plus emodin) captured by the Complementary Exposure pattern: the targets of the drugs both hit the HCoV-host subnetwork, but target separate neighborhoods in the human protein-protein interactome network. In summary, this study offers powerful network-based methodologies for rapid identification of candidate repurposable drugs and potential drug combinations toward future clinical trials for HCoVs.", - "rel_num_authors": 6, + "rel_link": "https://medrxiv.org/cgi/content/short/2020.02.04.20020438", + "rel_abs": "The 2019-nCoV outbreak occurred near the Chinese Spring Festival transport period in Wuhan. As an important transportation center, the migration of Wuhan accelerated the spread of 2019-nCoV across mainland China. Based on the cumulative Baidu migration index (CBMI), we first analyzed the proportion of Wuhans migrant population to other cities. Our results confirm that there is a significant correlation between the export population of Wuhan and reported cases in various regions. We subsequently found that the mortality rate in Hubei Province was much higher than that in other regions of mainland China, while the investigation of potential cases in Wuhan was far behind other provinces in Mainland China, which indicates the effectiveness of early isolation.", + "rel_num_authors": 4, "rel_authors": [ { - "author_name": "Yadi Zhou", - "author_inst": "Cleveland Clinic" - }, - { - "author_name": "Yuan Hou", - "author_inst": "Cleveland Clinic" - }, - { - "author_name": "Jiayu Shen", - "author_inst": "Cleveland Clinic" + "author_name": "Gehui Jin", + "author_inst": "Ningbo University" }, { - "author_name": "Yin Huang", - "author_inst": "Cleveland Clinic" + "author_name": "Jiayu Yu", + "author_inst": "Ningbo University" }, { - "author_name": "William Martin", - "author_inst": "Cleveland Clinic" + "author_name": "Liyuan Han", + "author_inst": "Ningbo University" }, { - "author_name": "Feixiong Cheng", - "author_inst": "Cleveland Clinic" + "author_name": "Shiwei Duan", + "author_inst": "Ningbo University" } ], "version": "1", - "license": "cc_by_nc", + "license": "cc_by", "type": "PUBLISHAHEADOFPRINT", "category": "infectious diseases" }, @@ -1642446,43 +1643359,67 @@ "category": "genetics" }, { - "rel_doi": "10.1101/2020.01.30.926881", - "rel_title": "Engineered unnatural ubiquitin for optimal detection of deubiquitinating enzymes", + "rel_doi": "10.1101/2020.01.30.927806", + "rel_title": "The digestive system is a potential route of 2019-nCov infection: a bioinformatics analysis based on single-cell transcriptomes", "rel_date": "2020-01-31", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.30.926881", - "rel_abs": "Deubiquitinating enzymes (DUBs) are responsible for removing ubiquitin (Ub) from its protein conjugates. DUBs have been implicated as attractive therapeutic targets in the treatment of viral diseases, neurodegenerative disorders and cancer. The lack of selective chemical tools for the exploration of these enzymes significantly impairs the determination of their roles in both normal and pathological states. Commercially available fluorogenic substrates are based on the C-terminal Ub motif or contain Ub coupled to a fluorophore (Z-LRGG-AMC, Ub-AMC); therefore, these substrates suffer from lack of selectivity. By using a hybrid combinatorial substrate library (HyCoSuL) and a defined P2 library containing a wide variety of nonproteinogenic amino acids, we established a full substrate specificity profile for two DUBs--MERS PLpro and human UCH-L3. Based on these results, we designed and synthesized Ub-based substrates and activity-based probes (ABPs) containing selected unnatural amino acids located in the C-terminal Ub motif. Biochemical analysis and cell-based experiments confirmed the activity and selectivity of engineered Ub-based substrates and probes. Using this approach, we propose that for any protease that recognizes Ub and Ub-like substrates, a highly active and selective unnatural substrate or probe can be engineered.", - "rel_num_authors": 6, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.30.927806", + "rel_abs": "Since December 2019, a newly identified coronavirus (2019 novel coronavirus, 2019-nCov) is causing outbreak of pneumonia in one of largest cities, Wuhan, in Hubei province of China and has draw significant public health attention. The same as severe acute respiratory syndrome coronavirus (SARS-CoV), 2019-nCov enters into host cells via cell receptor angiotensin converting enzyme II (ACE2). In order to dissect the ACE2-expressing cell composition and proportion and explore a potential route of the 2019-nCov infection in digestive system infection, 4 datasets with single-cell transcriptomes of lung, esophagus, gastric, ileum and colon were analyzed. The data showed that ACE2 was not only highly expressed in the lung AT2 cells, esophagus upper and stratified epithelial cells but also in absorptive enterocytes from ileum and colon. These results indicated along with respiratory systems, digestive system is a potential routes for 2019-nCov infection. In conclusion, this study has provided the bioinformatics evidence of the potential route for infection of 2019-nCov in digestive system along with respiratory tract and may have significant impact for our healthy policy setting regards to prevention of 2019-nCoV infection.", + "rel_num_authors": 12, "rel_authors": [ { - "author_name": "Wioletta Rut", - "author_inst": "Department of Chemical Biology and Bioimaging, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland" + "author_name": "Hao Zhang", + "author_inst": "Department of Rheumatology and Immunology, Changzheng Hospital, Second Military Medical University" }, { - "author_name": "Mikolaj Zmudzinski", - "author_inst": "Department of Chemical Biology and Bioimaging, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland" + "author_name": "Zijian Kang", + "author_inst": "Department of Rheumatology and Immunology, Changzheng Hospital, Second Military Medical University" }, { - "author_name": "Scott J. Snipas", - "author_inst": "Sanford Burnham Prebys Medical Discovery Institute, 10901 North Torrey Pines Road, La Jolla, CA 92037, USA" + "author_name": "Haiyi Gong", + "author_inst": "Department of Orthopaedic Oncology, Changzheng Hospital, Second Military Medical University" }, { - "author_name": "Miklos Bekes", - "author_inst": "Department of Biochemistry & Molecular Pharmacology, New York University School of Medicine, New York, NY 10016, USA" + "author_name": "Da Xu", + "author_inst": "Depanrtment of Urology, The Third Affiliated Hospital of Second Military Medical University" }, { - "author_name": "Tony T. Huang", - "author_inst": "Department of Biochemistry & Molecular Pharmacology, New York University School of Medicine, New York, NY 10016, USA" + "author_name": "Jing Wang", + "author_inst": "Department of Neurosurgery, Changhai Hospital, Second Military Medical University," }, { - "author_name": "Marcin Drag", - "author_inst": "Department of Chemical Biology and Bioimaging, Wroclaw University of Science and Technology, Wyb. Wyspianskiego 27, 50-370 Wroclaw, Poland" + "author_name": "Zifu Li", + "author_inst": "Department of Neurosurgery, Changhai Hospital, Second Military Medical University," + }, + { + "author_name": "Xingang Cui", + "author_inst": "Depanrtment of Urology, The Third Affiliated Hospital of Second Military Medical University" + }, + { + "author_name": "Jianru Xiao", + "author_inst": "Department of Orthopaedic Oncology, Changzheng Hospital, Second Military Medical University" + }, + { + "author_name": "Tong Meng", + "author_inst": "Tongji Hospital, Tongji University School of Medicine, Tongji University" + }, + { + "author_name": "Wang Zhou", + "author_inst": "Peking-Tsinghua Center for Life Sciences, TsinghuaUniversity" + }, + { + "author_name": "Jianmin Liu", + "author_inst": "Department of Neurosurgery, Changhai Hospital, Second Military Medical University" + }, + { + "author_name": "Huji Xu", + "author_inst": "Department of Rheumatology and Immunology, Changzheng Hospital, Second Military Medical University" } ], "version": "1", - "license": "cc_no", + "license": "cc_by_nc_nd", "type": "new results", - "category": "biochemistry" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.01.31.929042", @@ -1643663,55 +1644600,135 @@ "category": "microbiology" }, { - "rel_doi": "10.1101/2020.01.21.914044", - "rel_title": "Host and infectivity prediction of Wuhan 2019 novel coronavirus using deep learning algorithm", - "rel_date": "2020-01-24", + "rel_doi": "10.1101/2020.01.22.914952", + "rel_title": "Discovery of a novel coronavirus associated with the recent pneumonia outbreak in humans and its potential bat origin", + "rel_date": "2020-01-23", "rel_site": "bioRxiv", - "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.21.914044", - "rel_abs": "The recent outbreak of pneumonia in Wuhan, China caused by the 2019 Novel Coronavirus (2019-nCoV) emphasizes the importance of detecting novel viruses and predicting their risks of infecting people. In this report, we introduced the VHP (Virus Host Prediction) to predict the potential hosts of viruses using deep learning algorithm. Our prediction suggests that 2019-nCoV has close infectivity with other human coronaviruses, especially the severe acute respiratory syndrome coronavirus (SARS-CoV), Bat SARS-like Coronaviruses and the Middle East respiratory syndrome coronavirus (MERS-CoV). Based on our prediction, compared to the Coronaviruses infecting other vertebrates, bat coronaviruses are assigned with more similar infectivity patterns with 2019-nCoVs. Furthermore, by comparing the infectivity patterns of all viruses hosted on vertebrates, we found mink viruses show a closer infectivity pattern to 2019-nCov. These consequences of infectivity pattern analysis illustrate that bat and mink may be two candidate reservoirs of 2019-nCov.These results warn us to beware of 2019-nCoV and guide us to further explore the properties and reservoir of it.\n\nOne Sentence SummaryIt is of great value to identify whether a newly discovered virus has the risk of infecting human. Guo et al. proposed a virus host prediction method based on deep learning to detect what kind of host a virus can infect with DNA sequence as input. Applied to the Wuhan 2019 Novel Coronavirus, our prediction demonstrated that several vertebrate-infectious coronaviruses have strong potential to infect human. This method will be helpful in future viral analysis and early prevention and control of viral pathogens.", - "rel_num_authors": 9, + "rel_link": "https://biorxiv.org/cgi/content/short/2020.01.22.914952", + "rel_abs": "Since the SARS outbreak 18 years ago, a large number of severe acute respiratory syndrome related coronaviruses (SARSr-CoV) have been discovered in their natural reservoir host, bats1-4. Previous studies indicated that some of those bat SARSr-CoVs have the potential to infect humans5-7. Here we report the identification and characterization of a novel coronavirus (nCoV-2019) which caused an epidemic of acute respiratory syndrome in humans, in Wuhan, China. The epidemic, started from December 12th, 2019, has caused 198 laboratory confirmed infections with three fatal cases by January 20th, 2020. Full-length genome sequences were obtained from five patients at the early stage of the outbreak. They are almost identical to each other and share 79.5% sequence identify to SARS-CoV. Furthermore, it was found that nCoV-2019 is 96% identical at the whole genome level to a bat coronavirus. The pairwise protein sequence analysis of seven conserved non-structural proteins show that this virus belongs to the species of SARSr-CoV. The nCoV-2019 virus was then isolated from the bronchoalveolar lavage fluid of a critically ill patient, which can be neutralized by sera from several patients. Importantly, we have confirmed that this novel CoV uses the same cell entry receptor, ACE2, as SARS-CoV.", + "rel_num_authors": 29, "rel_authors": [ { - "author_name": "Qian Guo", - "author_inst": "State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering, and Center for Quantitative Biology, and " + "author_name": "Peng Zhou", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" }, { - "author_name": "Mo Li", - "author_inst": "State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering, and Center for Quantitative Biology, and " + "author_name": "Xing-Lou Yang", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" }, { - "author_name": "Chunhui Wang", - "author_inst": "State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering, and Center for Quantitative Biology, and " + "author_name": "Xian-Guang Wang", + "author_inst": "Wuhan Jinyintan Hospital" }, { - "author_name": "Zhengcheng Fang", - "author_inst": "State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering, and Center for Quantitative Biology, and " + "author_name": "Ben Hu", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" }, { - "author_name": "Peihong Wang", - "author_inst": "State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering, and Center for Quantitative Biology, and " + "author_name": "Lei Zhang", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" }, { - "author_name": "Jie Tan", - "author_inst": "State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering, and Center for Quantitative Biology, and " + "author_name": "Wei Zhang", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" }, { - "author_name": "Shufang Wu", - "author_inst": "State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering, and Center for Quantitative Biology, and " + "author_name": "Hao-Rui Si", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" }, { - "author_name": "Yonghong Xiao", - "author_inst": "State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, College of Medicine, Zhejiang University" + "author_name": "Yan Zhu", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" }, { - "author_name": "Huaiqiu Zhu", - "author_inst": "State Key Laboratory for Turbulence and Complex Systems, Department of Biomedical Engineering, College of Engineering, and Center for Quantitative Biology, Peki" + "author_name": "Bei Li", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Chao-Lin Huang", + "author_inst": "Wuhan Jinyintan Hospital" + }, + { + "author_name": "Hui-Dong Chen", + "author_inst": "Wuhan Jinyintan Hospital" + }, + { + "author_name": "Jing Chen", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Yun Luo", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Hua Guo", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Ren-Di Jiang", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Mei-Qin Liu", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Ying Chen", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Xu-Rui Shen", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Xi Wang", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Xiao-Shuang Zheng", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Kai Zhao", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Quan-Jiao Chen", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Fei Deng", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" + }, + { + "author_name": "Lin-Lin Liu", + "author_inst": "Hubei Provincial Center for Disease Control and Prevention" + }, + { + "author_name": "Bing Yan", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Fa-Xian Zhan", + "author_inst": "Hubei Provincial Center for Disease Control and Prevention" + }, + { + "author_name": "Yan-Yi Wang", + "author_inst": "CAS Key Laboratory of Special Pathogens, Wuhan Institute of Virology, Center for Biosafety Mega-Science, Chinese Academy of Sciences" + }, + { + "author_name": "Gengfu Xiao", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" + }, + { + "author_name": "Zheng-Li Shi", + "author_inst": "Wuhan Institute of Virology, Chinese Academy of Sciences" } ], "version": "1", - "license": "cc_by_nc_nd", + "license": "cc_no", "type": "new results", - "category": "systems biology" + "category": "microbiology" }, { "rel_doi": "10.1101/2020.01.21.914929",